A Game Theoretic Fault Detection Filter

NASA Technical Reports Server (NTRS)

Chung, Walter H.; Speyer, Jason L.

1995-01-01

The fault detection process is modelled as a disturbance attenuation problem. The solution to this problem is found via differential game theory, leading to an H(sub infinity) filter which bounds the transmission of all exogenous signals save the fault to be detected. For a general class of linear systems which includes some time-varying systems, it is shown that this transmission bound can be taken to zero by simultaneously bringing the sensor noise weighting to zero. Thus, in the limit, a complete transmission block can he achieved, making the game filter into a fault detection filter. When we specialize this result to time-invariant system, it is found that the detection filter attained in the limit is identical to the well known Beard-Jones Fault Detection Filter. That is, all fault inputs other than the one to be detected (the "nuisance faults") are restricted to an invariant subspace which is unobservable to a projection on the output. For time-invariant systems, it is also shown that in the limit, the order of the state-space and the game filter can be reduced by factoring out the invariant subspace. The result is a lower dimensional filter which can observe only the fault to be detected. A reduced-order filter can also he generated for time-varying systems, though the computational overhead may be intensive. An example given at the end of the paper demonstrates the effectiveness of the filter as a tool for fault detection and identification.

Model-based fault detection and isolation for intermittently active faults with application to motion-based thruster fault detection and isolation for spacecraft

NASA Technical Reports Server (NTRS)

Wilson, Edward (Inventor)

2008-01-01

The present invention is a method for detecting and isolating fault modes in a system having a model describing its behavior and regularly sampled measurements. The models are used to calculate past and present deviations from measurements that would result with no faults present, as well as with one or more potential fault modes present. Algorithms that calculate and store these deviations, along with memory of when said faults, if present, would have an effect on the said actual measurements, are used to detect when a fault is present. Related algorithms are used to exonerate false fault modes and finally to isolate the true fault mode. This invention is presented with application to detection and isolation of thruster faults for a thruster-controlled spacecraft. As a supporting aspect of the invention, a novel, effective, and efficient filtering method for estimating the derivative of a noisy signal is presented.

Reset Tree-Based Optical Fault Detection

PubMed Central

Lee, Dong-Geon; Choi, Dooho; Seo, Jungtaek; Kim, Howon

2013-01-01

In this paper, we present a new reset tree-based scheme to protect cryptographic hardware against optical fault injection attacks. As one of the most powerful invasive attacks on cryptographic hardware, optical fault attacks cause semiconductors to misbehave by injecting high-energy light into a decapped integrated circuit. The contaminated result from the affected chip is then used to reveal secret information, such as a key, from the cryptographic hardware. Since the advent of such attacks, various countermeasures have been proposed. Although most of these countermeasures are strong, there is still the possibility of attack. In this paper, we present a novel optical fault detection scheme that utilizes the buffers on a circuit's reset signal tree as a fault detection sensor. To evaluate our proposal, we model radiation-induced currents into circuit components and perform a SPICE simulation. The proposed scheme is expected to be used as a supplemental security tool. PMID:23698267

[Design of High Frequency Signal Detecting Circuit of Human Body Impedance Used for Ultrashort Wave Diathermy Apparatus].

PubMed

Fan, Xu; Wang, Yunguang; Cheng, Haiping; Chong, Xiaochen

2016-02-01

The present circuit was designed to apply to human tissue impedance tuning and matching device in ultra-short wave treatment equipment. In order to judge if the optimum status of circuit parameter between energy emitter circuit and accepter circuit is in well syntony, we designed a high frequency envelope detect circuit to coordinate with automatic adjust device of accepter circuit, which would achieve the function of human tissue impedance matching and tuning. Using the sampling coil to receive the signal of amplitude-modulated wave, we compared the voltage signal of envelope detect circuit with electric current of energy emitter circuit. The result of experimental study was that the signal, which was transformed by the envelope detect circuit, was stable and could be recognized by low speed Analog to Digital Converter (ADC) and was proportional to the electric current signal of energy emitter circuit. It could be concluded that the voltage, transformed by envelope detect circuit can mirror the real circuit state of syntony and realize the function of human tissue impedance collecting.

Changes in transthoracic electrical impedance at high altitude.

PubMed

Hoon, R S; Balasubramanian, V; Tiwari, S C; Mathew, O P; Behl, A; Sharma, S C; Chadha, K S

1977-01-01

Mean transthoracic electrical impedance (impedance) which is inversely related to intrathoracic extravascular fluid volume was measured in 121 normal healthy volunteers at sea-level and at 3658 metres altitude. Fifty (group A) reached the high altitude location after an hour's journey in a pressurised aircraft. Twenty-five (group D) underwent slow road ascent including acclimatisation en route. Thirty permanent residents (group B) and 16 temporary residents at high altitude (group C) were also studied. Serial studies in the 30 subjects of group A who developed symptoms of high altidue sickness showed a significant decrease of impedance up to the fourth day of exposure to high altitude which later returned to normal. The 4 volunteers who developed severe symptoms showed the largest drop in impedance. A case of acute pulmonary oedema developing at 4300 metres showed an impedance value of 24-1 ohms on admission. After effective treatment the impedance increased by 11-9 to 36-0 ohms. Twenty asymptomatic subjects of group A and 25 of group D showed a small average increase in impedance values at high altitude. These obstructions suggest that measurement of transthoracic electrical impedance may be a valuable means of detecting incipient high altitude pulmonary oedema.

Detecting Faults In High-Voltage Transformers

NASA Technical Reports Server (NTRS)

Blow, Raymond K.

1988-01-01

Simple fixture quickly shows whether high-voltage transformer has excessive voids in dielectric materials and whether high-voltage lead wires too close to transformer case. Fixture is "go/no-go" indicator; corona appears if transformer contains such faults. Nests in wire mesh supported by cap of clear epoxy. If transformer has defects, blue glow of corona appears in mesh and is seen through cap.

Maneuver Classification for Aircraft Fault Detection

NASA Technical Reports Server (NTRS)

Oza, Nikunj C.; Tumer, Irem Y.; Tumer, Kagan; Huff, Edward M.

2003-01-01

Automated fault detection is an increasingly important problem in aircraft maintenance and operation. Standard methods of fault detection assume the availability of either data produced during all possible faulty operation modes or a clearly-defined means to determine whether the data provide a reasonable match to known examples of proper operation. In the domain of fault detection in aircraft, identifying all possible faulty and proper operating modes is clearly impossible. We envision a system for online fault detection in aircraft, one part of which is a classifier that predicts the maneuver being performed by the aircraft as a function of vibration data and other available data. To develop such a system, we use flight data collected under a controlled test environment, subject to many sources of variability. We explain where our classifier fits into the envisioned fault detection system as well as experiments showing the promise of this classification subsystem.

Baseline impedance measured during high-resolution esophageal impedance manometry reliably discriminates GERD patients.

PubMed

Ravi, K; Geno, D M; Vela, M F; Crowell, M D; Katzka, D A

2017-05-01

Baseline impedance measured with ambulatory impedance pH monitoring (MII-pH) and a mucosal impedance catheter detects gastroesophageal reflux disease (GERD). However, these tools are limited by cost or patient tolerance. We investigated whether baseline impedance measured during high-resolution impedance manometry (HRIM) distinguishes GERD patients from controls. Consecutive patients with clinical HRIM and MII-pH testing were identified. Gastroesophageal reflux disease was defined by esophageal pH <4 for ≥5% of both the supine and total study time, whereas controls had an esophageal pH <4 for ≤3% of the study performed off PPI. Baseline impedance was measured over 15 seconds during the landmark period of HRIM and over three 10 minute intervals during the overnight period of MII-pH. Among 29 GERD patients and 26 controls, GERD patients had a mean esophageal acid exposure time of 22.7% compared to 1.2% in controls (P<.0001). Mean baseline impedance during HRIM was lower in GERD (1061 Ω) than controls (2814 Ω) (P<.0001). Baseline mucosal impedance measured during HRIM and MII-pH correlated (r=0.59, P<.0001). High-resolution esophageal manometry baseline impedance had high diagnostic accuracy for GERD, with an area under the curve (AUC) of 0.931 on receiver operating characteristics (ROC) analysis. A HRIM baseline impedance threshold of 1582 Ω had a sensitivity of 86.2% and specificity of 88.5% for GERD, with a positive predictive value of 89.3% and negative predictive value of 85.2%. Baseline impedance measured during HRIM can reliably discriminate GERD patients with at least moderate esophageal acid exposure from controls. This diagnostic tool may represent an accurate, cost-effective, and less invasive test for GERD. © 2016 John Wiley & Sons Ltd.

A Portable Impedance Immunosensing System for Rapid Detection of Salmonella Typhimurium

PubMed Central

Wen, Tao; Wang, Ronghui; Sotero, America; Li, Yanbin

2017-01-01

Salmonella Typhimurium is one of the most dangerous foodborne pathogens and poses a significant threat to human health. The objective of this study was to develop a portable impedance immunosensing system for rapid and sensitive detection of S. Typhimurium in poultry. The developed portable impedance immunosensing system consisted of a gold interdigitated array microelectrode (IDAM), a signal acquisitive interface and a laptop computer with LabVIEW software. The IDAM was first functionalized with 16-Mercaptohexadecanoic acid, and streptavidin was immobilized onto the electrode surface through covalent bonding. Then, biotin-labelled S. Typhimurium-antibody was immobilized onto the IDAM surface. Samples were dropped on the surface of the IDAM and the S. Typhimurium cells in the samples were captured by the antibody on the IDAM. This resulted in impedance changes that were measured and displayed with the LabVIEW software. An equivalent circuit of the immunosensor demonstrated that the largest change in impedance was due to the electron-transfer resistance. The equivalent circuit showed an increase of 35% for the electron-transfer resistance value compared to the negative control. The calibration result indicated that the portable impedance immunosensing system could be used to measure the standard impedance elements, and it had a maximum error of measurement of approximately 13%. For pure culture detection, the system had a linear relationship between the impedance change and the logarithmic value of S. Typhimurium cells ranging from 76 to 7.6 × 106 CFU (colony-forming unit) (50 μL)−1. The immunosensor also had a correlation coefficient of 0.98, and a high specificity for detection of S. Typhimurium cells with a limit of detection (LOD) of 102 CFU (50 μL)−1. The detection time from the moment a sample was introduced to the display of the results was 1 h. To conclude, the portable impedance immunosensing system for detection of S. Typhimurium achieved an LOD

A Portable Impedance Immunosensing System for Rapid Detection of Salmonella Typhimurium.

PubMed

Wen, Tao; Wang, Ronghui; Sotero, America; Li, Yanbin

2017-08-28

Salmonella Typhimurium is one of the most dangerous foodborne pathogens and poses a significant threat to human health. The objective of this study was to develop a portable impedance immunosensing system for rapid and sensitive detection of S . Typhimurium in poultry. The developed portable impedance immunosensing system consisted of a gold interdigitated array microelectrode (IDAM), a signal acquisitive interface and a laptop computer with LabVIEW software. The IDAM was first functionalized with 16-Mercaptohexadecanoic acid, and streptavidin was immobilized onto the electrode surface through covalent bonding. Then, biotin-labelled S . Typhimurium -antibody was immobilized onto the IDAM surface. Samples were dropped on the surface of the IDAM and the S . Typhimurium cells in the samples were captured by the antibody on the IDAM. This resulted in impedance changes that were measured and displayed with the LabVIEW software. An equivalent circuit of the immunosensor demonstrated that the largest change in impedance was due to the electron-transfer resistance. The equivalent circuit showed an increase of 35% for the electron-transfer resistance value compared to the negative control. The calibration result indicated that the portable impedance immunosensing system could be used to measure the standard impedance elements, and it had a maximum error of measurement of approximately 13%. For pure culture detection, the system had a linear relationship between the impedance change and the logarithmic value of S . Typhimurium cells ranging from 76 to 7.6 × 10⁶ CFU (colony-forming unit) (50 μL) -1 . The immunosensor also had a correlation coefficient of 0.98, and a high specificity for detection of S . Typhimurium cells with a limit of detection (LOD) of 10² CFU (50 μL) -1 . The detection time from the moment a sample was introduced to the display of the results was 1 h. To conclude, the portable impedance immunosensing system for detection of S . Typhimurium achieved

Aircraft Fault Detection and Classification Using Multi-Level Immune Learning Detection

NASA Technical Reports Server (NTRS)

Wong, Derek; Poll, Scott; KrishnaKumar, Kalmanje

2005-01-01

This work is an extension of a recently developed software tool called MILD (Multi-level Immune Learning Detection), which implements a negative selection algorithm for anomaly and fault detection that is inspired by the human immune system. The immunity-based approach can detect a broad spectrum of known and unforeseen faults. We extend MILD by applying a neural network classifier to identify the pattern of fault detectors that are activated during fault detection. Consequently, MILD now performs fault detection and identification of the system under investigation. This paper describes the application of MILD to detect and classify faults of a generic transport aircraft augmented with an intelligent flight controller. The intelligent control architecture is designed to accommodate faults without the need to explicitly identify them. Adding knowledge about the existence and type of a fault will improve the handling qualities of a degraded aircraft and impact tactical and strategic maneuvering decisions. In addition, providing fault information to the pilot is important for maintaining situational awareness so that he can avoid performing an action that might lead to unexpected behavior - e.g., an action that exceeds the remaining control authority of the damaged aircraft. We discuss the detection and classification results of simulated failures of the aircraft's control system and show that MILD is effective at determining the problem with low false alarm and misclassification rates.

Fault Current Distribution and Pole Earth Potential Rise (EPR) Under Substation Fault

NASA Astrophysics Data System (ADS)

Nnassereddine, M.; Rizk, J.; Hellany, A.; Nagrial, M.

2013-09-01

New high-voltage (HV) substations are fed by transmission lines. The position of these lines necessitates earthing design to ensure safety compliance of the system. Conductive structures such as steel or concrete poles are widely used in HV transmission mains. The earth potential rise (EPR) generated by a fault at the substation could result in an unsafe condition. This article discusses EPR based on substation fault. The pole EPR assessment under substation fault is assessed with and without mutual impedance consideration. Split factor determination with and without the mutual impedance of the line is also discussed. Furthermore, a simplified formula to compute the pole grid current under substation fault is included. Also, it includes the introduction of the n factor which determines the number of poles that required earthing assessments under substation fault. A case study is shown.

A SVM framework for fault detection of the braking system in a high speed train

NASA Astrophysics Data System (ADS)

Liu, Jie; Li, Yan-Fu; Zio, Enrico

2017-03-01

In April 2015, the number of operating High Speed Trains (HSTs) in the world has reached 3603. An efficient, effective and very reliable braking system is evidently very critical for trains running at a speed around 300 km/h. Failure of a highly reliable braking system is a rare event and, consequently, informative recorded data on fault conditions are scarce. This renders the fault detection problem a classification problem with highly unbalanced data. In this paper, a Support Vector Machine (SVM) framework, including feature selection, feature vector selection, model construction and decision boundary optimization, is proposed for tackling this problem. Feature vector selection can largely reduce the data size and, thus, the computational burden. The constructed model is a modified version of the least square SVM, in which a higher cost is assigned to the error of classification of faulty conditions than the error of classification of normal conditions. The proposed framework is successfully validated on a number of public unbalanced datasets. Then, it is applied for the fault detection of braking systems in HST: in comparison with several SVM approaches for unbalanced datasets, the proposed framework gives better results.

Applications of Fault Detection in Vibrating Structures

NASA Technical Reports Server (NTRS)

Eure, Kenneth W.; Hogge, Edward; Quach, Cuong C.; Vazquez, Sixto L.; Russell, Andrew; Hill, Boyd L.

2012-01-01

Structural fault detection and identification remains an area of active research. Solutions to fault detection and identification may be based on subtle changes in the time series history of vibration signals originating from various sensor locations throughout the structure. The purpose of this paper is to document the application of vibration based fault detection methods applied to several structures. Overall, this paper demonstrates the utility of vibration based methods for fault detection in a controlled laboratory setting and limitations of applying the same methods to a similar structure during flight on an experimental subscale aircraft.

Classification of Aircraft Maneuvers for Fault Detection

NASA Technical Reports Server (NTRS)

Oza, Nikunj C.; Tumer, Irem Y.; Tumer, Kagan; Huff, Edward M.; Clancy, Daniel (Technical Monitor)

2002-01-01

Automated fault detection is an increasingly important problem in aircraft maintenance and operation. Standard methods of fault detection assume the availability of either data produced during all possible faulty operation modes or a clearly-defined means to determine whether the data is a reasonable match to known examples of proper operation. In our domain of fault detection in aircraft, the first assumption is unreasonable and the second is difficult to determine. We envision a system for online fault detection in aircraft, one part of which is a classifier that predicts the maneuver being performed by the aircraft as a function of vibration data and other available data. We explain where this subsystem fits into our envisioned fault detection system as well its experiments showing the promise of this classification subsystem.

Immunity-Based Aircraft Fault Detection System

NASA Technical Reports Server (NTRS)

Dasgupta, D.; KrishnaKumar, K.; Wong, D.; Berry, M.

2004-01-01

In the study reported in this paper, we have developed and applied an Artificial Immune System (AIS) algorithm for aircraft fault detection, as an extension to a previous work on intelligent flight control (IFC). Though the prior studies had established the benefits of IFC, one area of weakness that needed to be strengthened was the control dead band induced by commanding a failed surface. Since the IFC approach uses fault accommodation with no detection, the dead band, although it reduces over time due to learning, is present and causes degradation in handling qualities. If the failure can be identified, this dead band can be further A ed to ensure rapid fault accommodation and better handling qualities. The paper describes the application of an immunity-based approach that can detect a broad spectrum of known and unforeseen failures. The approach incorporates the knowledge of the normal operational behavior of the aircraft from sensory data, and probabilistically generates a set of pattern detectors that can detect any abnormalities (including faults) in the behavior pattern indicating unsafe in-flight operation. We developed a tool called MILD (Multi-level Immune Learning Detection) based on a real-valued negative selection algorithm that can generate a small number of specialized detectors (as signatures of known failure conditions) and a larger set of generalized detectors for unknown (or possible) fault conditions. Once the fault is detected and identified, an adaptive control system would use this detection information to stabilize the aircraft by utilizing available resources (control surfaces). We experimented with data sets collected under normal and various simulated failure conditions using a piloted motion-base simulation facility. The reported results are from a collection of test cases that reflect the performance of the proposed immunity-based fault detection algorithm.

Impedance measurements for detecting pathogens attached to antibodies

DOEpatents

Miles, Robin R.; Venkateswaran, Kodumudi S.; Fuller, Christopher K.

2004-12-28

The use of impedance measurements to detect the presence of pathogens attached to antibody-coated beads. In a fluidic device antibodies are immobilized on a surface of a patterned interdigitated electrode. Pathogens in a sample fluid streaming past the electrode attach to the immobilized antibodies, which produces a change in impedance between two adjacent electrodes, which impedance change is measured and used to detect the presence of a pathogen. To amplify the signal, beads coated with antibodies are introduced and the beads would stick to the pathogen causing a greater change in impedance between the two adjacent electrodes.

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.

Detection and Modeling of High-Dimensional Thresholds for Fault Detection and Diagnosis

NASA Technical Reports Server (NTRS)

He, Yuning

2015-01-01

Many Fault Detection and Diagnosis (FDD) systems use discrete models for detection and reasoning. To obtain categorical values like oil pressure too high, analog sensor values need to be discretized using a suitablethreshold. Time series of analog and discrete sensor readings are processed and discretized as they come in. This task isusually performed by the wrapper code'' of the FDD system, together with signal preprocessing and filtering. In practice,selecting the right threshold is very difficult, because it heavily influences the quality of diagnosis. If a threshold causesthe alarm trigger even in nominal situations, false alarms will be the consequence. On the other hand, if threshold settingdoes not trigger in case of an off-nominal condition, important alarms might be missed, potentially causing hazardoussituations. In this paper, we will in detail describe the underlying statistical modeling techniques and algorithm as well as the Bayesian method for selecting the most likely shape and its parameters. Our approach will be illustrated by several examples from the Aerospace domain.

Classification of Aircraft Maneuvers for Fault Detection

NASA Technical Reports Server (NTRS)

Oza, Nikunj; Tumer, Irem Y.; Tumer, Kagan; Huff, Edward M.; Koga, Dennis (Technical Monitor)

2002-01-01

Automated fault detection is an increasingly important problem in aircraft maintenance and operation. Standard methods of fault detection assume the availability of either data produced during all possible faulty operation modes or a clearly-defined means to determine whether the data provide a reasonable match to known examples of proper operation. In the domain of fault detection in aircraft, the first assumption is unreasonable and the second is difficult to determine. We envision a system for online fault detection in aircraft, one part of which is a classifier that predicts the maneuver being performed by the aircraft as a function of vibration data and other available data. To develop such a system, we use flight data collected under a controlled test environment, subject to many sources of variability. We explain where our classifier fits into the envisioned fault detection system as well as experiments showing the promise of this classification subsystem.

Soft Computing Application in Fault Detection of Induction Motor

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

Konar, P.; Puhan, P. S.; Chattopadhyay, P. Dr.

2010-10-26

The paper investigates the effectiveness of different patter classifier like Feed Forward Back Propagation (FFBPN), Radial Basis Function (RBF) and Support Vector Machine (SVM) for detection of bearing faults in Induction Motor. The steady state motor current with Park's Transformation has been used for discrimination of inner race and outer race bearing defects. The RBF neural network shows very encouraging results for multi-class classification problems and is hoped to set up a base for incipient fault detection of induction motor. SVM is also found to be a very good fault classifier which is highly competitive with RBF.

Expert System Detects Power-Distribution Faults

NASA Technical Reports Server (NTRS)

Walters, Jerry L.; Quinn, Todd M.

1994-01-01

Autonomous Power Expert (APEX) computer program is prototype expert-system program detecting faults in electrical-power-distribution system. Assists human operators in diagnosing faults and deciding what adjustments or repairs needed for immediate recovery from faults or for maintenance to correct initially nonthreatening conditions that could develop into faults. Written in Lisp.

Potential fault region detection in TFDS images based on convolutional neural network

NASA Astrophysics Data System (ADS)

Sun, Junhua; Xiao, Zhongwen

2016-10-01

In recent years, more than 300 sets of Trouble of Running Freight Train Detection System (TFDS) have been installed on railway to monitor the safety of running freight trains in China. However, TFDS is simply responsible for capturing, transmitting, and storing images, and fails to recognize faults automatically due to some difficulties such as such as the diversity and complexity of faults and some low quality images. To improve the performance of automatic fault recognition, it is of great importance to locate the potential fault areas. In this paper, we first introduce a convolutional neural network (CNN) model to TFDS and propose a potential fault region detection system (PFRDS) for simultaneously detecting four typical types of potential fault regions (PFRs). The experimental results show that this system has a higher performance of image detection to PFRs in TFDS. An average detection recall of 98.95% and precision of 100% are obtained, demonstrating the high detection ability and robustness against various poor imaging situations.

Incipient fault detection study for advanced spacecraft systems

NASA Technical Reports Server (NTRS)

Milner, G. Martin; Black, Michael C.; Hovenga, J. Mike; Mcclure, Paul F.

1986-01-01

A feasibility study to investigate the application of vibration monitoring to the rotating machinery of planned NASA advanced spacecraft components is described. Factors investigated include: (1) special problems associated with small, high RPM machines; (2) application across multiple component types; (3) microgravity; (4) multiple fault types; (5) eight different analysis techniques including signature analysis, high frequency demodulation, cepstrum, clustering, amplitude analysis, and pattern recognition are compared; and (6) small sample statistical analysis is used to compare performance by computation of probability of detection and false alarm for an ensemble of repeated baseline and faulted tests. Both detection and classification performance are quantified. Vibration monitoring is shown to be an effective means of detecting the most important problem types for small, high RPM fans and pumps typical of those planned for the advanced spacecraft. A preliminary monitoring system design and implementation plan is presented.

Fault Detection for Automotive Shock Absorber

NASA Astrophysics Data System (ADS)

Hernandez-Alcantara, Diana; Morales-Menendez, Ruben; Amezquita-Brooks, Luis

2015-11-01

Fault detection for automotive semi-active shock absorbers is a challenge due to the non-linear dynamics and the strong influence of the disturbances such as the road profile. First obstacle for this task, is the modeling of the fault, which has been shown to be of multiplicative nature. Many of the most widespread fault detection schemes consider additive faults. Two model-based fault algorithms for semiactive shock absorber are compared: an observer-based approach and a parameter identification approach. The performance of these schemes is validated and compared using a commercial vehicle model that was experimentally validated. Early results shows that a parameter identification approach is more accurate, whereas an observer-based approach is less sensible to parametric uncertainty.

Fault detection and isolation for complex system

NASA Astrophysics Data System (ADS)

Jing, Chan Shi; Bayuaji, Luhur; Samad, R.; Mustafa, M.; Abdullah, N. R. H.; Zain, Z. M.; Pebrianti, Dwi

2017-07-01

Fault Detection and Isolation (FDI) is a method to monitor, identify, and pinpoint the type and location of system fault in a complex multiple input multiple output (MIMO) non-linear system. A two wheel robot is used as a complex system in this study. The aim of the research is to construct and design a Fault Detection and Isolation algorithm. The proposed method for the fault identification is using hybrid technique that combines Kalman filter and Artificial Neural Network (ANN). The Kalman filter is able to recognize the data from the sensors of the system and indicate the fault of the system in the sensor reading. Error prediction is based on the fault magnitude and the time occurrence of fault. Additionally, Artificial Neural Network (ANN) is another algorithm used to determine the type of fault and isolate the fault in the system.

Planetary Gearbox Fault Detection Using Vibration Separation Techniques

NASA Technical Reports Server (NTRS)

Lewicki, David G.; LaBerge, Kelsen E.; Ehinger, Ryan T.; Fetty, Jason

2011-01-01

Studies were performed to demonstrate the capability to detect planetary gear and bearing faults in helicopter main-rotor transmissions. The work supported the Operations Support and Sustainment (OSST) program with the U.S. Army Aviation Applied Technology Directorate (AATD) and Bell Helicopter Textron. Vibration data from the OH-58C planetary system were collected on a healthy transmission as well as with various seeded-fault components. Planetary fault detection algorithms were used with the collected data to evaluate fault detection effectiveness. Planet gear tooth cracks and spalls were detectable using the vibration separation techniques. Sun gear tooth cracks were not discernibly detectable from the vibration separation process. Sun gear tooth spall defects were detectable. Ring gear tooth cracks were only clearly detectable by accelerometers located near the crack location or directly across from the crack. Enveloping provided an effective method for planet bearing inner- and outer-race spalling fault detection.

The Fault Block Model: A novel approach for faulted gas reservoirs

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

Ursin, J.R.; Moerkeseth, P.O.

1994-12-31

The Fault Block Model was designed for the development of gas production from Sleipner Vest. The reservoir consists of marginal marine sandstone of Hugine Formation. Modeling of highly faulted and compartmentalized reservoirs is severely impeded by the nature and extent of known and undetected faults and, in particular, their effectiveness as flow barrier. The model presented is efficient and superior to other models, for highly faulted reservoir, i.e. grid based simulators, because it minimizes the effect of major undetected faults and geological uncertainties. In this article the authors present the Fault Block Model as a new tool to better understandmore » the implications of geological uncertainty in faulted gas reservoirs with good productivity, with respect to uncertainty in well coverage and optimum gas recovery.« less

MgB2-based superconductors for fault current limiters

NASA Astrophysics Data System (ADS)

Sokolovsky, V.; Prikhna, T.; Meerovich, V.; Eisterer, M.; Goldacker, W.; Kozyrev, A.; Weber, H. W.; Shapovalov, A.; Sverdun, V.; Moshchil, V.

2017-02-01

A promising solution of the fault current problem in power systems is the application of fast-operating nonlinear superconducting fault current limiters (SFCLs) with the capability of rapidly increasing their impedance, and thus limiting high fault currents. We report the results of experiments with models of inductive (transformer type) SFCLs based on the ring-shaped bulk MgB2 prepared under high quasihydrostatic pressure (2 GPa) and by hot pressing technique (30 MPa). It was shown that the SFCLs meet the main requirements to fault current limiters: they possess low impedance in the nominal regime of the protected circuit and can fast increase their impedance limiting both the transient and the steady-state fault currents. The study of quenching currents of MgB2 rings (SFCL activation current) and AC losses in the rings shows that the quenching current density and critical current density determined from AC losses can be 10-20 times less than the critical current determined from the magnetization experiments.

Soft-Fault Detection Technologies Developed for Electrical Power Systems

NASA Technical Reports Server (NTRS)

Button, Robert M.

2004-01-01

The NASA Glenn Research Center, partner universities, and defense contractors are working to develop intelligent power management and distribution (PMAD) technologies for future spacecraft and launch vehicles. The goals are to provide higher performance (efficiency, transient response, and stability), higher fault tolerance, and higher reliability through the application of digital control and communication technologies. It is also expected that these technologies will eventually reduce the design, development, manufacturing, and integration costs for large, electrical power systems for space vehicles. The main focus of this research has been to incorporate digital control, communications, and intelligent algorithms into power electronic devices such as direct-current to direct-current (dc-dc) converters and protective switchgear. These technologies, in turn, will enable revolutionary changes in the way electrical power systems are designed, developed, configured, and integrated in aerospace vehicles and satellites. Initial successes in integrating modern, digital controllers have proven that transient response performance can be improved using advanced nonlinear control algorithms. One technology being developed includes the detection of "soft faults," those not typically covered by current systems in use today. Soft faults include arcing faults, corona discharge faults, and undetected leakage currents. Using digital control and advanced signal analysis algorithms, we have shown that it is possible to reliably detect arcing faults in high-voltage dc power distribution systems (see the preceding photograph). Another research effort has shown that low-level leakage faults and cable degradation can be detected by analyzing power system parameters over time. This additional fault detection capability will result in higher reliability for long-lived power systems such as reusable launch vehicles and space exploration missions.

Distributed Fault Detection Based on Credibility and Cooperation for WSNs in Smart Grids.

PubMed

Shao, Sujie; Guo, Shaoyong; Qiu, Xuesong

2017-04-28

Due to the increasingly important role in monitoring and data collection that sensors play, accurate and timely fault detection is a key issue for wireless sensor networks (WSNs) in smart grids. This paper presents a novel distributed fault detection mechanism for WSNs based on credibility and cooperation. Firstly, a reasonable credibility model of a sensor is established to identify any suspicious status of the sensor according to its own temporal data correlation. Based on the credibility model, the suspicious sensor is then chosen to launch fault diagnosis requests. Secondly, the sending time of fault diagnosis request is discussed to avoid the transmission overhead brought about by unnecessary diagnosis requests and improve the efficiency of fault detection based on neighbor cooperation. The diagnosis reply of a neighbor sensor is analyzed according to its own status. Finally, to further improve the accuracy of fault detection, the diagnosis results of neighbors are divided into several classifications to judge the fault status of the sensors which launch the fault diagnosis requests. Simulation results show that this novel mechanism can achieve high fault detection ratio with a small number of fault diagnoses and low data congestion probability.

Distributed Fault Detection Based on Credibility and Cooperation for WSNs in Smart Grids

PubMed Central

Shao, Sujie; Guo, Shaoyong; Qiu, Xuesong

2017-01-01

Due to the increasingly important role in monitoring and data collection that sensors play, accurate and timely fault detection is a key issue for wireless sensor networks (WSNs) in smart grids. This paper presents a novel distributed fault detection mechanism for WSNs based on credibility and cooperation. Firstly, a reasonable credibility model of a sensor is established to identify any suspicious status of the sensor according to its own temporal data correlation. Based on the credibility model, the suspicious sensor is then chosen to launch fault diagnosis requests. Secondly, the sending time of fault diagnosis request is discussed to avoid the transmission overhead brought about by unnecessary diagnosis requests and improve the efficiency of fault detection based on neighbor cooperation. The diagnosis reply of a neighbor sensor is analyzed according to its own status. Finally, to further improve the accuracy of fault detection, the diagnosis results of neighbors are divided into several classifications to judge the fault status of the sensors which launch the fault diagnosis requests. Simulation results show that this novel mechanism can achieve high fault detection ratio with a small number of fault diagnoses and low data congestion probability. PMID:28452925

Multiple resolution chirp reflectometry for fault localization and diagnosis in a high voltage cable in automotive electronics

NASA Astrophysics Data System (ADS)

Chang, Seung Jin; Lee, Chun Ku; Shin, Yong-June; Park, Jin Bae

2016-12-01

A multiple chirp reflectometry system with a fault estimation process is proposed to obtain multiple resolution and to measure the degree of fault in a target cable. A multiple resolution algorithm has the ability to localize faults, regardless of fault location. The time delay information, which is derived from the normalized cross-correlation between the incident signal and bandpass filtered reflected signals, is converted to a fault location and cable length. The in-phase and quadrature components are obtained by lowpass filtering of the mixed signal of the incident signal and the reflected signal. Based on in-phase and quadrature components, the reflection coefficient is estimated by the proposed fault estimation process including the mixing and filtering procedure. Also, the measurement uncertainty for this experiment is analyzed according to the Guide to the Expression of Uncertainty in Measurement. To verify the performance of the proposed method, we conduct comparative experiments to detect and measure faults under different conditions. Considering the installation environment of the high voltage cable used in an actual vehicle, target cable length and fault position are designed. To simulate the degree of fault, the variety of termination impedance (10 Ω , 30 Ω , 50 Ω , and 1 \\text{k} Ω ) are used and estimated by the proposed method in this experiment. The proposed method demonstrates advantages in that it has multiple resolution to overcome the blind spot problem, and can assess the state of the fault.

Analysis of different device-based intrathoracic impedance vectors for detection of heart failure events (from the Detect Fluid Early from Intrathoracic Impedance Monitoring study).

PubMed

Heist, E Kevin; Herre, John M; Binkley, Philip F; Van Bakel, Adrian B; Porterfield, James G; Porterfield, Linda M; Qu, Fujian; Turkel, Melanie; Pavri, Behzad B

2014-10-15

Detect Fluid Early from Intrathoracic Impedance Monitoring (DEFEAT-PE) is a prospective, multicenter study of multiple intrathoracic impedance vectors to detect pulmonary congestion (PC) events. Changes in intrathoracic impedance between the right ventricular (RV) coil and device can (RVcoil→Can) of implantable cardioverter-defibrillators (ICDs) and cardiac resynchronization therapy ICDs (CRT-Ds) are used clinically for the detection of PC events, but other impedance vectors and algorithms have not been studied prospectively. An initial 75-patient study was used to derive optimal impedance vectors to detect PC events, with 2 vector combinations selected for prospective analysis in DEFEAT-PE (ICD vectors: RVring→Can + RVcoil→Can, detection threshold 13 days; CRT-D vectors: left ventricular ring→Can + RVcoil→Can, detection threshold 14 days). Impedance changes were considered true positive if detected <30 days before an adjudicated PC event. One hundred sixty-two patients were enrolled (80 with ICDs and 82 with CRT-Ds), all with ≥1 previous PC event. One hundred forty-four patients provided study data, with 214 patient-years of follow-up and 139 PC events. Sensitivity for PC events of the prespecified algorithms was as follows: ICD: sensitivity 32.3%, false-positive rate 1.28 per patient-year; CRT-D: sensitivity 32.4%, false-positive rate 1.66 per patient-year. An alternative algorithm, ultimately approved by the US Food and Drug Administration (RVring→Can + RVcoil→Can, detection threshold 14 days), resulted in (for all patients) sensitivity of 21.6% and a false-positive rate of 0.9 per patient-year. The CRT-D thoracic impedance vector algorithm selected in the derivation study was not superior to the ICD algorithm RVring→Can + RVcoil→Can when studied prospectively. In conclusion, to achieve an acceptably low false-positive rate, the intrathoracic impedance algorithms studied in DEFEAT-PE resulted in low sensitivity for the prediction of heart

Tunable architecture for aircraft fault detection

NASA Technical Reports Server (NTRS)

Ganguli, Subhabrata (Inventor); Papageorgiou, George (Inventor); Glavaski-Radovanovic, Sonja (Inventor)

2012-01-01

A method for detecting faults in an aircraft is disclosed. The method involves predicting at least one state of the aircraft and tuning at least one threshold value to tightly upper bound the size of a mismatch between the at least one predicted state and a corresponding actual state of the non-faulted aircraft. If the mismatch between the at least one predicted state and the corresponding actual state is greater than or equal to the at least one threshold value, the method indicates that at least one fault has been detected.

Arc burst pattern analysis fault detection system

NASA Technical Reports Server (NTRS)

Russell, B. Don (Inventor); Aucoin, B. Michael (Inventor); Benner, Carl L. (Inventor)

1997-01-01

A method and apparatus are provided for detecting an arcing fault on a power line carrying a load current. Parameters indicative of power flow and possible fault events on the line, such as voltage and load current, are monitored and analyzed for an arc burst pattern exhibited by arcing faults in a power system. These arcing faults are detected by identifying bursts of each half-cycle of the fundamental current. Bursts occurring at or near a voltage peak indicate arcing on that phase. Once a faulted phase line is identified, a comparison of the current and voltage reveals whether the fault is located in a downstream direction of power flow toward customers, or upstream toward a generation station. If the fault is located downstream, the line is de-energized, and if located upstream, the line may remain energized to prevent unnecessary power outages.

Randomness fault detection system

NASA Technical Reports Server (NTRS)

Russell, B. Don (Inventor); Aucoin, B. Michael (Inventor); Benner, Carl L. (Inventor)

1996-01-01

A method and apparatus are provided for detecting a fault on a power line carrying a line parameter such as a load current. The apparatus monitors and analyzes the load current to obtain an energy value. The energy value is compared to a threshold value stored in a buffer. If the energy value is greater than the threshold value a counter is incremented. If the energy value is greater than a high value threshold or less than a low value threshold then a second counter is incremented. If the difference between two subsequent energy values is greater than a constant then a third counter is incremented. A fault signal is issued if the counter is greater than a counter limit value and either the second counter is greater than a second limit value or the third counter is greater than a third limit value.

