Control system failure monitoring using generalized parity relations. M.S. Thesis Interim Technical Report

NASA Technical Reports Server (NTRS)

Vanschalkwyk, Christiaan Mauritz

1991-01-01

Many applications require that a control system must be tolerant to the failure of its components. This is especially true for large space-based systems that must work unattended and with long periods between maintenance. Fault tolerance can be obtained by detecting the failure of the control system component, determining which component has failed, and reconfiguring the system so that the failed component is isolated from the controller. Component failure detection experiments that were conducted on an experimental space structure, the NASA Langley Mini-Mast are presented. Two methodologies for failure detection and isolation (FDI) exist that do not require the specification of failure modes and are applicable to both actuators and sensors. These methods are known as the Failure Detection Filter and the method of Generalized Parity Relations. The latter method was applied to three different sensor types on the Mini-Mast. Failures were simulated in input-output data that were recorded during operation of the Mini-Mast. Both single and double sensor parity relations were tested and the effect of several design parameters on the performance of these relations is discussed. The detection of actuator failures is also treated. It is shown that in all the cases it is possible to identify the parity relations directly from input-output data. Frequency domain analysis is used to explain the behavior of the parity relations.

A preliminary design for flight testing the FINDS algorithm

NASA Technical Reports Server (NTRS)

Caglayan, A. K.; Godiwala, P. M.

1986-01-01

This report presents a preliminary design for flight testing the FINDS (Fault Inferring Nonlinear Detection System) algorithm on a target flight computer. The FINDS software was ported onto the target flight computer by reducing the code size by 65%. Several modifications were made to the computational algorithms resulting in a near real-time execution speed. Finally, a new failure detection strategy was developed resulting in a significant improvement in the detection time performance. In particular, low level MLS, IMU and IAS sensor failures are detected instantaneously with the new detection strategy, while accelerometer and the rate gyro failures are detected within the minimum time allowed by the information generated in the sensor residuals based on the point mass equations of motion. All of the results have been demonstrated by using five minutes of sensor flight data for the NASA ATOPS B-737 aircraft in a Microwave Landing System (MLS) environment.

Sensor Fault Detection and Diagnosis Simulation of a Helicopter Engine in an Intelligent Control Framework

NASA Technical Reports Server (NTRS)

Litt, Jonathan; Kurtkaya, Mehmet; Duyar, Ahmet

1994-01-01

This paper presents an application of a fault detection and diagnosis scheme for the sensor faults of a helicopter engine. The scheme utilizes a model-based approach with real time identification and hypothesis testing which can provide early detection, isolation, and diagnosis of failures. It is an integral part of a proposed intelligent control system with health monitoring capabilities. The intelligent control system will allow for accommodation of faults, reduce maintenance cost, and increase system availability. The scheme compares the measured outputs of the engine with the expected outputs of an engine whose sensor suite is functioning normally. If the differences between the real and expected outputs exceed threshold values, a fault is detected. The isolation of sensor failures is accomplished through a fault parameter isolation technique where parameters which model the faulty process are calculated on-line with a real-time multivariable parameter estimation algorithm. The fault parameters and their patterns can then be analyzed for diagnostic and accommodation purposes. The scheme is applied to the detection and diagnosis of sensor faults of a T700 turboshaft engine. Sensor failures are induced in a T700 nonlinear performance simulation and data obtained are used with the scheme to detect, isolate, and estimate the magnitude of the faults.

Oxygen sensor signal validation for the safety of the rebreather diver.

PubMed

Sieber, Arne; L'abbate, Antonio; Bedini, Remo

2009-03-01

In electronically controlled, closed-circuit rebreather diving systems, the partial pressure of oxygen inside the breathing loop is controlled with three oxygen sensors, a microcontroller and a solenoid valve - critical components that may fail. State-of-the-art detection of sensor failure, based on a voting algorithm, may fail under circumstances where two or more sensors show the same but incorrect values. The present paper details a novel rebreather controller that offers true sensor-signal validation, thus allowing efficient and reliable detection of sensor failure. The core components of this validation system are two additional solenoids, which allow an injection of oxygen or diluent gas directly across the sensor membrane.

HYTESS 2: A Hypothetical Turbofan Engine Simplified Simulation with multivariable control and sensor analytical redundancy

NASA Technical Reports Server (NTRS)

Merrill, W. C.

1986-01-01

A hypothetical turbofan engine simplified simulation with a multivariable control and sensor failure detection, isolation, and accommodation logic (HYTESS II) is presented. The digital program, written in FORTRAN, is self-contained, efficient, realistic and easily used. Simulated engine dynamics were developed from linearized operating point models. However, essential nonlinear effects are retained. The simulation is representative of the hypothetical, low bypass ratio turbofan engine with an advanced control and failure detection logic. Included is a description of the engine dynamics, the control algorithm, and the sensor failure detection logic. Details of the simulation including block diagrams, variable descriptions, common block definitions, subroutine descriptions, and input requirements are given. Example simulation results are also presented.

Spacecraft dynamics characterization and control system failure detection. Volume 3: Control system failure monitoring

NASA Technical Reports Server (NTRS)

Vanschalkwyk, Christiaan M.

1992-01-01

We discuss the application of Generalized Parity Relations to two experimental flexible space structures, the NASA Langley Mini-Mast and Marshall Space Flight Center ACES mast. We concentrate on the generation of residuals and make no attempt to implement the Decision Function. It should be clear from the examples that are presented whether it would be possible to detect the failure of a specific component. We derive the equations from Generalized Parity Relations. Two special cases are treated: namely, Single Sensor Parity Relations (SSPR) and Double Sensor Parity Relations (DSPR). Generalized Parity Relations for actuators are also derived. The NASA Langley Mini-Mast and the application of SSPR and DSPR to a set of displacement sensors located at the tip of the Mini-Mast are discussed. The performance of a reduced order model that includes the first five models of the mast is compared to a set of parity relations that was identified on a set of input-output data. Both time domain and frequency domain comparisons are made. The effect of the sampling period and model order on the performance of the Residual Generators are also discussed. Failure detection experiments where the sensor set consisted of two gyros and an accelerometer are presented. The effects of model order and sampling frequency are again illustrated. The detection of actuator failures is discussed. We use Generalized Parity Relations to monitor control system component failures on the ACES mast. An overview is given of the Failure Detection Filter and experimental results are discussed. Conclusions and directions for future research are given.

Sensors and systems for space applications: a methodology for developing fault detection, diagnosis, and recovery

NASA Astrophysics Data System (ADS)

Edwards, John L.; Beekman, Randy M.; Buchanan, David B.; Farner, Scott; Gershzohn, Gary R.; Khuzadi, Mbuyi; Mikula, D. F.; Nissen, Gerry; Peck, James; Taylor, Shaun

2007-04-01

Human space travel is inherently dangerous. Hazardous conditions will exist. Real time health monitoring of critical subsystems is essential for providing a safe abort timeline in the event of a catastrophic subsystem failure. In this paper, we discuss a practical and cost effective process for developing critical subsystem failure detection, diagnosis and response (FDDR). We also present the results of a real time health monitoring simulation of a propellant ullage pressurization subsystem failure. The health monitoring development process identifies hazards, isolates hazard causes, defines software partitioning requirements and quantifies software algorithm development. The process provides a means to establish the number and placement of sensors necessary to provide real time health monitoring. We discuss how health monitoring software tracks subsystem control commands, interprets off-nominal operational sensor data, predicts failure propagation timelines, corroborate failures predictions and formats failure protocol.

Failure detection and correction for turbofan engines

NASA Technical Reports Server (NTRS)

Corley, R. C.; Spang, H. A., III

1977-01-01

In this paper, a failure detection and correction strategy for turbofan engines is discussed. This strategy allows continuing control of the engines in the event of a sensor failure. An extended Kalman filter is used to provide the best estimate of the state of the engine based on currently available sensor outputs. Should a sensor failure occur the control is based on the best estimate rather than the sensor output. The extended Kalman filter consists of essentially two parts, a nonlinear model of the engine and up-date logic which causes the model to track the actual engine. Details on the model and up-date logic are presented. To allow implementation, approximations are made to the feedback gain matrix which result in a single feedback matrix which is suitable for use over the entire flight envelope. The effect of these approximations on stability and response is discussed. Results from a detailed nonlinear simulation indicate that good control can be maintained even under multiple failures.

Sensor failure detection for jet engines

NASA Technical Reports Server (NTRS)

Merrill, Walter C.

1988-01-01

The use of analytical redundancy to improve gas turbine engine control system reliability through sensor failure detection, isolation, and accommodation is surveyed. Both the theoretical and application papers that form the technology base of turbine engine analytical redundancy research are discussed. Also, several important application efforts are reviewed. An assessment of the state-of-the-art in analytical redundancy technology is given.

40 CFR 65.112 - Standards: Compressors.

Code of Federal Regulations, 2013 CFR

2013-07-01

... barrier fluid system shall be equipped with a sensor that will detect failure of the seal system, barrier fluid system, or both. Each sensor shall be observed daily or shall be equipped with an alarm unless the... criterion that indicates failure of the seal system, the barrier fluid system, or both. If the sensor...

40 CFR 63.1031 - Compressors standards.

Code of Federal Regulations, 2013 CFR

2013-07-01

... service. Each barrier fluid system shall be equipped with a sensor that will detect failure of the seal system, barrier fluid system, or both. Each sensor shall be observed daily or shall be equipped with an... both. If the sensor indicates failure of the seal system, the barrier fluid system, or both based on...

40 CFR 61.242-3 - Standards: Compressors.

Code of Federal Regulations, 2012 CFR

2012-07-01

... paragraphs (a)-(c) of this section shall be equipped with a sensor that will detect failure of the seal system, barrier fluid system, or both. (e)(1) Each sensor as required in paragraph (d) of this section... system, or both. (f) If the sensor indicates failure of the seal system, the barrier fluid system, or...

40 CFR 63.1012 - Compressor standards.

Code of Federal Regulations, 2011 CFR

2011-07-01

... fluid system degassing reservoir that is routed to a process or fuel gas system or connected by a closed... sensor that will detect failure of the seal system, barrier fluid system, or both. Each sensor shall be... the seal system, the barrier fluid system, or both. If the sensor indicates failure of the seal system...

40 CFR 63.1012 - Compressor standards.

Code of Federal Regulations, 2010 CFR

2010-07-01

... fluid system degassing reservoir that is routed to a process or fuel gas system or connected by a closed... sensor that will detect failure of the seal system, barrier fluid system, or both. Each sensor shall be... the seal system, the barrier fluid system, or both. If the sensor indicates failure of the seal system...

Continuous Particulate Filter State of Health Monitoring Using Radio Frequency Sensing

DOE PAGES

Sappok, Alexander; Ragaller, Paul; Herman, Andrew; ...

2018-04-03

Reliable means for on-board detection of particulate filter failures or malfunctions are needed to meet diagnostics (OBD) requirements. Detecting these failures, which result in tailpipe particulate matter (PM) emissions exceeding the OBD limit, over all operating conditions is challenging. Current approaches employ differential pressure sensors and downstream PM sensors, in combination with particulate filter and engine-out soot models. These conventional monitors typically operate over narrowly-defined time windows and do not provide a direct measure of the filter’s state of health. In contrast, radio frequency (RF) sensors, which transmit a wireless signal through the filter substrate provide a direct means formore » interrogating the condition of the filter itself. Here, this study investigated the use of RF sensors for the continuous measurement of filter trapping efficiency, which was compared to downstream measurements with an AVL Microsoot Sensor, and a PM sampling probe simulating the geometry and installation configuration of a conventional PM sensor. The study included several particulate filter failure modes, both above and below the OBD threshold. Finally, the results confirmed the use of RF sensors to provide a direct and continuous measure of the particulate filter’s state of health over a range of typical in-use operating conditions, thereby significantly increasing the time window over which filter failures may be detected.« less

Continuous Particulate Filter State of Health Monitoring Using Radio Frequency Sensing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sappok, Alexander; Ragaller, Paul; Herman, Andrew

Reliable means for on-board detection of particulate filter failures or malfunctions are needed to meet diagnostics (OBD) requirements. Detecting these failures, which result in tailpipe particulate matter (PM) emissions exceeding the OBD limit, over all operating conditions is challenging. Current approaches employ differential pressure sensors and downstream PM sensors, in combination with particulate filter and engine-out soot models. These conventional monitors typically operate over narrowly-defined time windows and do not provide a direct measure of the filter’s state of health. In contrast, radio frequency (RF) sensors, which transmit a wireless signal through the filter substrate provide a direct means formore » interrogating the condition of the filter itself. Here, this study investigated the use of RF sensors for the continuous measurement of filter trapping efficiency, which was compared to downstream measurements with an AVL Microsoot Sensor, and a PM sampling probe simulating the geometry and installation configuration of a conventional PM sensor. The study included several particulate filter failure modes, both above and below the OBD threshold. Finally, the results confirmed the use of RF sensors to provide a direct and continuous measure of the particulate filter’s state of health over a range of typical in-use operating conditions, thereby significantly increasing the time window over which filter failures may be detected.« less

A real time microcomputer implementation of sensor failure detection for turbofan engines

NASA Technical Reports Server (NTRS)

Delaat, John C.; Merrill, Walter C.

1989-01-01

An algorithm was developed which detects, isolates, and accommodates sensor failures using analytical redundancy. The performance of this algorithm was demonstrated on a full-scale F100 turbofan engine. The algorithm was implemented in real-time on a microprocessor-based controls computer which includes parallel processing and high order language programming. Parallel processing was used to achieve the required computational power for the real-time implementation. High order language programming was used in order to reduce the programming and maintenance costs of the algorithm implementation software. The sensor failure algorithm was combined with an existing multivariable control algorithm to give a complete control implementation with sensor analytical redundancy. The real-time microprocessor implementation of the algorithm which resulted in the successful completion of the algorithm engine demonstration, is described.

40 CFR 60.482-3a - Standards: Compressors.

Code of Federal Regulations, 2012 CFR

2012-07-01

... equipped with a sensor that will detect failure of the seal system, barrier fluid system, or both. (e)(1) Each sensor as required in paragraph (d) of this section shall be checked daily or shall be equipped... both. (f) If the sensor indicates failure of the seal system, the barrier system, or both based on the...

Low-cost failure sensor design and development for water pipeline distribution systems.

PubMed

Khan, K; Widdop, P D; Day, A J; Wood, A S; Mounce, S R; Machell, J

2002-01-01

This paper describes the design and development of a new sensor which is low cost to manufacture and install and is reliable in operation with sufficient accuracy, resolution and repeatability for use in newly developed systems for pipeline monitoring and leakage detection. To provide an appropriate signal, the concept of a "failure" sensor is introduced, in which the output is not necessarily proportional to the input, but is unmistakably affected when an unusual event occurs. The design of this failure sensor is based on the water opacity which can be indicative of an unusual event in a water distribution network. The laboratory work and field trials necessary to design and prove out this type of failure sensor are described here. It is concluded that a low-cost failure sensor of this type has good potential for use in a comprehensive water monitoring and management system based on Artificial Neural Networks (ANN).

Autonomous Component Health Management with Failed Component Detection, Identification, and Avoidance

NASA Technical Reports Server (NTRS)

Davis, Robert N.; Polites, Michael E.; Trevino, Luis C.

2004-01-01

This paper details a novel scheme for autonomous component health management (ACHM) with failed actuator detection and failed sensor detection, identification, and avoidance. This new scheme has features that far exceed the performance of systems with triple-redundant sensing and voting, yet requires fewer sensors and could be applied to any system with redundant sensing. Relevant background to the ACHM scheme is provided, and the simulation results for the application of that scheme to a single-axis spacecraft attitude control system with a 3rd order plant and dual-redundant measurement of system states are presented. ACHM fulfills key functions needed by an integrated vehicle health monitoring (IVHM) system. It is: autonomous; adaptive; works in realtime; provides optimal state estimation; identifies failed components; avoids failed components; reconfigures for multiple failures; reconfigures for intermittent failures; works for hard-over, soft, and zero-output failures; and works for both open- and closed-loop systems. The ACHM scheme combines a prefilter that generates preliminary state estimates, detects and identifies failed sensors and actuators, and avoids the use of failed sensors in state estimation with a fixed-gain Kalman filter that generates optimal state estimates and provides model-based state estimates that comprise an integral part of the failure detection logic. The results show that ACHM successfully isolates multiple persistent and intermittent hard-over, soft, and zero-output failures. It is now ready to be tested on a computer model of an actual system.

An Indirect Adaptive Control Scheme in the Presence of Actuator and Sensor Failures

NASA Technical Reports Server (NTRS)

Sun, Joy Z.; Josh, Suresh M.

2009-01-01

The problem of controlling a system in the presence of unknown actuator and sensor faults is addressed. The system is assumed to have groups of actuators, and groups of sensors, with each group consisting of multiple redundant similar actuators or sensors. The types of actuator faults considered consist of unknown actuators stuck in unknown positions, as well as reduced actuator effectiveness. The sensor faults considered include unknown biases and outages. The approach employed for fault detection and estimation consists of a bank of Kalman filters based on multiple models, and subsequent control reconfiguration to mitigate the effect of biases caused by failed components as well as to obtain stability and satisfactory performance using the remaining actuators and sensors. Conditions for fault identifiability are presented, and the adaptive scheme is applied to an aircraft flight control example in the presence of actuator failures. Simulation results demonstrate that the method can rapidly and accurately detect faults and estimate the fault values, thus enabling safe operation and acceptable performance in spite of failures.

A study of redundancy management strategy for tetrad strap-down inertial systems. [error detection codes

NASA Technical Reports Server (NTRS)

Hruby, R. J.; Bjorkman, W. S.; Schmidt, S. F.; Carestia, R. A.

1979-01-01

Algorithms were developed that attempt to identify which sensor in a tetrad configuration has experienced a step failure. An algorithm is also described that provides a measure of the confidence with which the correct identification was made. Experimental results are presented from real-time tests conducted on a three-axis motion facility utilizing an ortho-skew tetrad strapdown inertial sensor package. The effects of prediction errors and of quantization on correct failure identification are discussed as well as an algorithm for detecting second failures through prediction.

Lyapunov-Based Sensor Failure Detection And Recovery For The Reverse Water Gas Shift Process

NASA Technical Reports Server (NTRS)

Haralambous, Michael G.

2001-01-01

Livingstone, a model-based AI software system, is planned for use in the autonomous fault diagnosis, reconfiguration, and control of the oxygen-producing reverse water gas shift (RWGS) process test-bed located in the Applied Chemistry Laboratory at KSC. In this report the RWGS process is first briefly described and an overview of Livingstone is given. Next, a Lyapunov-based approach for detecting and recovering from sensor failures, differing significantly from that used by Livingstone, is presented. In this new method, models used are in terms of the defining differential equations of system components, thus differing from the qualitative, static models used by Livingstone. An easily computed scalar inequality constraint, expressed in terms of sensed system variables, is used to determine the existence of sensor failures. In the event of sensor failure, an observer/estimator is used for determining which sensors have failed. The theory underlying the new approach is developed. Finally, a recommendation is made to use the Lyapunov-based approach to complement the capability of Livingstone and to use this combination in the RWGS process.

LYAPUNOV-Based Sensor Failure Detection and Recovery for the Reverse Water Gas Shift Process

NASA Technical Reports Server (NTRS)

Haralambous, Michael G.

2002-01-01

Livingstone, a model-based AI software system, is planned for use in the autonomous fault diagnosis, reconfiguration, and control of the oxygen-producing reverse water gas shift (RWGS) process test-bed located in the Applied Chemistry Laboratory at KSC. In this report the RWGS process is first briefly described and an overview of Livingstone is given. Next, a Lyapunov-based approach for detecting and recovering from sensor failures, differing significantly from that used by Livingstone, is presented. In this new method, models used are in t e m of the defining differential equations of system components, thus differing from the qualitative, static models used by Livingstone. An easily computed scalar inequality constraint, expressed in terms of sensed system variables, is used to determine the existence of sensor failures. In the event of sensor failure, an observer/estimator is used for determining which sensors have failed. The theory underlying the new approach is developed. Finally, a recommendation is made to use the Lyapunov-based approach to complement the capability of Livingstone and to use this combination in the RWGS process.

General test plan redundant sensor strapdown IMU evaluation program

NASA Technical Reports Server (NTRS)

Hartwell, T.; Irwin, H. A.; Miyatake, Y.; Wedekind, D. E.

1971-01-01

The general test plan for a redundant sensor strapdown inertial measuring unit evaluation program is presented. The inertial unit contains six gyros and three orthogonal accelerometers. The software incorporates failure detection and correction logic and a land vehicle navigation program. The principal objective of the test is a demonstration of the practicability, reliability, and performance of the inertial measuring unit with failure detection and correction in operational environments.

Extended Testability Analysis Tool

NASA Technical Reports Server (NTRS)

Melcher, Kevin; Maul, William A.; Fulton, Christopher

2012-01-01

The Extended Testability Analysis (ETA) Tool is a software application that supports fault management (FM) by performing testability analyses on the fault propagation model of a given system. Fault management includes the prevention of faults through robust design margins and quality assurance methods, or the mitigation of system failures. Fault management requires an understanding of the system design and operation, potential failure mechanisms within the system, and the propagation of those potential failures through the system. The purpose of the ETA Tool software is to process the testability analysis results from a commercial software program called TEAMS Designer in order to provide a detailed set of diagnostic assessment reports. The ETA Tool is a command-line process with several user-selectable report output options. The ETA Tool also extends the COTS testability analysis and enables variation studies with sensor sensitivity impacts on system diagnostics and component isolation using a single testability output. The ETA Tool can also provide extended analyses from a single set of testability output files. The following analysis reports are available to the user: (1) the Detectability Report provides a breakdown of how each tested failure mode was detected, (2) the Test Utilization Report identifies all the failure modes that each test detects, (3) the Failure Mode Isolation Report demonstrates the system s ability to discriminate between failure modes, (4) the Component Isolation Report demonstrates the system s ability to discriminate between failure modes relative to the components containing the failure modes, (5) the Sensor Sensor Sensitivity Analysis Report shows the diagnostic impact due to loss of sensor information, and (6) the Effect Mapping Report identifies failure modes that result in specified system-level effects.

Passive wireless antenna sensors for crack detection and shear/compression sensing

NASA Astrophysics Data System (ADS)

Mohammad, Irshad

Despite the fact that engineering components and structures are carefully designed against fatigue failures, 50 to 90% of mechanical failures are due to fatigue crack development. The severity of the failure depends on both the crack length and its orientation. Many types of sensors are available that can detect fatigue crack propagation. However, crack orientation detection has been rarely reported in the literature. We evaluated a patch antenna sensor capable of detecting crack propagation as well as crack orientation changes. The aim of these sensors would be to evaluate the real-time health condition of metallic structures to avoid catastrophic failures. The proposed crack sensing system consists of a dielectric substrate with a ground plane on one side of the substrate and an antenna patch printed on the other side of the substrate. The ground plane and the antenna patch, both conductive in nature, form an electromagnetic resonant cavity that radiates at distinct frequencies. These frequencies are monitored to evaluate the condition of cracks. A wireless sensor array can be realized by implementing a wireless interrogation unit. The scientific merits of this research are: 1) high sensitivity: it was demonstrated that the antenna sensors can detect crack growth with a sub-millimeter resolution; 2) passive wireless operation: based on microstrip antennas, the antenna sensors encode the sensing information in the backscattered antenna signal and thus can transmit the information without needing a local battery; 3) thin and conformal: the entire sensor unit is less than a millimeter thick and highly conformal; 4) crack orientation detection: the crack orientation on the structure can be precisely evaluated based on a single parameter, which only few sensors can accomplish. In addition to crack detection, the patch antenna sensors are also investigated for measuring shear and pressure forces, with an aim to study the formation, diagnostics and prevention of foot ulcers in diabetic patients. These sensors were vertically integrated and embedded in the insole of shoes for measuring plantar pressure/shear distribution. The scientific merits of this proposed research are: 1) simultaneous shear/pressure measurement : current smart shoe technology can only measure shear and pressure separately due to the size of the shear sensor. The proposed sensor can measure shear and pressure deformation simultaneously; 2) high sensitivity and spatial resolution: these sensors are very sensitive and have compact size that enables measuring stress distribution with fine spatial resolution; 3) passive and un-tethered operation: the sensor transponder was mounted on the top surface of the shoe to facilitate wireless interrogation of the sensor array embedded in the insole of the shoe, eliminating external wiring completely.

Sensory redundancy management: The development of a design methodology for determining threshold values through a statistical analysis of sensor output data

NASA Technical Reports Server (NTRS)

Scalzo, F.

1983-01-01

Sensor redundancy management (SRM) requires a system which will detect failures and reconstruct avionics accordingly. A probability density function to determine false alarm rates, using an algorithmic approach was generated. Microcomputer software was developed which will print out tables of values for the cummulative probability of being in the domain of failure; system reliability; and false alarm probability, given a signal is in the domain of failure. The microcomputer software was applied to the sensor output data for various AFT1 F-16 flights and sensor parameters. Practical recommendations for further research were made.

A Sensor Failure Simulator for Control System Reliability Studies

NASA Technical Reports Server (NTRS)

Melcher, K. J.; Delaat, J. C.; Merrill, W. C.; Oberle, L. G.; Sadler, G. G.; Schaefer, J. H.

1986-01-01

A real-time Sensor Failure Simulator (SFS) was designed and assembled for the Advanced Detection, Isolation, and Accommodation (ADIA) program. Various designs were considered. The design chosen features an IBM-PC/XT. The PC is used to drive analog circuitry for simulating sensor failures in real-time. A user defined scenario describes the failure simulation for each of the five incoming sensor signals. Capabilities exist for editing, saving, and retrieving the failure scenarios. The SFS has been tested closed-loop with the Controls Interface and Monitoring (CIM) unit, the ADIA control, and a real-time F100 hybrid simulation. From a productivity viewpoint, the menu driven user interface has proven to be efficient and easy to use. From a real-time viewpoint, the software controlling the simulation loop executes at greater than 100 cycles/sec.

A sensor failure simulator for control system reliability studies

NASA Astrophysics Data System (ADS)

Melcher, K. J.; Delaat, J. C.; Merrill, W. C.; Oberle, L. G.; Sadler, G. G.; Schaefer, J. H.

A real-time Sensor Failure Simulator (SFS) was designed and assembled for the Advanced Detection, Isolation, and Accommodation (ADIA) program. Various designs were considered. The design chosen features an IBM-PC/XT. The PC is used to drive analog circuitry for simulating sensor failures in real-time. A user defined scenario describes the failure simulation for each of the five incoming sensor signals. Capabilities exist for editing, saving, and retrieving the failure scenarios. The SFS has been tested closed-loop with the Controls Interface and Monitoring (CIM) unit, the ADIA control, and a real-time F100 hybrid simulation. From a productivity viewpoint, the menu driven user interface has proven to be efficient and easy to use. From a real-time viewpoint, the software controlling the simulation loop executes at greater than 100 cycles/sec.

Orthogonal series generalized likelihood ratio test for failure detection and isolation. [for aircraft control

NASA Technical Reports Server (NTRS)

Hall, Steven R.; Walker, Bruce K.

1990-01-01

A new failure detection and isolation algorithm for linear dynamic systems is presented. This algorithm, the Orthogonal Series Generalized Likelihood Ratio (OSGLR) test, is based on the assumption that the failure modes of interest can be represented by truncated series expansions. This assumption leads to a failure detection algorithm with several desirable properties. Computer simulation results are presented for the detection of the failures of actuators and sensors of a C-130 aircraft. The results show that the OSGLR test generally performs as well as the GLR test in terms of time to detect a failure and is more robust to failure mode uncertainty. However, the OSGLR test is also somewhat more sensitive to modeling errors than the GLR test.

A real-time simulation evaluation of an advanced detection. Isolation and accommodation algorithm for sensor failures in turbine engines

NASA Technical Reports Server (NTRS)

Merrill, W. C.; Delaat, J. C.

1986-01-01

An advanced sensor failure detection, isolation, and accommodation (ADIA) algorithm has been developed for use with an aircraft turbofan engine control system. In a previous paper the authors described the ADIA algorithm and its real-time implementation. Subsequent improvements made to the algorithm and implementation are discussed, and the results of an evaluation presented. The evaluation used a real-time, hybrid computer simulation of an F100 turbofan engine.

Advanced detection, isolation, and accommodation of sensor failures in turbofan engines: Real-time microcomputer implementation

NASA Technical Reports Server (NTRS)

Delaat, John C.; Merrill, Walter C.

1990-01-01

The objective of the Advanced Detection, Isolation, and Accommodation Program is to improve the overall demonstrated reliability of digital electronic control systems for turbine engines. For this purpose, an algorithm was developed which detects, isolates, and accommodates sensor failures by using analytical redundancy. The performance of this algorithm was evaluated on a real time engine simulation and was demonstrated on a full scale F100 turbofan engine. The real time implementation of the algorithm is described. The implementation used state-of-the-art microprocessor hardware and software, including parallel processing and high order language programming.

40 CFR 63.1007 - Pumps in light liquid service standards.

Code of Federal Regulations, 2011 CFR

2011-07-01

... sensor that indicates failure of the seal system, the barrier fluid system, or both. The owner or... reservoir that is routed to a process or fuel gas system or connected by a closed vent system to a control... liquid service. (iv) Each barrier fluid system is equipped with a sensor that will detect failure of the...

40 CFR 65.107 - Standards: Pumps in light liquid service.

Code of Federal Regulations, 2010 CFR

2010-07-01

... frequency of drips and to the sensor that indicates failure of the seal system, the barrier fluid system, or... or fuel gas system or connected by a closed vent system to a control device that complies with the... equipped with a sensor that will detect failure of the seal system, the barrier fluid system, or both. (v...

40 CFR 63.1007 - Pumps in light liquid service standards.

Code of Federal Regulations, 2010 CFR

2010-07-01

... sensor that indicates failure of the seal system, the barrier fluid system, or both. The owner or... reservoir that is routed to a process or fuel gas system or connected by a closed vent system to a control... liquid service. (iv) Each barrier fluid system is equipped with a sensor that will detect failure of the...

40 CFR 63.1026 - Pumps in light liquid service standards.

Code of Federal Regulations, 2010 CFR

2010-07-01

... presence and frequency of drips and to the sensor that indicates failure of the seal system, the barrier... or fuel gas system or connected by a closed-vent system to a control device that complies with the.... (iv) Each barrier fluid system is equipped with a sensor that will detect failure of the seal system...

Apparatus for sensor failure detection and correction in a gas turbine engine control system

NASA Technical Reports Server (NTRS)

Spang, H. A., III; Wanger, R. P. (Inventor)

1981-01-01

A gas turbine engine control system maintains a selected level of engine performance despite the failure or abnormal operation of one or more engine parameter sensors. The control system employs a continuously updated engine model which simulates engine performance and generates signals representing real time estimates of the engine parameter sensor signals. The estimate signals are transmitted to a control computational unit which utilizes them in lieu of the actual engine parameter sensor signals to control the operation of the engine. The estimate signals are also compared with the corresponding actual engine parameter sensor signals and the resulting difference signals are utilized to update the engine model. If a particular difference signal exceeds specific tolerance limits, the difference signal is inhibited from updating the model and a sensor failure indication is provided to the engine operator.

On Identifiability of Bias-Type Actuator-Sensor Faults in Multiple-Model-Based Fault Detection and Identification

NASA Technical Reports Server (NTRS)

Joshi, Suresh M.

2012-01-01

This paper explores a class of multiple-model-based fault detection and identification (FDI) methods for bias-type faults in actuators and sensors. These methods employ banks of Kalman-Bucy filters to detect the faults, determine the fault pattern, and estimate the fault values, wherein each Kalman-Bucy filter is tuned to a different failure pattern. Necessary and sufficient conditions are presented for identifiability of actuator faults, sensor faults, and simultaneous actuator and sensor faults. It is shown that FDI of simultaneous actuator and sensor faults is not possible using these methods when all sensors have biases.

Robust Fault Detection and Isolation for Stochastic Systems

NASA Technical Reports Server (NTRS)

George, Jemin; Gregory, Irene M.

2010-01-01

This paper outlines the formulation of a robust fault detection and isolation scheme that can precisely detect and isolate simultaneous actuator and sensor faults for uncertain linear stochastic systems. The given robust fault detection scheme based on the discontinuous robust observer approach would be able to distinguish between model uncertainties and actuator failures and therefore eliminate the problem of false alarms. Since the proposed approach involves precise reconstruction of sensor faults, it can also be used for sensor fault identification and the reconstruction of true outputs from faulty sensor outputs. Simulation results presented here validate the effectiveness of the robust fault detection and isolation system.

Time-Frequency Methods for Structural Health Monitoring †

PubMed Central

Pyayt, Alexander L.; Kozionov, Alexey P.; Mokhov, Ilya I.; Lang, Bernhard; Meijer, Robert J.; Krzhizhanovskaya, Valeria V.; Sloot, Peter M. A.

2014-01-01

Detection of early warning signals for the imminent failure of large and complex engineered structures is a daunting challenge with many open research questions. In this paper we report on novel ways to perform Structural Health Monitoring (SHM) of flood protection systems (levees, earthen dikes and concrete dams) using sensor data. We present a robust data-driven anomaly detection method that combines time-frequency feature extraction, using wavelet analysis and phase shift, with one-sided classification techniques to identify the onset of failure anomalies in real-time sensor measurements. The methodology has been successfully tested at three operational levees. We detected a dam leakage in the retaining dam (Germany) and “strange” behaviour of sensors installed in a Boston levee (UK) and a Rhine levee (Germany). PMID:24625740

33 CFR 117.743 - Rahway River.

Code of Federal Regulations, 2010 CFR

2010-07-01

... lights anytime the bridge is not in the full open position. (d) An infrared sensor system shall be... the infrared sensor system. (g) If the infrared sensors detect a vessel or other obstruction.... (j) In the event of a failure, or obstruction to the infrared sensor system, the bridge shall...

33 CFR 117.743 - Rahway River.

Code of Federal Regulations, 2011 CFR

2011-07-01

... lights anytime the bridge is not in the full open position. (d) An infrared sensor system shall be... the infrared sensor system. (g) If the infrared sensors detect a vessel or other obstruction.... (j) In the event of a failure, or obstruction to the infrared sensor system, the bridge shall...

33 CFR 117.743 - Rahway River.

Code of Federal Regulations, 2012 CFR

2012-07-01

... lights anytime the bridge is not in the full open position. (d) An infrared sensor system shall be... the infrared sensor system. (g) If the infrared sensors detect a vessel or other obstruction.... (j) In the event of a failure, or obstruction to the infrared sensor system, the bridge shall...

33 CFR 117.743 - Rahway River.

Code of Federal Regulations, 2014 CFR

2014-07-01

... lights anytime the bridge is not in the full open position. (d) An infrared sensor system shall be... the infrared sensor system. (g) If the infrared sensors detect a vessel or other obstruction.... (j) In the event of a failure, or obstruction to the infrared sensor system, the bridge shall...

33 CFR 117.743 - Rahway River.

Code of Federal Regulations, 2013 CFR

2013-07-01

... lights anytime the bridge is not in the full open position. (d) An infrared sensor system shall be... the infrared sensor system. (g) If the infrared sensors detect a vessel or other obstruction.... (j) In the event of a failure, or obstruction to the infrared sensor system, the bridge shall...

FINDS: A fault inferring nonlinear detection system programmers manual, version 3.0

NASA Technical Reports Server (NTRS)

Lancraft, R. E.

1985-01-01

Detailed software documentation of the digital computer program FINDS (Fault Inferring Nonlinear Detection System) Version 3.0 is provided. FINDS is a highly modular and extensible computer program designed to monitor and detect sensor failures, while at the same time providing reliable state estimates. In this version of the program the FINDS methodology is used to detect, isolate, and compensate for failures in simulated avionics sensors used by the Advanced Transport Operating Systems (ATOPS) Transport System Research Vehicle (TSRV) in a Microwave Landing System (MLS) environment. It is intended that this report serve as a programmers guide to aid in the maintenance, modification, and revision of the FINDS software.

Overview of the Smart Network Element Architecture and Recent Innovations

NASA Technical Reports Server (NTRS)

Perotti, Jose M.; Mata, Carlos T.; Oostdyk, Rebecca L.

2008-01-01

In industrial environments, system operators rely on the availability and accuracy of sensors to monitor processes and detect failures of components and/or processes. The sensors must be networked in such a way that their data is reported to a central human interface, where operators are tasked with making real-time decisions based on the state of the sensors and the components that are being monitored. Incorporating health management functions at this central location aids the operator by automating the decision-making process to suggest, and sometimes perform, the action required by current operating conditions. Integrated Systems Health Management (ISHM) aims to incorporate data from many sources, including real-time and historical data and user input, and extract information and knowledge from that data to diagnose failures and predict future failures of the system. By distributing health management processing to lower levels of the architecture, there is less bandwidth required for ISHM, enhanced data fusion, make systems and processes more robust, and improved resolution for the detection and isolation of failures in a system, subsystem, component, or process. The Smart Network Element (SNE) has been developed at NASA Kennedy Space Center to perform intelligent functions at sensors and actuators' level in support of ISHM.

Event Detection in Aerospace Systems using Centralized Sensor Networks: A Comparative Study of Several Methodologies

NASA Technical Reports Server (NTRS)

Mehr, Ali Farhang; Sauvageon, Julien; Agogino, Alice M.; Tumer, Irem Y.

2006-01-01

Recent advances in micro electromechanical systems technology, digital electronics, and wireless communications have enabled development of low-cost, low-power, multifunctional miniature smart sensors. These sensors can be deployed throughout a region in an aerospace vehicle to build a network for measurement, detection and surveillance applications. Event detection using such centralized sensor networks is often regarded as one of the most promising health management technologies in aerospace applications where timely detection of local anomalies has a great impact on the safety of the mission. In this paper, we propose to conduct a qualitative comparison of several local event detection algorithms for centralized redundant sensor networks. The algorithms are compared with respect to their ability to locate and evaluate an event in the presence of noise and sensor failures for various node geometries and densities.

Flight test results of the strapdown ring laser gyro tetrad inertial navigation system

NASA Technical Reports Server (NTRS)

Carestia, R. A.; Hruby, R. J.; Bjorkman, W. S.

1983-01-01

A helicopter flight test program undertaken to evaluate the performance of Tetrad (a strap down, laser gyro, inertial navigation system) is described. The results of 34 flights show a mean final navigational velocity error of 5.06 knots, with a standard deviation of 3.84 knots; a corresponding mean final position error of 2.66 n. mi., with a standard deviation of 1.48 n. mi.; and a modeled mean position error growth rate for the 34 tests of 1.96 knots, with a standard deviation of 1.09 knots. No laser gyro or accelerometer failures were detected during the flight tests. Off line parity residual studies used simulated failures with the prerecorded flight test and laboratory test data. The airborne Tetrad system's failure--detection logic, exercised during the tests, successfully demonstrated the detection of simulated ""hard'' failures and the system's ability to continue successfully to navigate by removing the simulated faulted sensor from the computations. Tetrad's four ring laser gyros provided reliable and accurate angular rate sensing during the 4 yr of the test program, and no sensor failures were detected during the evaluation of free inertial navigation performance.

Robust detection, isolation and accommodation for sensor failures

NASA Technical Reports Server (NTRS)

Emami-Naeini, A.; Akhter, M. M.; Rock, S. M.

1986-01-01

The objective is to extend the recent advances in robust control system design of multivariable systems to sensor failure detection, isolation, and accommodation (DIA), and estimator design. This effort provides analysis tools to quantify the trade-off between performance robustness and DIA sensitivity, which are to be used to achieve higher levels of performance robustness for given levels of DIA sensitivity. An innovations-based DIA scheme is used. Estimators, which depend upon a model of the process and process inputs and outputs, are used to generate these innovations. Thresholds used to determine failure detection are computed based on bounds on modeling errors, noise properties, and the class of failures. The applicability of the newly developed tools are demonstrated on a multivariable aircraft turbojet engine example. A new concept call the threshold selector was developed. It represents a significant and innovative tool for the analysis and synthesis of DiA algorithms. The estimators were made robust by introduction of an internal model and by frequency shaping. The internal mode provides asymptotically unbiased filter estimates.The incorporation of frequency shaping of the Linear Quadratic Gaussian cost functional modifies the estimator design to make it suitable for sensor failure DIA. The results are compared with previous studies which used thresholds that were selcted empirically. Comparison of these two techniques on a nonlinear dynamic engine simulation shows improved performance of the new method compared to previous techniques

Automatic tracking of wake vortices using ground-wind sensor data

DOT National Transportation Integrated Search

1977-01-03

Algorithms for automatic tracking of wake vortices using ground-wind anemometer : data are developed. Methods of bad-data suppression, track initiation, and : track termination are included. An effective sensor-failure detection-and identification : ...

A Fault Tolerance Mechanism for On-Road Sensor Networks

PubMed Central

Feng, Lei; Guo, Shaoyong; Sun, Jialu; Yu, Peng; Li, Wenjing

2016-01-01

On-Road Sensor Networks (ORSNs) play an important role in capturing traffic flow data for predicting short-term traffic patterns, driving assistance and self-driving vehicles. However, this kind of network is prone to large-scale communication failure if a few sensors physically fail. In this paper, to ensure that the network works normally, an effective fault-tolerance mechanism for ORSNs which mainly consists of backup on-road sensor deployment, redundant cluster head deployment and an adaptive failure detection and recovery method is proposed. Firstly, based on the N − x principle and the sensors’ failure rate, this paper formulates the backup sensor deployment problem in the form of a two-objective optimization, which explains the trade-off between the cost and fault resumption. In consideration of improving the network resilience further, this paper introduces a redundant cluster head deployment model according to the coverage constraint. Then a common solving method combining integer-continuing and sequential quadratic programming is explored to determine the optimal location of these two deployment problems. Moreover, an Adaptive Detection and Resume (ADR) protocol is deigned to recover the system communication through route and cluster adjustment if there is a backup on-road sensor mismatch. The final experiments show that our proposed mechanism can achieve an average 90% recovery rate and reduce the average number of failed sensors at most by 35.7%. PMID:27918483

High Reliability Engine Control Demonstrated for Aircraft Engines

NASA Technical Reports Server (NTRS)

Guo, Ten-Huei

1999-01-01

For a dual redundant-control system, which is typical for short-haul aircraft, if a failure is detected in a control sensor, the engine control is transferred to a safety mode and an advisory is issued for immediate maintenance action to replace the failed sensor. The safety mode typically results in severely degraded engine performance. The goal of the High Reliability Engine Control (HREC) program was to demonstrate that the neural-network-based sensor validation technology can safely operate an engine by using the nominal closed-loop control during and after sensor failures. With this technology, engine performance could be maintained, and the sensor could be replaced as a conveniently scheduled maintenance action.

Partial Discharge Monitoring in Power Transformers Using Low-Cost Piezoelectric Sensors

PubMed Central

Castro, Bruno; Clerice, Guilherme; Ramos, Caio; Andreoli, André; Baptista, Fabricio; Campos, Fernando; Ulson, José

2016-01-01

Power transformers are crucial in an electric power system. Failures in transformers can affect the quality and cause interruptions in the power supply. Partial discharges are a phenomenon that can cause failures in the transformers if not properly monitored. Typically, the monitoring requires high-cost corrective maintenance or even interruptions of the power system. Therefore, the development of online non-invasive monitoring systems to detect partial discharges in power transformers has great relevance since it can reduce significant maintenance costs. Although commercial acoustic emission sensors have been used to monitor partial discharges in power transformers, they still represent a significant cost. In order to overcome this drawback, this paper presents a study of the feasibility of low-cost piezoelectric sensors to identify partial discharges in mineral insulating oil of power transformers. The analysis of the feasibility of the proposed low-cost sensor is performed by its comparison with a commercial acoustic emission sensor commonly used to detect partial discharges. The comparison between the responses in the time and frequency domain of both sensors was carried out and the experimental results indicate that the proposed piezoelectric sensors have great potential in the detection of acoustic waves generated by partial discharges in insulation oil, contributing for the popularization of this noninvasive technique. PMID:27517931

Partial Discharge Monitoring in Power Transformers Using Low-Cost Piezoelectric Sensors.

PubMed

Castro, Bruno; Clerice, Guilherme; Ramos, Caio; Andreoli, André; Baptista, Fabricio; Campos, Fernando; Ulson, José

2016-08-10

Power transformers are crucial in an electric power system. Failures in transformers can affect the quality and cause interruptions in the power supply. Partial discharges are a phenomenon that can cause failures in the transformers if not properly monitored. Typically, the monitoring requires high-cost corrective maintenance or even interruptions of the power system. Therefore, the development of online non-invasive monitoring systems to detect partial discharges in power transformers has great relevance since it can reduce significant maintenance costs. Although commercial acoustic emission sensors have been used to monitor partial discharges in power transformers, they still represent a significant cost. In order to overcome this drawback, this paper presents a study of the feasibility of low-cost piezoelectric sensors to identify partial discharges in mineral insulating oil of power transformers. The analysis of the feasibility of the proposed low-cost sensor is performed by its comparison with a commercial acoustic emission sensor commonly used to detect partial discharges. The comparison between the responses in the time and frequency domain of both sensors was carried out and the experimental results indicate that the proposed piezoelectric sensors have great potential in the detection of acoustic waves generated by partial discharges in insulation oil, contributing for the popularization of this noninvasive technique.

Sensor Data Qualification System (SDQS) Implementation Study

NASA Technical Reports Server (NTRS)

Wong, Edmond; Melcher, Kevin; Fulton, Christopher; Maul, William

2009-01-01

The Sensor Data Qualification System (SDQS) is being developed to provide a sensor fault detection capability for NASA s next-generation launch vehicles. In addition to traditional data qualification techniques (such as limit checks, rate-of-change checks and hardware redundancy checks), SDQS can provide augmented capability through additional techniques that exploit analytical redundancy relationships to enable faster and more sensitive sensor fault detection. This paper documents the results of a study that was conducted to determine the best approach for implementing a SDQS network configuration that spans multiple subsystems, similar to those that may be implemented on future vehicles. The best approach is defined as one that most minimizes computational resource requirements without impacting the detection of sensor failures.

Flight test results of the Strapdown hexad Inertial Reference Unit (SIRU). Volume 1: Flight test summary

NASA Technical Reports Server (NTRS)

Hruby, R. J.; Bjorkman, W. S.

1977-01-01

Flight test results of the strapdown inertial reference unit (SIRU) navigation system are presented. The fault-tolerant SIRU navigation system features a redundant inertial sensor unit and dual computers. System software provides for detection and isolation of inertial sensor failures and continued operation in the event of failures. Flight test results include assessments of the system's navigational performance and fault tolerance.

40 CFR 63.163 - Standards: Pumps in light liquid service.

Code of Federal Regulations, 2011 CFR

2011-07-01

...) Equipped with a barrier fluid degassing reservoir that is routed to a process or fuel gas system or... with a sensor that will detect failure of the seal system, the barrier fluid system, or both. (4) Each... per million or greater is measured, a leak is detected. (5) Each sensor as described in paragraph (e...

Fault Detection and Isolation for Hydraulic Control

NASA Technical Reports Server (NTRS)

1987-01-01

Pressure sensors and isolation valves act to shut down defective servochannel. Redundant hydraulic system indirectly senses failure in any of its electrical control channels and mechanically isolates hydraulic channel controlled by faulty electrical channel so flat it cannot participate in operating system. With failure-detection and isolation technique, system can sustains two failed channels and still functions at full performance levels. Scheme useful on aircraft or other systems with hydraulic servovalves where failure cannot be tolerated.

Virtual Sensor for Failure Detection, Identification and Recovery in the Transition Phase of a Morphing Aircraft

PubMed Central

Heredia, Guillermo; Ollero, Aníbal

2010-01-01

The Helicopter Adaptive Aircraft (HADA) is a morphing aircraft which is able to take-off as a helicopter and, when in forward flight, unfold the wings that are hidden under the fuselage, and transfer the power from the main rotor to a propeller, thus morphing from a helicopter to an airplane. In this process, the reliable folding and unfolding of the wings is critical, since a failure may determine the ability to perform a mission, and may even be catastrophic. This paper proposes a virtual sensor based Fault Detection, Identification and Recovery (FDIR) system to increase the reliability of the HADA aircraft. The virtual sensor is able to capture the nonlinear interaction between the folding/unfolding wings aerodynamics and the HADA airframe using the navigation sensor measurements. The proposed FDIR system has been validated using a simulation model of the HADA aircraft, which includes real phenomena as sensor noise and sampling characteristics and turbulence and wind perturbations. PMID:22294922

Virtual sensor for failure detection, identification and recovery in the transition phase of a morphing aircraft.

PubMed

Heredia, Guillermo; Ollero, Aníbal

2010-01-01

The Helicopter Adaptive Aircraft (HADA) is a morphing aircraft which is able to take-off as a helicopter and, when in forward flight, unfold the wings that are hidden under the fuselage, and transfer the power from the main rotor to a propeller, thus morphing from a helicopter to an airplane. In this process, the reliable folding and unfolding of the wings is critical, since a failure may determine the ability to perform a mission, and may even be catastrophic. This paper proposes a virtual sensor based Fault Detection, Identification and Recovery (FDIR) system to increase the reliability of the HADA aircraft. The virtual sensor is able to capture the nonlinear interaction between the folding/unfolding wings aerodynamics and the HADA airframe using the navigation sensor measurements. The proposed FDIR system has been validated using a simulation model of the HADA aircraft, which includes real phenomena as sensor noise and sampling characteristics and turbulence and wind perturbations.

Bearing system

DOEpatents

Kapich, Davorin D.

1987-01-01

A bearing system includes backup bearings for supporting a rotating shaft upon failure of primary bearings. In the preferred embodiment, the backup bearings are rolling element bearings having their rolling elements disposed out of contact with their associated respective inner races during normal functioning of the primary bearings. Displacement detection sensors are provided for detecting displacement of the shaft upon failure of the primary bearings. Upon detection of the failure of the primary bearings, the rolling elements and inner races of the backup bearings are brought into mutual contact by axial displacement of the shaft.

Reliability analysis and fault-tolerant system development for a redundant strapdown inertial measurement unit. [inertial platforms

NASA Technical Reports Server (NTRS)

Motyka, P.

1983-01-01

A methodology is developed and applied for quantitatively analyzing the reliability of a dual, fail-operational redundant strapdown inertial measurement unit (RSDIMU). A Markov evaluation model is defined in terms of the operational states of the RSDIMU to predict system reliability. A 27 state model is defined based upon a candidate redundancy management system which can detect and isolate a spectrum of failure magnitudes. The results of parametric studies are presented which show the effect on reliability of the gyro failure rate, both the gyro and accelerometer failure rates together, false alarms, probability of failure detection, probability of failure isolation, and probability of damage effects and mission time. A technique is developed and evaluated for generating dynamic thresholds for detecting and isolating failures of the dual, separated IMU. Special emphasis is given to the detection of multiple, nonconcurrent failures. Digital simulation time histories are presented which show the thresholds obtained and their effectiveness in detecting and isolating sensor failures.

40 CFR 265.1053 - Standards: Compressors.

Code of Federal Regulations, 2010 CFR

2010-07-01

... equipped with a sensor that will detect failure of the seal system, barrier fluid system, or both. (e)(1) Each sensor as required in paragraph (d) of this section shall be checked daily or shall be equipped... compressor is located within the boundary of an unmanned plant site, in which case the sensor must be checked...

40 CFR 264.1053 - Standards: Compressors.

Code of Federal Regulations, 2010 CFR

2010-07-01

... equipped with a sensor that will detect failure of the seal system, barrier fluid system, or both. (e)(1) Each sensor as required in paragraph (d) of this section shall be checked daily or shall be equipped... compressor is located within the boundary of an unmanned plant site, in which case the sensor must be checked...

40 CFR 264.1053 - Standards: Compressors.

Code of Federal Regulations, 2011 CFR

2011-07-01

... equipped with a sensor that will detect failure of the seal system, barrier fluid system, or both. (e)(1) Each sensor as required in paragraph (d) of this section shall be checked daily or shall be equipped... compressor is located within the boundary of an unmanned plant site, in which case the sensor must be checked...

40 CFR 265.1053 - Standards: Compressors.

Code of Federal Regulations, 2011 CFR

2011-07-01

... equipped with a sensor that will detect failure of the seal system, barrier fluid system, or both. (e)(1) Each sensor as required in paragraph (d) of this section shall be checked daily or shall be equipped... compressor is located within the boundary of an unmanned plant site, in which case the sensor must be checked...

40 CFR 264.1053 - Standards: Compressors.

Code of Federal Regulations, 2014 CFR

2014-07-01

... equipped with a sensor that will detect failure of the seal system, barrier fluid system, or both. (e)(1) Each sensor as required in paragraph (d) of this section shall be checked daily or shall be equipped... compressor is located within the boundary of an unmanned plant site, in which case the sensor must be checked...

40 CFR 264.1053 - Standards: Compressors.

Code of Federal Regulations, 2013 CFR

2013-07-01

... equipped with a sensor that will detect failure of the seal system, barrier fluid system, or both. (e)(1) Each sensor as required in paragraph (d) of this section shall be checked daily or shall be equipped... compressor is located within the boundary of an unmanned plant site, in which case the sensor must be checked...

40 CFR 265.1053 - Standards: Compressors.

Code of Federal Regulations, 2013 CFR

2013-07-01

... equipped with a sensor that will detect failure of the seal system, barrier fluid system, or both. (e)(1) Each sensor as required in paragraph (d) of this section shall be checked daily or shall be equipped... compressor is located within the boundary of an unmanned plant site, in which case the sensor must be checked...

40 CFR 265.1053 - Standards: Compressors.

Code of Federal Regulations, 2012 CFR

2012-07-01

... equipped with a sensor that will detect failure of the seal system, barrier fluid system, or both. (e)(1) Each sensor as required in paragraph (d) of this section shall be checked daily or shall be equipped... compressor is located within the boundary of an unmanned plant site, in which case the sensor must be checked...

40 CFR 264.1053 - Standards: Compressors.

Code of Federal Regulations, 2012 CFR

2012-07-01

... equipped with a sensor that will detect failure of the seal system, barrier fluid system, or both. (e)(1) Each sensor as required in paragraph (d) of this section shall be checked daily or shall be equipped... compressor is located within the boundary of an unmanned plant site, in which case the sensor must be checked...

40 CFR 265.1053 - Standards: Compressors.

Code of Federal Regulations, 2014 CFR

2014-07-01

... equipped with a sensor that will detect failure of the seal system, barrier fluid system, or both. (e)(1) Each sensor as required in paragraph (d) of this section shall be checked daily or shall be equipped... compressor is located within the boundary of an unmanned plant site, in which case the sensor must be checked...

Spatiotemporal models for data-anomaly detection in dynamic environmental monitoring campaigns

Treesearch

E.W. Dereszynski; T.G. Dietterich

2011-01-01

The ecological sciences have benefited greatly from recent advances in wireless sensor technologies. These technologies allow researchers to deploy networks of automated sensors, which can monitor a landscape at very fine temporal and spatial scales. However, these networks are subject to harsh conditions, which lead to malfunctions in individual sensors and failures...

Flight test results of the strapdown hexad inertial reference unit (SIRU). Volume 2: Test report

NASA Technical Reports Server (NTRS)

Hruby, R. J.; Bjorkman, W. S.

1977-01-01

Results of flight tests of the Strapdown Inertial Reference Unit (SIRU) navigation system are presented. The fault tolerant SIRU navigation system features a redundant inertial sensor unit and dual computers. System software provides for detection and isolation of inertial sensor failures and continued operation in the event of failures. Flight test results include assessments of the system's navigational performance and fault tolerance. Performance shortcomings are analyzed.

Sensors on instrumented socks for detection of lower leg edema--An in vitro study.

PubMed

Zhang, Song; Rajamani, Rajesh

2015-01-01

This paper presents the design, sensing principles and in vitro evaluation of a novel instrumented sock intended for prediction and prevention of acute decompensated heart failure. The sock contains a drift-free ankle size sensor and a leg tissue elasticity sensor. Both sensors are inexpensive and developed using innovative new sensing ideas. Preliminary tests with the sensor prototypes show promising results: The ankle size sensor is capable of measuring 1 mm changes in ankle diameter and the tissue elasticity sensor can detect 0.15 MPa differences in elasticity. A low-profile instrumented sock prototype with these two sensors has been successfully fabricated and will be evaluated in the future in an IRB-approved human study.

Real-time sensor data validation

NASA Technical Reports Server (NTRS)

Bickmore, Timothy W.

1994-01-01

This report describes the status of an on-going effort to develop software capable of detecting sensor failures on rocket engines in real time. This software could be used in a rocket engine controller to prevent the erroneous shutdown of an engine due to sensor failures which would otherwise be interpreted as engine failures by the control software. The approach taken combines analytical redundancy with Bayesian belief networks to provide a solution which has well defined real-time characteristics and well-defined error rates. Analytical redundancy is a technique in which a sensor's value is predicted by using values from other sensors and known or empirically derived mathematical relations. A set of sensors and a set of relations among them form a network of cross-checks which can be used to periodically validate all of the sensors in the network. Bayesian belief networks provide a method of determining if each of the sensors in the network is valid, given the results of the cross-checks. This approach has been successfully demonstrated on the Technology Test Bed Engine at the NASA Marshall Space Flight Center. Current efforts are focused on extending the system to provide a validation capability for 100 sensors on the Space Shuttle Main Engine.

Formal Specification and Validation of a Hybrid Connectivity Restoration Algorithm for Wireless Sensor and Actor Networks †

PubMed Central

Imran, Muhammad; Zafar, Nazir Ahmad

2012-01-01

Maintaining inter-actor connectivity is extremely crucial in mission-critical applications of Wireless Sensor and Actor Networks (WSANs), as actors have to quickly plan optimal coordinated responses to detected events. Failure of a critical actor partitions the inter-actor network into disjoint segments besides leaving a coverage hole, and thus hinders the network operation. This paper presents a Partitioning detection and Connectivity Restoration (PCR) algorithm to tolerate critical actor failure. As part of pre-failure planning, PCR determines critical/non-critical actors based on localized information and designates each critical node with an appropriate backup (preferably non-critical). The pre-designated backup detects the failure of its primary actor and initiates a post-failure recovery process that may involve coordinated multi-actor relocation. To prove the correctness, we construct a formal specification of PCR using Z notation. We model WSAN topology as a dynamic graph and transform PCR to corresponding formal specification using Z notation. Formal specification is analyzed and validated using the Z Eves tool. Moreover, we simulate the specification to quantitatively analyze the efficiency of PCR. Simulation results confirm the effectiveness of PCR and the results shown that it outperforms contemporary schemes found in the literature.

Method and apparatus for detecting and determining event characteristics with reduced data collection

NASA Technical Reports Server (NTRS)

Totman, Peter D. (Inventor); Everton, Randy L. (Inventor); Egget, Mark R. (Inventor); Macon, David J. (Inventor)

2007-01-01

A method and apparatus for detecting and determining event characteristics such as, for example, the material failure of a component, in a manner which significantly reduces the amount of data collected. A sensor array, including a plurality of individual sensor elements, is coupled to a programmable logic device (PLD) configured to operate in a passive state and an active state. A triggering event is established such that the PLD records information only upon detection of the occurrence of the triggering event which causes a change in state within one or more of the plurality of sensor elements. Upon the occurrence of the triggering event, the change in state of the one or more sensor elements causes the PLD to record in memory which sensor element detected the event and at what time the event was detected. The PLD may be coupled with a computer for subsequent downloading and analysis of the acquired data.

Device for self-verifying temperature measurement and control

DOEpatents

Watkins, Arthur D.; Cannon, Collins P.; Tolle, Charles R.

2004-08-03

A measuring instrument includes a first temperature sensor, a second temperature sensor and circuitry. The first and second temperature sensors each generate a signal indicative of the temperature of a medium being detected. The circuitry is configured to activate verification of temperature being sensed with the first sensor. According to one construction, the first temperature sensor comprises at least one thermocouple temperature sensor and the second temperature sensor comprises an optical temperature sensor, each sensor measuring temperature over the same range of temperature, but using a different physical phenomena. Also according to one construction, the circuitry comprises a computer configured to detect failure of one of the thermocouples by comparing temperature of the optical temperature sensor with each of the thermocouple temperature sensors. Even further, an output control signal is generated via a fuzzy inference machine and control apparatus.

Device and method for self-verifying temperature measurement and control

DOEpatents

Watkins, Arthur D.; Cannon, Collins P.; Tolle, Charles R.

2002-10-29

A measuring instrument includes a first temperature sensor, a second temperature sensor and circuitry. The first and second temperature sensors each generate a signal indicative of the temperature of a medium being detected. The circuitry is configured to activate verification of temperature being sensed with the first sensor. According to one construction, the first temperature sensor comprises at least one thermocouple temperature sensor and the second temperature sensor comprises an optical temperature sensor, each sensor measuring temperature over the same range of temperature, but using a different physical phenomena. Also according to one construction, the circuitry comprises a computer configured to detect failure of one of the thermocouples by comparing temperature of the optical temperature sensor with each of the thermocouple temperature sensors. Even further, an output control signal is generated via a fuzzy inference machine and control apparatus.

Failure Control Techniques for the SSME

NASA Technical Reports Server (NTRS)

Taniguchi, M. H.

1987-01-01

Since ground testing of the Space Shuttle Main Engine (SSME) began in 1975, the detection of engine anomalies and the prevention of major damage have been achieved by a multi-faceted detection/shutdown system. The system continues the monitoring task today and consists of the following: sensors, automatic redline and other limit logic, redundant sensors and controller voting logic, conditional decision logic, and human monitoring. Typically, on the order of 300 to 500 measurements are sensed and recorded for each test, while on the order of 100 are used for control and monitoring. Despite extensive monitoring by the current detection system, twenty-seven (27) major incidents have occurred. This number would appear insignificant compared with over 1200 hot-fire tests which have taken place since 1976. However, the number suggests the requirement for and future benefits of a more advanced failure detection system.

Comparison of Event Detection Methods for Centralized Sensor Networks

NASA Technical Reports Server (NTRS)

Sauvageon, Julien; Agogiono, Alice M.; Farhang, Ali; Tumer, Irem Y.

2006-01-01

The development of an Integrated Vehicle Health Management (IVHM) for space vehicles has become a great concern. Smart Sensor Networks is one of the promising technologies that are catching a lot of attention. In this paper, we propose to a qualitative comparison of several local event (hot spot) detection algorithms in centralized redundant sensor networks. The algorithms are compared regarding their ability to locate and evaluate the event under noise and sensor failures. The purpose of this study is to check if the ratio performance/computational power of the Mote Fuzzy Validation and Fusion algorithm is relevant compare to simpler methods.

Optimally robust redundancy relations for failure detection in uncertain systems

NASA Technical Reports Server (NTRS)

Lou, X.-C.; Willsky, A. S.; Verghese, G. C.