Detection of CMOS bridging faults using minimal stuck-at fault test sets

NASA Technical Reports Server (NTRS)

Ijaz, Nabeel; Frenzel, James F.

1993-01-01

The performance of minimal stuck-at fault test sets at detecting bridging faults are evaluated. New functional models of circuit primitives are presented which allow accurate representation of bridging faults under switch-level simulation. The effectiveness of the patterns is evaluated using both voltage and current testing.

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.

High resolution seismics methods in application to fault zone detection

NASA Astrophysics Data System (ADS)

Matula, Rafal; Czaja, Klaudia; Mahmod, Adam Ahmed

2014-05-01

Surveys were carried out along border line between Outer Carpathians, Inner Carpathians and Pieniny Klippen Belt. Main point of interest was imaging transition zone structured by para-conglomerates, sandstone and clays lenses, crossing in near neighbourhood of Stare Bystre, village in the southern part of Poland. Actually geological works states existence of two hypothetical faults, first at the direction NE-SW and second NNW-SSE. Main aim of geological and geophysical investigation was to prove that mentioned fault has a system of smaller discontinuities connected with previous main fault activity. Para-conglomerate exposures, which is localized close to discussed fault is cut by visible system of cracks. That fact provide geological evidences that this system could be the effect of previous fault activity so in other words, it has a continuation up to main discontinuities. What is more part of the same formation para-conglomerates is covered by Neogen river sediments, so non-direct detection methods of cracks azimuth must be applied. Geophysical investigation was located near mentioned exposure and conducted in 3-D variant. Measurements were extremely focused on determining any changes of elevation buried para-conglomerates and velocity variation inside studied sediments. Seismic methods such as refraction and refraction tomography were used to imaging bedrock. Surveys were carried out in non typical acquisition, azimuthal schema. During field works 24- channels seismograph and 4 Hz, 10 Hz and 100 Hz geophones were used. Hypothetical discontinuities were estimated after analysing seismic records and expressed by velocity variation in bedding rocks and additionally evaluated changes in its elevation. Furthermore, in this study attempt of use refraction wave attributes related to loosing rock - para-conglomerates continuity were exposed. The presentation of geophysical data had a volumetric character what was easier to interpret and better related to assumptions

Creating an automated chiller fault detection and diagnostics tool using a data fault library.

PubMed

Bailey, Margaret B; Kreider, Jan F

2003-07-01

Reliable, automated detection and diagnosis of abnormal behavior within vapor compression refrigeration cycle (VCRC) equipment is extremely desirable for equipment owners and operators. The specific type of VCRC equipment studied in this paper is a 70-ton helical rotary, air-cooled chiller. The fault detection and diagnostic (FDD) tool developed as part of this research analyzes chiller operating data and detects faults through recognizing trends or patterns existing within the data. The FDD method incorporates a neural network (NN) classifier to infer the current state given a vector of observables. Therefore the FDD method relies upon the availability of normal and fault empirical data for training purposes and therefore a fault library of empirical data is assembled. This paper presents procedures for conducting sophisticated fault experiments on chillers that simulate air-cooled condenser, refrigerant, and oil related faults. The experimental processes described here are not well documented in literature and therefore will provide the interested reader with a useful guide. In addition, the authors provide evidence, based on both thermodynamics and empirical data analysis, that chiller performance is significantly degraded during fault operation. The chiller's performance degradation is successfully detected and classified by the NN FDD classifier as discussed in the paper's final section.

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

Methods based on chi-squared analysis are presented for detecting system and individual-port failures in the high-angle-of-attack flush airdata sensing system on the NASA F-18 High Alpha Research Vehicle. The HI-FADS hardware is introduced, and the aerodynamic model describes measured pressure in terms of dynamic pressure, angle of attack, angle of sideslip, and static pressure. Chi-squared analysis is described in the presentation of the concept for failure detection and fault management which includes nominal, iteration, and fault-management modes. A matrix of pressure orifices arranged in concentric circles on the nose of the aircraft indicate the parameters which are applied to the regression algorithms. The sensing techniques are applied to the F-18 flight data, and two examples are given of the computed angle-of-attack time histories. The failure-detection and fault-management techniques permit the matrix to be multiply redundant, and the chi-squared analysis is shown to be useful in the detection of failures.

Event-Triggered Fault Detection of Nonlinear Networked Systems.

PubMed

Li, Hongyi; Chen, Ziran; Wu, Ligang; Lam, Hak-Keung; Du, Haiping

2017-04-01

This paper investigates the problem of fault detection for nonlinear discrete-time networked systems under an event-triggered scheme. A polynomial fuzzy fault detection filter is designed to generate a residual signal and detect faults in the system. A novel polynomial event-triggered scheme is proposed to determine the transmission of the signal. A fault detection filter is designed to guarantee that the residual system is asymptotically stable and satisfies the desired performance. Polynomial approximated membership functions obtained by Taylor series are employed for filtering analysis. Furthermore, sufficient conditions are represented in terms of sum of squares (SOSs) and can be solved by SOS tools in MATLAB environment. A numerical example is provided to demonstrate the effectiveness of the proposed results.

Detection of Rooftop Cooling Unit Faults Based on Electrical Measurements

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

Armstrong, Peter R.; Laughman, C R.; Leeb, S B.

Non-intrusive load monitoring (NILM) is accomplished by sampling voltage and current at high rates and reducing the resulting start transients or harmonic contents to concise ''signatures''. Changes in these signatures can be used to detect, and in many cases directly diagnose, equipment and component faults associated with roof-top cooling units. Use of the NILM for fault detection and diagnosis (FDD) is important because (1) it complements other FDD schemes that are based on thermo-fluid sensors and analyses and (2) it is minimally intrusive (one measuring point in the relatively protected confines of the control panel) and therefore inherently reliable. Thismore » paper describes changes in the power signatures of fans and compressors that were found, experimentally and theoretically, to be useful for fault detection.« less

PV Systems Reliability Final Technical Report: Ground Fault Detection

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

Lavrova, Olga; Flicker, Jack David; Johnson, Jay

We have examined ground faults in PhotoVoltaic (PV) arrays and the efficacy of fuse, current detection (RCD), current sense monitoring/relays (CSM), isolation/insulation (Riso) monitoring, and Ground Fault Detection and Isolation (GFID) using simulations based on a Simulation Program with Integrated Circuit Emphasis SPICE ground fault circuit model, experimental ground faults installed on real arrays, and theoretical equations.

Optimal Sensor Allocation for Fault Detection and Isolation

NASA Technical Reports Server (NTRS)

Azam, Mohammad; Pattipati, Krishna; Patterson-Hine, Ann

2004-01-01

Automatic fault diagnostic schemes rely on various types of sensors (e.g., temperature, pressure, vibration, etc) to measure the system parameters. Efficacy of a diagnostic scheme is largely dependent on the amount and quality of information available from these sensors. The reliability of sensors, as well as the weight, volume, power, and cost constraints, often makes it impractical to monitor a large number of system parameters. An optimized sensor allocation that maximizes the fault diagnosibility, subject to specified weight, volume, power, and cost constraints is required. Use of optimal sensor allocation strategies during the design phase can ensure better diagnostics at a reduced cost for a system incorporating a high degree of built-in testing. In this paper, we propose an approach that employs multiple fault diagnosis (MFD) and optimization techniques for optimal sensor placement for fault detection and isolation (FDI) in complex systems. Keywords: sensor allocation, multiple fault diagnosis, Lagrangian relaxation, approximate belief revision, multidimensional knapsack problem.

Acoustic Detection of Faults and Degradation in a High-Bypass Turbofan Engine during VIPR Phase III Testing

NASA Technical Reports Server (NTRS)

Boyle, Devin K.

2017-01-01

The Vehicle Integrated Propulsion Research (VIPR) Phase III project was executed at Edwards Air Force Base, California, by the National Aeronautics and Space Administration and several industry, academic, and government partners in the summer of 2015. One of the research objectives was to use external radial acoustic microphone arrays to detect changes in the noise characteristics produced by the research engine during volcanic ash ingestion and seeded fault insertion scenarios involving bleed air valves. Preliminary results indicate the successful acoustic detection of suspected degradation as a result of cumulative exposure to volcanic ash. This detection is shown through progressive changes, particularly in the high-frequency content, as a function of exposure to greater cumulative quantities of ash. Additionally, detection of the simulated failure of the 14th stage stability bleed valve and, to a lesser extent, the station 2.5 stability bleed valve, to their fully-open fail-safe positions was achieved by means of spectral comparisons between nominal (normal valve operation) and seeded fault scenarios.

Latest Progress of Fault Detection and Localization in Complex Electrical Engineering

NASA Astrophysics Data System (ADS)

Zhao, Zheng; Wang, Can; Zhang, Yagang; Sun, Yi

2014-01-01

In the researches of complex electrical engineering, efficient fault detection and localization schemes are essential to quickly detect and locate faults so that appropriate and timely corrective mitigating and maintenance actions can be taken. In this paper, under the current measurement precision of PMU, we will put forward a new type of fault detection and localization technology based on fault factor feature extraction. Lots of simulating experiments indicate that, although there are disturbances of white Gaussian stochastic noise, based on fault factor feature extraction principal, the fault detection and localization results are still accurate and reliable, which also identifies that the fault detection and localization technology has strong anti-interference ability and great redundancy.

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,

A Kalman Filter Based Technique for Stator Turn-Fault Detection of the Induction Motors

NASA Astrophysics Data System (ADS)

Ghanbari, Teymoor; Samet, Haidar

2017-11-01

Monitoring of the Induction Motors (IMs) through stator current for different faults diagnosis has considerable economic and technical advantages in comparison with the other techniques in this content. Among different faults of an IM, stator and bearing faults are more probable types, which can be detected by analyzing signatures of the stator currents. One of the most reliable indicators for fault detection of IMs is lower sidebands of power frequency in the stator currents. This paper deals with a novel simple technique for detecting stator turn-fault of the IMs. Frequencies of the lower sidebands are determined using the motor specifications and their amplitudes are estimated by a Kalman Filter (KF). Instantaneous Total Harmonic Distortion (ITHD) of these harmonics is calculated. Since variation of the ITHD for the three-phase currents is considerable in case of stator turn-fault, the fault can be detected using this criterion, confidently. Different simulation results verify high performance of the proposed method. The performance of the method is also confirmed using some experiments.

Rapid and highly sensitive detection of Enterovirus 71 by using nanogold-enhanced electrochemical impedance spectroscopy

NASA Astrophysics Data System (ADS)

Li, Hsing-Yuan; Tseng, Shing-Hua; Cheng, Tsai-Mu; Chu, Hsueh-Liang; Lu, Yu-Ning; Wang, Fang-Yu; Tsai, Li-Yun; Shieh, Juo-Yu; Yang, Jyh-Yuan; Juan, Chien-Chang; Tu, Lung-Chen; Chang, Chia-Ching

2013-07-01

Enterovirus 71 (EV71) infection is an emerging infectious disease causing neurological complications and/or death within two to three days after the development of fever and rash. A low viral titre in clinical specimens makes the detection of EV71 difficult. Conventional approaches for detecting EV71 are time consuming, poorly sensitive, or complicated, and cannot be used effectively for clinical diagnosis. Furthermore, EV71 and Coxsackie virus A16 (CA16) may cross react in conventional assays. Therefore, a rapid, highly sensitive, specific, and user-friendly test is needed. We developed an EV71-specific nanogold-modified working electrode for electrochemical impedance spectroscopy in the detection of EV71. Our results show that EV71 can be distinguished from CA16, Herpes simplex virus, and lysozyme, with the modified nanogold electrode being able to detect EV71 in concentrations as low as 1 copy number/50 μl reaction volume, and the duration between sample preparation and detection being 11 min. This detection platform may have the potential for use in point-of-care diagnostics.

Latent component-based gear tooth fault detection filter using advanced parametric modeling

NASA Astrophysics Data System (ADS)

Ettefagh, M. M.; Sadeghi, M. H.; Rezaee, M.; Chitsaz, S.

2009-10-01

In this paper, a new parametric model-based filter is proposed for gear tooth fault detection. The designing of the filter consists of identifying the most proper latent component (LC) of the undamaged gearbox signal by analyzing the instant modules (IMs) and instant frequencies (IFs) and then using the component with lowest IM as the proposed filter output for detecting fault of the gearbox. The filter parameters are estimated by using the LC theory in which an advanced parametric modeling method has been implemented. The proposed method is applied on the signals, extracted from simulated gearbox for detection of the simulated gear faults. In addition, the method is used for quality inspection of the produced Nissan-Junior vehicle gearbox by gear profile error detection in an industrial test bed. For evaluation purpose, the proposed method is compared with the previous parametric TAR/AR-based filters in which the parametric model residual is considered as the filter output and also Yule-Walker and Kalman filter are implemented for estimating the parameters. The results confirm the high performance of the new proposed fault detection method.

[Research on Detection Method with Wearable Respiration Device Based on the Theory of Bio-impedance].

PubMed

Liu, Guangda; Wang, Xianzhong; Cai, Jing; Wang, Wei; Zha, Yutong

2016-12-01

Considering the importance of the human respiratory signal detection and based on the Cole-Cole bio-impedance model,we developed a wearable device for detecting human respiratory signal.The device can be used to analyze the impedance characteristics of human body at different frequencies based on the bio-impedance theory.The device is also based on the method of proportion measurement to design a high signal to noise ratio(SNR)circuit to get human respiratory signal.In order to obtain the waveform of the respiratory signal and the value of the respiration rate,we used the techniques of discrete Fourier transform(DFT)and dynamic difference threshold peak detection.Experiments showed that this system was valid,and we could see that it could accurately detect the waveform of respiration and the detection accuracy rate of respiratory wave peak point detection results was over 98%.So it can meet the needs of the actual breath test.

Induction machine bearing faults detection based on a multi-dimensional MUSIC algorithm and maximum likelihood estimation.

PubMed

Elbouchikhi, Elhoussin; Choqueuse, Vincent; Benbouzid, Mohamed

2016-07-01

Condition monitoring of electric drives is of paramount importance since it contributes to enhance the system reliability and availability. Moreover, the knowledge about the fault mode behavior is extremely important in order to improve system protection and fault-tolerant control. Fault detection and diagnosis in squirrel cage induction machines based on motor current signature analysis (MCSA) has been widely investigated. Several high resolution spectral estimation techniques have been developed and used to detect induction machine abnormal operating conditions. This paper focuses on the application of MCSA for the detection of abnormal mechanical conditions that may lead to induction machines failure. In fact, this paper is devoted to the detection of single-point defects in bearings based on parametric spectral estimation. A multi-dimensional MUSIC (MD MUSIC) algorithm has been developed for bearing faults detection based on bearing faults characteristic frequencies. This method has been used to estimate the fundamental frequency and the fault related frequency. Then, an amplitude estimator of the fault characteristic frequencies has been proposed and fault indicator has been derived for fault severity measurement. The proposed bearing faults detection approach is assessed using simulated stator currents data, issued from a coupled electromagnetic circuits approach for air-gap eccentricity emulating bearing faults. Then, experimental data are used for validation purposes. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Fault detection of gearbox using time-frequency method

NASA Astrophysics Data System (ADS)

Widodo, A.; Satrijo, Dj.; Prahasto, T.; Haryanto, I.

2017-04-01

This research deals with fault detection and diagnosis of gearbox by using vibration signature. In this work, fault detection and diagnosis are approached by employing time-frequency method, and then the results are compared with cepstrum analysis. Experimental work has been conducted for data acquisition of vibration signal thru self-designed gearbox test rig. This test-rig is able to demonstrate normal and faulty gearbox i.e., wears and tooth breakage. Three accelerometers were used for vibration signal acquisition from gearbox, and optical tachometer was used for shaft rotation speed measurement. The results show that frequency domain analysis using fast-fourier transform was less sensitive to wears and tooth breakage condition. However, the method of short-time fourier transform was able to monitor the faults in gearbox. Wavelet Transform (WT) method also showed good performance in gearbox fault detection using vibration signal after employing time synchronous averaging (TSA).

Interdigitated microelectrode (IME) impedance sensor for the detection of viable Salmonella typhimurium.

PubMed

Yang, Liju; Li, Yanbin; Griffis, Carl L; Johnson, Michael G

2004-05-15

Interdigitated microelectrodes (IMEs) were used as impedance sensors for rapid detection of viable Salmonella typhimurium in a selective medium and milk samples. The impedance growth curves, impedance against bacterial growth time, were recorded at four frequencies (10Hz, 100Hz, 1kHz, and 10kHz) during the growth of S. typhimurium. The impedance did not change until the cell number reached 10(5)-10(6) CFUml(-1). The greatest change in impedance was observed at 10Hz. To better understand the mechanism of the IME impedance sensor, an equivalent electrical circuit, consisting of double layer capacitors, a dielectric capacitor, and a medium resistor, was introduced and used for interpreting the change in impedance during bacterial growth. Bacterial attachment to the electrode surface was observed with scanning electron microscopy, and it had effect on the impedance measurement. The detection time, t(D), defined as the time for the impedance to start change, was obtained from the impedance growth curve at 10Hz and had a linear relationship with the logarithmic value of the initial cell number of S. typhimurium in the medium and milk samples. The regression equations for the cell numbers between 4.8 and 5.4 x 10(5) CFUml(-1) were t(D) = -1.38 log N + 10.18 with R(2) = 0.99 in the pure medium and t(D) = -1.54 log N + 11.33 with R(2) = 0.98 in milk samples, respectively. The detection times for 4.8 and 5.4 x 10(5) CFUml(-1) initial cell numbers were 9.3 and 2.2 h, respectively, and the detection limit could be as low as 1 cell in a sample.

A high frequency electromagnetic impedance imaging system

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

Tseng, Hung-Wen; Lee, Ki Ha; Becker, Alex

2003-01-15

Non-invasive, high resolution geophysical mapping of the shallow subsurface is necessary for delineation of buried hazardous wastes, detecting unexploded ordinance, verifying and monitoring of containment or moisture contents, and other environmental applications. Electromagnetic (EM) techniques can be used for this purpose since electrical conductivity and dielectric permittivity are representative of the subsurface media. Measurements in the EM frequency band between 1 and 100 MHz are very important for such applications, because the induction number of many targets is small and the ability to determine the subsurface distribution of both electrical properties is required. Earlier workers were successful in developing systemsmore » for detecting anomalous areas, but quantitative interpretation of the data was difficult. Accurate measurements are necessary, but difficult to achieve for high-resolution imaging of the subsurface. We are developing a broadband non-invasive method for accurately mapping the electrical conductivity and dielectric permittivity of the shallow subsurface using an EM impedance approach similar to the MT exploration technique. Electric and magnetic sensors were tested to ensure that stray EM scattering is minimized and the quality of the data collected with the high-frequency impedance (HFI) system is good enough to allow high-resolution, multi-dimensional imaging of hidden targets. Additional efforts are being made to modify and further develop existing sensors and transmitters to improve the imaging capability and data acquisition efficiency.« less

Pseudo-fault signal assisted EMD for fault detection and isolation in rotating machines

NASA Astrophysics Data System (ADS)

Singh, Dheeraj Sharan; Zhao, Qing

2016-12-01

This paper presents a novel data driven technique for the detection and isolation of faults, which generate impacts in a rotating equipment. The technique is built upon the principles of empirical mode decomposition (EMD), envelope analysis and pseudo-fault signal for fault separation. Firstly, the most dominant intrinsic mode function (IMF) is identified using EMD of a raw signal, which contains all the necessary information about the faults. The envelope of this IMF is often modulated with multiple vibration sources and noise. A second level decomposition is performed by applying pseudo-fault signal (PFS) assisted EMD on the envelope. A pseudo-fault signal is constructed based on the known fault characteristic frequency of the particular machine. The objective of using external (pseudo-fault) signal is to isolate different fault frequencies, present in the envelope . The pseudo-fault signal serves dual purposes: (i) it solves the mode mixing problem inherent in EMD, (ii) it isolates and quantifies a particular fault frequency component. The proposed technique is suitable for real-time implementation, which has also been validated on simulated fault and experimental data corresponding to a bearing and a gear-box set-up, respectively.

Impedance Based Detection of Delamination in Composite Structures

NASA Astrophysics Data System (ADS)

Djemana, M.; Hrairi, M.

2017-03-01

Nowadays commercial and military aircrafts are increasingly using composite materials to take advantage of their excellent specific strength and stiffness properties but impacts on composites due to bird-strike, hail-storm cause barely visible impact damage (BVID) that underscores the need for robust structural health monitoring methods. Hence, damage identification in composite materials is a widely researched area that has to deal with problems coming from the anisotropic nature of composites and the fact that much of the damage occurs beneath the top surface of the laminate. This paper focuses on understanding self-sensing piezoelectric wafer active sensors (PWAS) to conduct electromechanical impedance (EMI) in glass fibre reinforced polymer composite to perform structural health monitoring. With the aid of a 3D ANSYS finite element model, an analysis of different techniques for the detection of position and size of a delamination in a composite structure using piezoelectric patches had been performed. The real part of the impedance is used because it is known to be more reactive to damage or changes in the structure’s integrity and less sensitive to ambient temperature changes compared to the imaginary part. Comparison with experimental results is presented to validate the FE results. The experimental setup utilizes as its main apparatus an impedance analyser HP4194 that reads the in-situ EMI of PWAS bonded to the monitored composite structure. A good match between experimental and numerical results has been observed for low and high frequencies. The analysis in this paper provides necessary basis for delamination detection in composite structures using EMI technique

Multiple incipient sensor faults diagnosis with application to high-speed railway traction devices.

PubMed

Wu, Yunkai; Jiang, Bin; Lu, Ningyun; Yang, Hao; Zhou, Yang

2017-03-01

This paper deals with the problem of incipient fault diagnosis for a class of Lipschitz nonlinear systems with sensor biases and explores further results of total measurable fault information residual (ToMFIR). Firstly, state and output transformations are introduced to transform the original system into two subsystems. The first subsystem is subject to system disturbances and free from sensor faults, while the second subsystem contains sensor faults but without any system disturbances. Sensor faults in the second subsystem are then formed as actuator faults by using a pseudo-actuator based approach. Since the effects of system disturbances on the residual are completely decoupled, multiple incipient sensor faults can be detected by constructing ToMFIR, and the fault detectability condition is then derived for discriminating the detectable incipient sensor faults. Further, a sliding-mode observers (SMOs) based fault isolation scheme is designed to guarantee accurate isolation of multiple sensor faults. Finally, simulation results conducted on a CRH2 high-speed railway traction device are given to demonstrate the effectiveness of the proposed approach. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

A novel end-to-end fault detection and localization protocol for wavelength-routed WDM networks

NASA Astrophysics Data System (ADS)

Zeng, Hongqing; Vukovic, Alex; Huang, Changcheng

2005-09-01

Recently the wavelength division multiplexing (WDM) networks are becoming prevalent for telecommunication networks. However, even a very short disruption of service caused by network faults may lead to high data loss in such networks due to the high date rates, increased wavelength numbers and density. Therefore, the network survivability is critical and has been intensively studied, where fault detection and localization is the vital part but has received disproportional attentions. In this paper we describe and analyze an end-to-end lightpath fault detection scheme in data plane with the fault notification in control plane. The endeavor is focused on reducing the fault detection time. In this protocol, the source node of each lightpath keeps sending hello packets to the destination node exactly following the path for data traffic. The destination node generates an alarm once a certain number of consecutive hello packets are missed within a given time period. Then the network management unit collects all alarms and locates the faulty source based on the network topology, as well as sends fault notification messages via control plane to either the source node or all upstream nodes along the lightpath. The performance evaluation shows such a protocol can achieve fast fault detection, and at the same time, the overhead brought to the user data by hello packets is negligible.

Impedance Biosensing to detect food allergens, endocrine disrupting chemicals, and food pathogens

NASA Astrophysics Data System (ADS)

Radhakrishnan, Rajeswaran

Electrochemical impedance biosensors can be viewed as an AC electroanalytical method for the analyte detection in the fields of biomedicine, environmental monitoring, and food and agriculture, amongst others. The most common format for AC impedance biosensing involves surface immobilization of an antibody, receptor protein, DNA strand, or other species capable of bio-recognition, and AC impedance detection of the binding event. Technological application of AC impedance biosensors has been hindered by several obstacles, including the more complex circuitry required for AC relative to DC electrochemistry, chemical and physical interference arising from non-specific adsorption, and the stability and reproducibility of protein immobilization. One focus of these PhD studies is on methods to reduce or compensate for non-specific adsorption, including sample dilution, site blocking with BSA, and the use of control electrodes onto which reference antibodies are immobilized. Examples that will be presented include impedance detection of food pathogens, such as Listeria monocytogenes, using a mouse monoclonal antibody immobilized onto an Au electrode. This yields detection limits of 5 CFU/ml and 4 CFU/ml for ideal solutions and filtered tomato extract, respectively. Control experiments with an Au electrode onto which a mouse monoclonal antibody to GAPDH is immobilized demonstrate that non-specific adsorption is insignificant for the system and methodology studied here. Control experiments with Salmonella enterica demonstrate no cross-reactivity to this food pathogen. In addition, Detection of two endocrine-disrupting chemicals (EDC), norfluoxetine and BDE-47, is reported here by impedance biosensing, with a detection limit of 8.5 and 1.3 ng/ml for norfluoxetine and BDE-47, respectively. Additional research has focused on alternative substrates and linker chemistries for protein immobilization, including the use of degenerate (highly doped) Si and bidendate thiol monolayer

An integrated microfluidic analysis microsystems with bacterial capture enrichment and in-situ impedance detection

NASA Astrophysics Data System (ADS)

Liu, Hai-Tao; Wen, Zhi-Yu; Xu, Yi; Shang, Zheng-Guo; Peng, Jin-Lan; Tian, Peng

2017-09-01

In this paper, an integrated microfluidic analysis microsystems with bacterial capture enrichment and in-situ impedance detection was purposed based on microfluidic chips dielectrophoresis technique and electrochemical impedance detection principle. The microsystems include microfluidic chip, main control module, and drive and control module, and signal detection and processing modulet and result display unit. The main control module produce the work sequence of impedance detection system parts and achieve data communication functions, the drive and control circuit generate AC signal which amplitude and frequency adjustable, and it was applied on the foodborne pathogens impedance analysis microsystems to realize the capture enrichment and impedance detection. The signal detection and processing circuit translate the current signal into impendence of bacteria, and transfer to computer, the last detection result is displayed on the computer. The experiment sample was prepared by adding Escherichia coli standard sample into chicken sample solution, and the samples were tested on the dielectrophoresis chip capture enrichment and in-situ impedance detection microsystems with micro-array electrode microfluidic chips. The experiments show that the Escherichia coli detection limit of microsystems is 5 × 104 CFU/mL and the detection time is within 6 min in the optimization of voltage detection 10 V and detection frequency 500 KHz operating conditions. The integrated microfluidic analysis microsystems laid the solid foundation for rapid real-time in-situ detection of bacteria.

Generic, scalable and decentralized fault detection for robot swarms.

PubMed

Tarapore, Danesh; Christensen, Anders Lyhne; Timmis, Jon

2017-01-01

Robot swarms are large-scale multirobot systems with decentralized control which means that each robot acts based only on local perception and on local coordination with neighboring robots. The decentralized approach to control confers number of potential benefits. In particular, inherent scalability and robustness are often highlighted as key distinguishing features of robot swarms compared with systems that rely on traditional approaches to multirobot coordination. It has, however, been shown that swarm robotics systems are not always fault tolerant. To realize the robustness potential of robot swarms, it is thus essential to give systems the capacity to actively detect and accommodate faults. In this paper, we present a generic fault-detection system for robot swarms. We show how robots with limited and imperfect sensing capabilities are able to observe and classify the behavior of one another. In order to achieve this, the underlying classifier is an immune system-inspired algorithm that learns to distinguish between normal behavior and abnormal behavior online. Through a series of experiments, we systematically assess the performance of our approach in a detailed simulation environment. In particular, we analyze our system's capacity to correctly detect robots with faults, false positive rates, performance in a foraging task in which each robot exhibits a composite behavior, and performance under perturbations of the task environment. Results show that our generic fault-detection system is robust, that it is able to detect faults in a timely manner, and that it achieves a low false positive rate. The developed fault-detection system has the potential to enable long-term autonomy for robust multirobot systems, thus increasing the usefulness of robots for a diverse repertoire of upcoming applications in the area of distributed intelligent automation.

Generic, scalable and decentralized fault detection for robot swarms

PubMed Central

Christensen, Anders Lyhne; Timmis, Jon

2017-01-01

Robot swarms are large-scale multirobot systems with decentralized control which means that each robot acts based only on local perception and on local coordination with neighboring robots. The decentralized approach to control confers number of potential benefits. In particular, inherent scalability and robustness are often highlighted as key distinguishing features of robot swarms compared with systems that rely on traditional approaches to multirobot coordination. It has, however, been shown that swarm robotics systems are not always fault tolerant. To realize the robustness potential of robot swarms, it is thus essential to give systems the capacity to actively detect and accommodate faults. In this paper, we present a generic fault-detection system for robot swarms. We show how robots with limited and imperfect sensing capabilities are able to observe and classify the behavior of one another. In order to achieve this, the underlying classifier is an immune system-inspired algorithm that learns to distinguish between normal behavior and abnormal behavior online. Through a series of experiments, we systematically assess the performance of our approach in a detailed simulation environment. In particular, we analyze our system’s capacity to correctly detect robots with faults, false positive rates, performance in a foraging task in which each robot exhibits a composite behavior, and performance under perturbations of the task environment. Results show that our generic fault-detection system is robust, that it is able to detect faults in a timely manner, and that it achieves a low false positive rate. The developed fault-detection system has the potential to enable long-term autonomy for robust multirobot systems, thus increasing the usefulness of robots for a diverse repertoire of upcoming applications in the area of distributed intelligent automation. PMID:28806756

Development of a morphological convolution operator for bearing fault detection

NASA Astrophysics Data System (ADS)

Li, Yifan; Liang, Xihui; Liu, Weiwei; Wang, Yan

2018-05-01

This paper presents a novel signal processing scheme, namely morphological convolution operator (MCO) lifted morphological undecimated wavelet (MUDW), for rolling element bearing fault detection. In this scheme, a MCO is first designed to fully utilize the advantage of the closing & opening gradient operator and the closing-opening & opening-closing gradient operator for feature extraction as well as the merit of excellent denoising characteristics of the convolution operator. The MCO is then introduced into MUDW for the purpose of improving the fault detection ability of the reported MUDWs. Experimental vibration signals collected from a train wheelset test rig and the bearing data center of Case Western Reserve University are employed to evaluate the effectiveness of the proposed MCO lifted MUDW on fault detection of rolling element bearings. The results show that the proposed approach has a superior performance in extracting fault features of defective rolling element bearings. In addition, comparisons are performed between two reported MUDWs and the proposed MCO lifted MUDW. The MCO lifted MUDW outperforms both of them in detection of outer race faults and inner race faults of rolling element bearings.

Optimization of Second Fault Detection Thresholds to Maximize Mission POS

NASA Technical Reports Server (NTRS)

Anzalone, Evan

2018-01-01

In order to support manned spaceflight safety requirements, the Space Launch System (SLS) has defined program-level requirements for key systems to ensure successful operation under single fault conditions. To accommodate this with regards to Navigation, the SLS utilizes an internally redundant Inertial Navigation System (INS) with built-in capability to detect, isolate, and recover from first failure conditions and still maintain adherence to performance requirements. The unit utilizes multiple hardware- and software-level techniques to enable detection, isolation, and recovery from these events in terms of its built-in Fault Detection, Isolation, and Recovery (FDIR) algorithms. Successful operation is defined in terms of sufficient navigation accuracy at insertion while operating under worst case single sensor outages (gyroscope and accelerometer faults at launch). In addition to first fault detection and recovery, the SLS program has also levied requirements relating to the capability of the INS to detect a second fault, tracking any unacceptable uncertainty in knowledge of the vehicle's state. This detection functionality is required in order to feed abort analysis and ensure crew safety. Increases in navigation state error and sensor faults can drive the vehicle outside of its operational as-designed environments and outside of its performance envelope causing loss of mission, or worse, loss of crew. The criteria for operation under second faults allows for a larger set of achievable missions in terms of potential fault conditions, due to the INS operating at the edge of its capability. As this performance is defined and controlled at the vehicle level, it allows for the use of system level margins to increase probability of mission success on the operational edges of the design space. Due to the implications of the vehicle response to abort conditions (such as a potentially failed INS), it is important to consider a wide range of failure scenarios in terms of

Botulinum neurotoxin serotypes detected by electrochemical impedance spectroscopy.

PubMed

Savage, Alison C; Buckley, Nicholas; Halliwell, Jennifer; Gwenin, Christopher

2015-05-06

Botulinum neurotoxin is one of the deadliest biological toxins known to mankind and is able to cause the debilitating disease botulism. The rapid detection of the different serotypes of botulinum neurotoxin is essential for both diagnosis of botulism and identifying the presence of toxin in potential cases of terrorism and food contamination. The modes of action of botulinum neurotoxins are well-established in literature and differ for each serotype. The toxins are known to specifically cleave portions of the SNARE proteins SNAP-25 or VAMP; an interaction that can be monitored by electrochemical impedance spectroscopy. This study presents a SNAP-25 and a VAMP biosensors for detecting the activity of five botulinum neurotoxin serotypes (A-E) using electrochemical impedance spectroscopy. The biosensors are able to detect concentrations of toxins as low as 25 fg/mL, in a short time-frame compared with the current standard methods of detection. Both biosensors show greater specificity for their compatible serotypes compared with incompatible serotypes and denatured toxins.

Botulinum Neurotoxin Serotypes Detected by Electrochemical Impedance Spectroscopy

PubMed Central

Savage, Alison C.; Buckley, Nicholas; Halliwell, Jennifer; Gwenin, Christopher

2015-01-01

Botulinum neurotoxin is one of the deadliest biological toxins known to mankind and is able to cause the debilitating disease botulism. The rapid detection of the different serotypes of botulinum neurotoxin is essential for both diagnosis of botulism and identifying the presence of toxin in potential cases of terrorism and food contamination. The modes of action of botulinum neurotoxins are well-established in literature and differ for each serotype. The toxins are known to specifically cleave portions of the SNARE proteins SNAP-25 or VAMP; an interaction that can be monitored by electrochemical impedance spectroscopy. This study presents a SNAP-25 and a VAMP biosensors for detecting the activity of five botulinum neurotoxin serotypes (A–E) using electrochemical impedance spectroscopy. The biosensors are able to detect concentrations of toxins as low as 25 fg/mL, in a short time-frame compared with the current standard methods of detection. Both biosensors show greater specificity for their compatible serotypes compared with incompatible serotypes and denatured toxins. PMID:25954998

Dielectrophoresis and dielectrophoretic impedance detection of adenovirus and rotavirus

NASA Astrophysics Data System (ADS)

Nakano, Michihiko; Ding, Zhenhao; Suehiro, Junya

2016-01-01

The aim of this study is the electrical detection of pathogenic viruses, namely, adenovirus and rotavirus, using dielectrophoretic impedance measurement (DEPIM). DEPIM consists of two simultaneous processes: dielectrophoretic trapping of the target and measurement of the impedance change and increase in conductance with the number of trapped targets. This is the first study of applying DEPIM, which was originally developed to detect bacteria suspended in aqueous solutions, to virus detection. The dielectric properties of the viruses were also investigated in terms of their dielectrophoretic behavior. Although their estimated dielectric properties were different from those of bacteria, the trapped viruses increased the conductance of the microelectrode in a manner similar to that in bacteria detection. We demonstrated the electrical detection of viruses within 60 s at concentrations as low as 70 ng/ml for adenovirus and 50 ng/ml for rotavirus.

Robust fault detection of turbofan engines subject to adaptive controllers via a Total Measurable Fault Information Residual (ToMFIR) technique.

PubMed

Chen, Wen; Chowdhury, Fahmida N; Djuric, Ana; Yeh, Chih-Ping

2014-09-01

This paper provides a new design of robust fault detection for turbofan engines with adaptive controllers. The critical issue is that the adaptive controllers can depress the faulty effects such that the actual system outputs remain the pre-specified values, making it difficult to detect faults/failures. To solve this problem, a Total Measurable Fault Information Residual (ToMFIR) technique with the aid of system transformation is adopted to detect faults in turbofan engines with adaptive controllers. This design is a ToMFIR-redundancy-based robust fault detection. The ToMFIR is first introduced and existing results are also summarized. The Detailed design process of the ToMFIRs is presented and a turbofan engine model is simulated to verify the effectiveness of the proposed ToMFIR-based fault-detection strategy. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

All-to-all sequenced fault detection system

DOEpatents

Archer, Charles Jens; Pinnow, Kurt Walter; Ratterman, Joseph D.; Smith, Brian Edward

2010-11-02

An apparatus, program product and method enable nodal fault detection by sequencing communications between all system nodes. A master node may coordinate communications between two slave nodes before sequencing to and initiating communications between a new pair of slave nodes. The communications may be analyzed to determine the nodal fault.

Fault Detection for Nonlinear Process With Deterministic Disturbances: A Just-In-Time Learning Based Data Driven Method.

PubMed

Yin, Shen; Gao, Huijun; Qiu, Jianbin; Kaynak, Okyay

2017-11-01

Data-driven fault detection plays an important role in industrial systems due to its applicability in case of unknown physical models. In fault detection, disturbances must be taken into account as an inherent characteristic of processes. Nevertheless, fault detection for nonlinear processes with deterministic disturbances still receive little attention, especially in data-driven field. To solve this problem, a just-in-time learning-based data-driven (JITL-DD) fault detection method for nonlinear processes with deterministic disturbances is proposed in this paper. JITL-DD employs JITL scheme for process description with local model structures to cope with processes dynamics and nonlinearity. The proposed method provides a data-driven fault detection solution for nonlinear processes with deterministic disturbances, and owns inherent online adaptation and high accuracy of fault detection. Two nonlinear systems, i.e., a numerical example and a sewage treatment process benchmark, are employed to show the effectiveness of the proposed method.

An Uncertainty-Based Distributed Fault Detection Mechanism for Wireless Sensor Networks

PubMed Central

Yang, Yang; Gao, Zhipeng; Zhou, Hang; Qiu, Xuesong

2014-01-01

Exchanging too many messages for fault detection will cause not only a degradation of the network quality of service, but also represents a huge burden on the limited energy of sensors. Therefore, we propose an uncertainty-based distributed fault detection through aided judgment of neighbors for wireless sensor networks. The algorithm considers the serious influence of sensing measurement loss and therefore uses Markov decision processes for filling in missing data. Most important of all, fault misjudgments caused by uncertainty conditions are the main drawbacks of traditional distributed fault detection mechanisms. We draw on the experience of evidence fusion rules based on information entropy theory and the degree of disagreement function to increase the accuracy of fault detection. Simulation results demonstrate our algorithm can effectively reduce communication energy overhead due to message exchanges and provide a higher detection accuracy ratio. PMID:24776937

An uncertainty-based distributed fault detection mechanism for wireless sensor networks.

PubMed

Yang, Yang; Gao, Zhipeng; Zhou, Hang; Qiu, Xuesong

2014-04-25

Exchanging too many messages for fault detection will cause not only a degradation of the network quality of service, but also represents a huge burden on the limited energy of sensors. Therefore, we propose an uncertainty-based distributed fault detection through aided judgment of neighbors for wireless sensor networks. The algorithm considers the serious influence of sensing measurement loss and therefore uses Markov decision processes for filling in missing data. Most important of all, fault misjudgments caused by uncertainty conditions are the main drawbacks of traditional distributed fault detection mechanisms. We draw on the experience of evidence fusion rules based on information entropy theory and the degree of disagreement function to increase the accuracy of fault detection. Simulation results demonstrate our algorithm can effectively reduce communication energy overhead due to message exchanges and provide a higher detection accuracy ratio.

Fault detection and diagnosis of diesel engine valve trains

NASA Astrophysics Data System (ADS)

Flett, Justin; Bone, Gary M.

2016-05-01

This paper presents the development of a fault detection and diagnosis (FDD) system for use with a diesel internal combustion engine (ICE) valve train. A novel feature is generated for each of the valve closing and combustion impacts. Deformed valve spring faults and abnormal valve clearance faults were seeded on a diesel engine instrumented with one accelerometer. Five classification methods were implemented experimentally and compared. The FDD system using the Naïve-Bayes classification method produced the best overall performance, with a lowest detection accuracy (DA) of 99.95% and a lowest classification accuracy (CA) of 99.95% for the spring faults occurring on individual valves. The lowest DA and CA values for multiple faults occurring simultaneously were 99.95% and 92.45%, respectively. The DA and CA results demonstrate the accuracy of our FDD system for diesel ICE valve train fault scenarios not previously addressed in the literature.

Detection of microbial concentration in ice-cream using the impedance technique.

PubMed

Grossi, M; Lanzoni, M; Pompei, A; Lazzarini, R; Matteuzzi, D; Riccò, B

2008-06-15

The detection of microbial concentration, essential for safe and high quality food products, is traditionally made with the plate count technique, that is reliable, but also slow and not easily realized in the automatic form, as required for direct use in industrial machines. To this purpose, the method based on impedance measurements represents an attractive alternative since it can produce results in about 10h, instead of the 24-48h needed by standard plate counts and can be easily realized in automatic form. In this paper such a method has been experimentally studied in the case of ice-cream products. In particular, all main ice-cream compositions of real interest have been considered and no nutrient media has been used to dilute the samples. A measurement set-up has been realized using benchtop instruments for impedance measurements on samples whose bacteria concentration was independently measured by means of standard plate counts. The obtained results clearly indicate that impedance measurement represents a feasible and reliable technique to detect total microbial concentration in ice-cream, suitable to be implemented as an embedded system for industrial machines.

Sliding mode based fault detection, reconstruction and fault tolerant control scheme for motor systems.

PubMed

Mekki, Hemza; Benzineb, Omar; Boukhetala, Djamel; Tadjine, Mohamed; Benbouzid, Mohamed

2015-07-01

The fault-tolerant control problem belongs to the domain of complex control systems in which inter-control-disciplinary information and expertise are required. This paper proposes an improved faults detection, reconstruction and fault-tolerant control (FTC) scheme for motor systems (MS) with typical faults. For this purpose, a sliding mode controller (SMC) with an integral sliding surface is adopted. This controller can make the output of system to track the desired position reference signal in finite-time and obtain a better dynamic response and anti-disturbance performance. But this controller cannot deal directly with total system failures. However an appropriate combination of the adopted SMC and sliding mode observer (SMO), later it is designed to on-line detect and reconstruct the faults and also to give a sensorless control strategy which can achieve tolerance to a wide class of total additive failures. The closed-loop stability is proved, using the Lyapunov stability theory. Simulation results in healthy and faulty conditions confirm the reliability of the suggested framework. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Fault detection in reciprocating compressor valves under varying load conditions

NASA Astrophysics Data System (ADS)

Pichler, Kurt; Lughofer, Edwin; Pichler, Markus; Buchegger, Thomas; Klement, Erich Peter; Huschenbett, Matthias

2016-03-01

This paper presents a novel approach for detecting cracked or broken reciprocating compressor valves under varying load conditions. The main idea is that the time frequency representation of vibration measurement data will show typical patterns depending on the fault state. The problem is to detect these patterns reliably. For the detection task, we make a detour via the two dimensional autocorrelation. The autocorrelation emphasizes the patterns and reduces noise effects. This makes it easier to define appropriate features. After feature extraction, classification is done using logistic regression and support vector machines. The method's performance is validated by analyzing real world measurement data. The results will show a very high detection accuracy while keeping the false alarm rates at a very low level for different compressor loads, thus achieving a load-independent method. The proposed approach is, to our best knowledge, the first automated method for reciprocating compressor valve fault detection that can handle varying load conditions.

A signal-based fault detection and classification method for heavy haul wagons

NASA Astrophysics Data System (ADS)

Li, Chunsheng; Luo, Shihui; Cole, Colin; Spiryagin, Maksym; Sun, Yanquan

2017-12-01

This paper proposes a signal-based fault detection and isolation (FDI) system for heavy haul wagons considering the special requirements of low cost and robustness. The sensor network of the proposed system consists of just two accelerometers mounted on the front left and rear right of the carbody. Seven fault indicators (FIs) are proposed based on the cross-correlation analyses of the sensor-collected acceleration signals. Bolster spring fault conditions are focused on in this paper, including two different levels (small faults and moderate faults) and two locations (faults in the left and right bolster springs of the first bogie). A fully detailed dynamic model of a typical 40t axle load heavy haul wagon is developed to evaluate the deterioration of dynamic behaviour under proposed fault conditions and demonstrate the detectability of the proposed FDI method. Even though the fault conditions considered in this paper did not deteriorate the wagon dynamic behaviour dramatically, the proposed FIs show great sensitivity to the bolster spring faults. The most effective and efficient FIs are chosen for fault detection and classification. Analysis results indicate that it is possible to detect changes in bolster stiffness of ±25% and identify the fault location.

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.

Arc Fault Detection & Localization by Electromagnetic-Acoustic Remote Sensing

NASA Astrophysics Data System (ADS)

Vasile, C.; Ioana, C.

2017-05-01

Electrical arc faults that occur in photovoltaic systems represent a danger due to their economic impact on production and distribution. In this paper we propose a complete system, with focus on the methodology, that enables the detection and localization of the arc fault, by the use of an electromagnetic-acoustic sensing system. By exploiting the multiple emissions of the arc fault, in conjunction with a real-time detection signal processing method, we ensure accurate detection and localization. In its final form, this present work will present in greater detail the complete system, the methods employed, results and performance, alongside further works that will be carried on.

A distributed fault-detection and diagnosis system using on-line parameter estimation

NASA Technical Reports Server (NTRS)

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

1991-01-01

The development of a model-based fault-detection and diagnosis system (FDD) is reviewed. The system can be used as an integral part of an intelligent control system. It determines the faults of a system from comparison of the measurements of the system with a priori information represented by the model of the system. The method of modeling a complex system is described and a description of diagnosis models which include process faults is presented. There are three distinct classes of fault modes covered by the system performance model equation: actuator faults, sensor faults, and performance degradation. A system equation for a complete model that describes all three classes of faults is given. The strategy for detecting the fault and estimating the fault parameters using a distributed on-line parameter identification scheme is presented. A two-step approach is proposed. The first step is composed of a group of hypothesis testing modules, (HTM) in parallel processing to test each class of faults. The second step is the fault diagnosis module which checks all the information obtained from the HTM level, isolates the fault, and determines its magnitude. The proposed FDD system was demonstrated by applying it to detect actuator and sensor faults added to a simulation of the Space Shuttle Main Engine. The simulation results show that the proposed FDD system can adequately detect the faults and estimate their magnitudes.

A Novel Online Data-Driven Algorithm for Detecting UAV Navigation Sensor Faults.

PubMed

Sun, Rui; Cheng, Qi; Wang, Guanyu; Ochieng, Washington Yotto

2017-09-29

The use of Unmanned Aerial Vehicles (UAVs) has increased significantly in recent years. On-board integrated navigation sensors are a key component of UAVs' flight control systems and are essential for flight safety. In order to ensure flight safety, timely and effective navigation sensor fault detection capability is required. In this paper, a novel data-driven Adaptive Neuron Fuzzy Inference System (ANFIS)-based approach is presented for the detection of on-board navigation sensor faults in UAVs. Contrary to the classic UAV sensor fault detection algorithms, based on predefined or modelled faults, the proposed algorithm combines an online data training mechanism with the ANFIS-based decision system. The main advantages of this algorithm are that it allows real-time model-free residual analysis from Kalman Filter (KF) estimates and the ANFIS to build a reliable fault detection system. In addition, it allows fast and accurate detection of faults, which makes it suitable for real-time applications. Experimental results have demonstrated the effectiveness of the proposed fault detection method in terms of accuracy and misdetection rate.

Arc fault detection system

DOEpatents

Jha, K.N.

1999-05-18

An arc fault detection system for use on ungrounded or high-resistance-grounded power distribution systems is provided which can be retrofitted outside electrical switchboard circuits having limited space constraints. The system includes a differential current relay that senses a current differential between current flowing from secondary windings located in a current transformer coupled to a power supply side of a switchboard, and a total current induced in secondary windings coupled to a load side of the switchboard. When such a current differential is experienced, a current travels through a operating coil of the differential current relay, which in turn opens an upstream circuit breaker located between the switchboard and a power supply to remove the supply of power to the switchboard. 1 fig.

Arc fault detection system

DOEpatents

Jha, Kamal N.

1999-01-01

An arc fault detection system for use on ungrounded or high-resistance-grounded power distribution systems is provided which can be retrofitted outside electrical switchboard circuits having limited space constraints. The system includes a differential current relay that senses a current differential between current flowing from secondary windings located in a current transformer coupled to a power supply side of a switchboard, and a total current induced in secondary windings coupled to a load side of the switchboard. When such a current differential is experienced, a current travels through a operating coil of the differential current relay, which in turn opens an upstream circuit breaker located between the switchboard and a power supply to remove the supply of power to the switchboard.

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

Implementation of a model based fault detection and diagnosis for actuation faults of the Space Shuttle main engine

NASA Technical Reports Server (NTRS)

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

1992-01-01

In a previous study, Guo, Merrill and Duyar, 1990, reported a conceptual development of a fault detection and diagnosis system for actuation faults of the space shuttle main engine. This study, which is a continuation of the previous work, implements the developed fault detection and diagnosis scheme for the real time actuation fault diagnosis of the space shuttle main engine. The scheme will be used as an integral part of an intelligent control system demonstration experiment at NASA Lewis. The diagnosis system utilizes a model based method with real time identification and hypothesis testing for actuation, sensor, and performance degradation faults.

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

Development of high impedance measurement system for water leakage detection in implantable neuroprosthetic devices.

PubMed

Yousif, Aziz; Kelly, Shawn K

2016-08-01

There has been a push for a greater number of channels in implantable neuroprosthetic devices; but, that number has largely been limited by current hermetic packaging technology. Microfabricated packaging is becoming reality, but a standard testing system is needed to prepare these devices for clinical trials. Impedance measurements of electrodes built into the packaging layers may give an early warning of device failure and predict device lifetime. Because the impedance magnitudes of such devices can be on the order of gigaohms, a versatile system was designed to accommodate ultra-high impedances and allow future integrated circuit implementation in current neural prosthetic technologies. Here we present the circuitry, control software, and preliminary testing results of our designed system.

Main propulsion functional path analysis for performance monitoring fault detection and annunciation

NASA Technical Reports Server (NTRS)

Keesler, E. L.

1974-01-01

A total of 48 operational flight instrumentation measurements were identified for use in performance monitoring and fault detection. The Operational Flight Instrumentation List contains all measurements identified for fault detection and annunciation. Some 16 controller data words were identified for use in fault detection and annunciation.

A Unified Nonlinear Adaptive Approach for Detection and Isolation of Engine Faults

NASA Technical Reports Server (NTRS)

Tang, Liang; DeCastro, Jonathan A.; Zhang, Xiaodong; Farfan-Ramos, Luis; Simon, Donald L.

2010-01-01

A challenging problem in aircraft engine health management (EHM) system development is to detect and isolate faults in system components (i.e., compressor, turbine), actuators, and sensors. Existing nonlinear EHM methods often deal with component faults, actuator faults, and sensor faults separately, which may potentially lead to incorrect diagnostic decisions and unnecessary maintenance. Therefore, it would be ideal to address sensor faults, actuator faults, and component faults under one unified framework. This paper presents a systematic and unified nonlinear adaptive framework for detecting and isolating sensor faults, actuator faults, and component faults for aircraft engines. The fault detection and isolation (FDI) architecture consists of a parallel bank of nonlinear adaptive estimators. Adaptive thresholds are appropriately designed such that, in the presence of a particular fault, all components of the residual generated by the adaptive estimator corresponding to the actual fault type remain below their thresholds. If the faults are sufficiently different, then at least one component of the residual generated by each remaining adaptive estimator should exceed its threshold. Therefore, based on the specific response of the residuals, sensor faults, actuator faults, and component faults can be isolated. The effectiveness of the approach was evaluated using the NASA C-MAPSS turbofan engine model, and simulation results are presented.

Power plant fault detection using artificial neural network

NASA Astrophysics Data System (ADS)

Thanakodi, Suresh; Nazar, Nazatul Shiema Moh; Joini, Nur Fazriana; Hidzir, Hidzrin Dayana Mohd; Awira, Mohammad Zulfikar Khairul

2018-02-01

The fault that commonly occurs in power plants is due to various factors that affect the system outage. There are many types of faults in power plants such as single line to ground fault, double line to ground fault, and line to line fault. The primary aim of this paper is to diagnose the fault in 14 buses power plants by using an Artificial Neural Network (ANN). The Multilayered Perceptron Network (MLP) that detection trained utilized the offline training methods such as Gradient Descent Backpropagation (GDBP), Levenberg-Marquardt (LM), and Bayesian Regularization (BR). The best method is used to build the Graphical User Interface (GUI). The modelling of 14 buses power plant, network training, and GUI used the MATLAB software.

Incipient Fault Detection for Rolling Element Bearings under Varying Speed Conditions.

PubMed

Xue, Lang; Li, Naipeng; Lei, Yaguo; Li, Ningbo

2017-06-20

Varying speed conditions bring a huge challenge to incipient fault detection of rolling element bearings because both the change of speed and faults could lead to the amplitude fluctuation of vibration signals. Effective detection methods need to be developed to eliminate the influence of speed variation. This paper proposes an incipient fault detection method for bearings under varying speed conditions. Firstly, relative residual (RR) features are extracted, which are insensitive to the varying speed conditions and are able to reflect the degradation trend of bearings. Then, a health indicator named selected negative log-likelihood probability (SNLLP) is constructed to fuse a feature set including RR features and non-dimensional features. Finally, based on the constructed SNLLP health indicator, a novel alarm trigger mechanism is designed to detect the incipient fault. The proposed method is demonstrated using vibration signals from bearing tests and industrial wind turbines. The results verify the effectiveness of the proposed method for incipient fault detection of rolling element bearings under varying speed conditions.

Robust Fault Detection for Switched Fuzzy Systems With Unknown Input.

PubMed

Han, Jian; Zhang, Huaguang; Wang, Yingchun; Sun, Xun

2017-10-03

This paper investigates the fault detection problem for a class of switched nonlinear systems in the T-S fuzzy framework. The unknown input is considered in the systems. A novel fault detection unknown input observer design method is proposed. Based on the proposed observer, the unknown input can be removed from the fault detection residual. The weighted H∞ performance level is considered to ensure the robustness. In addition, the weighted H₋ performance level is introduced, which can increase the sensibility of the proposed detection method. To verify the proposed scheme, a numerical simulation example and an electromechanical system simulation example are provided at the end of this paper.

Fault tolerant filtering and fault detection for quantum systems driven by fields in single photon states

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

Gao, Qing, E-mail: qing.gao.chance@gmail.com; Dong, Daoyi, E-mail: daoyidong@gmail.com; Petersen, Ian R., E-mail: i.r.petersen@gmai.com

The purpose of this paper is to solve the fault tolerant filtering and fault detection problem for a class of open quantum systems driven by a continuous-mode bosonic input field in single photon states when the systems are subject to stochastic faults. Optimal estimates of both the system observables and the fault process are simultaneously calculated and characterized by a set of coupled recursive quantum stochastic differential equations.

Failure Detecting Method of Fault Current Limiter System with Rectifier

NASA Astrophysics Data System (ADS)

Tokuda, Noriaki; Matsubara, Yoshio; Asano, Masakuni; Ohkuma, Takeshi; Sato, Yoshibumi; Takahashi, Yoshihisa

A fault current limiter (FCL) is extensively needed to suppress fault current, particularly required for trunk power systems connecting high-voltage transmission lines, such as 500kV class power system which constitutes the nucleus of the electric power system. We proposed a new type FCL system (rectifier type FCL), consisting of solid-state diodes, DC reactor and bypass AC reactor, and demonstrated the excellent performances of this FCL by developing the small 6.6kV and 66kV model. It is important to detect the failure of power devices used in the rectifier under the normal operating condition, for keeping the excellent reliability of the power system. In this paper, we have proposed a new failure detecting method of power devices most suitable for the rectifier type FCL. This failure detecting system is simple and compact. We have adapted the proposed system to the 66kV prototype single-phase model and successfully demonstrated to detect the failure of power devices.

Nuclear Power Plant Thermocouple Sensor-Fault Detection and Classification Using Deep Learning and Generalized Likelihood Ratio Test

NASA Astrophysics Data System (ADS)

Mandal, Shyamapada; Santhi, B.; Sridhar, S.; Vinolia, K.; Swaminathan, P.

2017-06-01

In this paper, an online fault detection and classification method is proposed for thermocouples used in nuclear power plants. In the proposed method, the fault data are detected by the classification method, which classifies the fault data from the normal data. Deep belief network (DBN), a technique for deep learning, is applied to classify the fault data. The DBN has a multilayer feature extraction scheme, which is highly sensitive to a small variation of data. Since the classification method is unable to detect the faulty sensor; therefore, a technique is proposed to identify the faulty sensor from the fault data. Finally, the composite statistical hypothesis test, namely generalized likelihood ratio test, is applied to compute the fault pattern of the faulty sensor signal based on the magnitude of the fault. The performance of the proposed method is validated by field data obtained from thermocouple sensors of the fast breeder test reactor.

Multi-gap high impedance plasma opening switch

DOEpatents

Mason, R.J.

1996-10-22

A high impedance plasma opening switch having an anode and a cathode and at least one additional electrode placed between the anode and cathode is disclosed. The presence of the additional electrodes leads to the creation of additional plasma gaps which are in series, increasing the net impedance of the switch. An equivalent effect can be obtained by using two or more conventional plasma switches with their plasma gaps wired in series. Higher impedance switches can provide high current and voltage to higher impedance loads such as plasma radiation sources. 12 figs.

Multi-gap high impedance plasma opening switch

DOEpatents

Mason, Rodney J.

1996-01-01

A high impedance plasma opening switch having an anode and a cathode and at least one additional electrode placed between the anode and cathode. The presence of the additional electrodes leads to the creation of additional plasma gaps which are in series, increasing the net impedance of the switch. An equivalent effect can be obtained by using two or more conventional plasma switches with their plasma gaps wired in series. Higher impedance switches can provide high current and voltage to higher impedance loads such as plasma radiation sources.

Gastrointestinal Impedance Spectroscopy to Detect Hypoperfusion During Hemorrhage.

PubMed

Bloch, Andreas; Kohler, Andreas; Posthaus, Horst; Berger, David; Santos, Laura; Jakob, Stephan; Takala, Jukka; Haenggi, Matthias

2017-08-01

Changes in tissue impedance (Ω) have been proposed as early signs of impaired tissue perfusion. We hypothesized that hemorrhage may induce early changes in alimentary tract tissue impedance and that these can be detected by impedance spectroscopy. We evaluated impedance spectroscopy in an acute hemorrhage model in pigs. Twenty anesthetized pigs were randomized to stepwise hemorrhage to mean arterial blood pressure (MAP) targets of 60 mm Hg, 50 mm Hg, 45 mm Hg, and 40 mm Hg, followed by retransfusion in two steps, or control (n = 10 each). In the end, 500 mL of enteral nutrition was administered in both groups. Ω in four sites (sublingually, esophagus, stomach, proximal jejunum) and cardiac output (Qtot thermodilution), superior mesenteric artery blood flow (QSMA; Doppler ultrasound), and jejunal mucosal blood flow (LDF; laser Doppler) were measured. The bleeding (total volume 838 ± 185 mL; mean ± SD) resulted in progressive hypotension (actual MAP 65 ± 3 mm Hg, 59 ± 4 mm Hg, 55 ± 5 mm Hg, and 46 ± 6 mm Hg) and decrease in Qtot, QSMA, and mucosal LDF. Bleeding did not change Ω in any of the monitoring sites. Retransfusion restored the blood flows to at least baseline levels, again without change in Ω. Enteral nutrition did not alter Ω or any of the blood flows.Five animals (three in the hemorrhage group, two in the control group) had histologically proven acute gastric focal necrosis at the site of It transducer. Gastrointestinal impedance spectroscopy does not detect early changes in tissue perfusion during progressive hemorrhage or retransfusion. Ω spectroscopy is unlikely to provide any additional information of hypovolemia-induced early changes in gastrointestinal perfusion.

Fault detection in rotor bearing systems using time frequency techniques

NASA Astrophysics Data System (ADS)

Chandra, N. Harish; Sekhar, A. S.

2016-05-01

Faults such as misalignment, rotor cracks and rotor to stator rub can exist collectively in rotor bearing systems. It is an important task for rotor dynamic personnel to monitor and detect faults in rotating machinery. In this paper, the rotor startup vibrations are utilized to solve the fault identification problem using time frequency techniques. Numerical simulations are performed through finite element analysis of the rotor bearing system with individual and collective combinations of faults as mentioned above. Three signal processing tools namely Short Time Fourier Transform (STFT), Continuous Wavelet Transform (CWT) and Hilbert Huang Transform (HHT) are compared to evaluate their detection performance. The effect of addition of Signal to Noise ratio (SNR) on three time frequency techniques is presented. The comparative study is focused towards detecting the least possible level of the fault induced and the computational time consumed. The computation time consumed by HHT is very less when compared to CWT based diagnosis. However, for noisy data CWT is more preferred over HHT. To identify fault characteristics using wavelets a procedure to adjust resolution of the mother wavelet is presented in detail. Experiments are conducted to obtain the run-up data of a rotor bearing setup for diagnosis of shaft misalignment and rotor stator rubbing faults.

Fault detection, isolation, and diagnosis of self-validating multifunctional sensors.

PubMed

Yang, Jing-Li; Chen, Yin-Sheng; Zhang, Li-Li; Sun, Zhen

2016-06-01

A novel fault detection, isolation, and diagnosis (FDID) strategy for self-validating multifunctional sensors is presented in this paper. The sparse non-negative matrix factorization-based method can effectively detect faults by using the squared prediction error (SPE) statistic, and the variables contribution plots based on SPE statistic can help to locate and isolate the faulty sensitive units. The complete ensemble empirical mode decomposition is employed to decompose the fault signals to a series of intrinsic mode functions (IMFs) and a residual. The sample entropy (SampEn)-weighted energy values of each IMFs and the residual are estimated to represent the characteristics of the fault signals. Multi-class support vector machine is introduced to identify the fault mode with the purpose of diagnosing status of the faulty sensitive units. The performance of the proposed strategy is compared with other fault detection strategies such as principal component analysis, independent component analysis, and fault diagnosis strategies such as empirical mode decomposition coupled with support vector machine. The proposed strategy is fully evaluated in a real self-validating multifunctional sensors experimental system, and the experimental results demonstrate that the proposed strategy provides an excellent solution to the FDID research topic of self-validating multifunctional sensors.

Sensor fault detection and recovery in satellite attitude control

NASA Astrophysics Data System (ADS)

Nasrolahi, Seiied Saeed; Abdollahi, Farzaneh

2018-04-01

This paper proposes an integrated sensor fault detection and recovery for the satellite attitude control system. By introducing a nonlinear observer, the healthy sensor measurements are provided. Considering attitude dynamics and kinematic, a novel observer is developed to detect the fault in angular rate as well as attitude sensors individually or simultaneously. There is no limit on type and configuration of attitude sensors. By designing a state feedback based control signal and Lyapunov stability criterion, the uniformly ultimately boundedness of tracking errors in the presence of sensor faults is guaranteed. Finally, simulation results are presented to illustrate the performance of the integrated scheme.

High input impedance amplifier

NASA Technical Reports Server (NTRS)

Kleinberg, Leonard L.

1995-01-01

High input impedance amplifiers are provided which reduce the input impedance solely to a capacitive reactance, or, in a somewhat more complex design, provide an extremely high essentially infinite, capacitive reactance. In one embodiment, where the input impedance is reduced in essence, to solely a capacitive reactance, an operational amplifier in a follower configuration is driven at its non-inverting input and a resistor with a predetermined magnitude is connected between the inverting and non-inverting inputs. A second embodiment eliminates the capacitance from the input by adding a second stage to the first embodiment. The second stage is a second operational amplifier in a non-inverting gain-stage configuration where the output of the first follower stage drives the non-inverting input of the second stage and the output of the second stage is fed back to the non-inverting input of the first stage through a capacitor of a predetermined magnitude. These amplifiers, while generally useful, are very useful as sensor buffer amplifiers that may eliminate significant sources of error.

Incipient Fault Detection for Rolling Element Bearings under Varying Speed Conditions

PubMed Central

Xue, Lang; Li, Naipeng; Lei, Yaguo; Li, Ningbo

2017-01-01

Varying speed conditions bring a huge challenge to incipient fault detection of rolling element bearings because both the change of speed and faults could lead to the amplitude fluctuation of vibration signals. Effective detection methods need to be developed to eliminate the influence of speed variation. This paper proposes an incipient fault detection method for bearings under varying speed conditions. Firstly, relative residual (RR) features are extracted, which are insensitive to the varying speed conditions and are able to reflect the degradation trend of bearings. Then, a health indicator named selected negative log-likelihood probability (SNLLP) is constructed to fuse a feature set including RR features and non-dimensional features. Finally, based on the constructed SNLLP health indicator, a novel alarm trigger mechanism is designed to detect the incipient fault. The proposed method is demonstrated using vibration signals from bearing tests and industrial wind turbines. The results verify the effectiveness of the proposed method for incipient fault detection of rolling element bearings under varying speed conditions. PMID:28773035

System for detecting and limiting electrical ground faults within electrical devices

DOEpatents

Gaubatz, Donald C.

1990-01-01

An electrical ground fault detection and limitation system for employment with a nuclear reactor utilizing a liquid metal coolant. Elongate electromagnetic pumps submerged within the liquid metal coolant and electrical support equipment experiencing an insulation breakdown occasion the development of electrical ground fault current. Without some form of detection and control, these currents may build to damaging power levels to expose the pump drive components to liquid metal coolant such as sodium with resultant undesirable secondary effects. Such electrical ground fault currents are detected and controlled through the employment of an isolated power input to the pumps and with the use of a ground fault control conductor providing a direct return path from the affected components to the power source. By incorporating a resistance arrangement with the ground fault control conductor, the amount of fault current permitted to flow may be regulated to the extent that the reactor may remain in operation until maintenance may be performed, notwithstanding the existence of the fault. Monitors such as synchronous demodulators may be employed to identify and evaluate fault currents for each phase of a polyphase power, and control input to the submerged pump and associated support equipment.

Microfabricated AC impedance sensor

DOEpatents

Krulevitch, Peter; Ackler, Harold D.; Becker, Frederick; Boser, Bernhard E.; Eldredge, Adam B.; Fuller, Christopher K.; Gascoyne, Peter R. C.; Hamilton, Julie K.; Swierkowski, Stefan P.; Wang, Xiao-Bo

2002-01-01

A microfabricated instrument for detecting and identifying cells and other particles based on alternating current (AC) impedance measurements. The microfabricated AC impedance sensor includes two critical elements: 1) a microfluidic chip, preferably of glass substrates, having at least one microchannel therein and with electrodes patterned on both substrates, and 2) electrical circuits that connect to the electrodes on the microfluidic chip and detect signals associated with particles traveling down the microchannels. These circuits enable multiple AC impedance measurements of individual particles at high throughput rates with sufficient resolution to identify different particle and cell types as appropriate for environmental detection and clinical diagnostic applications.

Fault detection of helicopter gearboxes using the multi-valued influence matrix method

NASA Technical Reports Server (NTRS)

Chin, Hsinyung; Danai, Kourosh; Lewicki, David G.

1993-01-01

In this paper we investigate the effectiveness of a pattern classifying fault detection system that is designed to cope with the variability of fault signatures inherent in helicopter gearboxes. For detection, the measurements are monitored on-line and flagged upon the detection of abnormalities, so that they can be attributed to a faulty or normal case. As such, the detection system is composed of two components, a quantization matrix to flag the measurements, and a multi-valued influence matrix (MVIM) that represents the behavior of measurements during normal operation and at fault instances. Both the quantization matrix and influence matrix are tuned during a training session so as to minimize the error in detection. To demonstrate the effectiveness of this detection system, it was applied to vibration measurements collected from a helicopter gearbox during normal operation and at various fault instances. The results indicate that the MVIM method provides excellent results when the full range of faults effects on the measurements are included in the training set.

Sensor fault detection and isolation system for a condensation process.

PubMed

Castro, M A López; Escobar, R F; Torres, L; Aguilar, J F Gómez; Hernández, J A; Olivares-Peregrino, V H

2016-11-01

This article presents the design of a sensor Fault Detection and Isolation (FDI) system for a condensation process based on a nonlinear model. The condenser is modeled by dynamic and thermodynamic equations. For this work, the dynamic equations are described by three pairs of differential equations which represent the energy balance between the fluids. The thermodynamic equations consist in algebraic heat transfer equations and empirical equations, that allow for the estimation of heat transfer coefficients. The FDI system consists of a bank of two nonlinear high-gain observers, in order to detect, estimate and to isolate the fault in any of both outlet temperature sensors. The main contributions of this work were the experimental validation of the condenser nonlinear model and the FDI system. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Fiber Bragg Grating Sensor for Fault Detection in Radial and Network Transmission Lines

PubMed Central

Moghadas, Amin A.; Shadaram, Mehdi

2010-01-01

In this paper, a fiber optic based sensor capable of fault detection in both radial and network overhead transmission power line systems is investigated. Bragg wavelength shift is used to measure the fault current and detect fault in power systems. Magnetic fields generated by currents in the overhead transmission lines cause a strain in magnetostrictive material which is then detected by Fiber Bragg Grating (FBG). The Fiber Bragg interrogator senses the reflected FBG signals, and the Bragg wavelength shift is calculated and the signals are processed. A broadband light source in the control room scans the shift in the reflected signal. Any surge in the magnetic field relates to an increased fault current at a certain location. Also, fault location can be precisely defined with an artificial neural network (ANN) algorithm. This algorithm can be easily coordinated with other protective devices. It is shown that the faults in the overhead transmission line cause a detectable wavelength shift on the reflected signal of FBG and can be used to detect and classify different kind of faults. The proposed method has been extensively tested by simulation and results confirm that the proposed scheme is able to detect different kinds of fault in both radial and network system. PMID:22163416

Antibody biosensors for spoilage yeast detection based on impedance spectroscopy.

PubMed

Tubía, I; Paredes, J; Pérez-Lorenzo, E; Arana, S

2018-04-15

Brettanomyces is a yeast species responsible for wine and cider spoilage, producing volatile phenols that result in off-odors and loss of fruity sensorial qualities. Current commercial detection methods for these spoilage species are liable to frequent false positives, long culture times and fungal contamination. In this work, an interdigitated (IDE) biosensor was created to detect Brettanomyces using immunological reactions and impedance spectroscopy analysis. To promote efficient antibody immobilization on the electrodes' surface and to decrease non-specific adsorption, a Self-Assembled Monolayer (SAM) was developed. An impedance spectroscopy analysis, over four yeast strains, confirmed our device's increased efficacy. Compared to label-free sensors, antibody biosensors showed a higher relative impedance. The results also suggested that these biosensors could be a promising method to monitor some spoilage yeasts, offering an efficient alternative to the laborious and expensive traditional methods. Copyright © 2017 Elsevier B.V. All rights reserved.

Using impedance measurements for detecting pathogens trapped in an electric field

DOEpatents

Miles, Robin R.

2004-07-20

Impedance measurements between the electrodes in an electric field is utilized to detect the presence of pathogens trapped in the electric field. Since particles trapped in a field using the dielectiphoretic force changes the impedance between the electrodes by changing the dielectric material between the electrodes, the degree of particle trapping can be determined by measuring the impedance. This measurement is used to determine if sufficient pathogen have been collected to analyze further or potentially to identify the pathogen.

Fault detection of Tennessee Eastman process based on topological features and SVM

NASA Astrophysics Data System (ADS)

Zhao, Huiyang; Hu, Yanzhu; Ai, Xinbo; Hu, Yu; Meng, Zhen

2018-03-01

Fault detection in industrial process is a popular research topic. Although the distributed control system(DCS) has been introduced to monitor the state of industrial process, it still cannot satisfy all the requirements for fault detection of all the industrial systems. In this paper, we proposed a novel method based on topological features and support vector machine(SVM), for fault detection of industrial process. The proposed method takes global information of measured variables into account by complex network model and predicts whether a system has generated some faults or not by SVM. The proposed method can be divided into four steps, i.e. network construction, network analysis, model training and model testing respectively. Finally, we apply the model to Tennessee Eastman process(TEP). The results show that this method works well and can be a useful supplement for fault detection of industrial process.

Fuzzy logic based on-line fault detection and classification in transmission line.

PubMed

Adhikari, Shuma; Sinha, Nidul; Dorendrajit, Thingam

2016-01-01

This study presents fuzzy logic based online fault detection and classification of transmission line using Programmable Automation and Control technology based National Instrument Compact Reconfigurable i/o (CRIO) devices. The LabVIEW software combined with CRIO can perform real time data acquisition of transmission line. When fault occurs in the system current waveforms are distorted due to transients and their pattern changes according to the type of fault in the system. The three phase alternating current, zero sequence and positive sequence current data generated by LabVIEW through CRIO-9067 are processed directly for relaying. The result shows that proposed technique is capable of right tripping action and classification of type of fault at high speed therefore can be employed in practical application.