1986-01-01

All failure detection methods are based, either explicitly or implicitly, on the use of redundancy, i.e. on (possibly dynamic) relations among the measured variables. The robustness of the failure detection process consequently depends to a great degree on the reliability of the redundancy relations, which in turn is affected by the inevitable presence of model uncertainties. In this paper the problem of determining redundancy relations that are optimally robust is addressed in a sense that includes several major issues of importance in practical failure detection and that provides a significant amount of intuition concerning the geometry of robust failure detection. A procedure is given involving the construction of a single matrix and its singular value decomposition for the determination of a complete sequence of redundancy relations, ordered in terms of their level of robustness. This procedure also provides the basis for comparing levels of robustness in redundancy provided by different sets of sensors.

System for detecting operating errors in a variable valve timing engine using pressure sensors

DOEpatents

Wiles, Matthew A.; Marriot, Craig D

2013-07-02

A method and control module includes a pressure sensor data comparison module that compares measured pressure volume signal segments to ideal pressure volume segments. A valve actuation hardware remedy module performs a hardware remedy in response to comparing the measured pressure volume signal segments to the ideal pressure volume segments when a valve actuation hardware failure is detected.

Implantable Wireless MEMS Sensors for Medical Uses

NASA Technical Reports Server (NTRS)

Chimbayo, Alexander

2006-01-01

Sensors designed and fabricated according to the principles of microelectromechanical systems (MEMS) are being developed for several medical applications in outer space and on Earth. The designs of these sensors are based on a core design family of pressure sensors, small enough to fit into the eye of a needle, that are fabricated by a "dissolved wafer" process. The sensors are expected to be implantable, batteryless, and wireless. They would be both powered and interrogated by hand-held radio transceivers from distances up to about 6 in. (about 15 cm). One type of sensor would be used to measure blood pressure, particularly for congestive heart failure. Another type would be used to monitor fluids in patients who have hydrocephalus (high brain pressure). Still other types would be used to detect errors in delivery of drugs and to help patients having congestive heart failure.

Aliasing Signal Separation of Superimposed Abrasive Debris Based on Degenerate Unmixing Estimation Technique.

PubMed

Li, Tongyang; Wang, Shaoping; Zio, Enrico; Shi, Jian; Hong, Wei

2018-03-15

Leakage is the most important failure mode in aircraft hydraulic systems caused by wear and tear between friction pairs of components. The accurate detection of abrasive debris can reveal the wear condition and predict a system's lifespan. The radial magnetic field (RMF)-based debris detection method provides an online solution for monitoring the wear condition intuitively, which potentially enables a more accurate diagnosis and prognosis on the aviation hydraulic system's ongoing failures. To address the serious mixing of pipe abrasive debris, this paper focuses on the superimposed abrasive debris separation of an RMF abrasive sensor based on the degenerate unmixing estimation technique. Through accurately separating and calculating the morphology and amount of the abrasive debris, the RMF-based abrasive sensor can provide the system with wear trend and sizes estimation of the wear particles. A well-designed experiment was conducted and the result shows that the proposed method can effectively separate the mixed debris and give an accurate count of the debris based on RMF abrasive sensor detection.

New early warning system for gravity-driven ruptures based on codetection of acoustic signal

NASA Astrophysics Data System (ADS)

Faillettaz, J.

2016-12-01

Gravity-driven rupture phenomena in natural media - e.g. landslide, rockfalls, snow or ice avalanches - represent an important class of natural hazards in mountainous regions. To protect the population against such events, a timely evacuation often constitutes the only effective way to secure the potentially endangered area. However, reliable prediction of imminence of such failure events remains challenging due to the nonlinear and complex nature of geological material failure hampered by inherent heterogeneity, unknown initial mechanical state, and complex load application (rainfall, temperature, etc.). Here, a simple method for real-time early warning that considers both the heterogeneity of natural media and characteristics of acoustic emissions attenuation is proposed. This new method capitalizes on codetection of elastic waves emanating from microcracks by multiple and spatially separated sensors. Event-codetection is considered as surrogate for large event size with more frequent codetected events (i.e., detected concurrently on more than one sensor) marking imminence of catastrophic failure. Simple numerical model based on a Fiber Bundle Model considering signal attenuation and hypothetical arrays of sensors confirms the early warning potential of codetection principles. Results suggest that although statistical properties of attenuated signal amplitude could lead to misleading results, monitoring the emergence of large events announcing impeding failure is possible even with attenuated signals depending on sensor network geometry and detection threshold. Preliminary application of the proposed method to acoustic emissions during failure of snow samples has confirmed the potential use of codetection as indicator for imminent failure at lab scale. The applicability of such simple and cheap early warning system is now investigated at a larger scale (hillslope). First results of such a pilot field experiment are presented and analysed.

Dynamic Leading-Edge Stagnation Point Determination Utilizing an Array of Hot-Film Sensors with Unknown Calibration

NASA Technical Reports Server (NTRS)

Ellsworth, Joel C.

2017-01-01

During flight-testing of the National Aeronautics and Space Administration (NASA) Gulfstream III (G-III) airplane (Gulfstream Aerospace Corporation, Savannah, Georgia) SubsoniC Research Aircraft Testbed (SCRAT) between March 2013 and April 2015 it became evident that the sensor array used for stagnation point detection was not functioning as expected. The stagnation point detection system is a self calibrating hot-film array; the calibration was unknown and varied between flights, however, the channel with the lowest power consumption was expected to correspond with the point of least surface shear. While individual channels showed the expected behavior for the hot-film sensors, more often than not the lowest power consumption occurred at a single sensor (despite in-flight maneuvering) in the array located far from the expected stagnation point. An algorithm was developed to process the available system output and determine the stagnation point location. After multiple updates and refinements, the final algorithm was not sensitive to the failure of a single sensor in the array, but adjacent failures beneath the stagnation point crippled the algorithm.

Development of three-axis inkjet printer for gear sensors

NASA Astrophysics Data System (ADS)

Iba, Daisuke; Rodriguez Lopez, Ricardo; Kamimoto, Takahiro; Nakamura, Morimasa; Miura, Nanako; Iizuka, Takashi; Masuda, Arata; Moriwaki, Ichiro; Sone, Akira

2016-04-01

The long-term objective of our research is to develop sensor systems for detection of gear failure signs. As a very first step, this paper proposes a new method to create sensors directly printed on gears by a printer and conductive ink, and shows the printing system configuration and the procedure of sensor development. The developing printer system is a laser sintering system consisting of a laser and CNC machinery. The laser is able to synthesize micro conductive patterns, and introduced to the CNC machinery as a tool. In order to synthesize sensors on gears, we first design the micro-circuit pattern on a gear through the use of 3D-CAD, and create a program (G-code) for the CNC machinery by CAM. This paper shows initial experiments with the laser sintering process in order to obtain the optimal parameters for the laser setting. This new method proposed here may provide a new manufacturing process for mechanical parts, which have an additional functionality to detect failure, and possible improvements include creating more economical and sustainable systems.

An Efficient Distributed Coverage Hole Detection Protocol for Wireless Sensor Networks.

PubMed

Sahoo, Prasan Kumar; Chiang, Ming-Jer; Wu, Shih-Lin

2016-03-17

In wireless sensor networks (WSNs), certain areas of the monitoring region may have coverage holes and serious coverage overlapping due to the random deployment of sensors. The failure of electronic components, software bugs and destructive agents could lead to the random death of the nodes. Sensors may be dead due to exhaustion of battery power, which may cause the network to be uncovered and disconnected. Based on the deployment nature of the nodes in remote or hostile environments, such as a battlefield or desert, it is impossible to recharge or replace the battery. However, the data gathered by the sensors are highly essential for the analysis, and therefore, the collaborative detection of coverage holes has strategic importance in WSNs. In this paper, distributed coverage hole detection algorithms are designed, where nodes can collaborate to detect the coverage holes autonomously. The performance evaluation of our protocols suggests that our protocols outperform in terms of hole detection time, limited power consumption and control packet overhead to detect holes as compared to other similar protocols.

Model-Based Method for Sensor Validation

NASA Technical Reports Server (NTRS)

Vatan, Farrokh

2012-01-01

Fault detection, diagnosis, and prognosis are essential tasks in the operation of autonomous spacecraft, instruments, and in situ platforms. One of NASA s key mission requirements is robust state estimation. Sensing, using a wide range of sensors and sensor fusion approaches, plays a central role in robust state estimation, and there is a need to diagnose sensor failure as well as component failure. Sensor validation can be considered to be part of the larger effort of improving reliability and safety. The standard methods for solving the sensor validation problem are based on probabilistic analysis of the system, from which the method based on Bayesian networks is most popular. Therefore, these methods can only predict the most probable faulty sensors, which are subject to the initial probabilities defined for the failures. The method developed in this work is based on a model-based approach and provides the faulty sensors (if any), which can be logically inferred from the model of the system and the sensor readings (observations). The method is also more suitable for the systems when it is hard, or even impossible, to find the probability functions of the system. The method starts by a new mathematical description of the problem and develops a very efficient and systematic algorithm for its solution. The method builds on the concepts of analytical redundant relations (ARRs).

Learning to Classify with Possible Sensor Failures

DTIC Science & Technology

2014-05-04

SVMs), have demonstrated good classification performance when the training data is representative of the test data [1, 2, 3]. However, in many real...Detection of people and animals using non- imaging sensors,” Information Fusion (FUSION), 2011 Proceedings of the 14th International Conference on, pp...classification methods in terms of both classification accuracy and anomaly detection rate using 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND SUBTITLE 13

Real-time diagnostics of the reusable rocket engine using on-line system identification

NASA Technical Reports Server (NTRS)

Guo, T.-H.; Merrill, W.; Duyar, A.

1990-01-01

A model-based failure diagnosis system has been proposed for real-time diagnosis of SSME failures. Actuation, sensor, and system degradation failure modes are all considered by the proposed system. In the case of SSME actuation failures, it was shown that real-time identification can effectively be used for failure diagnosis purposes. It is a direct approach since it reduces the detection, isolation, and the estimation of the extent of the failures to the comparison of parameter values before and after the failure. As with any model-based failure detection system, the proposed approach requires a fault model that embodies the essential characteristics of the failure process. The proposed diagnosis approach has the added advantage that it can be used as part of an intelligent control system for failure accommodation purposes.

Note: Durability analysis of optical fiber hydrogen sensor based on Pd-Y alloy film.

PubMed

Huang, Peng-cheng; Chen, You-ping; Zhang, Gang; Song, Han; Liu, Yi

2016-02-01

The Pd-Y alloy sensing film has an excellent property for hydrogen detection, but just for one month, the sensing film's property decreases seriously. To study the failure of the sensing film, the XPS spectra analysis was used to explore the chemical content of the Pd-Y alloy film, and analysis results demonstrate that the yttrium was oxidized. The paper presented that such an oxidized process was the potential reason of the failure of the sensing film. By understanding the reason of the failure of the sensing film better, we could improve the manufacturing process to enhance the property of hydrogen sensor.

A new debris sensor based on dual excitation sources for online debris monitoring

NASA Astrophysics Data System (ADS)

Hong, Wei; Wang, Shaoping; Tomovic, Mileta M.; Liu, Haokuo; Wang, Xingjian

2015-09-01

Mechanical systems could be severely damaged by loose debris generated through wear processes between contact surfaces. Hence, debris detection is necessary for effective fault diagnosis, life prediction, and prevention of catastrophic failures. This paper presents a new in-line debris sensor for hydraulic systems based on dual excitation sources. The proposed sensor makes magnetic lines more concentrated while at the same time improving magnetic field uniformity. As a result the sensor has higher sensitivity and improved precision. This paper develops the sensor model, discusses sensor structural features, and introduces a measurement method for debris size identification. Finally, experimental verification is presented indicating that that the sensor can effectively detect 81 μm (cube) or larger particles in 12 mm outside diameter (OD) organic glass pipe.

Conductive ink print on PA66 gear for manufacturing condition monitoring sensors

NASA Astrophysics Data System (ADS)

Futagawa, Shintaro; Iba, Daisuke; Kamimoto, Takahiro; Nakamura, Morimasa; Miura, Nanako; Iizuka, Takashi; Masuda, Arata; Sone, Akira; Moriwaki, Ichiro

2018-03-01

Failures detection of rotating machine elements, such as gears, is an important issue. The purpose of this study was to try to solve this issue by printing conductive ink on gears to manufacture condition-monitoring sensors. In this work, three types of crack detection sensor were designed and the sprayed conductive ink was directly sintered on polyimide (PI) - coated polyamide (PA) 66 gears by laser. The result showed that it was possible to produce narrow circuit lines of the conductive ink including Ag by laser sintering technique and the complex shape sensors on the lateral side of the PA66 gears, module 1.0 mm and tooth number 48. A preliminary operation test was carried out for investigation of the function of the sensors. As a result of the test, the sensors printed in this work should be effective for detecting cracks at tooth root of the gears and will allow for the development of better equipment and detection techniques for health monitoring of gears.

Sensor Data Quality and Angular Rate Down-Selection Algorithms on SLS EM-1

NASA Technical Reports Server (NTRS)

Park, Thomas; Smith, Austin; Oliver, T. Emerson

2018-01-01

The NASA Space Launch System Block 1 launch vehicle is equipped with an Inertial Navigation System (INS) and multiple Rate Gyro Assemblies (RGA) that are used in the Guidance, Navigation, and Control (GN&C) algorithms. The INS provides the inertial position, velocity, and attitude of the vehicle along with both angular rate and specific force measurements. Additionally, multiple sets of co-located rate gyros supply angular rate data. The collection of angular rate data, taken along the launch vehicle, is used to separate out vehicle motion from flexible body dynamics. Since the system architecture uses redundant sensors, the capability was developed to evaluate the health (or validity) of the independent measurements. A suite of Sensor Data Quality (SDQ) algorithms is responsible for assessing the angular rate data from the redundant sensors. When failures are detected, SDQ will take the appropriate action and disqualify or remove faulted sensors from forward processing. Additionally, the SDQ algorithms contain logic for down-selecting the angular rate data used by the GNC software from the set of healthy measurements. This paper explores the trades and analyses that were performed in selecting a set of robust fault-detection algorithms included in the GN&C flight software. These trades included both an assessment of hardware-provided health and status data as well as an evaluation of different algorithms based on time-to-detection, type of failures detected, and probability of detecting false positives. We then provide an overview of the algorithms used for both fault-detection and measurement down selection. We next discuss the role of trajectory design, flexible-body models, and vehicle response to off-nominal conditions in setting the detection thresholds. Lastly, we present lessons learned from software integration and hardware-in-the-loop testing.

Fault detection and diagnosis using neural network approaches

NASA Technical Reports Server (NTRS)

Kramer, Mark A.

1992-01-01

Neural networks can be used to detect and identify abnormalities in real-time process data. Two basic approaches can be used, the first based on training networks using data representing both normal and abnormal modes of process behavior, and the second based on statistical characterization of the normal mode only. Given data representative of process faults, radial basis function networks can effectively identify failures. This approach is often limited by the lack of fault data, but can be facilitated by process simulation. The second approach employs elliptical and radial basis function neural networks and other models to learn the statistical distributions of process observables under normal conditions. Analytical models of failure modes can then be applied in combination with the neural network models to identify faults. Special methods can be applied to compensate for sensor failures, to produce real-time estimation of missing or failed sensors based on the correlations codified in the neural network.

Effective Sensor Selection and Data Anomaly Detection for Condition Monitoring of Aircraft Engines

PubMed Central

Liu, Liansheng; Liu, Datong; Zhang, Yujie; Peng, Yu

2016-01-01

In a complex system, condition monitoring (CM) can collect the system working status. The condition is mainly sensed by the pre-deployed sensors in/on the system. Most existing works study how to utilize the condition information to predict the upcoming anomalies, faults, or failures. There is also some research which focuses on the faults or anomalies of the sensing element (i.e., sensor) to enhance the system reliability. However, existing approaches ignore the correlation between sensor selecting strategy and data anomaly detection, which can also improve the system reliability. To address this issue, we study a new scheme which includes sensor selection strategy and data anomaly detection by utilizing information theory and Gaussian Process Regression (GPR). The sensors that are more appropriate for the system CM are first selected. Then, mutual information is utilized to weight the correlation among different sensors. The anomaly detection is carried out by using the correlation of sensor data. The sensor data sets that are utilized to carry out the evaluation are provided by National Aeronautics and Space Administration (NASA) Ames Research Center and have been used as Prognostics and Health Management (PHM) challenge data in 2008. By comparing the two different sensor selection strategies, the effectiveness of selection method on data anomaly detection is proved. PMID:27136561

Effective Sensor Selection and Data Anomaly Detection for Condition Monitoring of Aircraft Engines.

PubMed

Liu, Liansheng; Liu, Datong; Zhang, Yujie; Peng, Yu

2016-04-29

In a complex system, condition monitoring (CM) can collect the system working status. The condition is mainly sensed by the pre-deployed sensors in/on the system. Most existing works study how to utilize the condition information to predict the upcoming anomalies, faults, or failures. There is also some research which focuses on the faults or anomalies of the sensing element (i.e., sensor) to enhance the system reliability. However, existing approaches ignore the correlation between sensor selecting strategy and data anomaly detection, which can also improve the system reliability. To address this issue, we study a new scheme which includes sensor selection strategy and data anomaly detection by utilizing information theory and Gaussian Process Regression (GPR). The sensors that are more appropriate for the system CM are first selected. Then, mutual information is utilized to weight the correlation among different sensors. The anomaly detection is carried out by using the correlation of sensor data. The sensor data sets that are utilized to carry out the evaluation are provided by National Aeronautics and Space Administration (NASA) Ames Research Center and have been used as Prognostics and Health Management (PHM) challenge data in 2008. By comparing the two different sensor selection strategies, the effectiveness of selection method on data anomaly detection is proved.

40 CFR 60.482-3a - Standards: Compressors.

Code of Federal Regulations, 2013 CFR

2013-07-01

... of VOC in the Synthetic Organic Chemicals Manufacturing Industry for Which Construction... equipped with a sensor that will detect failure of the seal system, barrier fluid system, or both. (e)(1) Each sensor as required in paragraph (d) of this section shall be checked daily or shall be equipped...

40 CFR 60.482-3 - Standards: Compressors.

Code of Federal Regulations, 2012 CFR

2012-07-01

... of VOC in the Synthetic Organic Chemicals Manufacturing Industry for which Construction... be equipped with a sensor that will detect failure of the seal system, barrier fluid system, or both. (e)(1) Each sensor as required in paragraph (d) shall be checked daily or shall be equipped with an...

40 CFR 60.482-3 - Standards: Compressors.

Code of Federal Regulations, 2013 CFR

2013-07-01

... of VOC in the Synthetic Organic Chemicals Manufacturing Industry for which Construction... be equipped with a sensor that will detect failure of the seal system, barrier fluid system, or both. (e)(1) Each sensor as required in paragraph (d) shall be checked daily or shall be equipped with an...

40 CFR 60.482-3a - Standards: Compressors.

Code of Federal Regulations, 2014 CFR

2014-07-01

... of VOC in the Synthetic Organic Chemicals Manufacturing Industry for Which Construction... equipped with a sensor that will detect failure of the seal system, barrier fluid system, or both. (e)(1) Each sensor as required in paragraph (d) of this section shall be checked daily or shall be equipped...

40 CFR 60.482-3 - Standards: Compressors.

Code of Federal Regulations, 2014 CFR

2014-07-01

... of VOC in the Synthetic Organic Chemicals Manufacturing Industry for which Construction... be equipped with a sensor that will detect failure of the seal system, barrier fluid system, or both. (e)(1) Each sensor as required in paragraph (d) shall be checked daily or shall be equipped with an...

On-Board Particulate Filter Failure Prevention and Failure Diagnostics Using Radio Frequency Sensing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sappok, Alex; Ragaller, Paul; Herman, Andrew

The increasing use of diesel and gasoline particulate filters requires advanced on-board diagnostics (OBD) to prevent and detect filter failures and malfunctions. Early detection of upstream (engine-out) malfunctions is paramount to preventing irreversible damage to downstream aftertreatment system components. Such early detection can mitigate the failure of the particulate filter resulting in the escape of emissions exceeding permissible limits and extend the component life. However, despite best efforts at early detection and filter failure prevention, the OBD system must also be able to detect filter failures when they occur. In this study, radio frequency (RF) sensors were used to directlymore » monitor the particulate filter state of health for both gasoline particulate filter (GPF) and diesel particulate filter (DPF) applications. The testing included controlled engine dynamometer evaluations, which characterized soot slip from various filter failure modes, as well as on-road fleet vehicle tests. The results show a high sensitivity to detect conditions resulting in soot leakage from the particulate filter, as well as potential for direct detection of structural failures including internal cracks and melted regions within the filter media itself. Furthermore, the measurements demonstrate, for the first time, the capability to employ a direct and continuous monitor of particulate filter diagnostics to both prevent and detect potential failure conditions in the field.« less

Using Wireless Sensor Networks in Improvised Explosive Device Detection

DTIC Science & Technology

2007-12-01

data collection (permitting self - healing when a node failure occurs); Sensor nodes Gateway nodes 24 • Energy efficiency (necessary to maintain...Runner” robotic platform (see Figure 1). It is reported that this system can detect a wide range of IEDs, even those concealed in vehicles. However...be as simple as running over a rubber hose to produce enough air pressure to activate a switch. Some IEDs have been remotely detonated with radio

Fault detection and diagnosis in a spacecraft attitude determination system

NASA Astrophysics Data System (ADS)

Pirmoradi, F. N.; Sassani, F.; de Silva, C. W.

2009-09-01

This paper presents a new scheme for fault detection and diagnosis (FDD) in spacecraft attitude determination (AD) sensors. An integrated attitude determination system, which includes measurements of rate and angular position using rate gyros and vector sensors, is developed. Measurement data from all sensors are fused by a linearized Kalman filter, which is designed based on the system kinematics, to provide attitude estimation and the values of the gyro bias. Using this information the erroneous sensor measurements are corrected, and unbounded sensor measurement errors are avoided. The resulting bias-free data are used in the FDD scheme. The FDD algorithm uses model-based state estimation, combining the information from the rotational dynamics and kinematics of a spacecraft with the sensor measurements to predict the future sensor outputs. Fault isolation is performed through extended Kalman filters (EKFs). The innovation sequences of EKFs are monitored by several statistical tests to detect the presence of a failure and to localize the failures in all AD sensors. The isolation procedure is developed in two phases. In the first phase, two EKFs are designed, which use subsets of measurements to provide state estimates and form residuals, which are used to verify the source of the fault. In the second phase of isolation, testing of multiple hypotheses is performed. The generalized likelihood ratio test is utilized to identify the faulty components. In the scheme developed in this paper a relatively small number of hypotheses is used, which results in faster isolation and highly distinguishable fault signatures. An important feature of the developed FDD scheme is that it can provide attitude estimations even if only one type of sensors is functioning properly.

Micro-encapsulated sensors for in vivo assessment of the oxidative stress in aquatic organisms

NASA Astrophysics Data System (ADS)

Sadovoy, Anton; Teh, Cathleen; Escobar, Marco; Meglinski, Igor; Korzh, Vladimir

2011-10-01

Oxidative stress results from an imbalance between the production and detoxification of reactive oxygen spices (ROS). ROS are natural byproducts of normal metabolism of oxygen and have important roles in cell signaling and homeostasis. Many heart related diseases like heart failure and myocardial infarction develop as a result of oxidative stress. Current treatment cannot improve the progressive decline in heart function experienced by all patients. Therefore heart failure is the cause of around 25% of all deaths in the Asia Pacific region. Thus any step taken to address the oxidative stress problem is essential for enhancing human health and improve their quality of life. Current approach is dedicated to develop micron-size oxidation stress-sensor for in-vivo measuring level of ROS in KillerRed expressing transgenic zebrafish larvae. Central to our investigation is the light-inducible heart failure animal model we developed in zebrafish that expressed KillerRed in the heart. By utilizing the photosensitizer properties of KillerRed to produce ROS upon green light illumination, heart failure can be repeatedly induced in a non-invasive manner. Importantly, the use of this biological platform permits the development of physiologically sensitive ROS sensor and identifies efficient antioxidants that improve heart contractility. The biosensor approach is based on utilizing biocompatible polyelectrolyte microcapsules as a carry of fluorescent dyes sensitive to amount of reactive oxygen spices. Microcapsule prevents dye diffusion in tissue that makes use toxic dyes possible. Microcapsule's wall is permeable for environment with size less than 500 Da. The oxidation stress-sensors are injected directly in zebrafish pericardium with further circulation along blood system. Detecting of ROS is obtained by using laser scanning microscopy by illuminating oxidation stress-sensors and detecting changing excitation signal from the fluorescent dye.

Micro-encapsulated sensors for in vivo assessment of the oxidative stress in aquatic organisms

NASA Astrophysics Data System (ADS)

Sadovoy, Anton; Teh, Cathleen; Escobar, Marco; Meglinski, Igor; Korzh, Vladimir

2012-03-01

Oxidative stress results from an imbalance between the production and detoxification of reactive oxygen spices (ROS). ROS are natural byproducts of normal metabolism of oxygen and have important roles in cell signaling and homeostasis. Many heart related diseases like heart failure and myocardial infarction develop as a result of oxidative stress. Current treatment cannot improve the progressive decline in heart function experienced by all patients. Therefore heart failure is the cause of around 25% of all deaths in the Asia Pacific region. Thus any step taken to address the oxidative stress problem is essential for enhancing human health and improve their quality of life. Current approach is dedicated to develop micron-size oxidation stress-sensor for in-vivo measuring level of ROS in KillerRed expressing transgenic zebrafish larvae. Central to our investigation is the light-inducible heart failure animal model we developed in zebrafish that expressed KillerRed in the heart. By utilizing the photosensitizer properties of KillerRed to produce ROS upon green light illumination, heart failure can be repeatedly induced in a non-invasive manner. Importantly, the use of this biological platform permits the development of physiologically sensitive ROS sensor and identifies efficient antioxidants that improve heart contractility. The biosensor approach is based on utilizing biocompatible polyelectrolyte microcapsules as a carry of fluorescent dyes sensitive to amount of reactive oxygen spices. Microcapsule prevents dye diffusion in tissue that makes use toxic dyes possible. Microcapsule's wall is permeable for environment with size less than 500 Da. The oxidation stress-sensors are injected directly in zebrafish pericardium with further circulation along blood system. Detecting of ROS is obtained by using laser scanning microscopy by illuminating oxidation stress-sensors and detecting changing excitation signal from the fluorescent dye.

A definitional framework for the human/biometric sensor interaction model

NASA Astrophysics Data System (ADS)

Elliott, Stephen J.; Kukula, Eric P.

2010-04-01

Existing definitions for biometric testing and evaluation do not fully explain errors in a biometric system. This paper provides a definitional framework for the Human Biometric-Sensor Interaction (HBSI) model. This paper proposes six new definitions based around two classifications of presentations, erroneous and correct. The new terms are: defective interaction (DI), concealed interaction (CI), false interaction (FI), failure to detect (FTD), failure to extract (FTX), and successfully acquired samples (SAS). As with all definitions, the new terms require a modification to the general biometric model developed by Mansfield and Wayman [1].

Integral Sensor Fault Detection and Isolation for Railway Traction Drive.

PubMed

Garramiola, Fernando; Del Olmo, Jon; Poza, Javier; Madina, Patxi; Almandoz, Gaizka

2018-05-13

Due to the increasing importance of reliability and availability of electric traction drives in Railway applications, early detection of faults has become an important key for Railway traction drive manufacturers. Sensor faults are important sources of failures. Among the different fault diagnosis approaches, in this article an integral diagnosis strategy for sensors in traction drives is presented. Such strategy is composed of an observer-based approach for direct current (DC)-link voltage and catenary current sensors, a frequency analysis approach for motor current phase sensors and a hardware redundancy solution for speed sensors. None of them requires any hardware change requirement in the actual traction drive. All the fault detection and isolation approaches have been validated in a Hardware-in-the-loop platform comprising a Real Time Simulator and a commercial Traction Control Unit for a tram. In comparison to safety-critical systems in Aerospace applications, Railway applications do not need instantaneous detection, and the diagnosis is validated in a short time period for reliable decision. Combining the different approaches and existing hardware redundancy, an integral fault diagnosis solution is provided, to detect and isolate faults in all the sensors installed in the traction drive.

Integral Sensor Fault Detection and Isolation for Railway Traction Drive

PubMed Central

del Olmo, Jon; Poza, Javier; Madina, Patxi; Almandoz, Gaizka

2018-01-01

Due to the increasing importance of reliability and availability of electric traction drives in Railway applications, early detection of faults has become an important key for Railway traction drive manufacturers. Sensor faults are important sources of failures. Among the different fault diagnosis approaches, in this article an integral diagnosis strategy for sensors in traction drives is presented. Such strategy is composed of an observer-based approach for direct current (DC)-link voltage and catenary current sensors, a frequency analysis approach for motor current phase sensors and a hardware redundancy solution for speed sensors. None of them requires any hardware change requirement in the actual traction drive. All the fault detection and isolation approaches have been validated in a Hardware-in-the-loop platform comprising a Real Time Simulator and a commercial Traction Control Unit for a tram. In comparison to safety-critical systems in Aerospace applications, Railway applications do not need instantaneous detection, and the diagnosis is validated in a short time period for reliable decision. Combining the different approaches and existing hardware redundancy, an integral fault diagnosis solution is provided, to detect and isolate faults in all the sensors installed in the traction drive. PMID:29757251

An Efficient Distributed Coverage Hole Detection Protocol for Wireless Sensor Networks

PubMed Central

Kumar Sahoo, Prasan; Chiang, Ming-Jer; Wu, Shih-Lin

2016-01-01

In wireless sensor networks (WSNs), certain areas of the monitoring region may have coverage holes and serious coverage overlapping due to the random deployment of sensors. The failure of electronic components, software bugs and destructive agents could lead to the random death of the nodes. Sensors may be dead due to exhaustion of battery power, which may cause the network to be uncovered and disconnected. Based on the deployment nature of the nodes in remote or hostile environments, such as a battlefield or desert, it is impossible to recharge or replace the battery. However, the data gathered by the sensors are highly essential for the analysis, and therefore, the collaborative detection of coverage holes has strategic importance in WSNs. In this paper, distributed coverage hole detection algorithms are designed, where nodes can collaborate to detect the coverage holes autonomously. The performance evaluation of our protocols suggests that our protocols outperform in terms of hole detection time, limited power consumption and control packet overhead to detect holes as compared to other similar protocols. PMID:26999143

Aliasing Signal Separation of Superimposed Abrasive Debris Based on Degenerate Unmixing Estimation Technique

PubMed Central

Li, Tongyang; Wang, Shaoping; Zio, Enrico; Shi, Jian; Hong, Wei

2018-01-01

Leakage is the most important failure mode in aircraft hydraulic systems caused by wear and tear between friction pairs of components. The accurate detection of abrasive debris can reveal the wear condition and predict a system’s lifespan. The radial magnetic field (RMF)-based debris detection method provides an online solution for monitoring the wear condition intuitively, which potentially enables a more accurate diagnosis and prognosis on the aviation hydraulic system’s ongoing failures. To address the serious mixing of pipe abrasive debris, this paper focuses on the superimposed abrasive debris separation of an RMF abrasive sensor based on the degenerate unmixing estimation technique. Through accurately separating and calculating the morphology and amount of the abrasive debris, the RMF-based abrasive sensor can provide the system with wear trend and sizes estimation of the wear particles. A well-designed experiment was conducted and the result shows that the proposed method can effectively separate the mixed debris and give an accurate count of the debris based on RMF abrasive sensor detection. PMID:29543733

40 CFR 61.242-3 - Standards: Compressors.

Code of Federal Regulations, 2010 CFR

2010-07-01

... barrier fluid system degassing reservoir that is routed to a process or fuel gas system or connected by a... paragraphs (a)-(c) of this section shall be equipped with a sensor that will detect failure of the seal system, barrier fluid system, or both. (e)(1) Each sensor as required in paragraph (d) of this section...

40 CFR 60.482-3a - Standards: Compressors.

Code of Federal Regulations, 2010 CFR

2010-07-01

... (2) Equipped with a barrier fluid system degassing reservoir that is routed to a process or fuel gas... equipped with a sensor that will detect failure of the seal system, barrier fluid system, or both. (e)(1) Each sensor as required in paragraph (d) of this section shall be checked daily or shall be equipped...

40 CFR 65.112 - Standards: Compressors.

Code of Federal Regulations, 2010 CFR

2010-07-01

... fuel gas system, or connected by a closed vent system to a control device that meets the requirements... barrier fluid system shall be equipped with a sensor that will detect failure of the seal system, barrier fluid system, or both. Each sensor shall be observed daily or shall be equipped with an alarm unless the...

40 CFR 61.242-3 - Standards: Compressors.

Code of Federal Regulations, 2011 CFR

2011-07-01

... barrier fluid system degassing reservoir that is routed to a process or fuel gas system or connected by a... paragraphs (a)-(c) of this section shall be equipped with a sensor that will detect failure of the seal system, barrier fluid system, or both. (e)(1) Each sensor as required in paragraph (d) of this section...

40 CFR 63.1031 - Compressors standards.

Code of Federal Regulations, 2011 CFR

2011-07-01

... gas system or connected by a closed-vent system to a control device that meets the requirements of... service. Each barrier fluid system shall be equipped with a sensor that will detect failure of the seal system, barrier fluid system, or both. Each sensor shall be observed daily or shall be equipped with an...

40 CFR 65.112 - Standards: Compressors.

Code of Federal Regulations, 2011 CFR

2011-07-01

... fuel gas system, or connected by a closed vent system to a control device that meets the requirements... barrier fluid system shall be equipped with a sensor that will detect failure of the seal system, barrier fluid system, or both. Each sensor shall be observed daily or shall be equipped with an alarm unless the...

40 CFR 63.1031 - Compressors standards.

Code of Federal Regulations, 2010 CFR

2010-07-01

... gas system or connected by a closed-vent system to a control device that meets the requirements of... service. Each barrier fluid system shall be equipped with a sensor that will detect failure of the seal system, barrier fluid system, or both. Each sensor shall be observed daily or shall be equipped with an...

40 CFR 60.482-3a - Standards: Compressors.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (2) Equipped with a barrier fluid system degassing reservoir that is routed to a process or fuel gas... equipped with a sensor that will detect failure of the seal system, barrier fluid system, or both. (e)(1) Each sensor as required in paragraph (d) of this section shall be checked daily or shall be equipped...

Development of a Distributed Crack Sensor Using Coaxial Cable.

PubMed

Zhou, Zhi; Jiao, Tong; Zhao, Peng; Liu, Jia; Xiao, Hai

2016-07-29

Cracks, the important factor of structure failure, reflect structural damage directly. Thus, it is significant to realize distributed, real-time crack monitoring. To overcome the shortages of traditional crack detectors, such as the inconvenience of installation, vulnerability, and low measurement range, etc., an improved topology-based cable sensor with a shallow helical groove on the outside surface of a coaxial cable is proposed in this paper. The sensing mechanism, fabrication method, and performances are investigated both numerically and experimentally. Crack monitoring experiments of the reinforced beams are also presented in this paper, illustrating the utility of this sensor in practical applications. These studies show that the sensor can identify a minimum crack width of 0.02 mm and can measure multiple cracks with a spatial resolution of 3 mm. In addition, it is also proved that the sensor performs well to detect the initiation and development of cracks until structure failure.

Development of a Distributed Crack Sensor Using Coaxial Cable

PubMed Central

Zhou, Zhi; Jiao, Tong; Zhao, Peng; Liu, Jia; Xiao, Hai

2016-01-01

Cracks, the important factor of structure failure, reflect structural damage directly. Thus, it is significant to realize distributed, real-time crack monitoring. To overcome the shortages of traditional crack detectors, such as the inconvenience of installation, vulnerability, and low measurement range, etc., an improved topology-based cable sensor with a shallow helical groove on the outside surface of a coaxial cable is proposed in this paper. The sensing mechanism, fabrication method, and performances are investigated both numerically and experimentally. Crack monitoring experiments of the reinforced beams are also presented in this paper, illustrating the utility of this sensor in practical applications. These studies show that the sensor can identify a minimum crack width of 0.02 mm and can measure multiple cracks with a spatial resolution of 3 mm. In addition, it is also proved that the sensor performs well to detect the initiation and development of cracks until structure failure. PMID:27483280

Design and evaluation of a failure detection and isolation algorithm for restructurable control systems

NASA Technical Reports Server (NTRS)

Weiss, Jerold L.; Hsu, John Y.

1986-01-01

The use of a decentralized approach to failure detection and isolation for use in restructurable control systems is examined. This work has produced: (1) A method for evaluating fundamental limits to FDI performance; (2) Application using flight recorded data; (3) A working control element FDI system with maximal sensitivity to critical control element failures; (4) Extensive testing on realistic simulations; and (5) A detailed design methodology involving parameter optimization (with respect to model uncertainties) and sensitivity analyses. This project has concentrated on detection and isolation of generic control element failures since these failures frequently lead to emergency conditions and since knowledge of remaining control authority is essential for control system redesign. The failures are generic in the sense that no temporal failure signature information was assumed. Thus, various forms of functional failures are treated in a unified fashion. Such a treatment results in a robust FDI system (i.e., one that covers all failure modes) but sacrifices some performance when detailed failure signature information is known, useful, and employed properly. It was assumed throughout that all sensors are validated (i.e., contain only in-spec errors) and that only the first failure of a single control element needs to be detected and isolated. The FDI system which has been developed will handle a class of multiple failures.

An Autonomous Self-Aware and Adaptive Fault Tolerant Routing Technique for Wireless Sensor Networks

PubMed Central

Abba, Sani; Lee, Jeong-A

2015-01-01

We propose an autonomous self-aware and adaptive fault-tolerant routing technique (ASAART) for wireless sensor networks. We address the limitations of self-healing routing (SHR) and self-selective routing (SSR) techniques for routing sensor data. We also examine the integration of autonomic self-aware and adaptive fault detection and resiliency techniques for route formation and route repair to provide resilience to errors and failures. We achieved this by using a combined continuous and slotted prioritized transmission back-off delay to obtain local and global network state information, as well as multiple random functions for attaining faster routing convergence and reliable route repair despite transient and permanent node failure rates and efficient adaptation to instantaneous network topology changes. The results of simulations based on a comparison of the ASAART with the SHR and SSR protocols for five different simulated scenarios in the presence of transient and permanent node failure rates exhibit a greater resiliency to errors and failure and better routing performance in terms of the number of successfully delivered network packets, end-to-end delay, delivered MAC layer packets, packet error rate, as well as efficient energy conservation in a highly congested, faulty, and scalable sensor network. PMID:26295236

An Autonomous Self-Aware and Adaptive Fault Tolerant Routing Technique for Wireless Sensor Networks.

PubMed

Abba, Sani; Lee, Jeong-A

2015-08-18

We propose an autonomous self-aware and adaptive fault-tolerant routing technique (ASAART) for wireless sensor networks. We address the limitations of self-healing routing (SHR) and self-selective routing (SSR) techniques for routing sensor data. We also examine the integration of autonomic self-aware and adaptive fault detection and resiliency techniques for route formation and route repair to provide resilience to errors and failures. We achieved this by using a combined continuous and slotted prioritized transmission back-off delay to obtain local and global network state information, as well as multiple random functions for attaining faster routing convergence and reliable route repair despite transient and permanent node failure rates and efficient adaptation to instantaneous network topology changes. The results of simulations based on a comparison of the ASAART with the SHR and SSR protocols for five different simulated scenarios in the presence of transient and permanent node failure rates exhibit a greater resiliency to errors and failure and better routing performance in terms of the number of successfully delivered network packets, end-to-end delay, delivered MAC layer packets, packet error rate, as well as efficient energy conservation in a highly congested, faulty, and scalable sensor network.

Embedded Bragg grating fiber optic sensor for composite flexbeams

NASA Astrophysics Data System (ADS)

Bullock, Daniel; Dunphy, James; Hufstetler, Gerard

1993-03-01

An embedded fiber-optic (F-O) sensor has been developed for translaminar monitoring of the structural integrity of composites, with a view to application in composite helicopter flexbeams for bearingless main rotor hubs. This through-thickness strain sensor is much more sensitive than conventional in-plane embedded F-O sensors to ply delamination, on the basis of a novel insertion technique and innovative Bragg grating sensor. Experimental trials have demonstrated the detection by this means of potential failures in advance of the edge-delamination or crack-propagation effect.

A high sensitivity wear debris sensor using ferrite cores for online oil condition monitoring

NASA Astrophysics Data System (ADS)

Zhu, Xiaoliang; Zhong, Chong; Zhe, Jiang

2017-07-01

Detecting wear debris and measuring the increasing number of wear debris in lubrication oil can indicate abnormal machine wear well ahead of machine failure, and thus are indispensable for online machine health monitoring. A portable wear debris sensor with ferrite cores for online monitoring is presented. The sensor detects wear debris by measuring the inductance change of two planar coils wound around a pair of ferrite cores that make the magnetic flux denser and more uniform in the sensing channel, thereby improving the sensitivity of the sensor. Static testing results showed this wear debris sensor is capable of detecting 11 µm and 50 µm ferrous debris in 1 mm and 7 mm diameter fluidic pipes, respectively; such a high sensitivity has not been achieved before. Furthermore, a synchronized sampling method was also applied to reduce the data size and realize real-time data processing. Dynamic testing results demonstrated that the sensor is capable of detecting wear debris in real time with a high throughput of 750 ml min-1 the measured debris concentration is in good agreement with the actual concentration.

Robust failure detection filters. M.S. Thesis

NASA Technical Reports Server (NTRS)

Sanmartin, A. M.

1985-01-01

The robustness of detection filters applied to the detection of actuator failures on a free-free beam is analyzed. This analysis is based on computer simulation tests of the detection filters in the presence of different types of model mismatch, and on frequency response functions of the transfers corresponding to the model mismatch. The robustness of detection filters based on a model of the beam containing a large number of structural modes varied dramatically with the placement of some of the filter poles. The dynamics of these filters were very hard to analyze. The design of detection filters with a number of modes equal to the number of sensors was trivial. They can be configured to detect any number of actuator failure events. The dynamics of these filters were very easy to analyze and their robustness properties were much improved. A change of the output transformation allowed the filter to perform satisfactorily with realistic levels of model mismatch.

Conductometric Sensor for Soot Mass Flow Detection in Exhausts of Internal Combustion Engines

PubMed Central

Feulner, Markus; Hagen, Gunter; Müller, Andreas; Schott, Andreas; Zöllner, Christian; Brüggemann, Dieter; Moos, Ralf

2015-01-01

Soot sensors are required for on-board diagnostics (OBD) of automotive diesel particulate filters (DPF) to detect filter failures. Widely used for this purpose are conductometric sensors, measuring an electrical current or resistance between two electrodes. Soot particles deposit on the electrodes, which leads to an increase in current or decrease in resistance. If installed upstream of a DPF, the “engine-out” soot emissions can also be determined directly by soot sensors. Sensors were characterized in diesel engine real exhausts under varying operation conditions and with two different kinds of diesel fuel. The sensor signal was correlated to the actual soot mass and particle number, measured with an SMPS. Sensor data and soot analytics (SMPS) agreed very well, an impressing linear correlation in a double logarithmic representation was found. This behavior was even independent of the used engine settings or of the biodiesel content. PMID:26580621

Conductometric Sensor for Soot Mass Flow Detection in Exhausts of Internal Combustion Engines.

PubMed

Feulner, Markus; Hagen, Gunter; Müller, Andreas; Schott, Andreas; Zöllner, Christian; Brüggemann, Dieter; Moos, Ralf

2015-11-13

Soot sensors are required for on-board diagnostics (OBD) of automotive diesel particulate filters (DPF) to detect filter failures. Widely used for this purpose are conductometric sensors, measuring an electrical current or resistance between two electrodes. Soot particles deposit on the electrodes, which leads to an increase in current or decrease in resistance. If installed upstream of a DPF, the "engine-out" soot emissions can also be determined directly by soot sensors. Sensors were characterized in diesel engine real exhausts under varying operation conditions and with two different kinds of diesel fuel. The sensor signal was correlated to the actual soot mass and particle number, measured with an SMPS. Sensor data and soot analytics (SMPS) agreed very well, an impressing linear correlation in a double logarithmic representation was found. This behavior was even independent of the used engine settings or of the biodiesel content.

Expert system for online surveillance of nuclear reactor coolant pumps

DOEpatents

Gross, Kenny C.; Singer, Ralph M.; Humenik, Keith E.

1993-01-01

An expert system for online surveillance of nuclear reactor coolant pumps. This system provides a means for early detection of pump or sensor degradation. Degradation is determined through the use of a statistical analysis technique, sequential probability ratio test, applied to information from several sensors which are responsive to differing physical parameters. The results of sequential testing of the data provide the operator with an early warning of possible sensor or pump failure.

Robust detection-isolation-accommodation for sensor failures

NASA Technical Reports Server (NTRS)

Weiss, J. L.; Pattipati, K. R.; Willsky, A. S.; Eterno, J. S.; Crawford, J. T.

1985-01-01

The results of a one year study to: (1) develop a theory for Robust Failure Detection and Identification (FDI) in the presence of model uncertainty, (2) develop a design methodology which utilizes the robust FDI ththeory, (3) apply the methodology to a sensor FDI problem for the F-100 jet engine, and (4) demonstrate the application of the theory to the evaluation of alternative FDI schemes are presented. Theoretical results in statistical discrimination are used to evaluate the robustness of residual signals (or parity relations) in terms of their usefulness for FDI. Furthermore, optimally robust parity relations are derived through the optimization of robustness metrics. The result is viewed as decentralization of the FDI process. A general structure for decentralized FDI is proposed and robustness metrics are used for determining various parameters of the algorithm.

40 CFR 60.482-2 - Standards: Pumps in light liquid service.

Code of Federal Regulations, 2011 CFR

2011-07-01

...; or (ii) Equipped with a barrier fluid degassing reservoir that is routed to a process or fuel gas... in VOC service. (3) Each barrier fluid system is equipped with a sensor that will detect failure of...) Designate the visual indications of liquids dripping as a leak. (5)(i) Each sensor as described in paragraph...

40 CFR 63.164 - Standards: Compressors.

Code of Federal Regulations, 2010 CFR

2010-07-01

... process or fuel gas system or connected by a closed-vent system to a control device that complies with the... with a sensor that will detect failure of the seal system, barrier fluid system, or both. (e)(1) Each sensor as required in paragraph (d) of this section shall be observed daily or shall be equipped with an...

40 CFR 63.164 - Standards: Compressors.

Code of Federal Regulations, 2011 CFR

2011-07-01

... process or fuel gas system or connected by a closed-vent system to a control device that complies with the... with a sensor that will detect failure of the seal system, barrier fluid system, or both. (e)(1) Each sensor as required in paragraph (d) of this section shall be observed daily or shall be equipped with an...

40 CFR 60.482-3 - Standards: Compressors.

Code of Federal Regulations, 2010 CFR

2010-07-01

... process or fuel gas system or connected by a closed vent system to a control device that complies with the... be equipped with a sensor that will detect failure of the seal system, barrier fluid system, or both. (e)(1) Each sensor as required in paragraph (d) shall be checked daily or shall be equipped with an...

40 CFR 60.482-3 - Standards: Compressors.

Code of Federal Regulations, 2011 CFR

2011-07-01

... process or fuel gas system or connected by a closed vent system to a control device that complies with the... be equipped with a sensor that will detect failure of the seal system, barrier fluid system, or both. (e)(1) Each sensor as required in paragraph (d) shall be checked daily or shall be equipped with an...

40 CFR 60.482-2 - Standards: Pumps in light liquid service.

Code of Federal Regulations, 2010 CFR

2010-07-01

...; or (ii) Equipped with a barrier fluid degassing reservoir that is routed to a process or fuel gas... in VOC service. (3) Each barrier fluid system is equipped with a sensor that will detect failure of...) Designate the visual indications of liquids dripping as a leak. (5)(i) Each sensor as described in paragraph...

Comparative Study of Vibration Condition Indicators for Detecting Cracks in Spur Gears

NASA Technical Reports Server (NTRS)

Nanadic, Nenad; Ardis, Paul; Hood, Adrian; Thurston, Michael; Ghoshal, Anindya; Lewicki, David

2013-01-01

This paper reports the results of an empirical study on the tooth breakage failure mode in spur gears. Of four dominant gear failure modes (breakage, wear, pitting, and scoring), tooth breakage is the most precipitous and often leads to catastrophic failures. The cracks were initiated using a fatigue tester and a custom-designed single-tooth bending fixture to simulate over-load conditions, instead of traditional notching using wire electrical discharge machining (EDM). The cracks were then propagated on a dynamometer. The ground truth of damage level during crack propagation was monitored with crack-propagation sensors. Ten crack propagations have been performed to compare the existing condition indicators (CIs) with respect to their: ability to detect a crack, ability to assess the damage, and sensitivity to sensor placement. Of more than thirty computed CIs, this paper compares five commonly used: raw RMS, FM0, NA4, raw kurtosis, and NP4. The performance of combined CIs was also investigated, using linear, logistic, and boosted regression trees based feature fusion.

40 CFR 68.67 - Process hazard analysis.

Code of Federal Regulations, 2014 CFR

2014-07-01

...) CHEMICAL ACCIDENT PREVENTION PROVISIONS Program 3 Prevention Program § 68.67 Process hazard analysis. (a... instrumentation with alarms, and detection hardware such as hydrocarbon sensors.); (4) Consequences of failure of...

40 CFR 68.67 - Process hazard analysis.

Code of Federal Regulations, 2013 CFR

2013-07-01

...) CHEMICAL ACCIDENT PREVENTION PROVISIONS Program 3 Prevention Program § 68.67 Process hazard analysis. (a... instrumentation with alarms, and detection hardware such as hydrocarbon sensors.); (4) Consequences of failure of...

Gear Fault Detection Effectiveness as Applied to Tooth Surface Pitting Fatigue Damage

NASA Technical Reports Server (NTRS)

Lewicki, David G.; Dempsey, Paula J.; Heath, Gregory F.; Shanthakumaran, Perumal

2009-01-01

A study was performed to evaluate fault detection effectiveness as applied to gear tooth pitting fatigue damage. Vibration and oil-debris monitoring (ODM) data were gathered from 24 sets of spur pinion and face gears run during a previous endurance evaluation study. Three common condition indicators (RMS, FM4, and NA4) were deduced from the time-averaged vibration data and used with the ODM to evaluate their performance for gear fault detection. The NA4 parameter showed to be a very good condition indicator for the detection of gear tooth surface pitting failures. The FM4 and RMS parameters performed average to below average in detection of gear tooth surface pitting failures. The ODM sensor was successful in detecting a significant amount of debris from all the gear tooth pitting fatigue failures. Excluding outliers, the average cumulative mass at the end of a test was 40 mg.

Onboard Sensor Data Qualification in Human-Rated Launch Vehicles

NASA Technical Reports Server (NTRS)

Wong, Edmond; Melcher, Kevin J.; Maul, William A.; Chicatelli, Amy K.; Sowers, Thomas S.; Fulton, Christopher; Bickford, Randall

2012-01-01

The avionics system software for human-rated launch vehicles requires an implementation approach that is robust to failures, especially the failure of sensors used to monitor vehicle conditions that might result in an abort determination. Sensor measurements provide the basis for operational decisions on human-rated launch vehicles. This data is often used to assess the health of system or subsystem components, to identify failures, and to take corrective action. An incorrect conclusion and/or response may result if the sensor itself provides faulty data, or if the data provided by the sensor has been corrupted. Operational decisions based on faulty sensor data have the potential to be catastrophic, resulting in loss of mission or loss of crew. To prevent these later situations from occurring, a Modular Architecture and Generalized Methodology for Sensor Data Qualification in Human-rated Launch Vehicles has been developed. Sensor Data Qualification (SDQ) is a set of algorithms that can be implemented in onboard flight software, and can be used to qualify data obtained from flight-critical sensors prior to the data being used by other flight software algorithms. Qualified data has been analyzed by SDQ and is determined to be a true representation of the sensed system state; that is, the sensor data is determined not to be corrupted by sensor faults or signal transmission faults. Sensor data can become corrupted by faults at any point in the signal path between the sensor and the flight computer. Qualifying the sensor data has the benefit of ensuring that erroneous data is identified and flagged before otherwise being used for operational decisions, thus increasing confidence in the response of the other flight software processes using the qualified data, and decreasing the probability of false alarms or missed detections.

Improving the durability of the optical fiber sensor based on strain transfer analysis

NASA Astrophysics Data System (ADS)

Wang, Huaping; Jiang, Lizhong; Xiang, Ping

2018-05-01

To realize the reliable and long-term strain detection, the durability of optical fiber sensors has attracted more and more attention. The packaging technique has been considered as an effective method, which can enhance the survival ratios of optical fiber sensors to resist the harsh construction and service environment in civil engineering. To monitor the internal strain of structures, the embedded installation is adopted. Due to the different material properties between host material and the protective layer, the monitored structure embedded with sensors can be regarded as a typical model containing inclusions. Interfacial characteristic between the sensor and host material exists obviously, and the contacted interface is prone to debonding failure induced by the large interfacial shear stress. To recognize the local interfacial debonding damage and extend the effective life cycle of the embedded sensor, strain transfer analysis of a general three-layered sensing model is conducted to investigate the failure mechanism. The perturbation of the embedded sensor on the local strain field of host material is discussed. Based on the theoretical analysis, the distribution of the interfacial shear stress along the sensing length is characterized and adopted for the diagnosis of local interfacial debonding, and the sensitive parameters influencing the interfacial shear stress are also investigated. The research in this paper explores the interfacial debonding failure mechanism of embedded sensors based on the strain transfer analysis and provides theoretical basis for enhancing the interfacial bonding properties and improving the durability of embedded optical fiber sensors.

Studies on Automobile Clutch Release Bearing Characteristics with Acoustic Emission

NASA Astrophysics Data System (ADS)

Chen, Guoliang; Chen, Xiaoyang

Automobile clutch release bearings are important automotive driveline components. For the clutch release bearing, early fatigue failure diagnosis is significant, but the early fatigue failure response signal is not obvious, because failure signals are susceptible to noise on the transmission path and to working environment factors such as interference. With an improvement in vehicle design, clutch release bearing fatigue life indicators have increasingly become an important requirement. Contact fatigue is the main failure mode of release rolling bearing components. Acoustic emission techniques in contact fatigue failure detection have unique advantages, which include highly sensitive nondestructive testing methods. In the acoustic emission technique to detect a bearing, signals are collected from multiple sensors. Each signal contains partial fault information, and there is overlap between the signals' fault information. Therefore, the sensor signals receive simultaneous source information integration is complete fragment rolling bearing fault acoustic emission signal, which is the key issue of accurate fault diagnosis. Release bearing comprises the following components: the outer ring, inner ring, rolling ball, cage. When a failure occurs (such as cracking, pitting), the other components will impact damaged point to produce acoustic emission signal. Release bearings mainly emit an acoustic emission waveform with a Rayleigh wave propagation. Elastic waves emitted from the sound source, and it is through the part surface bearing scattering. Dynamic simulation of rolling bearing failure will contribute to a more in-depth understanding of the characteristics of rolling bearing failure, because monitoring and fault diagnosis of rolling bearings provide a theoretical basis and foundation.

Advances in Micromechanics Modeling of Composites Structures for Structural Health Monitoring

NASA Astrophysics Data System (ADS)

Moncada, Albert

Although high performance, light-weight composites are increasingly being used in applications ranging from aircraft, rotorcraft, weapon systems and ground vehicles, the assurance of structural reliability remains a critical issue. In composites, damage is absorbed through various fracture processes, including fiber failure, matrix cracking and delamination. An important element in achieving reliable composite systems is a strong capability of assessing and inspecting physical damage of critical structural components. Installation of a robust Structural Health Monitoring (SHM) system would be very valuable in detecting the onset of composite failure. A number of major issues still require serious attention in connection with the research and development aspects of sensor-integrated reliable SHM systems for composite structures. In particular, the sensitivity of currently available sensor systems does not allow detection of micro level damage; this limits the capability of data driven SHM systems. As a fundamental layer in SHM, modeling can provide in-depth information on material and structural behavior for sensing and detection, as well as data for learning algorithms. This dissertation focuses on the development of a multiscale analysis framework, which is used to detect various forms of damage in complex composite structures. A generalized method of cells based micromechanics analysis, as implemented in NASA's MAC/GMC code, is used for the micro-level analysis. First, a baseline study of MAC/GMC is performed to determine the governing failure theories that best capture the damage progression. The deficiencies associated with various layups and loading conditions are addressed. In most micromechanics analysis, a representative unit cell (RUC) with a common fiber packing arrangement is used. The effect of variation in this arrangement within the RUC has been studied and results indicate this variation influences the macro-scale effective material properties and failure stresses. The developed model has been used to simulate impact damage in a composite beam and an airfoil structure. The model data was verified through active interrogation using piezoelectric sensors. The multiscale model was further extended to develop a coupled damage and wave attenuation model, which was used to study different damage states such as fiber-matrix debonding in composite structures with surface bonded piezoelectric sensors.

Remote Structural Health Monitoring and Advanced Prognostics of Wind Turbines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Douglas Brown; Bernard Laskowski

The prospect of substantial investment in wind energy generation represents a significant capital investment strategy. In order to maximize the life-cycle of wind turbines, associated rotors, gears, and structural towers, a capability to detect and predict (prognostics) the onset of mechanical faults at a sufficiently early stage for maintenance actions to be planned would significantly reduce both maintenance and operational costs. Advancement towards this effort has been made through the development of anomaly detection, fault detection and fault diagnosis routines to identify selected fault modes of a wind turbine based on available sensor data preceding an unscheduled emergency shutdown. Themore » anomaly detection approach employs spectral techniques to find an approximation of the data using a combination of attributes that capture the bulk of variability in the data. Fault detection and diagnosis (FDD) is performed using a neural network-based classifier trained from baseline and fault data recorded during known failure conditions. The approach has been evaluated for known baseline conditions and three selected failure modes: pitch rate failure, low oil pressure failure and a gearbox gear-tooth failure. Experimental results demonstrate the approach can distinguish between these failure modes and normal baseline behavior within a specified statistical accuracy.« less

Framework for a space shuttle main engine health monitoring system

NASA Technical Reports Server (NTRS)

Hawman, Michael W.; Galinaitis, William S.; Tulpule, Sharayu; Mattedi, Anita K.; Kamenetz, Jeffrey

1990-01-01

A framework developed for a health management system (HMS) which is directed at improving the safety of operation of the Space Shuttle Main Engine (SSME) is summarized. An emphasis was placed on near term technology through requirements to use existing SSME instrumentation and to demonstrate the HMS during SSME ground tests within five years. The HMS framework was developed through an analysis of SSME failure modes, fault detection algorithms, sensor technologies, and hardware architectures. A key feature of the HMS framework design is that a clear path from the ground test system to a flight HMS was maintained. Fault detection techniques based on time series, nonlinear regression, and clustering algorithms were developed and demonstrated on data from SSME ground test failures. The fault detection algorithms exhibited 100 percent detection of faults, had an extremely low false alarm rate, and were robust to sensor loss. These algorithms were incorporated into a hierarchical decision making strategy for overall assessment of SSME health. A preliminary design for a hardware architecture capable of supporting real time operation of the HMS functions was developed. Utilizing modular, commercial off-the-shelf components produced a reliable low cost design with the flexibility to incorporate advances in algorithm and sensor technology as they become available.

Development of sensitive holographic devices for physiological metal ion detection

NASA Astrophysics Data System (ADS)

Sabad-e.-Gul; Martin, Suzanne; Cassidy, John; Naydenova, Izabela

2017-08-01

The development of selective alkali metal ions sensors in particular is a subject of significant interest. In this respect, the level of blood electrolytes, particularly H+, Na+, K+ and Cl- , is widely used to monitor aberrant physiologies associated with pulmonary emphysema, acute and chronic renal failure, heart failure, diabetes. The sensors reported in this paper are created by holographic recording of surface relief structures in a self-processing photopolymer material. The structures are functionalized by ionophores dibenzo-18-crown-6 (DC) and tetraethyl 4-tert-butylcalix[4]arene (TBC) in plasticised polyvinyl chloride (PVC) matrix. Interrogation of these structures by light allows indirect measurements of chemical analytes' concentration in real time. We present results on the optimisation and testing of the holographic sensor. A self-processing acrylamide-based photopolymer was used to fabricate the required photonic structures. The performance of the sensors for detection of K+ and Na+ was investigated. It was observed that the functionalisation with DC provides a selective response of the devices to K+ over Na+ and TBC coated surface structures are selectively sensitive to Na+. The sensor responds to Na+ within the physiological ranges. Normal levels of Na+ and K+ in human serum lie within the ranges 135-148mM and 3.5-5.3 mM respectively.

40 CFR 60.482-2a - Standards: Pumps in light liquid service.

Code of Federal Regulations, 2011 CFR

2011-07-01

... routed to a process or fuel gas system or connected by a closed vent system to a control device that... sensor that will detect failure of the seal system, the barrier fluid system, or both. (4)(i) Each pump... indications of liquids dripping as a leak. (5)(i) Each sensor as described in paragraph (d)(3) is checked...

A Gossip-based Energy Efficient Protocol for Robust In-network Aggregation in Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Fauji, Shantanu

We consider the problem of energy efficient and fault tolerant in--network aggregation for wireless sensor networks (WSNs). In-network aggregation is the process of aggregation while collecting data from sensors to the base station. This process should be energy efficient due to the limited energy at the sensors and tolerant to the high failure rates common in sensor networks. Tree based in--network aggregation protocols, although energy efficient, are not robust to network failures. Multipath routing protocols are robust to failures to a certain degree but are not energy efficient due to the overhead in the maintenance of multiple paths. We propose a new protocol for in-network aggregation in WSNs, which is energy efficient, achieves high lifetime, and is robust to the changes in the network topology. Our protocol, gossip--based protocol for in-network aggregation (GPIA) is based on the spreading of information via gossip. GPIA is not only adaptive to failures and changes in the network topology, but is also energy efficient. Energy efficiency of GPIA comes from all the nodes being capable of selective message reception and detecting convergence of the aggregation early. We experimentally show that GPIA provides significant improvement over some other competitors like the Ridesharing, Synopsis Diffusion and the pure version of gossip. GPIA shows ten fold, five fold and two fold improvement over the pure gossip, the synopsis diffusion and Ridesharing protocols in terms of network lifetime, respectively. Further, GPIA retains gossip's robustness to failures and improves upon the accuracy of synopsis diffusion and Ridesharing.