High Frequency Electromagnetic Impedance Measurements for Characterization, Monitoring and Verification Efforts

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

Lee, Ki Ha; Becker, Alex; Framgos, William

1999-06-01

Non-invasive, high-resolution imaging of the shallow subsurface is needed for delineation of buried waste, detection of unexploded ordinance, verification and monitoring of containment structures, and other environmental applications. Electromagnetic measurements at frequencies between 1 and 100 MHz are important for such applications, because the induction number of many targets is small and the ability to determine the dielectric permittivity in addition to electrical conductivity of the subsurface is possible. Earlier workers were successful in developing systems for detecting anomalous areas, but no quantifiable information was accurately determined. For high-resolution imaging, accurate measurements are necessary so the field data can bemore » mapped into the space of the subsurface parameters. We are developing a non-invasive method for accurately imaging the electrical conductivity and dielectric permittivity of the shallow subsurface using the plane wave impedance approach. Electric and magnetic sensors are being tested in a known area against theoretical predictions, thereby insuring that the data collected with the high-frequency impedance (HFI) system will support high-resolution, multi-dimensional imaging techniques.« less

High-Frequency Electromagnetic Impedance Measurements for Characterization, Monitoring, and Verification Efforts

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

Lee, Ki Ha; Becker, Alex

2000-06-01

Non-invasive, high-resolution imaging of the shallow subsurface is needed for delineation of buried waste, detection of unexploded ordinance, verification and monitoring of containment structures, and other environmental applications. Electromagnetic measurements at frequencies between 1 and 100 MHz are important for such applications, because the induction number of many targets is small and the ability to determine the dielectric permittivity in addition to electrical conductivity of the subsurface is possible. Earlier workers were successful in developing systems for detecting anomalous areas, but no quantifiable information was accurately determined. For high-resolution imaging, accurate measurements are necessary so the field data can bemore » mapped into the space of the subsurface parameters. We are developing a non-invasive method for accurately imaging the electrical conductivity and dielectric permittivity of the shallow subsurface using the plane wave impedance approach (Song et al., 1997). Electric and magnetic sensors are being tested in a known area against theoretical predictions, thereby insuring that the data collected with the high-frequency impedance (HFI) system will support high-resolution, multi-dimensional imaging techniques.« less

High-Frequency Electromagnetic Impedance Measurements for Characterization, Monitoring and Verification Efforts

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

Lee, Ki Ha; Becker, Alex; Tseng, Hung-Wen

2001-06-10

Non-invasive, high-resolution imaging of the shallow subsurface is needed for delineation of buried waste, detection of unexploded ordinance, verification and monitoring of containment structures, and other environmental applications. Electromagnetic (EM) measurements at frequencies between 1 and 100 MHz are important for such applications, because the induction number of many targets is small and the ability to determine the dielectric permittivity in addition to electrical conductivity of the subsurface is possible. Earlier workers were successful in developing systems for detecting anomalous areas, but no quantifiable information was accurately determined. For high-resolution imaging, accurate measurements are necessary so the field data canmore » be mapped into the space of the subsurface parameters. We are developing a non-invasive method for accurately mapping the electrical conductivity and dielectric permittivity of the shallow subsurface using the EM impedance approach (Frangos, 2001; Lee and Becker, 2001). Electric and magnetic sensors are being tested in a known area against theoretical predictions, thereby insuring that the data collected with the high-frequency impedance (HFI) system will support high-resolution, multi-dimensional imaging techniques.« less

Improved Sensor Fault Detection, Isolation, and Mitigation Using Multiple Observers Approach

PubMed Central

Wang, Zheng; Anand, D. M.; Moyne, J.; Tilbury, D. M.

2017-01-01

Traditional Fault Detection and Isolation (FDI) methods analyze a residual signal to detect and isolate sensor faults. The residual signal is the difference between the sensor measurements and the estimated outputs of the system based on an observer. The traditional residual-based FDI methods, however, have some limitations. First, they require that the observer has reached its steady state. In addition, residual-based methods may not detect some sensor faults, such as faults on critical sensors that result in an unobservable system. Furthermore, the system may be in jeopardy if actions required for mitigating the impact of the faulty sensors are not taken before the faulty sensors are identified. The contribution of this paper is to propose three new methods to address these limitations. Faults that occur during the observers' transient state can be detected by analyzing the convergence rate of the estimation error. Open-loop observers, which do not rely on sensor information, are used to detect faults on critical sensors. By switching among different observers, we can potentially mitigate the impact of the faulty sensor during the FDI process. These three methods are systematically integrated with a previously developed residual-based method to provide an improved FDI and mitigation capability framework. The overall approach is validated mathematically, and the effectiveness of the overall approach is demonstrated through simulation on a 5-state suspension system. PMID:28924303

SVD and Hankel matrix based de-noising approach for ball bearing fault detection and its assessment using artificial faults

NASA Astrophysics Data System (ADS)

Golafshan, Reza; Yuce Sanliturk, Kenan

2016-03-01

Ball bearings remain one of the most crucial components in industrial machines and due to their critical role, it is of great importance to monitor their conditions under operation. However, due to the background noise in acquired signals, it is not always possible to identify probable faults. This incapability in identifying the faults makes the de-noising process one of the most essential steps in the field of Condition Monitoring (CM) and fault detection. In the present study, Singular Value Decomposition (SVD) and Hankel matrix based de-noising process is successfully applied to the ball bearing time domain vibration signals as well as to their spectrums for the elimination of the background noise and the improvement the reliability of the fault detection process. The test cases conducted using experimental as well as the simulated vibration signals demonstrate the effectiveness of the proposed de-noising approach for the ball bearing fault detection.

Weak fault detection and health degradation monitoring using customized standard multiwavelets

NASA Astrophysics Data System (ADS)

Yuan, Jing; Wang, Yu; Peng, Yizhen; Wei, Chenjun

2017-09-01

Due to the nonobvious symptoms contaminated by a large amount of background noise, it is challenging to beforehand detect and predictively monitor the weak faults for machinery security assurance. Multiwavelets can act as adaptive non-stationary signal processing tools, potentially viable for weak fault diagnosis. However, the signal-based multiwavelets suffer from such problems as the imperfect properties missing the crucial orthogonality, the decomposition distortion impossibly reflecting the relationships between the faults and signatures, the single objective optimization and independence for fault prognostic. Thus, customized standard multiwavelets are proposed for weak fault detection and health degradation monitoring, especially the weak fault signature quantitative identification. First, the flexible standard multiwavelets are designed using the construction method derived from scalar wavelets, seizing the desired properties for accurate detection of weak faults and avoiding the distortion issue for feature quantitative identification. Second, the multi-objective optimization combined three dimensionless indicators of the normalized energy entropy, normalized singular entropy and kurtosis index is introduced to the evaluation criterions, and benefits for selecting the potential best basis functions for weak faults without the influence of the variable working condition. Third, an ensemble health indicator fused by the kurtosis index, impulse index and clearance index of the original signal along with the normalized energy entropy and normalized singular entropy by the customized standard multiwavelets is achieved using Mahalanobis distance to continuously monitor the health condition and track the performance degradation. Finally, three experimental case studies are implemented to demonstrate the feasibility and effectiveness of the proposed method. The results show that the proposed method can quantitatively identify the fault signature of a slight rub on

Detection of Frictional Heating on Faults Using Raman Spectra of Carbonaceous Material

NASA Astrophysics Data System (ADS)

Ito, K.; Ujiie, K.; Kagi, H.

2017-12-01

Raman spectra of carbonaceous material (RSCM) have been used as geothermometer in sedimentary and metamorphic rocks. However, it remains poorly understood whether RSCM are useful for detecting past frictional heating on faults. To detect increased heating during seismic slip, we examine the thrust fault in the Jurassic accretionary complex, central Japan. The thrust fault zone includes 10 cm-thick cataclasite and a few mm-thick dark layer. The cataclasite is characterized by fragments of black and gray chert in the black carbonaceous mudstone matrix. The dark layer is marked by intensely cracked gray chert fragments in the dark matrix of carbonaceous mudstone composition, which bounds the fractured gray chert above from the cataclasite below. The RSCM are analyzed for carbonaceous material in the cataclasite, dark layer, and host rock <10 mm from cataclasite and dark layer boundaries. The result indicates that there is no increased carbonization in the cataclasite. In contrast, the dark layer and part of host rocks <2 mm from the dark layer boundaries show prominent increase in carbonization. The absent of increased carbonization in the cataclasite could be attributed to insufficient frictional heating associated with distributed shear and/or faulting at low slip rates. The dark layer exhibits the appearance of fault and injection veins, and the dark layer boundaries are irregularly embayed or intensely cracked; these features have been characteristically observed in pseudotachylytes. Therefore, the increased carbonization in the dark layer is likely resulted from increased heating during earthquake faulting. The intensely cracked fragments in the dark layer and cracked wall rocks may reflect thermal fracturing in chert, which is caused by heat conduction from the molten zone. We suggest that RSCM are useful for the detection of increased heating on faults, particularly when the temperature is high enough for frictional melting and thermal fracturing.

Coordinated Fault-Tolerance for High-Performance Computing Final Project Report

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

Panda, Dhabaleswar Kumar; Beckman, Pete

2011-07-28

With the Coordinated Infrastructure for Fault Tolerance Systems (CIFTS, as the original project came to be called) project, our aim has been to understand and tackle the following broad research questions, the answers to which will help the HEC community analyze and shape the direction of research in the field of fault tolerance and resiliency on future high-end leadership systems. Will availability of global fault information, obtained by fault information exchange between the different HEC software on a system, allow individual system software to better detect, diagnose, and adaptively respond to faults? If fault-awareness is raised throughout the system throughmore » fault information exchange, is it possible to get all system software working together to provide a more comprehensive end-to-end fault management on the system? What are the missing fault-tolerance features that widely used HEC system software lacks today that would inhibit such software from taking advantage of systemwide global fault information? What are the practical limitations of a systemwide approach for end-to-end fault management based on fault awareness and coordination? What mechanisms, tools, and technologies are needed to bring about fault awareness and coordination of responses on a leadership-class system? What standards, outreach, and community interaction are needed for adoption of the concept of fault awareness and coordination for fault management on future systems? Keeping our overall objectives in mind, the CIFTS team has taken a parallel fourfold approach. Our central goal was to design and implement a light-weight, scalable infrastructure with a simple, standardized interface to allow communication of fault-related information through the system and facilitate coordinated responses. This work led to the development of the Fault Tolerance Backplane (FTB) publish-subscribe API specification, together with a reference implementation and several experimental implementations on

Resistivity structure of Sumatran Fault (Aceh segment) derived from 1-D magnetotelluric modeling

NASA Astrophysics Data System (ADS)

Nurhasan, Sutarno, D.; Bachtiar, H.; Sugiyanto, D.; Ogawa, Y.; Kimata, F.; Fitriani, D.

2012-06-01

Sumatran Fault Zone is the most active fault in Indonesia as a result of strike-slip component of Indo-Australian oblique convergence. With the length of 1900 km, Sumatran fault was divided into 20 segments starting from the southernmost Sumatra Island having small slip rate and increasing to the north end of Sumatra Island. There are several geophysical methods to analyze fault structure depending on physical parameter used in these methods, such as seismology, geodesy and electromagnetic. Magnetotelluric method which is one of geophysical methods has been widely used in mapping and sounding resistivity distribution because it does not only has the ability for detecting contras resistivity but also has a penetration range up to hundreds of kilometers. Magnetotelluric survey was carried out in Aceh region with the 12 total sites crossing Sumatran Fault on Aceh and Seulimeum segments. Two components of electric and magnetic fields were recorded during 10 hours in average with the frequency range from 320 Hz to 0,01 Hz. Analysis of the pseudosection of phase and apparent resistivity exhibit vertical low phase flanked on the west and east by high phase describing the existence of resistivity contras in this region. Having rotated the data to N45°E direction, interpretation of the result has been performed using three different methods of 1D MT modeling i.e. Bostick inversion, 1D MT inversion of TM data, and 1D MT inversion of the impedance determinant. By comparison, we concluded that the use of TM data only and the impedance determinant in 1D inversion yield the more reliable resistivity structure of the fault compare to other methods. Based on this result, it has been shown clearly that Sumatra Fault is characterized by vertical contras resistivity indicating the existence of Aceh and Seulimeum faults which has a good agreement with the geological data.

Automatic Channel Fault Detection on a Small Animal APD-Based Digital PET Scanner

NASA Astrophysics Data System (ADS)

Charest, Jonathan; Beaudoin, Jean-François; Cadorette, Jules; Lecomte, Roger; Brunet, Charles-Antoine; Fontaine, Réjean

2014-10-01

Avalanche photodiode (APD) based positron emission tomography (PET) scanners show enhanced imaging capabilities in terms of spatial resolution and contrast due to the one to one coupling and size of individual crystal-APD detectors. However, to ensure the maximal performance, these PET scanners require proper calibration by qualified scanner operators, which can become a cumbersome task because of the huge number of channels they are made of. An intelligent system (IS) intends to alleviate this workload by enabling a diagnosis of the observational errors of the scanner. The IS can be broken down into four hierarchical blocks: parameter extraction, channel fault detection, prioritization and diagnosis. One of the main activities of the IS consists in analyzing available channel data such as: normalization coincidence counts and single count rates, crystal identification classification data, energy histograms, APD bias and noise thresholds to establish the channel health status that will be used to detect channel faults. This paper focuses on the first two blocks of the IS: parameter extraction and channel fault detection. The purpose of the parameter extraction block is to process available data on individual channels into parameters that are subsequently used by the fault detection block to generate the channel health status. To ensure extensibility, the channel fault detection block is divided into indicators representing different aspects of PET scanner performance: sensitivity, timing, crystal identification and energy. Some experiments on a 8 cm axial length LabPET scanner located at the Sherbrooke Molecular Imaging Center demonstrated an erroneous channel fault detection rate of 10% (with a 95% confidence interval (CI) of [9, 11]) which is considered tolerable. Globally, the IS achieves a channel fault detection efficiency of 96% (CI: [95, 97]), which proves that many faults can be detected automatically. Increased fault detection efficiency would be

An integrated microsystem with dielectrophoresis enrichment and impedance detection for detection of Escherichia coli

USDA-ARS?s Scientific Manuscript database

An integrated microsystem device with matched interdigitated microelectrode chip was fabricated for enrichment and detection of Escherichia coli O157:H7. The microsystem has integrated with positive dielectrophoresis (pDEP) enrichment and in situ impedance detection, whose total volume is only 3.0 ×...

Distributed fault detection over sensor networks with Markovian switching topologies

NASA Astrophysics Data System (ADS)

Ge, Xiaohua; Han, Qing-Long

2014-05-01

This paper deals with the distributed fault detection for discrete-time Markov jump linear systems over sensor networks with Markovian switching topologies. The sensors are scatteredly deployed in the sensor field and the fault detectors are physically distributed via a communication network. The system dynamics changes and sensing topology variations are modeled by a discrete-time Markov chain with incomplete mode transition probabilities. Each of these sensor nodes firstly collects measurement outputs from its all underlying neighboring nodes, processes these data in accordance with the Markovian switching topologies, and then transmits the processed data to the remote fault detector node. Network-induced delays and accumulated data packet dropouts are incorporated in the data transmission between the sensor nodes and the distributed fault detector nodes through the communication network. To generate localized residual signals, mode-independent distributed fault detection filters are proposed. By means of the stochastic Lyapunov functional approach, the residual system performance analysis is carried out such that the overall residual system is stochastically stable and the error between each residual signal and the fault signal is made as small as possible. Furthermore, a sufficient condition on the existence of the mode-independent distributed fault detection filters is derived in the simultaneous presence of incomplete mode transition probabilities, Markovian switching topologies, network-induced delays, and accumulated data packed dropouts. Finally, a stirred-tank reactor system is given to show the effectiveness of the developed theoretical results.

Electrochemical impedance spectroscopy based MEMS sensors for phthalates detection in water and juices

NASA Astrophysics Data System (ADS)

Zia, Asif I.; Mohd Syaifudin, A. R.; Mukhopadhyay, S. C.; Yu, P. L.; Al-Bahadly, I. H.; Gooneratne, Chinthaka P.; Kosel, Jǘrgen; Liao, Tai-Shan

2013-06-01

Phthalate esters are ubiquitous environmental and food pollutants well known as endocrine disrupting compounds (EDCs). These developmental and reproductive toxicants pose a grave risk to the human health due to their unlimited use in consumer plastic industry. Detection of phthalates is strictly laboratory based time consuming and expensive process and requires expertise of highly qualified and skilled professionals. We present a real time, non-invasive, label free rapid detection technique to quantify phthalates' presence in deionized water and fruit juices. Electrochemical impedance spectroscopy (EIS) technique applied to a novel planar inter-digital (ID) capacitive sensor plays a vital role to explore the presence of phthalate esters in bulk fluid media. The ID sensor with multiple sensing gold electrodes was fabricated on silicon substrate using micro-electromechanical system (MEMS) device fabrication technology. A thin film of parylene C polymer was coated as a passivation layer to enhance the capacitive sensing capabilities of the sensor and to reduce the magnitude of Faradic current flowing through the sensor. Various concentrations, 0.002ppm through to 2ppm of di (2-ethylhexyl) phthalate (DEHP) in deionized water, were exposed to the sensing system by dip testing method. Impedance spectra obtained was analysed to determine sample conductance which led to consequent evaluation of its dielectric properties. Electro-chemical impedance spectrum analyser algorithm was employed to model the experimentally obtained impedance spectra. Curve fitting technique was applied to deduce constant phase element (CPE) equivalent circuit based on Randle's equivalent circuit model. The sensing system was tested to detect different concentrations of DEHP in orange juice as a real world application. The result analysis indicated that our rapid testing technique is able to detect the presence of DEHP in all test samples distinctively.

Detecting Blind Fault with Fractal and Roughness Factors from High Resolution LiDAR DEM at Taiwan

NASA Astrophysics Data System (ADS)

Cheng, Y. S.; Yu, T. T.

2014-12-01

There is no obvious fault scarp associated with blind fault. The traditional method of mapping this unrevealed geological structure is the cluster of seismicity. Neither the seismic event nor the completeness of cluster could be captured by network to chart the location of the entire possible active blind fault within short period of time. High resolution DEM gathered by LiDAR could denote actual terrain information despite the existence of plantation. 1-meter interval DEM of mountain region at Taiwan is utilized by fractal, entropy and roughness calculating with MATLAB code. By jointing these handing, the regions of non-sediment deposit are charted automatically. Possible blind fault associated with Chia-Sen earthquake at southern Taiwan is served as testing ground. GIS layer help in removing the difference from various geological formation, then multi-resolution fractal index is computed around the target region. The type of fault movement controls distribution of fractal index number. The scale of blind fault governs degree of change in fractal index. Landslide induced by rainfall and/or earthquake possesses larger degree of geomorphology alteration than blind fault; special treatment in removing these phenomena is required. Highly weathered condition at Taiwan should erase the possible trace remained upon DEM from the ruptured of blind fault while reoccurrence interval is higher than hundreds of years. This is one of the obstacle in finding possible blind fault at Taiwan.

A high-fidelity airbus benchmark for system fault detection and isolation and flight control law clearance

NASA Astrophysics Data System (ADS)

Goupil, Ph.; Puyou, G.

2013-12-01

This paper presents a high-fidelity generic twin engine civil aircraft model developed by Airbus for advanced flight control system research. The main features of this benchmark are described to make the reader aware of the model complexity and representativeness. It is a complete representation including the nonlinear rigid-body aircraft model with a full set of control surfaces, actuator models, sensor models, flight control laws (FCL), and pilot inputs. Two applications of this benchmark in the framework of European projects are presented: FCL clearance using optimization and advanced fault detection and diagnosis (FDD).

Passive fault current limiting device

DOEpatents

Evans, Daniel J.; Cha, Yung S.

1999-01-01

A passive current limiting device and isolator is particularly adapted for use at high power levels for limiting excessive currents in a circuit in a fault condition such as an electrical short. The current limiting device comprises a magnetic core wound with two magnetically opposed, parallel connected coils of copper, a high temperature superconductor or other electrically conducting material, and a fault element connected in series with one of the coils. Under normal operating conditions, the magnetic flux density produced by the two coils cancel each other. Under a fault condition, the fault element is triggered to cause an imbalance in the magnetic flux density between the two coils which results in an increase in the impedance in the coils. While the fault element may be a separate current limiter, switch, fuse, bimetal strip or the like, it preferably is a superconductor current limiter conducting one-half of the current load compared to the same limiter wired to carry the total current of the circuit. The major voltage during a fault condition is in the coils wound on the common core in a preferred embodiment.

Passive fault current limiting device

DOEpatents

Evans, D.J.; Cha, Y.S.

1999-04-06

A passive current limiting device and isolator is particularly adapted for use at high power levels for limiting excessive currents in a circuit in a fault condition such as an electrical short. The current limiting device comprises a magnetic core wound with two magnetically opposed, parallel connected coils of copper, a high temperature superconductor or other electrically conducting material, and a fault element connected in series with one of the coils. Under normal operating conditions, the magnetic flux density produced by the two coils cancel each other. Under a fault condition, the fault element is triggered to cause an imbalance in the magnetic flux density between the two coils which results in an increase in the impedance in the coils. While the fault element may be a separate current limiter, switch, fuse, bimetal strip or the like, it preferably is a superconductor current limiter conducting one-half of the current load compared to the same limiter wired to carry the total current of the circuit. The major voltage during a fault condition is in the coils wound on the common core in a preferred embodiment. 6 figs.

Label-Free Toxin Detection by Means of Time-Resolved Electrochemical Impedance Spectroscopy

PubMed Central

Chai, Changhoon; Takhistov, Paul

2010-01-01

The real-time detection of trace concentrations of biological toxins requires significant improvement of the detection methods from those reported in the literature. To develop a highly sensitive and selective detection device it is necessary to determine the optimal measuring conditions for the electrochemical sensor in three domains: time, frequency and polarization potential. In this work we utilized a time-resolved electrochemical impedance spectroscopy for the detection of trace concentrations of Staphylococcus enterotoxin B (SEB). An anti-SEB antibody has been attached to the nano-porous aluminum surface using 3-aminopropyltriethoxysilane/glutaraldehyde coupling system. This immobilization method allows fabrication of a highly reproducible and stable sensing device. Using developed immobilization procedure and optimized detection regime, it is possible to determine the presence of SEB at the levels as low as 10 pg/mL in 15 minutes. PMID:22315560

Techniques for Fault Detection and Visualization of Telemetry Dependence Relationships for Root Cause Fault Analysis in Complex Systems

NASA Astrophysics Data System (ADS)

Guy, Nathaniel

This thesis explores new ways of looking at telemetry data, from a time-correlative perspective, in order to see patterns within the data that may suggest root causes of system faults. It was thought initially that visualizing an animated Pearson Correlation Coefficient (PCC) matrix for telemetry channels would be sufficient to give new understanding; however, testing showed that the high dimensionality and inability to easily look at change over time in this approach impeded understanding. Different correlative techniques, combined with the time curve visualization proposed by Bach et al (2015), were adapted to visualize both raw telemetry and telemetry data correlations. Review revealed that these new techniques give insights into the data, and an intuitive grasp of data families, which show the effectiveness of this approach for enhancing system understanding and assisting with root cause analysis for complex aerospace systems.

ASCS online fault detection and isolation based on an improved MPCA

NASA Astrophysics Data System (ADS)

Peng, Jianxin; Liu, Haiou; Hu, Yuhui; Xi, Junqiang; Chen, Huiyan

2014-09-01

Multi-way principal component analysis (MPCA) has received considerable attention and been widely used in process monitoring. A traditional MPCA algorithm unfolds multiple batches of historical data into a two-dimensional matrix and cut the matrix along the time axis to form subspaces. However, low efficiency of subspaces and difficult fault isolation are the common disadvantages for the principal component model. This paper presents a new subspace construction method based on kernel density estimation function that can effectively reduce the storage amount of the subspace information. The MPCA model and the knowledge base are built based on the new subspace. Then, fault detection and isolation with the squared prediction error (SPE) statistic and the Hotelling ( T 2) statistic are also realized in process monitoring. When a fault occurs, fault isolation based on the SPE statistic is achieved by residual contribution analysis of different variables. For fault isolation of subspace based on the T 2 statistic, the relationship between the statistic indicator and state variables is constructed, and the constraint conditions are presented to check the validity of fault isolation. Then, to improve the robustness of fault isolation to unexpected disturbances, the statistic method is adopted to set the relation between single subspace and multiple subspaces to increase the corrective rate of fault isolation. Finally fault detection and isolation based on the improved MPCA is used to monitor the automatic shift control system (ASCS) to prove the correctness and effectiveness of the algorithm. The research proposes a new subspace construction method to reduce the required storage capacity and to prove the robustness of the principal component model, and sets the relationship between the state variables and fault detection indicators for fault isolation.

Robust Fault Detection Using Robust Z1 Estimation and Fuzzy Logic

NASA Technical Reports Server (NTRS)

Curry, Tramone; Collins, Emmanuel G., Jr.; Selekwa, Majura; Guo, Ten-Huei (Technical Monitor)

2001-01-01

This research considers the application of robust Z(sub 1), estimation in conjunction with fuzzy logic to robust fault detection for an aircraft fight control system. It begins with the development of robust Z(sub 1) estimators based on multiplier theory and then develops a fixed threshold approach to fault detection (FD). It then considers the use of fuzzy logic for robust residual evaluation and FD. Due to modeling errors and unmeasurable disturbances, it is difficult to distinguish between the effects of an actual fault and those caused by uncertainty and disturbance. Hence, it is the aim of a robust FD system to be sensitive to faults while remaining insensitive to uncertainty and disturbances. While fixed thresholds only allow a decision on whether a fault has or has not occurred, it is more valuable to have the residual evaluation lead to a conclusion related to the degree of, or probability of, a fault. Fuzzy logic is a viable means of determining the degree of a fault and allows the introduction of human observations that may not be incorporated in the rigorous threshold theory. Hence, fuzzy logic can provide a more reliable and informative fault detection process. Using an aircraft flight control system, the results of FD using robust Z(sub 1) estimation with a fixed threshold are demonstrated. FD that combines robust Z(sub 1) estimation and fuzzy logic is also demonstrated. It is seen that combining the robust estimator with fuzzy logic proves to be advantageous in increasing the sensitivity to smaller faults while remaining insensitive to uncertainty and disturbances.

High temperature superconducting fault current limiter

DOEpatents

Hull, J.R.

1997-02-04

A fault current limiter for an electrical circuit is disclosed. The fault current limiter includes a high temperature superconductor in the electrical circuit. The high temperature superconductor is cooled below its critical temperature to maintain the superconducting electrical properties during operation as the fault current limiter. 15 figs.

Avionic Air Data Sensors Fault Detection and Isolation by means of Singular Perturbation and Geometric Approach

PubMed Central

2017-01-01

Singular Perturbations represent an advantageous theory to deal with systems characterized by a two-time scale separation, such as the longitudinal dynamics of aircraft which are called phugoid and short period. In this work, the combination of the NonLinear Geometric Approach and the Singular Perturbations leads to an innovative Fault Detection and Isolation system dedicated to the isolation of faults affecting the air data system of a general aviation aircraft. The isolation capabilities, obtained by means of the approach proposed in this work, allow for the solution of a fault isolation problem otherwise not solvable by means of standard geometric techniques. Extensive Monte-Carlo simulations, exploiting a high fidelity aircraft simulator, show the effectiveness of the proposed Fault Detection and Isolation system. PMID:28946673

High temperature superconducting fault current limiter

DOEpatents

Hull, John R.

1997-01-01

A fault current limiter (10) for an electrical circuit (14). The fault current limiter (10) includes a high temperature superconductor (12) in the electrical circuit (14). The high temperature superconductor (12) is cooled below its critical temperature to maintain the superconducting electrical properties during operation as the fault current limiter (10).

High-Frequency Electromagnetic Impedance Measurements for Characterization, Monitoring and Verification Efforts

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

Lee, Ki Ha; Becker, Alex; Tseng, Hung-Wen

2004-06-16

Non-invasive, high-resolution imaging of the shallow subsurface is needed for delineation of buried waste, detection of unexploded ordinance, verification and monitoring of containment structures, and other environmental applications. Electromagnetic (EM) measurements at frequencies between 0.1 and 100 MHz are important for such applications, because the induction number of many targets is small and the ability to determine the dielectric permittivity in addition to electrical conductivity of the subsurface is possible. Earlier workers were successful in developing systems for detecting anomalous areas, but no quantifiable information was accurately determined. For high-resolution imaging, accurate measurements are necessary so the field data canmore » be mapped into the space of the subsurface parameters. We are developing a non-invasive method for accurately mapping the electrical conductivity and dielectric permittivity of the shallow subsurface using the EM impedance approach (Frangos, 2001; Lee and Becker, 2001; Song et al., 2002, Tseng et al., 2003). Electric and magnetic sensors are being tested and calibrated on sea water and in a known area against theoretical predictions, thereby insuring that the data collected with the high-frequency impedance (HFI) system will support high-resolution, multi-dimensional imaging techniques.« less

High-Frequency Electromagnetic Impedance Measurements for Characterization, Monitoring and Verification Efforts

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

Lee, Ki Ha; Becker, Alex; Tseng, Hung-Wen

2002-11-20

Non-invasive, high-resolution imaging of the shallow subsurface is needed for delineation of buried waste, detection of unexploded ordinance, verification and monitoring of containment structures, and other environmental applications. Electromagnetic (EM) measurements at frequencies between 1 and 100 MHz are important for such applications, because the induction number of many targets is small and the ability to determine the dielectric permittivity in addition to electrical conductivity of the subsurface is possible. Earlier workers were successful in developing systems for detecting anomalous areas, but no quantifiable information was accurately determined. For high-resolution imaging, accurate measurements are necessary so the field data canmore » be mapped into the space of the subsurface parameters. We are developing a non-invasive method for accurately mapping the electrical conductivity and dielectric permittivity of the shallow subsurface using the EM impedance approach (Frangos, 2001; Lee and Becker, 2001; Song et al., 2002). Electric and magnetic sensors are being tested in a known area against theoretical predictions, thereby insuring that the data collected with the high-frequency impedance (HFI) system will support high-resolution, multi-dimensional imaging techniques.« less

Sideband Algorithm for Automatic Wind Turbine Gearbox Fault Detection and Diagnosis: Preprint

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

Zappala, D.; Tavner, P.; Crabtree, C.

2013-01-01

Improving the availability of wind turbines (WT) is critical to minimize the cost of wind energy, especially for offshore installations. As gearbox downtime has a significant impact on WT availabilities, the development of reliable and cost-effective gearbox condition monitoring systems (CMS) is of great concern to the wind industry. Timely detection and diagnosis of developing gear defects within a gearbox is an essential part of minimizing unplanned downtime of wind turbines. Monitoring signals from WT gearboxes are highly non-stationary as turbine load and speed vary continuously with time. Time-consuming and costly manual handling of large amounts of monitoring data representmore » one of the main limitations of most current CMSs, so automated algorithms are required. This paper presents a fault detection algorithm for incorporation into a commercial CMS for automatic gear fault detection and diagnosis. The algorithm allowed the assessment of gear fault severity by tracking progressive tooth gear damage during variable speed and load operating conditions of the test rig. Results show that the proposed technique proves efficient and reliable for detecting gear damage. Once implemented into WT CMSs, this algorithm can automate data interpretation reducing the quantity of information that WT operators must handle.« less

Fast and sensitive detection of foodborne pathogen using electrochemical impedance analysis, urease catalysis and microfluidics.

PubMed

Chen, Qi; Wang, Dan; Cai, Gaozhe; Xiong, Yonghua; Li, Yuntao; Wang, Maohua; Huo, Huiling; Lin, Jianhan

2016-12-15

Early screening of pathogenic bacteria is a key to prevent and control of foodborne diseases. In this study, we developed a fast and sensitive bacteria detection method integrating electrochemical impedance analysis, urease catalysis with microfluidics and using Listeria as model. The Listeria cells, the anti-Listeria monoclonal antibodies modified magnetic nanoparticles (MNPs), and the anti-Listeria polyclonal antibodies and urease modified gold nanoparticles (AuNPs) were incubated in a fluidic separation chip with active mixing to form the MNP-Listeria-AuNP-urease sandwich complexes. The complexes were captured in the separation chip by applying a high gradient magnetic field, and the urea was injected to resuspend the complexes and hydrolyzed under the catalysis of the urease on the complexes into ammonium ions and carbonate ions, which were transported into a microfluidic detection chip with an interdigitated microelectrode for impedance measurement to determine the amount of the Listeria cells. The capture efficiency of the Listeria cells in the separation chip was ∼93% with a shorter time of 30min due to the faster immuno-reaction using the active magnetic mixing. The changes on both impedance magnitude and phase angle were demonstrated to be able to detect the Listeria cells as low as 1.6×10(2)CFU/mL. The detection time was reduced from original ∼2h to current ∼1h. The recoveries of the spiked lettuce samples ranged from 82.1% to 89.6%, indicating the applicability of this proposed biosensor. This microfluidic impedance biosensor has shown the potential for online, automatic and sensitive bacteria separation and detection. Copyright © 2016 Elsevier B.V. All rights reserved.

Fuzzy model-based observers for fault detection in CSTR.

PubMed

Ballesteros-Moncada, Hazael; Herrera-López, Enrique J; Anzurez-Marín, Juan

2015-11-01

Under the vast variety of fuzzy model-based observers reported in the literature, what would be the properone to be used for fault detection in a class of chemical reactor? In this study four fuzzy model-based observers for sensor fault detection of a Continuous Stirred Tank Reactor were designed and compared. The designs include (i) a Luenberger fuzzy observer, (ii) a Luenberger fuzzy observer with sliding modes, (iii) a Walcott-Zak fuzzy observer, and (iv) an Utkin fuzzy observer. A negative, an oscillating fault signal, and a bounded random noise signal with a maximum value of ±0.4 were used to evaluate and compare the performance of the fuzzy observers. The Utkin fuzzy observer showed the best performance under the tested conditions. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Fault detection and diagnosis in asymmetric multilevel inverter using artificial neural network

NASA Astrophysics Data System (ADS)

Raj, Nithin; Jagadanand, G.; George, Saly

2018-04-01

The increased component requirement to realise multilevel inverter (MLI) fallout in a higher fault prospect due to power semiconductors. In this scenario, efficient fault detection and diagnosis (FDD) strategies to detect and locate the power semiconductor faults have to be incorporated in addition to the conventional protection systems. Even though a number of FDD methods have been introduced in the symmetrical cascaded H-bridge (CHB) MLIs, very few methods address the FDD in asymmetric CHB-MLIs. In this paper, the gate-open circuit FDD strategy in asymmetric CHB-MLI is presented. Here, a single artificial neural network (ANN) is used to detect and diagnose the fault in both binary and trinary configurations of the asymmetric CHB-MLIs. In this method, features of the output voltage of the MLIs are used as to train the ANN for FDD method. The results prove the validity of the proposed method in detecting and locating the fault in both asymmetric MLI configurations. Finally, the ANN response to the input parameter variation is also analysed to access the performance of the proposed ANN-based FDD strategy.

Detection and quantification of Alicyclobacillus acidoterrestris by electrical impedance in apple juice.

PubMed

Fernández, Pilar; Gabaldón, José Antonio; Periago, Mª Jesús

2017-12-01

Alicyclobacillus acidoterrestris is a thermotolerant bacterium able to grow in fruit juices and drinks, as the spoilage by Alicyclobacillus in the final product does not product any gas, but leads to a "medicine flavor" due to the formation of guaicol. Also, its detection is a challenge for the quality control departments, because it takes several days to get the results of traditional microbiology methods. This study aimed at developing a more accurate electrical impedance technique for the detection of A. acidoterrestris in concentrated apple juice. Samples of apple juice were inoculated with A. acidoterrestris spores isolated from a peach and grape juice. For the spore germination, several heat-shock treatments were tested (80 °C/10 min, 70 °C/20 min and 60 °C/30 min). Direct and indirect electrical impedance was applied to detect and quantify the microorganism in the inoculated apple juice, using BAT broth and Bimedia 002A (pH 4). The 80 °C/10 min treatment was selected for spore activation. The valid electrical impedance technique was the indirect method in BAT broth, which measured the changes in the impedance through the formation of CO 2 . In addition, a positive correlation (r = 0.98, R 2  = 0.97) was observed between the classical microbiology (BAM agar) and the indirect impedance method. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Mode-Shape-Based Fault Detection Methodology for Cantilever Beams

NASA Technical Reports Server (NTRS)

Tejada, Arturo

2009-01-01

An important goal of NASA's Internal Vehicle Health Management program (IVHM) is to develop and verify methods and technologies for fault detection in critical airframe structures. A particularly promising new technology under development at NASA Langley Research Center is distributed Bragg fiber optic strain sensors. These sensors can be embedded in, for instance, aircraft wings to continuously monitor surface strain during flight. Strain information can then be used in conjunction with well-known vibrational techniques to detect faults due to changes in the wing's physical parameters or to the presence of incipient cracks. To verify the benefits of this technology, the Formal Methods Group at NASA LaRC has proposed the use of formal verification tools such as PVS. The verification process, however, requires knowledge of the physics and mathematics of the vibrational techniques and a clear understanding of the particular fault detection methodology. This report presents a succinct review of the physical principles behind the modeling of vibrating structures such as cantilever beams (the natural model of a wing). It also reviews two different classes of fault detection techniques and proposes a particular detection method for cracks in wings, which is amenable to formal verification. A prototype implementation of these methods using Matlab scripts is also described and is related to the fundamental theoretical concepts.

Modeling, Detection, and Disambiguation of Sensor Faults for Aerospace Applications

NASA Technical Reports Server (NTRS)

Balaban, Edward; Saxena, Abhinav; Bansal, Prasun; Goebel, Kai F.; Curran, Simon

2009-01-01

Sensor faults continue to be a major hurdle for systems health management to reach its full potential. At the same time, few recorded instances of sensor faults exist. It is equally difficult to seed particular sensor faults. Therefore, research is underway to better understand the different fault modes seen in sensors and to model the faults. The fault models can then be used in simulated sensor fault scenarios to ensure that algorithms can distinguish between sensor faults and system faults. The paper illustrates the work with data collected from an electro-mechanical actuator in an aerospace setting, equipped with temperature, vibration, current, and position sensors. The most common sensor faults, such as bias, drift, scaling, and dropout were simulated and injected into the experimental data, with the goal of making these simulations as realistic as feasible. A neural network based classifier was then created and tested on both experimental data and the more challenging randomized data sequences. Additional studies were also conducted to determine sensitivity of detection and disambiguation efficacy to severity of fault conditions.

Batch process fault detection and identification based on discriminant global preserving kernel slow feature analysis.

PubMed

Zhang, Hanyuan; Tian, Xuemin; Deng, Xiaogang; Cao, Yuping

2018-05-16

As an attractive nonlinear dynamic data analysis tool, global preserving kernel slow feature analysis (GKSFA) has achieved great success in extracting the high nonlinearity and inherently time-varying dynamics of batch process. However, GKSFA is an unsupervised feature extraction method and lacks the ability to utilize batch process class label information, which may not offer the most effective means for dealing with batch process monitoring. To overcome this problem, we propose a novel batch process monitoring method based on the modified GKSFA, referred to as discriminant global preserving kernel slow feature analysis (DGKSFA), by closely integrating discriminant analysis and GKSFA. The proposed DGKSFA method can extract discriminant feature of batch process as well as preserve global and local geometrical structure information of observed data. For the purpose of fault detection, a monitoring statistic is constructed based on the distance between the optimal kernel feature vectors of test data and normal data. To tackle the challenging issue of nonlinear fault variable identification, a new nonlinear contribution plot method is also developed to help identifying the fault variable after a fault is detected, which is derived from the idea of variable pseudo-sample trajectory projection in DGKSFA nonlinear biplot. Simulation results conducted on a numerical nonlinear dynamic system and the benchmark fed-batch penicillin fermentation process demonstrate that the proposed process monitoring and fault diagnosis approach can effectively detect fault and distinguish fault variables from normal variables. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Simultaneous Event-Triggered Fault Detection and Estimation for Stochastic Systems Subject to Deception Attacks.

PubMed

Li, Yunji; Wu, QingE; Peng, Li

2018-01-23

In this paper, a synthesized design of fault-detection filter and fault estimator is considered for a class of discrete-time stochastic systems in the framework of event-triggered transmission scheme subject to unknown disturbances and deception attacks. A random variable obeying the Bernoulli distribution is employed to characterize the phenomena of the randomly occurring deception attacks. To achieve a fault-detection residual is only sensitive to faults while robust to disturbances, a coordinate transformation approach is exploited. This approach can transform the considered system into two subsystems and the unknown disturbances are removed from one of the subsystems. The gain of fault-detection filter is derived by minimizing an upper bound of filter error covariance. Meanwhile, system faults can be reconstructed by the remote fault estimator. An recursive approach is developed to obtain fault estimator gains as well as guarantee the fault estimator performance. Furthermore, the corresponding event-triggered sensor data transmission scheme is also presented for improving working-life of the wireless sensor node when measurement information are aperiodically transmitted. Finally, a scaled version of an industrial system consisting of local PC, remote estimator and wireless sensor node is used to experimentally evaluate the proposed theoretical results. In particular, a novel fault-alarming strategy is proposed so that the real-time capacity of fault-detection is guaranteed when the event condition is triggered.

Induction motor inter turn fault detection using infrared thermographic analysis

NASA Astrophysics Data System (ADS)

Singh, Gurmeet; Anil Kumar, T. Ch.; Naikan, V. N. A.

2016-07-01

Induction motors are the most commonly used prime movers in industries. These are subjected to various environmental, thermal and load stresses that ultimately reduces the motor efficiency and later leads to failure. Inter turn fault is the second most commonly observed faults in the motors and is considered the most severe. It can lead to the failure of complete phase and can even cause accidents, if left undetected or untreated. This paper proposes an online and non invasive technique that uses infrared thermography, in order to detect the presence of inter turn fault in induction motor drive. Two methods have been proposed that detect the fault and estimate its severity. One method uses transient thermal monitoring during the start of motor and other applies pseudo coloring technique on infrared image of the motor, after it reaches a thermal steady state. The designed template for pseudo-coloring is in acquiescence with the InterNational Electrical Testing Association (NETA) thermographic standard. An index is proposed to assess the severity of the fault present in the motor.

On-line early fault detection and diagnosis of municipal solid waste incinerators

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

Zhao Jinsong; Huang Jianchao; Sun Wei

A fault detection and diagnosis framework is proposed in this paper for early fault detection and diagnosis (FDD) of municipal solid waste incinerators (MSWIs) in order to improve the safety and continuity of production. In this framework, principal component analysis (PCA), one of the multivariate statistical technologies, is used for detecting abnormal events, while rule-based reasoning performs the fault diagnosis and consequence prediction, and also generates recommendations for fault mitigation once an abnormal event is detected. A software package, SWIFT, is developed based on the proposed framework, and has been applied in an actual industrial MSWI. The application shows thatmore » automated real-time abnormal situation management (ASM) of the MSWI can be achieved by using SWIFT, resulting in an industrially acceptable low rate of wrong diagnosis, which has resulted in improved process continuity and environmental performance of the MSWI.« less

Adaptively Adjusted Event-Triggering Mechanism on Fault Detection for Networked Control Systems.

PubMed

Wang, Yu-Long; Lim, Cheng-Chew; Shi, Peng

2016-12-08

This paper studies the problem of adaptively adjusted event-triggering mechanism-based fault detection for a class of discrete-time networked control system (NCS) with applications to aircraft dynamics. By taking into account the fault occurrence detection progress and the fault occurrence probability, and introducing an adaptively adjusted event-triggering parameter, a novel event-triggering mechanism is proposed to achieve the efficient utilization of the communication network bandwidth. Both the sensor-to-control station and the control station-to-actuator network-induced delays are taken into account. The event-triggered sensor and the event-triggered control station are utilized simultaneously to establish new network-based closed-loop models for the NCS subject to faults. Based on the established models, the event-triggered simultaneous design of fault detection filter (FDF) and controller is presented. A new algorithm for handling the adaptively adjusted event-triggering parameter is proposed. Performance analysis verifies the effectiveness of the adaptively adjusted event-triggering mechanism, and the simultaneous design of FDF and controller.

Rapid detection of contaminant bacteria in platelet concentrate using differential impedance.

PubMed

Zhao, Z; Chalmers, A; Rieder, R

2014-08-01

Current FDA-approved culture-based methods for the bacterial testing of platelet concentrate (PC) can yield false-negative results attributed to Poisson-limited sampling errors incurred near the time of collection that result in undetectable bacterial concentrations. Testing PC at the point of issue (POI) extends the incubation period for any contaminant bacteria increasing the probability of detection. Data are presented from time-course experiments designed to simulate POI testing of bacterially contaminated PCs at different stages of growth using differential impedance sensing. Whole-blood-derived PCs were typically spiked with low numbers of bacteria (approximately 100 CFU/ml) and incubated under standard PC storage conditions. Each infected unit was evaluated every two hours over a 12-h period. All samples were treated with a chemical compound that induces stress in the bacterial cells only. The development of any bacterial stress was monitored by detecting changes in the dielectric properties of the PC using differential impedance. Differential impedance measurements and corresponding cell counts at the different time-points are presented for six organisms implicated in post-transfusion-septic reactions. All infected PCs were detected once contaminant bacteria reached concentrations ranging between 0·6 × 10(3) and 6 × 10(3)  CFU/ml irrespective of the phase of growth. Results were obtained within 30 min after the start of the assay and without the need for cell lysis or centrifugation. Differential impedance sensing can detect bacterial contamination in PC rapidly at concentrations below clinical thresholds known to cause adverse effects. © 2014 International Society of Blood Transfusion.

Development of Fault Models for Hybrid Fault Detection and Diagnostics Algorithm: October 1, 2014 -- May 5, 2015

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

Cheung, Howard; Braun, James E.

This report describes models of building faults created for OpenStudio to support the ongoing development of fault detection and diagnostic (FDD) algorithms at the National Renewable Energy Laboratory. Building faults are operating abnormalities that degrade building performance, such as using more energy than normal operation, failing to maintain building temperatures according to the thermostat set points, etc. Models of building faults in OpenStudio can be used to estimate fault impacts on building performance and to develop and evaluate FDD algorithms. The aim of the project is to develop fault models of typical heating, ventilating and air conditioning (HVAC) equipment inmore » the United States, and the fault models in this report are grouped as control faults, sensor faults, packaged and split air conditioner faults, water-cooled chiller faults, and other uncategorized faults. The control fault models simulate impacts of inappropriate thermostat control schemes such as an incorrect thermostat set point in unoccupied hours and manual changes of thermostat set point due to extreme outside temperature. Sensor fault models focus on the modeling of sensor biases including economizer relative humidity sensor bias, supply air temperature sensor bias, and water circuit temperature sensor bias. Packaged and split air conditioner fault models simulate refrigerant undercharging, condenser fouling, condenser fan motor efficiency degradation, non-condensable entrainment in refrigerant, and liquid line restriction. Other fault models that are uncategorized include duct fouling, excessive infiltration into the building, and blower and pump motor degradation.« less

Development of Fault Models for Hybrid Fault Detection and Diagnostics Algorithm: October 1, 2014 -- May 5, 2015

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

Cheung, Howard; Braun, James E.

2015-12-31

This report describes models of building faults created for OpenStudio to support the ongoing development of fault detection and diagnostic (FDD) algorithms at the National Renewable Energy Laboratory. Building faults are operating abnormalities that degrade building performance, such as using more energy than normal operation, failing to maintain building temperatures according to the thermostat set points, etc. Models of building faults in OpenStudio can be used to estimate fault impacts on building performance and to develop and evaluate FDD algorithms. The aim of the project is to develop fault models of typical heating, ventilating and air conditioning (HVAC) equipment inmore » the United States, and the fault models in this report are grouped as control faults, sensor faults, packaged and split air conditioner faults, water-cooled chiller faults, and other uncategorized faults. The control fault models simulate impacts of inappropriate thermostat control schemes such as an incorrect thermostat set point in unoccupied hours and manual changes of thermostat set point due to extreme outside temperature. Sensor fault models focus on the modeling of sensor biases including economizer relative humidity sensor bias, supply air temperature sensor bias, and water circuit temperature sensor bias. Packaged and split air conditioner fault models simulate refrigerant undercharging, condenser fouling, condenser fan motor efficiency degradation, non-condensable entrainment in refrigerant, and liquid line restriction. Other fault models that are uncategorized include duct fouling, excessive infiltration into the building, and blower and pump motor degradation.« less

Detection and diagnosis of bearing and cutting tool faults using hidden Markov models

NASA Astrophysics Data System (ADS)

Boutros, Tony; Liang, Ming

2011-08-01

Over the last few decades, the research for new fault detection and diagnosis techniques in machining processes and rotating machinery has attracted increasing interest worldwide. This development was mainly stimulated by the rapid advance in industrial technologies and the increase in complexity of machining and machinery systems. In this study, the discrete hidden Markov model (HMM) is applied to detect and diagnose mechanical faults. The technique is tested and validated successfully using two scenarios: tool wear/fracture and bearing faults. In the first case the model correctly detected the state of the tool (i.e., sharp, worn, or broken) whereas in the second application, the model classified the severity of the fault seeded in two different engine bearings. The success rate obtained in our tests for fault severity classification was above 95%. In addition to the fault severity, a location index was developed to determine the fault location. This index has been applied to determine the location (inner race, ball, or outer race) of a bearing fault with an average success rate of 96%. The training time required to develop the HMMs was less than 5 s in both the monitoring cases.

Smart Sensor for Online Detection of Multiple-Combined Faults in VSD-Fed Induction Motors

PubMed Central

Garcia-Ramirez, Armando G.; Osornio-Rios, Roque A.; Granados-Lieberman, David; Garcia-Perez, Arturo; Romero-Troncoso, Rene J.

2012-01-01

Induction motors fed through variable speed drives (VSD) are widely used in different industrial processes. Nowadays, the industry demands the integration of smart sensors to improve the fault detection in order to reduce cost, maintenance and power consumption. Induction motors can develop one or more faults at the same time that can be produce severe damages. The combined fault identification in induction motors is a demanding task, but it has been rarely considered in spite of being a common situation, because it is difficult to identify two or more faults simultaneously. This work presents a smart sensor for online detection of simple and multiple-combined faults in induction motors fed through a VSD in a wide frequency range covering low frequencies from 3 Hz and high frequencies up to 60 Hz based on a primary sensor being a commercially available current clamp or a hall-effect sensor. The proposed smart sensor implements a methodology based on the fast Fourier transform (FFT), RMS calculation and artificial neural networks (ANN), which are processed online using digital hardware signal processing based on field programmable gate array (FPGA).

System and method for bearing fault detection using stator current noise cancellation

DOEpatents

Zhou, Wei; Lu, Bin; Habetler, Thomas G.; Harley, Ronald G.; Theisen, Peter J.

2010-08-17

A system and method for detecting incipient mechanical motor faults by way of current noise cancellation is disclosed. The system includes a controller configured to detect indicia of incipient mechanical motor faults. The controller further includes a processor programmed to receive a baseline set of current data from an operating motor and define a noise component in the baseline set of current data. The processor is also programmed to repeatedly receive real-time operating current data from the operating motor and remove the noise component from the operating current data in real-time to isolate any fault components present in the operating current data. The processor is then programmed to generate a fault index for the operating current data based on any isolated fault components.

A Model-Based Probabilistic Inversion Framework for Wire Fault Detection Using TDR

NASA Technical Reports Server (NTRS)

Schuet, Stefan R.; Timucin, Dogan A.; Wheeler, Kevin R.

2010-01-01

Time-domain reflectometry (TDR) is one of the standard methods for diagnosing faults in electrical wiring and interconnect systems, with a long-standing history focused mainly on hardware development of both high-fidelity systems for laboratory use and portable hand-held devices for field deployment. While these devices can easily assess distance to hard faults such as sustained opens or shorts, their ability to assess subtle but important degradation such as chafing remains an open question. This paper presents a unified framework for TDR-based chafing fault detection in lossy coaxial cables by combining an S-parameter based forward modeling approach with a probabilistic (Bayesian) inference algorithm. Results are presented for the estimation of nominal and faulty cable parameters from laboratory data.

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.

Fault finder

DOEpatents

Bunch, Richard H.

1986-01-01

A fault finder for locating faults along a high voltage electrical transmission line. Real time monitoring of background noise and improved filtering of input signals is used to identify the occurrence of a fault. A fault is detected at both a master and remote unit spaced along the line. A master clock synchronizes operation of a similar clock at the remote unit. Both units include modulator and demodulator circuits for transmission of clock signals and data. All data is received at the master unit for processing to determine an accurate fault distance calculation.

Hybrid Model-Based and Data-Driven Fault Detection and Diagnostics for Commercial Buildings

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

Frank, Stephen; Heaney, Michael; Jin, Xin

Commercial buildings often experience faults that produce undesirable behavior in building systems. Building faults waste energy, decrease occupants' comfort, and increase operating costs. Automated fault detection and diagnosis (FDD) tools for buildings help building owners discover and identify the root causes of faults in building systems, equipment, and controls. Proper implementation of FDD has the potential to simultaneously improve comfort, reduce energy use, and narrow the gap between actual and optimal building performance. However, conventional rule-based FDD requires expensive instrumentation and valuable engineering labor, which limit deployment opportunities. This paper presents a hybrid, automated FDD approach that combines building energymore » models and statistical learning tools to detect and diagnose faults noninvasively, using minimal sensors, with little customization. We compare and contrast the performance of several hybrid FDD algorithms for a small security building. Our results indicate that the algorithms can detect and diagnose several common faults, but more work is required to reduce false positive rates and improve diagnosis accuracy.« less

Smartphone-based portable biosensing system using impedance measurement with printed electrodes for 2,4,6-trinitrotoluene (TNT) detection.

PubMed

Zhang, Diming; Jiang, Jing; Chen, Junye; Zhang, Qian; Lu, Yanli; Yao, Yao; Li, Shuang; Logan Liu, Gang; Liu, Qingjun

2015-08-15

Rapid, sensitive, selective and portable detection of 2,4,6-trinitrotoluene (TNT) is in high demand for public safety and environmental monitoring. In this study, we reported a smartphone-based system using impedance monitoring for TNT detection. The screen-printed electrodes modified with TNT-specific peptides were used as disposable a biosensor to produce impedance responses to TNT. The responses could be monitored by a hand-held device and send out to smartphone through Bluetooth. Then, the smartphone was used to display TNT responses in real time and report concentration finally. In the measurement, the system was demonstrated to detect TNT at concentration as low as 10(-6) M and distinguish TNT versus different chemicals in high specificity. Thus, the smartphone-based biosensing platform provided a convenient and efficient approach to design portable instruments for chemical detections such as TNT recognition. Copyright © 2015 Elsevier B.V. All rights reserved.

Detection of stator winding faults in induction motors using three-phase current monitoring.

PubMed

Sharifi, Rasool; Ebrahimi, Mohammad

2011-01-01

The objective of this paper is to propose a new method for the detection of inter-turn short circuits in the stator windings of induction motors. In the previous reported methods, the supply voltage unbalance was the major difficulty, and this was solved mostly based on the sequence component impedance or current which are difficult to implement. Some other methods essentially are included in the offline methods. The proposed method is based on the motor current signature analysis and utilizes three phase current spectra to overcome the mentioned problem. Simulation results indicate that under healthy conditions, the rotor slot harmonics have the same magnitude in three phase currents, while under even 1 turn (0.3%) short circuit condition they differ from each other. Although the magnitude of these harmonics depends on the level of unbalanced voltage, they have the same magnitude in three phases in these conditions. Experiments performed under various load, fault, and supply voltage conditions validate the simulation results and demonstrate the effectiveness of the proposed technique. It is shown that the detection of resistive slight short circuits, without sensitivity to supply voltage unbalance is possible. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Robust fault detection of wind energy conversion systems based on dynamic neural networks.

PubMed

Talebi, Nasser; Sadrnia, Mohammad Ali; Darabi, Ahmad

2014-01-01

Occurrence of faults in wind energy conversion systems (WECSs) is inevitable. In order to detect the occurred faults at the appropriate time, avoid heavy economic losses, ensure safe system operation, prevent damage to adjacent relevant systems, and facilitate timely repair of failed components; a fault detection system (FDS) is required. Recurrent neural networks (RNNs) have gained a noticeable position in FDSs and they have been widely used for modeling of complex dynamical systems. One method for designing an FDS is to prepare a dynamic neural model emulating the normal system behavior. By comparing the outputs of the real system and neural model, incidence of the faults can be identified. In this paper, by utilizing a comprehensive dynamic model which contains both mechanical and electrical components of the WECS, an FDS is suggested using dynamic RNNs. The presented FDS detects faults of the generator's angular velocity sensor, pitch angle sensors, and pitch actuators. Robustness of the FDS is achieved by employing an adaptive threshold. Simulation results show that the proposed scheme is capable to detect the faults shortly and it has very low false and missed alarms rate.

Robust Fault Detection of Wind Energy Conversion Systems Based on Dynamic Neural Networks

PubMed Central

Talebi, Nasser; Sadrnia, Mohammad Ali; Darabi, Ahmad

2014-01-01

Occurrence of faults in wind energy conversion systems (WECSs) is inevitable. In order to detect the occurred faults at the appropriate time, avoid heavy economic losses, ensure safe system operation, prevent damage to adjacent relevant systems, and facilitate timely repair of failed components; a fault detection system (FDS) is required. Recurrent neural networks (RNNs) have gained a noticeable position in FDSs and they have been widely used for modeling of complex dynamical systems. One method for designing an FDS is to prepare a dynamic neural model emulating the normal system behavior. By comparing the outputs of the real system and neural model, incidence of the faults can be identified. In this paper, by utilizing a comprehensive dynamic model which contains both mechanical and electrical components of the WECS, an FDS is suggested using dynamic RNNs. The presented FDS detects faults of the generator's angular velocity sensor, pitch angle sensors, and pitch actuators. Robustness of the FDS is achieved by employing an adaptive threshold. Simulation results show that the proposed scheme is capable to detect the faults shortly and it has very low false and missed alarms rate. PMID:24744774

Functional Fault Modeling of a Cryogenic System for Real-Time Fault Detection and Isolation

NASA Technical Reports Server (NTRS)

Ferrell, Bob; Lewis, Mark; Perotti, Jose; Oostdyk, Rebecca; Brown, Barbara

2010-01-01

The purpose of this paper is to present the model development process used to create a Functional Fault Model (FFM) of a liquid hydrogen (L H2) system that will be used for realtime fault isolation in a Fault Detection, Isolation and Recover (FDIR) system. The paper explains th e steps in the model development process and the data products required at each step, including examples of how the steps were performed fo r the LH2 system. It also shows the relationship between the FDIR req uirements and steps in the model development process. The paper concl udes with a description of a demonstration of the LH2 model developed using the process and future steps for integrating the model in a live operational environment.

A vertically aligned carbon nanotube-based impedance sensing biosensor for rapid and high sensitive detection of cancer cells.

PubMed

Abdolahad, Mohammad; Taghinejad, Mohammad; Taghinejad, Hossein; Janmaleki, Mohsen; Mohajerzadeh, Shams

2012-03-21

A novel vertically aligned carbon nanotube based electrical cell impedance sensing biosensor (CNT-ECIS) was demonstrated for the first time as a more rapid, sensitive and specific device for the detection of cancer cells. This biosensor is based on the fast entrapment of cancer cells on vertically aligned carbon nanotube arrays and leads to mechanical and electrical interactions between CNT tips and entrapped cell membranes, changing the impedance of the biosensor. CNT-ECIS was fabricated through a photolithography process on Ni/SiO(2)/Si layers. Carbon nanotube arrays have been grown on 9 nm thick patterned Ni microelectrodes by DC-PECVD. SW48 colon cancer cells were passed over the surface of CNT covered electrodes to be specifically entrapped on elastic nanotube beams. CNT arrays act as both adhesive and conductive agents and impedance changes occurred as fast as 30 s (for whole entrapment and signaling processes). CNT-ECIS detected the cancer cells with the concentration as low as 4000 cells cm(-2) on its surface and a sensitivity of 1.7 × 10(-3)Ω cm(2). Time and cell efficiency factor (TEF and CEF) parameters were defined which describe the sensor's rapidness and resolution, respectively. TEF and CEF of CNT-ECIS were much higher than other cell based electrical biosensors which are compared in this paper.

Integrated ensemble noise-reconstructed empirical mode decomposition for mechanical fault detection

NASA Astrophysics Data System (ADS)

Yuan, Jing; Ji, Feng; Gao, Yuan; Zhu, Jun; Wei, Chenjun; Zhou, Yu

2018-05-01

A new branch of fault detection is utilizing the noise such as enhancing, adding or estimating the noise so as to improve the signal-to-noise ratio (SNR) and extract the fault signatures. Hereinto, ensemble noise-reconstructed empirical mode decomposition (ENEMD) is a novel noise utilization method to ameliorate the mode mixing and denoised the intrinsic mode functions (IMFs). Despite the possibility of superior performance in detecting weak and multiple faults, the method still suffers from the major problems of the user-defined parameter and the powerless capability for a high SNR case. Hence, integrated ensemble noise-reconstructed empirical mode decomposition is proposed to overcome the drawbacks, improved by two noise estimation techniques for different SNRs as well as the noise estimation strategy. Independent from the artificial setup, the noise estimation by the minimax thresholding is improved for a low SNR case, which especially shows an outstanding interpretation for signature enhancement. For approximating the weak noise precisely, the noise estimation by the local reconfiguration using singular value decomposition (SVD) is proposed for a high SNR case, which is particularly powerful for reducing the mode mixing. Thereinto, the sliding window for projecting the phase space is optimally designed by the correlation minimization. Meanwhile, the reasonable singular order for the local reconfiguration to estimate the noise is determined by the inflection point of the increment trend of normalized singular entropy. Furthermore, the noise estimation strategy, i.e. the selection approaches of the two estimation techniques along with the critical case, is developed and discussed for different SNRs by means of the possible noise-only IMF family. The method is validated by the repeatable simulations to demonstrate the synthetical performance and especially confirm the capability of noise estimation. Finally, the method is applied to detect the local wear fault

An Integrated Fault Tolerant Robotic Controller System for High Reliability and Safety

NASA Technical Reports Server (NTRS)

Marzwell, Neville I.; Tso, Kam S.; Hecht, Myron

1994-01-01

This paper describes the concepts and features of a fault-tolerant intelligent robotic control system being developed for applications that require high dependability (reliability, availability, and safety). The system consists of two major elements: a fault-tolerant controller and an operator workstation. The fault-tolerant controller uses a strategy which allows for detection and recovery of hardware, operating system, and application software failures.The fault-tolerant controller can be used by itself in a wide variety of applications in industry, process control, and communications. The controller in combination with the operator workstation can be applied to robotic applications such as spaceborne extravehicular activities, hazardous materials handling, inspection and maintenance of high value items (e.g., space vehicles, reactor internals, or aircraft), medicine, and other tasks where a robot system failure poses a significant risk to life or property.

Process fault detection and nonlinear time series analysis for anomaly detection in safeguards

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

Burr, T.L.; Mullen, M.F.; Wangen, L.E.

In this paper we discuss two advanced techniques, process fault detection and nonlinear time series analysis, and apply them to the analysis of vector-valued and single-valued time-series data. We investigate model-based process fault detection methods for analyzing simulated, multivariate, time-series data from a three-tank system. The model-predictions are compared with simulated measurements of the same variables to form residual vectors that are tested for the presence of faults (possible diversions in safeguards terminology). We evaluate two methods, testing all individual residuals with a univariate z-score and testing all variables simultaneously with the Mahalanobis distance, for their ability to detect lossmore » of material from two different leak scenarios from the three-tank system: a leak without and with replacement of the lost volume. Nonlinear time-series analysis tools were compared with the linear methods popularized by Box and Jenkins. We compare prediction results using three nonlinear and two linear modeling methods on each of six simulated time series: two nonlinear and four linear. The nonlinear methods performed better at predicting the nonlinear time series and did as well as the linear methods at predicting the linear values.« less

Signal injection as a fault detection technique.

PubMed

Cusidó, Jordi; Romeral, Luis; Ortega, Juan Antonio; Garcia, Antoni; Riba, Jordi

2011-01-01

Double frequency tests are used for evaluating stator windings and analyzing the temperature. Likewise, signal injection on induction machines is used on sensorless motor control fields to find out the rotor position. Motor Current Signature Analysis (MCSA), which focuses on the spectral analysis of stator current, is the most widely used method for identifying faults in induction motors. Motor faults such as broken rotor bars, bearing damage and eccentricity of the rotor axis can be detected. However, the method presents some problems at low speed and low torque, mainly due to the proximity between the frequencies to be detected and the small amplitude of the resulting harmonics. This paper proposes the injection of an additional voltage into the machine being tested at a frequency different from the fundamental one, and then studying the resulting harmonics around the new frequencies appearing due to the composition between injected and main frequencies.

Signal Injection as a Fault Detection Technique

PubMed Central

Cusidó, Jordi; Romeral, Luis; Ortega, Juan Antonio; Garcia, Antoni; Riba, Jordi

2011-01-01

Double frequency tests are used for evaluating stator windings and analyzing the temperature. Likewise, signal injection on induction machines is used on sensorless motor control fields to find out the rotor position. Motor Current Signature Analysis (MCSA), which focuses on the spectral analysis of stator current, is the most widely used method for identifying faults in induction motors. Motor faults such as broken rotor bars, bearing damage and eccentricity of the rotor axis can be detected. However, the method presents some problems at low speed and low torque, mainly due to the proximity between the frequencies to be detected and the small amplitude of the resulting harmonics. This paper proposes the injection of an additional voltage into the machine being tested at a frequency different from the fundamental one, and then studying the resulting harmonics around the new frequencies appearing due to the composition between injected and main frequencies. PMID:22163801

Advanced power system protection and incipient fault detection and protection of spaceborne power systems

NASA Technical Reports Server (NTRS)

Russell, B. Don

1989-01-01

This research concentrated on the application of advanced signal processing, expert system, and digital technologies for the detection and control of low grade, incipient faults on spaceborne power systems. The researchers have considerable experience in the application of advanced digital technologies and the protection of terrestrial power systems. This experience was used in the current contracts to develop new approaches for protecting the electrical distribution system in spaceborne applications. The project was divided into three distinct areas: (1) investigate the applicability of fault detection algorithms developed for terrestrial power systems to the detection of faults in spaceborne systems; (2) investigate the digital hardware and architectures required to monitor and control spaceborne power systems with full capability to implement new detection and diagnostic algorithms; and (3) develop a real-time expert operating system for implementing diagnostic and protection algorithms. Significant progress has been made in each of the above areas. Several terrestrial fault detection algorithms were modified to better adapt to spaceborne power system environments. Several digital architectures were developed and evaluated in light of the fault detection algorithms.

Neural adaptive observer-based sensor and actuator fault detection in nonlinear systems: Application in UAV.

PubMed

Abbaspour, Alireza; Aboutalebi, Payam; Yen, Kang K; Sargolzaei, Arman

2017-03-01

A new online detection strategy is developed to detect faults in sensors and actuators of unmanned aerial vehicle (UAV) systems. In this design, the weighting parameters of the Neural Network (NN) are updated by using the Extended Kalman Filter (EKF). Online adaptation of these weighting parameters helps to detect abrupt, intermittent, and incipient faults accurately. We apply the proposed fault detection system to a nonlinear dynamic model of the WVU YF-22 unmanned aircraft for its evaluation. The simulation results show that the new method has better performance in comparison with conventional recurrent neural network-based fault detection strategies. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Space shuttle main engine fault detection using neural networks

NASA Technical Reports Server (NTRS)

Bishop, Thomas; Greenwood, Dan; Shew, Kenneth; Stevenson, Fareed

1991-01-01

A method for on-line Space Shuttle Main Engine (SSME) anomaly detection and fault typing using a feedback neural network is described. The method involves the computation of features representing time-variance of SSME sensor parameters, using historical test case data. The network is trained, using backpropagation, to recognize a set of fault cases. The network is then able to diagnose new fault cases correctly. An essential element of the training technique is the inclusion of randomly generated data along with the real data, in order to span the entire input space of potential non-nominal data.

Advanced Information Processing System - Fault detection and error handling

NASA Technical Reports Server (NTRS)

Lala, J. H.

1985-01-01

The Advanced Information Processing System (AIPS) is designed to provide a fault tolerant and damage tolerant data processing architecture for a broad range of aerospace vehicles, including tactical and transport aircraft, and manned and autonomous spacecraft. A proof-of-concept (POC) system is now in the detailed design and fabrication phase. This paper gives an overview of a preliminary fault detection and error handling philosophy in AIPS.

Sensitivity of PZT Impedance Sensors for Damage Detection of Concrete Structures

PubMed Central

Yang, Yaowen; Hu, Yuhang; Lu, Yong

2008-01-01

Piezoelectric ceramic Lead Zirconate Titanate (PZT) based electro-mechanical impedance (EMI) technique for structural health monitoring (SHM) has been successfully applied to various engineering systems. However, fundamental research work on the sensitivity of the PZT impedance sensors for damage detection is still in need. In the traditional EMI method, the PZT electro-mechanical (EM) admittance (inverse of the impedance) is used as damage indicator, which is difficult to specify the effect of damage on structural properties. This paper uses the structural mechanical impedance (SMI) extracted from the PZT EM admittance signature as the damage indicator. A comparison study on the sensitivity of the EM admittance and the structural mechanical impedance to the damages in a concrete structure is conducted. Results show that the SMI is more sensitive to the damage than the EM admittance thus a better indicator for damage detection. Furthermore, this paper proposes a dynamic system consisting of a number of single-degree-of-freedom elements with mass, spring and damper components to model the SMI. A genetic algorithm is employed to search for the optimal value of the unknown parameters in the dynamic system. An experiment is carried out on a two-storey concrete frame subjected to base vibrations that simulate earthquake. A number of PZT sensors are regularly arrayed and bonded to the frame structure to acquire PZT EM admittance signatures. The relationship between the damage index and the distance of the PZT sensor from the damage is studied. Consequently, the sensitivity of the PZT sensors is discussed and their sensing region in concrete is derived. PMID:27879711

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.

Insulator-based DEP with impedance measurements for analyte detection

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

Davalos, Rafael V.; Simmons, Blake A.; Crocker, Robert W.

2010-03-16

Disclosed herein are microfluidic devices for assaying at least one analyte specie in a sample comprising at least one analyte concentration area in a microchannel having insulating structures on or in at least one wall of the microchannel which provide a nonuniform electric field in the presence of an electric field provided by off-chip electrodes; and a pair of passivated sensing electrodes for impedance detection in a detection area. Also disclosed are assay methods and methods of making.

High-efficient and high-content cytotoxic recording via dynamic and continuous cell-based impedance biosensor technology.

PubMed

Hu, Ning; Fang, Jiaru; Zou, Ling; Wan, Hao; Pan, Yuxiang; Su, Kaiqi; Zhang, Xi; Wang, Ping

2016-10-01

Cell-based bioassays were effective method to assess the compound toxicity by cell viability, and the traditional label-based methods missed much information of cell growth due to endpoint detection, while the higher throughputs were demanded to obtain dynamic information. Cell-based biosensor methods can dynamically and continuously monitor with cell viability, however, the dynamic information was often ignored or seldom utilized in the toxin and drug assessment. Here, we reported a high-efficient and high-content cytotoxic recording method via dynamic and continuous cell-based impedance biosensor technology. The dynamic cell viability, inhibition ratio and growth rate were derived from the dynamic response curves from the cell-based impedance biosensor. The results showed that the biosensors has the dose-dependent manners to diarrhetic shellfish toxin, okadiac acid based on the analysis of the dynamic cell viability and cell growth status. Moreover, the throughputs of dynamic cytotoxicity were compared between cell-based biosensor methods and label-based endpoint methods. This cell-based impedance biosensor can provide a flexible, cost and label-efficient platform of cell viability assessment in the shellfish toxin screening fields.

Set-membership fault detection under noisy environment with application to the detection of abnormal aircraft control surface positions

NASA Astrophysics Data System (ADS)

El Houda Thabet, Rihab; Combastel, Christophe; Raïssi, Tarek; Zolghadri, Ali

2015-09-01

The paper develops a set membership detection methodology which is applied to the detection of abnormal positions of aircraft control surfaces. Robust and early detection of such abnormal positions is an important issue for early system reconfiguration and overall optimisation of aircraft design. In order to improve fault sensitivity while ensuring a high level of robustness, the method combines a data-driven characterisation of noise and a model-driven approach based on interval prediction. The efficiency of the proposed methodology is illustrated through simulation results obtained based on data recorded in several flight scenarios of a highly representative aircraft benchmark.

Spontaneous non-volcanic tremor detected in the Anza Seismic Gap of San Jacinto Fault

NASA Astrophysics Data System (ADS)

Hutchison, A. A.; Ghosh, A.

2017-12-01

Non-volcanic tremor (NVT), a type of slow earthquake, is becoming more frequently detected along plate boundaries, particularly in subduction zones, and is also observed along the San Andreas Fault [e.g. Nadeau & Dolenc, 2005]. NVT is typically associated with transient deformation (i.e. slow slip) in the transition zone [e.g. Ide et al., 2007], and at times it is observed with deep creep along faults [e.g. Beroza & Ide, 2011]. Using several independent location and detection methods including multi-beam backprojection [Ghosh et al., 2009a; 2012], envelope cross correlation [Wech & Creager, 2008], spectral analyses and visual inspection of existing network stations and high-density mini seismic array data, we detect multiple discrete spontaneous tremor events in the Anza Gap of the San Jacinto Fault (SJF) in June, 2011. The events occur on the SJF where the Hot Springs Fault terminates, on the northwestern boundary of the Anza Gap, below the inferred seismogenic zone characterized by velocity weakening frictional behavior [e.g. Lindsay et al., 2014]. The location methods provide consistent locations for each event in our catalog. Low slowness values help rule-out surface noise that may result in false detections. Analyses of frequency spectra show these time windows are depleted in high frequency energy in the displacement amplitude spectrum compared to small local regular (fast) earthquakes. This spectral pattern is characteristic of tremor [Shelly et al., 2007]. We interpret this tremor to be a seismic manifestation of slow-slip events below the seismogenic zone. Recently, an independent geodetic study suggests that the 2010 El Mayor-Cucupah earthquake triggered a slow-slip event in the Anza Gap [Inbal et al., 2017]. In addition, multiple studies infer deep creep in the SJF [e.g. Meng & Peng et al., 2016; Jiang & Fialko, 2016] indicating that this fault is capable of producing slow slip events. Transient tectonic behavior like tremor and slow slip may be playing

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.

All row, planar fault detection system

DOEpatents

Archer, Charles Jens; Pinnow, Kurt Walter; Ratterman, Joseph D; Smith, Brian Edward

2013-07-23

An apparatus, program product and method for detecting nodal faults may simultaneously cause designated nodes of a cell to communicate with all nodes adjacent to each of the designated nodes. Furthermore, all nodes along the axes of the designated nodes are made to communicate with their adjacent nodes, and the communications are analyzed to determine if a node or connection is faulty.

Gear-box fault detection using time-frequency based methods

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

Odgaard, Peter Fogh; Stoustrup, Jakob

2015-01-01

Gear-box fault monitoring and detection is important for optimization of power generation and availability of wind turbines. The current industrial approach is to use condition monitoring systems, which runs in parallel with the wind turbine control system, using expensive additional sensors. An alternative would be to use the existing measurements which are normally available for the wind turbine control system. The usage of these sensors instead would cut down the cost of the wind turbine by not using additional sensors. One of these available measurements is the generator speed, in which changes in the gear-box resonance frequency can be detected.more » Two different time-frequency based approaches are presented in this paper. One is a filter based approach and the other is based on a Karhunen-Loeve basis. Both of them detects the gear-box fault with an acceptable detection delay.« less

Fault detection and diagnosis of photovoltaic systems

NASA Astrophysics Data System (ADS)

Wu, Xing

The rapid growth of the solar industry over the past several years has expanded the significance of photovoltaic (PV) systems. One of the primary aims of research in building-integrated PV systems is to improve the performance of the system's efficiency, availability, and reliability. Although much work has been done on technological design to increase a photovoltaic module's efficiency, there is little research so far on fault diagnosis for PV systems. Faults in a PV system, if not detected, may not only reduce power generation, but also threaten the availability and reliability, effectively the "security" of the whole system. In this paper, first a circuit-based simulation baseline model of a PV system with maximum power point tracking (MPPT) is developed using MATLAB software. MATLAB is one of the most popular tools for integrating computation, visualization and programming in an easy-to-use modeling environment. Second, data collection of a PV system at variable surface temperatures and insolation levels under normal operation is acquired. The developed simulation model of PV system is then calibrated and improved by comparing modeled I-V and P-V characteristics with measured I--V and P--V characteristics to make sure the simulated curves are close to those measured values from the experiments. Finally, based on the circuit-based simulation model, a PV model of various types of faults will be developed by changing conditions or inputs in the MATLAB model, and the I--V and P--V characteristic curves, and the time-dependent voltage and current characteristics of the fault modalities will be characterized for each type of fault. These will be developed as benchmark I-V or P-V, or prototype transient curves. If a fault occurs in a PV system, polling and comparing actual measured I--V and P--V characteristic curves with both normal operational curves and these baseline fault curves will aid in fault diagnosis.