Adaptive Connectivity Restoration from Node Failure(s) in Wireless Sensor Networks

PubMed Central

Wang, Huaiyuan; Ding, Xu; Huang, Cheng; Wu, Xiaobei

2016-01-01

Recently, there is a growing interest in the applications of wireless sensor networks (WSNs). A set of sensor nodes is deployed in order to collectively survey an area of interest and/or perform specific surveillance tasks in some of the applications, such as battlefield reconnaissance. Due to the harsh deployment environments and limited energy supply, nodes may fail, which impacts the connectivity of the whole network. Since a single node failure (cut-vertex) will destroy the connectivity and divide the network into disjoint blocks, most of the existing studies focus on the problem of single node failure. However, the failure of multiple nodes would be a disaster to the whole network and must be repaired effectively. Only few studies are proposed to handle the problem of multiple cut-vertex failures, which is a special case of multiple node failures. Therefore, this paper proposes a comprehensive solution to address the problems of node failure (single and multiple). Collaborative Single Node Failure Restoration algorithm (CSFR) is presented to solve the problem of single node failure only with cooperative communication, but CSFR-M, which is the extension of CSFR, handles the single node failure problem more effectively with node motion. Moreover, Collaborative Connectivity Restoration Algorithm (CCRA) is proposed on the basis of cooperative communication and node maneuverability to restore network connectivity after multiple nodes fail. CSFR-M and CCRA are reactive methods that initiate the connectivity restoration after detecting the node failure(s). In order to further minimize the energy dissipation, CCRA opts to simplify the recovery process by gridding. Moreover, the distance that an individual node needs to travel during recovery is reduced by choosing the nearest suitable candidates. Finally, extensive simulations validate the performance of CSFR, CSFR-M and CCRA. PMID:27690030

Parylene MEMS patency sensor for assessment of hydrocephalus shunt obstruction.

PubMed

Kim, Brian J; Jin, Willa; Baldwin, Alexander; Yu, Lawrence; Christian, Eisha; Krieger, Mark D; McComb, J Gordon; Meng, Ellis

2016-10-01

Neurosurgical ventricular shunts inserted to treat hydrocephalus experience a cumulative failure rate of 80 % over 12 years; obstruction is responsible for most failures with a majority occurring at the proximal catheter. Current diagnosis of shunt malfunction is imprecise and involves neuroimaging studies and shunt tapping, an invasive measurement of intracranial pressure and shunt patency. These patients often present emergently and a delay in care has dire consequences. A microelectromechanical systems (MEMS) patency sensor was developed to enable direct and quantitative tracking of shunt patency in order to detect proximal shunt occlusion prior to the development of clinical symptoms thereby avoiding delays in treatment. The sensor was fabricated on a flexible polymer substrate to eventually allow integration into a shunt. In this study, the sensor was packaged for use with external ventricular drainage systems for clinical validation. Insights into the transduction mechanism of the sensor were obtained. The impact of electrode size, clinically relevant temperatures and flows, and hydrogen peroxide (H2O2) plasma sterilization on sensor function were evaluated. Sensor performance in the presence of static and dynamic obstruction was demonstrated using 3 different models of obstruction. Electrode size was found to have a minimal effect on sensor performance and increased temperature and flow resulted in a slight decrease in the baseline impedance due to an increase in ionic mobility. However, sensor response did not vary within clinically relevant temperature and flow ranges. H2O2 plasma sterilization also had no effect on sensor performance. This low power and simple format sensor was developed with the intention of future integration into shunts for wireless monitoring of shunt state and more importantly, a more accurate and timely diagnosis of shunt failure.

Biocompatible hydrogel membranes for the protection of RNA aptamer-based electrochemical sensors

NASA Astrophysics Data System (ADS)

Schoukroun-Barnes, Lauren R.; Wagan, Samiullah; Liu, Juan; Leach, Jennie B.; White, Ryan J.

2013-05-01

Electrochemical-aptamer based (E-AB) sensors represent a universal specific, selective, and sensitive sensing platform for the detection of small molecule targets. Their specific detection abilities are afforded by oligonucleotide (RNA or DNA) aptamers employed as electrode-bound biorecognition elements. Sensor signaling is predicated on bindinginduced changes in conformation and/or flexibility of the aptamer that is readily measurable electrochemically. While sensors fabricated using DNA aptamers can achieve specific and selective detection even in unadulterated sample matrices, such as blood serum, RNA-based sensors fail when challenged in the same sample matrix without significant sample pretreatment. This failure is at least partially a result of enzymatic degradation of the RNA sensing element. This degradation destroys the sensing aptamer inhibiting the quantitative measurement of the target analyte and thus limits the application of E-AB sensors constructed with RNA aptamer. To circumvent this, we demonstrate that a biocompatible hydrogel membrane protects the RNA aptamer sensor surface from enzymatic degradation for at least 3 hours - a remarkable improvement over the rapid (~minutes) degradation of unprotected sensors. To demonstrate this, we characterize the response of sensors fabricated with representative DNA and RNA aptamers directed against the aminoglycoside antibiotic, tobramycin in blood serum both protected and unprotected by a polyacrylamide membrane. Furthermore, we find encapsulation of the sensor surface with the hydrogel does not significantly impede the detection ability of aptamer-based sensors. This hydrogel-aptamer interface will thus likely prove useful for the long-term monitoring of therapeutics in complex biological media.

A multi-sensor approach to landslide monitoring of rainfall-induced failures in Scotland.

NASA Astrophysics Data System (ADS)

Gilles, Charlie; Hoey, Trevor; Williams, Richard

2017-04-01

Landslides are of significant interest in upland areas of the United Kingdom due to their: complex mechanics, potential to channelize into hazardous debris flows and their costly potential impacts on infrastructure. The British Geological Survey National Landslide Database contains an average of 367 landslides per year (from 1970). Slope failures in the UK are typically triggered by extended periods of intense rainfall, and can occur at any time of year. In any given rainfall event that triggers landslides, most potentially vulnerable slopes remain stable. Accurate warning systems would be facilitated by identifying landslide precursors prior to failure events. This project tests whether such precursors can be identified in the valley of Glen Ogle, Scotland (87 km north-west of Edinburgh), where in summer 2004 two debris flows blocked the main road (A85), trapping fifty-seven people. Two adjacent sites have been selected on a west facing slope in Glen Ogle, one of which (the control) has been stable since at least 2004 and the other failed in 2004 and remains unstable. Understanding the immediate causes and antecedent conditions responsible for landslides requires a multi-scale approach. This project uses multiple sensors to assess failure mechanisms of landslides in Glen Ogle: (1) 3-monthly, high (1.8 arcsec) resolution terrestrial laser scanning of topography to detect changes and identify patterns of movement prior to major failure, using the Riegl VZ-1000 (NERC Geophysical Equipment Fund); (2) rainfall and soil moisture data to monitor pore pressure of landslide failure prior to and after hydrologically triggered events; (3) monitoring ground motion using grain-scale sensors which are becoming lower cost, more efficient in terms of power, and can be wirelessly networked these will be used to detect small scale movement of the landslide. Comparative data from the control and test sites will be presented, from which patterns of surface deformation between failure events will be derived.

Development of a wireless nonlinear wave modulation spectroscopy (NWMS) sensor node for fatigue crack detection

NASA Astrophysics Data System (ADS)

Liu, Peipei; Yang, Suyoung; Lim, Hyung Jin; Park, Hyung Chul; Ko, In Chang; Sohn, Hoon

2014-03-01

Fatigue crack is one of the main culprits for the failure of metallic structures. Recently, it has been shown that nonlinear wave modulation spectroscopy (NWMS) is effective in detecting nonlinear mechanisms produced by fatigue crack. In this study, an active wireless sensor node for fatigue crack detection is developed based on NWMS. Using PZT transducers attached to a target structure, ultrasonic waves at two distinctive frequencies are generated, and their modulation due to fatigue crack formation is detected using another PZT transducer. Furthermore, a reference-free NWMS algorithm is developed so that fatigue crack can be detected without relying on history data of the structure with minimal parameter adjustment by the end users. The algorithm is embedded into FPGA, and the diagnosis is transmitted to a base station using a commercial wireless communication system. The whole design of the sensor node is fulfilled in a low power working strategy. Finally, an experimental verification has been performed using aluminum plate specimens to show the feasibility of the developed active wireless NWMS sensor node.

Gyro and accelerometer failure detection and identification in redundant sensor systems

NASA Technical Reports Server (NTRS)

Potter, J. E.; Deckert, J. C.

1972-01-01

Algorithms for failure detection and identification for redundant noncolinear arrays of single degree of freedom gyros and accelerometers are described. These algorithms are optimum in the sense that detection occurs as soon as it is no longer possible to account for the instrument outputs as the outputs of good instruments operating within their noise tolerances, and identification occurs as soon as it is true that only a particular instrument failure could account for the actual instrument outputs within the noise tolerance of good instruments. An estimation algorithm is described which minimizes the maximum possible estimation error magnitude for the given set of instrument outputs. Monte Carlo simulation results are presented for the application of the algorithms to an inertial reference unit consisting of six gyros and six accelerometers in two alternate configurations.

SSME leak detection feasibility investigation by utilization of infrared sensor technology

NASA Technical Reports Server (NTRS)

Shohadaee, Ahmad A.; Crawford, Roger A.

1990-01-01

This investigation examined the potential of using state-of-the-art technology of infrared (IR) thermal imaging systems combined with computer, digital image processing and expert systems for Space Shuttle Main Engines (SSME) propellant path peak detection as an early warning system of imminent engine failure. A low-cost, laboratory experiment was devised and an experimental approach was established. The system was installed, checked out, and data were successfully acquired demonstrating the proof-of-concept. The conclusion from this investigation is that both numerical and experimental results indicate that the leak detection by using infrared sensor technology proved to be feasible for a rocket engine health monitoring system.

A Multiple Sensor Machine Vision System Technology for the Hardwood

Treesearch

Richard W. Conners; D.Earl Kline; Philip A. Araman

1995-01-01

For the last few years the authors have been extolling the virtues of a multiple sensor approach to hardwood defect detection. Since 1989 the authors have actively been trying to develop such a system. This paper details some of the successes and failures that have been experienced to date. It also discusses what remains to be done and gives time lines for the...

Failure detection and fault management techniques for flush airdata sensing systems

NASA Technical Reports Server (NTRS)

Whitmore, Stephen A.; Moes, Timothy R.; Leondes, Cornelius T.

1992-01-01

A high-angle-of-attack flush airdata sensing system was installed and flight tested on the F-18 High Alpha Research Vehicle at NASA-Dryden. This system uses a matrix of pressure orifices arranged in concentric circles on the nose of the vehicle to determine angles of attack, angles of sideslip, dynamic pressure, and static pressure as well as other airdata parameters. Results presented use an arrangement of 11 symmetrically distributed ports on the aircraft nose. Experience with this sensing system data indicates that the primary concern for real-time implementation is the detection and management of overall system and individual pressure sensor failures. The multiple port sensing system is more tolerant to small disturbances in the measured pressure data than conventional probe-based intrusive airdata systems. However, under adverse circumstances, large undetected failures in individual pressure ports can result in algorithm divergence and catastrophic failure of the entire system. How system and individual port failures may be detected using chi sq. analysis is shown. Once identified, the effects of failures are eliminated using weighted least squares.

Corrosivity Sensor for Exposed Pipelines Based on Wireless Energy Transfer.

PubMed

Lawand, Lydia; Shiryayev, Oleg; Al Handawi, Khalil; Vahdati, Nader; Rostron, Paul

2017-05-30

External corrosion was identified as one of the main causes of pipeline failures worldwide. A solution that addresses the issue of detecting and quantifying corrosivity of environment for application to existing exposed pipelines has been developed. It consists of a sensing array made of an assembly of thin strips of pipeline steel and a circuit that provides a visual sensor reading to the operator. The proposed sensor is passive and does not require a constant power supply. Circuit design was validated through simulations and lab experiments. Accelerated corrosion experiment was conducted to confirm the feasibility of the proposed corrosivity sensor design.

Gear Fault Detection Effectiveness as Applied to Tooth Surface Pitting Fatigue Damage

NASA Technical Reports Server (NTRS)

Lewicki, David G.; Dempsey, Paula J.; Heath, Gregory F.; Shanthakumaran, Perumal

2010-01-01

A study was performed to evaluate fault detection effectiveness as applied to gear-tooth-pitting-fatigue damage. Vibration and oil-debris monitoring (ODM) data were gathered from 24 sets of spur pinion and face gears run during a previous endurance evaluation study. Three common condition indicators (RMS, FM4, and NA4 [Ed. 's note: See Appendix A-Definitions D were deduced from the time-averaged vibration data and used with the ODM to evaluate their performance for gear fault detection. The NA4 parameter showed to be a very good condition indicator for the detection of gear tooth surface pitting failures. The FM4 and RMS parameters perfomu:d average to below average in detection of gear tooth surface pitting failures. The ODM sensor was successful in detecting a significant 8lDOunt of debris from all the gear tooth pitting fatigue failures. Excluding outliers, the average cumulative mass at the end of a test was 40 mg.

10th Annual Systems Engineering Conference: Volume 2 Wednesday

DTIC Science & Technology

2007-10-25

intelligently optimize resource performance. Self - Healing Detect hardware/software failures and reconfigure to permit continued operations. Self ...Types Wake Ice WEAPON/PLATFORM ACOUSTICS Self -Noise Radiated Noise Beam Forming Pulse Types Submarines, surface ships, and platform sensors P r o p P r o...Computing Self -Protecting Detect internal/external attacks and protect it’s resources from exploitation. Self -Optimizing Detect sub-optimal behaviors and

Optimization of Sensor Monitoring Strategies for Emissions

NASA Astrophysics Data System (ADS)

Klise, K. A.; Laird, C. D.; Downey, N.; Baker Hebert, L.; Blewitt, D.; Smith, G. R.

2016-12-01

Continuous or regularly scheduled monitoring has the potential to quickly identify changes in air quality. However, even with low-cost sensors, only a limited number of sensors can be placed to monitor airborne pollutants. The physical placement of these sensors and the sensor technology used can have a large impact on the performance of a monitoring strategy. Furthermore, sensors can be placed for different objectives, including maximum coverage, minimum time to detection or exposure, or to quantify emissions. Different objectives may require different monitoring strategies, which need to be evaluated by stakeholders before sensors are placed in the field. In this presentation, we outline methods to enhance ambient detection programs through optimal design of the monitoring strategy. These methods integrate atmospheric transport models with sensor characteristics, including fixed and mobile sensors, sensor cost and failure rate. The methods use site specific pre-computed scenarios which capture differences in meteorology, terrain, concentration averaging times, gas concentration, and emission characteristics. The pre-computed scenarios become input to a mixed-integer, stochastic programming problem that solves for sensor locations and types that maximize the effectiveness of the detection program. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Detection of Ultrasonic Stress Waves in Structures Using 3D Shaped Optic Fiber Based on a Mach-Zehnder Interferometer.

PubMed

Lan, Chengming; Zhou, Wensong; Xie, Yawen

2018-04-16

This work proposes a 3D shaped optic fiber sensor for ultrasonic stress waves detection based on the principle of a Mach–Zehnder interferometer. This sensor can be used to receive acoustic emission signals in the passive damage detection methods and other types of ultrasonic signals propagating in the active damage detection methods, such as guided wave-based methods. The sensitivity of an ultrasonic fiber sensor based on the Mach–Zehnder interferometer mainly depends on the length of the sensing optical fiber; therefore, the proposed sensor achieves the maximum possible sensitivity by wrapping an optical fiber on a hollow cylinder with a base. The deformation of the optical fiber is produced by the displacement field of guided waves in the hollow cylinder. The sensor was first analyzed using the finite element method, which demonstrated its basic sensing capacity, and the simulation signals have the same characteristics in the frequency domain as the excitation signal. Subsequently, the primary investigations were conducted via a series of experiments. The sensor was used to detect guided wave signals excited by a piezoelectric wafer in an aluminum plate, and subsequently it was tested on a reinforced concrete beam, which produced acoustic emission signals via impact loading and crack extension when it was loaded to failure. The signals obtained from a piezoelectric acoustic emission sensor were used for comparison, and the results indicated that the proposed 3D fiber optic sensor can detect ultrasonic signals in the specific frequency response range.

Detection of Ultrasonic Stress Waves in Structures Using 3D Shaped Optic Fiber Based on a Mach–Zehnder Interferometer

PubMed Central

Xie, Yawen

2018-01-01

This work proposes a 3D shaped optic fiber sensor for ultrasonic stress waves detection based on the principle of a Mach–Zehnder interferometer. This sensor can be used to receive acoustic emission signals in the passive damage detection methods and other types of ultrasonic signals propagating in the active damage detection methods, such as guided wave-based methods. The sensitivity of an ultrasonic fiber sensor based on the Mach–Zehnder interferometer mainly depends on the length of the sensing optical fiber; therefore, the proposed sensor achieves the maximum possible sensitivity by wrapping an optical fiber on a hollow cylinder with a base. The deformation of the optical fiber is produced by the displacement field of guided waves in the hollow cylinder. The sensor was first analyzed using the finite element method, which demonstrated its basic sensing capacity, and the simulation signals have the same characteristics in the frequency domain as the excitation signal. Subsequently, the primary investigations were conducted via a series of experiments. The sensor was used to detect guided wave signals excited by a piezoelectric wafer in an aluminum plate, and subsequently it was tested on a reinforced concrete beam, which produced acoustic emission signals via impact loading and crack extension when it was loaded to failure. The signals obtained from a piezoelectric acoustic emission sensor were used for comparison, and the results indicated that the proposed 3D fiber optic sensor can detect ultrasonic signals in the specific frequency response range. PMID:29659540

Reactor protection system with automatic self-testing and diagnostic

DOEpatents

Gaubatz, Donald C.

1996-01-01

A reactor protection system having four divisions, with quad redundant sensors for each scram parameter providing input to four independent microprocessor-based electronic chassis. Each electronic chassis acquires the scram parameter data from its own sensor, digitizes the information, and then transmits the sensor reading to the other three electronic chassis via optical fibers. To increase system availability and reduce false scrams, the reactor protection system employs two levels of voting on a need for reactor scram. The electronic chassis perform software divisional data processing, vote 2/3 with spare based upon information from all four sensors, and send the divisional scram signals to the hardware logic panel, which performs a 2/4 division vote on whether or not to initiate a reactor scram. Each chassis makes a divisional scram decision based on data from all sensors. Automatic detection and discrimination against failed sensors allows the reactor protection system to automatically enter a known state when sensor failures occur. Cross communication of sensor readings allows comparison of four theoretically "identical" values. This permits identification of sensor errors such as drift or malfunction. A diagnostic request for service is issued for errant sensor data. Automated self test and diagnostic monitoring, sensor input through output relay logic, virtually eliminate the need for manual surveillance testing. This provides an ability for each division to cross-check all divisions and to sense failures of the hardware logic.

Reactor protection system with automatic self-testing and diagnostic

DOEpatents

Gaubatz, D.C.

1996-12-17

A reactor protection system is disclosed having four divisions, with quad redundant sensors for each scram parameter providing input to four independent microprocessor-based electronic chassis. Each electronic chassis acquires the scram parameter data from its own sensor, digitizes the information, and then transmits the sensor reading to the other three electronic chassis via optical fibers. To increase system availability and reduce false scrams, the reactor protection system employs two levels of voting on a need for reactor scram. The electronic chassis perform software divisional data processing, vote 2/3 with spare based upon information from all four sensors, and send the divisional scram signals to the hardware logic panel, which performs a 2/4 division vote on whether or not to initiate a reactor scram. Each chassis makes a divisional scram decision based on data from all sensors. Automatic detection and discrimination against failed sensors allows the reactor protection system to automatically enter a known state when sensor failures occur. Cross communication of sensor readings allows comparison of four theoretically ``identical`` values. This permits identification of sensor errors such as drift or malfunction. A diagnostic request for service is issued for errant sensor data. Automated self test and diagnostic monitoring, sensor input through output relay logic, virtually eliminate the need for manual surveillance testing. This provides an ability for each division to cross-check all divisions and to sense failures of the hardware logic. 16 figs.

Real-Time Sensor Validation, Signal Reconstruction, and Feature Detection for an RLV Propulsion Testbed

NASA Technical Reports Server (NTRS)

Jankovsky, Amy L.; Fulton, Christopher E.; Binder, Michael P.; Maul, William A., III; Meyer, Claudia M.

1998-01-01

A real-time system for validating sensor health has been developed in support of the reusable launch vehicle program. This system was designed for use in a propulsion testbed as part of an overall effort to improve the safety, diagnostic capability, and cost of operation of the testbed. The sensor validation system was designed and developed at the NASA Lewis Research Center and integrated into a propulsion checkout and control system as part of an industry-NASA partnership, led by Rockwell International for the Marshall Space Flight Center. The system includes modules for sensor validation, signal reconstruction, and feature detection and was designed to maximize portability to other applications. Review of test data from initial integration testing verified real-time operation and showed the system to perform correctly on both hard and soft sensor failure test cases. This paper discusses the design of the sensor validation and supporting modules developed at LeRC and reviews results obtained from initial test cases.

Current Status of Hybrid Bearing Damage Detection

NASA Technical Reports Server (NTRS)

Dempsey, Paula J.; Certo, Joseph M.; Morales, Wilfredo

2004-01-01

Advances in material development and processing have led to the introduction of ceramic hybrid bearings for many applications. The introduction of silicon nitride hybrid bearings into the high pressure oxidizer turbopump, on the space shuttle main engine, led NASA to solve a highly persistent and troublesome bearing problem. Hybrid bearings consist of ceramic balls and steel races. The majority of hybrid bearings utilize Si3N4 balls. The aerospace industry is currently studying the use of hybrid bearings and naturally the failure modes of these bearings become an issue in light of the limited data available. In today s turbine engines and helicopter transmissions, the health of the bearings is detected by the properties of the debris found in the lubrication line when damage begins to occur. Current oil debris sensor technology relies on the magnetic properties of the debris to detect damage. Since the ceramic rolling elements of hybrid bearings have no metallic properties, a new sensing system must be developed to indicate the system health if ceramic components are to be safely implemented in aerospace applications. The ceramic oil debris sensor must be capable of detecting ceramic and metallic component damage with sufficient reliability and forewarning to prevent a catastrophic failure. The objective of this research is to provide a background summary on what is currently known about hybrid bearing failure modes and to report preliminary results on the detection of silicon nitride debris, in oil, using a commercial particle counter.

Intelligent transient transitions detection of LRE test bed

NASA Astrophysics Data System (ADS)

Zhu, Fengyu; Shen, Zhengguang; Wang, Qi

2013-01-01

Health Monitoring Systems is an implementation of monitoring strategies for complex systems whereby avoiding catastrophic failure, extending life and leading to improved asset management. A Health Monitoring Systems generally encompasses intelligence at many levels and sub-systems including sensors, actuators, devices, etc. In this paper, a smart sensor is studied, which is use to detect transient transitions of liquid-propellant rocket engines test bed. In consideration of dramatic changes of variable condition, wavelet decomposition is used to work real time in areas. Contrast to traditional Fourier transform method, the major advantage of adding wavelet analysis is the ability to detect transient transitions as well as obtaining the frequency content using a much smaller data set. Historically, transient transitions were only detected by offline analysis of the data. The methods proposed in this paper provide an opportunity to detect transient transitions automatically as well as many additional data anomalies, and provide improved data-correction and sensor health diagnostic abilities. The developed algorithms have been tested on actual rocket test data.

MEMS based shock pulse detection sensor for improved rotary Stirling cooler end of life prediction

NASA Astrophysics Data System (ADS)

Hübner, M.; Münzberg, M.

2018-05-01

The widespread use of rotary Stirling coolers in high performance thermal imagers used for critical 24/7 surveillance tasks justifies any effort to significantly enhance the reliability and predictable uptime of those coolers. Typically the lifetime of the whole imaging device is limited due to continuous wear and finally failure of the rotary compressor of the Stirling cooler, especially due to failure of the comprised bearings. MTTF based lifetime predictions, even based on refined MTTF models taking operational scenario dependent scaling factors into account, still lack in precision to forecast accurately the end of life (EOL) of individual coolers. Consequently preventive maintenance of individual coolers to avoid failures of the main sensor in critical operational scenarios are very costly or even useless. We have developed an integrated test method based on `Micro Electromechanical Systems', so called MEMS sensors, which significantly improves the cooler EOL prediction. The recently commercially available MEMS acceleration sensors have mechanical resonance frequencies up to 50 kHz. They are able to detect solid borne shock pulses in the cooler structure, originating from e.g. metal on metal impacts driven by periodical forces acting on moving inner parts of the rotary compressor within wear dependent slack and play. The impact driven transient shock pulse analyses uses only the high frequency signal <10kHz and differs therefore from the commonly used broadband low frequencies vibrational analysis of reciprocating machines. It offers a direct indicator of the individual state of wear. The predictive cooler lifetime model based on the shock pulse analysis is presented and results are discussed.

Target Detection over the Diurnal Cycle Using a Multispectral Infrared Sensor.

PubMed

Zhao, Huijie; Ji, Zheng; Li, Na; Gu, Jianrong; Li, Yansong

2016-12-29

When detecting a target over the diurnal cycle, a conventional infrared thermal sensor might lose the target due to the thermal crossover, which could happen at any time throughout the day when the infrared image contrast between target and background in a scene is indistinguishable due to the temperature variation. In this paper, the benefits of using a multispectral-based infrared sensor over the diurnal cycle have been shown. Firstly, a brief theoretical analysis on how the thermal crossover influences a conventional thermal sensor, within the conditions where the thermal crossover would happen and why the mid-infrared (3~5 μm) multispectral technology is effective, is presented. Furthermore, the effectiveness of this technology is also described and we describe how the prototype design and multispectral technology is employed to help solve the thermal crossover detection problem. Thirdly, several targets are set up outside and imaged in the field experiment over a 24-h period. The experimental results show that the multispectral infrared imaging system can enhance the contrast of the detected images and effectively solve the failure of the conventional infrared sensor during the diurnal cycle, which is of great significance for infrared surveillance applications.

A wire-based dual-analyte sensor for glucose and lactate: in vitro and in vivo evaluation.

PubMed

Ward, W Kenneth; House, Jody L; Birck, Jonathan; Anderson, Ellen M; Jansen, Lawrence B

2004-06-01

Continuous measurement of lactate is potentially useful for detecting physical exhaustion and for monitoring critical care conditions characterized by hypoperfusion, such as heart failure. In some conditions, it may be desirable to monitor more than one metabolic parameter concurrently. For this reason, we designed and fabricated twisted wire-based microelectrodes that can measure both lactate and glucose. These dual-analyte sensors were characterized in vitro by measuring their response to the analyte of interest and to assess whether they were susceptible to interference from the other analyte. When measured in stirred aqueous buffer, lactate sensors detected a very small amount of crosstalk from glucose in vitro, although this signal was less than 3% of the response to lactate. Glucose sensors did not detect crosstalk from lactate. Sensors were implanted subcutaneously in rats and tested during infusions of lactate and glucose. Each sensing electrode responded rapidly to changes in its analyte concentration, and there was no evidence of in vivo crosstalk. This study constitutes proof of the concept that oxidase-based, amperometric wire microsensors can detect changes in glucose and lactate during subcutaneous implantation in rats.

Target Detection over the Diurnal Cycle Using a Multispectral Infrared Sensor

PubMed Central

Zhao, Huijie; Ji, Zheng; Li, Na; Gu, Jianrong; Li, Yansong

2016-01-01

When detecting a target over the diurnal cycle, a conventional infrared thermal sensor might lose the target due to the thermal crossover, which could happen at any time throughout the day when the infrared image contrast between target and background in a scene is indistinguishable due to the temperature variation. In this paper, the benefits of using a multispectral-based infrared sensor over the diurnal cycle have been shown. Firstly, a brief theoretical analysis on how the thermal crossover influences a conventional thermal sensor, within the conditions where the thermal crossover would happen and why the mid-infrared (3~5 μm) multispectral technology is effective, is presented. Furthermore, the effectiveness of this technology is also described and we describe how the prototype design and multispectral technology is employed to help solve the thermal crossover detection problem. Thirdly, several targets are set up outside and imaged in the field experiment over a 24-h period. The experimental results show that the multispectral infrared imaging system can enhance the contrast of the detected images and effectively solve the failure of the conventional infrared sensor during the diurnal cycle, which is of great significance for infrared surveillance applications. PMID:28036073

Sensor fault detection and isolation via high-gain observers: application to a double-pipe heat exchanger.

PubMed

Escobar, R F; Astorga-Zaragoza, C M; Téllez-Anguiano, A C; Juárez-Romero, D; Hernández, J A; Guerrero-Ramírez, G V

2011-07-01

This paper deals with fault detection and isolation (FDI) in sensors applied to a concentric-pipe counter-flow heat exchanger. The proposed FDI is based on the analytical redundancy implementing nonlinear high-gain observers which are used to generate residuals when a sensor fault is presented (as software sensors). By evaluating the generated residual, it is possible to switch between the sensor and the observer when a failure is detected. Experiments in a heat exchanger pilot validate the effectiveness of the approach. The FDI technique is easy to implement allowing the industries to have an excellent alternative tool to keep their heat transfer process under supervision. The main contribution of this work is based on a dynamic model with heat transfer coefficients which depend on temperature and flow used to estimate the output temperatures of a heat exchanger. This model provides a satisfactory approximation of the states of the heat exchanger in order to allow its implementation in a FDI system used to perform supervision tasks. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

FRP debonding monitoring using OTDR techniques

NASA Astrophysics Data System (ADS)

Hou, Shuang; Cai, C. S. Steve; Ou, Jinping

2009-07-01

Debonding failure has been reported as the dominant failure mode for FRP strengthening in flexure. This paper explores a novel debonding monitoring method for FRP strengthened structures by means of OTDR-based fiber optic technology. Interface slip as a key factor in debonding failures will be measured through sensing optic fibers, which is instrumented in the interface between FRP and concrete in the direction perpendicular to the FRP filaments. Slip in the interface will induce power losses in the optic fiber signals at the intersection point of the FRP strip and the sensing optic fiber and the signal change will be detected through OTDR device. The FRP double shear tests and three-point bending tests were conducted to verify the effectiveness of the proposed monitoring method. It is found that the early bebonding can be detected before it causes the interface failure. The sensing optic fiber shows signal changes in the slip value at about 36~156 micrometer which is beyond sensing capacity of the conventional sensors. The tests results show that the proposed method is feasible in slip measurement with high sensitivity, and would be cost effective because of the low price of sensors used, which shows its potential of large-scale applications in civil infrastructures, especially for bridges.

Metallic wear debris sensors: promising developments in failure prevention for wind turbine gearsets and similar components

NASA Astrophysics Data System (ADS)

Poley, Jack; Dines, Michael

2011-04-01

Wind turbines are frequently located in remote, hard-to-reach locations, making it difficult to apply traditional oil analysis sampling of the machine's critical gearset at timely intervals. Metal detection sensors are excellent candidates for sensors designed to monitor machine condition in vivo. Remotely sited components, such as wind turbines, therefore, can be comfortably monitored from a distance. Online sensor technology has come of age with products now capable of identifying onset of wear in time to avoid or mitigate failure. Online oil analysis is now viable, and can be integrated with onsite testing to vet sensor alarms, as well as traditional oil analysis, as furnished by offsite laboratories. Controlled laboratory research data were gathered from tests conducted on a typical wind turbine gearbox, wherein total ferrous particle measurement and metallic particle counting were employed and monitored. The results were then compared with a physical inspection for wear experienced by the gearset. The efficacy of results discussed herein strongly suggests the viability of metallic wear debris sensors in today's wind turbine gearsets, as correlation between sensor data and machine trauma were very good. By extension, similar components and settings would also seem amenable to wear particle sensor monitoring. To our knowledge no experiments such as described herein, have previously been conducted and published.

Operating systems and network protocols for wireless sensor networks.

PubMed

Dutta, Prabal; Dunkels, Adam

2012-01-13

Sensor network protocols exist to satisfy the communication needs of diverse applications, including data collection, event detection, target tracking and control. Network protocols to enable these services are constrained by the extreme resource scarcity of sensor nodes-including energy, computing, communications and storage-which must be carefully managed and multiplexed by the operating system. These challenges have led to new protocols and operating systems that are efficient in their energy consumption, careful in their computational needs and miserly in their memory footprints, all while discovering neighbours, forming networks, delivering data and correcting failures.

Outlier Detection for Sensor Systems (ODSS): A MATLAB Macro for Evaluating Microphone Sensor Data Quality.

PubMed

Vasta, Robert; Crandell, Ian; Millican, Anthony; House, Leanna; Smith, Eric

2017-10-13

Microphone sensor systems provide information that may be used for a variety of applications. Such systems generate large amounts of data. One concern is with microphone failure and unusual values that may be generated as part of the information collection process. This paper describes methods and a MATLAB graphical interface that provides rapid evaluation of microphone performance and identifies irregularities. The approach and interface are described. An application to a microphone array used in a wind tunnel is used to illustrate the methodology.

Nonlinear structural crack growth monitoring

DOEpatents

Welch, Donald E.; Hively, Lee M.; Holdaway, Ray F.

2002-01-01

A method and apparatus are provided for the detection, through nonlinear manipulation of data, of an indicator of imminent failure due to crack growth in structural elements. The method is a process of determining energy consumption due to crack growth and correlating the energy consumption with physical phenomena indicative of a failure event. The apparatus includes sensors for sensing physical data factors, processors or the like for computing a relationship between the physical data factors and phenomena indicative of the failure event, and apparatus for providing notification of the characteristics and extent of such phenomena.

Advancements of Data Anomaly Detection Research in Wireless Sensor Networks: A Survey and Open Issues

PubMed Central

Rassam, Murad A.; Zainal, Anazida; Maarof, Mohd Aizaini

2013-01-01

Wireless Sensor Networks (WSNs) are important and necessary platforms for the future as the concept “Internet of Things” has emerged lately. They are used for monitoring, tracking, or controlling of many applications in industry, health care, habitat, and military. However, the quality of data collected by sensor nodes is affected by anomalies that occur due to various reasons, such as node failures, reading errors, unusual events, and malicious attacks. Therefore, anomaly detection is a necessary process to ensure the quality of sensor data before it is utilized for making decisions. In this review, we present the challenges of anomaly detection in WSNs and state the requirements to design efficient and effective anomaly detection models. We then review the latest advancements of data anomaly detection research in WSNs and classify current detection approaches in five main classes based on the detection methods used to design these approaches. Varieties of the state-of-the-art models for each class are covered and their limitations are highlighted to provide ideas for potential future works. Furthermore, the reviewed approaches are compared and evaluated based on how well they meet the stated requirements. Finally, the general limitations of current approaches are mentioned and further research opportunities are suggested and discussed. PMID:23966182

A dual-processor multi-frequency implementation of the FINDS algorithm

NASA Technical Reports Server (NTRS)

Godiwala, Pankaj M.; Caglayan, Alper K.

1987-01-01

This report presents a parallel processing implementation of the FINDS (Fault Inferring Nonlinear Detection System) algorithm on a dual processor configured target flight computer. First, a filter initialization scheme is presented which allows the no-fail filter (NFF) states to be initialized using the first iteration of the flight data. A modified failure isolation strategy, compatible with the new failure detection strategy reported earlier, is discussed and the performance of the new FDI algorithm is analyzed using flight recorded data from the NASA ATOPS B-737 aircraft in a Microwave Landing System (MLS) environment. The results show that low level MLS, IMU, and IAS sensor failures are detected and isolated instantaneously, while accelerometer and rate gyro failures continue to take comparatively longer to detect and isolate. The parallel implementation is accomplished by partitioning the FINDS algorithm into two parts: one based on the translational dynamics and the other based on the rotational kinematics. Finally, a multi-rate implementation of the algorithm is presented yielding significantly low execution times with acceptable estimation and FDI performance.

Corrosivity Sensor for Exposed Pipelines Based on Wireless Energy Transfer

PubMed Central

Lawand, Lydia; Shiryayev, Oleg; Al Handawi, Khalil; Vahdati, Nader; Rostron, Paul

2017-01-01

External corrosion was identified as one of the main causes of pipeline failures worldwide. A solution that addresses the issue of detecting and quantifying corrosivity of environment for application to existing exposed pipelines has been developed. It consists of a sensing array made of an assembly of thin strips of pipeline steel and a circuit that provides a visual sensor reading to the operator. The proposed sensor is passive and does not require a constant power supply. Circuit design was validated through simulations and lab experiments. Accelerated corrosion experiment was conducted to confirm the feasibility of the proposed corrosivity sensor design. PMID:28556805

Landslide and Flood Warning System Prototypes based on Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Hloupis, George; Stavrakas, Ilias; Triantis, Dimos

2010-05-01

Wireless sensor networks (WSNs) are one of the emerging areas that received great attention during the last few years. This is mainly due to the fact that WSNs have provided scientists with the capability of developing real-time monitoring systems equipped with sensors based on Micro-Electro-Mechanical Systems (MEMS). WSNs have great potential for many applications in environmental monitoring since the sensor nodes that comprised from can host several MEMS sensors (such as temperature, humidity, inertial, pressure, strain-gauge) and transducers (such as position, velocity, acceleration, vibration). The resulting devices are small and inexpensive but with limited memory and computing resources. Each sensor node contains a sensing module which along with an RF transceiver. The communication is broadcast-based since the network topology can change rapidly due to node failures [1]. Sensor nodes can transmit their measurements to central servers through gateway nodes without any processing or they make preliminary calculations locally in order to produce results that will be sent to central servers [2]. Based on the above characteristics, two prototypes using WSNs are presented in this paper: A Landslide detection system and a Flood warning system. Both systems sent their data to central processing server where the core of processing routines exists. Transmission is made using Zigbee and IEEE 802.11b protocol but is capable to use VSAT communication also. Landslide detection system uses structured network topology. Each measuring node comprises of a columnar module that is half buried to the area under investigation. Each sensing module contains a geophone, an inclinometer and a set of strain gauges. Data transmitted to central processing server where possible landslide evolution is monitored. Flood detection system uses unstructured network topology since the failure rate of sensor nodes is expected higher. Each sensing module contains a custom water level sensor (based on plastic optical fiber). Data transmitted directly to server where the early warning algorithms monitor the water level variations in real time. Both sensor nodes use power harvesting techniques in order to extend their battery life as much as possible. [1] Yick J.; Mukherjee, B.; Ghosal, D. Wireless sensor network survey. Comput. Netw. 2008, 52, 2292-2330. [2] Garcia, M.; Bri, D.; Boronat, F.; Lloret, J. A new neighbor selection strategy for group-based wireless sensor networks, In The Fourth International Conference on Networking and Services (ICNS 2008), Gosier, Guadalupe, March 16-21, 2008.

Real-time Bayesian anomaly detection in streaming environmental data

NASA Astrophysics Data System (ADS)

Hill, David J.; Minsker, Barbara S.; Amir, Eyal

2009-04-01

With large volumes of data arriving in near real time from environmental sensors, there is a need for automated detection of anomalous data caused by sensor or transmission errors or by infrequent system behaviors. This study develops and evaluates three automated anomaly detection methods using dynamic Bayesian networks (DBNs), which perform fast, incremental evaluation of data as they become available, scale to large quantities of data, and require no a priori information regarding process variables or types of anomalies that may be encountered. This study investigates these methods' abilities to identify anomalies in eight meteorological data streams from Corpus Christi, Texas. The results indicate that DBN-based detectors, using either robust Kalman filtering or Rao-Blackwellized particle filtering, outperform a DBN-based detector using Kalman filtering, with the former having false positive/negative rates of less than 2%. These methods were successful at identifying data anomalies caused by two real events: a sensor failure and a large storm.

Temperature measurement and damage detection in concrete beams exposed to fire using PPP-BOTDA based fiber optic sensors

NASA Astrophysics Data System (ADS)

Bao, Yi; Hoehler, Matthew S.; Smith, Christopher M.; Bundy, Matthew; Chen, Genda

2017-10-01

In this study, Brillouin scattering-based distributed fiber optic sensor is implemented to measure temperature distributions and detect cracks in concrete structures subjected to fire for the first time. A telecommunication-grade optical fiber is characterized as a high temperature sensor with pulse pre-pump Brillouin optical time domain analysis (PPP-BODTA), and implemented to measure spatially-distributed temperatures in reinforced concrete beams in fire. Four beams were tested to failure in a natural gas fueled compartment fire, each instrumented with one fused silica, single-mode optical fiber as a distributed sensor and four thermocouples. Prior to concrete cracking, the distributed temperature was validated at locations of the thermocouples by a relative difference of less than 9%. The cracks in concrete can be identified as sharp peaks in the temperature distribution since the cracks are locally filled with hot air. Concrete cracking did not affect the sensitivity of the distributed sensor but concrete spalling broke the optical fiber loop required for PPP-BOTDA measurements.

A Method to have Multi-Layer Thermal Insulation Provide Damage Detection

NASA Technical Reports Server (NTRS)

Woodward, Stanley E.; Taylor, Bryant D.; Jones, Thomas W.; Shams, Qamar A.; Lyons, Frankel; Henderson, Donald

2007-01-01

Design and testing of a multi-layer thermal insulation system that also provides debris and micrometeorite damage detection is presented. One layer of the insulation is designed as an array of passive open-circuit electrically conductive spiral trace sensors. The sensors are a new class of sensors that are electrically open-circuits that have no electrical connections thereby eliminating one cause of failure to circuits. The sensors are powered using external oscillating magnetic fields. Once electrically active, they produce their own harmonic magnetic fields. The responding field frequency changes if any sensor is damaged. When the sensors are used together in close proximity, the inductive coupling between sensors provides a means of telemetry. The spiral trace design using reflective electrically conductive material provides sufficient area coverage for the sensor array to serves as a layer of thermal insulation. The other insulation layers are designed to allow the sensor s magnetic field to permeate the insulation layers while having total reflective surface area to reduce thermal energy transfer. Results of characterizing individual sensors and the sensor array s response to punctures are presented. Results of hypervelocity impact testing using projectiles of 1-3.6 millimeter diameter having speeds ranging from 6.7-7.1 kilometers per second are also presented.

Seismic damage identification using multi-line distributed fiber optic sensor system

NASA Astrophysics Data System (ADS)

Ou, Jinping; Hou, Shuang

2005-06-01

Determination of the actual nonlinear inelastic response mechanisms developed by civil structures such as buildings and bridges during strong earthquakes and post-earthquake damage assessment of these structures represent very difficult challenges for earthquake structural engineers. One of the main reasons is that the traditional sensor can't serve for such a long period to cover an earthquake and the seismic damage location in the structure can't be predicted in advance definitely. It is thought that the seismic damage of reinforced concrete (RC) structure can be related to the maximum response the structure, which can also be related to the cracks on the concrete. A distributed fiber optic sensor was developed to detect the cracks on the reinforced concrete structure under load. Fiber optic couples were used in the sensor system to extend the sensor system's capacity from one random point detection to more. An optical time domain reflectometer (OTDR) is employed for interrogation of the sensor signal. Fiber optic sensors are attached on the surface of the concrete by the epoxy glue. By choosing the strength of epoxy, the damage state of the concrete can be responded to the occurrence of the Fresnel scattering in the fiber optic sensor. Experiments involved monotonic loading to failure. Finally, the experimental results in terms of crack detection capability are presented and discussed.

Preliminary input to the space shuttle reaction control subsystem failure detection and identification software requirements (uncontrolled)

NASA Technical Reports Server (NTRS)

Bergmann, E.

1976-01-01

The current baseline method and software implementation of the space shuttle reaction control subsystem failure detection and identification (RCS FDI) system is presented. This algorithm is recommended for conclusion in the redundancy management (RM) module of the space shuttle guidance, navigation, and control system. Supporting software is presented, and recommended for inclusion in the system management (SM) and display and control (D&C) systems. RCS FDI uses data from sensors in the jets, in the manifold isolation valves, and in the RCS fuel and oxidizer storage tanks. A list of jet failures and fuel imbalance warnings is generated for use by the jet selection algorithm of the on-orbit and entry flight control systems, and to inform the crew and ground controllers of RCS failure status. Manifold isolation valve close commands are generated in the event of failed on or leaking jets to prevent loss of large quantities of RCS fuel.

Distributed fiber optic strain sensing to detect artificial pitting corrosion in stirrups

NASA Astrophysics Data System (ADS)

Zhang, Jiachen; Kancharla, Vinutha; Hoult, Neil A.

2017-04-01

Pitting corrosion is difficult to identify through visual inspection and can lead to sudden structural failures. As such, an experimental study was undertaken to investigate whether distributed fiber optic strain sensors are capable of detecting the locations and strain changes associated with stirrup corrosion in reinforced concrete beams. In comparison to conventional strain gauges, this type of sensor can measure the strain response along the entire length of the fiber optic cable. Two specimens were tested: a control and a deteriorated beam. The deteriorated beam was artificially corroded by reducing the cross sectional area of the closed stirrups by 50% on both sides of the stirrup at the mid-height. This level of area reduction represents severe pitting corrosion. The beams were instrumented with nylon coated fiber optic sensors to measure the distributed strains, and then tested to failure under three point bending. The load deflection behavior of the two specimens was compared to assess the impact of the artificial pitting corrosion on the capacity. Digital Image Correlation was used to locate the extent and trajectory of the crack paths. It was found that the pitting corrosion had no impact on capacity or stiffness. Also, in this investigation the fiber optic sensing system failed to detect the location and strain changes due to pitting corrosion since the shear cracks did not intersect with the pitting location.

Development of biosensors for non-invasive measurements of heart failure biomarkers in saliva

NASA Astrophysics Data System (ADS)

Alcacer, Albert; Streklas, Angelos; Baraket, Abdoullatif; Zine, Nadia; Errachid, Abdelhamid; Bausells, Joan

2017-06-01

Biomedical engineering research today is focused on non-invasive techniques for detection of biomarkers related to specific health issues 1. Three metal layer microelectrode (μE) sensors have been implemented to detect specific biomarkers which can be found in human saliva related with heart failure problems 2 such as interleukin and Tumore Necrosis Factor-α (TNF-α), and used as highly sensitive saliva sensors. We designed specialized μEs combining different technologies for multiple measurements aiming to a lab-on-a-chip future integration. Measurements are based to basic principles of Cyclic Voltammetry (CV) and Electrochemical Impedance Spectroscopy (EIS). Thus, certain planar technology was used involving three metal layers of gold, platinum and silver deposited over an oxidized silicon substrate following standard cleanroom procedures of lithography for the definition of μEs, sputtering physical vapor deposition (PVD) for gold, evaporation PVD for silver and platinum, and plasma enhanced chemical vapor deposition (PECVD) for passivation layer of silicon nitride.

Commercial Aircraft Integrated Vehicle Health Management Study

NASA Technical Reports Server (NTRS)

Reveley, Mary S.; Briggs, Jeffrey L.; Evans, Joni K.; Jones, Sharon Monica; Kurtoglu, Tolga; Leone, Karen M.; Sandifer, Carl E.; Thomas, Megan A.

2010-01-01

Statistical data and literature from academia, industry, and other government agencies were reviewed and analyzed to establish requirements for fixture work in detection, diagnosis, prognosis, and mitigation for IVHM related hardware and software. Around 15 to 20 percent of commercial aircraft accidents between 1988 and 2003 involved inalftfnctions or failures of some aircraft system or component. Engine and landing gear failures/malfunctions dominate both accidents and incidents. The IVI vl Project research technologies were found to map to the Joint Planning and Development Office's National Research and Development Plan (RDP) as well as the Safety Working Group's National Aviation Safety Strategic. Plan (NASSP). Future directions in Aviation Technology as related to IVHlvl were identified by reviewing papers from three conferences across a five year time span. A total of twenty-one trend groups in propulsion, aeronautics and aircraft categories were compiled. Current and ftiture directions of IVHM related technologies were gathered and classified according to eight categories: measurement and inspection, sensors, sensor management, detection, component and subsystem monitoring, diagnosis, prognosis, and mitigation.

External corrosion and leakage detection of oil and gas pipeline using FBG fiber optics and a trigger

NASA Astrophysics Data System (ADS)

Ge, Yaomou

Oil and gas pipelines play a critical role in delivering the energy resources from producing fields to power communities around the world. However, there are many threats to pipeline integrity, which may lead to significant incidents, causing safety, environmental and economic problems. Corrosion has been a big threat to oil and gas pipelines for a long time, which has attributed to approximately 18% of the significant incidents in oil and gas pipelines. In addition, external corrosion of pipelines accounts for a significant portion (more than 25%) of pipeline failure. External corrosion detection is the research area of this thesis. In this thesis, a review of existing corrosion detection or monitoring methods is presented, and optical fiber sensors show a great promise in corrosion detection of oil and gas pipelines. Several scenarios of optical fiber corrosion sensors are discussed, and two of them are selected for future research. A new corrosion and leakage detection sensor, consisting of a custom designed trigger and a FBG optical fiber, will be presented. This new device has been experimentally tested and it shows great promise.

Graphite nanoplatelet enabled embeddable fiber sensor for in situ curing monitoring and structural health monitoring of polymeric composites.

PubMed

Luo, Sida; Liu, Tao

2014-06-25

A graphite nanoplatelet (GNP) thin film enabled 1D fiber sensor (GNP-FibSen) was fabricated by a continuous roll-to-roll spray coating process, characterized by scanning electron microscopy and Raman spectroscopy and evaluated by coupled electrical-mechanical tensile testing. The neat GNP-FibSen sensor shows very high gauge sensitivity with a gauge factor of ∼17. By embedding the sensor in fiberglass prepreg laminate parts, the dual functionalities of the GNP-FibSen sensor were demonstrated. In the manufacturing process, the resistance change of the embedded sensor provides valuable local resin curing information. After the manufacturing process, the same sensor is able to map the strain/stress states and detect the failure of the host composite. The superior durability of the embedded GNP-FibSen sensor has been demonstrated through 10,000 cycles of coupled electromechanical tests.

Ampoule failure sensor time response testing: Experiment 1

NASA Technical Reports Server (NTRS)

Johnson, M. L.; Watring, D. A.

1994-01-01

The response time of an ampoule failure sensor exposed to a liquid or vapor gallium-arsenide (GaAs) is investigated. The experimental configuration represents the sample/ampoule cartridge assembly used in NASA's Crystal Growth Furnace (CGF). The sensor is a chemical fuse made from a metal with which the semiconductor material reacts more rapidly than it does with the containing cartridge. For the III-IV compound of GaAs, a platinum metal was chosen based on the reaction of platinum and arsenic at elevated temperatures which forms a low melting eutectic. Ampoule failure is indicated by a step change in resistance of the failure sensor on the order of megohms. The sensors will increase the safety of crystal growth experiments by providing an indication that an ampoule has failed. Experimental results indicate that the response times (after a known ampoule failure) for the 0.003 and 0.010 inch ampoule failure sensors are 2.4 and 3.6 minutes, respectively. This ampoule failure sensor will be utilized in the CGF during the second United States Microgravity Laboratory Mission (USML-2) and is the subject of a NASA patent application.

Malfunctions in radioactivity sensors' networks

NASA Astrophysics Data System (ADS)

Khalipova, Veronika; Damart, Guillaume; Beauzamy, Bernard; Bruna, Giovanni

2018-01-01

The capacity to promptly and efficiently detect any source of contamination of the environment (a radioactive cloud) at a local and a country scale is mandatory to a safe and secure exploitation of civil nuclear energy. It must rely upon a robust network of measurement devices, to be optimized vs. several parameters, including the overall reliability, the investment, the operation and maintenance costs. We show that a network can be arranged in different ways, but many of them are inadequate. Through simulations, we test the efficiency of several configurations of sensors, in the same domain. The denser arrangement turns out to be the more efficient, but the efficiency is increased when sensors are non-uniformly distributed over the country, with accumulation at the borders. In the case of France, as radioactive threats are most likely to come from the East, the best solution is densifying the sensors close to the eastern border. Our approach differs from previous work because it is "failure oriented": we determine the laws of probability for all types of failures and deduce in this respect the best organization of the network.

Real-Time Detection of Infusion Site Failures in a Closed-Loop Artificial Pancreas.

PubMed

Howsmon, Daniel P; Baysal, Nihat; Buckingham, Bruce A; Forlenza, Gregory P; Ly, Trang T; Maahs, David M; Marcal, Tatiana; Towers, Lindsey; Mauritzen, Eric; Deshpande, Sunil; Huyett, Lauren M; Pinsker, Jordan E; Gondhalekar, Ravi; Doyle, Francis J; Dassau, Eyal; Hahn, Juergen; Bequette, B Wayne

2018-05-01

As evidence emerges that artificial pancreas systems improve clinical outcomes for patients with type 1 diabetes, the burden of this disease will hopefully begin to be alleviated for many patients and caregivers. However, reliance on automated insulin delivery potentially means patients will be slower to act when devices stop functioning appropriately. One such scenario involves an insulin infusion site failure, where the insulin that is recorded as delivered fails to affect the patient's glucose as expected. Alerting patients to these events in real time would potentially reduce hyperglycemia and ketosis associated with infusion site failures. An infusion site failure detection algorithm was deployed in a randomized crossover study with artificial pancreas and sensor-augmented pump arms in an outpatient setting. Each arm lasted two weeks. Nineteen participants wore infusion sets for up to 7 days. Clinicians contacted patients to confirm infusion site failures detected by the algorithm and instructed on set replacement if failure was confirmed. In real time and under zone model predictive control, the infusion site failure detection algorithm achieved a sensitivity of 88.0% (n = 25) while issuing only 0.22 false positives per day, compared with a sensitivity of 73.3% (n = 15) and 0.27 false positives per day in the SAP arm (as indicated by retrospective analysis). No association between intervention strategy and duration of infusion sets was observed ( P = .58). As patient burden is reduced by each generation of advanced diabetes technology, fault detection algorithms will help ensure that patients are alerted when they need to manually intervene. Clinical Trial Identifier: www.clinicaltrials.gov,NCT02773875.

Detecting Solenoid Valve Deterioration in In-Use Electronic Diesel Fuel Injection Control Systems

PubMed Central

Tsai, Hsun-Heng; Tseng, Chyuan-Yow

2010-01-01

The diesel engine is the main power source for most agricultural vehicles. The control of diesel engine emissions is an important global issue. Fuel injection control systems directly affect fuel efficiency and emissions of diesel engines. Deterioration faults, such as rack deformation, solenoid valve failure, and rack-travel sensor malfunction, are possibly in the fuel injection module of electronic diesel control (EDC) systems. Among these faults, solenoid valve failure is most likely to occur for in-use diesel engines. According to the previous studies, this failure is a result of the wear of the plunger and sleeve, based on a long period of usage, lubricant degradation, or engine overheating. Due to the difficulty in identifying solenoid valve deterioration, this study focuses on developing a sensor identification algorithm that can clearly classify the usability of the solenoid valve, without disassembling the fuel pump of an EDC system for in-use agricultural vehicles. A diagnostic algorithm is proposed, including a feedback controller, a parameter identifier, a linear variable differential transformer (LVDT) sensor, and a neural network classifier. Experimental results show that the proposed algorithm can accurately identify the usability of solenoid valves. PMID:22163597

Detecting solenoid valve deterioration in in-use electronic diesel fuel injection control systems.

PubMed

Tsai, Hsun-Heng; Tseng, Chyuan-Yow

2010-01-01

The diesel engine is the main power source for most agricultural vehicles. The control of diesel engine emissions is an important global issue. Fuel injection control systems directly affect fuel efficiency and emissions of diesel engines. Deterioration faults, such as rack deformation, solenoid valve failure, and rack-travel sensor malfunction, are possibly in the fuel injection module of electronic diesel control (EDC) systems. Among these faults, solenoid valve failure is most likely to occur for in-use diesel engines. According to the previous studies, this failure is a result of the wear of the plunger and sleeve, based on a long period of usage, lubricant degradation, or engine overheating. Due to the difficulty in identifying solenoid valve deterioration, this study focuses on developing a sensor identification algorithm that can clearly classify the usability of the solenoid valve, without disassembling the fuel pump of an EDC system for in-use agricultural vehicles. A diagnostic algorithm is proposed, including a feedback controller, a parameter identifier, a linear variable differential transformer (LVDT) sensor, and a neural network classifier. Experimental results show that the proposed algorithm can accurately identify the usability of solenoid valves.

Fault Diagnostics for Turbo-Shaft Engine Sensors Based on a Simplified On-Board Model

PubMed Central

Lu, Feng; Huang, Jinquan; Xing, Yaodong

2012-01-01

Combining a simplified on-board turbo-shaft model with sensor fault diagnostic logic, a model-based sensor fault diagnosis method is proposed. The existing fault diagnosis method for turbo-shaft engine key sensors is mainly based on a double redundancies technique, and this can't be satisfied in some occasions as lack of judgment. The simplified on-board model provides the analytical third channel against which the dual channel measurements are compared, while the hardware redundancy will increase the structure complexity and weight. The simplified turbo-shaft model contains the gas generator model and the power turbine model with loads, this is built up via dynamic parameters method. Sensor fault detection, diagnosis (FDD) logic is designed, and two types of sensor failures, such as the step faults and the drift faults, are simulated. When the discrepancy among the triplex channels exceeds a tolerance level, the fault diagnosis logic determines the cause of the difference. Through this approach, the sensor fault diagnosis system achieves the objectives of anomaly detection, sensor fault diagnosis and redundancy recovery. Finally, experiments on this method are carried out on a turbo-shaft engine, and two types of faults under different channel combinations are presented. The experimental results show that the proposed method for sensor fault diagnostics is efficient. PMID:23112645

Fault diagnostics for turbo-shaft engine sensors based on a simplified on-board model.

PubMed

Lu, Feng; Huang, Jinquan; Xing, Yaodong

2012-01-01

Combining a simplified on-board turbo-shaft model with sensor fault diagnostic logic, a model-based sensor fault diagnosis method is proposed. The existing fault diagnosis method for turbo-shaft engine key sensors is mainly based on a double redundancies technique, and this can't be satisfied in some occasions as lack of judgment. The simplified on-board model provides the analytical third channel against which the dual channel measurements are compared, while the hardware redundancy will increase the structure complexity and weight. The simplified turbo-shaft model contains the gas generator model and the power turbine model with loads, this is built up via dynamic parameters method. Sensor fault detection, diagnosis (FDD) logic is designed, and two types of sensor failures, such as the step faults and the drift faults, are simulated. When the discrepancy among the triplex channels exceeds a tolerance level, the fault diagnosis logic determines the cause of the difference. Through this approach, the sensor fault diagnosis system achieves the objectives of anomaly detection, sensor fault diagnosis and redundancy recovery. Finally, experiments on this method are carried out on a turbo-shaft engine, and two types of faults under different channel combinations are presented. The experimental results show that the proposed method for sensor fault diagnostics is efficient.

Tapered Roller Bearing Damage Detection Using Decision Fusion Analysis

NASA Technical Reports Server (NTRS)

Dempsey, Paula J.; Kreider, Gary; Fichter, Thomas

2006-01-01

A diagnostic tool was developed for detecting fatigue damage of tapered roller bearings. Tapered roller bearings are used in helicopter transmissions and have potential for use in high bypass advanced gas turbine aircraft engines. A diagnostic tool was developed and evaluated experimentally by collecting oil debris data from failure progression tests conducted using health monitoring hardware. Failure progression tests were performed with tapered roller bearings under simulated engine load conditions. Tests were performed on one healthy bearing and three pre-damaged bearings. During each test, data from an on-line, in-line, inductance type oil debris sensor and three accelerometers were monitored and recorded for the occurrence of bearing failure. The bearing was removed and inspected periodically for damage progression throughout testing. Using data fusion techniques, two different monitoring technologies, oil debris analysis and vibration, were integrated into a health monitoring system for detecting bearing surface fatigue pitting damage. The data fusion diagnostic tool was evaluated during bearing failure progression tests under simulated engine load conditions. This integrated system showed improved detection of fatigue damage and health assessment of the tapered roller bearings as compared to using individual health monitoring technologies.

Analytical redundancy management mechanization and flight data analysis for the F-8 digital fly-by-wire aircraft flight control sensors

NASA Technical Reports Server (NTRS)

Deckert, J. C.

1983-01-01

The details are presented of an onboard digital computer algorithm designed to reliably detect and isolate the first failure in a duplex set of flight control sensors aboard the NASA F-8 digital fly-by-wire aircraft. The algorithm's successful flight test program is summarized, and specific examples are presented of algorithm behavior in response to software-induced signal faults, both with and without aircraft parameter modeling errors.

Dual permeability FEM models for distributed fiber optic sensors development

NASA Astrophysics Data System (ADS)

Aguilar-López, Juan Pablo; Bogaard, Thom

2017-04-01

Fiber optic cables are commonly known for being robust and reliable mediums for transferring information at the speed of light in glass. Billions of kilometers of cable have been installed around the world for internet connection and real time information sharing. Yet, fiber optic cable is not only a mean for information transfer but also a way to sense and measure physical properties of the medium in which is installed. For dike monitoring, it has been used in the past for detecting inner core and foundation temperature changes which allow to estimate water infiltration during high water events. The DOMINO research project, aims to develop a fiber optic based dike monitoring system which allows to directly sense and measure any pore pressure change inside the dike structure. For this purpose, questions like which location, how many sensors, which measuring frequency and which accuracy are required for the sensor development. All these questions may be initially answered with a finite element model which allows to estimate the effects of pore pressure change in different locations along the cross section while having a time dependent estimation of a stability factor. The sensor aims to monitor two main failure mechanisms at the same time; The piping erosion failure mechanism and the macro-stability failure mechanism. Both mechanisms are going to be modeled and assessed in detail with a finite element based dual permeability Darcy-Richards numerical solution. In that manner, it is possible to assess different sensing configurations with different loading scenarios (e.g. High water levels, rainfall events and initial soil moisture and permeability conditions). The results obtained for the different configurations are later evaluated based on an entropy based performance evaluation. The added value of this kind of modelling approach for the sensor development is that it allows to simultaneously model the piping erosion and macro-stability failure mechanisms in a time dependent manner. In that way, the estimated pore pressures may be related to the monitored one and to both failure mechanisms. Furthermore, the approach is intended to be used in a later stage for the real time monitoring of the failure.

Real time health monitoring and control system methodology for flexible space structures

NASA Astrophysics Data System (ADS)

Jayaram, Sanjay

This dissertation is concerned with the Near Real-time Autonomous Health Monitoring of Flexible Space Structures. The dynamics of multi-body flexible systems is uncertain due to factors such as high non-linearity, consideration of higher modal frequencies, high dimensionality, multiple inputs and outputs, operational constraints, as well as unexpected failures of sensors and/or actuators. Hence a systematic framework of developing a high fidelity, dynamic model of a flexible structural system needs to be understood. The fault detection mechanism that will be an integrated part of an autonomous health monitoring system comprises the detection of abnormalities in the sensors and/or actuators and correcting these detected faults (if possible). Applying the robust control law and the robust measures that are capable of detecting and recovering/replacing the actuators rectifies the actuator faults. The fault tolerant concept applied to the sensors will be in the form of an Extended Kalman Filter (EKF). The EKF is going to weigh the information coming from multiple sensors (redundant sensors used to measure the same information) and automatically identify the faulty sensors and weigh the best estimate from the remaining sensors. The mechanization is comprised of instrumenting flexible deployable panels (solar array) with multiple angular position and rate sensors connected to the data acquisition system. The sensors will give position and rate information of the solar panel in all three axes (i.e. roll, pitch and yaw). The position data corresponds to the steady state response and the rate data will give better insight on the transient response of the system. This is a critical factor for real-time autonomous health monitoring. MATLAB (and/or C++) software will be used for high fidelity modeling and fault tolerant mechanism.

A Diagnostic Approach for Electro-Mechanical Actuators in Aerospace Systems

NASA Technical Reports Server (NTRS)

Balaban, Edward; Saxena, Abhinav; Bansal, Prasun; Goebel, Kai Frank; Stoelting, Paul; Curran, Simon

2009-01-01

Electro-mechanical actuators (EMA) are finding increasing use in aerospace applications, especially with the trend towards all all-electric aircraft and spacecraft designs. However, electro-mechanical actuators still lack the knowledge base accumulated for other fielded actuator types, particularly with regard to fault detection and characterization. This paper presents a thorough analysis of some of the critical failure modes documented for EMAs and describes experiments conducted on detecting and isolating a subset of them. The list of failures has been prepared through an extensive Failure Modes and Criticality Analysis (FMECA) reference, literature review, and accessible industry experience. Methods for data acquisition and validation of algorithms on EMA test stands are described. A variety of condition indicators were developed that enabled detection, identification, and isolation among the various fault modes. A diagnostic algorithm based on an artificial neural network is shown to operate successfully using these condition indicators and furthermore, robustness of these diagnostic routines to sensor faults is demonstrated by showing their ability to distinguish between them and component failures. The paper concludes with a roadmap leading from this effort towards developing successful prognostic algorithms for electromechanical actuators.

OGUPSA sensor scheduling architecture and algorithm

NASA Astrophysics Data System (ADS)

Zhang, Zhixiong; Hintz, Kenneth J.

1996-06-01

This paper introduces a new architecture for a sensor measurement scheduler as well as a dynamic sensor scheduling algorithm called the on-line, greedy, urgency-driven, preemptive scheduling algorithm (OGUPSA). OGUPSA incorporates a preemptive mechanism which uses three policies, (1) most-urgent-first (MUF), (2) earliest- completed-first (ECF), and (3) least-versatile-first (LVF). The three policies are used successively to dynamically allocate and schedule and distribute a set of arriving tasks among a set of sensors. OGUPSA also can detect the failure of a task to meet a deadline as well as generate an optimal schedule in the sense of minimum makespan for a group of tasks with the same priorities. A side benefit is OGUPSA's ability to improve dynamic load balance among all sensors while being a polynomial time algorithm. Results of a simulation are presented for a simple sensor system.

A neural network-based estimator for the mixture ratio of the Space Shuttle Main Engine

NASA Astrophysics Data System (ADS)

Guo, T. H.; Musgrave, J.

1992-11-01

In order to properly utilize the available fuel and oxidizer of a liquid propellant rocket engine, the mixture ratio is closed loop controlled during main stage (65 percent - 109 percent power) operation. However, because of the lack of flight-capable instrumentation for measuring mixture ratio, the value of mixture ratio in the control loop is estimated using available sensor measurements such as the combustion chamber pressure and the volumetric flow, and the temperature and pressure at the exit duct on the low pressure fuel pump. This estimation scheme has two limitations. First, the estimation formula is based on an empirical curve fitting which is accurate only within a narrow operating range. Second, the mixture ratio estimate relies on a few sensor measurements and loss of any of these measurements will make the estimate invalid. In this paper, we propose a neural network-based estimator for the mixture ratio of the Space Shuttle Main Engine. The estimator is an extension of a previously developed neural network based sensor failure detection and recovery algorithm (sensor validation). This neural network uses an auto associative structure which utilizes the redundant information of dissimilar sensors to detect inconsistent measurements. Two approaches have been identified for synthesizing mixture ratio from measurement data using a neural network. The first approach uses an auto associative neural network for sensor validation which is modified to include the mixture ratio as an additional output. The second uses a new network for the mixture ratio estimation in addition to the sensor validation network. Although mixture ratio is not directly measured in flight, it is generally available in simulation and in test bed firing data from facility measurements of fuel and oxidizer volumetric flows. The pros and cons of these two approaches will be discussed in terms of robustness to sensor failures and accuracy of the estimate during typical transients using simulation data.

A neural network-based estimator for the mixture ratio of the Space Shuttle Main Engine

NASA Technical Reports Server (NTRS)

Guo, T. H.; Musgrave, J.

1992-01-01

In order to properly utilize the available fuel and oxidizer of a liquid propellant rocket engine, the mixture ratio is closed loop controlled during main stage (65 percent - 109 percent power) operation. However, because of the lack of flight-capable instrumentation for measuring mixture ratio, the value of mixture ratio in the control loop is estimated using available sensor measurements such as the combustion chamber pressure and the volumetric flow, and the temperature and pressure at the exit duct on the low pressure fuel pump. This estimation scheme has two limitations. First, the estimation formula is based on an empirical curve fitting which is accurate only within a narrow operating range. Second, the mixture ratio estimate relies on a few sensor measurements and loss of any of these measurements will make the estimate invalid. In this paper, we propose a neural network-based estimator for the mixture ratio of the Space Shuttle Main Engine. The estimator is an extension of a previously developed neural network based sensor failure detection and recovery algorithm (sensor validation). This neural network uses an auto associative structure which utilizes the redundant information of dissimilar sensors to detect inconsistent measurements. Two approaches have been identified for synthesizing mixture ratio from measurement data using a neural network. The first approach uses an auto associative neural network for sensor validation which is modified to include the mixture ratio as an additional output. The second uses a new network for the mixture ratio estimation in addition to the sensor validation network. Although mixture ratio is not directly measured in flight, it is generally available in simulation and in test bed firing data from facility measurements of fuel and oxidizer volumetric flows. The pros and cons of these two approaches will be discussed in terms of robustness to sensor failures and accuracy of the estimate during typical transients using simulation data.

Applicability of a Crack-Detection System for Use in Rotor Disk Spin Test Experiments Being Evaluated

NASA Technical Reports Server (NTRS)

Abdul-Aziz, Ali; Baaklini, George Y.; Roth, Don J.

2004-01-01

Engine makers and aviation safety government institutions continue to have a strong interest in monitoring the health of rotating components in aircraft engines to improve safety and to lower maintenance costs. To prevent catastrophic failure (burst) of the engine, they use nondestructive evaluation (NDE) and major overhauls for periodic inspections to discover any cracks that might have formed. The lowest cost fluorescent penetrant inspection NDE technique can fail to disclose cracks that are tightly closed during rest or that are below the surface. The NDE eddy current system is more effective at detecting both crack types, but it requires careful setup and operation and only a small portion of the disk can be practically inspected. So that sensor systems can sustain normal function in a severe environment, health-monitoring systems require the sensor system to transmit a signal if a crack detected in the component is above a predetermined length (but below the length that would lead to failure) and lastly to act neutrally upon the overall performance of the engine system and not interfere with engine maintenance operations. Therefore, more reliable diagnostic tools and high-level techniques for detecting damage and monitoring the health of rotating components are very essential in maintaining engine safety and reliability and in assessing life.

System and Method for Outlier Detection via Estimating Clusters

NASA Technical Reports Server (NTRS)

Iverson, David J. (Inventor)

2016-01-01

An efficient method and system for real-time or offline analysis of multivariate sensor data for use in anomaly detection, fault detection, and system health monitoring is provided. Models automatically derived from training data, typically nominal system data acquired from sensors in normally operating conditions or from detailed simulations, are used to identify unusual, out of family data samples (outliers) that indicate possible system failure or degradation. Outliers are determined through analyzing a degree of deviation of current system behavior from the models formed from the nominal system data. The deviation of current system behavior is presented as an easy to interpret numerical score along with a measure of the relative contribution of each system parameter to any off-nominal deviation. The techniques described herein may also be used to "clean" the training data.

Rule-based fault diagnosis of hall sensors and fault-tolerant control of PMSM

NASA Astrophysics Data System (ADS)

Song, Ziyou; Li, Jianqiu; Ouyang, Minggao; Gu, Jing; Feng, Xuning; Lu, Dongbin

2013-07-01

Hall sensor is widely used for estimating rotor phase of permanent magnet synchronous motor(PMSM). And rotor position is an essential parameter of PMSM control algorithm, hence it is very dangerous if Hall senor faults occur. But there is scarcely any research focusing on fault diagnosis and fault-tolerant control of Hall sensor used in PMSM. From this standpoint, the Hall sensor faults which may occur during the PMSM operating are theoretically analyzed. According to the analysis results, the fault diagnosis algorithm of Hall sensor, which is based on three rules, is proposed to classify the fault phenomena accurately. The rotor phase estimation algorithms, based on one or two Hall sensor(s), are initialized to engender the fault-tolerant control algorithm. The fault diagnosis algorithm can detect 60 Hall fault phenomena in total as well as all detections can be fulfilled in 1/138 rotor rotation period. The fault-tolerant control algorithm can achieve a smooth torque production which means the same control effect as normal control mode (with three Hall sensors). Finally, the PMSM bench test verifies the accuracy and rapidity of fault diagnosis and fault-tolerant control strategies. The fault diagnosis algorithm can detect all Hall sensor faults promptly and fault-tolerant control algorithm allows the PMSM to face failure conditions of one or two Hall sensor(s). In addition, the transitions between health-control and fault-tolerant control conditions are smooth without any additional noise and harshness. Proposed algorithms can deal with the Hall sensor faults of PMSM in real applications, and can be provided to realize the fault diagnosis and fault-tolerant control of PMSM.

Vibration monitoring via nano-composite piezoelectric foam bushings

NASA Astrophysics Data System (ADS)

Bird, Evan T.; Merrell, A. Jake; Anderson, Brady K.; Newton, Cory N.; Rosquist, Parker G.; Fullwood, David T.; Bowden, Anton E.; Seeley, Matthew K.

2016-11-01

Most mechanical systems produce vibrations as an inherent side effect of operation. Though some vibrations are acceptable in operation, others can cause damage or signal a machine’s imminent failure. These vibrations would optimally be monitored in real-time, without human supervision to prevent failure and excessive wear in machinery. This paper explores a new alternative to currently-used machine-monitoring equipment, namely a piezoelectric foam sensor system. These sensors are made of a silicone-based foam embedded with nano- and micro-scale conductive particles. Upon impact, they emit an electric response that is directly correlated with impact energy, with no electrical power input. In the present work, we investigated their utility as self-sensing bushings on machinery. These sensors were found to accurately detect both the amplitude and frequency of typical machine vibrations. The bushings could potentially save time and money over other vibration sensing mechanisms, while simultaneously providing a potential control input that could be utilized for correcting vibrational imbalance.

Fault Detection and Safety in Closed-Loop Artificial Pancreas Systems

PubMed Central

2014-01-01

Continuous subcutaneous insulin infusion pumps and continuous glucose monitors enable individuals with type 1 diabetes to achieve tighter blood glucose control and are critical components in a closed-loop artificial pancreas. Insulin infusion sets can fail and continuous glucose monitor sensor signals can suffer from a variety of anomalies, including signal dropout and pressure-induced sensor attenuations. In addition to hardware-based failures, software and human-induced errors can cause safety-related problems. Techniques for fault detection, safety analyses, and remote monitoring techniques that have been applied in other industries and applications, such as chemical process plants and commercial aircraft, are discussed and placed in the context of a closed-loop artificial pancreas. PMID:25049365

The research of single intersection sensor signal control based on section data

NASA Astrophysics Data System (ADS)

Liu, Yunxiang; Huang, Yue; Wang, Hao

2016-12-01

Propose a sensing signal intersection control design electronic license based on the design by setting the intersection readers to interact with active electronic tags equipped vehicles, vehicle information obtained on the road section. In the vehicle detection sensor may control the green density as evaluation criteria are extended when the vehicle is higher than the threshold, the green density continuity, whereas the switching phases. Induction showed improved control strategy can achieve real-time traffic signal control effectively in high saturation intersection, to overcome the traditional sensor control failure at high saturation drawbacks and improve the utilization of urban Intersection comparative analysis by simulation.

Method and apparatus for detection of catalyst failure on-board a motor vehicle using a dual oxygen sensor and an algorithm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Clemmens, W.B.; Koupal, J.W.; Sabourin, M.A.

1993-07-20

Apparatus is described for detecting motor vehicle exhaust gas catalytic converter deterioration comprising a first exhaust gas oxygen sensor adapted for communication with an exhaust stream before passage of the exhaust stream through a catalytic converter and a second exhaust gas oxygen sensor adapted for communication with the exhaust stream after passage of the exhaust stream through the catalytic converter, an on-board vehicle computational means, said computational means adapted to accept oxygen content signals from the before and after catalytic converter oxygen sensors and adapted to generate signal threshold values, said computational means adapted to compare over repeated time intervalsmore » the oxygen content signals to the signal threshold values and to store the output of the compared oxygen content signals, and in response after a specified number of time intervals for a specified mode of motor vehicle operation to determine and indicate a level of catalyst deterioration.« less

Diagnostic tolerance for missing sensor data

NASA Technical Reports Server (NTRS)

Scarl, Ethan A.

1989-01-01

For practical automated diagnostic systems to continue functioning after failure, they must not only be able to diagnose sensor failures but also be able to tolerate the absence of data from the faulty sensors. It is shown that conventional (associational) diagnostic methods will have combinatoric problems when trying to isolate faulty sensors, even if they adequately diagnose other components. Moreover, attempts to extend the operation of diagnostic capability past sensor failure will necessarily compound those difficulties. Model-based reasoning offers a structured alternative that has no special problems diagnosing faulty sensors and can operate gracefully when sensor data is missing.

Data Optical Networking Architecture Using Wavelength-Division Multiplexing Method for Optical Sensors

NASA Technical Reports Server (NTRS)

Nguyen, Hung D.

2008-01-01

Recently there has been a growth in the number of fiber optical sensors used for health monitoring in the hostile environment of commercial aircraft. Health monitoring to detect the onset of failure in structural systems from such causes as corrosion, stress corrosion cracking, and fatigue is a critical factor in safety as well in aircraft maintenance costs. This report presents an assessment of an analysis model of optical data networking architectures used for monitoring data signals among these optical sensors. Our model is focused on the design concept of the wavelength-division multiplexing (WDM) method since most of the optical sensors deployed in the aircraft for health monitoring typically operate in a wide spectrum of optical wavelengths from 710 to 1550 nm.

Failure Analysis of CCD Image Sensors Using SQUID and GMR Magnetic Current Imaging

NASA Technical Reports Server (NTRS)

Felt, Frederick S.

2005-01-01

During electrical testing of a Full Field CCD Image Senor, electrical shorts were detected on three of six devices. These failures occurred after the parts were soldered to the PCB. Failure analysis was performed to determine the cause and locations of these failures on the devices. After removing the fiber optic faceplate, optical inspection was performed on the CCDs to understand the design and package layout. Optical inspection revealed that the device had a light shield ringing the CCD array. This structure complicated the failure analysis. Alternate methods of analysis were considered, including liquid crystal, light and thermal emission, LT/A, TT/A SQUID, and MP. Of these, SQUID and MP techniques were pursued for further analysis. Also magnetoresistive current imaging technology is discussed and compared to SQUID.

Large Scale Application of Vibration Sensors for Fan Monitoring at Commercial Layer Hen Houses

PubMed Central

Chen, Yan; Ni, Ji-Qin; Diehl, Claude A.; Heber, Albert J.; Bogan, Bill W.; Chai, Li-Long

2010-01-01

Continuously monitoring the operation of each individual fan can significantly improve the measurement quality of aerial pollutant emissions from animal buildings that have a large number of fans. To monitor the fan operation by detecting the fan vibration is a relatively new technique. A low-cost electronic vibration sensor was developed and commercialized. However, its large scale application has not yet been evaluated. This paper presents long-term performance results of this vibration sensor at two large commercial layer houses. Vibration sensors were installed on 164 fans of 130 cm diameter to continuously monitor the fan on/off status for two years. The performance of the vibration sensors was compared with fan rotational speed (FRS) sensors. The vibration sensors exhibited quick response and high sensitivity to fan operations and therefore satisfied the general requirements of air quality research. The study proved that detecting fan vibration was an effective method to monitor the on/off status of a large number of single-speed fans. The vibration sensor itself was $2 more expensive than a magnetic proximity FRS sensor but the overall cost including installation and data acquisition hardware was $77 less expensive than the FRS sensor. A total of nine vibration sensors failed during the study and the failure rate was related to the batches of product. A few sensors also exhibited unsteady sensitivity. As a new product, the quality of the sensor should be improved to make it more reliable and acceptable. PMID:22163544

Hybrid Bearing Prognostic Test Rig

NASA Technical Reports Server (NTRS)

Dempsey, Paula J.; Certo, Joseph M.; Handschuh, Robert F.; Dimofte, Florin

2005-01-01

The NASA Glenn Research Center has developed a new Hybrid Bearing Prognostic Test Rig to evaluate the performance of sensors and algorithms in predicting failures of rolling element bearings for aeronautics and space applications. The failure progression of both conventional and hybrid (ceramic rolling elements, metal races) bearings can be tested from fault initiation to total failure. The effects of different lubricants on bearing life can also be evaluated. Test conditions monitored and recorded during the test include load, oil temperature, vibration, and oil debris. New diagnostic research instrumentation will also be evaluated for hybrid bearing damage detection. This paper summarizes the capabilities of this new test rig.

[Implantable sensors for outpatient assessment of ventricular filling pressure in advanced heart failure : Which telemonitoring design is optimal?

PubMed

Herrmann, E; Fichtlscherer, S; Hohnloser, S H; Zeiher, A M; Aßmus, B

2016-12-01

Patients with advanced heart failure suffer from frequent hospitalizations. Non-invasive hemodynamic telemonitoring for assessment of ventricular filling pressure has been shown to reduce hospitalizations. We report on the right ventricular (RVP), the pulmonary artery (PAP) and the left atrial pressure (LAP) sensor for non-invasive assessment of the ventricular filling pressure. A literature search concerning the available implantable pressure sensors for noninvasive haemodynamic telemonitoring in patients with advanced heart failure was performed. Until now, only implantation of the PAP-sensor was able to reduce hospitalizations for cardiac decompensation and to improve quality of life. The right ventricular pressure sensor missed the primary endpoint of a significant reduction of hospitalizations, clinical data using the left atrial pressure sensor are still pending. The implantation of a pressure sensor for assessment of pulmonary artery filling pressure is suitable for reducing hospitalizations for heart failure and for improving quality of life in patients with advanced heart failure.

Inferring Gear Damage from Oil-Debris and Vibration Data

NASA Technical Reports Server (NTRS)

Dempsey, Paula

2006-01-01

A system for real-time detection of surface-fatigue-pitting damage to gears for use in a helicopter transmission is based on fuzzy-logic used to fuse data from sensors that measure oil-borne debris, referred to as "oil debris" in the article, and vibration signatures. A system to detect helicopter-transmission gear damage is beneficial because the power train of a helicopter is essential for propulsion, lift, and maneuvering, hence, the integrity of the transmission is critical to helicopter safety. To enable detection of an impending transmission failure, an ideal diagnostic system should provide real-time monitoring of the "health" of the transmission, be capable of a high level of reliable detection (with minimization of false alarms), and provide human users with clear information on the health of the system without making it necessary for them to interpret large amounts of sensor data.

Integrated condition monitoring of a fleet of offshore wind turbines with focus on acceleration streaming processing

NASA Astrophysics Data System (ADS)

Helsen, Jan; Gioia, Nicoletta; Peeters, Cédric; Jordaens, Pieter-Jan

2017-05-01

Particularly offshore there is a trend to cluster wind turbines in large wind farms, and in the near future to operate such a farm as an integrated power production plant. Predictability of individual turbine behavior across the entire fleet is key in such a strategy. Failure of turbine subcomponents should be detected well in advance to allow early planning of all necessary maintenance actions; Such that they can be performed during low wind and low electricity demand periods. In order to obtain the insights to predict component failure, it is necessary to have an integrated clean dataset spanning all turbines of the fleet for a sufficiently long period of time. This paper illustrates our big-data approach to do this. In addition, advanced failure detection algorithms are necessary to detect failures in this dataset. This paper discusses a multi-level monitoring approach that consists of a combination of machine learning and advanced physics based signal-processing techniques. The advantage of combining different data sources to detect system degradation is in the higher certainty due to multivariable criteria. In order to able to perform long-term acceleration data signal processing at high frequency a streaming processing approach is necessary. This allows the data to be analysed as the sensors generate it. This paper illustrates this streaming concept on 5kHz acceleration data. A continuous spectrogram is generated from the data-stream. Real-life offshore wind turbine data is used. Using this streaming approach for calculating bearing failure features on continuous acceleration data will support failure propagation detection.

Investigation of Tapered Roller Bearing Damage Detection Using Oil Debris Analysis

NASA Technical Reports Server (NTRS)

Dempsey, Paula J.; Krieder, Gary; Fichter, Thomas

2006-01-01

A diagnostic tool was developed for detecting fatigue damage to tapered roller bearings. Tapered roller bearings are used in helicopter transmissions and have potential for use in high bypass advanced gas turbine aircraft engines. This diagnostic tool was developed and evaluated experimentally by collecting oil debris data from failure progression tests performed by The Timken Company in their Tapered Roller Bearing Health Monitoring Test Rig. Failure progression tests were performed under simulated engine load conditions. Tests were performed on one healthy bearing and three predamaged bearings. During each test, data from an on-line, in-line, inductance type oil debris sensor was monitored and recorded for the occurrence of debris generated during failure of the bearing. The bearing was removed periodically for inspection throughout the failure progression tests. Results indicate the accumulated oil debris mass is a good predictor of damage on tapered roller bearings. The use of a fuzzy logic model to enable an easily interpreted diagnostic metric was proposed and demonstrated.

Efficient Actor Recovery Paradigm for Wireless Sensor and Actor Networks

PubMed Central

Mahjoub, Reem K.; Elleithy, Khaled

2017-01-01

The actor nodes are the spine of wireless sensor and actor networks (WSANs) that collaborate to perform a specific task in an unverified and uneven environment. Thus, there is a possibility of high failure rate in such unfriendly scenarios due to several factors such as power consumption of devices, electronic circuit failure, software errors in nodes or physical impairment of the actor nodes and inter-actor connectivity problem. Therefore, it is extremely important to discover the failure of a cut-vertex actor and network-disjoint in order to improve the Quality-of-Service (QoS). In this paper, we propose an Efficient Actor Recovery (EAR) paradigm to guarantee the contention-free traffic-forwarding capacity. The EAR paradigm consists of a Node Monitoring and Critical Node Detection (NMCND) algorithm that monitors the activities of the nodes to determine the critical node. In addition, it replaces the critical node with backup node prior to complete node-failure which helps balancing the network performance. The packets are handled using Network Integration and Message Forwarding (NIMF) algorithm that determines the source of forwarding the packets; either from actor or sensor. This decision-making capability of the algorithm controls the packet forwarding rate to maintain the network for a longer time. Furthermore, for handling the proper routing strategy, Priority-Based Routing for Node Failure Avoidance (PRNFA) algorithm is deployed to decide the priority of the packets to be forwarded based on the significance of information available in the packet. To validate the effectiveness of the proposed EAR paradigm, the proposed algorithms were tested using OMNET++ simulation. PMID:28420102

Efficient Actor Recovery Paradigm for Wireless Sensor and Actor Networks.

PubMed

Mahjoub, Reem K; Elleithy, Khaled

2017-04-14

The actor nodes are the spine of wireless sensor and actor networks (WSANs) that collaborate to perform a specific task in an unverified and uneven environment. Thus, there is a possibility of high failure rate in such unfriendly scenarios due to several factors such as power consumption of devices, electronic circuit failure, software errors in nodes or physical impairment of the actor nodes and inter-actor connectivity problem. Therefore, it is extremely important to discover the failure of a cut-vertex actor and network-disjoint in order to improve the Quality-of-Service (QoS). In this paper, we propose an Efficient Actor Recovery (EAR) paradigm to guarantee the contention-free traffic-forwarding capacity. The EAR paradigm consists of a Node Monitoring and Critical Node Detection (NMCND) algorithm that monitors the activities of the nodes to determine the critical node. In addition, it replaces the critical node with backup node prior to complete node-failure which helps balancing the network performance. The packets are handled using Network Integration and Message Forwarding (NIMF) algorithm that determines the source of forwarding the packets; either from actor or sensor. This decision-making capability of the algorithm controls the packet forwarding rate to maintain the network for a longer time. Furthermore, for handling the proper routing strategy, Priority-Based Routing for Node Failure Avoidance (PRNFA) algorithm is deployed to decide the priority of the packets to be forwarded based on the significance of information available in the packet. To validate the effectiveness of the proposed EAR paradigm, the proposed algorithms were tested using OMNET++ simulation.

Detecting unknown attacks in wireless sensor networks that contain mobile nodes.

PubMed

Banković, Zorana; Fraga, David; Moya, José M; Vallejo, Juan Carlos

2012-01-01

As wireless sensor networks are usually deployed in unattended areas, security policies cannot be updated in a timely fashion upon identification of new attacks. This gives enough time for attackers to cause significant damage. Thus, it is of great importance to provide protection from unknown attacks. However, existing solutions are mostly concentrated on known attacks. On the other hand, mobility can make the sensor network more resilient to failures, reactive to events, and able to support disparate missions with a common set of sensors, yet the problem of security becomes more complicated. In order to address the issue of security in networks with mobile nodes, we propose a machine learning solution for anomaly detection along with the feature extraction process that tries to detect temporal and spatial inconsistencies in the sequences of sensed values and the routing paths used to forward these values to the base station. We also propose a special way to treat mobile nodes, which is the main novelty of this work. The data produced in the presence of an attacker are treated as outliers, and detected using clustering techniques. These techniques are further coupled with a reputation system, in this way isolating compromised nodes in timely fashion. The proposal exhibits good performances at detecting and confining previously unseen attacks, including the cases when mobile nodes are compromised.

Algorithmic network monitoring for a modern water utility: a case study in Jerusalem.

PubMed

Armon, A; Gutner, S; Rosenberg, A; Scolnicov, H

2011-01-01

We report on the design, deployment, and use of TaKaDu, a real-time algorithmic Water Infrastructure Monitoring solution, with a strong focus on water loss reduction and control. TaKaDu is provided as a commercial service to several customers worldwide. It has been in use at HaGihon, the Jerusalem utility, since mid 2009. Water utilities collect considerable real-time data from their networks, e.g. by means of a SCADA system and sensors measuring flow, pressure, and other data. We discuss how an algorithmic statistical solution analyses this wealth of raw data, flexibly using many types of input and picking out and reporting significant events and failures in the network. Of particular interest to most water utilities is the early detection capability for invisible leaks, also a means for preventing large visible bursts. The system also detects sensor and SCADA failures, various water quality issues, DMA boundary breaches, unrecorded or unintended network changes (like a valve or pump state change), and other events, including types unforeseen during system design. We discuss results from use at HaGihon, showing clear operational value.

Development of Acceleration Sensor and Acceleration Evaluation System for Super-Low-Range Frequencies

NASA Astrophysics Data System (ADS)

Asano, Shogo; Matsumoto, Hideki

2001-05-01

This paper describes the development process for acceleration sensors used on automobiles and an acceleration evaluation system designed specifically for acceleration at super-low-range frequencies. The features of the newly developed sensor are as follows. 1) Original piezo-bimorph design based on a disc-center-fixed structure achieves pyroeffect cancelling and stabilization of sensor characteristics and enables the detection of the acceleration of 0.0009 G at the super-low-range-frequency of 0.03 Hz. 2) The addition of a self-diagnostic function utilizing the characteristics of piezoceramics enables constant monitoring of sensor failure. The frequency range of acceleration for accurate vehicle motion control is considered to be from DC to about 50 Hz. However, the measurement of acceleration in the super-low-range frequency near DC has been difficult because of mechanical and electrical noise interruption. This has delayed the development of the acceleration sensor for automotive use. We have succeeded in the development of an acceleration evaluation system for super-low-range frequencies from 0.015 Hz to 2 Hz with detection of the acceleration range from 0.0002 G (0.2 gal) to 1 G, as well as the development of a piezoelectric-type acceleration sensor for automotive use.

Finite Energy and Bounded Attacks on Control System Sensor Signals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Djouadi, Seddik M; Melin, Alexander M; Ferragut, Erik M

Control system networks are increasingly being connected to enterprise level networks. These connections leave critical industrial controls systems vulnerable to cyber-attacks. Most of the effort in protecting these cyber-physical systems (CPS) has been in securing the networks using information security techniques and protection and reliability concerns at the control system level against random hardware and software failures. However, besides these failures the inability of information security techniques to protect against all intrusions means that the control system must be resilient to various signal attacks for which new analysis and detection methods need to be developed. In this paper, sensor signalmore » attacks are analyzed for observer-based controlled systems. The threat surface for sensor signal attacks is subdivided into denial of service, finite energy, and bounded attacks. In particular, the error signals between states of attack free systems and systems subject to these attacks are quantified. Optimal sensor and actuator signal attacks for the finite and infinite horizon linear quadratic (LQ) control in terms of maximizing the corresponding cost functions are computed. The closed-loop system under optimal signal attacks are provided. Illustrative numerical examples are provided together with an application to a power network with distributed LQ controllers.« less

Initial flight results of the TRMM Kalman filter

NASA Technical Reports Server (NTRS)

Andrews, Stephen F.; Morgenstern, Wendy M.

1998-01-01

The Tropical Rainfall Measuring Mission (TRMM) spacecraft is a nadir pointing spacecraft that nominally controls attitude based on the Earth Sensor Assembly (ESA) output. After a potential single point failure in the ESA was identified, the contingency attitude determination method chosen to backup the ESA-based system was a sixth-order extended Kalman filter that uses magnetometer and digital sun sensor measurements. A brief description of the TRMM Kalman filter will be given, including some implementation issues and algorithm heritage. Operational aspects of the Kalman filter and some failure detection and correction will be described. The Kalman filter was tested in a sun pointing attitude and in a nadir pointing attitude during the in-orbit checkout period, and results from those tests will be presented. This paper will describe some lessons learned from the experience of the TRMM team.

Initial Flight Results of the TRMM Kalman Filter

NASA Technical Reports Server (NTRS)

Andrews, Stephen F.; Morgenstern, Wendy M.

1998-01-01

The Tropical Rainfall Measuring Mission (TRMM) spacecraft is a nadir pointing spacecraft that nominally controls attitude based on the Earth Sensor Assembly (ESA) output. After a potential single point failure in the ESA was identified, the contingency attitude determination method chosen to backup the ESA-based system was a sixth-order extended Kalman filter that uses magnetometer and digital sun sensor measurements. A brief description of the TRMM Kalman filter will be given, including some implementation issues and algorithm heritage. Operational aspects of the Kalman filter and some failure detection and correction will be described. The Kalman filter was tested in a sun pointing attitude and in a nadir pointing attitude during the in-orbit checkout period, and results from those tests will be presented. This paper will describe some lessons learned from the experience of the TRMM team.

Distributed optical fibre sensing for early detection of shallow landslides triggering.

PubMed

Schenato, Luca; Palmieri, Luca; Camporese, Matteo; Bersan, Silvia; Cola, Simonetta; Pasuto, Alessandro; Galtarossa, Andrea; Salandin, Paolo; Simonini, Paolo

2017-10-31

A distributed optical fibre sensing system is used to measure landslide-induced strains on an optical fibre buried in a large scale physical model of a slope. The fibre sensing cable is deployed at the predefined failure surface and interrogated by means of optical frequency domain reflectometry. The strain evolution is measured with centimetre spatial resolution until the occurrence of the slope failure. Standard legacy sensors measuring soil moisture and pore water pressure are installed at different depths and positions along the slope for comparison and validation. The evolution of the strain field is related to landslide dynamics with unprecedented resolution and insight. In fact, the results of the experiment clearly identify several phases within the evolution of the landslide and show that optical fibres can detect precursory signs of failure well before the collapse, paving the way for the development of more effective early warning systems.

Improving detection and identification of seismic signals due to landslides: a methodology based on field scale controlled experiments

NASA Astrophysics Data System (ADS)

Yfantis, G.; Carvajal, H. E.; Pytharouli, S.; Lunn, R. J.

2013-12-01

A number of published studies use seismic sensors to understand the physics involved in slope deformation. In this research we artificially induce failure to two meter scaled slopes in the field and use 12 short period 3D seismometers to monitor the failure. To our knowledge there has been no previous controlled experiments that can allow calibration and validation of the interpreted seismic signals. Inside the body of one of the artificial landslides we embed a pile of glass shards. During movement the pile deforms emitting seismic signals due to friction among the glass shards. Our aim is twofold: First we investigate whether the seismic sensors can record pre-cursory and failure signals. Secondly, we test our hypothesis that the glass shards produce seismic signals with higher amplitudes and a distinct frequency pattern, compared to those emitted by common landslide seismicity and local background noise. Two vertical faces, 2m high, were excavated 3m apart in high porous tropical clay. This highly attenuating material makes the detection of weak seismic signals challenging. Slope failure was induced by increasing the vertical load at the landslide's crown. Special care was taken in the design of all experimental procedures to not add to the area's seismic noise. Measurements took place during 18 hours (during afternoon and night) without any change in soil and weather conditions. The 3D sensors were placed on the ground surface close to the crown, forming a dense microseismic network with 5-to-10m spacing and two nanoseismic arrays, with aperture sizes of 10 and 20 m. This design allowed a direct comparison of the recorded signals emitted by the two landslides. The two faces failed for loading between 70 and 100kN and as a result the pile of glass shards was horizontally deformed allowing differential movement between the shards. After the main failure both landslides were continuing to deform due to soil compaction and horizontal displacement. We apply signal processing techniques to identify and locate the emitted signals related to slope movement, despite high background noise levels and high attenuating geological conditions. Results were groundproofed by visual observations. Our study shows that short period seismic sensors can successfully monitor the brittle behaviour of dry clays for deformations larger than 1 centimetre, as well as weak ground failures. The use of glass, or any other coarse and brittle material, has advantages over soil only, since the friction among the glass shards allows for a more distinct frequency pattern. This makes detection of slope movements easier at heterogeneous environments were signals are emitted following movements of different material types as well as in areas characterised by high background noise levels. Our results provide information on the slope behaviour, a powerful tool for geotechnical engineering applications.

Focus on Mechanical Failures: Mechanisms and Detection. Proceedings of the Meeting (45th) of the Mechanical Failures Prevention Group Held in Annapolis, Maryland on April 9 - 11, 1999

DTIC Science & Technology

1991-04-04

solution to this immediate problem and, as the technology developed, opened doors to applied tribology for advanced maintenance through Mechanical Systems...Integrity Management. The development of other technologies as well enhanced Spectron’s capability, but it was the major advances in electronics and...strain gages will also be studied. The results of this program will provide a basis for future work in the area of advanced sensor technology . ONCUBSIONS

Robust Fault Detection for Aircraft Using Mixed Structured Singular Value Theory and Fuzzy Logic

NASA Technical Reports Server (NTRS)

Collins, Emmanuel G.

2000-01-01

The purpose of fault detection is to identify when a fault or failure has occurred in a system such as an aircraft or expendable launch vehicle. The faults may occur in sensors, actuators, structural components, etc. One of the primary approaches to model-based fault detection relies on analytical redundancy. That is the output of a computer-based model (actually a state estimator) is compared with the sensor measurements of the actual system to determine when a fault has occurred. Unfortunately, the state estimator is based on an idealized mathematical description of the underlying plant that is never totally accurate. As a result of these modeling errors, false alarms can occur. This research uses mixed structured singular value theory, a relatively recent and powerful robustness analysis tool, to develop robust estimators and demonstrates the use of these estimators in fault detection. To allow qualitative human experience to be effectively incorporated into the detection process fuzzy logic is used to predict the seriousness of the fault that has occurred.

Gyro-based Maximum-Likelihood Thruster Fault Detection and Identification

NASA Technical Reports Server (NTRS)

Wilson, Edward; Lages, Chris; Mah, Robert; Clancy, Daniel (Technical Monitor)

2002-01-01

When building smaller, less expensive spacecraft, there is a need for intelligent fault tolerance vs. increased hardware redundancy. If fault tolerance can be achieved using existing navigation sensors, cost and vehicle complexity can be reduced. A maximum likelihood-based approach to thruster fault detection and identification (FDI) for spacecraft is developed here and applied in simulation to the X-38 space vehicle. The system uses only gyro signals to detect and identify hard, abrupt, single and multiple jet on- and off-failures. Faults are detected within one second and identified within one to five accords,

Preliminary Study on Acoustic Detection of Faults Experienced by a High-Bypass Turbofan Engine

NASA Technical Reports Server (NTRS)

Boyle, Devin K.

2014-01-01

The vehicle integrated propulsion research (VIPR) effort conducted by NASA and several partners provided an unparalleled opportunity to test a relatively low TRL concept regarding the use of far field acoustics to identify faults occurring in a high bypass turbofan engine. Though VIPR Phase II ground based aircraft installed engine testing wherein a multitude of research sensors and methods were evaluated, an array of acoustic microphones was used to determine the viability of such an array to detect failures occurring in a commercially representative high bypass turbofan engine. The failures introduced during VIPR testing included commanding the engine's low pressure compressor (LPC) exit and high pressure compressor (HPC) 14th stage bleed values abruptly to their failsafe positions during steady state

Failure monitoring of E-glass/vinylester composites using fiber grating acoustic sensor

NASA Astrophysics Data System (ADS)

Azmi, A. I.; Raju; Peng, G. D.

2013-06-01

This paper reports an application of an optical fiber sensor in a continuous and in situ failure testing of an E-glass/vinylester top hat stiffener (THS). The sensor head was constructed from a compact phase-shifted fiber Bragg grating (PS-FBG). The narrow transmission channel of the PS-FBG is highly sensitive to small perturbation, hence suitable to be used in acoustic emission (AE) assessment technique. The progressive failure of THS was tested under transverse loading to experimentally simulate the actual loading in practice. Our experimental tests have demonstrated, in good agreement with the commercial piezoelectric sensors, that the important failures information of the THS was successfully recorded by the simple intensity-type PS-FBG sensor.

Design and evaluation of a high sensitivity spiral TDR scour sensor

NASA Astrophysics Data System (ADS)

Gao, Quan; (Bill Yu, Xiong

2015-08-01

Bridge scour accounts for more than half of the reported bridge failures in the United States. Scour monitoring technology based on time domain reflectometry (TDR) features the advantages of being automatic and inexpensive. The senior author’s team has developed a few generations of a TDR bridge scour monitoring system, which have succeeded in both laboratory and field evaluations. In this study, an innovative spiral TDR sensor is proposed to further improve the sensitivity of the TDR sensor in scour detection. The spiral TDR sensor is made of a parallel copper wire waveguide wrapped around a mounting rod. By using a spiral path for the waveguide, the TDR sensor achieves higher sensitivity than the traditional straight TDR probes due to longer travel distance of the electromagnetic (EM) wave per unit length in the spiral probe versus traditional probe. The performance of the new TDR spiral scour sensor is validated by calibration with liquids with known dielectric constant and wet soils. Laboratory simulated scour-refilling experiments are performed to evaluate the performance of the new spiral probe in detecting the sediment-water interface and therefore the scour-refill process. The tests results indicate that scour depth variation of less than 2 cm can be easily detected by this new spiral sensor. A theory is developed based on the dielectric mixing model to simplify the TDR signal analyses for scour depth detection. The sediment layer thickness (directly related to scour depth) varies linearly with the square root of the bulk dielectric constant of the water-sediment mixture measured by the spiral TDR probe, which matches the results of theoretical prediction. The estimated sediment layer thickness and therefore scour depth from the spiral TDR sensor agrees very well with that by direct physical measurement. The spiral TDR sensor is four times more sensitive than a traditional straight TDR probe.

Continuous glucose monitoring: quality of hypoglycaemia detection.

PubMed

Zijlstra, E; Heise, T; Nosek, L; Heinemann, L; Heckermann, S

2013-02-01

To evaluate the accuracy of a (widely used) continuous glucose monitoring (CGM)-system and its ability to detect hypoglycaemic events. A total of 18 patients with type 1 diabetes mellitus used continuous glucose monitoring (Guardian REAL-Time CGMS) during two 9-day in-house periods. A hypoglycaemic threshold alarm alerted patients to sensor readings <70 mg/dl. Continuous glucose monitoring sensor readings were compared to laboratory reference measurements taken every 4 h and in case of a hypoglycaemic alarm. A total of 2317 paired data points were evaluated. Overall, the mean absolute relative difference (MARD) was 16.7%. The percentage of data points in the clinically accurate or acceptable Clarke Error Grid zones A + B was 94.6%. In the hypoglycaemic range, accuracy worsened (MARD 38.8%) leading to a failure to detect more than half of the true hypoglycaemic events (sensitivity 37.5%). Furthermore, more than half of the alarms that warn patients for hypoglycaemia were false (false alert rate 53.3%). Above the low alert threshold, the sensor confirmed 2077 of 2182 reference values (specificity 95.2%). Patients using continuous glucose monitoring should be aware of its limitation to accurately detect hypoglycaemia. © 2012 Blackwell Publishing Ltd.

Deployment of an inductance-based quasi-digital sensor to detect metallic wear debris in lubricant oil of rotating machinery

NASA Astrophysics Data System (ADS)

Sanga, Ramesh; Srinivasan, V. S.; Sivaramakrishna, M.; Prabhakara Rao, G.

2018-07-01

In rotating machinery due to continuous rotational induced wear and tear, metallic debris will be produced and mixes with the in-service lubricant oil over the course of time. This debris gives the sign of potential machine failure due to the aging of critical parts like gears and bearings. The size and type of wear debris has a direct relationship with the degree of wear in the machine and gives information about the healthiness of equipment. This article presents an inductive quasi-digital sensor to detect the metallic debris, its type; size in the lubrication oil of rotating machinery. A microcontroller based low cost, low power, high resolution and high precise instrument with alarm indication and LCD is developed to detect ferrous debris of sizes from 30 µm and non-ferrous debris of 50 µm. It is thoroughly tested and calibrated with ferrous, non-ferrous debris of different sizes in the air environment. Finally, an experiment is conducted to check the performance of the instrument by circulating lubricant oil containing ferrous, non-ferrous debris through the sensor.

Real-Time Diagnosis of Faults Using a Bank of Kalman Filters

NASA Technical Reports Server (NTRS)

Kobayashi, Takahisa; Simon, Donald L.

2006-01-01

A new robust method of automated real-time diagnosis of faults in an aircraft engine or a similar complex system involves the use of a bank of Kalman filters. In order to be highly reliable, a diagnostic system must be designed to account for the numerous failure conditions that an aircraft engine may encounter in operation. The method achieves this objective though the utilization of multiple Kalman filters, each of which is uniquely designed based on a specific failure hypothesis. A fault-detection-and-isolation (FDI) system, developed based on this method, is able to isolate faults in sensors and actuators while detecting component faults (abrupt degradation in engine component performance). By affording a capability for real-time identification of minor faults before they grow into major ones, the method promises to enhance safety and reduce operating costs. The robustness of this method is further enhanced by incorporating information regarding the aging condition of an engine. In general, real-time fault diagnostic methods use the nominal performance of a "healthy" new engine as a reference condition in the diagnostic process. Such an approach does not account for gradual changes in performance associated with aging of an otherwise healthy engine. By incorporating information on gradual, aging-related changes, the new method makes it possible to retain at least some of the sensitivity and accuracy needed to detect incipient faults while preventing false alarms that could result from erroneous interpretation of symptoms of aging as symptoms of failures. The figure schematically depicts an FDI system according to the new method. The FDI system is integrated with an engine, from which it accepts two sets of input signals: sensor readings and actuator commands. Two main parts of the FDI system are a bank of Kalman filters and a subsystem that implements FDI decision rules. Each Kalman filter is designed to detect a specific sensor or actuator fault. When a sensor or actuator fault occurs, large estimation errors are generated by all filters except the one using the correct hypothesis. By monitoring the residual output of each filter, the specific fault that has occurred can be detected and isolated on the basis of the decision rules. A set of parameters that indicate the performance of the engine components is estimated by the "correct" Kalman filter for use in detecting component faults. To reduce the loss of diagnostic accuracy and sensitivity in the face of aging, the FDI system accepts information from a steady-state-condition-monitoring system. This information is used to update the Kalman filters and a data bank of trim values representative of the current aging condition.

Sensor Data Quality and Angular Rate Down-Selection Algorithms on SLS EM-1

NASA Technical Reports Server (NTRS)

Park, Thomas; Oliver, Emerson; Smith, Austin

2018-01-01

The NASA Space Launch System Block 1 launch vehicle is equipped with an Inertial Navigation System (INS) and multiple Rate Gyro Assemblies (RGA) that are used in the Guidance, Navigation, and Control (GN&C) algorithms. The INS provides the inertial position, velocity, and attitude of the vehicle along with both angular rate and specific force measurements. Additionally, multiple sets of co-located rate gyros supply angular rate data. The collection of angular rate data, taken along the launch vehicle, is used to separate out vehicle motion from flexible body dynamics. Since the system architecture uses redundant sensors, the capability was developed to evaluate the health (or validity) of the independent measurements. A suite of Sensor Data Quality (SDQ) algorithms is responsible for assessing the angular rate data from the redundant sensors. When failures are detected, SDQ will take the appropriate action and disqualify or remove faulted sensors from forward processing. Additionally, the SDQ algorithms contain logic for down-selecting the angular rate data used by the GN&C software from the set of healthy measurements. This paper provides an overview of the algorithms used for both fault-detection and measurement down selection.

Radio aneurysm coils for noninvasive detection of cerebral embolization failures: a preliminary study.

PubMed

Mohammadi, Abdolreza Rashidi; Chen, Keqin; Ali, Mohamed Sultan Mohamed; Takahata, Kenichi

2011-12-15

The rupture of a cerebral aneurysm is the most common cause of subarachnoid hemorrhage. Endovascular embolization of the aneurysms by implantation of Guglielmi detachable coils (GDC) has become a major treatment approach in the prevention of a rupture. Implantation of the coils induces formation of tissues over the coils, embolizing the aneurysm. However, blood entry into the coiled aneurysm often occurs due to failures in the embolization process. Current diagnostic methods used for aneurysms, such as X-ray angiography and computer tomography, are ineffective for continuous monitoring of the disease and require extremely expensive equipment. Here we present a novel technique for wireless monitoring of cerebral aneurysms using implanted embolization coils as radiofrequency resonant sensors that detect the blood entry. The experiments show that commonly used embolization coils could be utilized as electrical inductors or antennas. As the blood flows into a coil-implanted aneurysm, parasitic capacitance of the coil is modified because of the difference in permittivity between the blood and the tissues grown around the coil, resulting in a change in the coil's resonant frequency. The resonances of platinum GDC-like coils embedded in aneurysm models are detected to show average responses of 224-819 MHz/ml to saline injected into the models. This preliminary demonstration indicates a new possibility in the use of implanted GDC as a wireless sensor for embolization failures, the first step toward realizing long-term, noninvasive, and cost-effective remote monitoring of cerebral aneurysms treated with coil embolization. Copyright © 2011 Elsevier B.V. All rights reserved.

Development and Application of a Portable Health Algorithms Test System

NASA Technical Reports Server (NTRS)

Melcher, Kevin J.; Fulton, Christopher E.; Maul, William A.; Sowers, T. Shane

2007-01-01

This paper describes the development and initial demonstration of a Portable Health Algorithms Test (PHALT) System that is being developed by researchers at the NASA Glenn Research Center (GRC). The PHALT System was conceived as a means of evolving the maturity and credibility of algorithms developed to assess the health of aerospace systems. Comprising an integrated hardware-software environment, the PHALT System allows systems health management algorithms to be developed in a graphical programming environment; to be tested and refined using system simulation or test data playback; and finally, to be evaluated in a real-time hardware-in-the-loop mode with a live test article. In this paper, PHALT System development is described through the presentation of a functional architecture, followed by the selection and integration of hardware and software. Also described is an initial real-time hardware-in-the-loop demonstration that used sensor data qualification algorithms to diagnose and isolate simulated sensor failures in a prototype Power Distribution Unit test-bed. Success of the initial demonstration is highlighted by the correct detection of all sensor failures and the absence of any real-time constraint violations.

Monitoring nocturnal heart rate with bed sensor.

PubMed

Migliorini, M; Kortelainen, J M; Pärkkä, J; Tenhunen, M; Himanen, S L; Bianchi, A M

2014-01-01

This article is part of the Focus Theme of Methods of Information in Medicine on "Biosignal Interpretation: Advanced Methods for Studying Cardiovascular and Respiratory Systems". The aim of this study is to assess the reliability of the estimated Nocturnal Heart Rate (HR), recorded through a bed sensor, compared with the one obtained from standard electrocardiography (ECG). Twenty-eight sleep deprived patients were recorded for one night each through matrix of piezoelectric sensors, integrated into the mattress, through polysomnography (PSG) simultaneously. The two recording methods have been compared in terms of signal quality and differences in heart beat detection. On average, coverage of 92.7% of the total sleep time was obtained for the bed sensor, testifying the good quality of the recordings. The average beat-to-beat error of the inter-beat intervals was 1.06%. These results suggest a good overall signal quality, however, considering fast heart rates (HR > 100 bpm), performances were worse: in fact, the sensitivity in the heart beat detection was 28.4% while the false positive rate was 3.8% which means that a large amount of fast beats were not detected. The accuracy of the measurements made using the bed sensor has less than 10% of failure rate especially in periods with HR lower than 70 bpm. For fast heart beats the uncertainty increases. This can be explained by the change in morphology of the bed sensor signal in correspondence of a higher HR.

Acoustic emission detection of macro-cracks on engraving tool steel inserts during the injection molding cycle using PZT sensors.

PubMed

Svečko, Rajko; Kusić, Dragan; Kek, Tomaž; Sarjaš, Andrej; Hančič, Aleš; Grum, Janez

2013-05-14

This paper presents an improved monitoring system for the failure detection of engraving tool steel inserts during the injection molding cycle. This system uses acoustic emission PZT sensors mounted through acoustic waveguides on the engraving insert. We were thus able to clearly distinguish the defect through measured AE signals. Two engraving tool steel inserts were tested during the production of standard test specimens, each under the same processing conditions. By closely comparing the captured AE signals on both engraving inserts during the filling and packing stages, we were able to detect the presence of macro-cracks on one engraving insert. Gabor wavelet analysis was used for closer examination of the captured AE signals' peak amplitudes during the filling and packing stages. The obtained results revealed that such a system could be used successfully as an improved tool for monitoring the integrity of an injection molding process.

Acoustic Emission Detection of Macro-Cracks on Engraving Tool Steel Inserts during the Injection Molding Cycle Using PZT Sensors

PubMed Central

Svečko, Rajko; Kusić, Dragan; Kek, Tomaž; Sarjaš, Andrej; Hančič, Aleš; Grum, Janez

2013-01-01

This paper presents an improved monitoring system for the failure detection of engraving tool steel inserts during the injection molding cycle. This system uses acoustic emission PZT sensors mounted through acoustic waveguides on the engraving insert. We were thus able to clearly distinguish the defect through measured AE signals. Two engraving tool steel inserts were tested during the production of standard test specimens, each under the same processing conditions. By closely comparing the captured AE signals on both engraving inserts during the filling and packing stages, we were able to detect the presence of macro-cracks on one engraving insert. Gabor wavelet analysis was used for closer examination of the captured AE signals' peak amplitudes during the filling and packing stages. The obtained results revealed that such a system could be used successfully as an improved tool for monitoring the integrity of an injection molding process. PMID:23673677

A study of the use of vibration and stress wave sensing for the detection of bearing failure

NASA Technical Reports Server (NTRS)

Ensor, L. C.; Feng, C. C.

1975-01-01

Results from an experimental study of vibrations and stress waves emitted from ball bearings are presented. Fatique tests were run with both high quality bearings and man faulted bearings, all of one size. Tests were instrumented with different sensors to detect the noises from 10 Hz to 1 MHz. Frequency spectrum plots are presented. The modulation characteristics of the ultrasonic noises were analyzed, and acoustic emission type measurements were conducted. Results are presented which show that there are usable acoustic signal levels even beyond 500 KHz. These signal levels are modulated by a low frequency carrier which is a function of the stress loading and acoustic transmissibility. The results were correlated to fault size in the bearings. The correlation shows that the sensor used for signals from 100 KHz to 1 MHz gave the best sensitivity and detected the generation of very small spalls or pits.

Color constancy by characterization of illumination chromaticity

NASA Astrophysics Data System (ADS)

Nikkanen, Jarno T.

2011-05-01

Computational color constancy algorithms play a key role in achieving desired color reproduction in digital cameras. Failure to estimate illumination chromaticity correctly will result in invalid overall colour cast in the image that will be easily detected by human observers. A new algorithm is presented for computational color constancy. Low computational complexity and low memory requirement make the algorithm suitable for resource-limited camera devices, such as consumer digital cameras and camera phones. Operation of the algorithm relies on characterization of the range of possible illumination chromaticities in terms of camera sensor response. The fact that only illumination chromaticity is characterized instead of the full color gamut, for example, increases robustness against variations in sensor characteristics and against failure of diagonal model of illumination change. Multiple databases are used in order to demonstrate the good performance of the algorithm in comparison to the state-of-the-art color constancy algorithms.

Fiber Bragg Grating Sensor System for Monitoring Smart Composite Aerospace Structures

NASA Technical Reports Server (NTRS)

Moslehi, Behzad; Black, Richard J.; Gowayed, Yasser

2012-01-01

Lightweight, electromagnetic interference (EMI) immune, fiber-optic, sensor- based structural health monitoring (SHM) will play an increasing role in aerospace structures ranging from aircraft wings to jet engine vanes. Fiber Bragg Grating (FBG) sensors for SHM include advanced signal processing, system and damage identification, and location and quantification algorithms. Potentially, the solution could be developed into an autonomous onboard system to inspect and perform non-destructive evaluation and SHM. A novel method has been developed to massively multiplex FBG sensors, supported by a parallel processing interrogator, which enables high sampling rates combined with highly distributed sensing (up to 96 sensors per system). The interrogation system comprises several subsystems. A broadband optical source subsystem (BOSS) and routing and interface module (RIM) send light from the interrogation system to a composite embedded FBG sensor matrix, which returns measurand-dependent wavelengths back to the interrogation system for measurement with subpicometer resolution. In particular, the returned wavelengths are channeled by the RIM to a photonic signal processing subsystem based on powerful optical chips, then passed through an optoelectronic interface to an analog post-detection electronics subsystem, digital post-detection electronics subsystem, and finally via a data interface to a computer. A range of composite structures has been fabricated with FBGs embedded. Stress tensile, bending, and dynamic strain tests were performed. The experimental work proved that the FBG sensors have a good level of accuracy in measuring the static response of the tested composite coupons (down to submicrostrain levels), the capability to detect and monitor dynamic loads, and the ability to detect defects in composites by a variety of methods including monitoring the decay time under different dynamic loading conditions. In addition to quasi-static and dynamic load monitoring, the system can capture acoustic emission events that can be a prelude to structural failure, as well as piezoactuator-induced ultrasonic Lamb-waves-based techniques as a basis for damage detection.

Method and system for detecting a failure or performance degradation in a dynamic system such as a flight vehicle

NASA Technical Reports Server (NTRS)

Miller, Robert H. (Inventor); Ribbens, William B. (Inventor)

2003-01-01

A method and system for detecting a failure or performance degradation in a dynamic system having sensors for measuring state variables and providing corresponding output signals in response to one or more system input signals are provided. The method includes calculating estimated gains of a filter and selecting an appropriate linear model for processing the output signals based on the input signals. The step of calculating utilizes one or more models of the dynamic system to obtain estimated signals. The method further includes calculating output error residuals based on the output signals and the estimated signals. The method also includes detecting one or more hypothesized failures or performance degradations of a component or subsystem of the dynamic system based on the error residuals. The step of calculating the estimated values is performed optimally with respect to one or more of: noise, uncertainty of parameters of the models and un-modeled dynamics of the dynamic system which may be a flight vehicle or financial market or modeled financial system.

Artificial Immune System for Flight Envelope Estimation and Protection

DTIC Science & Technology

2014-12-31

Throttle Failure 103 5.3. Estimation Algorithms for Sensor AC 108 5.3.1. Roll Rate Sensor Bias 108...4.13. Reference Features-Pattern for a Roll Rate Sensor Under Low Severity Failure 93 Figure 4.14. Reference Features-Pattern for a Roll Rate...Average PI for Different ACs 134 Figure 6.9. Roll Response Under High Magnitude Stabilator Failure 135 Figure 6.10. Pitch

Electromagnetic sensors for monitoring of scour and deposition processes at bridges and offshore wind turbines

NASA Astrophysics Data System (ADS)

Michalis, Panagiotis; Tarantino, Alessandro; Judd, Martin

2014-05-01

Recent increases in precipitation have resulted in severe and frequent flooding incidents. This has put hydraulic structures at high risk of failure due to scour, with severe consequences to public safety and significant economic losses. Foundation scour is the leading cause of bridge failures and one of the main climate change impacts to highway and railway infrastructure. Scour action is also being considered as a major risk for offshore wind farm developments as it leads to excessive excavation of the surrounding seabed. Bed level conditions at underwater foundations are very difficult to evaluate, considering that scour holes are often re-filled by deposited loose material which is easily eroded during smaller scale events. An ability to gather information concerning the evolution of scouring will enable the validation of models derived from laboratory-based studies and the assessment of different engineering designs. Several efforts have focused on the development of instrumentation techniques to measure scour processes at foundations. However, they are not being used routinely due to numerous technical and cost issues; therefore, scour continues to be inspected visually. This research project presents a new sensing technique, designed to measure scour depth variation and sediment deposition around the foundations of bridges and offshore wind turbines, and to provide an early warning of an impending structural failure. The monitoring system consists of a probe with integrated electromagnetic sensors, designed to detect the change in the surrounding medium around the foundation structure. The probe is linked to a wireless network to enable remote data acquisition. A developed prototype and a commercial sensor were evaluated to quantify their capabilities to detect scour and sediment deposition processes. Finite element modelling was performed to define the optimum geometric characteristics of the prototype scour sensor based on models with various permittivity conditions. The experimental analysis was conducted using simulations and open channel flume tests in different sediment and temperature conditions. The density and salinity effects on the response of the sensors were also evaluated and reported herein. The obtained results indicate that the sensors are capable of exhibiting high sensitivity to scour and sediment deposition processes under the different tested environmental conditions. Saline water and temperature induced electrical conductivity changes were also found to have inevitable influences on the sensor signals. Based on this research, it is concluded that the proposed monitoring system has considerable potential for field applications that will contribute to improving the resilience and sustainability of hydraulic and marine structures.

Resilient Sensor Networks with Spatiotemporal Interpolation of Missing Sensors: An Example of Space Weather Forecasting by Multiple Satellites

PubMed Central

Tokumitsu, Masahiro; Hasegawa, Keisuke; Ishida, Yoshiteru

2016-01-01

This paper attempts to construct a resilient sensor network model with an example of space weather forecasting. The proposed model is based on a dynamic relational network. Space weather forecasting is vital for a satellite operation because an operational team needs to make a decision for providing its satellite service. The proposed model is resilient to failures of sensors or missing data due to the satellite operation. In the proposed model, the missing data of a sensor is interpolated by other sensors associated. This paper demonstrates two examples of space weather forecasting that involves the missing observations in some test cases. In these examples, the sensor network for space weather forecasting continues a diagnosis by replacing faulted sensors with virtual ones. The demonstrations showed that the proposed model is resilient against sensor failures due to suspension of hardware failures or technical reasons. PMID:27092508

Resilient Sensor Networks with Spatiotemporal Interpolation of Missing Sensors: An Example of Space Weather Forecasting by Multiple Satellites.

PubMed

Tokumitsu, Masahiro; Hasegawa, Keisuke; Ishida, Yoshiteru

2016-04-15

This paper attempts to construct a resilient sensor network model with an example of space weather forecasting. The proposed model is based on a dynamic relational network. Space weather forecasting is vital for a satellite operation because an operational team needs to make a decision for providing its satellite service. The proposed model is resilient to failures of sensors or missing data due to the satellite operation. In the proposed model, the missing data of a sensor is interpolated by other sensors associated. This paper demonstrates two examples of space weather forecasting that involves the missing observations in some test cases. In these examples, the sensor network for space weather forecasting continues a diagnosis by replacing faulted sensors with virtual ones. The demonstrations showed that the proposed model is resilient against sensor failures due to suspension of hardware failures or technical reasons.

FDIR Strategy Validation with the B Method

NASA Astrophysics Data System (ADS)

Sabatier, D.; Dellandrea, B.; Chemouil, D.

2008-08-01

In a formation flying satellite system, the FDIR strategy (Failure Detection, Isolation and Recovery) is paramount. When a failure occurs, satellites should be able to take appropriate reconfiguration actions to obtain the best possible results given the failure, ranging from avoiding satellite-to-satellite collision to continuing the mission without disturbance if possible. To achieve this goal, each satellite in the formation has an implemented FDIR strategy that governs how it detects failures (from tests or by deduction) and how it reacts (reconfiguration using redundant equipments, avoidance manoeuvres, etc.). The goal is to protect the satellites first and the mission as much as possible. In a project initiated by the CNES, ClearSy experiments the B Method to validate the FDIR strategies developed by Thales Alenia Space, of the inter satellite positioning and communication devices that will be used for the SIMBOL-X (2 satellite configuration) and the PEGASE (3 satellite configuration) missions and potentially for other missions afterward. These radio frequency metrology sensor devices provide satellite positioning and inter satellite communication in formation flying. This article presents the results of this experience.

Automated Detection of Events of Scientific Interest

NASA Technical Reports Server (NTRS)

James, Mark

2007-01-01

A report presents a slightly different perspective of the subject matter of Fusing Symbolic and Numerical Diagnostic Computations (NPO-42512), which appears elsewhere in this issue of NASA Tech Briefs. Briefly, the subject matter is the X-2000 Anomaly Detection Language, which is a developmental computing language for fusing two diagnostic computer programs one implementing a numerical analysis method, the other implementing a symbolic analysis method into a unified event-based decision analysis software system for real-time detection of events. In the case of the cited companion NASA Tech Briefs article, the contemplated events that one seeks to detect would be primarily failures or other changes that could adversely affect the safety or success of a spacecraft mission. In the case of the instant report, the events to be detected could also include natural phenomena that could be of scientific interest. Hence, the use of X- 2000 Anomaly Detection Language could contribute to a capability for automated, coordinated use of multiple sensors and sensor-output-data-processing hardware and software to effect opportunistic collection and analysis of scientific data.

Friend or foe: exploiting sensor failures for transparent object localization and classification

NASA Astrophysics Data System (ADS)

Seib, Viktor; Barthen, Andreas; Marohn, Philipp; Paulus, Dietrich

2017-02-01

In this work we address the problem of detecting and recognizing transparent objects using depth images from an RGB-D camera. Using this type of sensor usually prohibits the localization of transparent objects since the structured light pattern of these cameras is not reflected by transparent surfaces. Instead, transparent surfaces often appear as undefined values in the resulting images. However, these erroneous sensor readings form characteristic patterns that we exploit in the presented approach. The sensor data is fed into a deep convolutional neural network that is trained to classify and localize drinking glasses. We evaluate our approach with four different types of transparent objects. To our best knowledge, no datasets offering depth images of transparent objects exist so far. With this work we aim at closing this gap by providing our data to the public.

Microfluidic stretchable RF electronics.