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.

System and method for motor fault detection using stator current noise cancellation

DOEpatents

Zhou, Wei; Lu, Bin; Nowak, Michael P.; Dimino, Steven A.

2010-12-07

A system and method for detecting incipient mechanical motor faults by way of current noise cancellation is disclosed. The system includes a controller configured to detect indicia of incipient mechanical motor faults. The controller further includes a processor programmed to receive a baseline set of current data from an operating motor and define a noise component in the baseline set of current data. The processor is also programmed to acquire at least on additional set of real-time operating current data from the motor during operation, redefine the noise component present in each additional set of real-time operating current data, and remove the noise component from the operating current data in real-time to isolate any fault components present in the operating current data. The processor is then programmed to generate a fault index for the operating current data based on any isolated fault components.

Hybrid Model-Based and Data-Driven Fault Detection and Diagnostics for Commercial Buildings: Preprint

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

Frank, Stephen; Heaney, Michael; Jin, Xin

Commercial buildings often experience faults that produce undesirable behavior in building systems. Building faults waste energy, decrease occupants' comfort, and increase operating costs. Automated fault detection and diagnosis (FDD) tools for buildings help building owners discover and identify the root causes of faults in building systems, equipment, and controls. Proper implementation of FDD has the potential to simultaneously improve comfort, reduce energy use, and narrow the gap between actual and optimal building performance. However, conventional rule-based FDD requires expensive instrumentation and valuable engineering labor, which limit deployment opportunities. This paper presents a hybrid, automated FDD approach that combines building energymore » models and statistical learning tools to detect and diagnose faults noninvasively, using minimal sensors, with little customization. We compare and contrast the performance of several hybrid FDD algorithms for a small security building. Our results indicate that the algorithms can detect and diagnose several common faults, but more work is required to reduce false positive rates and improve diagnosis accuracy.« less

Fault detection in mechanical systems with friction phenomena: an online neural approximation approach.

PubMed

Papadimitropoulos, Adam; Rovithakis, George A; Parisini, Thomas

2007-07-01

In this paper, the problem of fault detection in mechanical systems performing linear motion, under the action of friction phenomena is addressed. The friction effects are modeled through the dynamic LuGre model. The proposed architecture is built upon an online neural network (NN) approximator, which requires only system's position and velocity. The friction internal state is not assumed to be available for measurement. The neural fault detection methodology is analyzed with respect to its robustness and sensitivity properties. Rigorous fault detectability conditions and upper bounds for the detection time are also derived. Extensive simulation results showing the effectiveness of the proposed methodology are provided, including a real case study on an industrial actuator.

Runtime Verification in Context : Can Optimizing Error Detection Improve Fault Diagnosis

NASA Technical Reports Server (NTRS)

Dwyer, Matthew B.; Purandare, Rahul; Person, Suzette

2010-01-01

Runtime verification has primarily been developed and evaluated as a means of enriching the software testing process. While many researchers have pointed to its potential applicability in online approaches to software fault tolerance, there has been a dearth of work exploring the details of how that might be accomplished. In this paper, we describe how a component-oriented approach to software health management exposes the connections between program execution, error detection, fault diagnosis, and recovery. We identify both research challenges and opportunities in exploiting those connections. Specifically, we describe how recent approaches to reducing the overhead of runtime monitoring aimed at error detection might be adapted to reduce the overhead and improve the effectiveness of fault diagnosis.

Application of fault factor method to fault detection and diagnosis for space shuttle main engine

NASA Astrophysics Data System (ADS)

Cha, Jihyoung; Ha, Chulsu; Ko, Sangho; Koo, Jaye

2016-09-01

This paper deals with an application of the multiple linear regression algorithm to fault detection and diagnosis for the space shuttle main engine (SSME) during a steady state. In order to develop the algorithm, the energy balance equations, which balances the relation among pressure, mass flow rate and power at various locations within the SSME, are obtained. Then using the measurement data of some important parameters of the engine, fault factors which reflects the deviation of each equation from the normal state are estimated. The probable location of each fault and the levels of severity can be obtained from the estimated fault factors. This process is numerically demonstrated for the SSME at 104% Rated Propulsion Level (RPL) by using the simulated measurement data from the mathematical models of the engine. The result of the current study is particularly important considering that the recently developed reusable Liquid Rocket Engines (LREs) have staged-combustion cycles similarly to the SSME.

Modeling of electrical impedance tomography to detect breast cancer by finite volume methods

NASA Astrophysics Data System (ADS)

Ain, K.; Wibowo, R. A.; Soelistiono, S.

2017-05-01

The properties of the electrical impedance of tissue are an interesting study, because changes of the electrical impedance of organs are related to physiological and pathological. Both physiological and pathological properties are strongly associated with disease information. Several experiments shown that the breast cancer has a lower impedance than the normal breast tissue. Thus, the imaging based on impedance can be used as an alternative equipment to detect the breast cancer. This research carries out by modelling of Electrical Impedance Tomography to detect the breast cancer by finite volume methods. The research includes development of a mathematical model of the electric potential field by 2D Finite Volume Method, solving the forward problem and inverse problem by linear reconstruction method. The scanning is done by 16 channel electrode with neighbors method to collect data. The scanning is performed at a frequency of 10 kHz and 100 kHz with three objects numeric includes an anomaly at the surface, an anomaly at the depth and an anomaly at the surface and at depth. The simulation has been successfully to reconstruct image of functional anomalies of the breast cancer at the surface position, the depth position or a combination of surface and the depth.

Wind turbine fault detection and classification by means of image texture analysis

NASA Astrophysics Data System (ADS)

Ruiz, Magda; Mujica, Luis E.; Alférez, Santiago; Acho, Leonardo; Tutivén, Christian; Vidal, Yolanda; Rodellar, José; Pozo, Francesc

2018-07-01

The future of the wind energy industry passes through the use of larger and more flexible wind turbines in remote locations, which are increasingly offshore to benefit stronger and more uniform wind conditions. The cost of operation and maintenance of offshore wind turbines is approximately 15-35% of the total cost. Of this, 80% goes towards unplanned maintenance issues due to different faults in the wind turbine components. Thus, an auspicious way to contribute to the increasing demands and challenges is by applying low-cost advanced fault detection schemes. This work proposes a new method for detection and classification of wind turbine actuators and sensors faults in variable-speed wind turbines. For this purpose, time domain signals acquired from the operating wind turbine are represented as two-dimensional matrices to obtain grayscale digital images. Then, the image pattern recognition is processed getting texture features under a multichannel representation. In this work, four types of texture characteristics are used: statistical, wavelet, granulometric and Gabor features. Next, the most significant ones are selected using the conditional mutual criterion. Finally, the faults are detected and distinguished between them (classified) using an automatic classification tool. In particular, a 10-fold cross-validation is used to obtain a more generalized model and evaluates the classification performance. Coupled non-linear aero-hydro-servo-elastic simulations of a 5 MW offshore type wind turbine are carried out in several fault scenarios. The results show a promising methodology able to detect and classify the most common wind turbine faults.

An adaptive confidence limit for periodic non-steady conditions fault detection

NASA Astrophysics Data System (ADS)

Wang, Tianzhen; Wu, Hao; Ni, Mengqi; Zhang, Milu; Dong, Jingjing; Benbouzid, Mohamed El Hachemi; Hu, Xiong

2016-05-01

System monitoring has become a major concern in batch process due to the fact that failure rate in non-steady conditions is much higher than in steady ones. A series of approaches based on PCA have already solved problems such as data dimensionality reduction, multivariable decorrelation, and processing non-changing signal. However, if the data follows non-Gaussian distribution or the variables contain some signal changes, the above approaches are not applicable. To deal with these concerns and to enhance performance in multiperiod data processing, this paper proposes a fault detection method using adaptive confidence limit (ACL) in periodic non-steady conditions. The proposed ACL method achieves four main enhancements: Longitudinal-Standardization could convert non-Gaussian sampling data to Gaussian ones; the multiperiod PCA algorithm could reduce dimensionality, remove correlation, and improve the monitoring accuracy; the adaptive confidence limit could detect faults under non-steady conditions; the fault sections determination procedure could select the appropriate parameter of the adaptive confidence limit. The achieved result analysis clearly shows that the proposed ACL method is superior to other fault detection approaches under periodic non-steady conditions.

Fuzzy model-based fault detection and diagnosis for a pilot heat exchanger

NASA Astrophysics Data System (ADS)

Habbi, Hacene; Kidouche, Madjid; Kinnaert, Michel; Zelmat, Mimoun

2011-04-01

This article addresses the design and real-time implementation of a fuzzy model-based fault detection and diagnosis (FDD) system for a pilot co-current heat exchanger. The design method is based on a three-step procedure which involves the identification of data-driven fuzzy rule-based models, the design of a fuzzy residual generator and the evaluation of the residuals for fault diagnosis using statistical tests. The fuzzy FDD mechanism has been implemented and validated on the real co-current heat exchanger, and has been proven to be efficient in detecting and isolating process, sensor and actuator faults.

From experiment to design -- Fault characterization and detection in parallel computer systems using computational accelerators

NASA Astrophysics Data System (ADS)

Yim, Keun Soo

This dissertation summarizes experimental validation and co-design studies conducted to optimize the fault detection capabilities and overheads in hybrid computer systems (e.g., using CPUs and Graphics Processing Units, or GPUs), and consequently to improve the scalability of parallel computer systems using computational accelerators. The experimental validation studies were conducted to help us understand the failure characteristics of CPU-GPU hybrid computer systems under various types of hardware faults. The main characterization targets were faults that are difficult to detect and/or recover from, e.g., faults that cause long latency failures (Ch. 3), faults in dynamically allocated resources (Ch. 4), faults in GPUs (Ch. 5), faults in MPI programs (Ch. 6), and microarchitecture-level faults with specific timing features (Ch. 7). The co-design studies were based on the characterization results. One of the co-designed systems has a set of source-to-source translators that customize and strategically place error detectors in the source code of target GPU programs (Ch. 5). Another co-designed system uses an extension card to learn the normal behavioral and semantic execution patterns of message-passing processes executing on CPUs, and to detect abnormal behaviors of those parallel processes (Ch. 6). The third co-designed system is a co-processor that has a set of new instructions in order to support software-implemented fault detection techniques (Ch. 7). The work described in this dissertation gains more importance because heterogeneous processors have become an essential component of state-of-the-art supercomputers. GPUs were used in three of the five fastest supercomputers that were operating in 2011. Our work included comprehensive fault characterization studies in CPU-GPU hybrid computers. In CPUs, we monitored the target systems for a long period of time after injecting faults (a temporally comprehensive experiment), and injected faults into various types of

Sinusoidal synthesis based adaptive tracking for rotating machinery fault detection

NASA Astrophysics Data System (ADS)

Li, Gang; McDonald, Geoff L.; Zhao, Qing

2017-01-01

This paper presents a novel Sinusoidal Synthesis Based Adaptive Tracking (SSBAT) technique for vibration-based rotating machinery fault detection. The proposed SSBAT algorithm is an adaptive time series technique that makes use of both frequency and time domain information of vibration signals. Such information is incorporated in a time varying dynamic model. Signal tracking is then realized by applying adaptive sinusoidal synthesis to the vibration signal. A modified Least-Squares (LS) method is adopted to estimate the model parameters. In addition to tracking, the proposed vibration synthesis model is mainly used as a linear time-varying predictor. The health condition of the rotating machine is monitored by checking the residual between the predicted and measured signal. The SSBAT method takes advantage of the sinusoidal nature of vibration signals and transfers the nonlinear problem into a linear adaptive problem in the time domain based on a state-space realization. It has low computation burden and does not need a priori knowledge of the machine under the no-fault condition which makes the algorithm ideal for on-line fault detection. The method is validated using both numerical simulation and practical application data. Meanwhile, the fault detection results are compared with the commonly adopted autoregressive (AR) and autoregressive Minimum Entropy Deconvolution (ARMED) method to verify the feasibility and performance of the SSBAT method.

In-flight Fault Detection and Isolation in Aircraft Flight Control Systems

NASA Technical Reports Server (NTRS)

Azam, Mohammad; Pattipati, Krishna; Allanach, Jeffrey; Poll, Scott; Patterson-Hine, Ann

2005-01-01

In this paper we consider the problem of test design for real-time fault detection and isolation (FDI) in the flight control system of fixed-wing aircraft. We focus on the faults that are manifested in the control surface elements (e.g., aileron, elevator, rudder and stabilizer) of an aircraft. For demonstration purposes, we restrict our focus on the faults belonging to nine basic fault classes. The diagnostic tests are performed on the features extracted from fifty monitored system parameters. The proposed tests are able to uniquely isolate each of the faults at almost all severity levels. A neural network-based flight control simulator, FLTZ(Registered TradeMark), is used for the simulation of various faults in fixed-wing aircraft flight control systems for the purpose of FDI.

Fault-tolerant quantum error detection.

PubMed

Linke, Norbert M; Gutierrez, Mauricio; Landsman, Kevin A; Figgatt, Caroline; Debnath, Shantanu; Brown, Kenneth R; Monroe, Christopher

2017-10-01

Quantum computers will eventually reach a size at which quantum error correction becomes imperative. Quantum information can be protected from qubit imperfections and flawed control operations by encoding a single logical qubit in multiple physical qubits. This redundancy allows the extraction of error syndromes and the subsequent detection or correction of errors without destroying the logical state itself through direct measurement. We show the encoding and syndrome measurement of a fault-tolerantly prepared logical qubit via an error detection protocol on four physical qubits, represented by trapped atomic ions. This demonstrates the robustness of a logical qubit to imperfections in the very operations used to encode it. The advantage persists in the face of large added error rates and experimental calibration errors.

Fault-tolerant quantum error detection

PubMed Central

Linke, Norbert M.; Gutierrez, Mauricio; Landsman, Kevin A.; Figgatt, Caroline; Debnath, Shantanu; Brown, Kenneth R.; Monroe, Christopher

2017-01-01

Quantum computers will eventually reach a size at which quantum error correction becomes imperative. Quantum information can be protected from qubit imperfections and flawed control operations by encoding a single logical qubit in multiple physical qubits. This redundancy allows the extraction of error syndromes and the subsequent detection or correction of errors without destroying the logical state itself through direct measurement. We show the encoding and syndrome measurement of a fault-tolerantly prepared logical qubit via an error detection protocol on four physical qubits, represented by trapped atomic ions. This demonstrates the robustness of a logical qubit to imperfections in the very operations used to encode it. The advantage persists in the face of large added error rates and experimental calibration errors. PMID:29062889

Usage of Fault Detection Isolation & Recovery (FDIR) in Constellation (CxP) Launch Operations

NASA Technical Reports Server (NTRS)

Ferrell, Rob; Lewis, Mark; Perotti, Jose; Oostdyk, Rebecca; Spirkovska, Lilly; Hall, David; Brown, Barbara

2010-01-01

This paper will explore the usage of Fault Detection Isolation & Recovery (FDIR) in the Constellation Exploration Program (CxP), in particular Launch Operations at Kennedy Space Center (KSC). NASA's Exploration Technology Development Program (ETDP) is currently funding a project that is developing a prototype FDIR to demonstrate the feasibility of incorporating FDIR into the CxP Ground Operations Launch Control System (LCS). An architecture that supports multiple FDIR tools has been formulated that will support integration into the CxP Ground Operation's Launch Control System (LCS). In addition, tools have been selected that provide fault detection, fault isolation, and anomaly detection along with integration between Flight and Ground elements.

Compressive Sensing of Roller Bearing Faults via Harmonic Detection from Under-Sampled Vibration Signals

PubMed Central

Tang, Gang; Hou, Wei; Wang, Huaqing; Luo, Ganggang; Ma, Jianwei

2015-01-01

The Shannon sampling principle requires substantial amounts of data to ensure the accuracy of on-line monitoring of roller bearing fault signals. Challenges are often encountered as a result of the cumbersome data monitoring, thus a novel method focused on compressed vibration signals for detecting roller bearing faults is developed in this study. Considering that harmonics often represent the fault characteristic frequencies in vibration signals, a compressive sensing frame of characteristic harmonics is proposed to detect bearing faults. A compressed vibration signal is first acquired from a sensing matrix with information preserved through a well-designed sampling strategy. A reconstruction process of the under-sampled vibration signal is then pursued as attempts are conducted to detect the characteristic harmonics from sparse measurements through a compressive matching pursuit strategy. In the proposed method bearing fault features depend on the existence of characteristic harmonics, as typically detected directly from compressed data far before reconstruction completion. The process of sampling and detection may then be performed simultaneously without complete recovery of the under-sampled signals. The effectiveness of the proposed method is validated by simulations and experiments. PMID:26473858

A novel broadband impedance method for detection of cell-derived microparticles

PubMed Central

Lvovich, Vadim; Srikanthan, Sowmya; Silverstein, Roy L.

2010-01-01

A novel label-free method is presented to detect and quantify cell-derived microparticles (MPs) by the electrochemical potential-modulated electrochemical impedance spectroscopy (EIS). MPs are present in elevated concentrations during pathological conditions and play a major role in the establishment and pathogenesis of many diseases. Considering this, accurate detection and quantification of MPs is very important in clinical diagnostics and therapeutics. A combination of bulk solution electrokinetic sorting and interfacial impedance responses allows achieving detection limits as low as several MPs per µL. By fitting resulting EIS spectra with an equivalent electrical circuit, the bulk solution electrokinetic and interfacial impedance responses were characterized. In the bulk solution two major relaxations were prominent - β-relaxation in low MHz region due to the MP capacitive membrane bridging, and α-relaxation at ∼ 10 kHz due to counter ions diffusion. At low frequencies (10-0.1 Hz) at electrochemical potentials exceeding −100 mV, a facile interfacial Faradaic process of oxidation in MPs coupled with diffusion and non Faradaic double layer charging dominate, probably due to oxidation of phospholipids and/or proteins on the MP surface and MP lysis. Buffer influence on the MP detection demonstrated that that a relatively low conductivity Tyrode’s buffer background solution is preferential for the MP electrokinetic separation and characterization. This study also demonstrated that standard laboratory methods such as flow cytometry underestimate MP concentrations, especially those with smaller average sizes, by as much as a factor of 2 to 40. PMID:20729061

A novel broadband impedance method for detection of cell-derived microparticles.

PubMed

Lvovich, Vadim; Srikanthan, Sowmya; Silverstein, Roy L

2010-10-15

A novel label-free method is presented to detect and quantify cell-derived microparticles (MPs) by the electrochemical potential-modulated electrochemical impedance spectroscopy (EIS). MPs are present in elevated concentrations during pathological conditions and play a major role in the establishment and pathogenesis of many diseases. Considering this, accurate detection and quantification of MPs is very important in clinical diagnostics and therapeutics. A combination of bulk solution electrokinetic sorting and interfacial impedance responses allows achieving detection limits as low as several MPs per μL. By fitting resulting EIS spectra with an equivalent electrical circuit, the bulk solution electrokinetic and interfacial impedance responses were characterized. In the bulk solution two major relaxations were prominent-β-relaxation in low MHz region due to the MP capacitive membrane bridging, and α-relaxation at ∼10 kHz due to counter ions diffusion. At low frequencies (10-0.1 Hz) at electrochemical potentials exceeding -100 mV, a facile interfacial Faradaic process of oxidation in MPs coupled with diffusion and non-Faradaic double layer charging dominate, probably due to oxidation of phospholipids and/or proteins on the MP surface and MP lysis. Buffer influence on the MP detection demonstrated that a relatively low conductivity Tyrode's buffer background solution is preferential for the MP electrokinetic separation and characterization. This study also demonstrated that standard laboratory methods such as flow cytometry underestimate MP concentrations, especially those with smaller average sizes, by as much as a factor of 2-40. Copyright © 2010 Elsevier B.V. All rights reserved.

Methodology for fault detection in induction motors via sound and vibration signals

NASA Astrophysics Data System (ADS)

Delgado-Arredondo, Paulo Antonio; Morinigo-Sotelo, Daniel; Osornio-Rios, Roque Alfredo; Avina-Cervantes, Juan Gabriel; Rostro-Gonzalez, Horacio; Romero-Troncoso, Rene de Jesus

2017-01-01

Nowadays, timely maintenance of electric motors is vital to keep up the complex processes of industrial production. There are currently a variety of methodologies for fault diagnosis. Usually, the diagnosis is performed by analyzing current signals at a steady-state motor operation or during a start-up transient. This method is known as motor current signature analysis, which identifies frequencies associated with faults in the frequency domain or by the time-frequency decomposition of the current signals. Fault identification may also be possible by analyzing acoustic sound and vibration signals, which is useful because sometimes this information is the only available. The contribution of this work is a methodology for detecting faults in induction motors in steady-state operation based on the analysis of acoustic sound and vibration signals. This proposed approach uses the Complete Ensemble Empirical Mode Decomposition for decomposing the signal into several intrinsic mode functions. Subsequently, the frequency marginal of the Gabor representation is calculated to obtain the spectral content of the IMF in the frequency domain. This proposal provides good fault detectability results compared to other published works in addition to the identification of more frequencies associated with the faults. The faults diagnosed in this work are two broken rotor bars, mechanical unbalance and bearing defects.

An online outlier identification and removal scheme for improving fault detection performance.

PubMed

Ferdowsi, Hasan; Jagannathan, Sarangapani; Zawodniok, Maciej

2014-05-01

Measured data or states for a nonlinear dynamic system is usually contaminated by outliers. Identifying and removing outliers will make the data (or system states) more trustworthy and reliable since outliers in the measured data (or states) can cause missed or false alarms during fault diagnosis. In addition, faults can make the system states nonstationary needing a novel analytical model-based fault detection (FD) framework. In this paper, an online outlier identification and removal (OIR) scheme is proposed for a nonlinear dynamic system. Since the dynamics of the system can experience unknown changes due to faults, traditional observer-based techniques cannot be used to remove the outliers. The OIR scheme uses a neural network (NN) to estimate the actual system states from measured system states involving outliers. With this method, the outlier detection is performed online at each time instant by finding the difference between the estimated and the measured states and comparing its median with its standard deviation over a moving time window. The NN weight update law in OIR is designed such that the detected outliers will have no effect on the state estimation, which is subsequently used for model-based fault diagnosis. In addition, since the OIR estimator cannot distinguish between the faulty or healthy operating conditions, a separate model-based observer is designed for fault diagnosis, which uses the OIR scheme as a preprocessing unit to improve the FD performance. The stability analysis of both OIR and fault diagnosis schemes are introduced. Finally, a three-tank benchmarking system and a simple linear system are used to verify the proposed scheme in simulations, and then the scheme is applied on an axial piston pump testbed. The scheme can be applied to nonlinear systems whose dynamics and underlying distribution of states are subjected to change due to both unknown faults and operating conditions.

Comparison of three rf plasma impedance monitors on a high phase angle planar inductively coupled plasma source

NASA Astrophysics Data System (ADS)

Uchiyama, H.; Watanabe, M.; Shaw, D. M.; Bahia, J. E.; Collins, G. J.

1999-10-01

Accurate measurement of plasma source impedance is important for verification of plasma circuit models, as well as for plasma process characterization and endpoint detection. Most impedance measurement techniques depend in some manner on the cosine of the phase angle to determine the impedance of the plasma load. Inductively coupled plasmas are generally highly inductive, with the phase angle between the applied rf voltage and the rf current in the range of 88 to near 90 degrees. A small measurement error in this phase angle range results in a large error in the calculated cosine of the angle, introducing large impedance measurement variations. In this work, we have compared the measured impedance of a planar inductively coupled plasma using three commercial plasma impedance monitors (ENI V/I probe, Advanced Energy RFZ60 and Advanced Energy Z-Scan). The plasma impedance is independently verified using a specially designed match network and a calibrated load, representing the plasma, to provide a measurement standard.

Detecting Taiwan's Shanchiao Active Fault Using AMT and Gravity Methods

NASA Astrophysics Data System (ADS)

Liu, H.-C.; Yang, C.-H.

2009-04-01

Taiwan's Shanchiao normal fault runs in a northeast-southwest direction and is located on the western edge of the Taipei Basin in northern Taiwan. The overburden of the fault is late Quaternary sediment with a thickness of approximately a few tenth of a meter to several hundred meters. No detailed studies of the western side of the Shanchiao fault are available. As Taiwan is located on the Neotectonic Belt in the western Pacific, detecting active faults near the Taipei metropolitan area will provide necessary information for further disaster prevention. It is the responsibility of geologists and geophysicists in Taiwan to perform this task. Examination of the resistivity and density contrasts of subsurface layers permits a mapping of the Shanchiao fault and the deformed Tertiary strata of the Taipei Basin. The audio-frequency magnetotelluric (AMT) method and gravity method were chosen for this study. Significant resistivity and gravity anomalies were observed in the suspected fault zone. The interpretation reveals a good correlation between the features of the Shanchiao fault and resistivity and density distribution at depth. In this observation, AMT and gravity methods provides a viable means for mapping the Shanchiao fault position and studying its features associated with the subsidence of the western side of the Taipei Basin. This study indicates the AMT and gravity methods' considerable potential for accurately mapping an active fault.

A Wireless Sensor System for Real-Time Monitoring and Fault Detection of Motor Arrays.

PubMed

Medina-García, Jonathan; Sánchez-Rodríguez, Trinidad; Galán, Juan Antonio Gómez; Delgado, Aránzazu; Gómez-Bravo, Fernando; Jiménez, Raúl

2017-02-25

This paper presents a wireless fault detection system for industrial motors that combines vibration, motor current and temperature analysis, thus improving the detection of mechanical faults. The design also considers the time of detection and further possible actions, which are also important for the early detection of possible malfunctions, and thus for avoiding irreversible damage to the motor. The remote motor condition monitoring is implemented through a wireless sensor network (WSN) based on the IEEE 802.15.4 standard. The deployed network uses the beacon-enabled mode to synchronize several sensor nodes with the coordinator node, and the guaranteed time slot mechanism provides data monitoring with a predetermined latency. A graphic user interface offers remote access to motor conditions and real-time monitoring of several parameters. The developed wireless sensor node exhibits very low power consumption since it has been optimized both in terms of hardware and software. The result is a low cost, highly reliable and compact design, achieving a high degree of autonomy of more than two years with just one 3.3 V/2600 mAh battery. Laboratory and field tests confirm the feasibility of the wireless system.

A Wireless Sensor System for Real-Time Monitoring and Fault Detection of Motor Arrays

PubMed Central

Medina-García, Jonathan; Sánchez-Rodríguez, Trinidad; Galán, Juan Antonio Gómez; Delgado, Aránzazu; Gómez-Bravo, Fernando; Jiménez, Raúl

2017-01-01

This paper presents a wireless fault detection system for industrial motors that combines vibration, motor current and temperature analysis, thus improving the detection of mechanical faults. The design also considers the time of detection and further possible actions, which are also important for the early detection of possible malfunctions, and thus for avoiding irreversible damage to the motor. The remote motor condition monitoring is implemented through a wireless sensor network (WSN) based on the IEEE 802.15.4 standard. The deployed network uses the beacon-enabled mode to synchronize several sensor nodes with the coordinator node, and the guaranteed time slot mechanism provides data monitoring with a predetermined latency. A graphic user interface offers remote access to motor conditions and real-time monitoring of several parameters. The developed wireless sensor node exhibits very low power consumption since it has been optimized both in terms of hardware and software. The result is a low cost, highly reliable and compact design, achieving a high degree of autonomy of more than two years with just one 3.3 V/2600 mAh battery. Laboratory and field tests confirm the feasibility of the wireless system. PMID:28245623

Sonic impedance technique detects flaws in polyurethane foam spray-on insulation

NASA Technical Reports Server (NTRS)

Haralson, H. S.; Haynes, J. L.

1970-01-01

Sonic impedance testing detects voids and unbonded regions as small as 1 inch in diameter by 0.03 inch thick. Measurements are made manually or by automatic scanning and the readout is made by meter or recorder.

Fault healing promotes high-frequency earthquakes in laboratory experiments and on natural faults

USGS Publications Warehouse

McLaskey, Gregory C.; Thomas, Amanda M.; Glaser, Steven D.; Nadeau, Robert M.

2012-01-01

Faults strengthen or heal with time in stationary contact and this healing may be an essential ingredient for the generation of earthquakes. In the laboratory, healing is thought to be the result of thermally activated mechanisms that weld together micrometre-sized asperity contacts on the fault surface, but the relationship between laboratory measures of fault healing and the seismically observable properties of earthquakes is at present not well defined. Here we report on laboratory experiments and seismological observations that show how the spectral properties of earthquakes vary as a function of fault healing time. In the laboratory, we find that increased healing causes a disproportionately large amount of high-frequency seismic radiation to be produced during fault rupture. We observe a similar connection between earthquake spectra and recurrence time for repeating earthquake sequences on natural faults. Healing rates depend on pressure, temperature and mineralogy, so the connection between seismicity and healing may help to explain recent observations of large megathrust earthquakes which indicate that energetic, high-frequency seismic radiation originates from locations that are distinct from the geodetically inferred locations of large-amplitude fault slip

Automated Monitoring with a BSP Fault-Detection Test

NASA Technical Reports Server (NTRS)

Bickford, Randall L.; Herzog, James P.

2003-01-01

The figure schematically illustrates a method and procedure for automated monitoring of an asset, as well as a hardware- and-software system that implements the method and procedure. As used here, asset could signify an industrial process, power plant, medical instrument, aircraft, or any of a variety of other systems that generate electronic signals (e.g., sensor outputs). In automated monitoring, the signals are digitized and then processed in order to detect faults and otherwise monitor operational status and integrity of the monitored asset. The major distinguishing feature of the present method is that the fault-detection function is implemented by use of a Bayesian sequential probability (BSP) technique. This technique is superior to other techniques for automated monitoring because it affords sensitivity, not only to disturbances in the mean values, but also to very subtle changes in the statistical characteristics (variance, skewness, and bias) of the monitored signals.

Effects of Channel Modification on Detection and Dating of Fault Scarps

NASA Astrophysics Data System (ADS)

Sare, R.; Hilley, G. E.

2016-12-01

Template matching of scarp-like features could potentially generate morphologic age estimates for individual scarps over entire regions, but data noise and scarp modification limits detection of fault scarps by this method. Template functions based on diffusion in the cross-scarp direction may fail to accurately date scarps near channel boundaries. Where channels reduce scarp amplitudes, or where cross-scarp noise is significant, signal-to-noise ratios decrease and the scarp may be poorly resolved. In this contribution, we explore the bias in morphologic age of a complex scarp produced by systematic changes in fault scarp curvature. For example, fault scarps may be modified by encroaching channel banks and mass failure, lateral diffusion of material into a channel, or undercutting parallel to the base of a scarp. We quantify such biases on morphologic age estimates using a block offset model subject to two-dimensional linear diffusion. We carry out a synthetic study of the effects of two-dimensional transport on morphologic age calculated using a profile model, and compare these results to a well- studied and constrained site along the San Andreas Fault at Wallace Creek, CA. This study serves as a first step towards defining regions of high confidence in template matching results based on scarp length, channel geometry, and near-scarp topography.

High-rate real-time GPS network at Parkfield: Utility for detecting fault slip and seismic displacements

USGS Publications Warehouse

Langbein, J.; Bock, Y.

2004-01-01

A network of 13 continuous GPS stations near Parkfield, California has been converted from 30 second to 1 second sampling with positions of the stations estimated in real-time relative to a master station. Most stations are near the trace of the San Andreas fault, which exhibits creep. The noise spectra of the instantaneous 1 Hz positions show flicker noise at high frequencies and change to frequency independence at low frequencies; the change in character occurs between 6 to 8 hours. Our analysis indicates that 1-second sampled GPS can estimate horizontal displacements of order 6 mm at the 99% confidence level from a few seconds to a few hours. High frequency GPS can augment existing measurements in capturing large creep events and postseismic slip that would exceed the range of existing creepmeters, and can detect large seismic displacements. Copyright 2004 by the American Geophysical Union.

Fault detection and classification in electrical power transmission system using artificial neural network.

PubMed

Jamil, Majid; Sharma, Sanjeev Kumar; Singh, Rajveer

2015-01-01

This paper focuses on the detection and classification of the faults on electrical power transmission line using artificial neural networks. The three phase currents and voltages of one end are taken as inputs in the proposed scheme. The feed forward neural network along with back propagation algorithm has been employed for detection and classification of the fault for analysis of each of the three phases involved in the process. A detailed analysis with varying number of hidden layers has been performed to validate the choice of the neural network. The simulation results concluded that the present method based on the neural network is efficient in detecting and classifying the faults on transmission lines with satisfactory performances. The different faults are simulated with different parameters to check the versatility of the method. The proposed method can be extended to the Distribution network of the Power System. The various simulations and analysis of signals is done in the MATLAB(®) environment.

Fault detection and isolation in motion monitoring system.

PubMed

Kim, Duk-Jin; Suk, Myoung Hoon; Prabhakaran, B

2012-01-01

Pervasive computing becomes very active research field these days. A watch that can trace human movement to record motion boundary as well as to study of finding social life pattern by one's localized visiting area. Pervasive computing also helps patient monitoring. A daily monitoring system helps longitudinal study of patient monitoring such as Alzheimer's and Parkinson's or obesity monitoring. Due to the nature of monitoring sensor (on-body wireless sensor), however, signal noise or faulty sensors errors can be present at any time. Many research works have addressed these problems any with a large amount of sensor deployment. In this paper, we present the faulty sensor detection and isolation using only two on-body sensors. We have been investigating three different types of sensor errors: the SHORT error, the CONSTANT error, and the NOISY SENSOR error (see more details on section V). Our experimental results show that the success rate of isolating faulty signals are an average of over 91.5% on fault type 1, over 92% on fault type 2, and over 99% on fault type 3 with the fault prior of 30% sensor errors.

Application of fault detection techniques to spiral bevel gear fatigue data

NASA Technical Reports Server (NTRS)

Zakrajsek, James J.; Handschuh, Robert F.; Decker, Harry J.

1994-01-01

Results of applying a variety of gear fault detection techniques to experimental data is presented. A spiral bevel gear fatigue rig was used to initiate a naturally occurring fault and propagate the fault to a near catastrophic condition of the test gear pair. The spiral bevel gear fatigue test lasted a total of eighteen hours. At approximately five and a half hours into the test, the rig was stopped to inspect the gears for damage, at which time a small pit was identified on a tooth of the pinion. The test was then stopped an additional seven times throughout the rest of the test in order to observe and document the growth and propagation of the fault. The test was ended when a major portion of a pinion tooth broke off. A personal computer based diagnostic system was developed to obtain vibration data from the test rig, and to perform the on-line gear condition monitoring. A number of gear fault detection techniques, which use the signal average in both the time and frequency domain, were applied to the experimental data. Among the techniques investigated, two of the recently developed methods appeared to be the first to react to the start of tooth damage. These methods continued to react to the damage as the pitted area grew in size to cover approximately 75% of the face width of the pinion tooth. In addition, information gathered from one of the newer methods was found to be a good accumulative damage indicator. An unexpected result of the test showed that although the speed of the rig was held to within a band of six percent of the nominal speed, and the load within eighteen percent of nominal, the resulting speed and load variations substantially affected the performance of all of the gear fault detection techniques investigated.

Shallow Faulting in Morelia, Mexico, Based on Seismic Tomography and Geodetically Detected Land Subsidence

NASA Astrophysics Data System (ADS)

Cabral-Cano, E.; Arciniega-Ceballos, A.; Vergara-Huerta, F.; Chaussard, E.; Wdowinski, S.; DeMets, C.; Salazar-Tlaczani, L.

2013-12-01

Subsidence has been a common occurrence in several cities in central Mexico for the past three decades. This process causes substantial damage to the urban infrastructure and housing in several cities and it is a major factor to be considered when planning urban development, land-use zoning and hazard mitigation strategies. Since the early 1980's the city of Morelia in Central Mexico has experienced subsidence associated with groundwater extraction in excess of natural recharge from rainfall. Previous works have focused on the detection and temporal evolution of the subsidence spatial distribution. The most recent InSAR analysis confirms the permanence of previously detected rapidly subsiding areas such as the Rio Grande Meander area and also defines 2 subsidence patches previously undetected in the newly developed suburban sectors west of Morelia at the Fraccionamiento Del Bosque along, south of Hwy. 15 and another patch located north of Morelia along Gabino Castañeda del Rio Ave. Because subsidence-induced, shallow faulting develops at high horizontal strain localization, newly developed a subsidence areas are particularly prone to faulting and fissuring. Shallow faulting increases groundwater vulnerability because it disrupts discharge hydraulic infrastructure and creates a direct path for transport of surface pollutants into the underlying aquifer. Other sectors in Morelia that have been experiencing subsidence for longer time have already developed well defined faults such as La Colina, Central Camionera, Torremolinos and La Paloma faults. Local construction codes in the vicinity of these faults define a very narrow swath along which housing construction is not allowed. In order to better characterize these fault systems and provide better criteria for future municipal construction codes we have surveyed the La Colina and Torremolinos fault systems in the western sector of Morelia using seismic tomographic techniques. Our results indicate that La Colina Fault

A Design of Finite Memory Residual Generation Filter for Sensor Fault Detection

NASA Astrophysics Data System (ADS)

Kim, Pyung Soo

2017-04-01

In the current paper, a residual generation filter with finite memory structure is proposed for sensor fault detection. The proposed finite memory residual generation filter provides the residual by real-time filtering of fault vector using only the most recent finite measurements and inputs on the window. It is shown that the residual given by the proposed residual generation filter provides the exact fault for noisefree systems. The proposed residual generation filter is specified to the digital filter structure for the amenability to hardware implementation. Finally, to illustrate the capability of the proposed residual generation filter, extensive simulations are performed for the discretized DC motor system with two types of sensor faults, incipient soft bias-type fault and abrupt bias-type fault. In particular, according to diverse noise levels and windows lengths, meaningful simulation results are given for the abrupt bias-type fault.