PubMed

Cheng, Shi; Wu, Zhigang

2010-12-07

Stretchable electronics is a revolutionary technology that will potentially create a world of radically different electronic devices and systems that open up an entirely new spectrum of possibilities. This article proposes a microfluidic based solution for stretchable radio frequency (RF) electronics, using hybrid integration of active circuits assembled on flex foils and liquid alloy passive structures embedded in elastic substrates, e.g. polydimethylsiloxane (PDMS). This concept was employed to implement a 900 MHz stretchable RF radiation sensor, consisting of a large area elastic antenna and a cluster of conventional rigid components for RF power detection. The integrated radiation sensor except the power supply was fully embedded in a thin elastomeric substrate. Good electrical performance of the standalone stretchable antenna as well as the RF power detection sub-module was verified by experiments. The sensor successfully detected the RF radiation over 5 m distance in the system demonstration. Experiments on two-dimensional (2D) stretching up to 15%, folding and twisting of the demonstrated sensor were also carried out. Despite the integrated device was severely deformed, no failure in RF radiation sensing was observed in the tests. This technique illuminates a promising route of realizing stretchable and foldable large area integrated RF electronics that are of great interest to a variety of applications like wearable computing, health monitoring, medical diagnostics, and curvilinear electronics.

Analysis of SSEM Sensor Data Using BEAM

NASA Technical Reports Server (NTRS)

Zak, Michail; Park, Han; James, Mark

2004-01-01

A report describes analysis of space shuttle main engine (SSME) sensor data using Beacon-based Exception Analysis for Multimissions (BEAM) [NASA Tech Briefs articles, the two most relevant being Beacon-Based Exception Analysis for Multimissions (NPO- 20827), Vol. 26, No.9 (September 2002), page 32 and Integrated Formulation of Beacon-Based Exception Analysis for Multimissions (NPO- 21126), Vol. 27, No. 3 (March 2003), page 74] for automated detection of anomalies. A specific implementation of BEAM, using the Dynamical Invariant Anomaly Detector (DIAD), is used to find anomalies commonly encountered during SSME ground test firings. The DIAD detects anomalies by computing coefficients of an autoregressive model and comparing them to expected values extracted from previous training data. The DIAD was trained using nominal SSME test-firing data. DIAD detected all the major anomalies including blade failures, frozen sense lines, and deactivated sensors. The DIAD was particularly sensitive to anomalies caused by faulty sensors and unexpected transients. The system offers a way to reduce SSME analysis time and cost by automatically indicating specific time periods, signals, and features contributing to each anomaly. The software described here executes on a standard workstation and delivers analyses in seconds, a computing time comparable to or faster than the test duration itself, offering potential for real-time analysis.

F-8C adaptive flight control extensions. [for maximum likelihood estimation

NASA Technical Reports Server (NTRS)

Stein, G.; Hartmann, G. L.

1977-01-01

An adaptive concept which combines gain-scheduled control laws with explicit maximum likelihood estimation (MLE) identification to provide the scheduling values is described. The MLE algorithm was improved by incorporating attitude data, estimating gust statistics for setting filter gains, and improving parameter tracking during changing flight conditions. A lateral MLE algorithm was designed to improve true air speed and angle of attack estimates during lateral maneuvers. Relationships between the pitch axis sensors inherent in the MLE design were examined and used for sensor failure detection. Design details and simulation performance are presented for each of the three areas investigated.

Water quality monitor. [spacecraft potable water

NASA Technical Reports Server (NTRS)

West, S.; Crisos, J.; Baxter, W.

1979-01-01

The preprototype water quality monitor (WQM) subsystem was designed based on a breadboard monitor for pH, specific conductance, and total organic carbon (TOC). The breadboard equipment demonstrated the feasibility of continuous on-line analysis of potable water for a spacecraft. The WQM subsystem incorporated these breadboard features and, in addition, measures ammonia and includes a failure detection system. The sample, reagent, and standard solutions are delivered to the WQM sensing manifold where chemical operations and measurements are performed using flow through sensors for conductance, pH, TOC, and NH3. Fault monitoring flow detection is also accomplished in this manifold assembly. The WQM is designed to operate automatically using a hardwired electronic controller. In addition, automatic shutdown is incorporated which is keyed to four flow sensors strategically located within the fluid system.

Structural Anomaly Detection Using Fiber Optic Sensors and Inverse Finite Element Method

NASA Technical Reports Server (NTRS)

Quach, Cuong C.; Vazquez, Sixto L.; Tessler, Alex; Moore, Jason P.; Cooper, Eric G.; Spangler, Jan. L.

2005-01-01

NASA Langley Research Center is investigating a variety of techniques for mitigating aircraft accidents due to structural component failure. One technique under consideration combines distributed fiber optic strain sensing with an inverse finite element method for detecting and characterizing structural anomalies anomalies that may provide early indication of airframe structure degradation. The technique identifies structural anomalies that result in observable changes in localized strain but do not impact the overall surface shape. Surface shape information is provided by an Inverse Finite Element Method that computes full-field displacements and internal loads using strain data from in-situ fiberoptic sensors. This paper describes a prototype of such a system and reports results from a series of laboratory tests conducted on a test coupon subjected to increasing levels of damage.

Ampoule Failure System

NASA Technical Reports Server (NTRS)

Watring, Dale A. (Inventor); Johnson, Martin L. (Inventor)

1996-01-01

An ampoule failure system for use in material processing furnaces comprising a containment cartridge and an ampoule failure sensor. The containment cartridge contains an ampoule of toxic material therein and is positioned within a furnace for processing. An ampoule failure probe is positioned in the containment cartridge adjacent the ampoule for detecting a potential harmful release of toxic material therefrom during processing. The failure probe is spaced a predetermined distance from the ampoule and is chemically chosen so as to undergo a timely chemical reaction with the toxic material upon the harmful release thereof. The ampoule failure system further comprises a data acquisition system which is positioned externally of the furnace and is electrically connected to the ampoule failure probe so as to form a communicating electrical circuit. The data acquisition system includes an automatic shutdown device for shutting down the furnace upon the harmful release of toxic material. It also includes a resistance measuring device for measuring the resistance of the failure probe during processing. The chemical reaction causes a step increase in resistance of the failure probe whereupon the automatic shutdown device will responsively shut down the furnace.

Distributed torsion sensor based on cascaded coaxial cable Fabry-Perot interferometers

NASA Astrophysics Data System (ADS)

Cheng, Baokai; Zhu, Wenge; Hua, Liwei; Liu, Jie; Li, Yurong; Nygaard, Runar; Xiao, Hai

2016-07-01

Cascaded coaxial cable Fabry-Perot interferometers (FPI) are studied and demonstrated for distributed torsion measurement. Multiple weak reflectors are implemented on a coaxial cable so that any two consecutive reflectors can form a Fabry-Perot cavity. By fixing the cable sensor in a helical form on a shaft, the distributed torsion of the shaft can be measured by the cascaded Fabry-Perot cavities. A test on a single section shows that the sensor has a linear response with a sensitivity of 1.834 MHz (rad/m)-1 in the range of twisted rate from 0 to 8.726 rad m-1. The distributed torsion sensing capability is useful in drilling process monitoring, structure health monitoring and machine failure detection.

A Formal Approach to the Selection by Minimum Error and Pattern Method for Sensor Data Loss Reduction in Unstable Wireless Sensor Network Communications

PubMed Central

Kim, Changhwa; Shin, DongHyun

2017-01-01

There are wireless networks in which typically communications are unsafe. Most terrestrial wireless sensor networks belong to this category of networks. Another example of an unsafe communication network is an underwater acoustic sensor network (UWASN). In UWASNs in particular, communication failures occur frequently and the failure durations can range from seconds up to a few hours, days, or even weeks. These communication failures can cause data losses significant enough to seriously damage human life or property, depending on their application areas. In this paper, we propose a framework to reduce sensor data loss during communication failures and we present a formal approach to the Selection by Minimum Error and Pattern (SMEP) method that plays the most important role for the reduction in sensor data loss under the proposed framework. The SMEP method is compared with other methods to validate its effectiveness through experiments using real-field sensor data sets. Moreover, based on our experimental results and performance comparisons, the SMEP method has been validated to be better than others in terms of the average sensor data value error rate caused by sensor data loss. PMID:28498312

A Formal Approach to the Selection by Minimum Error and Pattern Method for Sensor Data Loss Reduction in Unstable Wireless Sensor Network Communications.

PubMed

Kim, Changhwa; Shin, DongHyun

2017-05-12

There are wireless networks in which typically communications are unsafe. Most terrestrial wireless sensor networks belong to this category of networks. Another example of an unsafe communication network is an underwater acoustic sensor network (UWASN). In UWASNs in particular, communication failures occur frequently and the failure durations can range from seconds up to a few hours, days, or even weeks. These communication failures can cause data losses significant enough to seriously damage human life or property, depending on their application areas. In this paper, we propose a framework to reduce sensor data loss during communication failures and we present a formal approach to the Selection by Minimum Error and Pattern (SMEP) method that plays the most important role for the reduction in sensor data loss under the proposed framework. The SMEP method is compared with other methods to validate its effectiveness through experiments using real-field sensor data sets. Moreover, based on our experimental results and performance comparisons, the SMEP method has been validated to be better than others in terms of the average sensor data value error rate caused by sensor data loss.

Towards sensor array materials: can failure be delayed?

PubMed Central

Mekid, Samir; Saheb, Nouari; Khan, Shafique M A; Qureshi, Khurram K

2015-01-01

Further to prior development in enhancing structural health using smart materials, an innovative class of materials characterized by the ability to feel senses like humans, i.e. ‘nervous materials’, is discussed. Designed at all scales, these materials will enhance personnel and public safety, and secure greater reliability of products. Materials may fail suddenly, but any system wishes that failure is known in good time and delayed until safe conditions are reached. Nervous materials are expected to be the solution to this statement. This new class of materials is based on the novel concept of materials capable of feeling multiple structural and external stimuli, e.g. stress, force, pressure and temperature, while feeding information back to a controller for appropriate real-time action. The strain–stress state is developed in real time with the identified and characterized source of stimulus, with optimized time response to retrieve initial specified conditions, e.g. shape and strength. Sensors are volumetrically embedded and distributed, emulating the human nervous system. Immediate applications are in aircraft, cars, nuclear energy and robotics. Such materials will reduce maintenance costs, detect initial failures and delay them with self-healing. This article reviews the common aspects and challenges surrounding this new class of materials with types of sensors to be embedded seamlessly or inherently, including appropriate embedding manufacturing techniques with modeling and simulation methods. PMID:27877794

Towards sensor array materials: can failure be delayed?

NASA Astrophysics Data System (ADS)

Mekid, Samir; Saheb, Nouari; Khan, Shafique M. A.; Qureshi, Khurram K.

2015-06-01

Further to prior development in enhancing structural health using smart materials, an innovative class of materials characterized by the ability to feel senses like humans, i.e. ‘nervous materials’, is discussed. Designed at all scales, these materials will enhance personnel and public safety, and secure greater reliability of products. Materials may fail suddenly, but any system wishes that failure is known in good time and delayed until safe conditions are reached. Nervous materials are expected to be the solution to this statement. This new class of materials is based on the novel concept of materials capable of feeling multiple structural and external stimuli, e.g. stress, force, pressure and temperature, while feeding information back to a controller for appropriate real-time action. The strain-stress state is developed in real time with the identified and characterized source of stimulus, with optimized time response to retrieve initial specified conditions, e.g. shape and strength. Sensors are volumetrically embedded and distributed, emulating the human nervous system. Immediate applications are in aircraft, cars, nuclear energy and robotics. Such materials will reduce maintenance costs, detect initial failures and delay them with self-healing. This article reviews the common aspects and challenges surrounding this new class of materials with types of sensors to be embedded seamlessly or inherently, including appropriate embedding manufacturing techniques with modeling and simulation methods.

Distributed multi-level supervision to effectively monitor the operations of a fleet of autonomous vehicles in agricultural tasks.

PubMed

Conesa-Muñoz, Jesús; Gonzalez-de-Soto, Mariano; Gonzalez-de-Santos, Pablo; Ribeiro, Angela

2015-03-05

This paper describes a supervisor system for monitoring the operation of automated agricultural vehicles. The system analyses all of the information provided by the sensors and subsystems on the vehicles in real time and notifies the user when a failure or potentially dangerous situation is detected. In some situations, it is even able to execute a neutralising protocol to remedy the failure. The system is based on a distributed and multi-level architecture that divides the supervision into different subsystems, allowing for better management of the detection and repair of failures. The proposed supervision system was developed to perform well in several scenarios, such as spraying canopy treatments against insects and diseases and selective weed treatments, by either spraying herbicide or burning pests with a mechanical-thermal actuator. Results are presented for selective weed treatment by the spraying of herbicide. The system successfully supervised the task; it detected failures such as service disruptions, incorrect working speeds, incorrect implement states, and potential collisions. Moreover, the system was able to prevent collisions between vehicles by taking action to avoid intersecting trajectories. The results show that the proposed system is a highly useful tool for managing fleets of autonomous vehicles. In particular, it can be used to manage agricultural vehicles during treatment operations.

Distributed Multi-Level Supervision to Effectively Monitor the Operations of a Fleet of Autonomous Vehicles in Agricultural Tasks

PubMed Central

Conesa-Muñoz, Jesús; Gonzalez-de-Soto, Mariano; Gonzalez-de-Santos, Pablo; Ribeiro, Angela

2015-01-01

This paper describes a supervisor system for monitoring the operation of automated agricultural vehicles. The system analyses all of the information provided by the sensors and subsystems on the vehicles in real time and notifies the user when a failure or potentially dangerous situation is detected. In some situations, it is even able to execute a neutralising protocol to remedy the failure. The system is based on a distributed and multi-level architecture that divides the supervision into different subsystems, allowing for better management of the detection and repair of failures. The proposed supervision system was developed to perform well in several scenarios, such as spraying canopy treatments against insects and diseases and selective weed treatments, by either spraying herbicide or burning pests with a mechanical-thermal actuator. Results are presented for selective weed treatment by the spraying of herbicide. The system successfully supervised the task; it detected failures such as service disruptions, incorrect working speeds, incorrect implement states, and potential collisions. Moreover, the system was able to prevent collisions between vehicles by taking action to avoid intersecting trajectories. The results show that the proposed system is a highly useful tool for managing fleets of autonomous vehicles. In particular, it can be used to manage agricultural vehicles during treatment operations. PMID:25751079

Application of fiber grating-based acoustic sensor in progressive failure testing of e-glass/vinylester curve composites

NASA Astrophysics Data System (ADS)

Azmi, Asrul Izam; Raju, Raju; Peng, Gang-Ding

2012-02-01

This paper reports an application of phase shifted fiber Bragg grating (PS-FBG) intensity-type acoustic sensor in a continuous and in-situ failure testing of an E-glass/vinylester top hat stiffener (THS). The narrow transmission channel of the PS-FBG is highly sensitive to small perturbation, hence suitable to be used in an effective acoustic emission (AE) assessment technique. The progressive failure of THS was tested under transverse loading to experimentally simulate the actual loading in practice. Our experimental tests have demonstrated, in good agreement with the commercial piezoelectric sensors, that the important failures information of the THS was successfully recorded by the simple intensity-type PS-FBG sensor.

Composite Bending Box Section Modal Vibration Fault Detection

NASA Technical Reports Server (NTRS)

Werlink, Rudy

2002-01-01

One of the primary concerns with Composite construction in critical structures such as wings and stabilizers is that hidden faults and cracks can develop operationally. In the real world, catastrophic sudden failure can result from these undetected faults in composite structures. Vibration data incorporating a broad frequency modal approach, could detect significant changes prior to failure. The purpose of this report is to investigate the usefulness of frequency mode testing before and after bending and torsion loading on a composite bending Box Test section. This test article is representative of construction techniques being developed for the recent NASA Blended Wing Body Low Speed Vehicle Project. The Box section represents the construction technique on the proposed blended wing aircraft. Modal testing using an impact hammer provides an frequency fingerprint before and after bending and torsional loading. If a significant structural discontinuity develops, the vibration response is expected to change. The limitations of the data will be evaluated for future use as a non-destructive in-situ method of assessing hidden damage in similarly constructed composite wing assemblies. Modal vibration fault detection sensitivity to band-width, location and axis will be investigated. Do the sensor accelerometers need to be near the fault and or in the same axis? The response data used in this report was recorded at 17 locations using tri-axial accelerometers. The modal tests were conducted following 5 independent loading conditions before load to failure and 2 following load to failure over a period of 6 weeks. Redundant data was used to minimize effects from uncontrolled variables which could lead to incorrect interpretations. It will be shown that vibrational modes detected failure at many locations when skin de-bonding failures occurred near the center section. Important considerations are the axis selected and frequency range.

Detection Methodologies for Pathogen and Toxins: A Review.

PubMed

Alahi, Md Eshrat E; Mukhopadhyay, Subhas Chandra

2017-08-16

Pathogen and toxin-contaminated foods and beverages are a major source of illnesses, even death, and have a significant economic impact worldwide. Human health is always under a potential threat, including from biological warfare, due to these dangerous pathogens. The agricultural and food production chain consists of many steps such as harvesting, handling, processing, packaging, storage, distribution, preparation, and consumption. Each step is susceptible to threats of environmental contamination or failure to safeguard the processes. The production process can be controlled in the food and agricultural sector, where smart sensors can play a major role, ensuring greater food quality and safety by low cost, fast, reliable, and profitable methods of detection. Techniques for the detection of pathogens and toxins may vary in cost, size, and specificity, speed of response, sensitivity, and precision. Smart sensors can detect, analyse and quantify at molecular levels contents of different biological origin and ensure quality of foods against spiking with pesticides, fertilizers, dioxin, modified organisms, anti-nutrients, allergens, drugs and so on. This paper reviews different methodologies to detect pathogens and toxins in foods and beverages.

Fault tolerant attitude control for small unmanned aircraft systems equipped with an airflow sensor array.

PubMed

Shen, H; Xu, Y; Dickinson, B T

2014-11-18

Inspired by sensing strategies observed in birds and bats, a new attitude control concept of directly using real-time pressure and shear stresses has recently been studied. It was shown that with an array of onboard airflow sensors, small unmanned aircraft systems can promptly respond to airflow changes and improve flight performances. In this paper, a mapping function is proposed to compute aerodynamic moments from the real-time pressure and shear data in a practical and computationally tractable formulation. Since many microscale airflow sensors are embedded on the small unmanned aircraft system surface, it is highly possible that certain sensors may fail. Here, an adaptive control system is developed that is robust to sensor failure as well as other numerical mismatches in calculating real-time aerodynamic moments. The advantages of the proposed method are shown in the following simulation cases: (i) feedback pressure and wall shear data from a distributed array of 45 airflow sensors; (ii) 50% failure of the symmetrically distributed airflow sensor array; and (iii) failure of all the airflow sensors on one wing. It is shown that even if 50% of the airflow sensors have failures, the aircraft is still stable and able to track the attitude commands.

Health management and controls for Earth-to-orbit propulsion systems

NASA Astrophysics Data System (ADS)

Bickford, R. L.

1995-03-01

Avionics and health management technologies increase the safety and reliability while decreasing the overall cost for Earth-to-orbit (ETO) propulsion systems. New ETO propulsion systems will depend on highly reliable fault tolerant flight avionics, advanced sensing systems and artificial intelligence aided software to ensure critical control, safety and maintenance requirements are met in a cost effective manner. Propulsion avionics consist of the engine controller, actuators, sensors, software and ground support elements. In addition to control and safety functions, these elements perform system monitoring for health management. Health management is enhanced by advanced sensing systems and algorithms which provide automated fault detection and enable adaptive control and/or maintenance approaches. Aerojet is developing advanced fault tolerant rocket engine controllers which provide very high levels of reliability. Smart sensors and software systems which significantly enhance fault coverage and enable automated operations are also under development. Smart sensing systems, such as flight capable plume spectrometers, have reached maturity in ground-based applications and are suitable for bridging to flight. Software to detect failed sensors has reached similar maturity. This paper will discuss fault detection and isolation for advanced rocket engine controllers as well as examples of advanced sensing systems and software which significantly improve component failure detection for engine system safety and health management.

Optical sensors for electrical elements of a medium voltage distribution network

NASA Astrophysics Data System (ADS)

De Maria, Letizia; Bartalesi, Daniele; Serragli, Paolo; Paladino, Domenico

2012-04-01

The aging of most of the components of the National transmission and distribution system can potentially influence the reliability of power supply in a Medium Voltage (MV) network. In order to prevent possible dangerous situations, selected diagnostic indicators on electrical parts exploiting reliable and potentially low-cost sensors are required. This paper presents results concerning two main research activities regarding the development and application of innovative optical sensors for the diagnostic of MV electrical components. The first concerns a multi-sensor prototype for the detection of pre-discharges in MV switchboards: it is the combination of three different types of sensors operating simultaneously to detect incipient failure and to reduce the occurrence of false alarms. The system is real-time controlled by an embedded computer through a LabView interface. The second activity refers to a diagnostic tool to provide significant real-time information about early aging of MV/Low Voltage (LV) transformers by means of its vibration fingerprint. A miniaturized Optical Micro-Electro-Mechanical System (MEMS) based unit has been assembled for vibration measurements, wireless connected to a remote computer and controlled via LabView interface. Preliminary comparative tests were carried out with standard piezoelectric accelerometers on a conventional MV/LV test transformer under open circuit and in short-circuited configuration.

Photonic Low Cost Micro-Sensor for in-Line Wear Particle Detection in Flowing Lube Oils.

PubMed

Mabe, Jon; Zubia, Joseba; Gorritxategi, Eneko

2017-03-14

The presence of microscopic particles in suspension in industrial fluids is often an early warning of latent or imminent failures in the equipment or processes where they are being used. This manuscript describes work undertaken to integrate different photonic principles with a micro- mechanical fluidic structure and an embedded processor to develop a fully autonomous wear debris sensor for in-line monitoring of industrial fluids. Lens-less microscopy, stroboscopic illumination, a CMOS imager and embedded machine vision technologies have been merged to develop a sensor solution that is able to detect and quantify the number and size of micrometric particles suspended in a continuous flow of a fluid. A laboratory test-bench has been arranged for setting up the configuration of the optical components targeting a static oil sample and then a sensor prototype has been developed for migrating the measurement principles to real conditions in terms of operating pressure and flow rate of the oil. Imaging performance is quantified using micro calibrated samples, as well as by measuring real used lubricated oils. Sampling a large fluid volume with a decent 2D spatial resolution, this photonic micro sensor offers a powerful tool at very low cost and compacted size for in-line wear debris monitoring.

Photonic Low Cost Micro-Sensor for in-Line Wear Particle Detection in Flowing Lube Oils

PubMed Central

Mabe, Jon; Zubia, Joseba; Gorritxategi, Eneko

2017-01-01

The presence of microscopic particles in suspension in industrial fluids is often an early warning of latent or imminent failures in the equipment or processes where they are being used. This manuscript describes work undertaken to integrate different photonic principles with a micro- mechanical fluidic structure and an embedded processor to develop a fully autonomous wear debris sensor for in-line monitoring of industrial fluids. Lens-less microscopy, stroboscopic illumination, a CMOS imager and embedded machine vision technologies have been merged to develop a sensor solution that is able to detect and quantify the number and size of micrometric particles suspended in a continuous flow of a fluid. A laboratory test-bench has been arranged for setting up the configuration of the optical components targeting a static oil sample and then a sensor prototype has been developed for migrating the measurement principles to real conditions in terms of operating pressure and flow rate of the oil. Imaging performance is quantified using micro calibrated samples, as well as by measuring real used lubricated oils. Sampling a large fluid volume with a decent 2D spatial resolution, this photonic micro sensor offers a powerful tool at very low cost and compacted size for in-line wear debris monitoring. PMID:28335436

Temperature Measurement and Damage Detection in Concrete Beams Exposed to Fire Using PPP-BOTDA Based Fiber Optic Sensors.

PubMed

Bao, Yi; Hoehler, Matthew S; Smith, Christopher M; Bundy, Matthew; Chen, Genda

2017-10-01

In this study, distributed fiber optic sensors based on pulse pre-pump Brillouin optical time domain analysis (PPP-BODTA) are characterized and deployed to measure spatially-distributed temperatures in reinforced concrete specimens exposed to fire. Four beams were tested to failure in a natural gas fueled compartment fire, each instrumented with one fused silica, single-mode optical fiber as a distributed sensor and four thermocouples. Prior to concrete cracking, the distributed temperature was validated at locations of the thermocouples by a relative difference of less than 9 %. The cracks in concrete can be identified as sharp peaks in the temperature distribution since the cracks are locally filled with hot air. Concrete cracking did not affect the sensitivity of the distributed sensor but concrete spalling broke the optical fiber loop required for PPP-BOTDA measurements.

Incipient Crack Detection in Composite Wind Turbine Blades

DOE Office of Scientific and Technical Information (OSTI.GOV)

Taylor, Stuart G.; Choi, Mijin; Jeong, Hyomi

2012-08-28

This paper presents some analysis results for incipient crack detection in a 9-meter CX-100 wind turbine blade that underwent fatigue loading to failure. The blade was manufactured to standard specifications, and it underwent harmonic excitation at its first resonance using a hydraulically-actuated excitation system until reaching catastrophic failure. This work investigates the ability of an ultrasonic guided wave approach to detect incipient damage prior to the surfacing of a visible, catastrophic crack. The blade was instrumented with piezoelectric transducers, which were used in an active, pitchcatch mode with guided waves over a range of excitation frequencies. The performance results inmore » detecting incipient crack formation in the fiberglass skin of the blade is assessed over the range of frequencies in order to determine the point at which the incipient crack became detectable. Higher excitation frequencies provide consistent results for paths along the rotor blade's carbon fiber spar cap, but performance falls off with increasing excitation frequencies for paths off of the spar cap. Lower excitation frequencies provide more consistent performance across all sensor paths.« less

A novel microbial fuel cell sensor with biocathode sensing element.

PubMed

Jiang, Yong; Liang, Peng; Liu, Panpan; Wang, Donglin; Miao, Bo; Huang, Xia

2017-08-15

The traditional microbial fuel cell (MFC) sensor with bioanode as sensing element delivers limited sensitivity to toxicity monitoring, restricted application to only anaerobic and organic rich water body, and increased potential fault warning to the combined shock of organic matter/toxicity. In this study, the biocathode for oxygen reduction reaction was employed for the first time as the sensing element in MFC sensor for toxicity monitoring. The results shown that the sensitivity of MFC sensor with biocathode sensing element (7.4±2.0 to 67.5±4.0mA% -1 cm -2 ) was much greater than that showed by bioanode sensing element (3.4±1.5 to 5.5±0.7mA% -1 cm -2 ). The biocathode sensing element achieved the lowest detection limit reported to date using MFC sensor for formaldehyde detection (0.0005%), while the bioanode was more applicable for higher concentration (>0.0025%). There was a quicker response of biocathode sensing element with the increase of conductivity and dissolved oxygen (DO). The biocathode sensing element made the MFC sensor directly applied to clean water body monitoring, e.g., drinking water and reclaimed water, without the amending of background organic matter, and it also decreased the warning failure when challenged by a combined shock of organic matter/toxicity. Copyright © 2017 Elsevier B.V. All rights reserved.

Angular approach combined to mechanical model for tool breakage detection by eddy current sensors

NASA Astrophysics Data System (ADS)

Ritou, M.; Garnier, S.; Furet, B.; Hascoet, J. Y.

2014-02-01

The paper presents a new complete approach for Tool Condition Monitoring (TCM) in milling. The aim is the early detection of small damages so that catastrophic tool failures are prevented. A versatile in-process monitoring system is introduced for reliability concerns. The tool condition is determined by estimates of the radial eccentricity of the teeth. An adequate criterion is proposed combining mechanical model of milling and angular approach.Then, a new solution is proposed for the estimate of cutting force using eddy current sensors implemented close to spindle nose. Signals are analysed in the angular domain, notably by synchronous averaging technique. Phase shifts induced by changes of machining direction are compensated. Results are compared with cutting forces measured with a dynamometer table.The proposed method is implemented in an industrial case of pocket machining operation. One of the cutting edges has been slightly damaged during the machining, as shown by a direct measurement of the tool. A control chart is established with the estimates of cutter eccentricity obtained during the machining from the eddy current sensors signals. Efficiency and reliability of the method is demonstrated by a successful detection of the damage.

Detection of cardiac activity using a 5.8 GHz radio frequency sensor.

PubMed

Vasu, V; Fox, N; Brabetz, T; Wren, M; Heneghan, C; Sezer, S

2009-01-01

A 5.8-GHz ISM-Band radio-frequency sensor has been developed for non-contact measurement of respiration and heart rate from stationary and semi-stationary subjects at a distance of 0.5 to 1.5 meters. We report on the accuracy of the heart rate measurements obtained using two algorithmic approaches, as compared to a reference heart rate obtained using a pulse oximeter. Simultaneous Photoplethysmograph (PPG) and non-contact sensor recordings were recorded over fifteen minute periods for ten healthy subjects (8M/2F, ages 29.6 + or - 5.6 yrs) One algorithm is based on automated detection of individual peaks associated with each cardiac cycle; a second algorithm extracts a heart rate over a 60-second period using spectral analysis. Peaks were also extracted manually for comparison with the automated method. The peak-detection methods were less accurate than the spectral methods, but suggest the possibility of acquiring beat by beat data; the spectral algorithms measured heart rate to within + or -10% for the ten subjects chosen. Non-contact measurement of heart rate will be useful in chronic disease monitoring for conditions such as heart failure and cardiovascular disease.

Experimental Robot Position Sensor Fault Tolerance Using Accelerometers and Joint Torque Sensors

NASA Technical Reports Server (NTRS)

Aldridge, Hal A.; Juang, Jer-Nan

1997-01-01

Robot systems in critical applications, such as those in space and nuclear environments, must be able to operate during component failure to complete important tasks. One failure mode that has received little attention is the failure of joint position sensors. Current fault tolerant designs require the addition of directly redundant position sensors which can affect joint design. The proposed method uses joint torque sensors found in most existing advanced robot designs along with easily locatable, lightweight accelerometers to provide a joint position sensor fault recovery mode. This mode uses the torque sensors along with a virtual passive control law for stability and accelerometers for joint position information. Two methods for conversion from Cartesian acceleration to joint position based on robot kinematics, not integration, are presented. The fault tolerant control method was tested on several joints of a laboratory robot. The controllers performed well with noisy, biased data and a model with uncertain parameters.

A two-tiered self-powered wireless monitoring system architecture for bridge health management

NASA Astrophysics Data System (ADS)

Kurata, Masahiro; Lynch, Jerome P.; Galchev, Tzeno; Flynn, Michael; Hipley, Patrick; Jacob, Vince; van der Linden, Gwendolyn; Mortazawi, Amir; Najafi, Khalil; Peterson, Rebecca L.; Sheng, Li-Hong; Sylvester, Dennis; Thometz, Edward

2010-04-01

Bridges are an important societal resource used to carry vehicular traffic within a transportation network. As such, the economic impact of the failure of a bridge is high; the recent failure of the I-35W Bridge in Minnesota (2007) serves as a poignant example. Structural health monitoring (SHM) systems can be adopted to detect and quantify structural degradation and damage in an affordable and real-time manner. This paper presents a detailed overview of a multi-tiered architecture for the design of a low power wireless monitoring system for large and complex infrastructure systems. The monitoring system architecture employs two wireless sensor nodes, each with unique functional features and varying power demand. At the lowest tier of the system architecture is the ultra-low power Phoenix wireless sensor node whose design has been optimized to draw minimal power during standby. These ultra low-power nodes are configured to communicate their measurements to a more functionally-rich wireless sensor node residing on the second-tier of the monitoring system architecture. While the Narada wireless sensor node offers more memory, greater processing power and longer communication ranges, it also consumes more power during operation. Radio frequency (RF) and mechanical vibration power harvesting is integrated with the wireless sensor nodes to allow them to operate freely for long periods of time (e.g., years). Elements of the proposed two-tiered monitoring system architecture are validated upon an operational long-span suspension bridge.

Towards Real-time, On-board, Hardware-Supported Sensor and Software Health Management for Unmanned Aerial Systems

NASA Technical Reports Server (NTRS)

Schumann, Johann; Rozier, Kristin Y.; Reinbacher, Thomas; Mengshoel, Ole J.; Mbaya, Timmy; Ippolito, Corey

2013-01-01

Unmanned aerial systems (UASs) can only be deployed if they can effectively complete their missions and respond to failures and uncertain environmental conditions while maintaining safety with respect to other aircraft as well as humans and property on the ground. In this paper, we design a real-time, on-board system health management (SHM) capability to continuously monitor sensors, software, and hardware components for detection and diagnosis of failures and violations of safety or performance rules during the flight of a UAS. Our approach to SHM is three-pronged, providing: (1) real-time monitoring of sensor and/or software signals; (2) signal analysis, preprocessing, and advanced on the- fly temporal and Bayesian probabilistic fault diagnosis; (3) an unobtrusive, lightweight, read-only, low-power realization using Field Programmable Gate Arrays (FPGAs) that avoids overburdening limited computing resources or costly re-certification of flight software due to instrumentation. Our implementation provides a novel approach of combining modular building blocks, integrating responsive runtime monitoring of temporal logic system safety requirements with model-based diagnosis and Bayesian network-based probabilistic analysis. We demonstrate this approach using actual data from the NASA Swift UAS, an experimental all-electric aircraft.

Multifunctional Cement Composites Strain and Damage Sensors Applied on Reinforced Concrete (RC) Structural Elements

PubMed Central

Baeza, Francisco Javier; Galao, Oscar; Zornoza, Emilio; Garcés, Pedro

2013-01-01

In this research, strain-sensing and damage-sensing functional properties of cement composites have been studied on a conventional reinforced concrete (RC) beam. Carbon nanofiber (CNFCC) and fiber (CFCC) cement composites were used as sensors on a 4 m long RC beam. Different casting conditions (in situ or attached), service location (under tension or compression) and electrical contacts (embedded or superficial) were compared. Both CNFCC and CFCC were suitable as strain sensors in reversible (elastic) sensing condition testing. CNFCC showed higher sensitivities (gage factor up to 191.8), while CFCC only reached gage factors values of 178.9 (tension) or 49.5 (compression). Furthermore, damage-sensing tests were run, increasing the applied load progressively up to the RC beam failure. In these conditions, CNFCC sensors were also strain sensitive, but no damage sensing mechanism was detected for the strain levels achieved during the tests. Hence, these cement composites could act as strain sensors, even for severe damaged structures near to their collapse. PMID:28809343

Multifunctional Cement Composites Strain and Damage Sensors Applied on Reinforced Concrete (RC) Structural Elements.

PubMed

Baeza, Francisco Javier; Galao, Oscar; Zornoza, Emilio; Garcés, Pedro

2013-03-06

In this research, strain-sensing and damage-sensing functional properties of cement composites have been studied on a conventional reinforced concrete (RC) beam. Carbon nanofiber (CNFCC) and fiber (CFCC) cement composites were used as sensors on a 4 m long RC beam. Different casting conditions ( in situ or attached), service location (under tension or compression) and electrical contacts (embedded or superficial) were compared. Both CNFCC and CFCC were suitable as strain sensors in reversible (elastic) sensing condition testing. CNFCC showed higher sensitivities (gage factor up to 191.8), while CFCC only reached gage factors values of 178.9 (tension) or 49.5 (compression). Furthermore, damage-sensing tests were run, increasing the applied load progressively up to the RC beam failure. In these conditions, CNFCC sensors were also strain sensitive, but no damage sensing mechanism was detected for the strain levels achieved during the tests. Hence, these cement composites could act as strain sensors, even for severe damaged structures near to their collapse.

Detection of gear cracks in a complex gearbox of wind turbines using supervised bounded component analysis of vibration signals collected from multi-channel sensors

NASA Astrophysics Data System (ADS)

Li, Zhixiong; Yan, Xinping; Wang, Xuping; Peng, Zhongxiao

2016-06-01

In the complex gear transmission systems, in wind turbines a crack is one of the most common failure modes and can be fatal to the wind turbine power systems. A single sensor may suffer with issues relating to its installation position and direction, resulting in the collection of weak dynamic responses of the cracked gear. A multi-channel sensor system is hence applied in the signal acquisition and the blind source separation (BSS) technologies are employed to optimally process the information collected from multiple sensors. However, literature review finds that most of the BSS based fault detectors did not address the dependence/correlation between different moving components in the gear systems; particularly, the popular used independent component analysis (ICA) assumes mutual independence of different vibration sources. The fault detection performance may be significantly influenced by the dependence/correlation between vibration sources. In order to address this issue, this paper presents a new method based on the supervised order tracking bounded component analysis (SOTBCA) for gear crack detection in wind turbines. The bounded component analysis (BCA) is a state of art technology for dependent source separation and is applied limitedly to communication signals. To make it applicable for vibration analysis, in this work, the order tracking has been appropriately incorporated into the BCA framework to eliminate the noise and disturbance signal components. Then an autoregressive (AR) model built with prior knowledge about the crack fault is employed to supervise the reconstruction of the crack vibration source signature. The SOTBCA only outputs one source signal that has the closest distance with the AR model. Owing to the dependence tolerance ability of the BCA framework, interfering vibration sources that are dependent/correlated with the crack vibration source could be recognized by the SOTBCA, and hence, only useful fault information could be preserved in the reconstructed signal. The crack failure thus could be precisely identified by the cyclic spectral correlation analysis. A series of numerical simulations and experimental tests have been conducted to illustrate the advantages of the proposed SOTBCA method for fatigue crack detection. Comparisons to three representative techniques, i.e. Erdogan's BCA (E-BCA), joint approximate diagonalization of eigen-matrices (JADE), and FastICA, have demonstrated the effectiveness of the SOTBCA. Hence the proposed approach is suitable for accurate gear crack detection in practical applications.

Managed traffic evacuation using distributed sensor processing

NASA Astrophysics Data System (ADS)

Ramuhalli, Pradeep; Biswas, Subir

2005-05-01

This paper presents an integrated sensor network and distributed event processing architecture for managed in-building traffic evacuation during natural and human-caused disasters, including earthquakes, fire and biological/chemical terrorist attacks. The proposed wireless sensor network protocols and distributed event processing mechanisms offer a new distributed paradigm for improving reliability in building evacuation and disaster management. The networking component of the system is constructed using distributed wireless sensors for measuring environmental parameters such as temperature, humidity, and detecting unusual events such as smoke, structural failures, vibration, biological/chemical or nuclear agents. Distributed event processing algorithms will be executed by these sensor nodes to detect the propagation pattern of the disaster and to measure the concentration and activity of human traffic in different parts of the building. Based on this information, dynamic evacuation decisions are taken for maximizing the evacuation speed and minimizing unwanted incidents such as human exposure to harmful agents and stampedes near exits. A set of audio-visual indicators and actuators are used for aiding the automated evacuation process. In this paper we develop integrated protocols, algorithms and their simulation models for the proposed sensor networking and the distributed event processing framework. Also, efficient harnessing of the individually low, but collectively massive, processing abilities of the sensor nodes is a powerful concept behind our proposed distributed event processing algorithms. Results obtained through simulation in this paper are used for a detailed characterization of the proposed evacuation management system and its associated algorithmic components.

Research on measurement of aviation magneto ignition strength and balance

NASA Astrophysics Data System (ADS)

Gao, Feng; He, Zhixiang; Zhang, Dingpeng

2017-12-01

Aviation magneto ignition system failure accounted for two-thirds of the total fault aviation piston engine and above. At present the method used for this failure diagnosis is often depended on the visual inspections in the civil aviation maintenance field. Due to human factors, the visual inspections cannot provide ignition intensity value and ignition equilibrium deviation value among the different spark plugs in the different cylinder of aviation piston engine. So air magneto ignition strength and balance testing has become an aviation piston engine maintenance technical problem needed to resolve. In this paper, the ultraviolet sensor with detection wavelength of 185~260nm and driving voltage of 320V DC is used as the core of ultraviolet detection to detect the ignition intensity of Aviation magneto ignition system and the balance deviation of the ignition intensity of each cylinder. The experimental results show that the rotational speed within the range 0 to 3500 RPM test error less than 0.34%, ignition strength analysis and calculation error is less than 0.13%, and measured the visual inspection is hard to distinguish between high voltage wire leakage failure of deviation value of 200 pulse ignition strength balance/Sec. The method to detect aviation piston engine maintenance of magneto ignition system fault has a certain reference value.

Description of a dual fail operational redundant strapdown inertial measurement unit for integrated avionics systems research

NASA Technical Reports Server (NTRS)

Bryant, W. H.; Morrell, F. R.

1981-01-01

An experimental redundant strapdown inertial measurement unit (RSDIMU) is developed as a link to satisfy safety and reliability considerations in the integrated avionics concept. The unit includes four two degree-of-freedom tuned rotor gyros, and four accelerometers in a skewed and separable semioctahedral array. These sensors are coupled to four microprocessors which compensate sensor errors. These microprocessors are interfaced with two flight computers which process failure detection, isolation, redundancy management, and general flight control/navigation algorithms. Since the RSDIMU is a developmental unit, it is imperative that the flight computers provide special visibility and facility in algorithm modification.

Proprioceptive Sensors' Fault Tolerant Control Strategy for an Autonomous Vehicle.

PubMed

Boukhari, Mohamed Riad; Chaibet, Ahmed; Boukhnifer, Moussa; Glaser, Sébastien

2018-06-09

In this contribution, a fault-tolerant control strategy for the longitudinal dynamics of an autonomous vehicle is presented. The aim is to be able to detect potential failures of the vehicle's speed sensor and then to keep the vehicle in a safe state. For this purpose, the separation principle, composed of a static output feedback controller and fault estimation observers, is designed. Indeed, two observer techniques were proposed: the proportional and integral observer and the descriptor observer. The effectiveness of the proposed scheme is validated by means of the experimental demonstrator of the VEDECOM (Véhicle Décarboné et Communinicant) Institut.

STS-51 pad abort. OV103-engine 2033 (ME-2) fuel flowmeter sensor open circuit

NASA Technical Reports Server (NTRS)

1993-01-01

The STS-51 initial launch attempt of Discovery (OV-103) was terminated on KSC launch pad 39B on 12 Aug. 1993 at 9:12 AM E.S.T. due to a sensor redundancy failure in the liquid hydrogen system of ME-2 (Engine 2033). The event description and time line are summarized. Propellant loading was initiated on 12 Aug. 1993 at 12:00 AM EST. All space shuttle main engine (SSME) chill parameters and Launch Commit Criteria (LCC) were nominal. At engine start plus 1.34 seconds a Failure Identification (FID) was posted against Engine 2033 for exceeding the 1800 spin intra-channel (A1-A2) Fuel Flowrate sensor channel qualification limit. The engine was shut down at 1.50 seconds followed by Engines 2032 and 2030. All shut down sequences were nominal and the mission was safely aborted. SSME Avionics hardware and software performed nominally during the incident. A review of vehicle data table (VDT) data and controller software logic revealed no failure indications other than the single FID 111-101, Fuel Flowrate Intra-Channel Test Channel A disqualification. Software logic was executed according to requirements and there was no anomalous controller software operation. Immediately following the abort, a Rocketdyne/NASA failure investigation team was assembled. The team successfully isolated the failure cause to an open circuit in a Fuel Flowrate Sensor. This type of failure has occurred eight previous times in ground testing. The sensor had performed acceptably on three previous flights of the engine and SSME flight history shows 684 combined fuel flow rate sensor channel flights without failure. The disqualification of an Engine 2 (SSME No. 2033) Fuel Flowrate sensor channel was a result of an instrumentation failure and not engine performance. All other engine operations were nominal. This disqualification resulted in an engine shutdown and safe sequential shutdown of all three engines prior to ignition of the solid boosters.

Sensing sheets based on large area electronics for fatigue crack detection

NASA Astrophysics Data System (ADS)

Yao, Yao; Glisic, Branko

2015-03-01

Reliable early-stage damage detection requires continuous structural health monitoring (SHM) over large areas of structure, and with high spatial resolution of sensors. This paper presents the development stage of prototype strain sensing sheets based on Large Area Electronics (LAE), in which thin-film strain gauges and control circuits are integrated on the flexible electronics and deposited on a polyimide sheet that can cover large areas. These sensing sheets were applied for fatigue crack detection on small-scale steel plates. Two types of sensing-sheet interconnects were designed and manufactured, and dense arrays of strain gauge sensors were assembled onto the interconnects. In total, four (two for each design type) strain sensing sheets were created and tested, which were sensitive to strain at virtually every point over the whole sensing sheet area. The sensing sheets were bonded to small-scale steel plates, which had a notch on the boundary so that fatigue cracks could be generated under cyclic loading. The fatigue tests were carried out at the Carleton Laboratory of Columbia University, and the steel plates were attached through a fixture to the loading machine that applied cyclic fatigue load. Fatigue cracks then occurred and propagated across the steel plates, leading to the failure of these test samples. The strain sensor that was close to the notch successfully detected the initialization of fatigue crack and localized the damage on the plate. The strain sensor that was away from the crack successfully detected the propagation of fatigue crack based on the time history of measured strain. Overall, the results of the fatigue tests validated general principles of the strain sensing sheets for crack detection.

Flight experience with flight control redundancy management

NASA Technical Reports Server (NTRS)

Szalai, K. J.; Larson, R. R.; Glover, R. D.

1980-01-01

Flight experience with both current and advanced redundancy management schemes was gained in recent flight research programs using the F-8 digital fly by wire aircraft. The flight performance of fault detection, isolation, and reconfiguration (FDIR) methods for sensors, computers, and actuators is reviewed. Results of induced failures as well as of actual random failures are discussed. Deficiencies in modeling and implementation techniques are also discussed. The paper also presents comparison off multisensor tracking in smooth air, in turbulence, during large maneuvers, and during maneuvers typical of those of large commercial transport aircraft. The results of flight tests of an advanced analytic redundancy management algorithm are compared with the performance of a contemporary algorithm in terms of time to detection, false alarms, and missed alarms. The performance of computer redundancy management in both iron bird and flight tests is also presented.

Active Self-Testing Noise Measurement Sensors for Large-Scale Environmental Sensor Networks

PubMed Central

Domínguez, Federico; Cuong, Nguyen The; Reinoso, Felipe; Touhafi, Abdellah; Steenhaut, Kris

2013-01-01

Large-scale noise pollution sensor networks consist of hundreds of spatially distributed microphones that measure environmental noise. These networks provide historical and real-time environmental data to citizens and decision makers and are therefore a key technology to steer environmental policy. However, the high cost of certified environmental microphone sensors render large-scale environmental networks prohibitively expensive. Several environmental network projects have started using off-the-shelf low-cost microphone sensors to reduce their costs, but these sensors have higher failure rates and produce lower quality data. To offset this disadvantage, we developed a low-cost noise sensor that actively checks its condition and indirectly the integrity of the data it produces. The main design concept is to embed a 13 mm speaker in the noise sensor casing and, by regularly scheduling a frequency sweep, estimate the evolution of the microphone's frequency response over time. This paper presents our noise sensor's hardware and software design together with the results of a test deployment in a large-scale environmental network in Belgium. Our middle-range-value sensor (around €50) effectively detected all experienced malfunctions, in laboratory tests and outdoor deployments, with a few false positives. Future improvements could further lower the cost of our sensor below €10. PMID:24351634

Multi-hop routing mechanism for reliable sensor computing.

PubMed

Chen, Jiann-Liang; Ma, Yi-Wei; Lai, Chia-Ping; Hu, Chia-Cheng; Huang, Yueh-Min

2009-01-01

Current research on routing in wireless sensor computing concentrates on increasing the service lifetime, enabling scalability for large number of sensors and supporting fault tolerance for battery exhaustion and broken nodes. A sensor node is naturally exposed to various sources of unreliable communication channels and node failures. Sensor nodes have many failure modes, and each failure degrades the network performance. This work develops a novel mechanism, called Reliable Routing Mechanism (RRM), based on a hybrid cluster-based routing protocol to specify the best reliable routing path for sensor computing. Table-driven intra-cluster routing and on-demand inter-cluster routing are combined by changing the relationship between clusters for sensor computing. Applying a reliable routing mechanism in sensor computing can improve routing reliability, maintain low packet loss, minimize management overhead and save energy consumption. Simulation results indicate that the reliability of the proposed RRM mechanism is around 25% higher than that of the Dynamic Source Routing (DSR) and ad hoc On-demand Distance Vector routing (AODV) mechanisms.

Autonomic and Coevolutionary Sensor Networking

NASA Astrophysics Data System (ADS)

Boonma, Pruet; Suzuki, Junichi

(WSNs) applications are often required to balance the tradeoffs among conflicting operational objectives (e.g., latency and power consumption) and operate at an optimal tradeoff. This chapter proposes and evaluates a architecture, called BiSNET/e, which allows WSN applications to overcome this issue. BiSNET/e is designed to support three major types of WSN applications: , and hybrid applications. Each application is implemented as a decentralized group of, which is analogous to a bee colony (application) consisting of bees (agents). Agents collect sensor data or detect an event (a significant change in sensor reading) on individual nodes, and carry sensor data to base stations. They perform these data collection and event detection functionalities by sensing their surrounding network conditions and adaptively invoking behaviors such as pheromone emission, reproduction, migration, swarming and death. Each agent has its own behavior policy, as a set of genes, which defines how to invoke its behaviors. BiSNET/e allows agents to evolve their behavior policies (genes) across generations and autonomously adapt their performance to given objectives. Simulation results demonstrate that, in all three types of applications, agents evolve to find optimal tradeoffs among conflicting objectives and adapt to dynamic network conditions such as traffic fluctuations and node failures/additions. Simulation results also illustrate that, in hybrid applications, data collection agents and event detection agents coevolve to augment their adaptability and performance.

Multi-Sensor Fusion with Interaction Multiple Model and Chi-Square Test Tolerant Filter.

PubMed

Yang, Chun; Mohammadi, Arash; Chen, Qing-Wei

2016-11-02

Motivated by the key importance of multi-sensor information fusion algorithms in the state-of-the-art integrated navigation systems due to recent advancements in sensor technologies, telecommunication, and navigation systems, the paper proposes an improved and innovative fault-tolerant fusion framework. An integrated navigation system is considered consisting of four sensory sub-systems, i.e., Strap-down Inertial Navigation System (SINS), Global Navigation System (GPS), the Bei-Dou2 (BD2) and Celestial Navigation System (CNS) navigation sensors. In such multi-sensor applications, on the one hand, the design of an efficient fusion methodology is extremely constrained specially when no information regarding the system's error characteristics is available. On the other hand, the development of an accurate fault detection and integrity monitoring solution is both challenging and critical. The paper addresses the sensitivity issues of conventional fault detection solutions and the unavailability of a precisely known system model by jointly designing fault detection and information fusion algorithms. In particular, by using ideas from Interacting Multiple Model (IMM) filters, the uncertainty of the system will be adjusted adaptively by model probabilities and using the proposed fuzzy-based fusion framework. The paper also addresses the problem of using corrupted measurements for fault detection purposes by designing a two state propagator chi-square test jointly with the fusion algorithm. Two IMM predictors, running in parallel, are used and alternatively reactivated based on the received information form the fusion filter to increase the reliability and accuracy of the proposed detection solution. With the combination of the IMM and the proposed fusion method, we increase the failure sensitivity of the detection system and, thereby, significantly increase the overall reliability and accuracy of the integrated navigation system. Simulation results indicate that the proposed fault tolerant fusion framework provides superior performance over its traditional counterparts.

Multi-Sensor Fusion with Interaction Multiple Model and Chi-Square Test Tolerant Filter

PubMed Central

Yang, Chun; Mohammadi, Arash; Chen, Qing-Wei

2016-01-01

Motivated by the key importance of multi-sensor information fusion algorithms in the state-of-the-art integrated navigation systems due to recent advancements in sensor technologies, telecommunication, and navigation systems, the paper proposes an improved and innovative fault-tolerant fusion framework. An integrated navigation system is considered consisting of four sensory sub-systems, i.e., Strap-down Inertial Navigation System (SINS), Global Navigation System (GPS), the Bei-Dou2 (BD2) and Celestial Navigation System (CNS) navigation sensors. In such multi-sensor applications, on the one hand, the design of an efficient fusion methodology is extremely constrained specially when no information regarding the system’s error characteristics is available. On the other hand, the development of an accurate fault detection and integrity monitoring solution is both challenging and critical. The paper addresses the sensitivity issues of conventional fault detection solutions and the unavailability of a precisely known system model by jointly designing fault detection and information fusion algorithms. In particular, by using ideas from Interacting Multiple Model (IMM) filters, the uncertainty of the system will be adjusted adaptively by model probabilities and using the proposed fuzzy-based fusion framework. The paper also addresses the problem of using corrupted measurements for fault detection purposes by designing a two state propagator chi-square test jointly with the fusion algorithm. Two IMM predictors, running in parallel, are used and alternatively reactivated based on the received information form the fusion filter to increase the reliability and accuracy of the proposed detection solution. With the combination of the IMM and the proposed fusion method, we increase the failure sensitivity of the detection system and, thereby, significantly increase the overall reliability and accuracy of the integrated navigation system. Simulation results indicate that the proposed fault tolerant fusion framework provides superior performance over its traditional counterparts. PMID:27827832

Leg edema quantification for heart failure patients via 3D imaging.

PubMed

Hayn, Dieter; Fruhwald, Friedrich; Riedel, Arthur; Falgenhauer, Markus; Schreier, Günter

2013-08-14

Heart failure is a common cardiac disease in elderly patients. After discharge, approximately 50% of all patients are readmitted to a hospital within six months. Recent studies show that home monitoring of heart failure patients can reduce the number of readmissions. Still, a large number of false positive alarms as well as underdiagnoses in other cases require more accurate alarm generation algorithms. New low-cost sensors for leg edema detection could be the missing link to help home monitoring to its breakthrough. We evaluated a 3D camera-based measurement setup in order to geometrically detect and quantify leg edemas. 3D images of legs were taken and geometric parameters were extracted semi-automatically from the images. Intra-subject variability for five healthy subjects was evaluated. Thereafter, correlation of 3D parameters with body weight and leg circumference was assessed during a clinical study at the Medical University of Graz. Strong correlation was found in between both reference values and instep height, while correlation in between curvature of the lower leg and references was very low. We conclude that 3D imaging might be a useful and cost-effective extension of home monitoring for heart failure patients, though further (prospective) studies are needed.

A Queueing Approach to Optimal Resource Replication in Wireless Sensor Networks

DTIC Science & Technology

2009-04-29

network (an energy- centric approach) or to ensure the proportion of query failures does not exceed a predetermined threshold (a failure- centric ...replication strategies in wireless sensor networks. The model can be used to minimize either the total transmission rate of the network (an energy- centric ...approach) or to ensure the proportion of query failures does not exceed a predetermined threshold (a failure- centric approach). The model explicitly

An Assessment of the Influence of the Industry Distribution Chain on the Oxygen Levels in Commercial Modified Atmosphere Packaged Cheddar Cheese Using Non-Destructive Oxygen Sensor Technology.

PubMed

O' Callaghan, Karen A M; Papkovsky, Dmitri B; Kerry, Joseph P

2016-06-20

The establishment and control of oxygen levels in packs of oxygen-sensitive food products such as cheese is imperative in order to maintain product quality over a determined shelf life. Oxygen sensors quantify oxygen concentrations within packaging using a reversible optical measurement process, and this non-destructive nature ensures the entire supply chain can be monitored and can assist in pinpointing negative issues pertaining to product packaging. This study was carried out in a commercial cheese packaging plant and involved the insertion of 768 sensors into 384 flow-wrapped cheese packs (two sensors per pack) that were flushed with 100% carbon dioxide prior to sealing. The cheese blocks were randomly assigned to two different storage groups to assess the effects of package quality, packaging process efficiency, and handling and distribution on package containment. Results demonstrated that oxygen levels increased in both experimental groups examined over the 30-day assessment period. The group subjected to a simulated industrial distribution route and handling procedures of commercial retailed cheese exhibited the highest level of oxygen detected on every day examined and experienced the highest rate of package failure. The study concluded that fluctuating storage conditions, product movement associated with distribution activities, and the possible presence of cheese-derived contaminants such as calcium lactate crystals were chief contributors to package failure.

An Assessment of the Influence of the Industry Distribution Chain on the Oxygen Levels in Commercial Modified Atmosphere Packaged Cheddar Cheese Using Non-Destructive Oxygen Sensor Technology

PubMed Central

O’ Callaghan, Karen A.M.; Papkovsky, Dmitri B.; Kerry, Joseph P.

2016-01-01

The establishment and control of oxygen levels in packs of oxygen-sensitive food products such as cheese is imperative in order to maintain product quality over a determined shelf life. Oxygen sensors quantify oxygen concentrations within packaging using a reversible optical measurement process, and this non-destructive nature ensures the entire supply chain can be monitored and can assist in pinpointing negative issues pertaining to product packaging. This study was carried out in a commercial cheese packaging plant and involved the insertion of 768 sensors into 384 flow-wrapped cheese packs (two sensors per pack) that were flushed with 100% carbon dioxide prior to sealing. The cheese blocks were randomly assigned to two different storage groups to assess the effects of package quality, packaging process efficiency, and handling and distribution on package containment. Results demonstrated that oxygen levels increased in both experimental groups examined over the 30-day assessment period. The group subjected to a simulated industrial distribution route and handling procedures of commercial retailed cheese exhibited the highest level of oxygen detected on every day examined and experienced the highest rate of package failure. The study concluded that fluctuating storage conditions, product movement associated with distribution activities, and the possible presence of cheese-derived contaminants such as calcium lactate crystals were chief contributors to package failure. PMID:27331815

A Remote Patient Monitoring System for Congestive Heart Failure

PubMed Central

Suh, Myung-kyung; Chen, Chien-An; Woodbridge, Jonathan; Tu, Michael Kai; Kim, Jung In; Nahapetian, Ani; Evangelista, Lorraine S.; Sarrafzadeh, Majid

2011-01-01

Congestive heart failure (CHF) is a leading cause of death in the United States affecting approximately 670,000 individuals. Due to the prevalence of CHF related issues, it is prudent to seek out methodologies that would facilitate the prevention, monitoring, and treatment of heart disease on a daily basis. This paper describes WANDA (Weight and Activity with Blood Pressure Monitoring System); a study that leverages sensor technologies and wireless communications to monitor the health related measurements of patients with CHF. The WANDA system is a three-tier architecture consisting of sensors, web servers, and back-end databases. The system was developed in conjunction with the UCLA School of Nursing and the UCLA Wireless Health Institute to enable early detection of key clinical symptoms indicative of CHF-related decompensation. This study shows that CHF patients monitored by WANDA are less likely to have readings fall outside a healthy range. In addition, WANDA provides a useful feedback system for regulating readings of CHF patients. PMID:21611788

Comparison of different modelling approaches of drive train temperature for the purposes of wind turbine failure detection

NASA Astrophysics Data System (ADS)

Tautz-Weinert, J.; Watson, S. J.

2016-09-01

Effective condition monitoring techniques for wind turbines are needed to improve maintenance processes and reduce operational costs. Normal behaviour modelling of temperatures with information from other sensors can help to detect wear processes in drive trains. In a case study, modelling of bearing and generator temperatures is investigated with operational data from the SCADA systems of more than 100 turbines. The focus is here on automated training and testing on a farm level to enable an on-line system, which will detect failures without human interpretation. Modelling based on linear combinations, artificial neural networks, adaptive neuro-fuzzy inference systems, support vector machines and Gaussian process regression is compared. The selection of suitable modelling inputs is discussed with cross-correlation analyses and a sensitivity study, which reveals that the investigated modelling techniques react in different ways to an increased number of inputs. The case study highlights advantages of modelling with linear combinations and artificial neural networks in a feedforward configuration.

Immunity-based detection, identification, and evaluation of aircraft sub-system failures

NASA Astrophysics Data System (ADS)

Moncayo, Hever Y.

This thesis describes the design, development, and flight-simulation testing of an integrated Artificial Immune System (AIS) for detection, identification, and evaluation of a wide variety of sensor, actuator, propulsion, and structural failures/damages including the prediction of the achievable states and other limitations on performance and handling qualities. The AIS scheme achieves high detection rate and low number of false alarms for all the failure categories considered. Data collected using a motion-based flight simulator are used to define the self for an extended sub-region of the flight envelope. The NASA IFCS F-15 research aircraft model is used and represents a supersonic fighter which include model following adaptive control laws based on non-linear dynamic inversion and artificial neural network augmentation. The flight simulation tests are designed to analyze and demonstrate the performance of the immunity-based aircraft failure detection, identification and evaluation (FDIE) scheme. A general robustness analysis is also presented by determining the achievable limits for a desired performance in the presence of atmospheric perturbations. For the purpose of this work, the integrated AIS scheme is implemented based on three main components. The first component performs the detection when one of the considered failures is present in the system. The second component consists in the identification of the failure category and the classification according to the failed element. During the third phase a general evaluation of the failure is performed with the estimation of the magnitude/severity of the failure and the prediction of its effect on reducing the flight envelope of the aircraft system. Solutions and alternatives to specific design issues of the AIS scheme, such as data clustering and empty space optimization, data fusion and duplication removal, definition of features, dimensionality reduction, and selection of cluster/detector shape are also analyzed in this thesis. They showed to have an important effect on detection performance and are a critical aspect when designing the configuration of the AIS. The results presented in this thesis show that the AIS paradigm addresses directly the complexity and multi-dimensionality associated with a damaged aircraft dynamic response and provides the tools necessary for a comprehensive/integrated solution to the FDIE problem. Excellent detection, identification, and evaluation performance has been recorded for all types of failures considered. The implementation of the proposed AIS-based scheme can potentially have a significant impact on the safety of aircraft operation. The output information obtained from the scheme will be useful to increase pilot situational awareness and determine automated compensation.

Robot Position Sensor Fault Tolerance

NASA Technical Reports Server (NTRS)

Aldridge, Hal A.

1997-01-01

Robot systems in critical applications, such as those in space and nuclear environments, must be able to operate during component failure to complete important tasks. One failure mode that has received little attention is the failure of joint position sensors. Current fault tolerant designs require the addition of directly redundant position sensors which can affect joint design. A new method is proposed that utilizes analytical redundancy to allow for continued operation during joint position sensor failure. Joint torque sensors are used with a virtual passive torque controller to make the robot joint stable without position feedback and improve position tracking performance in the presence of unknown link dynamics and end-effector loading. Two Cartesian accelerometer based methods are proposed to determine the position of the joint. The joint specific position determination method utilizes two triaxial accelerometers attached to the link driven by the joint with the failed position sensor. The joint specific method is not computationally complex and the position error is bounded. The system wide position determination method utilizes accelerometers distributed on different robot links and the end-effector to determine the position of sets of multiple joints. The system wide method requires fewer accelerometers than the joint specific method to make all joint position sensors fault tolerant but is more computationally complex and has lower convergence properties. Experiments were conducted on a laboratory manipulator. Both position determination methods were shown to track the actual position satisfactorily. A controller using the position determination methods and the virtual passive torque controller was able to servo the joints to a desired position during position sensor failure.

Acetaminophen and acetone sensing capabilities of nickel ferrite nanostructures

NASA Astrophysics Data System (ADS)

Mondal, Shrabani; Kumari, Manisha; Madhuri, Rashmi; Sharma, Prashant K.

2017-07-01

Present work elucidates the gas sensing and electrochemical sensing capabilities of sol-gel-derived nickel ferrite (NF) nanostructures based on the electrical and electrochemical properties. In current work, the choices of target species (acetone and acetaminophen) are strictly governed by their practical utility and concerning the safety measures. Acetone, the target analyte for gas sensing measurement is a common chemical used in varieties of application as well as provides an indirect way to monitor diabetes. The gas sensing experiments were performed within a homemade sensing chamber designed by our group. Acetone gas sensor (NF pellet sensor) response was monitored by tracking the change in resistance both in the presence and absence of acetone. At optimum operating temperature 300 °C, NF pellet sensor exhibits selective response for acetone in the presence of other common interfering gases like ethanol, benzene, and toluene. The electrochemical sensor fabricated to determine acetaminophen is prepared by coating NF onto the surface of pre-treated/cleaned pencil graphite electrode (NF-PGE). The common name of target analyte acetaminophen is paracetamol (PC), which is widespread worldwide as a well-known pain killer. Overdose of PC can cause renal failure even fatal diseases in children and demand accurate monitoring. Under optimal conditions NF-PGE shows a detection limit as low as 0.106 μM with selective detection ability towards acetaminophen in the presence of ascorbic acid (AA), which co-exists in our body. Use of cheap and abundant PGE instead of other electrodes (gold/Pt/glassy carbon electrode) can effectively reduce the cost barrier of such sensors. The obtained results elucidate an ample appeal of NF-sensors in real analytical applications viz. in environmental monitoring, pharmaceutical industry, drug detection, and health monitoring.

Using Wireless Sensor Networks and Trains as Data Mules to Monitor Slab Track Infrastructures.

PubMed

Cañete, Eduardo; Chen, Jaime; Díaz, Manuel; Llopis, Luis; Reyna, Ana; Rubio, Bartolomé

2015-06-26

Recently, slab track systems have arisen as a safer and more sustainable option for high speed railway infrastructures, compared to traditional ballasted tracks. Integrating Wireless Sensor Networks within these infrastructures can provide structural health related data that can be used to evaluate their degradation and to not only detect failures but also to predict them. The design of such systems has to deal with a scenario of large areas with inaccessible zones, where neither Internet coverage nor electricity supply is guaranteed. In this paper we propose a monitoring system for slab track systems that measures vibrations and displacements in the track. Collected data is transmitted to passing trains, which are used as data mules to upload the information to a remote control center. On arrival at the station, the data is stored in a database, which is queried by an application in order to detect and predict failures. In this paper, different communication architectures are designed and tested to select the most suitable system meeting such requirements as efficiency, low cost and data accuracy. In addition, to ensure communication between the sensing devices and the train, the communication system must take into account parameters such as train speed, antenna coverage, band and frequency.

Using Wireless Sensor Networks and Trains as Data Mules to Monitor Slab Track Infrastructures

PubMed Central

Cañete, Eduardo; Chen, Jaime; Díaz, Manuel; Llopis, Luis; Reyna, Ana; Rubio, Bartolomé

2015-01-01

Recently, slab track systems have arisen as a safer and more sustainable option for high speed railway infrastructures, compared to traditional ballasted tracks. Integrating Wireless Sensor Networks within these infrastructures can provide structural health related data that can be used to evaluate their degradation and to not only detect failures but also to predict them. The design of such systems has to deal with a scenario of large areas with inaccessible zones, where neither Internet coverage nor electricity supply is guaranteed. In this paper we propose a monitoring system for slab track systems that measures vibrations and displacements in the track. Collected data is transmitted to passing trains, which are used as data mules to upload the information to a remote control center. On arrival at the station, the data is stored in a database, which is queried by an application in order to detect and predict failures. In this paper, different communication architectures are designed and tested to select the most suitable system meeting such requirements as efficiency, low cost and data accuracy. In addition, to ensure communication between the sensing devices and the train, the communication system must take into account parameters such as train speed, antenna coverage, band and frequency. PMID:26131668

Inductive System Monitors Tasks

NASA Technical Reports Server (NTRS)

2008-01-01

The Inductive Monitoring System (IMS) software developed at Ames Research Center uses artificial intelligence and data mining techniques to build system-monitoring knowledge bases from archived or simulated sensor data. This information is then used to detect unusual or anomalous behavior that may indicate an impending system failure. Currently helping analyze data from systems that help fly and maintain the space shuttle and the International Space Station (ISS), the IMS has also been employed by data classes are then used to build a monitoring knowledge base. In real time, IMS performs monitoring functions: determining and displaying the degree of deviation from nominal performance. IMS trend analyses can detect conditions that may indicate a failure or required system maintenance. The development of IMS was motivated by the difficulty of producing detailed diagnostic models of some system components due to complexity or unavailability of design information. Successful applications have ranged from real-time monitoring of aircraft engine and control systems to anomaly detection in space shuttle and ISS data. IMS was used on shuttle missions STS-121, STS-115, and STS-116 to search the Wing Leading Edge Impact Detection System (WLEIDS) data for signs of possible damaging impacts during launch. It independently verified findings of the WLEIDS Mission Evaluation Room (MER) analysts and indicated additional points of interest that were subsequently investigated by the MER team. In support of the Exploration Systems Mission Directorate, IMS is being deployed as an anomaly detection tool on ISS mission control consoles in the Johnson Space Center Mission Operations Directorate. IMS has been trained to detect faults in the ISS Control Moment Gyroscope (CMG) systems. In laboratory tests, it has already detected several minor anomalies in real-time CMG data. When tested on archived data, IMS was able to detect precursors of the CMG1 failure nearly 15 hours in advance of the actual failure event. In the Aeronautics Research Mission Directorate, IMS successfully performed real-time engine health analysis. IMS was able to detect simulated failures and actual engine anomalies in an F/A-18 aircraft during the course of 25 test flights. IMS is also being used in colla

Integrating Oil Debris and Vibration Measurements for Intelligent Machine Health Monitoring. Degree awarded by Toledo Univ., May 2002

NASA Technical Reports Server (NTRS)

Dempsey, Paula J.

2003-01-01

A diagnostic tool for detecting damage to gears was developed. Two different measurement technologies, oil debris analysis and vibration were integrated into a health monitoring system for detecting surface fatigue pitting damage on gears. This integrated system showed improved detection and decision-making capabilities as compared to using individual measurement technologies. This diagnostic tool was developed and evaluated experimentally by collecting vibration and oil debris data from fatigue tests performed in the NASA Glenn Spur Gear Fatigue Rig. An oil debris sensor and the two vibration algorithms were adapted as the diagnostic tools. An inductance type oil debris sensor was selected for the oil analysis measurement technology. Gear damage data for this type of sensor was limited to data collected in the NASA Glenn test rigs. For this reason, this analysis included development of a parameter for detecting gear pitting damage using this type of sensor. The vibration data was used to calculate two previously available gear vibration diagnostic algorithms. The two vibration algorithms were selected based on their maturity and published success in detecting damage to gears. Oil debris and vibration features were then developed using fuzzy logic analysis techniques, then input into a multi sensor data fusion process. Results show combining the vibration and oil debris measurement technologies improves the detection of pitting damage on spur gears. As a result of this research, this new diagnostic tool has significantly improved detection of gear damage in the NASA Glenn Spur Gear Fatigue Rigs. This research also resulted in several other findings that will improve the development of future health monitoring systems. Oil debris analysis was found to be more reliable than vibration analysis for detecting pitting fatigue failure of gears and is capable of indicating damage progression. Also, some vibration algorithms are as sensitive to operational effects as they are to damage. Another finding was that clear threshold limits must be established for diagnostic tools. Based on additional experimental data obtained from the NASA Glenn Spiral Bevel Gear Fatigue Rig, the methodology developed in this study can be successfully implemented on other geared systems.

Caracterisation des signatures de decharges partielles en utilisant une nouvelle generation de coupleurs piezoelectriques

NASA Astrophysics Data System (ADS)

Danouj, Boujemaa

An important issue affecting the sustainability of power transformers is systematic and progressive deterioration of the insulation system by the action of partial discharge. Ideally, it is appropriate to use on line, non-destructive techniques for detection and diagnosis of failures related to insulation systems, in order to determine whether preventive maintenance action is required. Thus, huge material losses can be saved (spared), while improving reliability and system availability. Based on a new generation of piezoelectric sensors (High Temperature Ultrasonic Transducers HTUTs), recently developed by the Industrial Materials Institute (IMI) in Boucherville (Qc, Canada) and offers very interesting features (broad band frequency response, flexible, miniature, economic, etc..), we propose in this thesis an investigation on the applicability of this technology to the problematic of partial discharges. This work presents an analysis of the metrological performance of these sensors and demonstrated empirically the consistency of their measures. It outlines the results of validation from a comparative study with the measures of a standard detection circuit. In addition, it also presents the potential of these sensors to locate partial discharge source position by acoustic emission.

The resilient hybrid fiber sensor network with self-healing function

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Shibo, E-mail: Shibo-Xu@tju.edu.cn; Liu, Tiegen; Ge, Chunfeng

This paper presents a novel resilient fiber sensor network (FSN) with multi-ring architecture, which could interconnect various kinds of fiber sensors responsible for more than one measurands. We explain how the intelligent control system provides sensors with self-healing function meanwhile sensors are working properly, besides each fiber in FSN is under real-time monitoring. We explain the software process and emergency mechanism to respond failures or other circumstances. To improve the efficiency in the use of limited spectrum resources in some situations, we have two different structures to distribute the light sources rationally. Then, we propose a hybrid sensor working inmore » FSN which is a combination of a distributed sensor and a FBG (Fiber Bragg Grating) array fused in a common fiber sensing temperature and vibrations simultaneously with neglectable crosstalk to each other. By making a failure to a working fiber in experiment, the feasibility and effectiveness of the network with a hybrid sensor has been demonstrated, hybrid sensors could not only work as designed but also survive from destructive failures with the help of resilient network and smart and quick self-healing actions. The network has improved the viability of the fiber sensors and diversity of measurands.« less

Inversion Method for Early Detection of ARES-1 Case Breach Failure

NASA Technical Reports Server (NTRS)

Mackey, Ryan M.; Kulikov, Igor K.; Bajwa, Anupa; Berg, Peter; Smelyanskiy, Vadim

2010-01-01

A document describes research into the problem of detecting a case breach formation at an early stage of a rocket flight. An inversion algorithm for case breach allocation is proposed and analyzed. It is shown how the case breach can be allocated at an early stage of its development by using the rocket sensor data and the output data from the control block of the rocket navigation system. The results are simulated with MATLAB/Simulink software. The efficiency of an inversion algorithm for a case breach location is discussed. The research was devoted to the analysis of the ARES-l flight during the first 120 seconds after the launch and early prediction of case breach failure. During this time, the rocket is propelled by its first-stage Solid Rocket Booster (SRB). If a breach appears in SRB case, the gases escaping through it will produce the (side) thrust directed perpendicular to the rocket axis. The side thrust creates torque influencing the rocket attitude. The ARES-l control system will compensate for the side thrust until it reaches some critical value, after which the flight will be uncontrollable. The objective of this work was to obtain the start time of case breach development and its location using the rocket inertial navigation sensors and GNC data. The algorithm was effective for the detection and location of a breach in an SRB field joint at an early stage of its development.

Real-time diagnostics for a reusable rocket engine

NASA Technical Reports Server (NTRS)

Guo, T. H.; Merrill, W.; Duyar, A.

1992-01-01

A hierarchical, decentralized diagnostic system is proposed for the Real-Time Diagnostic System component of the Intelligent Control System (ICS) for reusable rocket engines. The proposed diagnostic system has three layers of information processing: condition monitoring, fault mode detection, and expert system diagnostics. The condition monitoring layer is the first level of signal processing. Here, important features of the sensor data are extracted. These processed data are then used by the higher level fault mode detection layer to do preliminary diagnosis on potential faults at the component level. Because of the closely coupled nature of the rocket engine propulsion system components, it is expected that a given engine condition may trigger more than one fault mode detector. Expert knowledge is needed to resolve the conflicting reports from the various failure mode detectors. This is the function of the diagnostic expert layer. Here, the heuristic nature of this decision process makes it desirable to use an expert system approach. Implementation of the real-time diagnostic system described above requires a wide spectrum of information processing capability. Generally, in the condition monitoring layer, fast data processing is often needed for feature extraction and signal conditioning. This is usually followed by some detection logic to determine the selected faults on the component level. Three different techniques are used to attack different fault detection problems in the NASA LeRC ICS testbed simulation. The first technique employed is the neural network application for real-time sensor validation which includes failure detection, isolation, and accommodation. The second approach demonstrated is the model-based fault diagnosis system using on-line parameter identification. Besides these model based diagnostic schemes, there are still many failure modes which need to be diagnosed by the heuristic expert knowledge. The heuristic expert knowledge is implemented using a real-time expert system tool called G2 by Gensym Corp. Finally, the distributed diagnostic system requires another level of intelligence to oversee the fault mode reports generated by component fault detectors. The decision making at this level can best be done using a rule-based expert system. This level of expert knowledge is also implemented using G2.

An adaptive tracking observer for failure-detection systems

NASA Technical Reports Server (NTRS)

Sidar, M.

1982-01-01

The design problem of adaptive observers applied to linear, constant and variable parameters, multi-input, multi-output systems, is considered. It is shown that, in order to keep the observer's (or Kalman filter) false-alarm rate (FAR) under a certain specified value, it is necessary to have an acceptable proper matching between the observer (or KF) model and the system parameters. An adaptive observer algorithm is introduced in order to maintain desired system-observer model matching, despite initial mismatching and/or system parameter variations. Only a properly designed adaptive observer is able to detect abrupt changes in the system (actuator, sensor failures, etc.) with adequate reliability and FAR. Conditions for convergence for the adaptive process were obtained, leading to a simple adaptive law (algorithm) with the possibility of an a priori choice of fixed adaptive gains. Simulation results show good tracking performance with small observer output errors and accurate and fast parameter identification, in both deterministic and stochastic cases.

Phased Array Probe Optimization for the Inspection of Titanium Billets

NASA Astrophysics Data System (ADS)

Rasselkorde, E.; Cooper, I.; Wallace, P.; Lupien, V.

2010-02-01

The manufacturing process of titanium billets can produce multiple sub-surface defects that are particularly difficult to detect during the early stages of production. Failure to detect these defects can lead to subsequent in-service failure. A new and novel automated quality control system is being developed for the inspection of titanium billets destined for use in aerospace applications. The sensors will be deployed by an automated system to minimise the use of manual inspections, which should improve the quality and reliability of these critical inspections early on in the manufacturing process. This paper presents the first part of the work, which is the design and the simulation of the phased array ultrasonic inspection of the billets. A series of phased array transducers were designed to optimise the ultrasonic inspection of a ten inch diameter billet made from Titanium 6Al-4V. A comparison was performed between different probes including a 2D annular sectorial array.

Capacitance-based damage detection sensing for aerospace structural composites

NASA Astrophysics Data System (ADS)

Bahrami, P.; Yamamoto, N.; Chen, Y.; Manohara, H.

2014-04-01

Damage detection technology needs improvement for aerospace engineering application because detection within complex composite structures is difficult yet critical to avoid catastrophic failure. Damage detection is challenging in aerospace structures because not all the damage detection technology can cover the various defect types (delamination, fiber fracture, matrix crack etc.), or conditions (visibility, crack length size, etc.). These defect states are expected to become even more complex with future introduction of novel composites including nano-/microparticle reinforcement. Currently, non-destructive evaluation (NDE) methods with X-ray, ultrasound, or eddy current have good resolutions (< 0.1 mm), but their detection capabilities is limited by defect locations and orientations and require massive inspection devices. System health monitoring (SHM) methods are often paired with NDE technologies to signal out sensed damage, but their data collection and analysis currently requires excessive wiring and complex signal analysis. Here, we present a capacitance sensor-based, structural defect detection technology with improved sensing capability. Thin dielectric polymer layer is integrated as part of the structure; the defect in the structure directly alters the sensing layer's capacitance, allowing full-coverage sensing capability independent of defect size, orientation or location. In this work, capacitance-based sensing capability was experimentally demonstrated with a 2D sensing layer consisting of a dielectric layer sandwiched by electrodes. These sensing layers were applied on substrate surfaces. Surface indentation damage (~1mm diameter) and its location were detected through measured capacitance changes: 1 to 250 % depending on the substrates. The damage detection sensors are light weight, and they can be conformably coated and can be part of the composite structure. Therefore it is suitable for aerospace structures such as cryogenic tanks and rocket fairings for example. The sensors can also be operating in space and harsh environment such as high temperature and vacuum.

Duplex Bioelectronic Tongue for Sensing Umami and Sweet Tastes Based on Human Taste Receptor Nanovesicles.

PubMed

Ahn, Sae Ryun; An, Ji Hyun; Song, Hyun Seok; Park, Jin Wook; Lee, Sang Hun; Kim, Jae Hyun; Jang, Jyongsik; Park, Tai Hyun

2016-08-23

For several decades, significant efforts have been made in developing artificial taste sensors to recognize the five basic tastes. So far, the well-established taste sensor is an E-tongue, which is constructed with polymer and lipid membranes. However, the previous artificial taste sensors have limitations in various food, beverage, and cosmetic industries because of their failure to mimic human taste reception. There are many interactions between tastants. Therefore, detecting the interactions in a multiplexing system is required. Herein, we developed a duplex bioelectronic tongue (DBT) based on graphene field-effect transistors that were functionalized with heterodimeric human umami taste and sweet taste receptor nanovesicles. Two types of nanovesicles, which have human T1R1/T1R3 for the umami taste and human T1R2/T1R3 for the sweet taste on their membranes, immobilized on micropatterned graphene surfaces were used for the simultaneous detection of the umami and sweet tastants. The DBT platform led to highly sensitive and selective recognition of target tastants at low concentrations (ca. 100 nM). Moreover, our DBT was able to detect the enhancing effect of taste enhancers as in a human taste sensory system. This technique can be a useful tool for the detection of tastes instead of sensory evaluation and development of new artificial tastants in the food and beverage industry.

Integrated development of light armored vehicles based on wargaming simulators

NASA Astrophysics Data System (ADS)

Palmarini, Marc; Rapanotti, John

2004-08-01

Vehicles are evolving into vehicle networks through improved sensors, computers and communications. Unless carefully planned, these complex systems can result in excessive crew workload and difficulty in optimizing the use of the vehicle. To overcome these problems, a war-gaming simulator is being developed as a common platform to integrate contributions from three different groups. The simulator, OneSAF, is used to integrate simplified models of technology and natural phenomena from scientists and engineers with tactics and doctrine from the military and analyzed in detail by operations analysts. This approach ensures the modelling of processes known to be important regardless of the level of information available about the system. Vehicle survivability can be improved as well with better sensors, computers and countermeasures to detect and avoid or destroy threats. To improve threat detection and reliability, Defensive Aids Suite (DAS) designs are based on three complementary sensor technologies including: acoustics, visible and infrared optics and radar. Both active armour and softkill countermeasures are considered. In a typical scenario, a search radar, providing continuous hemispherical coverage, detects and classifies the threat and cues a tracking radar. Data from the tracking radar is processed and an explosive grenade is launched to destroy or deflect the threat. The angle of attack and velocity from the search radar can be used by the soft-kill system to carry out an infrared search and track or an illuminated range-gated scan for the threat platform. Upon detection, obscuration, countermanoeuvres and counterfire can be used against the threat. The sensor suite is completed by acoustic detection of muzzle blast and shock waves. Automation and networking at the platoon level contribute to improved vehicle survivability. Sensor data fusion is essential in avoiding catastrophic failure of the DAS. The modular DAS components can be used with Light Armoured Vehicle (LAV) variants including: armoured personnel carriers and direct-fire support vehicles. OneSAF will be used to assess the performance of these DAS-equipped vehicles on a virtual battlefield.

Selective monitoring

NASA Astrophysics Data System (ADS)

Homem-de-Mello, Luiz S.

1992-04-01

While in NASA's earlier space missions such as Voyager the number of sensors was in the hundreds, future platforms such as the Space Station Freedom will have tens of thousands sensors. For these planned missions it will be impossible to use the comprehensive monitoring strategy that was used in the past in which human operators monitored all sensors all the time. A selective monitoring strategy must be substituted for the current comprehensive strategy. This selective monitoring strategy uses computer tools to preprocess the incoming data and direct the operators' attention to the most critical parts of the physical system at any given time. There are several techniques that can be used to preprocess the incoming information. This paper presents an approach to using diagnostic reasoning techniques to preprocess the sensor data and detect which parts of the physical system require more attention because components have failed or are most likely to have failed. Given the sensor readings and a model of the physical system, a number of assertions are generated and expressed as Boolean equations. The resulting system of Boolean equations is solved symbolically. Using a priori probabilities of component failure and Bayes' rule, revised probabilities of failure can be computed. These will indicate what components have failed or are the most likely to have failed. This approach is suitable for systems that are well understood and for which the correctness of the assertions can be guaranteed. Also, the system must be such that assertions can be made from instantaneous measurements. And the system must be such that changes are slow enough to allow the computation.

Smart Networked Elements in Support of ISHM

NASA Technical Reports Server (NTRS)

Oostdyk, Rebecca; Mata, Carlos; Perotti, Jose M.

2008-01-01

At the core of ISHM is the ability to extract information and knowledge from raw data. Conventional data acquisition systems sample and convert physical measurements to engineering units, which higher-level systems use to derive health and information about processes and systems. Although health management is essential at the top level, there are considerable advantages to implementing health-related functions at the sensor level. The distribution of processing to lower levels reduces bandwidth requirements, enhances data fusion, and improves the resolution for detection and isolation of failures in a system, subsystem, component, or process. The Smart Networked Element (SNE) has been developed to implement intelligent functions and algorithms at the sensor level in support of ISHM.

Digital flight control systems

NASA Technical Reports Server (NTRS)

Caglayan, A. K.; Vanlandingham, H. F.

1977-01-01

The design of stable feedback control laws for sampled-data systems with variable rate sampling was investigated. These types of sampled-data systems arise naturally in digital flight control systems which use digital actuators where it is desirable to decrease the number of control computer output commands in order to save wear and tear of the associated equipment. The design of aircraft control systems which are optimally tolerant of sensor and actuator failures was also studied. Detection of the failed sensor or actuator must be resolved and if the estimate of the state is used in the control law, then it is also desirable to have an estimator which will give the optimal state estimate even under the failed conditions.

Real time and in vivo monitoring of nitric oxide by electrochemical sensors--from dream to reality.

PubMed

Zhang, Xueji

2004-09-01

Nitric oxide is a key intercellular messenger in the human and animal bodies. The identification of nitric oxide (NO) as the endothelium-derived relaxing factor (EDRF) has driven an enormous effort to further elucidate the chemistry, biology and therapeutic actions of this important molecule. It has found that nitric oxide is involved in many disease states such as such as chronic heart failure, stroke, impotent (erectile dysfunction). The bioactivity of nitric oxide intrinsically linked to its diffusion from its site production to the sites of action. Accurate reliable in real time detection of NO in various biological systems is therefore crucial to understanding its biological role. However, the instability of NO in aqueous solution and its high reactivity with other molecules can cause difficulties for its measurement depending on the detection method employed. Although a variety of methods have been described to measure NO in aqueous environments, it is now generally accepted that electrochemical (amperometric) detection using NO-specific electrodes is the most reliable and sensitive technique available for real-time in situ detection of NO. In 1992 the first commercial NO electrode-based amperometric detection system was developed by WPI. The system has been used successfully for a number of years in a wide range of research applications, both in vitro and in vivo. Recently, many new electrochemical nitric sensors have been invented and commercialized. Here we describe some of the background principles in NO sensors design, methodology and their applications.

Filament Advance Detection Sensor for Fused Deposition Modelling 3D Printers

PubMed Central

Islán Marcos, Manuel

2018-01-01

The main purpose of this paper is to present a system to detect extrusion failures in fused deposition modelling (FDM) 3D printers by sensing that the filament is moving forward properly. After several years using these kind of machines, authors detected that there is not any system to detect the main problem in FDM machines. Authors thought in different sensors and used the weighted objectives method, one of the most common evaluation methods, for comparing design concepts based on an overall value per design concept. Taking into account the obtained scores of each specification, the best choice for this work is the optical encoder. Once the sensor is chosen, it is necessary to design de part where it will be installed without interfering with the normal function of the machine. To do it, photogrammetry scanning methodology was employed. The developed device perfectly detects the advance of the filament without affecting the normal operation of the machine. Also, it is achieved the primary objective of the system, avoiding loss of material, energy, and mechanical wear, keeping the premise of making a low-cost product that does not significantly increase the cost of the machine. This development has made it possible to use the printer with remains of coil filaments, which were not spent because they were not sufficient to complete an impression. Also, printing models in two colours with only one extruder has been enabled by this development. PMID:29747458

Filament Advance Detection Sensor for Fused Deposition Modelling 3D Printers.

PubMed

Soriano Heras, Enrique; Blaya Haro, Fernando; de Agustín Del Burgo, José M; Islán Marcos, Manuel; D'Amato, Roberto

2018-05-09

The main purpose of this paper is to present a system to detect extrusion failures in fused deposition modelling (FDM) 3D printers by sensing that the filament is moving forward properly. After several years using these kind of machines, authors detected that there is not any system to detect the main problem in FDM machines. Authors thought in different sensors and used the weighted objectives method, one of the most common evaluation methods, for comparing design concepts based on an overall value per design concept. Taking into account the obtained scores of each specification, the best choice for this work is the optical encoder. Once the sensor is chosen, it is necessary to design de part where it will be installed without interfering with the normal function of the machine. To do it, photogrammetry scanning methodology was employed. The developed device perfectly detects the advance of the filament without affecting the normal operation of the machine. Also, it is achieved the primary objective of the system, avoiding loss of material, energy, and mechanical wear, keeping the premise of making a low-cost product that does not significantly increase the cost of the machine. This development has made it possible to use the printer with remains of coil filaments, which were not spent because they were not sufficient to complete an impression. Also, printing models in two colours with only one extruder has been enabled by this development.

On the use of temperature for online condition monitoring of geared systems - A review

NASA Astrophysics Data System (ADS)

Touret, T.; Changenet, C.; Ville, F.; Lalmi, M.; Becquerelle, S.

2018-02-01

Gear unit condition monitoring is a key factor for mechanical system reliability management. When they are subjected to failure, gears and bearings may generate excessive vibration, debris and heat. Vibratory, acoustic or debris analyses are proven approaches to perform condition monitoring. An alternative to those methods is to use temperature as a condition indicator to detect gearbox failure. The review focuses on condition monitoring studies which use this thermal approach. According to the failure type and the measurement method, it exists a distinction whether it is contact (e.g. thermocouple) or non-contact temperature sensor (e.g. thermography). Capabilities and limitations of this approach are discussed. It is shown that the use of temperature for condition monitoring has a clear potential as an alternative to vibratory or acoustic health monitoring.

Management of redundancy in flight control systems using optimal decision theory

NASA Technical Reports Server (NTRS)

1981-01-01

The problem of using redundancy that exists between dissimilar systems in aircraft flight control is addressed. That is, using the redundancy that exists between a rate gyro and an accelerometer--devices that have dissimilar outputs which are related only through the dynamics of the aircraft motion. Management of this type of redundancy requires advanced logic so that the system can monitor failure status and can reconfigure itself in the event of one or more failures. An optimal decision theory was tutorially developed for the management of sensor redundancy and the theory is applied to two aircraft examples. The first example is the space shuttle and the second is a highly maneuvering high performance aircraft--the F8-C. The examples illustrate the redundancy management design process and the performance of the algorithms presented in failure detection and control law reconfiguration.

The Elderly’s Independent Living in Smart Homes: A Characterization of Activities and Sensing Infrastructure Survey to Facilitate Services Development

PubMed Central

Ni, Qin; García Hernando, Ana Belén; de la Cruz, Iván Pau

2015-01-01

Human activity detection within smart homes is one of the basis of unobtrusive wellness monitoring of a rapidly aging population in developed countries. Most works in this area use the concept of “activity” as the building block with which to construct applications such as healthcare monitoring or ambient assisted living. The process of identifying a specific activity encompasses the selection of the appropriate set of sensors, the correct preprocessing of their provided raw data and the learning/reasoning using this information. If the selection of the sensors and the data processing methods are wrongly performed, the whole activity detection process may fail, leading to the consequent failure of the whole application. Related to this, the main contributions of this review are the following: first, we propose a classification of the main activities considered in smart home scenarios which are targeted to older people’s independent living, as well as their characterization and formalized context representation; second, we perform a classification of sensors and data processing methods that are suitable for the detection of the aforementioned activities. Our aim is to help researchers and developers in these lower-level technical aspects that are nevertheless fundamental for the success of the complete application. PMID:26007717

The Elderly's Independent Living in Smart Homes: A Characterization of Activities and Sensing Infrastructure Survey to Facilitate Services Development.

PubMed

Ni, Qin; García Hernando, Ana Belén; de la Cruz, Iván Pau

2015-05-14

Human activity detection within smart homes is one of the basis of unobtrusive wellness monitoring of a rapidly aging population in developed countries. Most works in this area use the concept of "activity" as the building block with which to construct applications such as healthcare monitoring or ambient assisted living. The process of identifying a specific activity encompasses the selection of the appropriate set of sensors, the correct preprocessing of their provided raw data and the learning/reasoning using this information. If the selection of the sensors and the data processing methods are wrongly performed, the whole activity detection process may fail, leading to the consequent failure of the whole application. Related to this, the main contributions of this review are the following: first, we propose a classification of the main activities considered in smart home scenarios which are targeted to older people's independent living, as well as their characterization and formalized context representation; second, we perform a classification of sensors and data processing methods that are suitable for the detection of the aforementioned activities. Our aim is to help researchers and developers in these lower-level technical aspects that are nevertheless fundamental for the success of the complete application.

Multisensor and Multispectral Approach in Documenting and Analyzing Liquefaction Hazard using Remote Sensing

NASA Astrophysics Data System (ADS)

Oommen, T.; Baise, L. G.; Gens, R.; Prakash, A.; Gupta, R. P.

2008-12-01

Seismic liquefaction is the loss of strength of soil due to shaking that leads to various ground failures such as lateral spreading, settlements, tilting, and sand boils. It is important to document these failures after earthquakes to advance our study of when and where liquefaction occurs. The current approach of mapping these failures by field investigation teams suffers due to the inaccessibility to some of the sites immediately after the event, short life of some of these failures, difficulties in mapping the aerial extent of the failure, incomplete coverage etc. After the 2001 Bhuj earthquake (India), researchers, using the Indian remote sensing satellite, illustrated that satellite remote sensing can provide a synoptic view of the terrain and offer unbiased estimates of liquefaction failures. However, a multisensor (data from different sensors onboard of the same or different satellites) and multispectral (data collected in different spectral regions) approach is needed to efficiently document liquefaction incidences and/or its potential of occurrence due to the possibility of a particular satellite being located inappropriately to image an area shortly after an earthquake. The use of SAR satellite imagery ensures the acquisition of data in all weather conditions at day and night as well as information complimentary to the optical data sets. In this study, we analyze the applicability of the various satellites (Landsat, RADARSAT, Terra-MISR, IRS-1C, IRS-1D) in mapping liquefaction failures after the 2001 Bhuj earthquake using Support Vector Data Description (SVDD). The SVDD is a kernel based nonparametric outlier detection algorithm inspired by the Support Vector Machines (SVMs), which is a new generation learning algorithm based on the statistical learning theory. We present the applicability of SVDD for unsupervised change-detection studies (i.e. to identify post-earthquake liquefaction failures). The liquefaction occurrences identified from the different satellites using SVDD have been compared to the ground truth in terms of documented liquefaction failures by other researchers. We present the applicability and appropriateness of the various satellites and spectral regions for documenting liquefaction related failures. Results illustrate that the SVDD is a promising unsupervised change-detection algorithm, which can help in automating the documentation of earthquake induced liquefaction failures.

Two-Scale Simulation of Drop-Induced Failure of Polysilicon MEMS Sensors

PubMed Central

Mariani, Stefano; Ghisi, Aldo; Corigliano, Alberto; Martini, Roberto; Simoni, Barbara

2011-01-01

In this paper, an industrially-oriented two-scale approach is provided to model the drop-induced brittle failure of polysilicon MEMS sensors. The two length-scales here investigated are the package (macroscopic) and the sensor (mesoscopic) ones. Issues related to the polysilicon morphology at the micro-scale are disregarded; an upscaled homogenized constitutive law, able to describe the brittle cracking of silicon, is instead adopted at the meso-scale. The two-scale approach is validated against full three-scale Monte-Carlo simulations, which allow for stochastic effects linked to the microstructural properties of polysilicon. Focusing on inertial MEMS sensors exposed to drops, it is shown that the offered approach matches well the experimentally observed failure mechanisms. PMID:22163885

Exception handling for sensor fusion

NASA Astrophysics Data System (ADS)

Chavez, G. T.; Murphy, Robin R.

1993-08-01

This paper presents a control scheme for handling sensing failures (sensor malfunctions, significant degradations in performance due to changes in the environment, and errant expectations) in sensor fusion for autonomous mobile robots. The advantages of the exception handling mechanism are that it emphasizes a fast response to sensing failures, is able to use only a partial causal model of sensing failure, and leads to a graceful degradation of sensing if the sensing failure cannot be compensated for. The exception handling mechanism consists of two modules: error classification and error recovery. The error classification module in the exception handler attempts to classify the type and source(s) of the error using a modified generate-and-test procedure. If the source of the error is isolated, the error recovery module examines its cache of recovery schemes, which either repair or replace the current sensing configuration. If the failure is due to an error in expectation or cannot be identified, the planner is alerted. Experiments using actual sensor data collected by the CSM Mobile Robotics/Machine Perception Laboratory's Denning mobile robot demonstrate the operation of the exception handling mechanism.

Approach to Achieve High Availability in Critical Infrastructure

DTIC Science & Technology

2015-09-01

possibility of sensing temperature, vibration , noise , lubrication, and corrosion. The basis of condition-based maintenance is an accurate assessment of the... vibration would be a sign of possible issues such as misalignment or excessive wear and tear. Noise monitoring can complement the temperature sensor...Availability of good sensor Maintenance Approach Cooling systems Unobservable failure Vibration sensor TBM/CBM Blast doors Observable failure No TBM

Low-cost EEG-based sleep detection.

PubMed

Van Hal, Bryan; Rhodes, Samhita; Dunne, Bruce; Bossemeyer, Robert

2014-01-01

A real-time stage 1 sleep detection system using a low-cost single dry-sensor EEG headset is described. This device issues an auditory warning at the onset of stage 1 sleep using the "NeuroSky Mindset," an inexpensive commercial entertainment-based headset. The EEG signal is filtered into low/high alpha and low/high beta frequency bands which are analyzed to indicate the onset of sleep. Preliminary results indicate an 81% effective rate of detecting sleep with all failures being false positives of sleep onset. This device was able to predict and respond to the onset of drowsiness preceding stage 1 sleep allowing for earlier warnings with the result of fewer sleep-related accidents.

STS-114 Engine Cut-off Sensor Anomaly Technical Consultation Report

NASA Technical Reports Server (NTRS)

Wilson, Timmy R.; Kichak, Robert A.; Ungar, Eugene K.; Cherney, Robert; Rickman, Steve L.

2009-01-01

The NESC consultation team participated in real-time troubleshooting of the Main Propulsion System (MPS) Engine Cutoff (ECO) sensor system failures during STS-114 launch countdown. The team assisted with External Tank (ET) thermal and ECO Point Sensor Box (PSB) circuit analyses, and made real-time inputs to the Space Shuttle Program (SSP) problem resolution teams. Several long-term recommendations resulted. One recommendation was to conduct cryogenic tests of the ECO sensors to validate, or disprove, the theory that variations in circuit impedance due to cryogenic effects on swaged connections within the sensor were the root cause of STS-114 failures.

Gasohol Quality Control for Real Time Applications by Means of a Multimode Interference Fiber Sensor

PubMed Central

Rodríguez Rodríguez, Adolfo J.; Baldovino-Pantaleón, Oscar; Domínguez Cruz, Rene F.; Zamarreño, Carlos R.; Matías, Ignacio R.; May-Arrioja, Daniel A.

2014-01-01

In this work we demonstrate efficient quality control of a variety of gasoline and ethanol (gasohol) blends using a multimode interference (MMI) fiber sensor. The operational principle relies on the fact that the addition of ethanol to the gasohol blend reduces the refractive index (RI) of the gasoline. Since MMI sensors are capable of detecting small RI changes, the ethanol content of the gasohol blend is easily determined by tracking the MMI peak wavelength response. Gasohol blends with ethanol contents ranging from 0% to 50% has been clearly identified using this device, which provides a linear response with a maximum sensitivity of 0.270 nm/% EtOH. The sensor can also distinguish when water incorporated in the blend has exceeded the maximum volume tolerated by the gasohol blend, which is responsible for phase separation of the ethanol and gasoline and could cause serious engine failures. Since the MMI sensor is straightforward to fabricate and does not require any special coating it is a cost effective solution for real time and in-situ monitoring of the quality of gasohol blends. PMID:25256111

Adaptive Control in the Presence of Simultaneous Sensor Bias and Actuator Failures

NASA Technical Reports Server (NTRS)

Joshi, Suresh M.

2012-01-01

The problem of simultaneously accommodating unknown sensor biases and unknown actuator failures in uncertain systems is considered in a direct model reference adaptive control (MRAC) setting for state tracking using state feedback. Sensor biases and actuator faults may be present at the outset or may occur at unknown instants of time during operation. A modified MRAC law is proposed, which combines sensor bias estimation with control gain adaptation for accommodation of sensor biases and actuator failures. This control law is shown to provide signal boundedness in the resulting system. For the case when an external asymptotically stable sensor bias estimator is available, an MRAC law is developed to accomplish asymptotic state tracking and signal boundedness. For a special case wherein biases are only present in the rate measurements and bias-free position measurements are available, an MRAC law is developed using a model-independent bias estimator, and is shown to provide asymptotic state tracking with signal boundedness.

Estimating time available for sensor fusion exception handling

NASA Astrophysics Data System (ADS)

Murphy, Robin R.; Rogers, Erika

1995-09-01

In previous work, we have developed a generate, test, and debug methodology for detecting, classifying, and responding to sensing failures in autonomous and semi-autonomous mobile robots. An important issue has arisen from these efforts: how much time is there available to classify the cause of the failure and determine an alternative sensing strategy before the robot mission must be terminated? In this paper, we consider the impact of time for teleoperation applications where a remote robot attempts to autonomously maintain sensing in the presence of failures yet has the option to contact the local for further assistance. Time limits are determined by using evidential reasoning with a novel generalization of Dempster-Shafer theory. Generalized Dempster-Shafer theory is used to estimate the time remaining until the robot behavior must be suspended because of uncertainty; this becomes the time limit on autonomous exception handling at the remote. If the remote cannot complete exception handling in this time or needs assistance, responsibility is passed to the local, while the remote assumes a `safe' state. An intelligent assistant then facilitates human intervention, either directing the remote without human assistance or coordinating data collection and presentation to the operator within time limits imposed by the mission. The impact of time on exception handling activities is demonstrated using video camera sensor data.

Characterization of cement-based materials using a reusable piezoelectric impedance-based sensor

NASA Astrophysics Data System (ADS)

Tawie, R.; Lee, H. K.

2011-08-01

This paper proposes a reusable sensor, which employs a piezoceramic (PZT) plate as an active sensing transducer, for non-destructive monitoring of cement-based materials based on the electromechanical impedance (EMI) sensing technique. The advantage of the sensor design is that the PZT can be easily removed from the set-up and re-used for repetitive tests. The applicability of the sensor was demonstrated for monitoring of the setting of cement mortar. EMI measurements were performed using an impedance analyzer and the transformation of the specimen from the plastic to solid state was monitored by automatically measuring the changes in the PZT conductance spectra with respect to curing time using the root mean square deviation (RMSD) algorithm. In another experiment, drying-induced moisture loss of a hardened mortar specimen at saturated surface dry (SSD) condition was measured, and monitored using the reusable sensor to establish a correlation between the RMSD values and moisture loss rate. The reusable sensor was also demonstrated for detecting progressive damages imparted on a mortar specimen attached with the sensor under several loading levels before allowing it to load to failure. Overall, the reusable sensor is an effective and efficient monitoring device that could possibly be used for field application in characterization of cement-based materials.

Determining Performance Acceptability of Electrochemical Oxygen Sensors

NASA Technical Reports Server (NTRS)

Gonzales, Daniel

2012-01-01

A method has been developed to screen commercial electrochemical oxygen sensors to reduce the failure rate. There are three aspects to the method: First, the sensitivity over time (several days) can be measured and the rate of change of the sensitivity can be used to predict sensor failure. Second, an improvement to this method would be to store the sensors in an oxygen-free (e.g., nitrogen) environment and intermittently measure the sensitivity over time (several days) to accomplish the same result while preserving the sensor lifetime by limiting consumption of the electrode. Third, the second time derivative of the sensor response over time can be used to determine the point in time at which the sensors are sufficiently stable for use.

Intelligent Hardware-Enabled Sensor and Software Safety and Health Management for Autonomous UAS

NASA Technical Reports Server (NTRS)

Rozier, Kristin Y.; Schumann, Johann; Ippolito, Corey

2015-01-01

Unmanned Aerial Systems (UAS) can only be deployed if they can effectively complete their mission and respond to failures and uncertain environmental conditions while maintaining safety with respect to other aircraft as well as humans and property on the ground. We propose to design a real-time, onboard system health management (SHM) capability to continuously monitor essential system components such as sensors, software, and hardware systems for detection and diagnosis of failures and violations of safety or performance rules during the ight of a UAS. Our approach to SHM is three-pronged, providing: (1) real-time monitoring of sensor and software signals; (2) signal analysis, preprocessing, and advanced on-the- y temporal and Bayesian probabilistic fault diagnosis; (3) an unobtrusive, lightweight, read-only, low-power hardware realization using Field Programmable Gate Arrays (FPGAs) in order to avoid overburdening limited computing resources or costly re-certi cation of ight software due to instrumentation. No currently available SHM capabilities (or combinations of currently existing SHM capabilities) come anywhere close to satisfying these three criteria yet NASA will require such intelligent, hardwareenabled sensor and software safety and health management for introducing autonomous UAS into the National Airspace System (NAS). We propose a novel approach of creating modular building blocks for combining responsive runtime monitoring of temporal logic system safety requirements with model-based diagnosis and Bayesian network-based probabilistic analysis. Our proposed research program includes both developing this novel approach and demonstrating its capabilities using the NASA Swift UAS as a demonstration platform.

Digital Sensor Technology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thomas, Ken D.; Quinn, Edward L.; Mauck, Jerry L.

The nuclear industry has been slow to incorporate digital sensor technology into nuclear plant designs due to concerns with digital qualification issues. However, the benefits of digital sensor technology for nuclear plant instrumentation are substantial in terms of accuracy and reliability. This paper, which refers to a final report issued in 2013, demonstrates these benefits in direct comparisons of digital and analog sensor applications. Improved accuracy results from the superior operating characteristics of digital sensors. These include improvements in sensor accuracy and drift and other related parameters which reduce total loop uncertainty and thereby increase safety and operating margins. Anmore » example instrument loop uncertainty calculation for a pressure sensor application is presented to illustrate these improvements. This is a side-by-side comparison of the instrument loop uncertainty for both an analog and a digital sensor in the same pressure measurement application. Similarly, improved sensor reliability is illustrated with a sample calculation for determining the probability of failure on demand, an industry standard reliability measure. This looks at equivalent analog and digital temperature sensors to draw the comparison. The results confirm substantial reliability improvement with the digital sensor, due in large part to ability to continuously monitor the health of a digital sensor such that problems can be immediately identified and corrected. This greatly reduces the likelihood of a latent failure condition of the sensor at the time of a design basis event. Notwithstanding the benefits of digital sensors, there are certain qualification issues that are inherent with digital technology and these are described in the report. One major qualification impediment for digital sensor implementation is software common cause failure (SCCF).« less

Acoustic emission measurements of aerospace materials and structures

NASA Technical Reports Server (NTRS)

Sachse, Wolfgang; Gorman, Michael R.

1993-01-01

A development status evaluation is given for aerospace applications of AE location, detection, and source characterization. Attention is given to the neural-like processing of AE signals for graphite/epoxy. It is recommended that development efforts for AE make connections between the material failure process and source dynamics, and study the effects of composite material anisotropy and inhomogeneity on the propagation of AE waves. Broadband, as well as frequency- and wave-mode selective sensors, need to be developed.

On-Die Sensors for Transient Events

NASA Astrophysics Data System (ADS)

Suchak, Mihir Vimal

Failures caused by transient electromagnetic events like Electrostatic Discharge (ESD) are a major concern for embedded systems. The component often failing is an integrated circuit (IC). Determining which IC is affected in a multi-device system is a challenging task. Debugging errors often requires sophisticated lab setups which require intentionally disturbing and probing various parts of the system which might not be easily accessible. Opening the system and adding probes may change its response to the transient event, which further compounds the problem. On-die transient event sensors were developed that require relatively little area on die, making them inexpensive, they consume negligible static current, and do not interfere with normal operation of the IC. These circuits can be used to determine the pin involved and the level of the event in the event of a transient event affecting the IC, thus allowing the user to debug system-level transient events without modifying the system. The circuit and detection scheme design has been completed and verified in simulations with Cadence Virtuoso environment. Simulations accounted for the impact of the ESD protection circuits, parasitics from the I/O pin, package and I/O ring, and included a model of an ESD gun to test the circuit's response to an ESD pulse as specified in IEC 61000-4-2. Multiple detection schemes are proposed. The final detection scheme consists of an event detector and a level sensor. The event detector latches on the presence of an event at a pad, to determine on which pin an event occurred. The level sensor generates current proportional to the level of the event. This current is converted to a voltage and digitized at the A/D converter to be read by the microprocessor. Detection scheme shows good performance in simulations when checked against process variations and different kind of events.

A usability study of a mobile monitoring system for congestive heart failure patients.

PubMed

Svagård, I; Austad, H O; Seeberg, T; Vedum, J; Liverud, A; Mathiesen, B M; Keller, B; Bendixen, O C; Osborne, P; Strisland, F

2014-01-01

Sensor-based monitoring of congestive heart-failure (CHF) patients living at home can improve quality of care, detect exacerbations of disease at an earlier stage and motivate the patient for better self care. This paper reports on a usability study of the ESUMS system that provides continuous measurements of heart rate, activity, upper body posture and skin temperature via a sensor belt and a smartphone as patient terminal. Five CHF patients were included in the trial, all recently discharged from hospital. The nurses experienced continuous heart rate, activity and posture monitoring as useful and objective tools that helped them in their daily assessment of patient health. They also saw the system as an important educational tool to help patients gain insight into their own condition. Three patients liked that they could have a view of their own physiological and activity data, however the smartphones used in the study turned out to be too complicated for the patients to operate. A smartphone is built to be a multi-purpose device, and this may (conceptually and practically) be incompatible with the patients' demands for ease of use.

Sensor Selection and Data Validation for Reliable Integrated System Health Management

NASA Technical Reports Server (NTRS)

Garg, Sanjay; Melcher, Kevin J.

2008-01-01

For new access to space systems with challenging mission requirements, effective implementation of integrated system health management (ISHM) must be available early in the program to support the design of systems that are safe, reliable, highly autonomous. Early ISHM availability is also needed to promote design for affordable operations; increased knowledge of functional health provided by ISHM supports construction of more efficient operations infrastructure. Lack of early ISHM inclusion in the system design process could result in retrofitting health management systems to augment and expand operational and safety requirements; thereby increasing program cost and risk due to increased instrumentation and computational complexity. Having the right sensors generating the required data to perform condition assessment, such as fault detection and isolation, with a high degree of confidence is critical to reliable operation of ISHM. Also, the data being generated by the sensors needs to be qualified to ensure that the assessments made by the ISHM is not based on faulty data. NASA Glenn Research Center has been developing technologies for sensor selection and data validation as part of the FDDR (Fault Detection, Diagnosis, and Response) element of the Upper Stage project of the Ares 1 launch vehicle development. This presentation will provide an overview of the GRC approach to sensor selection and data quality validation and will present recent results from applications that are representative of the complexity of propulsion systems for access to space vehicles. A brief overview of the sensor selection and data quality validation approaches is provided below. The NASA GRC developed Systematic Sensor Selection Strategy (S4) is a model-based procedure for systematically and quantitatively selecting an optimal sensor suite to provide overall health assessment of a host system. S4 can be logically partitioned into three major subdivisions: the knowledge base, the down-select iteration, and the final selection analysis. The knowledge base required for productive use of S4 consists of system design information and heritage experience together with a focus on components with health implications. The sensor suite down-selection is an iterative process for identifying a group of sensors that provide good fault detection and isolation for targeted fault scenarios. In the final selection analysis, a statistical evaluation algorithm provides the final robustness test for each down-selected sensor suite. NASA GRC has developed an approach to sensor data qualification that applies empirical relationships, threshold detection techniques, and Bayesian belief theory to a network of sensors related by physics (i.e., analytical redundancy) in order to identify the failure of a given sensor within the network. This data quality validation approach extends the state-of-the-art, from red-lines and reasonableness checks that flag a sensor after it fails, to include analytical redundancy-based methods that can identify a sensor in the process of failing. The focus of this effort is on understanding the proper application of analytical redundancy-based data qualification methods for onboard use in monitoring Upper Stage sensors.

Multi-function microfluidic platform for sensor integration.

PubMed

Fernandes, Ana C; Semenova, Daria; Panjan, Peter; Sesay, Adama M; Gernaey, Krist V; Krühne, Ulrich

2018-03-06

The limited availability of metabolite-specific sensors for continuous sampling and monitoring is one of the main bottlenecks contributing to failures in bioprocess development. Furthermore, only a limited number of approaches exist to connect currently available measurement systems with high throughput reactor units. This is especially relevant in the biocatalyst screening and characterization stage of process development. In this work, a strategy for sensor integration in microfluidic platforms is demonstrated, to address the need for rapid, cost-effective and high-throughput screening in bioprocesses. This platform is compatible with different sensor formats by enabling their replacement and was built in order to be highly flexible and thus suitable for a wide range of applications. Moreover, this re-usable platform can easily be connected to analytical equipment, such as HPLC, laboratory scale reactors or other microfluidic chips through the use of standardized fittings. In addition, the developed platform includes a two-sensor system interspersed with a mixing channel, which allows the detection of samples that might be outside the first sensor's range of detection, through dilution of the sample solution up to 10 times. In order to highlight the features of the proposed platform, inline monitoring of glucose levels is presented and discussed. Glucose was chosen due to its importance in biotechnology as a relevant substrate. The platform demonstrated continuous measurement of substrate solutions for up to 12 h. Furthermore, the influence of the fluid velocity on substrate diffusion was observed, indicating the need for in-flow calibration to achieve a good quantitative output. Copyright © 2018 Elsevier B.V. All rights reserved.

Remote maintenance monitoring system

NASA Technical Reports Server (NTRS)

Simpkins, Lorenz G. (Inventor); Owens, Richard C. (Inventor); Rochette, Donn A. (Inventor)

1992-01-01

A remote maintenance monitoring system retrofits to a given hardware device with a sensor implant which gathers and captures failure data from the hardware device, without interfering with its operation. Failure data is continuously obtained from predetermined critical points within the hardware device, and is analyzed with a diagnostic expert system, which isolates failure origin to a particular component within the hardware device. For example, monitoring of a computer-based device may include monitoring of parity error data therefrom, as well as monitoring power supply fluctuations therein, so that parity error and power supply anomaly data may be used to trace the failure origin to a particular plane or power supply within the computer-based device. A plurality of sensor implants may be rerofit to corresponding plural devices comprising a distributed large-scale system. Transparent interface of the sensors to the devices precludes operative interference with the distributed network. Retrofit capability of the sensors permits monitoring of even older devices having no built-in testing technology. Continuous real time monitoring of a distributed network of such devices, coupled with diagnostic expert system analysis thereof, permits capture and analysis of even intermittent failures, thereby facilitating maintenance of the monitored large-scale system.

A global stochastic programming approach for the optimal placement of gas detectors with nonuniform unavailabilities

DOE PAGES

Liu, Jianfeng; Laird, Carl Damon

2017-09-22

Optimal design of a gas detection systems is challenging because of the numerous sources of uncertainty, including weather and environmental conditions, leak location and characteristics, and process conditions. Rigorous CFD simulations of dispersion scenarios combined with stochastic programming techniques have been successfully applied to the problem of optimal gas detector placement; however, rigorous treatment of sensor failure and nonuniform unavailability has received less attention. To improve reliability of the design, this paper proposes a problem formulation that explicitly considers nonuniform unavailabilities and all backup detection levels. The resulting sensor placement problem is a large-scale mixed-integer nonlinear programming (MINLP) problem thatmore » requires a tailored solution approach for efficient solution. We have developed a multitree method which depends on iteratively solving a sequence of upper-bounding master problems and lower-bounding subproblems. The tailored global solution strategy is tested on a real data problem and the encouraging numerical results indicate that our solution framework is promising in solving sensor placement problems. This study was selected for the special issue in JLPPI from the 2016 International Symposium of the MKO Process Safety Center.« less

A global stochastic programming approach for the optimal placement of gas detectors with nonuniform unavailabilities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Jianfeng; Laird, Carl Damon

Optimal design of a gas detection systems is challenging because of the numerous sources of uncertainty, including weather and environmental conditions, leak location and characteristics, and process conditions. Rigorous CFD simulations of dispersion scenarios combined with stochastic programming techniques have been successfully applied to the problem of optimal gas detector placement; however, rigorous treatment of sensor failure and nonuniform unavailability has received less attention. To improve reliability of the design, this paper proposes a problem formulation that explicitly considers nonuniform unavailabilities and all backup detection levels. The resulting sensor placement problem is a large-scale mixed-integer nonlinear programming (MINLP) problem thatmore » requires a tailored solution approach for efficient solution. We have developed a multitree method which depends on iteratively solving a sequence of upper-bounding master problems and lower-bounding subproblems. The tailored global solution strategy is tested on a real data problem and the encouraging numerical results indicate that our solution framework is promising in solving sensor placement problems. This study was selected for the special issue in JLPPI from the 2016 International Symposium of the MKO Process Safety Center.« less

High-Fidelity Modeling for Health Monitoring in Honeycomb Sandwich Structures

NASA Technical Reports Server (NTRS)

Luchinsky, Dimitry G.; Hafiychuk, Vasyl; Smelyanskiy, Vadim; Tyson, Richard W.; Walker, James L.; Miller, Jimmy L.

2011-01-01

High-Fidelity Model of the sandwich composite structure with real geometry is reported. The model includes two composite facesheets, honeycomb core, piezoelectric actuator/sensors, adhesive layers, and the impactor. The novel feature of the model is that it includes modeling of the impact and wave propagation in the structure before and after the impact. Results of modeling of the wave propagation, impact, and damage detection in sandwich honeycomb plates using piezoelectric actuator/sensor scheme are reported. The results of the simulations are compared with the experimental results. It is shown that the model is suitable for analysis of the physics of failure due to the impact and for testing structural health monitoring schemes based on guided wave propagation.

Prototyping the E-ELT M1 local control system communication infrastructure

NASA Astrophysics Data System (ADS)

Argomedo, J.; Kornweibel, N.; Grudzien, T.; Dimmler, M.; Andolfato, L.; Barriga, P.

2016-08-01

The primary mirror of the E-ELT is composed of 798 hexagonal segments of about 1.45 meters across. Each segment can be moved in piston and tip-tilt using three position actuators. Inductive edge sensors are used to provide feedback for global reconstruction of the mirror shape. The E-ELT M1 Local Control System will provide a deterministic infrastructure for collecting edge sensor and actuators readings and distribute the new position actuators references while at the same time providing failure detection, isolation and notification, synchronization, monitoring and configuration management. The present paper describes the prototyping activities carried out to verify the feasibility of the E-ELT M1 local control system communication architecture design and assess its performance and potential limitations.

Structural Health Monitoring Using High-Density Fiber Optic Strain Sensor and Inverse Finite Element Methods

NASA Technical Reports Server (NTRS)

Vazquez, Sixto L.; Tessler, Alexander; Quach, Cuong C.; Cooper, Eric G.; Parks, Jeffrey; Spangler, Jan L.

2005-01-01

In an effort to mitigate accidents due to system and component failure, NASA s Aviation Safety has partnered with industry, academia, and other governmental organizations to develop real-time, on-board monitoring capabilities and system performance models for early detection of airframe structure degradation. NASA Langley is investigating a structural health monitoring capability that uses a distributed fiber optic strain system and an inverse finite element method for measuring and modeling structural deformations. This report describes the constituent systems that enable this structural monitoring function and discusses results from laboratory tests using the fiber strain sensor system and the inverse finite element method to demonstrate structural deformation estimation on an instrumented test article

Spiral-Bevel-Gear Damage Detected Using Decision Fusion Analysis

NASA Technical Reports Server (NTRS)

Dempsey, Paula J.; Handschuh, Robert F.

2003-01-01

Helicopter transmission integrity is critical to helicopter safety because helicopters depend on the power train for propulsion, lift, and flight maneuvering. To detect impending transmission failures, the ideal diagnostic tools used in the health-monitoring system would provide real-time health monitoring of the transmission, demonstrate a high level of reliable detection to minimize false alarms, and provide end users with clear information on the health of the system without requiring them to interpret large amounts of sensor data. A diagnostic tool for detecting damage to spiral bevel gears was developed. (Spiral bevel gears are used in helicopter transmissions to transfer power between nonparallel intersecting shafts.) Data fusion was used to integrate two different monitoring technologies, oil debris analysis and vibration, into a health-monitoring system for detecting surface fatigue pitting damage on the gears.

49 CFR 395.15 - Automatic on-board recording devices.

Code of Federal Regulations, 2010 CFR

2010-10-01

... information concerning on-board system sensor failures and identification of edited data. Such support systems... driving today; (iv) Total hours on duty for the 7 consecutive day period, including today; (v) Total hours...-driver operation; (7) The on-board recording device/system identifies sensor failures and edited data...

Health management and controls for earth to orbit propulsion systems

NASA Technical Reports Server (NTRS)

Bickford, R. L.

1992-01-01

Fault detection and isolation for advanced rocket engine controllers are discussed focusing on advanced sensing systems and software which significantly improve component failure detection for engine safety and health management. Aerojet's Space Transportation Main Engine controller for the National Launch System is the state of the art in fault tolerant engine avionics. Health management systems provide high levels of automated fault coverage and significantly improve vehicle delivered reliability and lower preflight operations costs. Key technologies, including the sensor data validation algorithms and flight capable spectrometers, have been demonstrated in ground applications and are found to be suitable for bridging programs into flight applications.

Liquid-propellant rocket engines health-monitoring—a survey

NASA Astrophysics Data System (ADS)

Wu, Jianjun

2005-02-01

This paper is intended to give a summary on the health-monitoring technology, which is one of the key technologies both for improving and enhancing the reliability and safety of current rocket engines and for developing new-generation high reliable reusable rocket engines. The implication of health-monitoring and the fundamental principle obeyed by the fault detection and diagnostics are elucidated. The main aspects of health-monitoring such as system frameworks, failure modes analysis, algorithms of fault detection and diagnosis, control means and advanced sensor techniques are illustrated in some detail. At last, the evolution trend of health-monitoring techniques of liquid-propellant rocket engines is set out.

Cascading failure in the wireless sensor scale-free networks

NASA Astrophysics Data System (ADS)

Liu, Hao-Ran; Dong, Ming-Ru; Yin, Rong-Rong; Han, Li

2015-05-01

In the practical wireless sensor networks (WSNs), the cascading failure caused by a failure node has serious impact on the network performance. In this paper, we deeply research the cascading failure of scale-free topology in WSNs. Firstly, a cascading failure model for scale-free topology in WSNs is studied. Through analyzing the influence of the node load on cascading failure, the critical load triggering large-scale cascading failure is obtained. Then based on the critical load, a control method for cascading failure is presented. In addition, the simulation experiments are performed to validate the effectiveness of the control method. The results show that the control method can effectively prevent cascading failure. Project supported by the Natural Science Foundation of Hebei Province, China (Grant No. F2014203239), the Autonomous Research Fund of Young Teacher in Yanshan University (Grant No. 14LGB017) and Yanshan University Doctoral Foundation, China (Grant No. B867).

Emission control apparatus for internal combustion engines with a controllably disabled clamping circuit

DOE Office of Scientific and Technical Information (OSTI.GOV)

Asano, M.

1979-08-28

The invention discloses an emission control apparatus for internal combustion engine includes an exhaust composition sensor to sense the mixture ratio, a circuit for clamping the mixture ratio to a predetermined constant value to prevent the mixture from becoming too rich or too lean when a failure should occur in the control loop, for example, in the exhaust composition sensor failure and a circuit for interrupting the clamping circuit when the engine operating condition is such that the sensor is caused to produce low voltage signals although the sensor is functioning properly.

Continued Development of Meandering Winding Magnetometer (MWM (Register Trademark)) Eddy Current Sensors for the Health Monitoring, Modeling and Damage Detection of Composite Overwrapped Pressure Vessels

NASA Technical Reports Server (NTRS)

Russell, Richard; Wincheski, Russell; Jablonski, David; Washabaugh, Andy; Sheiretov, Yanko; Martin, Christopher; Goldfine, Neil

2011-01-01

Composite Overwrapped Pressure Vessels (COPVs) are used in essentially all NASA spacecraft, launch. vehicles and payloads to contain high-pressure fluids for propulsion, life support systems and science experiments. Failure of any COPV either in flight or during ground processing would result in catastrophic damage to the spacecraft or payload, and could lead to loss of life. Therefore, NASA continues to investigate new methods to non-destructively inspect (NDE) COPVs for structural anomalies and to provide a means for in-situ structural health monitoring (SHM) during operational service. Partnering with JENTEK Sensors, engineers at NASA, Kennedy Space Center have successfully conducted a proof-of-concept study to develop Meandering Winding Magnetometer (MWM) eddy current sensors designed to make direct measurements of the stresses of the internal layers of a carbon fiber composite wrapped COPV. During this study three different MWM sensors were tested at three orientations to demonstrate the ability of the technology to measure stresses at various fiber orientations and depths. These results showed good correlation with actual surface strain gage measurements. MWM-Array technology for scanning COPVs can reliably be used to image and detect mechanical damage. To validate this conclusion, several COPVs were scanned to obtain a baseline, and then each COPV was impacted at varying energy levels and then rescanned. The baseline subtracted images were used to demonstrate damage detection. These scans were performed with two different MWM-Arrays. with different geometries for near-surface and deeper penetration imaging at multiple frequencies and in multiple orientations of the linear MWM drive. This presentation will include a review of micromechanical models that relate measured sensor responses to composite material constituent properties, validated by the proof of concept study, as the basis for SHM and NDE data analysis as well as potential improvements including design changes to miniaturize and make the sensors durable in the vacuum of space

Rate-based structural health monitoring using permanently installed sensors

PubMed Central

2017-01-01

Permanently installed sensors are becoming increasingly ubiquitous, facilitating very frequent in situ measurements and consequently improved monitoring of ‘trends’ in the observed system behaviour. It is proposed that this newly available data may be used to provide prior warning and forecasting of critical events, particularly system failure. Numerous damage mechanisms are examples of positive feedback; they are ‘self-accelerating’ with an increasing rate of damage towards failure. The positive feedback leads to a common time-response behaviour which may be described by an empirical relation allowing prediction of the time to criticality. This study focuses on Structural Health Monitoring of engineering components; failure times are projected well in advance of failure for fatigue, creep crack growth and volumetric creep damage experiments. The proposed methodology provides a widely applicable framework for using newly available near-continuous data from permanently installed sensors to predict time until failure in a range of application areas including engineering, geophysics and medicine. PMID:28989308

Construction Condition and Damage Monitoring of Post-Tensioned PSC Girders Using Embedded Sensors.