Dynamic modeling of gearbox faults: A review

NASA Astrophysics Data System (ADS)

Liang, Xihui; Zuo, Ming J.; Feng, Zhipeng

2018-01-01

Gearbox is widely used in industrial and military applications. Due to high service load, harsh operating conditions or inevitable fatigue, faults may develop in gears. If the gear faults cannot be detected early, the health will continue to degrade, perhaps causing heavy economic loss or even catastrophe. Early fault detection and diagnosis allows properly scheduled shutdowns to prevent catastrophic failure and consequently result in a safer operation and higher cost reduction. Recently, many studies have been done to develop gearbox dynamic models with faults aiming to understand gear fault generation mechanism and then develop effective fault detection and diagnosis methods. This paper focuses on dynamics based gearbox fault modeling, detection and diagnosis. State-of-art and challenges are reviewed and discussed. This detailed literature review limits research results to the following fundamental yet key aspects: gear mesh stiffness evaluation, gearbox damage modeling and fault diagnosis techniques, gearbox transmission path modeling and method validation. In the end, a summary and some research prospects are presented.

Highly Sensitive and Practical Detection of Plant Viruses via Electrical Impedance of Droplets on Textured Silicon-Based Devices

PubMed Central

Ambrico, Marianna; Ambrico, Paolo Francesco; Minafra, Angelantonio; De Stradis, Angelo; Vona, Danilo; Cicco, Stefania R.; Palumbo, Fabio; Favia, Pietro; Ligonzo, Teresa

2016-01-01

Early diagnosis of plant virus infections before the disease symptoms appearance may represent a significant benefit in limiting disease spread by a prompt application of appropriate containment steps. We propose a label-free procedure applied on a device structure where the electrical signal transduction is evaluated via impedance spectroscopy techniques. The device consists of a droplet suspension embedding two representative purified plant viruses i.e., Tomato mosaic virus and Turnip yellow mosaic virus, put in contact with a highly hydrophobic plasma textured silicon surface. Results show a high sensitivity of the system towards the virus particles with an interestingly low detection limit, from tens to hundreds of attomolar corresponding to pg/mL of sap, which refers, in the infection time-scale, to a concentration of virus particles in still-symptomless plants. Such a threshold limit, together with an envisaged engineering of an easily manageable device, compared to more sophisticated apparatuses, may contribute in simplifying the in-field plant virus diagnostics. PMID:27869726

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.

High-resolution image of Calaveras fault seismicity

USGS Publications Warehouse

Schaff, D.P.; Bokelmann, G.H.R.; Beroza, G.C.; Waldhauser, F.; Ellsworth, W.L.

2002-01-01

By measuring relative earthquake arrival times using waveform cross correlation and locating earthquakes using the double difference technique, we are able to reduce hypocentral errors by 1 to 2 orders of magnitude over routine locations for nearly 8000 events along a 35-km section of the Calaveras Fault. This represents ~92% of all seismicity since 1984 and includes the rupture zone of the M 6.2 1984 Morgan Hill, California, earthquake. The relocated seismicity forms highly organized structures that were previously obscured by location errors. There are abundant repeating earthquake sequences as well as linear clusters of earthquakes. Large voids in seismicity appear with dimensions of kilometers that have been aseismic over the 30-year time interval, suggesting that these portions of the fault are either locked or creeping. The area of greatest slip in the Morgan Hill main shock coincides with the most prominent of these voids, suggesting that this part of the fault may be locked between large earthquakes. We find that the Calaveras Fault at depth is extremely thin, with an average upper bound on fault zone width of 75 m. Given the location error, however, this width is not resolvably different from zero. The relocations reveal active secondary faults, which we use to solve for the stress field in the immediate vicinity of the Calaveras Fault. We find that the maximum compressive stress is at a high angle, only 13 from the fault normal, supporting previous interpretations that this fault is weak.

Fault recovery characteristics of the fault tolerant multi-processor

NASA Technical Reports Server (NTRS)

Padilla, Peter A.

1990-01-01

The fault handling performance of the fault tolerant multiprocessor (FTMP) was investigated. Fault handling errors detected during fault injection experiments were characterized. In these fault injection experiments, the FTMP disabled a working unit instead of the faulted unit once every 500 faults, on the average. System design weaknesses allow active faults to exercise a part of the fault management software that handles byzantine or lying faults. It is pointed out that these weak areas in the FTMP's design increase the probability that, for any hardware fault, a good LRU (line replaceable unit) is mistakenly disabled by the fault management software. It is concluded that fault injection can help detect and analyze the behavior of a system in the ultra-reliable regime. Although fault injection testing cannot be exhaustive, it has been demonstrated that it provides a unique capability to unmask problems and to characterize the behavior of a fault-tolerant system.

Protection of Renewable-dominated Microgrids: Challenges and Potential Solutions.

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

Elkhatib, Mohamed; Ellis, Abraham; Milan Biswal

keywords : Microgrid Protection, Impedance Relay, Signal Processing-based Fault Detec- tion, Networked Microgrids, Communication-Assisted Protection In this report we address the challenge of designing efficient protection system for inverter- dominated microgrids. These microgrids are characterised with limited fault current capacity as a result of current-limiting protection functions of inverters. Typically, inverters limit their fault contribution in sub-cycle time frame to as low as 1.1 per unit. As a result, overcurrent protection could fail completely to detect faults in inverter-dominated microgrids. As part of this project a detailed literature survey of existing and proposed microgrid protection schemes were conducted. The surveymore » concluded that there is a gap in the available microgrid protection methods. The only credible protection solution available in literature for low- fault inverter-dominated microgrids is the differential protection scheme which represents a robust transmission-grade protection solution but at a very high cost. Two non-overcurrent protection schemes were investigated as part of this project; impedance-based protection and transient-based protection. Impedance-based protection depends on monitoring impedance trajectories at feeder relays to detect faults. Two communication-based impedance-based protection schemes were developed. the first scheme utilizes directional elements and pilot signals to locate the fault. The second scheme depends on a Central Protection Unit that communicates with all feeder relays to locate the fault based on directional flags received from feeder relays. The later approach could potentially be adapted to protect networked microgrids and dynamic topology microgrids. Transient-based protection relies on analyzing high frequency transients to detect and locate faults. This approach is very promising but its implementation in the filed faces several challenges. For example, high frequency transients

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.

Improved Statistical Fault Detection Technique and Application to Biological Phenomena Modeled by S-Systems.

PubMed

Mansouri, Majdi; Nounou, Mohamed N; Nounou, Hazem N

2017-09-01

In our previous work, we have demonstrated the effectiveness of the linear multiscale principal component analysis (PCA)-based moving window (MW)-generalized likelihood ratio test (GLRT) technique over the classical PCA and multiscale principal component analysis (MSPCA)-based GLRT methods. The developed fault detection algorithm provided optimal properties by maximizing the detection probability for a particular false alarm rate (FAR) with different values of windows, and however, most real systems are nonlinear, which make the linear PCA method not able to tackle the issue of non-linearity to a great extent. Thus, in this paper, first, we apply a nonlinear PCA to obtain an accurate principal component of a set of data and handle a wide range of nonlinearities using the kernel principal component analysis (KPCA) model. The KPCA is among the most popular nonlinear statistical methods. Second, we extend the MW-GLRT technique to one that utilizes exponential weights to residuals in the moving window (instead of equal weightage) as it might be able to further improve fault detection performance by reducing the FAR using exponentially weighed moving average (EWMA). The developed detection method, which is called EWMA-GLRT, provides improved properties, such as smaller missed detection and FARs and smaller average run length. The idea behind the developed EWMA-GLRT is to compute a new GLRT statistic that integrates current and previous data information in a decreasing exponential fashion giving more weight to the more recent data. This provides a more accurate estimation of the GLRT statistic and provides a stronger memory that will enable better decision making with respect to fault detection. Therefore, in this paper, a KPCA-based EWMA-GLRT method is developed and utilized in practice to improve fault detection in biological phenomena modeled by S-systems and to enhance monitoring process mean. The idea behind a KPCA-based EWMA-GLRT fault detection algorithm is to

High stresses stored in fault zones: example of the Nojima fault (Japan)

NASA Astrophysics Data System (ADS)

Boullier, Anne-Marie; Robach, Odile; Ildefonse, Benoît; Barou, Fabrice; Mainprice, David; Ohtani, Tomoyuki; Fujimoto, Koichiro

2018-04-01

During the last decade pulverized rocks have been described on outcrops along large active faults and attributed to damage related to a propagating seismic rupture front. Questions remain concerning the maximal lateral distance from the fault plane and maximal depth for dynamic damage to be imprinted in rocks. In order to document these questions, a representative core sample of granodiorite located 51.3 m from the Nojima fault (Japan) that was drilled after the Hyogo-ken Nanbu (Kobe) earthquake is studied by using electron backscattered diffraction (EBSD) and high-resolution X-ray Laue microdiffraction. Although located outside of the Nojima damage fault zone and macroscopically undeformed, the sample shows pervasive microfractures and local fragmentation. These features are attributed to the first stage of seismic activity along the Nojima fault characterized by laumontite as the main sealing mineral. EBSD mapping was used in order to characterize the crystallographic orientation and deformation microstructures in the sample, and X-ray microdiffraction was used to measure elastic strain and residual stresses on each point of the mapped quartz grain. Both methods give consistent results on the crystallographic orientation and show small and short wavelength misorientations associated with laumontite-sealed microfractures and alignments of tiny fluid inclusions. Deformation microstructures in quartz are symptomatic of the semi-brittle faulting regime, in which low-temperature brittle plastic deformation and stress-driven dissolution-deposition processes occur conjointly. This deformation occurred at a 3.7-11.1 km depth interval as indicated by the laumontite stability domain. Residual stresses are calculated from deviatoric elastic strain tensor measured using X-ray Laue microdiffraction using the Hooke's law. The modal value of the von Mises stress distribution is at 100 MPa and the mean at 141 MPa. Such stress values are comparable to the peak strength of a

Impedance Discontinuity Reduction Between High-Speed Differential Connectors and PCB Interfaces

NASA Technical Reports Server (NTRS)

Navidi, Sal; Agdinaoay, Rodell; Walter, Keith

2013-01-01

High-speed serial communication (i.e., Gigabit Ethernet) requires differential transmission and controlled impedances. Impedance control is essential throughout cabling, connector, and circuit board construction. An impedance discontinuity arises at the interface of a high-speed quadrax and twinax connectors and the attached printed circuit board (PCB). This discontinuity usually is lower impedance since the relative dielectric constant of the board is higher (i.e., polyimide approx. = 4) than the connector (Teflon approx. = 2.25). The discontinuity can be observed in transmit or receive eye diagrams, and can reduce the effective link margin of serial data networks. High-speed serial data network transmission improvements can be made at the connector-to-board interfaces as well as improving differential via hole impedances. The impedance discontinuity was improved by 10 percent by drilling a 20-mil (approx. = 0.5-mm) hole in between the pin of a differential connector spaced 55 mils (approx. = 1.4 mm) apart as it is attached to the PCB. The effective dielectric constant of the board can be lowered by drilling holes into the board material between the differential lines in a quadrax or twinax connector attachment points. The differential impedance is inversely proportional to the square root of the relative dielectric constant. This increases the differential impedance and thus reduces the above described impedance discontinuity. The differential via hole impedance can also be increased in the same manner. This technique can be extended to multiple smaller drilled holes as well as tapered holes (i.e., big in the middle followed by smaller ones diagonally).

Offline impedance measurements for detection and mitigation of dangerous implant interactions: an RF safety prescreen.

PubMed

Ellenor, Christopher W; Stang, Pascal P; Etezadi-Amoli, Maryam; Pauly, John M; Scott, Greig C

2015-03-01

The concept of a "radiofrequency safety prescreen" is investigated, wherein dangerous interactions between radiofrequency fields used in MRI, and conductive implants in patients are detected through impedance changes in the radiofrequency coil. The behavior of coupled oscillators is reviewed, and the resulting, observable impedance changes are discussed. A birdcage coil is loaded with a static head phantom and a wire phantom with a wire close to its resonant length, the shape, position, and orientation of which can be changed. Interactions are probed with a current sensor and network analyzer. Impedance spectra show dramatic, unmistakable splitting in cases of strong coupling, and strong correlation is observed between induced current and scattering parameters. The feasibility of a new, low-power prescreening technique has been demonstrated in a simple phantom experiment, which can unambiguously detect resonant interactions between an implanted wire and an imaging coil. A new technique has also been presented which can detect parallel transmit null modes for the wire. © 2014 Wiley Periodicals, Inc.

A Sparsity-Promoted Decomposition for Compressed Fault Diagnosis of Roller Bearings

PubMed Central

Wang, Huaqing; Ke, Yanliang; Song, Liuyang; Tang, Gang; Chen, Peng

2016-01-01

The traditional approaches for condition monitoring of roller bearings are almost always achieved under Shannon sampling theorem conditions, leading to a big-data problem. The compressed sensing (CS) theory provides a new solution to the big-data problem. However, the vibration signals are insufficiently sparse and it is difficult to achieve sparsity using the conventional techniques, which impedes the application of CS theory. Therefore, it is of great significance to promote the sparsity when applying the CS theory to fault diagnosis of roller bearings. To increase the sparsity of vibration signals, a sparsity-promoted method called the tunable Q-factor wavelet transform based on decomposing the analyzed signals into transient impact components and high oscillation components is utilized in this work. The former become sparser than the raw signals with noise eliminated, whereas the latter include noise. Thus, the decomposed transient impact components replace the original signals for analysis. The CS theory is applied to extract the fault features without complete reconstruction, which means that the reconstruction can be completed when the components with interested frequencies are detected and the fault diagnosis can be achieved during the reconstruction procedure. The application cases prove that the CS theory assisted by the tunable Q-factor wavelet transform can successfully extract the fault features from the compressed samples. PMID:27657063

Fault detection and multiclassifier fusion for unmanned aerial vehicles (UAVs)

NASA Astrophysics Data System (ADS)

Yan, Weizhong

2001-03-01

UAVs demand more accurate fault accommodation for their mission manager and vehicle control system in order to achieve a reliability level that is comparable to that of a pilot aircraft. This paper attempts to apply multi-classifier fusion techniques to achieve the necessary performance of the fault detection function for the Lockheed Martin Skunk Works (LMSW) UAV Mission Manager. Three different classifiers that meet the design requirements of the fault detection of the UAAV are employed. The binary decision outputs from the classifiers are then aggregated using three different classifier fusion schemes, namely, majority vote, weighted majority vote, and Naieve Bayes combination. All of the three schemes are simple and need no retraining. The three fusion schemes (except the majority vote that gives an average performance of the three classifiers) show the classification performance that is better than or equal to that of the best individual. The unavoidable correlation between the classifiers with binary outputs is observed in this study. We conclude that it is the correlation between the classifiers that limits the fusion schemes to achieve an even better performance.

Fault Detection and Diagnosis of Railway Point Machines by Sound Analysis

PubMed Central

Lee, Jonguk; Choi, Heesu; Park, Daihee; Chung, Yongwha; Kim, Hee-Young; Yoon, Sukhan

2016-01-01

Railway point devices act as actuators that provide different routes to trains by driving switchblades from the current position to the opposite one. Point failure can significantly affect railway operations, with potentially disastrous consequences. Therefore, early detection of anomalies is critical for monitoring and managing the condition of rail infrastructure. We present a data mining solution that utilizes audio data to efficiently detect and diagnose faults in railway condition monitoring systems. The system enables extracting mel-frequency cepstrum coefficients (MFCCs) from audio data with reduced feature dimensions using attribute subset selection, and employs support vector machines (SVMs) for early detection and classification of anomalies. Experimental results show that the system enables cost-effective detection and diagnosis of faults using a cheap microphone, with accuracy exceeding 94.1% whether used alone or in combination with other known methods. PMID:27092509

Rapid culture-based detection of living mycobacteria using microchannel electrical impedance spectroscopy (m-EIS).

PubMed

Kargupta, Roli; Puttaswamy, Sachidevi; Lee, Aiden J; Butler, Timothy E; Li, Zhongyu; Chakraborty, Sounak; Sengupta, Shramik

2017-06-10

Multiple techniques exist for detecting Mycobacteria, each having its own advantages and drawbacks. Among them, automated culture-based systems like the BACTEC-MGIT™ are popular because they are inexpensive, reliable and highly accurate. However, they have a relatively long "time-to-detection" (TTD). Hence, a method that retains the reliability and low-cost of the MGIT system, while reducing TTD would be highly desirable. Living bacterial cells possess a membrane potential, on account of which they store charge when subjected to an AC-field. This charge storage (bulk capacitance) can be estimated using impedance measurements at multiple frequencies. An increase in the number of living cells during culture is reflected in an increase in bulk capacitance, and this forms the basis of our detection. M. bovis BCG and M. smegmatis suspensions with differing initial loads are cultured in MGIT media supplemented with OADC and Middlebrook 7H9 media respectively, electrical "scans" taken at regular intervals and the bulk capacitance estimated from the scans. Bulk capacitance estimates at later time-points are statistically compared to the suspension's baseline value. A statistically significant increase is assumed to indicate the presence of proliferating mycobacteria. Our TTDs were 60 and 36 h for M. bovis BCG and 20 and 9 h for M. smegmatis with initial loads of 1000 CFU/ml and 100,000 CFU/ml respectively. The corresponding TTDs for the commercial BACTEC MGIT 960 system were 131 and 84.6 h for M. bovis BCG and 41.7 and 12 h for M smegmatis, respectively. Our culture-based detection method using multi-frequency impedance measurements is capable of detecting mycobacteria faster than current commercial systems.

Protection of Renewable-dominated Microgrids: Challenges and Potential Solutions

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

Elkhatib, Mohamed; Ellis, Abraham; Biswal, Milan

In this report we address the challenge of designing efficient protection system for inverter- dominated microgrids. These microgrids are characterised with limited fault current capacity as a result of current-limiting protection functions of inverters. Typically, inverters limit their fault contribution in sub-cycle time frame to as low as 1.1 per unit. As a result, overcurrent protection could fail completely to detect faults in inverter-dominated microgrids. As part of this project a detailed literature survey of existing and proposed microgrid protection schemes were conducted. The survey concluded that there is a gap in the available microgrid protection methods. The only crediblemore » protection solution available in literature for low- fault inverter-dominated microgrids is the differential protection scheme which represents a robust transmission-grade protection solution but at a very high cost. Two non-overcurrent protection schemes were investigated as part of this project; impedance-based protection and transient-based protection. Impedance-based protection depends on monitoring impedance trajectories at feeder relays to detect faults. Two communication-based impedance-based protection schemes were developed. the first scheme utilizes directional elements and pilot signals to locate the fault. The second scheme depends on a Central Protection Unit that communicates with all feeder relays to locate the fault based on directional flags received from feeder relays. The later approach could potentially be adapted to protect networked microgrids and dynamic topology microgrids. Transient-based protection relies on analyzing high frequency transients to detect and locate faults. This approach is very promising but its implementation in the filed faces several challenges. For example, high frequency transients due to faults can be confused with transients due to other events such as capacitor switching. Additionally, while detecting faults by analyzing

Abnormal fault-recovery characteristics of the fault-tolerant multiprocessor uncovered using a new fault-injection methodology

NASA Technical Reports Server (NTRS)

Padilla, Peter A.

1991-01-01

An investigation was made in AIRLAB of the fault handling performance of the Fault Tolerant MultiProcessor (FTMP). Fault handling errors detected during fault injection experiments were characterized. In these fault injection experiments, the FTMP disabled a working unit instead of the faulted unit once in every 500 faults, on the average. System design weaknesses allow active faults to exercise a part of the fault management software that handles Byzantine or lying faults. Byzantine faults behave such that the faulted unit points to a working unit as the source of errors. The design's problems involve: (1) the design and interface between the simplex error detection hardware and the error processing software, (2) the functional capabilities of the FTMP system bus, and (3) the communication requirements of a multiprocessor architecture. These weak areas in the FTMP's design increase the probability that, for any hardware fault, a good line replacement unit (LRU) is mistakenly disabled by the fault management software.

In-process fault detection for textile fabric production: onloom imaging

NASA Astrophysics Data System (ADS)

Neumann, Florian; Holtermann, Timm; Schneider, Dorian; Kulczycki, Ashley; Gries, Thomas; Aach, Til

2011-05-01

Constant and traceable high fabric quality is of high importance both for technical and for high-quality conventional fabrics. Usually, quality inspection is carried out by trained personal, whose detection rate and maximum period of concentration are limited. Low resolution automated fabric inspection machines using texture analysis were developed. Since 2003, systems for the in-process inspection on weaving machines ("onloom") are commercially available. With these defects can be detected, but not measured quantitative precisely. Most systems are also prone to inevitable machine vibrations. Feedback loops for fault prevention are not established. Technology has evolved since 2003: Camera and computer prices dropped, resolutions were enhanced, recording speeds increased. These are the preconditions for real-time processing of high-resolution images. So far, these new technological achievements are not used in textile fabric production. For efficient use, a measurement system must be integrated into the weaving process; new algorithms for defect detection and measurement must be developed. The goal of the joint project is the development of a modern machine vision system for nondestructive onloom fabric inspection. The system consists of a vibration-resistant machine integration, a high-resolution machine vision system, and new, reliable, and robust algorithms with quality database for defect documentation. The system is meant to detect, measure, and classify at least 80 % of economically relevant defects. Concepts for feedback loops into the weaving process will be pointed out.

A leakage-free resonance sparse decomposition technique for bearing fault detection in gearboxes

NASA Astrophysics Data System (ADS)

Osman, Shazali; Wang, Wilson

2018-03-01

Most of rotating machinery deficiencies are related to defects in rolling element bearings. Reliable bearing fault detection still remains a challenging task, especially for bearings in gearboxes as bearing-defect-related features are nonstationary and modulated by gear mesh vibration. A new leakage-free resonance sparse decomposition (LRSD) technique is proposed in this paper for early bearing fault detection of gearboxes. In the proposed LRSD technique, a leakage-free filter is suggested to remove strong gear mesh and shaft running signatures. A kurtosis and cosine distance measure is suggested to select appropriate redundancy r and quality factor Q. The signal residual is processed by signal sparse decomposition for highpass and lowpass resonance analysis to extract representative features for bearing fault detection. The effectiveness of the proposed technique is verified by a succession of experimental tests corresponding to different gearbox and bearing conditions.

Multiple fault separation and detection by joint subspace learning for the health assessment of wind turbine gearboxes

NASA Astrophysics Data System (ADS)

Du, Zhaohui; Chen, Xuefeng; Zhang, Han; Zi, Yanyang; Yan, Ruqiang

2017-09-01

The gearbox of a wind turbine (WT) has dominant failure rates and highest downtime loss among all WT subsystems. Thus, gearbox health assessment for maintenance cost reduction is of paramount importance. The concurrence of multiple faults in gearbox components is a common phenomenon due to fault induction mechanism. This problem should be considered before planning to replace the components of the WT gearbox. Therefore, the key fault patterns should be reliably identified from noisy observation data for the development of an effective maintenance strategy. However, most of the existing studies focusing on multiple fault diagnosis always suffer from inappropriate division of fault information in order to satisfy various rigorous decomposition principles or statistical assumptions, such as the smooth envelope principle of ensemble empirical mode decomposition and the mutual independence assumption of independent component analysis. Thus, this paper presents a joint subspace learning-based multiple fault detection (JSL-MFD) technique to construct different subspaces adaptively for different fault patterns. Its main advantage is its capability to learn multiple fault subspaces directly from the observation signal itself. It can also sparsely concentrate the feature information into a few dominant subspace coefficients. Furthermore, it can eliminate noise by simply performing coefficient shrinkage operations. Consequently, multiple fault patterns are reliably identified by utilizing the maximum fault information criterion. The superiority of JSL-MFD in multiple fault separation and detection is comprehensively investigated and verified by the analysis of a data set of a 750 kW WT gearbox. Results show that JSL-MFD is superior to a state-of-the-art technique in detecting hidden fault patterns and enhancing detection accuracy.

Methods and apparatus using commutative error detection values for fault isolation in multiple node computers

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

Almasi, Gheorghe; Blumrich, Matthias Augustin; Chen, Dong

Methods and apparatus perform fault isolation in multiple node computing systems using commutative error detection values for--example, checksums--to identify and to isolate faulty nodes. When information associated with a reproducible portion of a computer program is injected into a network by a node, a commutative error detection value is calculated. At intervals, node fault detection apparatus associated with the multiple node computer system retrieve commutative error detection values associated with the node and stores them in memory. When the computer program is executed again by the multiple node computer system, new commutative error detection values are created and stored inmore » memory. The node fault detection apparatus identifies faulty nodes by comparing commutative error detection values associated with reproducible portions of the application program generated by a particular node from different runs of the application program. Differences in values indicate a possible faulty node.« less

Capnography and chest wall impedance algorithms for ventilation detection during cardiopulmonary resuscitation

PubMed Central

Edelson, Dana P.; Eilevstjønn, Joar; Weidman, Elizabeth K.; Retzer, Elizabeth; Vanden Hoek, Terry L.; Abella, Benjamin S.

2009-01-01

Objective Hyperventilation is both common and detrimental during cardiopulmonary resuscitation (CPR). Chest wall impedance algorithms have been developed to detect ventilations during CPR. However, impedance signals are challenged by noise artifact from multiple sources, including chest compressions. Capnography has been proposed as an alternate method to measure ventilations. We sought to assess and compare the adequacy of these two approaches. Methods Continuous chest wall impedance and capnography were recorded during consecutive in-hospital cardiac arrests. Algorithms utilizing each of these data sources were compared to a manually determined “gold standard” reference ventilation rate. In addition, a combination algorithm, which utilized the highest of the impedance or capnography values in any given minute, was similarly evaluated. Results Data were collected from 37 cardiac arrests, yielding 438 min of data with continuous chest compressions and concurrent recording of impedance and capnography. The manually calculated mean ventilation rate was 13.3±4.3/min. In comparison, the defibrillator’s impedance-based algorithm yielded an average rate of 11.3±4.4/min (p=0.0001) while the capnography rate was 11.7±3.7/min (p=0.0009). There was no significant difference in sensitivity and positive predictive value between the two methods. The combination algorithm rate was 12.4±3.5/min (p=0.02), which yielded the highest fraction of minutes with respiratory rates within 2/min of the reference. The impedance signal was uninterpretable 19.5% of the time, compared with 9.7% for capnography. However, the signals were only simultaneously non-interpretable 0.8% of the time. Conclusions Both the impedance and capnography-based algorithms underestimated the ventilation rate. Reliable ventilation rate determination may require a novel combination of multiple algorithms during resuscitation. PMID:20036047

Stable, high-order computation of impedance-impedance operators for three-dimensional layered medium simulations.

PubMed

Nicholls, David P

2018-04-01

The faithful modelling of the propagation of linear waves in a layered, periodic structure is of paramount importance in many branches of the applied sciences. In this paper, we present a novel numerical algorithm for the simulation of such problems which is free of the artificial singularities present in related approaches. We advocate for a surface integral formulation which is phrased in terms of impedance-impedance operators that are immune to the Dirichlet eigenvalues which plague the Dirichlet-Neumann operators that appear in classical formulations. We demonstrate a high-order spectral algorithm to simulate these latter operators based upon a high-order perturbation of surfaces methodology which is rapid, robust and highly accurate. We demonstrate the validity and utility of our approach with a sequence of numerical simulations.

Stable, high-order computation of impedance-impedance operators for three-dimensional layered medium simulations

NASA Astrophysics Data System (ADS)

Nicholls, David P.

2018-04-01

The faithful modelling of the propagation of linear waves in a layered, periodic structure is of paramount importance in many branches of the applied sciences. In this paper, we present a novel numerical algorithm for the simulation of such problems which is free of the artificial singularities present in related approaches. We advocate for a surface integral formulation which is phrased in terms of impedance-impedance operators that are immune to the Dirichlet eigenvalues which plague the Dirichlet-Neumann operators that appear in classical formulations. We demonstrate a high-order spectral algorithm to simulate these latter operators based upon a high-order perturbation of surfaces methodology which is rapid, robust and highly accurate. We demonstrate the validity and utility of our approach with a sequence of numerical simulations.

Protection Relaying Scheme Based on Fault Reactance Operation Type

NASA Astrophysics Data System (ADS)

Tsuji, Kouichi

The theories of operation of existing relays are roughly divided into two types: one is the current differential types based on Kirchhoff's first law and the other is impedance types based on second law. We can apply the Kirchhoff's laws to strictly formulate fault phenomena, so the circuit equations are represented non linear simultaneous equations with variables fault point k and fault resistance Rf. This method has next two defect. 1) heavy computational burden for the iterative calculation on N-R method, 2) relay operator can not easily understand principle of numerical matrix operation. The new protection relay principles we proposed this paper focuses on the fact that the reactance component on fault point is almost zero. Two reactance Xf(S), Xf(R) on branch both ends are calculated by operation of solving linear equations. If signs of Xf(S) and Xf(R) are not same, it can be judged that the fault point exist in the branch. This reactance Xf corresponds to difference of branch reactance between actual fault point and imaginaly fault point. And so relay engineer can to understand fault location by concept of “distance". The simulation results using this new method indicates the highly precise estimation of fault locations compared with the inspected fault locations on operating transmission lines.

Fault detection and bypass in a sequence information signal processor

NASA Technical Reports Server (NTRS)

Peterson, John C. (Inventor); Chow, Edward T. (Inventor)

1992-01-01

The invention comprises a plurality of scan registers, each such register respectively associated with a processor element; an on-chip comparator, encoder and fault bypass register. Each scan register generates a unitary signal the logic state of which depends on the correctness of the input from the previous processor in the systolic array. These unitary signals are input to a common comparator which generates an output indicating whether or not an error has occurred. These unitary signals are also input to an encoder which identifies the location of any fault detected so that an appropriate multiplexer can be switched to bypass the faulty processor element. Input scan data can be readily programmed to fully exercise all of the processor elements so that no fault can remain undetected.

Detecting Faults in Southern California using Computer-Vision Techniques and Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) Interferometry

NASA Astrophysics Data System (ADS)

Barba, M.; Rains, C.; von Dassow, W.; Parker, J. W.; Glasscoe, M. T.

2013-12-01

Knowing the location and behavior of active faults is essential for earthquake hazard assessment and disaster response. In Interferometric Synthetic Aperture Radar (InSAR) images, faults are revealed as linear discontinuities. Currently, interferograms are manually inspected to locate faults. During the summer of 2013, the NASA-JPL DEVELOP California Disasters team contributed to the development of a method to expedite fault detection in California using remote-sensing technology. The team utilized InSAR images created from polarimetric L-band data from NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) project. A computer-vision technique known as 'edge-detection' was used to automate the fault-identification process. We tested and refined an edge-detection algorithm under development through NASA's Earthquake Data Enhanced Cyber-Infrastructure for Disaster Evaluation and Response (E-DECIDER) project. To optimize the algorithm we used both UAVSAR interferograms and synthetic interferograms generated through Disloc, a web-based modeling program available through NASA's QuakeSim project. The edge-detection algorithm detected seismic, aseismic, and co-seismic slip along faults that were identified and compared with databases of known fault systems. Our optimization process was the first step toward integration of the edge-detection code into E-DECIDER to provide decision support for earthquake preparation and disaster management. E-DECIDER partners that will use the edge-detection code include the California Earthquake Clearinghouse and the US Department of Homeland Security through delivery of products using the Unified Incident Command and Decision Support (UICDS) service. Through these partnerships, researchers, earthquake disaster response teams, and policy-makers will be able to use this new methodology to examine the details of ground and fault motions for moderate to large earthquakes. Following an earthquake, the newly discovered faults can

Fault detection for hydraulic pump based on chaotic parallel RBF network

NASA Astrophysics Data System (ADS)

Lu, Chen; Ma, Ning; Wang, Zhipeng

2011-12-01

In this article, a parallel radial basis function network in conjunction with chaos theory (CPRBF network) is presented, and applied to practical fault detection for hydraulic pump, which is a critical component in aircraft. The CPRBF network consists of a number of radial basis function (RBF) subnets connected in parallel. The number of input nodes for each RBF subnet is determined by different embedding dimension based on chaotic phase-space reconstruction. The output of CPRBF is a weighted sum of all RBF subnets. It was first trained using the dataset from normal state without fault, and then a residual error generator was designed to detect failures based on the trained CPRBF network. Then, failure detection can be achieved by the analysis of the residual error. Finally, two case studies are introduced to compare the proposed CPRBF network with traditional RBF networks, in terms of prediction and detection accuracy.

High-Intensity Radiated Field Fault-Injection Experiment for a Fault-Tolerant Distributed Communication System

NASA Technical Reports Server (NTRS)

Yates, Amy M.; Torres-Pomales, Wilfredo; Malekpour, Mahyar R.; Gonzalez, Oscar R.; Gray, W. Steven

2010-01-01

Safety-critical distributed flight control systems require robustness in the presence of faults. In general, these systems consist of a number of input/output (I/O) and computation nodes interacting through a fault-tolerant data communication system. The communication system transfers sensor data and control commands and can handle most faults under typical operating conditions. However, the performance of the closed-loop system can be adversely affected as a result of operating in harsh environments. In particular, High-Intensity Radiated Field (HIRF) environments have the potential to cause random fault manifestations in individual avionic components and to generate simultaneous system-wide communication faults that overwhelm existing fault management mechanisms. This paper presents the design of an experiment conducted at the NASA Langley Research Center's HIRF Laboratory to statistically characterize the faults that a HIRF environment can trigger on a single node of a distributed flight control system.

Hidden Markov models and neural networks for fault detection in dynamic systems

NASA Technical Reports Server (NTRS)

Smyth, Padhraic

1994-01-01

Neural networks plus hidden Markov models (HMM) can provide excellent detection and false alarm rate performance in fault detection applications, as shown in this viewgraph presentation. Modified models allow for novelty detection. Key contributions of neural network models are: (1) excellent nonparametric discrimination capability; (2) a good estimator of posterior state probabilities, even in high dimensions, and thus can be embedded within overall probabilistic model (HMM); and (3) simple to implement compared to other nonparametric models. Neural network/HMM monitoring model is currently being integrated with the new Deep Space Network (DSN) antenna controller software and will be on-line monitoring a new DSN 34-m antenna (DSS-24) by July, 1994.

Hideen Markov Models and Neural Networks for Fault Detection in Dynamic Systems

NASA Technical Reports Server (NTRS)

Smyth, Padhraic

1994-01-01

None given. (From conclusion): Neural networks plus Hidden Markov Models(HMM)can provide excellene detection and false alarm rate performance in fault detection applications. Modified models allow for novelty detection. Also covers some key contributions of neural network model, and application status.

The Frequency Spectral Properties of Electrode-Skin Contact Impedance on Human Head and Its Frequency-Dependent Effects on Frequency-Difference EIT in Stroke Detection from 10Hz to 1MHz.

PubMed

Yang, Lin; Dai, Meng; Xu, Canhua; Zhang, Ge; Li, Weichen; Fu, Feng; Shi, Xuetao; Dong, Xiuzhen

2017-01-01

Frequency-difference electrical impedance tomography (fdEIT) reconstructs frequency-dependent changes of a complex impedance distribution. It has a potential application in acute stroke detection because there are significant differences in impedance spectra between stroke lesions and normal brain tissues. However, fdEIT suffers from the influences of electrode-skin contact impedance since contact impedance varies greatly with frequency. When using fdEIT to detect stroke, it is critical to know the degree of measurement errors or image artifacts caused by contact impedance. To our knowledge, no study has systematically investigated the frequency spectral properties of electrode-skin contact impedance on human head and its frequency-dependent effects on fdEIT used in stroke detection within a wide frequency band (10 Hz-1 MHz). In this study, we first measured and analyzed the frequency spectral properties of electrode-skin contact impedance on 47 human subjects' heads within 10 Hz-1 MHz. Then, we quantified the frequency-dependent effects of contact impedance on fdEIT in stroke detection in terms of the current distribution beneath the electrodes and the contact impedance imbalance between two measuring electrodes. The results showed that the contact impedance at high frequencies (>100 kHz) significantly changed the current distribution beneath the electrode, leading to nonnegligible errors in boundary voltages and artifacts in reconstructed images. The contact impedance imbalance at low frequencies (<1 kHz) also caused significant measurement errors. We conclude that the contact impedance has critical frequency-dependent influences on fdEIT and further studies on reducing such influences are necessary to improve the application of fdEIT in stroke detection.