PubMed

Shin, Kyung-Joon; Lee, Seong-Cheol; Kim, Yun Yong; Kim, Jae-Min; Park, Seunghee; Lee, Hwanwoo

2017-08-10

The potential for monitoring the construction of post-tensioned concrete beams and detecting damage to the beams under loading conditions was investigated through an experimental program. First, embedded sensors were investigated that could measure pre-stress from the fabrication process to a failure condition. Four types of sensors were installed on a steel frame, and the applicability and the accuracy of these sensors were tested while pre-stress was applied to a tendon in the steel frame. As a result, a tri-sensor loading plate and a Fiber Bragg Grating (FBG) sensor were selected as possible candidates. With those sensors, two pre-stressed concrete flexural beams were fabricated and tested. The pre-stress of the tendons was monitored during the construction and loading processes. Through the test, it was proven that the variation in thepre-stress had been successfully monitored throughout the construction process. The losses of pre-stress that occurred during a jacking and storage process, even those which occurred inside the concrete, were measured successfully. The results of the loading test showed that tendon stress and strain within the pure span significantly increased, while the stress in areas near the anchors was almost constant. These results prove that FBG sensors installed in a middle section can be used to monitor the strain within, and the damage to pre-stressed concrete beams.

Construction Condition and Damage Monitoring of Post-Tensioned PSC Girders Using Embedded Sensors

PubMed Central

Shin, Kyung-Joon; Lee, Seong-Cheol; Kim, Yun Yong; Kim, Jae-Min; Park, Seunghee; Lee, Hwanwoo

2017-01-01

The potential for monitoring the construction of post-tensioned concrete beams and detecting damage to the beams under loading conditions was investigated through an experimental program. First, embedded sensors were investigated that could measure pre-stress from the fabrication process to a failure condition. Four types of sensors were installed on a steel frame, and the applicability and the accuracy of these sensors were tested while pre-stress was applied to a tendon in the steel frame. As a result, a tri-sensor loading plate and a Fiber Bragg Grating (FBG) sensor were selected as possible candidates. With those sensors, two pre-stressed concrete flexural beams were fabricated and tested. The pre-stress of the tendons was monitored during the construction and loading processes. Through the test, it was proven that the variation in thepre-stress had been successfully monitored throughout the construction process. The losses of pre-stress that occurred during a jacking and storage process, even those which occurred inside the concrete, were measured successfully. The results of the loading test showed that tendon stress and strain within the pure span significantly increased, while the stress in areas near the anchors was almost constant. These results prove that FBG sensors installed in a middle section can be used to monitor the strain within, and the damage to pre-stressed concrete beams. PMID:28796156

Optical-Fiber Leak Detector

NASA Technical Reports Server (NTRS)

Workman, Gary L.; Kosten, Susan E.

1994-01-01

Proposed optical-fiber sensor detects small changes in pressure in elastomeric O-ring or similar pressure seal, which may indicate deterioration of seal and interpreted as indications of incipient failure. According to concept, length of optical fiber embedded in seal. Light-emitting diode illuminates one end of fiber; photodetector measures intensity of light emerging from other end. Pressure-induced changes in seal bend fiber slightly, altering microbending-induced loss of light from fiber and alter intensity of light at photodetector. Change in intensity approximately proportional to change in pressure.

Distributed Health Monitoring System for Reusable Liquid Rocket Engines

NASA Technical Reports Server (NTRS)

Lin, C. F.; Figueroa, F.; Politopoulos, T.; Oonk, S.

2009-01-01

The ability to correctly detect and identify any possible failure in the systems, subsystems, or sensors within a reusable liquid rocket engine is a major goal at NASA John C. Stennis Space Center (SSC). A health management (HM) system is required to provide an on-ground operation crew with an integrated awareness of the condition of every element of interest by determining anomalies, examining their causes, and making predictive statements. However, the complexity associated with relevant systems, and the large amount of data typically necessary for proper interpretation and analysis, presents difficulties in implementing complete failure detection, identification, and prognostics (FDI&P). As such, this paper presents a Distributed Health Monitoring System for Reusable Liquid Rocket Engines as a solution to these problems through the use of highly intelligent algorithms for real-time FDI&P, and efficient and embedded processing at multiple levels. The end result is the ability to successfully incorporate a comprehensive HM platform despite the complexity of the systems under consideration.

Performance Evaluation of a Prototyped Wireless Ground Sensor Network

DTIC Science & Technology

2005-03-01

the network was capable of dynamic adaptation to failure and degradation. 14. SUBJECT TERMS: Wireless Sensor Network , Unmanned Sensor, Unattended...2 H. WIRELESS SENSOR NETWORKS .................................................................... 3...zation, and network traffic. The evaluated scenarios included outdoor, urban and indoor environments. The characteristics of wireless sensor networks , types

Wavelet-based information filtering for fault diagnosis of electric drive systems in electric ships.

PubMed

Silva, Andre A; Gupta, Shalabh; Bazzi, Ali M; Ulatowski, Arthur

2017-09-22

Electric machines and drives have enjoyed extensive applications in the field of electric vehicles (e.g., electric ships, boats, cars, and underwater vessels) due to their ease of scalability and wide range of operating conditions. This stems from their ability to generate the desired torque and power levels for propulsion under various external load conditions. However, as with the most electrical systems, the electric drives are prone to component failures that can degrade their performance, reduce the efficiency, and require expensive maintenance. Therefore, for safe and reliable operation of electric vehicles, there is a need for automated early diagnostics of critical failures such as broken rotor bars and electrical phase failures. In this regard, this paper presents a fault diagnosis methodology for electric drives in electric ships. This methodology utilizes the two-dimensional, i.e. scale-shift, wavelet transform of the sensor data to filter optimal information-rich regions which can enhance the diagnosis accuracy as well as reduce the computational complexity of the classifier. The methodology was tested on sensor data generated from an experimentally validated simulation model of electric drives under various cruising speed conditions. The results in comparison with other existing techniques show a high correct classification rate with low false alarm and miss detection rates. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Haul truck tire dynamics due to tire condition

NASA Astrophysics Data System (ADS)

Vaghar Anzabi, R.; Nobes, D. S.; Lipsett, M. G.

2012-05-01

Pneumatic tires are costly components on large off-road haul trucks used in surface mining operations. Tires are prone to damage during operation, and these events can lead to injuries to personnel, loss of equipment, and reduced productivity. Damage rates have significant variability, due to operating conditions and a range of tire fault modes. Currently, monitoring of tire condition is done by physical inspection; and the mean time between inspections is often longer than the mean time between incipient failure and functional failure of the tire. Options for new condition monitoring methods include off-board thermal imaging and camera-based optical methods for detecting abnormal deformation and surface features, as well as on-board sensors to detect tire faults during vehicle operation. Physics-based modeling of tire dynamics can provide a good understanding of the tire behavior, and give insight into observability requirements for improved monitoring systems. This paper describes a model to simulate the dynamics of haul truck tires when a fault is present to determine the effects of physical parameter changes that relate to faults. To simulate the dynamics, a lumped mass 'quarter-vehicle' model has been used to determine the response of the system to a road profile when a failure changes the original properties of the tire. The result is a model of tire vertical displacement that can be used to detect a fault, which will be tested under field conditions in time-varying conditions.

Generic Sensor Failure Modeling for Cooperative Systems.

PubMed

Jäger, Georg; Zug, Sebastian; Casimiro, António

2018-03-20

The advent of cooperative systems entails a dynamic composition of their components. As this contrasts current, statically composed systems, new approaches for maintaining their safety are required. In that endeavor, we propose an integration step that evaluates the failure model of shared information in relation to an application's fault tolerance and thereby promises maintainability of such system's safety. However, it also poses new requirements on failure models, which are not fulfilled by state-of-the-art approaches. Consequently, this work presents a mathematically defined generic failure model as well as a processing chain for automatically extracting such failure models from empirical data. By examining data of an Sharp GP2D12 distance sensor, we show that the generic failure model not only fulfills the predefined requirements, but also models failure characteristics appropriately when compared to traditional techniques.

Generic Sensor Failure Modeling for Cooperative Systems

PubMed Central

Jäger, Georg; Zug, Sebastian

2018-01-01

The advent of cooperative systems entails a dynamic composition of their components. As this contrasts current, statically composed systems, new approaches for maintaining their safety are required. In that endeavor, we propose an integration step that evaluates the failure model of shared information in relation to an application’s fault tolerance and thereby promises maintainability of such system’s safety. However, it also poses new requirements on failure models, which are not fulfilled by state-of-the-art approaches. Consequently, this work presents a mathematically defined generic failure model as well as a processing chain for automatically extracting such failure models from empirical data. By examining data of an Sharp GP2D12 distance sensor, we show that the generic failure model not only fulfills the predefined requirements, but also models failure characteristics appropriately when compared to traditional techniques. PMID:29558435

Indirect adaptive fuzzy fault-tolerant tracking control for MIMO nonlinear systems with actuator and sensor failures.

PubMed

Bounemeur, Abdelhamid; Chemachema, Mohamed; Essounbouli, Najib

2018-05-10

In this paper, an active fuzzy fault tolerant tracking control (AFFTTC) scheme is developed for a class of multi-input multi-output (MIMO) unknown nonlinear systems in the presence of unknown actuator faults, sensor failures and external disturbance. The developed control scheme deals with four kinds of faults for both sensors and actuators. The bias, drift, and loss of accuracy additive faults are considered along with the loss of effectiveness multiplicative fault. A fuzzy adaptive controller based on back-stepping design is developed to deal with actuator failures and unknown system dynamics. However, an additional robust control term is added to deal with sensor faults, approximation errors, and external disturbances. Lyapunov theory is used to prove the stability of the closed loop system. Numerical simulations on a quadrotor are presented to show the effectiveness of the proposed approach. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Detection and Analysis of the Magnetic Field Component of Electromagnetic Radiation Emission from Macroscopic Fracturing of Cement-Bound Granular Material

NASA Astrophysics Data System (ADS)

Maquiling, J. T.; Ceralde, P. I. B.

2016-12-01

Countries most prone to earthquake damage have been in pursuit of a possible earthquake precursor. This study aims to detect and measure the magnetic field component of the Electromagnetic Radiation (EMR) emitted by quasi-brittle materials that undergo macroscopic fracturing. Cement-Bound Granular Materials (CBGM) were prepared by mixing cement, sand and gravel in a beam mold. Additional aggregates in the form of saw dust were added to produce variable CBGM samples. A concrete beam holder was designed and fabricated such that induced cracks from impact loading would form at the center of the beam. Six Vernier software magnetic field sensors were used to detect the magnetic field (MF) component of the EMR emission. Initial calibration was done to minimize noise in the laboratory. The magnetic field sensors were set at a low amplification range (±6.4x10-3 T) setting with 0.0002 mT precision at 20-50 Hz. Sensor locations and orientations were specified and fixed throughout the experiment. The impact loading process was repeated until concrete failure. The time of drop was determined through the occurrence of peak sound levels (dB) induced by the collision noise using a sound level meter at fast time weighting. Magnetic field fluctuations manifesting near the occurrence of sound level impulses were recorded. Peak magnetic field values within ±200ms from the recorded time of impact were considered to be originating from the concrete fracture. Concrete samples consisting of cement, sand and gravel produced magnetic field emissions measuring 0.58-1.07 μT while the same concrete mixture added with dispersed fine sawdust released 0.55-1.28 μT. A more dispersed set of values of magnetic field emissions were observed for concrete with sawdust. Comparison between the average number of drops done before failure occurs between the two concrete mixtures also indicated that the addition of dispersed sawdust resulted to weaker CBGM samples. Upon increasing input energy from weight drop by 150%, magnetic field emissions from samples of the same concrete mixture showed significant increase with maximum magnitude of emission measured at 1.06 μT. A model of the magnetic field magnitudes with respect to sensor position was generated by non-linear data-fitting method using Microsoft Excel and SciLab.

A method for reduction of Acoustic Emission (AE) data with application in machine failure detection and diagnosis

NASA Astrophysics Data System (ADS)

Vicuña, Cristián Molina; Höweler, Christoph

2017-12-01

The use of AE in machine failure diagnosis has increased over the last years. Most AE-based failure diagnosis strategies use digital signal processing and thus require the sampling of AE signals. High sampling rates are required for this purpose (e.g. 2 MHz or higher), leading to streams of large amounts of data. This situation is aggravated if fine resolution and/or multiple sensors are required. These facts combine to produce bulky data, typically in the range of GBytes, for which sufficient storage space and efficient signal processing algorithms are required. This situation probably explains why, in practice, AE-based methods consist mostly in the calculation of scalar quantities such as RMS and Kurtosis, and the analysis of their evolution in time. While the scalar-based approach offers the advantage of maximum data reduction; it has the disadvantage that most part of the information contained in the raw AE signal is lost unrecoverably. This work presents a method offering large data reduction, while keeping the most important information conveyed by the raw AE signal, useful for failure detection and diagnosis. The proposed method consist in the construction of a synthetic, unevenly sampled signal which envelopes the AE bursts present on the raw AE signal in a triangular shape. The constructed signal - which we call TriSignal - also permits the estimation of most scalar quantities typically used for failure detection. But more importantly, it contains the information of the time of occurrence of the bursts, which is key for failure diagnosis. Lomb-Scargle normalized periodogram is used to construct the TriSignal spectrum, which reveals the frequency content of the TriSignal and provides the same information as the classic AE envelope. The paper includes application examples in planetary gearbox and low-speed rolling element bearing.

Latest Development in Advanced Sensors at Kennedy Space Center (KSC)

NASA Technical Reports Server (NTRS)

Perotti, Jose M.; Eckhoff, Anthony J.; Voska, N. (Technical Monitor)

2002-01-01

Inexpensive space transportation system must be developed in order to make spaceflight more affordable. To achieve this goal, there is a need to develop inexpensive smart sensors to allow autonomous checking of the health of the vehicle and associated ground support equipment, warn technicians or operators of an impending problem and facilitate rapid vehicle pre-launch operations. The Transducers and Data Acquisition group at Kennedy Space Center has initiated an effort to study, research, develop and prototype inexpensive smart sensors to accomplish these goals. Several technological challenges are being investigated and integrated in this project multi-discipline sensors; self-calibration, health self-diagnosis capabilities embedded in sensors; advanced data acquisition systems with failure prediction algorithms and failure correction (self-healing) capabilities.

Collaboration of Miniature Multi-Modal Mobile Smart Robots over a Network

DTIC Science & Technology

2015-08-14

theoretical research on mathematics of failures in sensor-network-based miniature multimodal mobile robots and electromechanical systems. The views...theoretical research on mathematics of failures in sensor-network-based miniature multimodal mobile robots and electromechanical systems. The...independently evolving research directions based on physics-based models of mechanical, electromechanical and electronic devices, operational constraints

Damage Characterization Method for Structural Health Management Using Reduced Number of Sensor Inputs

NASA Technical Reports Server (NTRS)

Krishnamurthy, T.; Hochhalter, Jacob D.; Gallegos, Adam M.

2012-01-01

The development of validated multidisciplinary Integrated Vehicle Health Management (IVHM) tools, technologies, and techniques to enable detection, diagnosis, prognosis, and mitigation in the presence of adverse conditions during flight will provide effective solutions to deal with safety related challenges facing next generation aircraft. The adverse conditions include loss of control caused by environmental factors, actuator and sensor faults or failures, and damage conditions. A major concern in these structures is the growth of undetected damage (cracks) due to fatigue and low velocity foreign impacts that can reach a critical size during flight, resulting in loss of control of the aircraft. Hence, development of efficient methodologies to determine the presence, location, and severity of damage in critical structural components is highly important in developing efficient structural health management systems.

Structural health monitoring technology for bolted carbon-carbon thermal protection panels

NASA Astrophysics Data System (ADS)

Yang, Jinkyu

2005-12-01

The research in this dissertation is motivated by the need for reliable inspection technologies for the detection of bolt loosening in Carbon-Carbon (C-C) Thermal Protection System (TPS) panels on Space Operation Vehicles (SOV) using minimal human intervention. A concept demonstrator of the Structural Health Monitoring (SHM) system was developed to autonomously detect the degradation of the mechanical integrity of the standoff C-C TPS panels. This system assesses the torque levels of the loosened bolts in the C-C TPS panel, as well as identifies the location of those bolts accordingly. During the course of building the proposed SHM prototype, efforts have been focused primarily on developing a trustworthy diagnostic scheme and a responsive sensor suite. Based on the microcontact conditions and damping phenomena of ultrasonic waves across the bolted joints, an Attenuation-based Diagnostic Method was proposed to assess the fastener integrity by observing the attenuation patterns of the resultant sensor signals. Parametric model studies and prototype testing validated the theoretical explanation of the attenuation-based method. Once the diagnostic scheme was determined, the implementation of a sensor suite was the next step. A new PZT-embedded sensor washer was developed to enhance remote sensing capability and achieve sufficient sensitivity by guiding diagnostic waves primarily through the inspection areas. The sensor-embedded washers replace the existing washers to constitute the sensor network, as well as to avoid jeopardizing the integrity of the original fastener components. After sensor design evolution and appropriate algorithm development, verification tests were conducted using a shaker and a full-scale oven, which simulated the acoustic and thermal environments during the re-entry process, respectively. The test results revealed that the proposed system successfully identifies the loss of the preload for the bolted joints that were loosened. The sensors were also found to be durable under the cyclic mechanical and thermal loads without major failures.

Flight-Tested Prototype of BEAM Software

NASA Technical Reports Server (NTRS)

Mackey, Ryan; Tikidjian, Raffi; James, Mark; Wang, David

2006-01-01

Researchers at JPL have completed a software prototype of BEAM (Beacon-based Exception Analysis for Multi-missions) and successfully tested its operation in flight onboard a NASA research aircraft. BEAM (see NASA Tech Briefs, Vol. 26, No. 9; and Vol. 27, No. 3) is an ISHM (Integrated Systems Health Management) technology that automatically analyzes sensor data and classifies system behavior as either nominal or anomalous, and further characterizes anomalies according to strength, duration, and affected signals. BEAM (see figure) can be used to monitor a wide variety of physical systems and sensor types in real time. In this series of tests, BEAM monitored the engines of a Dryden Flight Research Center F-18 aircraft, and performed onboard, unattended analysis of 26 engine sensors from engine startup to shutdown. The BEAM algorithm can detect anomalies based solely on the sensor data, which includes but is not limited to sensor failure, performance degradation, incorrect operation such as unplanned engine shutdown or flameout in this example, and major system faults. BEAM was tested on an F-18 simulator, static engine tests, and 25 individual flights totaling approximately 60 hours of flight time. During these tests, BEAM successfully identified planned anomalies (in-flight shutdowns of one engine) as well as minor unplanned anomalies (e.g., transient oil- and fuel-pressure drops), with no false alarms or suspected false-negative results for the period tested. BEAM also detected previously unknown behavior in the F- 18 compressor section during several flights. This result, confirmed by direct analysis of the raw data, serves as a significant test of BEAM's capability.

Control of Flexible Systems in the Presence of Failures

NASA Technical Reports Server (NTRS)

Magahami, Peiman G.; Cox, David E.; Bauer, Frank H. (Technical Monitor)

2001-01-01

Control of flexible systems under degradation or failure of sensors/actuators is considered. A Linear Matrix Inequality framework is used to synthesize H(sub infinity)-based controllers, which provide good disturbance rejection while capable of tolerating real parameter uncertainties in the system model, as well as potential degradation or failure of the control system hardware. In this approach, a one-at-a-time failure scenario is considered, wherein no more than one sensor or actuator is allowed to fail at any given time. A numerical example involving control synthesis for a two-dimensional flexible system is presented to demonstrate the feasibility of the proposed approach.

Structural health monitoring of IACC yachts using fiber optic distributed strain sensors: a technical challenge for America's Cup 2000

NASA Astrophysics Data System (ADS)

Murayama, Hideaki; Kageyama, Kazuro; Kimpara, Isao; Akiyoshi, Shimada; Naruse, Hiroshi

2000-06-01

In this study, we developed a health monitoring system using a fiber optic distributed strain sensor for International America's Cup Class (IACC) yachts. Most structural components of an IACC yacht consist of an aluminum honeycomb core sandwiched between carbon fiber reinforced plastic (CFRP) laminates. In such structures, delamination, skin/core debonding and debonding between adhered members will be result in serious fracture of the structure. We equipped two IACC yachts with fiber optic strain sensors designed to measured the distributed strain using a Brillouin optical time domain reflectometer (BOTDR) and to detect any deterioration or damage to the yacht's structures caused by such failures. And based on laboratory test results, we proposed a structural health monitoring technique for IACC yachts that involves analyzing their strain distribution. Some important information about structural conditions of the IACC yachts could be obtained from this system through the periodical strain measurements in the field.

Effect of Sensors on the Reliability and Control Performance of Power Circuits in the Web of Things (WoT)

PubMed Central

Bae, Sungwoo; Kim, Myungchin

2016-01-01

In order to realize a true WoT environment, a reliable power circuit is required to ensure interconnections among a range of WoT devices. This paper presents research on sensors and their effects on the reliability and response characteristics of power circuits in WoT devices. The presented research can be used in various power circuit applications, such as energy harvesting interfaces, photovoltaic systems, and battery management systems for the WoT devices. As power circuits rely on the feedback from voltage/current sensors, the system performance is likely to be affected by the sensor failure rates, sensor dynamic characteristics, and their interface circuits. This study investigated how the operational availability of the power circuits is affected by the sensor failure rates by performing a quantitative reliability analysis. In the analysis process, this paper also includes the effects of various reconstruction and estimation techniques used in power processing circuits (e.g., energy harvesting circuits and photovoltaic systems). This paper also reports how the transient control performance of power circuits is affected by sensor interface circuits. With the frequency domain stability analysis and circuit simulation, it was verified that the interface circuit dynamics may affect the transient response characteristics of power circuits. The verification results in this paper showed that the reliability and control performance of the power circuits can be affected by the sensor types, fault tolerant approaches against sensor failures, and the response characteristics of the sensor interfaces. The analysis results were also verified by experiments using a power circuit prototype. PMID:27608020

Fuzzy Risk Evaluation in Failure Mode and Effects Analysis Using a D Numbers Based Multi-Sensor Information Fusion Method.

PubMed

Deng, Xinyang; Jiang, Wen

2017-09-12

Failure mode and effect analysis (FMEA) is a useful tool to define, identify, and eliminate potential failures or errors so as to improve the reliability of systems, designs, and products. Risk evaluation is an important issue in FMEA to determine the risk priorities of failure modes. There are some shortcomings in the traditional risk priority number (RPN) approach for risk evaluation in FMEA, and fuzzy risk evaluation has become an important research direction that attracts increasing attention. In this paper, the fuzzy risk evaluation in FMEA is studied from a perspective of multi-sensor information fusion. By considering the non-exclusiveness between the evaluations of fuzzy linguistic variables to failure modes, a novel model called D numbers is used to model the non-exclusive fuzzy evaluations. A D numbers based multi-sensor information fusion method is proposed to establish a new model for fuzzy risk evaluation in FMEA. An illustrative example is provided and examined using the proposed model and other existing method to show the effectiveness of the proposed model.

Fuzzy Risk Evaluation in Failure Mode and Effects Analysis Using a D Numbers Based Multi-Sensor Information Fusion Method

PubMed Central

Deng, Xinyang

2017-01-01

Failure mode and effect analysis (FMEA) is a useful tool to define, identify, and eliminate potential failures or errors so as to improve the reliability of systems, designs, and products. Risk evaluation is an important issue in FMEA to determine the risk priorities of failure modes. There are some shortcomings in the traditional risk priority number (RPN) approach for risk evaluation in FMEA, and fuzzy risk evaluation has become an important research direction that attracts increasing attention. In this paper, the fuzzy risk evaluation in FMEA is studied from a perspective of multi-sensor information fusion. By considering the non-exclusiveness between the evaluations of fuzzy linguistic variables to failure modes, a novel model called D numbers is used to model the non-exclusive fuzzy evaluations. A D numbers based multi-sensor information fusion method is proposed to establish a new model for fuzzy risk evaluation in FMEA. An illustrative example is provided and examined using the proposed model and other existing method to show the effectiveness of the proposed model. PMID:28895905

Reliability Assessment for Low-cost Unmanned Aerial Vehicles

NASA Astrophysics Data System (ADS)

Freeman, Paul Michael

Existing low-cost unmanned aerospace systems are unreliable, and engineers must blend reliability analysis with fault-tolerant control in novel ways. This dissertation introduces the University of Minnesota unmanned aerial vehicle flight research platform, a comprehensive simulation and flight test facility for reliability and fault-tolerance research. An industry-standard reliability assessment technique, the failure modes and effects analysis, is performed for an unmanned aircraft. Particular attention is afforded to the control surface and servo-actuation subsystem. Maintaining effector health is essential for safe flight; failures may lead to loss of control incidents. Failure likelihood, severity, and risk are qualitatively assessed for several effector failure modes. Design changes are recommended to improve aircraft reliability based on this analysis. Most notably, the control surfaces are split, providing independent actuation and dual-redundancy. The simulation models for control surface aerodynamic effects are updated to reflect the split surfaces using a first-principles geometric analysis. The failure modes and effects analysis is extended by using a high-fidelity nonlinear aircraft simulation. A trim state discovery is performed to identify the achievable steady, wings-level flight envelope of the healthy and damaged vehicle. Tolerance of elevator actuator failures is studied using familiar tools from linear systems analysis. This analysis reveals significant inherent performance limitations for candidate adaptive/reconfigurable control algorithms used for the vehicle. Moreover, it demonstrates how these tools can be applied in a design feedback loop to make safety-critical unmanned systems more reliable. Control surface impairments that do occur must be quickly and accurately detected. This dissertation also considers fault detection and identification for an unmanned aerial vehicle using model-based and model-free approaches and applies those algorithms to experimental faulted and unfaulted flight test data. Flight tests are conducted with actuator faults that affect the plant input and sensor faults that affect the vehicle state measurements. A model-based detection strategy is designed and uses robust linear filtering methods to reject exogenous disturbances, e.g. wind, while providing robustness to model variation. A data-driven algorithm is developed to operate exclusively on raw flight test data without physical model knowledge. The fault detection and identification performance of these complementary but different methods is compared. Together, enhanced reliability assessment and multi-pronged fault detection and identification techniques can help to bring about the next generation of reliable low-cost unmanned aircraft.

Comparison of Pilots' Situational Awareness While Monitoring Autoland Approaches Using Conventional and Advanced Flight Display Formats

NASA Technical Reports Server (NTRS)

Kramer, Lynda J.; Busquets, Anthony M.

2000-01-01

A simulation experiment was performed to assess situation awareness (SA) and workload of pilots while monitoring simulated autoland operations in Instrument Meteorological Conditions with three advanced display concepts: two enhanced electronic flight information system (EFIS)-type display concepts and one totally synthetic, integrated pictorial display concept. Each concept incorporated sensor-derived wireframe runway and iconic depictions of sensor-detected traffic in different locations on the display media. Various scenarios, involving conflicting traffic situation assessments, main display failures, and navigation/autopilot system errors, were used to assess the pilots' SA and workload during autoland approaches with the display concepts. From the results, for each scenario, the integrated pictorial display concept provided the pilots with statistically equivalent or substantially improved SA over the other display concepts. In addition to increased SA, subjective rankings indicated that the pictorial concept offered reductions in overall pilot workload (in both mean ranking and spread) over the two enhanced EFIS-type display concepts. Out of the display concepts flown, the pilots ranked the pictorial concept as the display that was easiest to use to maintain situational awareness, to monitor an autoland approach, to interpret information from the runway and obstacle detecting sensor systems, and to make the decision to go around.

AVIRIS performance during the 1987 flight season: An AVIRIS project assessment and summary of the NASA-sponsored performance evaluation

NASA Technical Reports Server (NTRS)

Vane, Gregg; Porter, Wallace M.; Reimer, John H.; Chrien, Thomas G.; Green, Robert O.

1988-01-01

Results are presented of the assessment of AVIRIS performance during the 1987 flight season by the AVIRIS project and the earth scientists who were chartered by NASA to conduct an independent data quality and sensor performance evaluation. The AVIRIS evaluation program began in late June 1987 with the sensor meeting most of its design requirements except for signal-to-noise ratio in the fourth spectrometer, which was about half of the required level. Several events related to parts failures and design flaws further reduced sensor performance over the flight season. Substantial agreement was found between the assessments by the project and the independent investigators of the effects of these various factors. A summary of the engineering work that is being done to raise AVIRIS performance to its required level is given. In spite of degrading data quality over the flight season, several exciting scientific results were obtained from the data. These include the mapping of the spatial variation of atmospheric precipitable water, detection of environmentally-induced shifts in the spectral red edge of stressed vegetation, detection of spectral features related to pigment, leaf water and ligno-cellulose absorptions in plants, and the identification of many diagnostic mineral absorption features in a variety of geological settings.

Continuous leg dyskinesia assessment in Parkinson's disease -clinical validity and ecological effect.

PubMed

Ramsperger, Robert; Meckler, Stefan; Heger, Tanja; van Uem, Janet; Hucker, Svenja; Braatz, Ulrike; Graessner, Holm; Berg, Daniela; Manoli, Yiannos; Serrano, J Artur; Ferreira, Joaquim J; Hobert, Markus A; Maetzler, Walter

2016-05-01

Dyskinesias in Parkinson's disease (PD) patients are a common side effect of long-term dopaminergic therapy and are associated with motor dysfunctions, including gait and balance deficits. Although promising compounds have been developed to treat these symptoms, clinical trials have failed. This failure may, at least partly, be explained by the lack of objective and continuous assessment strategies. This study tested the clinical validity and ecological effect of an algorithm that detects and quantifies dyskinesias of the legs using a single ankle-worn sensor. Twenty-three PD patients (seven with leg dyskinesias) and 13 control subjects were investigated in the lab. Participants performed purposeful daily activity-like tasks while being video-taped. Clinical evaluation was performed using the leg dyskinesia item of the Unified Dyskinesia Rating Scale. The ecological effect of the developed algorithm was investigated in a multi-center, 12-week, home-based sub-study that included three patients with and seven without dyskinesias. In the lab-based sub-study, the sensor-based algorithm exhibited a specificity of 98%, a sensitivity of 85%, and an accuracy of 0.96 for the detection of dyskinesias and a correlation level of 0.61 (p < 0.001) with the clinical severity score. In the home-based sub-study, all patients could be correctly classified regarding the presence or absence of leg dyskinesias, supporting the ecological relevance of the algorithm. This study provides evidence of clinical validity and ecological effect of an algorithm derived from a single sensor on the ankle for detecting leg dyskinesias in PD patients. These results should motivate the investigation of leg dyskinesias in larger studies using wearable sensors. Copyright © 2016 Elsevier Ltd. All rights reserved.

Engine Icing Modeling and Simulation (Part 2): Performance Simulation of Engine Rollback Phenomena

NASA Technical Reports Server (NTRS)

May, Ryan D.; Guo, Ten-Huei; Veres, Joseph P.; Jorgenson, Philip C. E.

2011-01-01

Ice buildup in the compressor section of a commercial aircraft gas turbine engine can cause a number of engine failures. One of these failure modes is known as engine rollback: an uncommanded decrease in thrust accompanied by a decrease in fan speed and an increase in turbine temperature. This paper describes the development of a model which simulates the system level impact of engine icing using the Commercial Modular Aero-Propulsion System Simulation 40k (C-MAPSS40k). When an ice blockage is added to C-MAPSS40k, the control system responds in a manner similar to that of an actual engine, and, in cases with severe blockage, an engine rollback is observed. Using this capability to simulate engine rollback, a proof-of-concept detection scheme is developed and tested using only typical engine sensors. This paper concludes that the engine control system s limit protection is the proximate cause of iced engine rollback and that the controller can detect the buildup of ice particles in the compressor section. This work serves as a feasibility study for continued research into the detection and mitigation of engine rollback using the propulsion control system.

Smart Sensors Gather Information for Machine Diagnostics

NASA Technical Reports Server (NTRS)

2014-01-01

Stennis Space Center was interested in using smart sensors to monitor components on test stands and avert equipment failures. Partnering with St. Paul, Minnesota-based Lion Precision through a Cooperative Agreement, the team developed a smart sensor and the associated communication protocols. The same sensor is now commercially available for manufacturing.

Evaluation of an oil-debris monitoring device for use in helicopter transmissions

NASA Technical Reports Server (NTRS)

Lewicki, David G.; Blanchette, Donald M.; Biron, Gilles

1992-01-01

Experimental tests were performed on an OH-58A helicopter main-rotor transmission to evaluate an oil-debris monitoring device (ODMD). The tests were performed in the NASA 500-hp Helicopter Transmission Test Stand. Five endurance tests were run as part of a U.S. Navy/NASA/Army advanced lubricants program. The tests were run at 100 percent design speed, 117-percent design torque, and 121 C (250 F) oil inlet temperature. Each test lasted between 29 and 122 hr. The oils that were used conformed to MIL-L-23699 and DOD-L-85734 specifications. One test produced a massive sun-gear fatigue failure; another test produced a small spall on one sun-gear tooth; and a third test produced a catastrophic planet-bearing cage failure. The ODMD results were compared with oil spectroscopy results. The capability of the ODMD to detect transmission component failures was not demonstrated. Two of the five tests produced large amounts of debris. For these two tests, two separate ODMD sensors failed, possibly because of prolonged exposure to relatively high oil temperatures. One test produced a small amount of debris and was not detected by the ODMD or by oil spectroscopy. In general, the ODMD results matched the oil spectroscopy results. The ODMD results were extremely sensitive to oil temperature and flow rate.

Humidity sensor failure: a problem that should not be neglected

NASA Astrophysics Data System (ADS)

Liu, Y.; Tang, N.

2014-11-01

The problem of abnormally dry bias induced by radiosonde humidity sensor failure in the low and mid-troposphere is studied based on the global operational radiosonde relative humidity observations from December 2008 to November 2009. The concurrent humidity retrievals from the FORMOSAT-3/COSMIC radio occultation mission are also used to assess the quality of the radiosonde humidity observations. It is found that extremely dry relative humidity are common in the low and mid-troposphere, with an annual globally averaged occurrence of 4.2%. These low-humidity observations usually exist between 20 and 40° latitude in both the Northern Hemisphere and Southern Hemisphere, and from heights of 700 to 450 hPa. Winter and spring are the favored seasons for their occurrence, with a maximum fraction of 9.53 % in the Northern Hemisphere and 16.82% in the Southern Hemisphere. The phenomenon does not result from natural atmospheric variability, but rather humidity sensor failure. If the performance of humidity sensors is not good, low-humidity observations occur easily, particularly when the radiosonde ascends through stratiform clouds with high moisture content. The humidity sensor cannot adapt to the huge change of the atmospheric environment inside and outside stratiform clouds, resulting in sensor failure and no response to atmospheric change. These extremely dry relative humidity observations are erroneous. However, they have been archived as formal data and applied in many research studies. This may seriously undermine the reliability of numerical weather prediction and the analysis of weather and climate if quality control is not applied before using these data.

A probabilistic method to diagnose faults of air handling units

NASA Astrophysics Data System (ADS)

Dey, Debashis

Air handling unit (AHU) is one of the most extensively used equipment in large commercial buildings. This device is typically customized and lacks quality system integration which can result in hardwire failures and controller errors. Air handling unit Performance Assessment Rules (APAR) is a fault detection tool that uses a set of expert rules derived from mass and energy balances to detect faults in air handling units. APAR is computationally simple enough that it can be embedded in commercial building automation and control systems and relies only upon sensor data and control signals that are commonly available in these systems. Although APAR has many advantages over other methods, for example no training data required and easy to implement commercially, most of the time it is unable to provide the diagnosis of the faults. For instance, a fault on temperature sensor could be fixed bias, drifting bias, inappropriate location, complete failure. Also a fault in mixing box can be return and outdoor damper leak or stuck. In addition, when multiple rules are satisfied the list of faults increases. There is no proper way to have the correct diagnosis for rule based fault detection system. To overcome this limitation we proposed Bayesian Belief Network (BBN) as a diagnostic tool. BBN can be used to simulate diagnostic thinking of FDD experts through a probabilistic way. In this study we developed a new way to detect and diagnose faults in AHU through combining APAR rules and Bayesian Belief network. Bayesian Belief Network is used as a decision support tool for rule based expert system. BBN is highly capable to prioritize faults when multiple rules are satisfied simultaneously. Also it can get information from previous AHU operating conditions and maintenance records to provide proper diagnosis. The proposed model is validated with real time measured data of a campus building at University of Texas at San Antonio (UTSA).The results show that BBN is correctly able to prioritize faults which can be verified by manual investigation.

Ultrafast table-top dynamic radiography of spontaneous or stimulated events

DOEpatents

Smilowitz, Laura; Henson, Bryan

2018-01-16

Disclosed herein are representative embodiments of methods, apparatus, and systems for performing radiography. For example, certain embodiments concern X-ray radiography of spontaneous events. Particular embodiments of the disclosed technology provide continuous high-speed x-ray imaging of spontaneous dynamic events, such as explosions, reaction-front propagation, and even material failure. Further, in certain embodiments, x-ray activation and data collection activation are triggered by the object itself that is under observation (e.g., triggered by a change of state detected by one or more sensors monitoring the object itself).

Prediction of Composite Pressure Vessel Failure Location using Fiber Bragg Grating Sensors

NASA Technical Reports Server (NTRS)

Kreger, Steven T.; Taylor, F. Tad; Ortyl, Nicholas E.; Grant, Joseph

2006-01-01

Ten composite pressure vessels were instrumented with fiber Bragg grating sensors in order to assess the strain levels of the vessel under various loading conditions. This paper and presentation will discuss the testing methodology, the test results, compare the testing results to the analytical model, and present a possible methodology for predicting the failure location and strain level of composite pressure vessels.

Real-time method for establishing a detection map for a network of sensors

DOEpatents

Nguyen, Hung D; Koch, Mark W; Giron, Casey; Rondeau, Daniel M; Russell, John L

2012-09-11

A method for establishing a detection map of a dynamically configurable sensor network. This method determines an appropriate set of locations for a plurality of sensor units of a sensor network and establishes a detection map for the network of sensors while the network is being set up; the detection map includes the effects of the local terrain and individual sensor performance. Sensor performance is characterized during the placement of the sensor units, which enables dynamic adjustment or reconfiguration of the placement of individual elements of the sensor network during network set-up to accommodate variations in local terrain and individual sensor performance. The reconfiguration of the network during initial set-up to accommodate deviations from idealized individual sensor detection zones improves the effectiveness of the sensor network in detecting activities at a detection perimeter and can provide the desired sensor coverage of an area while minimizing unintentional gaps in coverage.

Direct Left Atrial Pressure Monitoring in Severe Heart Failure: Long-Term Sensor Performance

PubMed Central

Ritzema, Jay; Eigler, Neal L.; Melton, Iain C.; Krum, Henry; Adamson, Philip B.; Kar, Saibal; Shah, Prediman K.; Whiting, James S.; Heywood, J. Thomas; Rosero, Spencer; Singh, Jagmeet P.; Saxon, Leslie; Matthews, Ray; Crozier, Ian G.; Abraham, William T.

2010-01-01

We report the stability, accuracy, and development history of a new left atrial pressure (LAP) sensing system in ambulatory heart failure (HF) patients. A total of 84 patients with advanced HF underwent percutaneous transseptal implantation of the pressure sensor. Quarterly noninvasive calibration by modified Valsalva maneuver was achieved in all patients, and 96.5% of calibration sessions were successful with a reproducibility of 1.2 mmHg. Absolute sensor drift was maximal after 3 months at 4.7 mmHg (95% CI, 3.2–6.2 mmHg) and remained stable through 48 months. LAP was highly correlated with simultaneous pulmonary wedge pressure at 3 and 12 months (r = 0.98, average difference of 0.8 ± 4.0 mmHg). Freedom from device failure was 95% (n = 37) at 2 years and 88% (n = 12) at 4 years. Causes of failure were identified and mitigated with 100% freedom from device failure and less severe anomalies in the last 41 consecutive patients (p = 0.005). Accurate and reliable LAP measurement using a chronic implanted monitoring system is safe and feasible in patients with advanced heart failure. PMID:20945124

Ultrasonic stress wave characterization of composite materials

NASA Technical Reports Server (NTRS)

Duke, J. C., Jr.; Henneke, E. G., II; Stinchcomb, W. W.

1986-01-01

The work reported covers three simultaneous projects. The first project was concerned with: (1) establishing the sensitivity of the acousto-ultrasonic method for evaluating subtle forms of damage development in cyclically loaded composite materials, (2) establishing the ability of the acousto-ultrasonic method for detecting initial material imperfections that lead to localized damage growth and final specimen failure, and (3) characteristics of the NBS/Proctor sensor/receiver for acousto-ultrasonic evaluation of laminated composite materials. The second project was concerned with examining the nature of the wave propagation that occurs during acoustic-ultrasonic evaluation of composite laminates and demonstrating the role of Lamb or plate wave modes and their utilization for characterizing composite laminates. The third project was concerned with the replacement of contact-type receiving piezotransducers with noncontacting laser-optical sensors for acousto-ultrasonic signal acquisition.

Acoustic emission and acousto-ultrasonic signature analysis of failure mechanisms in carbon fiber reinforced polymer materials

NASA Astrophysics Data System (ADS)

Carey, Shawn Allen

Fiber reinforced polymer composite materials, particularly carbon (CFRPs), are being used for primary structural applications, particularly in the aerospace and naval industries. Advantages of CFRP materials, compared to traditional materials such as steel and aluminum, include: light weight, high strength to weight ratio, corrosion resistance, and long life expectancy. A concern with CFRPs is that despite quality control during fabrication, the material can contain many hidden internal flaws. These flaws in combination with unseen damage due to fatigue and low velocity impact have led to catastrophic failure of structures and components. Therefore a large amount of research has been conducted regarding nondestructive testing (NDT) and structural health monitoring (SHM) of CFRP materials. The principal objective of this research program was to develop methods to characterize failure mechanisms in CFRP materials used by the U.S. Army using acoustic emission (AE) and/or acousto-ultrasonic (AU) data. Failure mechanisms addressed include fiber breakage, matrix cracking, and delamination due to shear between layers. CFRP specimens were fabricated and tested in uniaxial tension to obtain AE and AU data. The specimens were designed with carbon fibers in different orientations to produce the different failure mechanisms. Some specimens were impacted with a blunt indenter prior to testing to simulate low-velocity impact. A signature analysis program was developed to characterize the AE data based on data examination using visual pattern recognition techniques. It was determined that it was important to characterize the AE event , using the location of the event as a parameter, rather than just the AE hit (signal recorded by an AE sensor). A back propagation neural network was also trained based on the results of the signature analysis program. Damage observed on the specimens visually with the aid of a scanning electron microscope agreed with the damage type assigned by the signature analysis program. The load level at which significant damage occurred in the specimens was evaluated using ASME Boiler and Pressure Vessel criteria. AU testing proved inconclusive for characterization of the damage due to common problems associated with AU testing such as: reproducibility difficulties due to degradation of the attachment of the sensors, damage not detected unless in the line of sight between sensors, and large intrinsic variation of the data.

Design of analytical failure detection using secondary observers

NASA Technical Reports Server (NTRS)

Sisar, M.

1982-01-01

The problem of designing analytical failure-detection systems (FDS) for sensors and actuators, using observers, is addressed. The use of observers in FDS is related to the examination of the n-dimensional observer error vector which carries the necessary information on possible failures. The problem is that in practical systems, in which only some of the components of the state vector are measured, one has access only to the m-dimensional observer-output error vector, with m or = to n. In order to cope with these cases, a secondary observer is synthesized to reconstruct the entire observer-error vector from the observer output error vector. This approach leads toward the design of highly sensitive and reliable FDS, with the possibility of obtaining a unique fingerprint for every possible failure. In order to keep the observer's (or Kalman filter) false-alarm rate under a certain specified value, it is necessary to have an acceptable matching between the observer (or Kalman filter) models and the system parameters. A previously developed adaptive observer algorithm is used to maintain the desired system-observer model matching, despite initial mismatching or system parameter variations. Conditions for convergence for the adaptive process are obtained, leading to a simple adaptive law (algorithm) with the possibility of an a priori choice of fixed adaptive gains. Simulation results show good tracking performance with small observer output errors, while accurate and fast parameter identification, in both deterministic and stochastic cases, is obtained.

Thermally activated TRP channels: molecular sensors for temperature detection.

PubMed

Castillo, Karen; Diaz-Franulic, Ignacio; Canan, Jonathan; Gonzalez-Nilo, Fernando; Latorre, Ramon

2018-01-24

Temperature sensing is one of the oldest capabilities of living organisms, and is essential for sustaining life, because failure to avoid extreme noxious temperatures can result in tissue damage or death. A subset of members of the transient receptor potential (TRP) ion channel family is finely tuned to detect temperatures ranging from extreme cold to noxious heat, giving rise to thermoTRP channels. Structural and functional experiments have shown that thermoTRP channels are allosteric proteins, containing different domains that sense changes in temperature, among other stimuli, triggering pore opening. Although temperature-dependence is well characterized in thermoTRP channels, the molecular nature of temperature-sensing elements remains unknown. Importantly, thermoTRP channels are involved in pain sensation, related to pathological conditions. Here, we provide an overview of thermoTRP channel activation. We also discuss the structural and functional evidence supporting the existence of an intrinsic temperature sensor in this class of channels, and we explore the basic thermodynamic principles for channel activation. Finally, we give a view of their role in painful pathophysiological conditions.

Integrated fiber optic structural health sensors for inflatable space habitats

NASA Astrophysics Data System (ADS)

Ohanian, Osgar John; Garg, Naman; Castellucci, Matthew A.

2017-04-01

Inflatable space habitats offer many advantages for future space missions; however, the long term integrity of these flexible structures is a major concern in harsh space environments. Structural Health Monitoring (SHM) of these structures is essential to ensure safe operation, provide early warnings of damage, and measure structural changes over long periods of time. To address this problem, the authors have integrated distributed fiber optic strain sensors to measure loading and to identify the occurrence and location of damage in the straps and webbing used in the structural restraint layer. The fiber optic sensors employed use Rayleigh backscatter combined with optical frequency domain reflectometry to enable measurement of strain every 0.65 mm (0.026 inches) along the sensor. The Kevlar woven straps that were tested exhibited large permanent deformation during initial cycling and continued to exhibit hysteresis thereafter, but there was a consistent linear relationship between the sensor's measurement and the actual strain applied. Damage was intentionally applied to a tensioned strap, and the distributed strain measurement clearly identified a change in the strain profile centered on the location of the damage. This change in structural health was identified at a loading that was less than half of the ultimate loading that caused a structural failure. This sensing technique will be used to enable integrated SHM sensors to detect loading and damage in future inflatable space habitat structures.

Forewarning of Debris flows using Intelligent Geophones

NASA Astrophysics Data System (ADS)

PK, I.; Ramesh, M. V.

2017-12-01

Landslides are one of the major catastrophic disasters that cause significant damage to human life and civil structures. Heavy rainfall on landslide prone areas can lead to most dangerous debris flow, where the materials such as mud, sand, soil, rock, water and air will move with greater velocity down the mountain. This sudden slope instability can lead to loss of human life and infrastructure. According to our knowledge, till now no one could identify the minutest factors that lead to initiation of the landslide. In this work, we aim to study the landslide phenomena deeply, using the landslide laboratory set up in our university. This unique mechanical simulator for landslide initiation is equipped with the capability to generate rainfall, seepage, etc., in the laboratory setup. Using this setup, we aim to study several landslide initiation scenarios generated by varying different parameters. The complete setup will be equipped with heterogeneous sensors such as rain gauge, moisture sensor, pore pressure sensor, strain gauges, tiltmeter, inclinometer, extensometer, and geophones. Our work will focus on the signals received from the intelligent geophone system for identifying the underground vibrations during a debris flow. Using the large amount of signals derived from the laboratory set up, we have performed detailed signal processing and data analysis to determine the fore warning signals captured by these heterogeneous sensors. Detailed study of these heterogeneous signals has provided the insights to forewarning the community based on the signals generated during the laboratory tests. In this work we will describe the details of the design, development, methodology, results, inferences and the suggestion for the next step to detect and forewarn the students. The response of intelligent geophone sensors at the time of failure, failure style and subsequent debris flow for heterogeneous soil layers were studied, thus helping in the development of fore warning systems for debris flows.

Disease management: remote monitoring in heart failure patients with implantable defibrillators, resynchronization devices, and haemodynamic monitors.

PubMed

Abraham, William T

2013-06-01

Heart failure represents a major public health concern, associated with high rates of morbidity and mortality. A particular focus of contemporary heart failure management is reduction of hospital admission and readmission rates. While optimal medical therapy favourably impacts the natural history of the disease, devices such as cardiac resynchronization therapy devices and implantable cardioverter defibrillators have added incremental value in improving heart failure outcomes. These devices also enable remote patient monitoring via device-based diagnostics. Device-based measurement of physiological parameters, such as intrathoracic impedance and heart rate variability, provide a means to assess risk of worsening heart failure and the possibility of future hospitalization. Beyond this capability, implantable haemodynamic monitors have the potential to direct day-to-day management of heart failure patients to significantly reduce hospitalization rates. The use of a pulmonary artery pressure measurement system has been shown to significantly reduce the risk of heart failure hospitalization in a large randomized controlled study, the CardioMEMS Heart Sensor Allows Monitoring of Pressure to Improve Outcomes in NYHA Class III Heart Failure Patients (CHAMPION) trial. Observations from a pilot study also support the potential use of a left atrial pressure monitoring system and physician-directed patient self-management paradigm; these observations are under further investigation in the ongoing LAPTOP-HF trial. All these devices depend upon high-intensity remote monitoring for successful detection of parameter deviations and for directing and following therapy.

2008 Year in Review

NASA Technical Reports Server (NTRS)

Figueroa, Jorge Fernando

2008-01-01

In February of 2008; NASA Stennis Space Center (SSC), NASA Kennedy Space Center (KSC), and The Applied Research Laboratory at Penn State University demonstrated a pilot implementation of an Integrated System Health Management (ISHM) capability at the Launch Complex 20 of KSC. The following significant accomplishments are associated with this development: (1) implementation of an architecture for ground operations ISHM, based on networked intelligent elements; (2) Use of standards for management of data, information, and knowledge (DIaK) leading to modular ISHM implementation with interoperable elements communicating according to standards (three standards were used: IEEE 1451 family of standards for smart sensors and actuators, Open Systems Architecture for Condition Based Maintenance (OSA-CBM) standard for communicating DIaK describing the condition of elements of a system, and the OPC standard for communicating data); (3) ISHM implementation using interoperable modules addressing health management of subsystems; and (4) use of a physical intelligent sensor node (smart network element or SNE capable of providing data and health) along with classic sensors originally installed in the facility. An operational demonstration included detection of anomalies (sensor failures, leaks, etc.), determination of causes and effects, communication among health nodes, and user interfaces.

Shear sensing in bonded composites with cantilever beam microsensors and dual-plane digital image correlation

NASA Astrophysics Data System (ADS)

Baur, Jeffery W.; Slinker, Keith; Kondash, Corey

2017-04-01

Understanding the shear strain, viscoelastic response, and onset of damage within bonded composites is critical to their design, processing, and reliability. This presentation will discuss the multidisciplinary research conducted which led to the conception, development, and demonstration of two methods for measuring the shear within a bonded joint - dualplane digital image correlation (DIC) and a micro-cantilever shear sensor. The dual plane DIC method was developed to measure the strain field on opposing sides of a transparent single-lap joint in order to spatially quantify the joint shear strain. The sensor consists of a single glass fiber cantilever beam with a radially-grown forest of carbon nanotubes (CNTs) within a capillary pore. When the fiber is deflected, the internal radial CNT array is compressed against an electrode within the pore and the corresponding decrease in electrical resistance is correlated with the external loading. When this small, simple, and low-cost sensor was integrated within a composite bonded joint and cycled in tension, the onset of damage prior to joint failure was observed. In a second sample configuration, both the dual plane DIC and the hair sensor detected viscoplastic changes in the strain of the sample in response to continued loading.

Embedded Strain Gauges for Condition Monitoring of Silicone Gaskets

PubMed Central

Schotzko, Timo; Lang, Walter

2014-01-01

A miniaturized strain gauge with a thickness of 5 µm is molded into a silicone O-ring. This is a first step toward embedding sensors in gaskets for structural health monitoring. The signal of the integrated sensor exhibits a linear correlation with the contact pressure of the O-ring. This affords the opportunity to monitor the gasket condition during installation. Thus, damages caused by faulty assembly can be detected instantly, and early failures, with their associated consequences, can be prevented. Through the embedded strain gauge, the contact pressure applied to the gasket can be directly measured. Excessive pressure and incorrect positioning of the gasket can cause structural damage to the material of the gasket, which can lead to an early outage. A platinum strain gauge is fabricated on a thin polyimide layer and is contacted through gold connections. The measured resistance pressure response exhibits hysteresis for the first few strain cycles, followed by a linear behavior. The short-term impact of the embedded sensor on the stability of the gasket is investigated. Pull-tests with O-rings and test specimens have indicated that the integration of the miniaturized sensors has no negative impact on the stability in the short term. PMID:25014099

Cacades: A reliable dissemination protocol for data collection sensor network

USGS Publications Warehouse

Peng, Y.; Song, W.; Huang, R.; Xu, M.; Shirazi, B.; LaHusen, R.; Pei, G.

2009-01-01

In this paper, we propose a fast and reliable data dissemination protocol Cascades to disseminate data from the sink(base station) to all or a subset of nodes in a data collection sensor network. Cascades makes use of the parentmonitor-children analogy to ensure reliable dissemination. Each node monitors whether or not its children have received the broadcast messages through snooping children's rebroadcasts or waiting for explicit ACKs. If a node detects a gap in its message sequences, it can fetch the missing messages from its neighbours reactively. Cascades also considers many practical issues for field deployment, such as dynamic topology, link/node failure, etc.. It therefore guarantees that a disseminated message from the sink will reach all intended receivers and the dissemination is terminated in a short time period. Notice that, all existing dissemination protocols either do not guarantee reliability or do not terminate [1, 2], which does not meet the requirement of real-time command control. We conducted experiment evaluations in both TOSSIM simulator and a sensor network testbed to compare Cascades with those existing dissemination protocols in TinyOS sensor networks, which show that Cascades achieves a higher degree of reliability, lower communication cost, and less delivery delay. ??2009 IEEE.

Defect Detection and Segmentation Framework for Remote Field Eddy Current Sensor Data

PubMed Central

2017-01-01

Remote-Field Eddy-Current (RFEC) technology is often used as a Non-Destructive Evaluation (NDE) method to prevent water pipe failures. By analyzing the RFEC data, it is possible to quantify the corrosion present in pipes. Quantifying the corrosion involves detecting defects and extracting their depth and shape. For large sections of pipelines, this can be extremely time-consuming if performed manually. Automated approaches are therefore well motivated. In this article, we propose an automated framework to locate and segment defects in individual pipe segments, starting from raw RFEC measurements taken over large pipelines. The framework relies on a novel feature to robustly detect these defects and a segmentation algorithm applied to the deconvolved RFEC signal. The framework is evaluated using both simulated and real datasets, demonstrating its ability to efficiently segment the shape of corrosion defects. PMID:28984823

Defect Detection and Segmentation Framework for Remote Field Eddy Current Sensor Data.

PubMed

Falque, Raphael; Vidal-Calleja, Teresa; Miro, Jaime Valls

2017-10-06

Remote-Field Eddy-Current (RFEC) technology is often used as a Non-Destructive Evaluation (NDE) method to prevent water pipe failures. By analyzing the RFEC data, it is possible to quantify the corrosion present in pipes. Quantifying the corrosion involves detecting defects and extracting their depth and shape. For large sections of pipelines, this can be extremely time-consuming if performed manually. Automated approaches are therefore well motivated. In this article, we propose an automated framework to locate and segment defects in individual pipe segments, starting from raw RFEC measurements taken over large pipelines. The framework relies on a novel feature to robustly detect these defects and a segmentation algorithm applied to the deconvolved RFEC signal. The framework is evaluated using both simulated and real datasets, demonstrating its ability to efficiently segment the shape of corrosion defects.

A performance study of unmanned aerial vehicle-based sensor networks under cyber attack

NASA Astrophysics Data System (ADS)

Puchaty, Ethan M.

In UAV-based sensor networks, an emerging area of interest is the performance of these networks under cyber attack. This study seeks to evaluate the performance trade-offs from a System-of-Systems (SoS) perspective between various UAV communications architecture options in the context two missions: tracking ballistic missiles and tracking insurgents. An agent-based discrete event simulation is used to model a sensor communication network consisting of UAVs, military communications satellites, ground relay stations, and a mission control center. Network susceptibility to cyber attack is modeled with probabilistic failures and induced data variability, with performance metrics focusing on information availability, latency, and trustworthiness. Results demonstrated that using UAVs as routers increased network availability with a minimal latency penalty and communications satellite networks were best for long distance operations. Redundancy in the number of links between communication nodes helped mitigate cyber-caused link failures and add robustness in cases of induced data variability by an adversary. However, when failures were not independent, redundancy and UAV routing were detrimental in some cases to network performance. Sensitivity studies indicated that long cyber-caused downtimes and increasing failure dependencies resulted in build-ups of failures and caused significant degradations in network performance.

Informing the Design of "Lifestyle Monitoring" Technology for the Detection of Health Deterioration in Long-Term Conditions: A Qualitative Study of People Living With Heart Failure.

PubMed

Hargreaves, Sarah; Hawley, Mark S; Haywood, Annette; Enderby, Pamela M

2017-06-28

Health technologies are being developed to help people living at home manage long-term conditions. One such technology is "lifestyle monitoring" (LM), a telecare technology based on the idea that home activities may be monitored unobtrusively via sensors to give an indication of changes in health-state. However, questions remain about LM technology: how home activities change when participants experience differing health-states; and how sensors might capture clinically important changes to inform timely interventions. The objective of this paper was to report the findings of a study aimed at identifying changes in activity indicative of important changes in health in people with long-term conditions, particularly changes indicative of exacerbation, by exploring the relationship between home activities and health among people with heart failure (HF). We aimed to add to the knowledge base informing the development of home monitoring technologies designed to detect health deterioration in order to facilitate early intervention and avoid hospital admissions. This qualitative study utilized semistructured interviews to explore everyday activities undertaken during the three health-states of HF: normal days, bad days, and exacerbations. Potential recruits were identified by specialist nurses and attendees at an HF support group. The sample was purposively selected to include a range of experience of living with HF. The sample comprised a total of 20 people with HF aged 50 years and above, and 11 spouses or partners of the individuals with HF. All resided in Northern England. Participant accounts revealed that home activities are in part shaped by the degree of intrusion from HF symptoms. During an exacerbation, participants undertook activities specifically to ease symptoms, and detailed activity changes were identified. Everyday activity was also influenced by a range of factors other than health. The study highlights the importance of careful development of LM technology to identify changes in activities that occur during clinically important changes in health. These detailed activity changes need to be considered by developers of LM sensors, platforms, and algorithms intended to detect early signs of deterioration. Results suggest that for LM to move forward, sensor set-up should be personalized to individual circumstances and targeted at individual health conditions. LM needs to take account of the uncertainties that arise from placing technology within the home, in order to inform sensor set-up and data interpretation. This targeted approach is likely to yield more clinically meaningful data and address some of the ethical issues of remote monitoring. ©Sarah Hargreaves, Mark S Hawley, Annette Haywood, Pamela M Enderby. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 28.06.2017.

Human heart failure biomarker immunosensor based on excessively tilted fiber gratings.

PubMed

Luo, Binbin; Wu, Shengxi; Zhang, Zhonghao; Zou, Wengen; Shi, Shenghui; Zhao, Mingfu; Zhong, Nianbing; Liu, Yong; Zou, Xue; Wang, Lingling; Chai, Weina; Hu, Chuanmin; Zhang, Lin

2017-01-01

A label-free immunosensor platform based on excessively tilted fiber gratings (Ex-TFGs) was developed for highly specific and fast detection of human N-terminal pro-B-type natriuretic peptide (NT-proBNP), which is considered a powerful biomarker for prognosis and risk stratification of heart failure (HF). High-purity anti-NT-proBNP monoclonal antibodies (MAbs) prepared in our laboratory were immobilized on fiber surface through the staphylococcal protein A (SPA) method for subsequent specific binding of the targeted NT-proBNP. Utilizing fiber optic grating demodulation system (FOGDS), immunoassays were carried out in vitro by monitoring the resonance wavelength shift of Ex-TFG biosensor with immobilized anti-NT-proBNP MAbs. Lowest detectable concentration of ~0.5ng/mL for NT-proBNP was obtained, and average sensitivity for NT-proBNP at a concentration range of 0~1.0 ng/mL was approximately 45.967 pm/(ng/mL). Several human serum samples were assessed by the proposed Ex-TFG biomarker sensor, with high specificity for NT-proBNP, indicating potential application in early diagnosing patients with acute HF symptoms.

Robust Modal Filtering and Control of the X-56A Model with Simulated Fiber Optic Sensor Failures

NASA Technical Reports Server (NTRS)

Suh, Peter M.; Chin, Alexander W.; Marvis, Dimitri N.

2014-01-01

The X-56A aircraft is a remotely-piloted aircraft with flutter modes intentionally designed into the flight envelope. The X-56A program must demonstrate flight control while suppressing all unstable modes. A previous X-56A model study demonstrated a distributed-sensing-based active shape and active flutter suppression controller. The controller relies on an estimator which is sensitive to bias. This estimator is improved herein, and a real-time robust estimator is derived and demonstrated on 1530 fiber optic sensors. It is shown in simulation that the estimator can simultaneously reject 230 worst-case fiber optic sensor failures automatically. These sensor failures include locations with high leverage (or importance). To reduce the impact of leverage outliers, concentration based on a Mahalanobis trim criterion is introduced. A redescending M-estimator with Tukey bisquare weights is used to improve location and dispersion estimates within each concentration step in the presence of asymmetry (or leverage). A dynamic simulation is used to compare the concentrated robust estimator to a state-of-the-art real-time robust multivariate estimator. The estimators support a previously-derived mu-optimal shape controller. It is found that during the failure scenario, the concentrated modal estimator keeps the system stable.

Robust Modal Filtering and Control of the X-56A Model with Simulated Fiber Optic Sensor Failures

NASA Technical Reports Server (NTRS)

Suh, Peter M.; Chin, Alexander W.; Mavris, Dimitri N.

2016-01-01

The X-56A aircraft is a remotely-piloted aircraft with flutter modes intentionally designed into the flight envelope. The X-56A program must demonstrate flight control while suppressing all unstable modes. A previous X-56A model study demonstrated a distributed-sensing-based active shape and active flutter suppression controller. The controller relies on an estimator which is sensitive to bias. This estimator is improved herein, and a real-time robust estimator is derived and demonstrated on 1530 fiber optic sensors. It is shown in simulation that the estimator can simultaneously reject 230 worst-case fiber optic sensor failures automatically. These sensor failures include locations with high leverage (or importance). To reduce the impact of leverage outliers, concentration based on a Mahalanobis trim criterion is introduced. A redescending M-estimator with Tukey bisquare weights is used to improve location and dispersion estimates within each concentration step in the presence of asymmetry (or leverage). A dynamic simulation is used to compare the concentrated robust estimator to a state-of-the-art real-time robust multivariate estimator. The estimators support a previously-derived mu-optimal shape controller. It is found that during the failure scenario, the concentrated modal estimator keeps the system stable.

A new fault diagnosis algorithm for AUV cooperative localization system

NASA Astrophysics Data System (ADS)

Shi, Hongyang; Miao, Zhiyong; Zhang, Yi

2017-10-01

Multiple AUVs cooperative localization as a new kind of underwater positioning technology, not only can improve the positioning accuracy, but also has many advantages the single AUV does not have. It is necessary to detect and isolate the fault to increase the reliability and availability of the AUVs cooperative localization system. In this paper, the Extended Multiple Model Adaptive Cubature Kalmam Filter (EMMACKF) method is presented to detect the fault. The sensor failures are simulated based on the off-line experimental data. Experimental results have shown that the faulty apparatus can be diagnosed effectively using the proposed method. Compared with Multiple Model Adaptive Extended Kalman Filter and Multi-Model Adaptive Unscented Kalman Filter, both accuracy and timelines have been improved to some extent.

Structural health monitoring and impact detection for primary aircraft structures

NASA Astrophysics Data System (ADS)

Kosters, Eric; van Els, Thomas J.

2010-04-01

The increasing use of thermoplastic carbon fiber-reinforced plastic (CFRP) materials in the aerospace industry for primary aircraft structures, such as wing leading-edge surfaces and fuselage sections, has led to rapid growth in the field of structural health monitoring (SHM). Impact, vibration, and load can all cause failure, such as delamination and matrix cracking, in composite materials. Moreover, the internal material damage can occur without being visible to the human eye, making inspection of and clear insight into structural integrity difficult using currently available evaluation methods. Here, we describe the detection of impact and its localization in materials and structures by high-speed interrogation of multiple-fiber Bragg grating (FBG) sensors mounted on a composite aircraft component.

Guided wave and damage detection in composite laminates using different fiber optic sensors.

PubMed

Li, Fucai; Murayama, Hideaki; Kageyama, Kazuro; Shirai, Takehiro

2009-01-01

Guided wave detection using different fiber optic sensors and their applications in damage detection for composite laminates were systematically investigated and compared in this paper. Two types of fiber optic sensors, namely fiber Bragg gratings (FBG) and Doppler effect-based fiber optic (FOD) sensors, were addressed and guided wave detection systems were constructed for both types. Guided waves generated by a piezoelectric transducer were propagated through a quasi-isotropic carbon fiber reinforced plastic (CFRP) laminate and acquired by these fiber optic sensors. Characteristics of these fiber optic sensors in ultrasonic guided wave detection were systematically compared. Results demonstrated that both the FBG and FOD sensors can be applied in guided wave and damage detection for the CFRP laminates. The signal-to-noise ratio (SNR) of guided wave signal captured by an FOD sensor is relatively high in comparison with that of the FBG sensor because of their different physical principles in ultrasonic detection. Further, the FOD sensor is sensitive to the damage-induced fundamental shear horizontal (SH(0)) guided wave that, however, cannot be detected by using the FBG sensor, because the FOD sensor is omnidirectional in ultrasound detection and, in contrast, the FBG sensor is severely direction dependent.

Sensor Technology Baseline Study for Enabling Condition Based Maintenance Plus in Army Ground Vehicles

DTIC Science & Technology

2012-03-01

for enabling condition based maintenance plus in Army ground vehicles. The sensor study was driven from Failure Mode Effects Analysis ( FMEA ...of Tables Table 1. Sensor technology baseline study based on engine FMEA report. ...................................5 Table 2. Sensor technology...baseline study based on transmission FMEA report. .........................8 Table 3. Sensor technology baseline study based on alternator FMEA report

Multi-Domain SDN Survivability for Agricultural Wireless Sensor Networks.

PubMed

Huang, Tao; Yan, Siyu; Yang, Fan; Liu, Jiang

2016-11-06

Wireless sensor networks (WSNs) have been widely applied in agriculture field; meanwhile, the advent of multi-domain software-defined networks (SDNs) have improved the wireless resource utilization rate and strengthened network management. In recent times, multi-domain SDNs have been applied to agricultural sensor networks, namely multi-domain software-defined wireless sensor networks (SDWSNs). However, when the SDNs controlling agriculture networks suddenly become unavailable, whether intra-domain or inter-domain, sensor network communication is abnormal because of the loss of control. Moreover, there are controller and switch info-updating problems even if the controller becomes available again. To resolve these problems, this paper proposes a new approach based on an Open vSwitch extension for multi-domain SDWSNs, which can enhance agriculture network survivability and stability. We achieved this by designing a connection-state mechanism, a communication mechanism on both L2 and L3, and an info-updating mechanism based on Open vSwitch. The experimental results show that, whether it is agricultural inter-domain or intra-domain during the controller failure period, the sensor switches can enter failure recovery mode as soon as possible so that the sensor network keeps a stable throughput, a short failure recovery time below 300 ms, and low packet loss. Further, the domain can smoothly control the domain network again once the controller becomes available. This approach based on an Open vSwitch extension can enhance the survivability and stability of multi-domain SDWSNs in precision agriculture.

Multi-Domain SDN Survivability for Agricultural Wireless Sensor Networks

PubMed Central

Huang, Tao; Yan, Siyu; Yang, Fan; Liu, Jiang

2016-01-01

Wireless sensor networks (WSNs) have been widely applied in agriculture field; meanwhile, the advent of multi-domain software-defined networks (SDNs) have improved the wireless resource utilization rate and strengthened network management. In recent times, multi-domain SDNs have been applied to agricultural sensor networks, namely multi-domain software-defined wireless sensor networks (SDWSNs). However, when the SDNs controlling agriculture networks suddenly become unavailable, whether intra-domain or inter-domain, sensor network communication is abnormal because of the loss of control. Moreover, there are controller and switch info-updating problems even if the controller becomes available again. To resolve these problems, this paper proposes a new approach based on an Open vSwitch extension for multi-domain SDWSNs, which can enhance agriculture network survivability and stability. We achieved this by designing a connection-state mechanism, a communication mechanism on both L2 and L3, and an info-updating mechanism based on Open vSwitch. The experimental results show that, whether it is agricultural inter-domain or intra-domain during the controller failure period, the sensor switches can enter failure recovery mode as soon as possible so that the sensor network keeps a stable throughput, a short failure recovery time below 300 ms, and low packet loss. Further, the domain can smoothly control the domain network again once the controller becomes available. This approach based on an Open vSwitch extension can enhance the survivability and stability of multi-domain SDWSNs in precision agriculture. PMID:27827971

Real-Time Sensor Validation System Developed for Reusable Launch Vehicle Testbed

NASA Technical Reports Server (NTRS)

Jankovsky, Amy L.

1997-01-01

A real-time system for validating sensor health has been developed for the reusable launch vehicle (RLV) program. This system, which is part of the propulsion checkout and control system (PCCS), was designed for use in an integrated propulsion technology demonstrator testbed built by Rockwell International and located at the NASA Marshall Space Flight Center. Work on the sensor health validation system, a result of an industry-NASA partnership, was completed at the NASA Lewis Research Center, then delivered to Marshall for integration and testing. The sensor validation software performs three basic functions: it identifies failed sensors, it provides reconstructed signals for failed sensors, and it identifies off-nominal system transient behavior that cannot be attributed to a failed sensor. The code is initiated by host software before the start of a propulsion system test, and it is called by the host program every control cycle. The output is posted to global memory for use by other PCCS modules. Output includes a list indicating the status of each sensor (i.e., failed, healthy, or reconstructed) and a list of features that are not due to a sensor failure. If a sensor failure is found, the system modifies that sensor's data array by substituting a reconstructed signal, when possible, for use by other PCCS modules.

Accelerated Aging Experiments for Prognostics of Damage Growth in Composite Materials

NASA Technical Reports Server (NTRS)

Saxena, Abhinav; Goebel, Kai Frank; Larrosa, Cecilia C.; Janapati, Vishnuvardhan; Roy, Surajit; Chang, Fu-Kuo

2011-01-01

Composite structures are gaining importance for use in the aerospace industry. Compared to metallic structures their behavior is less well understood. This lack of understanding may pose constraints on their use. One possible way to deal with some of the risks associated with potential failure is to perform in-situ monitoring to detect precursors of failures. Prognostic algorithms can be used to predict impending failures. They require large amounts of training data to build and tune damage model for making useful predictions. One of the key aspects is to get confirmatory feedback from data as damage progresses. These kinds of data are rarely available from actual systems. The next possible resource to collect such data is an accelerated aging platform. To that end this paper describes a fatigue cycling experiment with the goal to stress carbon-carbon composite coupons with various layups. Piezoelectric disc sensors were used to periodically interrogate the system. Analysis showed distinct differences in the signatures of growing failures between data collected at conditions. Periodic X-radiographs were taken to assess the damage ground truth. Results after signal processing showed clear trends of damage growth that were correlated to damage assessed from the X-ray images.

The Use of Probabilistic Methods to Evaluate the Systems Impact of Component Design Improvements on Large Turbofan Engines

NASA Technical Reports Server (NTRS)

Packard, Michael H.

2002-01-01

Probabilistic Structural Analysis (PSA) is now commonly used for predicting the distribution of time/cycles to failure of turbine blades and other engine components. These distributions are typically based on fatigue/fracture and creep failure modes of these components. Additionally, reliability analysis is used for taking test data related to particular failure modes and calculating failure rate distributions of electronic and electromechanical components. How can these individual failure time distributions of structural, electronic and electromechanical component failure modes be effectively combined into a top level model for overall system evaluation of component upgrades, changes in maintenance intervals, or line replaceable unit (LRU) redesign? This paper shows an example of how various probabilistic failure predictions for turbine engine components can be evaluated and combined to show their effect on overall engine performance. A generic model of a turbofan engine was modeled using various Probabilistic Risk Assessment (PRA) tools (Quantitative Risk Assessment Software (QRAS) etc.). Hypothetical PSA results for a number of structural components along with mitigation factors that would restrict the failure mode from propagating to a Loss of Mission (LOM) failure were used in the models. The output of this program includes an overall failure distribution for LOM of the system. The rank and contribution to the overall Mission Success (MS) is also given for each failure mode and each subsystem. This application methodology demonstrates the effectiveness of PRA for assessing the performance of large turbine engines. Additionally, the effects of system changes and upgrades, the application of different maintenance intervals, inclusion of new sensor detection of faults and other upgrades were evaluated in determining overall turbine engine reliability.

J-2X Abort System Development

NASA Technical Reports Server (NTRS)

Santi, Louis M.; Butas, John P.; Aguilar, Robert B.; Sowers, Thomas S.

2008-01-01

The J-2X is an expendable liquid hydrogen (LH2)/liquid oxygen (LOX) gas generator cycle rocket engine that is currently being designed as the primary upper stage propulsion element for the new NASA Ares vehicle family. The J-2X engine will contain abort logic that functions as an integral component of the Ares vehicle abort system. This system is responsible for detecting and responding to conditions indicative of impending Loss of Mission (LOM), Loss of Vehicle (LOV), and/or catastrophic Loss of Crew (LOC) failure events. As an earth orbit ascent phase engine, the J-2X is a high power density propulsion element with non-negligible risk of fast propagation rate failures that can quickly lead to LOM, LOV, and/or LOC events. Aggressive reliability requirements for manned Ares missions and the risk of fast propagating J-2X failures dictate the need for on-engine abort condition monitoring and autonomous response capability as well as traditional abort agents such as the vehicle computer, flight crew, and ground control not located on the engine. This paper describes the baseline J-2X abort subsystem concept of operations, as well as the development process for this subsystem. A strategy that leverages heritage system experience and responds to an evolving engine design as well as J-2X specific test data to support abort system development is described. The utilization of performance and failure simulation models to support abort system sensor selection, failure detectability and discrimination studies, decision threshold definition, and abort system performance verification and validation is outlined. The basis for abort false positive and false negative performance constraints is described. Development challenges associated with information shortfalls in the design cycle, abort condition coverage and response assessment, engine-vehicle interface definition, and abort system performance verification and validation are also discussed.

A novel radar sensor for the non-contact detection of speech signals.

PubMed

Jiao, Mingke; Lu, Guohua; Jing, Xijing; Li, Sheng; Li, Yanfeng; Wang, Jianqi

2010-01-01

Different speech detection sensors have been developed over the years but they are limited by the loss of high frequency speech energy, and have restricted non-contact detection due to the lack of penetrability. This paper proposes a novel millimeter microwave radar sensor to detect speech signals. The utilization of a high operating frequency and a superheterodyne receiver contributes to the high sensitivity of the radar sensor for small sound vibrations. In addition, the penetrability of microwaves allows the novel sensor to detect speech signals through nonmetal barriers. Results show that the novel sensor can detect high frequency speech energies and that the speech quality is comparable to traditional microphone speech. Moreover, the novel sensor can detect speech signals through a nonmetal material of a certain thickness between the sensor and the subject. Thus, the novel speech sensor expands traditional speech detection techniques and provides an exciting alternative for broader application prospects.

A Novel Radar Sensor for the Non-Contact Detection of Speech Signals

PubMed Central

Jiao, Mingke; Lu, Guohua; Jing, Xijing; Li, Sheng; Li, Yanfeng; Wang, Jianqi

2010-01-01

Different speech detection sensors have been developed over the years but they are limited by the loss of high frequency speech energy, and have restricted non-contact detection due to the lack of penetrability. This paper proposes a novel millimeter microwave radar sensor to detect speech signals. The utilization of a high operating frequency and a superheterodyne receiver contributes to the high sensitivity of the radar sensor for small sound vibrations. In addition, the penetrability of microwaves allows the novel sensor to detect speech signals through nonmetal barriers. Results show that the novel sensor can detect high frequency speech energies and that the speech quality is comparable to traditional microphone speech. Moreover, the novel sensor can detect speech signals through a nonmetal material of a certain thickness between the sensor and the subject. Thus, the novel speech sensor expands traditional speech detection techniques and provides an exciting alternative for broader application prospects. PMID:22399895

An Architecture for Real-Time Interpretation and Visualization of Structural Sensor Data in a Laboratory Environment

NASA Technical Reports Server (NTRS)

Doggett, William; Vazquez, Sixto

2000-01-01

A visualization system is being developed out of the need to monitor, interpret, and make decisions based on the information from several thousand sensors during experimental testing to facilitate development and validation of structural health monitoring algorithms. As an added benefit the system will enable complete real-time sensor assessment of complex test specimens. Complex structural specimens are routinely tested that have hundreds or thousands of sensors. During a test, it is impossible for a single researcher to effectively monitor all the sensors and subsequently interesting phenomena occur that are not recognized until post-test analysis. The ability to detect and alert the researcher to these unexpected phenomena as the test progresses will significantly enhance the understanding and utilization of complex test articles. Utilization is increased by the ability to halt a test when the health monitoring algorithm response is not satisfactory or when an unexpected phenomenon occurs, enabling focused investigation potentially through the installation of additional sensors. Often if the test continues, structural changes make it impossible to reproduce the conditions that exhibited the phenomena. The prohibitive time and costs associated with fabrication, sensoring, and subsequent testing of additional test articles generally makes it impossible to further investigate the phenomena. A scalable architecture is described to address the complex computational demands of structural health monitoring algorithm development and laboratory experimental test monitoring. The researcher monitors the test using a photographic quality 3D graphical model with actual sensor locations identified. In addition, researchers can quickly activate plots displaying time or load versus selected sensor response along with the expected values and predefined limits. The architecture has several key features. First, distributed dissimilar computers may be seamlessly integrated into the information flow. Second, virtual sensors may be defined that are complex functions of existing sensors or other virtual sensors. Virtual sensors represent a calculated value not directly measured by particular physical instrument. They can be used, for example, to represent the maximum difference in a range of sensors or the calculated buckling load based on the current strains. Third, the architecture enables autonomous response to preconceived events, where by the system can be configured to suspend or abort a test if a failure is detected in the load introduction system. Fourth, the architecture is designed to allow cooperative monitoring and control of the test progression from multiple stations both remote and local to the test system. To illustrate the architecture, a preliminary implementation is described monitoring the Stitched Composite Wing recently tested at LaRC.

Meeting the Challenges of Exploration Systems: Health Management Technologies for Aerospace Systems With Emphasis on Propulsion

NASA Technical Reports Server (NTRS)

Melcher, Kevin J.; Sowers, T. Shane; Maul, William A.

2005-01-01

The constraints of future Exploration Missions will require unique Integrated System Health Management (ISHM) capabilities throughout the mission. An ambitious launch schedule, human-rating requirements, long quiescent periods, limited human access for repair or replacement, and long communication delays all require an ISHM system that can span distinct yet interdependent vehicle subsystems, anticipate failure states, provide autonomous remediation, and support the Exploration Mission from beginning to end. NASA Glenn Research Center has developed and applied health management system technologies to aerospace propulsion systems for almost two decades. Lessons learned from past activities help define the approach to proper ISHM development: sensor selection- identifies sensor sets required for accurate health assessment; data qualification and validation-ensures the integrity of measurement data from sensor to data system; fault detection and isolation-uses measurements in a component/subsystem context to detect faults and identify their point of origin; information fusion and diagnostic decision criteria-aligns data from similar and disparate sources in time and use that data to perform higher-level system diagnosis; and verification and validation-uses data, real or simulated, to provide variable exposure to the diagnostic system for faults that may only manifest themselves in actual implementation, as well as faults that are detectable via hardware testing. This presentation describes a framework for developing health management systems and highlights the health management research activities performed by the Controls and Dynamics Branch at the NASA Glenn Research Center. It illustrates how those activities contribute to the development of solutions for Integrated System Health Management.

Enhancing the Reliability of Head Nodes in Underwater Sensor Networks

PubMed Central

Min, Hong; Cho, Yookun; Heo, Junyoung

2012-01-01

Underwater environments are quite different from terrestrial environments in terms of the communication media and operating conditions associated with those environments. In underwater sensor networks, the probability of node failure is high because sensor nodes are deployed in harsher environments than ground-based networks. The sensor nodes are surrounded by salt water and moved around by waves and currents. Many studies have focused on underwater communication environments in an effort to improve the data transmission throughput. In this paper, we present a checkpointing scheme for the head nodes to quickly recover from a head node failure. Experimental results show that the proposed scheme enhances the reliability of the networks and makes them more efficient in terms of energy consumption and the recovery latency compared to the previous scheme without checkpointing. PMID:22438707

Mini-UAV based sensory system for measuring environmental variables in greenhouses.

PubMed

Roldán, Juan Jesús; Joossen, Guillaume; Sanz, David; del Cerro, Jaime; Barrientos, Antonio

2015-02-02

This paper describes the design, construction and validation of a mobile sensory platform for greenhouse monitoring. The complete system consists of a sensory system on board a small quadrotor (i.e., a four rotor mini-UAV). The goals of this system include taking measures of temperature, humidity, luminosity and CO2 concentration and plotting maps of these variables. These features could potentially allow for climate control, crop monitoring or failure detection (e.g., a break in a plastic cover). The sensors have been selected by considering the climate and plant growth models and the requirements for their integration onboard the quadrotor. The sensors layout and placement have been determined through a study of quadrotor aerodynamics and the influence of the airflows from its rotors. All components of the system have been developed, integrated and tested through a set of field experiments in a real greenhouse. The primary contributions of this paper are the validation of the quadrotor as a platform for measuring environmental variables and the determination of the optimal location of sensors on a quadrotor.

Mini-UAV Based Sensory System for Measuring Environmental Variables in Greenhouses

PubMed Central

Roldán, Juan Jesús; Joossen, Guillaume; Sanz, David; del Cerro, Jaime; Barrientos, Antonio

2015-01-01

This paper describes the design, construction and validation of a mobile sensory platform for greenhouse monitoring. The complete system consists of a sensory system on board a small quadrotor (i.e., a four rotor mini-UAV). The goals of this system include taking measures of temperature, humidity, luminosity and CO2 concentration and plotting maps of these variables. These features could potentially allow for climate control, crop monitoring or failure detection (e.g., a break in a plastic cover). The sensors have been selected by considering the climate and plant growth models and the requirements for their integration onboard the quadrotor. The sensors layout and placement have been determined through a study of quadrotor aerodynamics and the influence of the airflows from its rotors. All components of the system have been developed, integrated and tested through a set of field experiments in a real greenhouse. The primary contributions of this paper are the validation of the quadrotor as a platform for measuring environmental variables and the determination of the optimal location of sensors on a quadrotor. PMID:25648713

Automatic Detection of Seismocardiogram Sensor Misplacement for Robust Pre-Ejection Period Estimation in Unsupervised Settings.

PubMed

Ashouri, Hazar; Inan, Omer T

2017-06-15

Seismocardiography (SCG), the measurement of the local chest vibrations due to the movements of blood and the heart, is a non-invasive technique for assessing myocardial contractility via the pre-ejection period (PEP). Recently, SCG-based extraction of PEP has been shown to be an effective means of classifying decompensated from compensated heart failure patients, and thus can be potentially used for monitoring such patients at home. Accurate extraction of PEP from SCG signals hinges on lab-based population data (i.e., regression curves) linking particular time-domain features of the SCG signal to corresponding features from reference standard bulky instruments such as impedance cardiography (ICG). Such regression curves, in the case of SCG, have always been estimated based on the "ideal" positioning of the SCG sensor on the chest. However, in settings such as the home where users may position the SCG measurement hardware on the chest without supervision, it is likely that the sensor will not always be placed exactly on this "ideal" location on the sternum, but rather on other positions on the chest as well. In this study, we show for the first time that the regression curve for estimating PEP from SCG signals differs significantly as the position of the sensor changes. We further devise a method to automatically detect when the sensor is placed in any position other than the desired one in order to avoid inaccurate systolic time interval estimation. Our classification algorithm for this purpose resulted in 0.83 precision and 0.82 recall when classifying whether the sensor is placed in the desired position or not. The classifier was tested with heartbeats taken both at rest, and also during exercise recovery to ensure that waveform changes due to positioning could be accurately discriminated from those due to physiological effects.

Testing of the on-board attitude determination and control algorithms for SAMPEX

NASA Technical Reports Server (NTRS)

Mccullough, Jon D.; Flatley, Thomas W.; Henretty, Debra A.; Markley, F. Landis; San, Josephine K.

1993-01-01

Algorithms for on-board attitude determination and control of the Solar, Anomalous, and Magnetospheric Particle Explorer (SAMPEX) have been expanded to include a constant gain Kalman filter for the spacecraft angular momentum, pulse width modulation for the reaction wheel command, an algorithm to avoid pointing the Heavy Ion Large Telescope (HILT) instrument boresight along the spacecraft velocity vector, and the addition of digital sun sensor (DSS) failure detection logic. These improved algorithms were tested in a closed-loop environment for three orbit geometries, one with the sun perpendicular to the orbit plane, and two with the sun near the orbit plane - at Autumnal Equinox and at Winter Solstice. The closed-loop simulator was enhanced and used as a truth model for the control systems' performance evaluation and sensor/actuator contingency analysis. The simulations were performed on a VAX 8830 using a prototype version of the on-board software.

Proceedings of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) Performance Evaluation Workshop

NASA Technical Reports Server (NTRS)

Vane, Gregg (Editor)

1988-01-01

The focus of the workshop was the assessment of data quality by the AVIRIS project. Summaries of 16 of the presentations are published. The AVIRIS performance evaluation period began in June 87 with flight data collection in the eastern U.S., and continued in the west until Oct. 87, after which the instrument was returned for post flight calibration. At the beginning, the sensor met all of the spatial, spectral and radiometric performance requirements except in spectrometer D, where the signal to noise ratio was below the required value. By the end, sensor performance had deteriorated due to failure of 2 critical parts and to some design deficiences. The independent assessment by the NASA investigators confirmed the assessment by the AVIRIS project. Some scientific results were derived and are presented. These include the mapping of the spatial variation of atmospheric precipitable water, detection of shift in chlorophyll red, and mineral identification.

TRPC5 channels participate in pressure-sensing in aortic baroreceptors

PubMed Central

Lau, On-Chai; Shen, Bing; Wong, Ching-On; Tjong, Yung-Wui; Lo, Chun-Yin; Wang, Hui-Chuan; Huang, Yu; Yung, Wing-Ho; Chen, Yang-Chao; Fung, Man-Lung; Rudd, John Anthony; Yao, Xiaoqiang

2016-01-01

Blood pressure is maintained within a normal physiological range by a sophisticated regulatory mechanism. Baroreceptors serve as a frontline sensor to detect the change in blood pressure. Nerve signals are then sent to the cardiovascular control centre in the brain in order to stimulate baroreflex responses. Here, we identify TRPC5 channels as a mechanical sensor in aortic baroreceptors. In Trpc5 knockout mice, the pressure-induced action potential firings in the afferent nerve and the baroreflex-mediated heart rate reduction are attenuated. Telemetric measurements of blood pressure demonstrate that Trpc5 knockout mice display severe daily blood pressure fluctuation. Our results suggest that TRPC5 channels represent a key pressure transducer in the baroreceptors and play an important role in maintaining blood pressure stability. Because baroreceptor dysfunction contributes to a variety of cardiovascular diseases including hypertension, heart failure and myocardial infarction, our findings may have important future clinical implications. PMID:27411851

Fuzzy Neural Network-Based Interacting Multiple Model for Multi-Node Target Tracking Algorithm

PubMed Central

Sun, Baoliang; Jiang, Chunlan; Li, Ming

2016-01-01

An interacting multiple model for multi-node target tracking algorithm was proposed based on a fuzzy neural network (FNN) to solve the multi-node target tracking problem of wireless sensor networks (WSNs). Measured error variance was adaptively adjusted during the multiple model interacting output stage using the difference between the theoretical and estimated values of the measured error covariance matrix. The FNN fusion system was established during multi-node fusion to integrate with the target state estimated data from different nodes and consequently obtain network target state estimation. The feasibility of the algorithm was verified based on a network of nine detection nodes. Experimental results indicated that the proposed algorithm could trace the maneuvering target effectively under sensor failure and unknown system measurement errors. The proposed algorithm exhibited great practicability in the multi-node target tracking of WSNs. PMID:27809271

Scheduling policies of intelligent sensors and sensor/actuators in flexible structures

NASA Astrophysics Data System (ADS)

Demetriou, Michael A.; Potami, Raffaele

2006-03-01

In this note, we revisit the problem of actuator/sensor placement in large civil infrastructures and flexible space structures within the context of spatial robustness. The positioning of these devices becomes more important in systems employing wireless sensor and actuator networks (WSAN) for improved control performance and for rapid failure detection. The ability of the sensing and actuating devices to possess the property of spatial robustness results in reduced control energy and therefore the spatial distribution of disturbances is integrated into the location optimization measures. In our studies, the structure under consideration is a flexible plate clamped at all sides. First, we consider the case of sensor placement and the optimization scheme attempts to produce those locations that minimize the effects of the spatial distribution of disturbances on the state estimation error; thus the sensor locations produce state estimators with minimized disturbance-to-error transfer function norms. A two-stage optimization procedure is employed whereby one first considers the open loop system and the spatial distribution of disturbances is found that produces the maximal effects on the entire open loop state. Once this "worst" spatial distribution of disturbances is found, the optimization scheme subsequently finds the locations that produce state estimators with minimum transfer function norms. In the second part, we consider the collocated actuator/sensor pairs and the optimization scheme produces those locations that result in compensators with the smallest norms of the disturbance-to-state transfer functions. Going a step further, an intelligent control scheme is presented which, at each time interval, activates a subset of the actuator/sensor pairs in order provide robustness against spatiotemporally moving disturbances and minimize power consumption by keeping some sensor/actuators in sleep mode.

The Localized Discovery and Recovery for Query Packet Losses in Wireless Sensor Networks with Distributed Detector Clusters

PubMed Central

Teng, Rui; Leibnitz, Kenji; Miura, Ryu

2013-01-01

An essential application of wireless sensor networks is to successfully respond to user queries. Query packet losses occur in the query dissemination due to wireless communication problems such as interference, multipath fading, packet collisions, etc. The losses of query messages at sensor nodes result in the failure of sensor nodes reporting the requested data. Hence, the reliable and successful dissemination of query messages to sensor nodes is a non-trivial problem. The target of this paper is to enable highly successful query delivery to sensor nodes by localized and energy-efficient discovery, and recovery of query losses. We adopt local and collective cooperation among sensor nodes to increase the success rate of distributed discoveries and recoveries. To enable the scalability in the operations of discoveries and recoveries, we employ a distributed name resolution mechanism at each sensor node to allow sensor nodes to self-detect the correlated queries and query losses, and then efficiently locally respond to the query losses. We prove that the collective discovery of query losses has a high impact on the success of query dissemination and reveal that scalability can be achieved by using the proposed approach. We further study the novel features of the cooperation and competition in the collective recovery at PHY and MAC layers, and show that the appropriate number of detectors can achieve optimal successful recovery rate. We evaluate the proposed approach with both mathematical analyses and computer simulations. The proposed approach enables a high rate of successful delivery of query messages and it results in short route lengths to recover from query losses. The proposed approach is scalable and operates in a fully distributed manner. PMID:23748172

A PVC/polypyrrole sensor designed for beef taste detection using electrochemical methods and sensory evaluation.

PubMed

Zhu, Lingtao; Wang, Xiaodan; Han, Yunxiu; Cai, Yingming; Jin, Jiahui; Wang, Hongmei; Xu, Liping; Wu, Ruijia

2018-03-01

An electrochemical sensor for detection of beef taste was designed in this study. This sensor was based on the structure of polyvinyl chloride/polypyrrole (PVC/PPy), which was polymerized onto the surface of a platinum (Pt) electrode to form a Pt-PPy-PVC film. Detecting by electrochemical methods, the sensor was well characterized by electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV). The sensor was applied to detect 10 rib-eye beef samples and the accuracy of the new sensor was validated by sensory evaluation and ion sensor detection. Several cluster analysis methods were used in the study to distinguish the beef samples. According to the obtained results, the designed sensor showed a high degree of association of electrochemical detection and sensory evaluation, which proved a fast and precise sensor for beef taste detection. Copyright © 2017 Elsevier Ltd. All rights reserved.

Description of a dual fail-operational redundant strapdown inertial measurement unit for integrated avionics systems research

NASA Technical Reports Server (NTRS)

Bryant, W. H.; Morrell, F. R.

1981-01-01

Attention is given to a redundant strapdown inertial measurement unit for integrated avionics. The system consists of four two-degree-of-freedom turned rotor gyros and four two-degree-of-freedom accelerometers in a skewed and separable semi-octahedral array. The unit is coupled through instrument electronics to two flight computers which compensate sensor errors. The flight computers are interfaced to the microprocessors and process failure detection, isolation, redundancy management and flight control/navigation algorithms. The unit provides dual fail-operational performance and has data processing frequencies consistent with integrated avionics concepts presently planned.

Development and implementation of an automatic integration system for fibre optic sensors in the braiding process with the objective of online-monitoring of composite structures

NASA Astrophysics Data System (ADS)

Hufenbach, W.; Gude, M.; Czulak, A.; Kretschmann, Martin

2014-04-01

Increasing economic, political and ecological pressure leads to steadily rising percentage of modern processing and manufacturing processes for fibre reinforced polymers in industrial batch production. Component weights beneath a level achievable by classic construction materials, which lead to a reduced energy and cost balance during product lifetime, justify the higher fabrication costs. However, complex quality control and failure prediction slow down the substitution by composite materials. High-resolution fibre-optic sensors (FOS), due their low diameter, high measuring point density and simple handling, show a high applicability potential for an automated sensor-integration in manufacturing processes, and therefore the online monitoring of composite products manufactured in industrial scale. Integrated sensors can be used to monitor manufacturing processes, part tests as well as the component structure during product life cycle, which simplifies allows quality control during production and the optimization of single manufacturing processes.[1;2] Furthermore, detailed failure analyses lead to a enhanced understanding of failure processes appearing in composite materials. This leads to a lower wastrel number and products of a higher value and longer product life cycle, whereby costs, material and energy are saved. This work shows an automation approach for FOS-integration in the braiding process. For that purpose a braiding wheel has been supplemented with an appliance for automatic sensor application, which has been used to manufacture preforms of high-pressure composite vessels with FOS-networks integrated between the fibre layers. All following manufacturing processes (vacuum infiltration, curing) and component tests (quasi-static pressure test, programmed delamination) were monitored with the help of the integrated sensor networks. Keywords: SHM, high-pressure composite vessel, braiding, automated sensor integration, pressure test, quality control, optic-fibre sensors, Rayleigh, Luna Technologies

Development of a neural network for early detection of renal osteodystrophy

NASA Astrophysics Data System (ADS)

Cheng, Shirley N.; Chan, Heang-Ping; Adler, Ronald; Niklason, Loren T.; Chang, Chair-Li

1991-07-01

Bone erosion presenting as subperiosteal resorption on the phalanges of the hand is an early manifestation of hyperparathyroidism associated with chronic renal failure. At present, the diagnosis is made by trained radiologists through visual inspection of hand radiographs. In this study, a neural network is being developed to assess the feasibility of computer-aided detection of these changes. A two-pass approach is adopted. The digitized image is first compressed by a Laplacian pyramid compact code. The first neural network locates the region of interest using vertical projections along the phalanges and then the horizontal projections across the phalanges. A second neural network is used to classify texture variations of trabecular patterns in the region using a concurrence matrix as the input to a two-dimensional sensor layer to detect the degree of associated osteopenia. Preliminary results demonstrate the feasibility of this approach.

Anomaly Detection Techniques with Real Test Data from a Spinning Turbine Engine-Like Rotor

NASA Technical Reports Server (NTRS)

Abdul-Aziz, Ali; Woike, Mark R.; Oza, Nikunj C.; Matthews, Bryan L.

2012-01-01

Online detection techniques to monitor the health of rotating engine components are becoming increasingly attractive to aircraft engine manufacturers in order to increase safety of operation and lower maintenance costs. Health monitoring remains a challenge to easily implement, especially in the presence of scattered loading conditions, crack size, component geometry, and materials properties. The current trend, however, is to utilize noninvasive types of health monitoring or nondestructive techniques to detect hidden flaws and mini-cracks before any catastrophic event occurs. These techniques go further to evaluate material discontinuities and other anomalies that have grown to the level of critical defects that can lead to failure. Generally, health monitoring is highly dependent on sensor systems capable of performing in various engine environmental conditions and able to transmit a signal upon a predetermined crack length, while acting in a neutral form upon the overall performance of the engine system.

Aircraft Anomaly Detection Using Performance Models Trained on Fleet Data

NASA Technical Reports Server (NTRS)

Gorinevsky, Dimitry; Matthews, Bryan L.; Martin, Rodney

2012-01-01

This paper describes an application of data mining technology called Distributed Fleet Monitoring (DFM) to Flight Operational Quality Assurance (FOQA) data collected from a fleet of commercial aircraft. DFM transforms the data into aircraft performance models, flight-to-flight trends, and individual flight anomalies by fitting a multi-level regression model to the data. The model represents aircraft flight performance and takes into account fixed effects: flight-to-flight and vehicle-to-vehicle variability. The regression parameters include aerodynamic coefficients and other aircraft performance parameters that are usually identified by aircraft manufacturers in flight tests. Using DFM, the multi-terabyte FOQA data set with half-million flights was processed in a few hours. The anomalies found include wrong values of competed variables, (e.g., aircraft weight), sensor failures and baises, failures, biases, and trends in flight actuators. These anomalies were missed by the existing airline monitoring of FOQA data exceedances.

Development of advanced seal verification

NASA Technical Reports Server (NTRS)

Workman, Gary L.; Kosten, Susan E.; Abushagur, Mustafa A.

1992-01-01

The purpose of this research is to develop a technique to monitor and insure seal integrity with a sensor that has no active elements to burn-out during a long duration activity, such as a leakage test or especially during a mission in space. The original concept proposed is that by implementing fiber optic sensors, changes in the integrity of a seal can be monitored in real time and at no time should the optical fiber sensor fail. The electrical components which provide optical excitation and detection through the fiber are not part of the seal; hence, if these electrical components fail, they can be easily changed without breaking the seal. The optical connections required for the concept to work does present a functional problem to work out. The utility of the optical fiber sensor for seal monitoring should be general enough that the degradation of a seal can be determined before catastrophic failure occurs and appropriate action taken. Two parallel efforts were performed in determining the feasibility of using optical fiber sensors for seal verification. In one study, research on interferometric measurements of the mechanical response of the optical fiber sensors to seal integrity was studied. In a second study, the implementation of the optical fiber to a typical vacuum chamber was implemented and feasibility studies on microbend experiments in the vacuum chamber were performed. Also, an attempt was made to quantify the amount of pressure actually being applied to the optical fiber using finite element analysis software by Algor.

Remote Left Ventricular Hemodynamic Monitoring Using a Novel Intracardiac Sensor.

PubMed

Mondritzki, Thomas; Boehme, Philip; White, Jason; Park, Jin Woo; Hoffmann, Jessica; Vogel, Julia; Kolkhof, Peter; Walsh, Stuart; Sandner, Peter; Bischoff, Erwin; Dinh, Wilfried; Hüser, Jörg; Truebel, Hubert

2018-05-01

Heart failure (HF) remains the most common reason for hospital admission in patients aged >65 years. Despite modern drug therapy, mortality and readmission rates for patients hospitalized with HF remain high. This necessitates further research to identify early patients at risk for readmission to limit hospitalization by timely adjustment of medical therapy. Implantable devices can monitor left ventricular (LV) hemodynamics and remotely and continuously detect the early signs of decompensation to trigger interventions and reduce the risk of hospitalization for HF. Here, we report the first preclinical study validating a new batteryless and easy to implant LV-microelectromechanical system to assess LV performance. A miniaturized implantable wireless pressure sensor was adapted for implantation in the LV apex. The LV-microelectromechanical system sensor was tested in a canine model of HF. The wireless pressure sensor measurements were compared with invasive left heart catheter-derived measurements at several time points. During different pharmacological challenge studies with dobutamine or vasopressin, the device was equally sensitive compared with invasive standard procedures. No adverse events or any observable reaction related to the implantation and application of the device for a period of 35 days was observed. Our miniaturized wireless pressure sensor placed in the LV (LV-microelectromechanical system) has the potential to become a new telemetric tool to earlier identify patients at risk for HF decompensation and to guide the treatment of patients with HF. © 2018 American Heart Association, Inc.

Strength and fatigue life evaluation of composite laminate with embedded sensors

NASA Astrophysics Data System (ADS)

Rathod, Vivek T.; Hiremath, S. R.; Roy Mahapatra, D.

2014-04-01

Prognosis regarding durability of composite structures using various Structural Health Monitoring (SHM) techniques is an important and challenging topic of research. Ultrasonic SHM systems with embedded transducers have potential application here due to their instant monitoring capability, compact packaging potential toward unobtrusiveness and noninvasiveness as compared to non-contact ultrasonic and eddy current techniques which require disassembly of the structure. However, embedded sensors pose a risk to the structure by acting as a flaw thereby reducing life. The present paper focuses on the determination of strength and fatigue life of the composite laminate with embedded film sensors like CNT nanocomposite, PVDF thin films and piezoceramic films. First, the techniques of embedding these sensors in composite laminates is described followed by the determination of static strength and fatigue life at coupon level testing in Universal Testing Machine (UTM). Failure mechanisms of the composite laminate with embedded sensors are studied for static and dynamic loading cases. The coupons are monitored for loading and failure using the embedded sensors. A comparison of the performance of these three types of embedded sensors is made to study their suitability in various applications. These three types of embedded sensors cover a wide variety of applications, and prove to be viable in embedded sensor based SHM of composite structures.

A wireless monitoring system for Hydrocephalus shunts.

PubMed

Narayanaswamy, A; Nourani, M; Tamil, L; Bianco, S

2015-08-01

Patients with Hydrocephalus are usually treated by diverting the excess Cerebrospinal Fluid (CSF) to other parts of the body using shunts. More than 40 percentage of shunts implanted fail within the first two years. Obstruction in the shunts is one of the major causes of failure (45 percent) and the detection of obstruction reduces the complexity of the revision surgery. This paper describes a proposed wireless monitoring system for clog detection and flow measurement in shunts. A prototype was built using multiple pressure sensors along the shunt catheters for sensing the location of clog and flow rate. Regular monitoring of flow rates can be used to adjust the valve in the shunt to prevent over drainage or under drainage of CSF. The accuracy of the flow measurement is more than 90 percent.

Thin film temperature sensor

NASA Technical Reports Server (NTRS)

Grant, H. P.; Przybyszewski, J. S.

1980-01-01

Thin film surface temperature sensors were developed. The sensors were made of platinum-platinum/10 percent rhodium thermocouples with associated thin film-to-lead wire connections and sputtered on aluminum oxide coated simulated turbine blades for testing. Tests included exposure to vibration, low velocity hydrocarbon hot gas flow to 1250 K, and furnace calibrations. Thermal electromotive force was typically two percent below standard type S thermocouples. Mean time to failure was 42 hours at a hot gas flow temperature of 1250 K and an average of 15 cycles to room temperature. Failures were mainly due to separation of the platinum thin film from the aluminum oxide surface. Several techniques to improve the adhesion of the platinum are discussed.

Development of compact slip detection sensor using dielectric elastomer

NASA Astrophysics Data System (ADS)

Choi, Jae-young; Hwang, Do-Yeon; Kim, Baek-chul; Moon, Hyungpil; Choi, Hyouk Ryeol; Koo, Ja Choon

2015-04-01

In this paper, we developed a resistance tactile sensor that can detect a slip on the surface of sensor structure. The presented sensor device has fingerprint-like structures that are similar with the role of the humans finger print. The resistance slip sensor that the novel developed uses acrylo-nitrile butadiene rubber (NBR) as a dielectric substrate and graphene as an electrode material. We can measure the slip as the structure of sensor makes a deformation and it changes the resistance through forming a new conductive route. To manufacture our sensor, we developed a new imprint process. By using this process, we can produce sensor with micro unit structure. To verify effectiveness of the proposed slip detection, experiment using prototype of resistance slip sensor is conducted with an algorithm to detect slip and slip is successfully detected. We will discuss the slip detection properties.

Propulsion health monitoring of a turbine engine disk using spin test data

NASA Astrophysics Data System (ADS)

Abdul-Aziz, Ali; Woike, Mark; Oza, Nikunj; Matthews, Bryan; Baakilini, George

2010-03-01

On line detection techniques to monitor the health of rotating engine components are becoming increasingly attractive options to aircraft engine companies in order to increase safety of operation and lower maintenance costs. Health monitoring remains a challenging feature to easily implement, especially, in the presence of scattered loading conditions, crack size, component geometry and materials properties. The current trend, however, is to utilize noninvasive types of health monitoring or nondestructive techniques to detect hidden flaws and mini cracks before any catastrophic event occurs. These techniques go further to evaluate materials' discontinuities and other anomalies that have grown to the level of critical defects which can lead to failure. Generally, health monitoring is highly dependent on sensor systems that are capable of performing in various engine environmental conditions and able to transmit a signal upon a predetermined crack length, while acting in a neutral form upon the overall performance of the engine system. Efforts are under way at NASA Glenn Research Center through support of the Intelligent Vehicle Health Management Project (IVHM) to develop and implement such sensor technology for a wide variety of applications. These efforts are focused on developing high temperature, wireless, low cost and durable products. Therefore, in an effort to address the technical issues concerning health monitoring of a rotor disk, this paper considers data collected from an experimental study using high frequency capacitive sensor technology to capture blade tip clearance and tip timing measurements in a rotating engine-like-disk-to predict the disk faults and assess its structural integrity. The experimental results collected at a range of rotational speeds from tests conducted at the NASA Glenn Research Center's Rotordynamics Laboratory will be evaluated using multiple data-driven anomaly detection techniques to identify anomalies in the disk. This study is expected to present a select evaluation of online health monitoring of a rotating disk using these high caliber sensors and test the capability of the in-house spin system.

Design of LPV fault-tolerant controller for pitch system of wind turbine

NASA Astrophysics Data System (ADS)

Wu, Dinghui; Zhang, Xiaolin

2017-07-01

To address failures of wind turbine pitch-angle sensors, traditional wind turbine linear parameter varying (LPV) model is transformed into a double-layer convex polyhedron LPV model. On the basis of this model, when the plurality of the sensor undergoes failure and details of the failure are inconvenient to obtain, each sub-controller is designed using distributed thought and gain scheduling method. The final controller is obtained using all of the sub-controllers by a convex combination. The design method corrects the errors of the linear model, improves the linear degree of the system, and solves the problem of multiple pitch angle faults to ensure stable operation of the wind turbine.

DREAMS-SIS: The Solar Irradiance Sensor on-board the ExoMars 2016 lander

NASA Astrophysics Data System (ADS)

Arruego, I.; Apéstigue, V.; Jiménez-Martín, J.; Martínez-Oter, J.; Álvarez-Ríos, F. J.; González-Guerrero, M.; Rivas, J.; Azcue, J.; Martín, I.; Toledo, D.; Gómez, L.; Jiménez-Michavila, M.; Yela, M.

2017-07-01

The Solar Irradiance Sensor (SIS) was part of the DREAMS (Dust characterization, Risk assessment, and Environment Analyzer on the Martian Surface) payload package on board the ExoMars 2016 Entry and Descent Module (EDM), "Schiaparelli". DREAMS was a meteorological station aimed at the measurement of several atmospheric parameters, as well as the presence of electric fields, during the surface operations of EDM. DREAMS-SIS is a highly miniaturized lightweight sensor designed for small meteorological stations, capable of estimating the aerosol optical depth (AOD) several times per sol, as well as performing a direct measurement of the global (direct plus scattered) irradiance on the Martian surface in the spectral range between 200 and 1100 nm. AOD is estimated from the irradiance measurements at two different spectral bands - Ultraviolet (UV) and near infrared (NIR) - which also enables color index (CI) analysis for the detection of clouds. Despite the failure in the landing of Schiaparelli, DREAMS-SIS is a valuable precursor for new developments being carried-on at present. The concept and design of DREAMS-SIS are here presented and its operating principles, supported by preliminary results from a short validation test, are described. Lessons learnt and future work towards a new generation of Sun irradiance sensors is also outlined.

Systems and methods for detecting a flame in a fuel nozzle of a gas turbine

DOEpatents

Kraemer, Gilbert Otto; Storey, James Michael; Lipinski, John; Mestroni, Julio Enrique; Williamson, David Lee; Marshall, Jason Randolph; Krull, Anthony

2013-05-07

A system may detect a flame about a fuel nozzle of a gas turbine. The gas turbine may have a compressor and a combustor. The system may include a first pressure sensor, a second pressure sensor, and a transducer. The first pressure sensor may detect a first pressure upstream of the fuel nozzle. The second pressure sensor may detect a second pressure downstream of the fuel nozzle. The transducer may be operable to detect a pressure difference between the first pressure sensor and the second pressure sensor.

Real-Time Adaptation of Decision Thresholds in Sensor Networks for Detection of Moving Targets (PREPRINT)

DTIC Science & Technology

2010-01-01

target kinematics for multiple sensor detections is referred to as the track - before - detect strategy, and is commonly adopted in multi-sensor surveillance...of moving targets. Wettergren [4] presented an application of track - before - detect strategies to undersea distributed sensor networks. In de- signing...the deployment of a distributed passive sensor network that employs this track - before - detect procedure, it is impera- tive that the placement of

Monolithic fiber optic sensor assembly

DOEpatents

Sanders, Scott

2015-02-10

A remote sensor element for spectrographic measurements employs a monolithic assembly of one or two fiber optics to two optical elements separated by a supporting structure to allow the flow of gases or particulates therebetween. In a preferred embodiment, the sensor element components are fused ceramic to resist high temperatures and failure from large temperature changes.

Structural health monitoring of glass/epoxy composite plates with MEMS PMN-PT sensors

NASA Astrophysics Data System (ADS)

Simon, Brenton R.; Tang, Hong-Yue; Horsley, David A.; La Saponara, Valeria; Lestari, Wahyu

2009-03-01

Sensors constructed with single-crystal PMN-PT, i.e. Pb(Mg1/3Nb2/3)O3-PbTiO3 or PMN, are developed in this paper for structural health monitoring of composite plates. To determine the potential of PMN-PT for this application, glass/epoxy composite specimens were created containing an embedded delamination-starter. Two different piezoelectric materials were bonded to the surface of each specimen: PMN-PT, the test material, was placed on one side of the specimen, while a traditional material, PZT-4, was placed on the other. A comparison of the ability of both materials to transmit and receive an ultrasonic pulse was conducted, with the received signal detected by both a second surface-bonded transducer constructed of the same material, as well as a laser Doppler vibrometer (LDV) analyzing the same location. The optimal frequency range of both sets of transducers is discussed and a comparison is presented of the experimental results to theory. The specimens will be fatigued until failure with further data collected every 3,000 cycles to characterize the ability of each material to detect the growing delamination in the composite structure. This additional information will be made available during the conference.

Reliability and availability evaluation of Wireless Sensor Networks for industrial applications.

PubMed

Silva, Ivanovitch; Guedes, Luiz Affonso; Portugal, Paulo; Vasques, Francisco

2012-01-01

Wireless Sensor Networks (WSN) currently represent the best candidate to be adopted as the communication solution for the last mile connection in process control and monitoring applications in industrial environments. Most of these applications have stringent dependability (reliability and availability) requirements, as a system failure may result in economic losses, put people in danger or lead to environmental damages. Among the different type of faults that can lead to a system failure, permanent faults on network devices have a major impact. They can hamper communications over long periods of time and consequently disturb, or even disable, control algorithms. The lack of a structured approach enabling the evaluation of permanent faults, prevents system designers to optimize decisions that minimize these occurrences. In this work we propose a methodology based on an automatic generation of a fault tree to evaluate the reliability and availability of Wireless Sensor Networks, when permanent faults occur on network devices. The proposal supports any topology, different levels of redundancy, network reconfigurations, criticality of devices and arbitrary failure conditions. The proposed methodology is particularly suitable for the design and validation of Wireless Sensor Networks when trying to optimize its reliability and availability requirements.

Reliability and Availability Evaluation of Wireless Sensor Networks for Industrial Applications

PubMed Central

Silva, Ivanovitch; Guedes, Luiz Affonso; Portugal, Paulo; Vasques, Francisco

2012-01-01

Wireless Sensor Networks (WSN) currently represent the best candidate to be adopted as the communication solution for the last mile connection in process control and monitoring applications in industrial environments. Most of these applications have stringent dependability (reliability and availability) requirements, as a system failure may result in economic losses, put people in danger or lead to environmental damages. Among the different type of faults that can lead to a system failure, permanent faults on network devices have a major impact. They can hamper communications over long periods of time and consequently disturb, or even disable, control algorithms. The lack of a structured approach enabling the evaluation of permanent faults, prevents system designers to optimize decisions that minimize these occurrences. In this work we propose a methodology based on an automatic generation of a fault tree to evaluate the reliability and availability of Wireless Sensor Networks, when permanent faults occur on network devices. The proposal supports any topology, different levels of redundancy, network reconfigurations, criticality of devices and arbitrary failure conditions. The proposed methodology is particularly suitable for the design and validation of Wireless Sensor Networks when trying to optimize its reliability and availability requirements. PMID:22368497

Stress Wave Source Characterization: Impact, Fracture, and Sliding Friction

NASA Astrophysics Data System (ADS)

McLaskey, Gregory Christofer

Rapidly varying forces, such as those associated with impact, rapid crack propagation, and fault rupture, are sources of stress waves which propagate through a solid body. This dissertation investigates how properties of a stress wave source can be identified or constrained using measurements recorded at an array of sensor sites located far from the source. This methodology is often called the method of acoustic emission and is useful for structural health monitoring and the noninvasive study of material behavior such as friction and fracture. In this dissertation, laboratory measurements of 1--300 mm wavelength stress waves are obtained by means of piezoelectric sensors which detect high frequency (10 kHz--3MHz) motions of a specimen's surface, picometers to nanometers in amplitude. Then, stress wave source characterization techniques are used to study ball impact, drying shrinkage cracking in concrete, and the micromechanics of stick-slip friction of Poly(methyl methacrylate) (PMMA) and rock/rock interfaces. In order to quantitatively relate recorded signals obtained with an array of sensors to a particular stress wave source, wave propagation effects and sensor distortions must be accounted for. This is achieved by modeling the physics of wave propagation and transduction as linear transfer functions. Wave propagation effects are precisely modeled by an elastodynamic Green's function, sensor distortion is characterized by an instrument response function, and the stress wave source is represented with a force moment tensor. These transfer function models are verified though calibration experiments which employ two different mechanical calibration sources: ball impact and glass capillary fracture. The suitability of the ball impact source model, based on Hertzian contact theory, is experimentally validated for small (˜1 mm) balls impacting massive plates composed of four different materials: aluminum, steel, glass, and PMMA. Using this transfer function approach and the two mechanical calibration sources, four types of piezoelectric sensors were calibrated: three commercially available sensors and the Glaser-type conical piezoelectric sensor, which was developed in the Glaser laboratory. The distorting effects of each sensor are modeled using autoregressive-moving average (ARMA) models, and because vital phase information is robustly incorporated into these models, they are useful for simulating or removing sensor-induced distortions, so that a displacement time history can be retrieved from recorded signals. The Glaser-type sensor was found to be very well modeled as a unidirectional displacement sensor which detects stress wave disturbances down to about 1 picometer in amplitude. Finally, the merits of a fully calibrated experimental system are demonstrated in a study of stress wave sources arising from sliding friction, and the relationship between those sources and earthquakes. A laboratory friction apparatus was built for this work which allows the micro-mechanisms of friction to be studied with stress wave analysis. Using an array of 14 Glaser-type sensors, and precise models of wave propagation effects and the sensor distortions, the physical origins of the stress wave sources are explored. Force-time functions and focal mechanisms are determined for discrete events found amid the "noise" of friction. These localized events are interpreted to be the rupture of micrometer-sized contacts, known as asperities. By comparing stress wave sources from stick-slip experiments on plastic/plastic and rock/rock interfaces, systematic differences were found. The rock interface produces very rapid (<1 microsecond) implosive forces indicative of brittle asperity failure and fault gouge formation, while rupture on the plastic interface releases only shear force and produces a source more similar to earthquakes commonly recorded in the field. The difference between the mechanisms is attributed to the vast differences in the hardness and melting temperatures of the two materials, which affect the distribution of asperities as well as their failure behavior. With proper scaling, the strong link between material properties and laboratory earthquakes will aid in our understanding of fault mechanics and the generation of earthquakes and seismic tremor.

46 CFR 129.570 - Overfill protection.

Code of Federal Regulations, 2014 CFR

2014-10-01

... alarm system or failure of electrical circuitry to the tank level sensor; and (3) Be able to be checked... that monitors the condition of the alarm circuitry and sensor. (d) The high-level alarm required by...

Development of microsized slip sensors using dielectric elastomer for incipient slippage

NASA Astrophysics Data System (ADS)

Hwang, Do-Yeon; Kim, Baek-chul; Cho, Han-Jeong; Li, Zhengyuan; Lee, Youngkwan; Nam, Jae-Do; Moon, Hyungpil; Choi, Hyouk Ryeol; Koo, J. C.

2014-04-01

A humanoid robot hand has received significant attention in various fields of study. In terms of dexterous robot hand, slip detecting tactile sensor is essential to grasping objects safely. Moreover, slip sensor is useful in robotics and prosthetics to improve precise control during manipulation tasks. In this paper, sensor based-human biomimetic structure is fabricated. We reported a resistance tactile sensor that enables to detect a slip on the surface of sensor structure. The resistance slip sensor that the novel developed uses acrylonitrile-butadiene rubber (NBR) as a dielectric substrate and carbon particle as an electrode material. The presented sensor device in this paper has fingerprint-like structures that are similar with the role of the human's finger print. It is possible to measure the slip as the structure of sensor makes a deformation and it changes the resistance through forming a new conductive route. To verify effectiveness of the proposed slip detection, experiment using prototype of resistance slip sensor is conducted with an algorithm to detect slip and slip was successfully detected. In this paper, we will discuss the slip detection properties so four sensor and detection principle.

Monitoring System for Storm Readiness and Recovery of Test Facilities: Integrated System Health Management (ISHM) Approach

NASA Technical Reports Server (NTRS)

Figueroa, Fernando; Morris, Jon; Turowski, Mark; Franzl, Richard; Walker, Mark; Kapadia, Ravi; Venkatesh, Meera; Schmalzel, John

2010-01-01

Severe weather events are likely occurrences on the Mississippi Gulf Coast. It is important to rapidly diagnose and mitigate the effects of storms on Stennis Space Center's rocket engine test complex to avoid delays to critical test article programs, reduce costs, and maintain safety. An Integrated Systems Health Management (ISHM) approach and technologies are employed to integrate environmental (weather) monitoring, structural modeling, and the suite of available facility instrumentation to provide information for readiness before storms, rapid initial damage assessment to guide mitigation planning, and then support on-going assurance as repairs are effected and finally support recertification. The system is denominated Katrina Storm Monitoring System (KStorMS). Integrated Systems Health Management (ISHM) describes a comprehensive set of capabilities that provide insight into the behavior the health of a system. Knowing the status of a system allows decision makers to effectively plan and execute their mission. For example, early insight into component degradation and impending failures provides more time to develop work around strategies and more effectively plan for maintenance. Failures of system elements generally occur over time. Information extracted from sensor data, combined with system-wide knowledge bases and methods for information extraction and fusion, inference, and decision making, can be used to detect incipient failures. If failures do occur, it is critical to detect and isolate them, and suggest an appropriate course of action. ISHM enables determining the condition (health) of every element in a complex system-of-systems or SoS (detect anomalies, diagnose causes, predict future anomalies), and provide data, information, and knowledge (DIaK) to control systems for safe and effective operation. ISHM capability is achieved by using a wide range of technologies that enable anomaly detection, diagnostics, prognostics, and advise for control: (1) anomaly detection algorithms and strategies, (2) fusion of DIaK for anomaly detection (model-based, numerical, statistical, empirical, expert-based, qualitative, etc.), (3) diagnostics/prognostics strategies and methods, (4) user interface, (5) advanced control strategies, (6) integration architectures/frameworks, (7) embedding of intelligence. Many of these technologies are mature, and they are being used in the KStorMS. The paper will describe the design, implementation, and operation of the KStorMS; and discuss further evolution to support other needs such as condition-based maintenance (CBM).

Providing Self-Healing Ability for Wireless Sensor Node by Using Reconfigurable Hardware

PubMed Central

Yuan, Shenfang; Qiu, Lei; Gao, Shang; Tong, Yao; Yang, Weiwei

2012-01-01

Wireless sensor networks (WSNs) have received tremendous attention over the past ten years. In engineering applications of WSNs, a number of sensor nodes are usually spread across some specific geographical area. Some of these nodes have to work in harsh environments. Dependability of the Wireless Sensor Network (WSN) is very important for its successful applications in the engineering area. In ordinary research, when a node has a failure, it is usually discarded and the network is reorganized to ensure the normal operation of the WSN. Using appropriate WSN re-organization methods, though the sensor networks can be reorganized, this causes additional maintenance costs and sometimes still decreases the function of the networks. In those situations where the sensor networks cannot be reorganized, the performance of the whole WSN will surely be degraded. In order to ensure the reliable and low cost operation of WSNs, a method to develop a wireless sensor node with self-healing ability based on reconfigurable hardware is proposed in this paper. Two self-healing WSN node realization paradigms based on reconfigurable hardware are presented, including a redundancy-based self-healing paradigm and a whole FPAA/FPGA based self-healing paradigm. The nodes designed with the self-healing ability can dynamically change their node configurations to repair the nodes' hardware failures. To demonstrate these two paradigms, a strain sensor node is adopted as an illustration to show the concepts. Two strain WSN sensor nodes with self-healing ability are developed respectively according to the proposed self-healing paradigms. Evaluation experiments on self-healing ability and power consumption are performed. Experimental results show that the developed nodes can self-diagnose the failures and recover to a normal state automatically. The research presented can improve the robustness of WSNs and reduce the maintenance cost of WSNs in engineering applications. PMID:23202176

Self-monitoring fiber reinforced polymer strengthening system for civil engineering infrastructures

NASA Astrophysics Data System (ADS)

Jiang, Guoliang; Dawood, Mina; Peters, Kara; Rizkalla, Sami

2008-03-01

Fiber reinforced polymer (FRP) materials are currently used for strengthening civil engineering infrastructures. The strengthening system is dependant on the bond characteristics of the FRP to the external surface of the structure to be effective in resisting the applied loads. This paper presents an innovative self-monitoring FRP strengthening system. The system consists of two components which can be embedded in FRP materials to monitor the global and local behavior of the strengthened structure respectively. The first component of the system is designed to evaluate the applied load acting on a structure based on elongation of the FRP layer along the entire span of the structure. Success of the global system has been demonstrated using a full-scale prestressed concrete bridge girder which was loaded up to failure. The test results indicate that this type of sensor can be used to accurately determine the load prior to failure within 15 percent of the measured value. The second sensor component consists of fiber Bragg grating sensors. The sensors were used to monitor the behavior of steel double-lap shear splices tested under tensile loading up to failure. The measurements were used to identify abnormal structural behavior such as epoxy cracking and FRP debonding. Test results were also compared to numerical values obtained from a three dimensional shear-lag model which was developed to predict the sensor response.

General Purpose Data-Driven Online System Health Monitoring with Applications to Space Operations

NASA Technical Reports Server (NTRS)

Iverson, David L.; Spirkovska, Lilly; Schwabacher, Mark

2010-01-01

Modern space transportation and ground support system designs are becoming increasingly sophisticated and complex. Determining the health state of these systems using traditional parameter limit checking, or model-based or rule-based methods is becoming more difficult as the number of sensors and component interactions grows. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. System health can be monitored by comparing real-time operating data with these nominal characterizations, providing detection of anomalous data signatures indicative of system faults, failures, or precursors of significant failures. The Inductive Monitoring System (IMS) is a general purpose, data-driven system health monitoring software tool that has been successfully applied to several aerospace applications and is under evaluation for anomaly detection in vehicle and ground equipment for next generation launch systems. After an introduction to IMS application development, we discuss these NASA online monitoring applications, including the integration of IMS with complementary model-based and rule-based methods. Although the examples presented in this paper are from space operations applications, IMS is a general-purpose health-monitoring tool that is also applicable to power generation and transmission system monitoring.