The Frequency Spectral Properties of Electrode-Skin Contact Impedance on Human Head and Its Frequency-Dependent Effects on Frequency-Difference EIT in Stroke Detection from 10Hz to 1MHz

PubMed Central

Zhang, Ge; Li, Weichen; Fu, Feng; Shi, Xuetao; Dong, Xiuzhen

2017-01-01

Frequency-difference electrical impedance tomography (fdEIT) reconstructs frequency-dependent changes of a complex impedance distribution. It has a potential application in acute stroke detection because there are significant differences in impedance spectra between stroke lesions and normal brain tissues. However, fdEIT suffers from the influences of electrode-skin contact impedance since contact impedance varies greatly with frequency. When using fdEIT to detect stroke, it is critical to know the degree of measurement errors or image artifacts caused by contact impedance. To our knowledge, no study has systematically investigated the frequency spectral properties of electrode-skin contact impedance on human head and its frequency-dependent effects on fdEIT used in stroke detection within a wide frequency band (10 Hz-1 MHz). In this study, we first measured and analyzed the frequency spectral properties of electrode-skin contact impedance on 47 human subjects’ heads within 10 Hz-1 MHz. Then, we quantified the frequency-dependent effects of contact impedance on fdEIT in stroke detection in terms of the current distribution beneath the electrodes and the contact impedance imbalance between two measuring electrodes. The results showed that the contact impedance at high frequencies (>100 kHz) significantly changed the current distribution beneath the electrode, leading to nonnegligible errors in boundary voltages and artifacts in reconstructed images. The contact impedance imbalance at low frequencies (<1 kHz) also caused significant measurement errors. We conclude that the contact impedance has critical frequency-dependent influences on fdEIT and further studies on reducing such influences are necessary to improve the application of fdEIT in stroke detection. PMID:28107524

Real-time imaging and detection of intracranial haemorrhage by electrical impedance tomography in a piglet model.

PubMed

Xu, C H; Wang, L; Shi, X T; You, F S; Fu, F; Liu, R G; Dai, M; Zhao, Z W; Gao, G D; Dong, X Z

2010-01-01

The aim of this study was to use electrical impedance tomography (EIT) to detect and image acute intracranial haemorrhage (ICH) in an animal model. Blood was infused into the frontal lobe of the brains of anaesthetized piglets and impedance was measured using 16 electrodes placed in a circle on the scalp. The EIT images were constructed using a filtered back-projection algorithm. The mean of all the pixel intensities within a region of interest--the mean resistivity value (MRV)--was used to evaluate the relative impedance changes in the target region. A symmetrical index (SI), reflecting the relative impedance on both sides of the brain, was also calculated. Changes in MRV and SI were associated with the injection of blood, demonstrating that EIT can successfully detect ICH in this animal model. The unique features of EIT may be beneficial for diagnosing ICH early in patients after cranial surgery, thereby reducing the risk of complications and mortality.

Pressure Monitoring to Detect Fault Rupture Due to CO 2 Injection

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

Keating, Elizabeth; Dempsey, David; Pawar, Rajesh

The capacity for fault systems to be reactivated by fluid injection is well-known. In the context of CO 2 sequestration, however, the consequence of reactivated faults with respect to leakage and monitoring is poorly understood. Using multi-phase fluid flow simulations, this study addresses key questions concerning the likelihood of ruptures, the timing of consequent upward leakage of CO 2, and the effectiveness of pressure monitoring in the reservoir and overlying zones for rupture detection. A range of injection scenarios was simulated using random sampling of uncertain parameters. These include the assumed distance between the injector and the vulnerable fault zone,more » the critical overpressure required for the fault to rupture, reservoir permeability, and the CO 2 injection rate. We assumed a conservative scenario, in which if at any time during the five-year simulations the critical fault overpressure is exceeded, the fault permeability is assumed to instantaneously increase. For the purposes of conservatism we assume that CO 2 injection continues ‘blindly’ after fault rupture. We show that, despite this assumption, in most cases the CO 2 plume does not reach the base of the ruptured fault after 5 years. As a result, one possible implication of this result is that leak mitigation strategies such as pressure management have a reasonable chance of preventing a CO 2 leak.« less

Pressure Monitoring to Detect Fault Rupture Due to CO 2 Injection

DOE PAGES

Keating, Elizabeth; Dempsey, David; Pawar, Rajesh

2017-08-18

The capacity for fault systems to be reactivated by fluid injection is well-known. In the context of CO 2 sequestration, however, the consequence of reactivated faults with respect to leakage and monitoring is poorly understood. Using multi-phase fluid flow simulations, this study addresses key questions concerning the likelihood of ruptures, the timing of consequent upward leakage of CO 2, and the effectiveness of pressure monitoring in the reservoir and overlying zones for rupture detection. A range of injection scenarios was simulated using random sampling of uncertain parameters. These include the assumed distance between the injector and the vulnerable fault zone,more » the critical overpressure required for the fault to rupture, reservoir permeability, and the CO 2 injection rate. We assumed a conservative scenario, in which if at any time during the five-year simulations the critical fault overpressure is exceeded, the fault permeability is assumed to instantaneously increase. For the purposes of conservatism we assume that CO 2 injection continues ‘blindly’ after fault rupture. We show that, despite this assumption, in most cases the CO 2 plume does not reach the base of the ruptured fault after 5 years. As a result, one possible implication of this result is that leak mitigation strategies such as pressure management have a reasonable chance of preventing a CO 2 leak.« less

Method and apparatus for in-situ detection and isolation of aircraft engine faults

NASA Technical Reports Server (NTRS)

Bonanni, Pierino Gianni (Inventor); Brunell, Brent Jerome (Inventor)

2007-01-01

A method for performing a fault estimation based on residuals of detected signals includes determining an operating regime based on a plurality of parameters, extracting predetermined noise standard deviations of the residuals corresponding to the operating regime and scaling the residuals, calculating a magnitude of a measurement vector of the scaled residuals and comparing the magnitude to a decision threshold value, extracting an average, or mean direction and a fault level mapping for each of a plurality of fault types, based on the operating regime, calculating a projection of the measurement vector onto the average direction of each of the plurality of fault types, determining a fault type based on which projection is maximum, and mapping the projection to a continuous-valued fault level using a lookup table.

Offline Impedance Measurements for Detection and Mitigation of Dangerous Implant Interactions: An RF Safety Prescreen

PubMed Central

Ellenor, Christopher W; Stang, Pascal P; Etezadi-Amoli, Maryam; Pauly, John M; Scott, Greig C

2015-01-01

Purpose The concept of a “radiofrequency safety prescreen” is investigated, wherein dangerous interactions between radiofrequency fields used in MRI, and conductive implants in patients are detected through impedance changes in the radiofrequency coil. Theory The behavior of coupled oscillators is reviewed, and the resulting, observable impedance changes are discussed. Methods A birdcage coil is loaded with a static head phantom and a wire phantom with a wire close to its resonant length, the shape, position, and orientation of which can be changed. Interactions are probed with a current sensor and network analyzer. Results Impedance spectra show dramatic, unmistakable splitting in cases of strong coupling, and strong correlation is observed between induced current and scattering parameters. Conclusions The feasibility of a new, low-power prescreening technique has been demonstrated in a simple phantom experiment, which can unambiguously detect resonant interactions between an implanted wire and an imaging coil. A new technique has also been presented which can detect parallel transmit null modes for the wire. Magn Reson Med 73:1328–1339, 2015. © 2014 Wiley Periodicals, Inc. PMID:24623586

Fault zone hydrogeology

NASA Astrophysics Data System (ADS)

Bense, V. F.; Gleeson, T.; Loveless, S. E.; Bour, O.; Scibek, J.

2013-12-01

Deformation along faults in the shallow crust (< 1 km) introduces permeability heterogeneity and anisotropy, which has an important impact on processes such as regional groundwater flow, hydrocarbon migration, and hydrothermal fluid circulation. Fault zones have the capacity to be hydraulic conduits connecting shallow and deep geological environments, but simultaneously the fault cores of many faults often form effective barriers to flow. The direct evaluation of the impact of faults to fluid flow patterns remains a challenge and requires a multidisciplinary research effort of structural geologists and hydrogeologists. However, we find that these disciplines often use different methods with little interaction between them. In this review, we document the current multi-disciplinary understanding of fault zone hydrogeology. We discuss surface- and subsurface observations from diverse rock types from unlithified and lithified clastic sediments through to carbonate, crystalline, and volcanic rocks. For each rock type, we evaluate geological deformation mechanisms, hydrogeologic observations and conceptual models of fault zone hydrogeology. Outcrop observations indicate that fault zones commonly have a permeability structure suggesting they should act as complex conduit-barrier systems in which along-fault flow is encouraged and across-fault flow is impeded. Hydrogeological observations of fault zones reported in the literature show a broad qualitative agreement with outcrop-based conceptual models of fault zone hydrogeology. Nevertheless, the specific impact of a particular fault permeability structure on fault zone hydrogeology can only be assessed when the hydrogeological context of the fault zone is considered and not from outcrop observations alone. To gain a more integrated, comprehensive understanding of fault zone hydrogeology, we foresee numerous synergistic opportunities and challenges for the discipline of structural geology and hydrogeology to co-evolve and

Sensitivity of PZT Impedance Sensors for Damage Detection of Concrete Structures.

PubMed

Yang, Yaowen; Hu, Yuhang; Lu, Yong

2008-01-21

Piezoelectric ceramic Lead Zirconate Titanate (PZT) based electro-mechanicalimpedance (EMI) technique for structural health monitoring (SHM) has been successfullyapplied to various engineering systems. However, fundamental research work on thesensitivity of the PZT impedance sensors for damage detection is still in need. In thetraditional EMI method, the PZT electro-mechanical (EM) admittance (inverse of theimpedance) is used as damage indicator, which is difficult to specify the effect of damage onstructural properties. This paper uses the structural mechanical impedance (SMI) extractedfrom the PZT EM admittance signature as the damage indicator. A comparison study on thesensitivity of the EM admittance and the structural mechanical impedance to the damages ina concrete structure is conducted. Results show that the SMI is more sensitive to the damagethan the EM admittance thus a better indicator for damage detection. Furthermore, this paperproposes a dynamic system consisting of a number of single-degree-of-freedom elementswith mass, spring and damper components to model the SMI. A genetic algorithm isemployed to search for the optimal value of the unknown parameters in the dynamic system.An experiment is carried out on a two-storey concrete frame subjected to base vibrations thatsimulate earthquake. A number of PZT sensors are regularly arrayed and bonded to the framestructure to acquire PZT EM admittance signatures. The relationship between the damageindex and the distance of the PZT sensor from the damage is studied. Consequently, thesensitivity of the PZT sensors is discussed and their sensing region in concrete is derived.

Fault Detection and Diagnosis System for the Air-conditioning

NASA Astrophysics Data System (ADS)

Nakahara, Nobuo

The fault detection and diagnosis system, the FDD system, for the HVAC was initiated around the middle of 1970s in Japan but it still remains at the elementary stage. The HVAC is really one of the most complicated and large scaled system for the FDD system. Besides, the maintenance engineering was never focussed as the target of the academic study since after the war, but the FDD system for some kinds of the components and subsystems has been developed for the sake of the practical industrial needs. Recently, international cooperative study in the IEA Annex 25 on the energy conservation for the building and community targetted on the BOFD, the building optimization, fault detection and diagnosis. Not a few academic peaple from various engineering field got interested and, moreover, some national projects seem to start in the European countries. The author has reviewed the state of the art of the FDD and BO as well based on the references and the experience at the IEA study.

A method based on multi-sensor data fusion for fault detection of planetary gearboxes.

PubMed

Lei, Yaguo; Lin, Jing; He, Zhengjia; Kong, Detong

2012-01-01

Studies on fault detection and diagnosis of planetary gearboxes are quite limited compared with those of fixed-axis gearboxes. Different from fixed-axis gearboxes, planetary gearboxes exhibit unique behaviors, which invalidate fault diagnosis methods that work well for fixed-axis gearboxes. It is a fact that for systems as complex as planetary gearboxes, multiple sensors mounted on different locations provide complementary information on the health condition of the systems. On this basis, a fault detection method based on multi-sensor data fusion is introduced in this paper. In this method, two features developed for planetary gearboxes are used to characterize the gear health conditions, and an adaptive neuro-fuzzy inference system (ANFIS) is utilized to fuse all features from different sensors. In order to demonstrate the effectiveness of the proposed method, experiments are carried out on a planetary gearbox test rig, on which multiple accelerometers are mounted for data collection. The comparisons between the proposed method and the methods based on individual sensors show that the former achieves much higher accuracies in detecting planetary gearbox faults.

Fault detection and identification in missile system guidance and control: a filtering approach

NASA Astrophysics Data System (ADS)

Padgett, Mary Lou; Evers, Johnny; Karplus, Walter J.

1996-03-01

Real-world applications of computational intelligence can enhance the fault detection and identification capabilities of a missile guidance and control system. A simulation of a bank-to- turn missile demonstrates that actuator failure may cause the missile to roll and miss the target. Failure of one fin actuator can be detected using a filter and depicting the filter output as fuzzy numbers. The properties and limitations of artificial neural networks fed by these fuzzy numbers are explored. A suite of networks is constructed to (1) detect a fault and (2) determine which fin (if any) failed. Both the zero order moment term and the fin rate term show changes during actuator failure. Simulations address the following questions: (1) How bad does the actuator failure have to be for detection to occur, (2) How bad does the actuator failure have to be for fault detection and isolation to occur, (3) are both zero order moment and fine rate terms needed. A suite of target trajectories are simulated, and properties and limitations of the approach reported. In some cases, detection of the failed actuator occurs within 0.1 second, and isolation of the failure occurs 0.1 after that. Suggestions for further research are offered.

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.

Bond-slip detection of concrete-encased composite structure using electro-mechanical impedance technique

NASA Astrophysics Data System (ADS)

Liang, Yabin; Li, Dongsheng; Parvasi, Seyed Mohammad; Kong, Qingzhao; Lim, Ing; Song, Gangbing

2016-09-01

Concrete-encased composite structure is a type of structure that takes the advantages of both steel and concrete materials, showing improved strength, ductility, and fire resistance compared to traditional reinforced concrete structures. The interface between concrete and steel profiles governs the interaction between these two materials under loading, however, debonding damage between these two materials may lead to severe degradation of the load transferring capacity which will affect the structural performance significantly. In this paper, the electro-mechanical impedance (EMI) technique using piezoceramic transducers was experimentally investigated to detect the bond-slip occurrence of the concrete-encased composite structure. The root-mean-square deviation is used to quantify the variations of the impedance signatures due to the presence of the bond-slip damage. In order to verify the validity of the proposed method, finite element model analysis was performed to simulate the behavior of concrete-steel debonding based on a 3D finite element concrete-steel bond model. The computed impedance signatures from the numerical results are compared with the results obtained from the experimental study, and both the numerical and experimental studies verify the proposed EMI method to detect bond slip of a concrete-encased composite structure.

Fault detection for piecewise affine systems with application to ship propulsion systems.

PubMed

Yang, Ying; Linlin, Li; Ding, Steven X; Qiu, Jianbin; Peng, Kaixiang

2017-09-09

In this paper, the design approach of non-synchronized diagnostic observer-based fault detection (FD) systems is investigated for piecewise affine processes via continuous piecewise Lyapunov functions. Considering that the dynamics of piecewise affine systems in different regions can be considerably different, the weighting matrices are used to weight the residual of each region, so as to optimize the fault detectability. A numerical example and a case study on a ship propulsion system are presented in the end to demonstrate the effectiveness of the proposed results. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Quantum optics in a high impedance environment

NASA Astrophysics Data System (ADS)

Puertas, Javier; Gheeraert, Nicolas; Krupko, Yuriy; Dassonneville, Remy; Planat, Luca; Foroughui, Farshad; Naud, Cecile; Guichard, Wiebke; Buisson, Olivier; Florens, Serge; Roch, Nicolas; Snyman, Izak

Understanding light matter interaction remains a key topic in fundamental physics. Its strength is imposed by the fine structure constant, α. For most atomic and molecular systems α =e2/ℏc 4 πɛo = 1 / 137 << 1 , giving weak interactions. When dealing with superconducting artificial atoms, α is either proportional to 1 /Zc (magnetic coupling) or Zc (electric coupling), where Zc is the characteristic impedance of the environment. Recent experiments followed the first approach, coupling a flux qubit to a low impedance environment, demonstrating strong interaction (α 1). In our work, we reached the large α regime, following a complementary approach: we couple electrically a transmon qubit to an array of 5000 SQUIDs. This metamaterial provides high characteristic impedance ( 3 kΩ), in-situ flux tunability and full control over its dispersion relation. In this new regime, all usual approximations break down and new phenomena such as frequency conversion at the single photon level are expected.

Meandered-line antenna with integrated high-impedance surface.

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

Forman, Michael A.

2010-09-01

A reduced-volume antenna composed of a meandered-line dipole antenna over a finite-width, high-impedance surface is presented. The structure is novel in that the high-impedance surface is implemented with four Sievenpiper via-mushroom unit cells, whose area is optimized to match the meandered-line dipole antenna. The result is an antenna similar in performance to patch antenna but one fourth the area that can be deployed directly on the surface of a conductor. Simulations demonstrate a 3.5 cm ({lambda}/4) square antenna with a bandwidth of 4% and a gain of 4.8 dBi at 2.5 GHz.

Torsional vibration signal analysis as a diagnostic tool for planetary gear fault detection

NASA Astrophysics Data System (ADS)

Xue, Song; Howard, Ian

2018-02-01

This paper aims to investigate the effectiveness of using the torsional vibration signal as a diagnostic tool for planetary gearbox faults detection. The traditional approach for condition monitoring of the planetary gear uses a stationary transducer mounted on the ring gear casing to measure all the vibration data when the planet gears pass by with the rotation of the carrier arm. However, the time variant vibration transfer paths between the stationary transducer and the rotating planet gear modulate the resultant vibration spectra and make it complex. Torsional vibration signals are theoretically free from this modulation effect and therefore, it is expected to be much easier and more effective to diagnose planetary gear faults using the fault diagnostic information extracted from the torsional vibration. In this paper, a 20 degree of freedom planetary gear lumped-parameter model was developed to obtain the gear dynamic response. In the model, the gear mesh stiffness variations are the main internal vibration generation mechanism and the finite element models were developed for calculation of the sun-planet and ring-planet gear mesh stiffnesses. Gear faults on different components were created in the finite element models to calculate the resultant gear mesh stiffnesses, which were incorporated into the planetary gear model later on to obtain the faulted vibration signal. Some advanced signal processing techniques were utilized to analyses the fault diagnostic results from the torsional vibration. It was found that the planetary gear torsional vibration not only successfully detected the gear fault, but also had the potential to indicate the location of the gear fault. As a result, the planetary gear torsional vibration can be considered an effective alternative approach for planetary gear condition monitoring.

Interdigitated Array microelectrode-based electrochemical impedance immunosensor for detection of Escherichia coli O157:H7.

PubMed

Yang, Liju; Li, Yanbin; Erf, Gisela F

2004-02-15

A label-free electrochemical impedance immunosensor for rapid detection of Escherichia coli O157:H7 was developed by immobilizing anti-E. coli antibodies onto an indium-tin oxide interdigitated array (IDA) microelectrode. Based on the general electronic equivalent model of an electrochemical cell and the behavior of the IDA microelectrode, an equivalent circuit, consisting of an ohmic resistor of the electrolyte between two electrodes and a double layer capacitor, an electron-transfer resistor, and a Warburg impedance around each electrode, was introduced for interpretation of the impedance components of the IDA microelectrode system. The results showed that the immobilization of antibodies and the binding of E. coli cells to the IDA microelectrode surface increased the electron-transfer resistance, which was directly measured with electrochemical impedance spectroscopy in the presence of [Fe(CN)(6)](3-/4-) as a redox probe. The electron-transfer resistance was correlated with the concentration of E. coli cells in a range from 4.36 x 10(5) to 4.36 x 10(8) cfu/mL with the detection limit of 10(6) cfu/mL.

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.

Bearing Fault Detection Based on Empirical Wavelet Transform and Correlated Kurtosis by Acoustic Emission.

PubMed

Gao, Zheyu; Lin, Jing; Wang, Xiufeng; Xu, Xiaoqiang

2017-05-24

Rolling bearings are widely used in rotating equipment. Detection of bearing faults is of great importance to guarantee safe operation of mechanical systems. Acoustic emission (AE), as one of the bearing monitoring technologies, is sensitive to weak signals and performs well in detecting incipient faults. Therefore, AE is widely used in monitoring the operating status of rolling bearing. This paper utilizes Empirical Wavelet Transform (EWT) to decompose AE signals into mono-components adaptively followed by calculation of the correlated kurtosis (CK) at certain time intervals of these components. By comparing these CK values, the resonant frequency of the rolling bearing can be determined. Then the fault characteristic frequencies are found by spectrum envelope. Both simulation signal and rolling bearing AE signals are used to verify the effectiveness of the proposed method. The results show that the new method performs well in identifying bearing fault frequency under strong background noise.

3D seismic detection of shallow faults and fluid migration pathways offshore Southern Costa Rica: Application of neural-network meta-attributes

NASA Astrophysics Data System (ADS)

Kluesner, J. W.; Silver, E. A.; Nale, S. M.; Bangs, N. L.; McIntosh, K. D.

2013-12-01

We employ a seismic meta-attribute workflow to detect and analyze probable faults and fluid-pathways in 3D within the sedimentary section offshore Southern Costa Rica. During the CRISP seismic survey in 2011 we collected an 11 x 55 km grid of 3D seismic reflection data and high-resolvability EM122 multibeam data, with coverage extending from the incoming plate to the outer-shelf. We mapped numerous seafloor seep indicators, with distributions ranging from the lower-slope to ~15 km landward of the shelf break [Kluesner et al., 2013, G3, doi:10.1002/ggge.20058; Silver et al., this meeting]. We used the OpendTect software package to calculate meta-attribute volumes from the 3D seismic data in order to detect and visualize seismic discontinuities in 3D. This methodology consists of dip-steered filtering to pre-condition the data, followed by combining a set of advanced dip-steered seismic attributes into a single object probability attribute using a user-trained neural-network pattern-recognition algorithm. The parameters of the advanced seismic attributes are set for optimal detection of the desired geologic discontinuity (e.g. faults or fluid-pathways). The product is a measure of probability for the desired target that ranges between 0 and 1, with 1 representing the highest probability. Within the sedimentary section of the CRISP survey the results indicate focused fluid-migration pathways along dense networks of intersecting normal faults with approximately N-S and E-W trends. This pattern extends from the middle slope to the outer-shelf region. Dense clusters of fluid-migration pathways are located above basement highs and deeply rooted reverse faults [see Bangs et al., this meeting], including a dense zone of fluid-pathways imaged below IODP Site U1413. In addition, fault intersections frequently show an increased signal of fluid-migration and these zones may act as major conduits for fluid-flow through the sedimentary cover. Imaged fluid pathways root into high

Simple random sampling-based probe station selection for fault detection in wireless sensor networks.

PubMed

Huang, Rimao; Qiu, Xuesong; Rui, Lanlan

2011-01-01

Fault detection for wireless sensor networks (WSNs) has been studied intensively in recent years. Most existing works statically choose the manager nodes as probe stations and probe the network at a fixed frequency. This straightforward solution leads however to several deficiencies. Firstly, by only assigning the fault detection task to the manager node the whole network is out of balance, and this quickly overloads the already heavily burdened manager node, which in turn ultimately shortens the lifetime of the whole network. Secondly, probing with a fixed frequency often generates too much useless network traffic, which results in a waste of the limited network energy. Thirdly, the traditional algorithm for choosing a probing node is too complicated to be used in energy-critical wireless sensor networks. In this paper, we study the distribution characters of the fault nodes in wireless sensor networks, validate the Pareto principle that a small number of clusters contain most of the faults. We then present a Simple Random Sampling-based algorithm to dynamic choose sensor nodes as probe stations. A dynamic adjusting rule for probing frequency is also proposed to reduce the number of useless probing packets. The simulation experiments demonstrate that the algorithm and adjusting rule we present can effectively prolong the lifetime of a wireless sensor network without decreasing the fault detected rate.

Simple Random Sampling-Based Probe Station Selection for Fault Detection in Wireless Sensor Networks

PubMed Central

Huang, Rimao; Qiu, Xuesong; Rui, Lanlan

2011-01-01

Fault detection for wireless sensor networks (WSNs) has been studied intensively in recent years. Most existing works statically choose the manager nodes as probe stations and probe the network at a fixed frequency. This straightforward solution leads however to several deficiencies. Firstly, by only assigning the fault detection task to the manager node the whole network is out of balance, and this quickly overloads the already heavily burdened manager node, which in turn ultimately shortens the lifetime of the whole network. Secondly, probing with a fixed frequency often generates too much useless network traffic, which results in a waste of the limited network energy. Thirdly, the traditional algorithm for choosing a probing node is too complicated to be used in energy-critical wireless sensor networks. In this paper, we study the distribution characters of the fault nodes in wireless sensor networks, validate the Pareto principle that a small number of clusters contain most of the faults. We then present a Simple Random Sampling-based algorithm to dynamic choose sensor nodes as probe stations. A dynamic adjusting rule for probing frequency is also proposed to reduce the number of useless probing packets. The simulation experiments demonstrate that the algorithm and adjusting rule we present can effectively prolong the lifetime of a wireless sensor network without decreasing the fault detected rate. PMID:22163789

Customized Multiwavelets for Planetary Gearbox Fault Detection Based on Vibration Sensor Signals

PubMed Central

Sun, Hailiang; Zi, Yanyang; He, Zhengjia; Yuan, Jing; Wang, Xiaodong; Chen, Lue

2013-01-01

Planetary gearboxes exhibit complicated dynamic responses which are more difficult to detect in vibration signals than fixed-axis gear trains because of the special gear transmission structures. Diverse advanced methods have been developed for this challenging task to reduce or avoid unscheduled breakdown and catastrophic accidents. It is feasible to make fault features distinct by using multiwavelet denoising which depends on the feature separation and the threshold denoising. However, standard and fixed multiwavelets are not suitable for accurate fault feature detections because they are usually independent of the measured signals. To overcome this drawback, a method to construct customized multiwavelets based on the redundant symmetric lifting scheme is proposed in this paper. A novel indicator which combines kurtosis and entropy is applied to select the optimal multiwavelets, because kurtosis is sensitive to sharp impulses and entropy is effective for periodic impulses. The improved neighboring coefficients method is introduced into multiwavelet denoising. The vibration signals of a planetary gearbox from a satellite communication antenna on a measurement ship are captured under various motor speeds. The results show the proposed method could accurately detect the incipient pitting faults on two neighboring teeth in the planetary gearbox. PMID:23334609

Software-implemented fault insertion: An FTMP example

NASA Technical Reports Server (NTRS)

Czeck, Edward W.; Siewiorek, Daniel P.; Segall, Zary Z.

1987-01-01

This report presents a model for fault insertion through software; describes its implementation on a fault-tolerant computer, FTMP; presents a summary of fault detection, identification, and reconfiguration data collected with software-implemented fault insertion; and compares the results to hardware fault insertion data. Experimental results show detection time to be a function of time of insertion and system workload. For the fault detection time, there is no correlation between software-inserted faults and hardware-inserted faults; this is because hardware-inserted faults must manifest as errors before detection, whereas software-inserted faults immediately exercise the error detection mechanisms. In summary, the software-implemented fault insertion is able to be used as an evaluation technique for the fault-handling capabilities of a system in fault detection, identification and recovery. Although the software-inserted faults do not map directly to hardware-inserted faults, experiments show software-implemented fault insertion is capable of emulating hardware fault insertion, with greater ease and automation.

Discriminating movements of liquid and gas in the rabbit colon with impedance manometry.

PubMed

Mohd Rosli, R; Leibbrandt, R E; Wiklendt, L; Costa, M; Wattchow, D A; Spencer, N J; Brookes, S J; Omari, T I; Dinning, P G

2018-05-01

High-resolution impedance manometry is a technique that is well established in esophageal motility studies for relating motor patterns to bolus flow. The use of this technique in the colon has not been established. In isolated segments of rabbit proximal colon, we recorded motor patterns and the movement of liquid or gas boluses with a high-resolution impedance manometry catheter. These detected movements were compared to video recorded changes in gut diameter. Using the characteristic shapes of the admittance (inverse of impedance) and pressure signals associated with gas or liquid flow we developed a computational algorithm for the automated detection of these events. Propagating contractions detected by video were also recorded by manometry and impedance. Neither pressure nor admittance signals alone could distinguish between liquid and gas transit, however the precise relationship between admittance and pressure signals during bolus flow could. Training our computational algorithm upon these characteristic shapes yielded a detection accuracy of 87.7% when compared to gas or liquid bolus events detected by manual analysis. Characterizing the relationship between both admittance and pressure recorded with high-resolution impedance manometry can not only help in detecting luminal transit in real time, but also distinguishes between liquid and gaseous content. This technique holds promise for determining the propulsive nature of human colonic motor patterns. © 2017 John Wiley & Sons Ltd.

Fault detection and diagnosis in an industrial fed-batch cell culture process.

PubMed

Gunther, Jon C; Conner, Jeremy S; Seborg, Dale E

2007-01-01

A flexible process monitoring method was applied to industrial pilot plant cell culture data for the purpose of fault detection and diagnosis. Data from 23 batches, 20 normal operating conditions (NOC) and three abnormal, were available. A principal component analysis (PCA) model was constructed from 19 NOC batches, and the remaining NOC batch was used for model validation. Subsequently, the model was used to successfully detect (both offline and online) abnormal process conditions and to diagnose the root causes. This research demonstrates that data from a relatively small number of batches (approximately 20) can still be used to monitor for a wide range of process faults.

Evaluating the performance of a fault detection and diagnostic system for vapor compression equipment

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

Breuker, M.S.; Braun, J.E.

This paper presents a detailed evaluation of the performance of a statistical, rule-based fault detection and diagnostic (FDD) technique presented by Rossi and Braun (1997). Steady-state and transient tests were performed on a simple rooftop air conditioner over a range of conditions and fault levels. The steady-state data without faults were used to train models that predict outputs for normal operation. The transient data with faults were used to evaluate FDD performance. The effect of a number of design variables on FDD sensitivity for different faults was evaluated and two prototype systems were specified for more complete evaluation. Good performancemore » was achieved in detecting and diagnosing five faults using only six temperatures (2 input and 4 output) and linear models. The performance improved by about a factor of two when ten measurements (three input and seven output) and higher order models were used. This approach for evaluating and optimizing the performance of the statistical, rule-based FDD technique could be used as a design and evaluation tool when applying this FDD method to other packaged air-conditioning systems. Furthermore, the approach could also be modified to evaluate the performance of other FDD methods.« less

Fault Detection and Severity Analysis of Servo Valves Using Recurrence Quantification Analysis

DTIC Science & Technology

2014-10-02

Fault Detection and Severity Analysis of Servo Valves Using Recurrence Quantification Analysis M. Samadani1, C. A. Kitio Kwuimy2, and C. Nataraj3...diagnostics of nonlinear systems. A detailed nonlinear math- ematical model of a servo electro-hydraulic system has been used to demonstrate the procedure...Two faults have been considered associated with the servo valve including the in- creased friction between spool and sleeve and the degradation of the

A H-infinity Fault Detection and Diagnosis Scheme for Discrete Nonlinear System Using Output Probability Density Estimation

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

Zhang Yumin; Lum, Kai-Yew; Wang Qingguo

In this paper, a H-infinity fault detection and diagnosis (FDD) scheme for a class of discrete nonlinear system fault using output probability density estimation is presented. Unlike classical FDD problems, the measured output of the system is viewed as a stochastic process and its square root probability density function (PDF) is modeled with B-spline functions, which leads to a deterministic space-time dynamic model including nonlinearities, uncertainties. A weighting mean value is given as an integral function of the square root PDF along space direction, which leads a function only about time and can be used to construct residual signal. Thus,more » the classical nonlinear filter approach can be used to detect and diagnose the fault in system. A feasible detection criterion is obtained at first, and a new H-infinity adaptive fault diagnosis algorithm is further investigated to estimate the fault. Simulation example is given to demonstrate the effectiveness of the proposed approaches.« less

A H-infinity Fault Detection and Diagnosis Scheme for Discrete Nonlinear System Using Output Probability Density Estimation

NASA Astrophysics Data System (ADS)

Zhang, Yumin; Wang, Qing-Guo; Lum, Kai-Yew

2009-03-01

In this paper, a H-infinity fault detection and diagnosis (FDD) scheme for a class of discrete nonlinear system fault using output probability density estimation is presented. Unlike classical FDD problems, the measured output of the system is viewed as a stochastic process and its square root probability density function (PDF) is modeled with B-spline functions, which leads to a deterministic space-time dynamic model including nonlinearities, uncertainties. A weighting mean value is given as an integral function of the square root PDF along space direction, which leads a function only about time and can be used to construct residual signal. Thus, the classical nonlinear filter approach can be used to detect and diagnose the fault in system. A feasible detection criterion is obtained at first, and a new H-infinity adaptive fault diagnosis algorithm is further investigated to estimate the fault. Simulation example is given to demonstrate the effectiveness of the proposed approaches.

Fault Injection Campaign for a Fault Tolerant Duplex Framework

NASA Technical Reports Server (NTRS)

Sacco, Gian Franco; Ferraro, Robert D.; von llmen, Paul; Rennels, Dave A.

2007-01-01

Fault tolerance is an efficient approach adopted to avoid or reduce the damage of a system failure. In this work we present the results of a fault injection campaign we conducted on the Duplex Framework (DF). The DF is a software developed by the UCLA group [1, 2] that uses a fault tolerant approach and allows to run two replicas of the same process on two different nodes of a commercial off-the-shelf (COTS) computer cluster. A third process running on a different node, constantly monitors the results computed by the two replicas, and eventually restarts the two replica processes if an inconsistency in their computation is detected. This approach is very cost efficient and can be adopted to control processes on spacecrafts where the fault rate produced by cosmic rays is not very high.

A High Input Impedance Low Noise Integrated Front-End Amplifier for Neural Monitoring.

PubMed

Zhou, Zhijun; Warr, Paul A

2016-12-01

Within neural monitoring systems, the front-end amplifier forms the critical element for signal detection and pre-processing, which determines not only the fidelity of the biosignal, but also impacts power consumption and detector size. In this paper, a novel combined feedback loop-controlled approach is proposed to compensate for input leakage currents generated by low noise amplifiers when in integrated circuit form alongside signal leakage into the input bias network. This loop topology ensures the Front-End Amplifier (FEA) maintains a high input impedance across all manufacturing and operational variations. Measured results from a prototype manufactured on the AMS 0.35 [Formula: see text] CMOS technology is provided. This FEA consumes 3.1 [Formula: see text] in 0.042 [Formula: see text], achieves input impedance of 42 [Formula: see text], and 18.2 [Formula: see text] input-referred noise.

DIFFERENTIAL FAULT SENSING CIRCUIT

DOEpatents

Roberts, J.H.

1961-09-01

A differential fault sensing circuit is designed for detecting arcing in high-voltage vacuum tubes arranged in parallel. A circuit is provided which senses differences in voltages appearing between corresponding elements likely to fault. Sensitivity of the circuit is adjusted to some level above which arcing will cause detectable differences in voltage. For particular corresponding elements, a group of pulse transformers are connected in parallel with diodes connected across the secondaries thereof so that only voltage excursions are transmitted to a thyratron which is biased to the sensitivity level mentioned.

Fault detection and isolation in the challenging Tennessee Eastman process by using image processing techniques.

PubMed

Hajihosseini, Payman; Anzehaee, Mohammad Mousavi; Behnam, Behzad

2018-05-22

The early fault detection and isolation in industrial systems is a critical factor in preventing equipment damage. In the proposed method, instead of using the time signals of sensors, the 2D image obtained by placing these signals next to each other in a matrix has been used; and then a novel fault detection and isolation procedure has been carried out based on image processing techniques. Different features including texture, wavelet transform, mean and standard deviation of the image accompanied with MLP and RBF neural networks based classifiers have been used for this purpose. Obtained results indicate the notable efficacy and success of the proposed method in detecting and isolating faults of the Tennessee Eastman benchmark process and its superiority over previous techniques. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Microfluidic Impedance Flow Cytometry Enabling High-Throughput Single-Cell Electrical Property Characterization

PubMed Central

Chen, Jian; Xue, Chengcheng; Zhao, Yang; Chen, Deyong; Wu, Min-Hsien; Wang, Junbo

2015-01-01

This article reviews recent developments in microfluidic impedance flow cytometry for high-throughput electrical property characterization of single cells. Four major perspectives of microfluidic impedance flow cytometry for single-cell characterization are included in this review: (1) early developments of microfluidic impedance flow cytometry for single-cell electrical property characterization; (2) microfluidic impedance flow cytometry with enhanced sensitivity; (3) microfluidic impedance and optical flow cytometry for single-cell analysis and (4) integrated point of care system based on microfluidic impedance flow cytometry. We examine the advantages and limitations of each technique and discuss future research opportunities from the perspectives of both technical innovation and clinical applications. PMID:25938973

Using impedance cardiography with postural change to stratify patients with hypertension.

PubMed

DeMarzo, Arthur P

2011-06-01

Early detection of cardiovascular disease in patients with hypertension could initiate appropriate treatment to control blood pressure and prevent the progression of cardiovascular disease. The goal of this study was to show how impedance cardiography waveform analysis with postural change can be used to detect subclinical cardiovascular disease in patients with high blood pressure. Patients with high blood pressure had impedance cardiography data obtained in two positions, standing upright and supine. In 50 adults, impedance cardiography indicated that all patients had abnormal data, with 44 (88%) having multiple abnormalities. Impedance cardiography showed 32 (64%) had ventricular dysfunction, 48 (96%) had vascular load abnormalities, 34 (68%) had hemodynamic abnormalities, 2 (4%) had hypovolemia, and 3 (6%) had hypervolemia. Hypertensive patients have diverse cardiovascular abnormalities that can be quantified by impedance cardiography. By stratifying patients with ventricular, vascular, and hemodynamic abnormalities, treatment could be customized based on the abnormal underlying mechanisms with the potential to rapidly control blood pressure, prevent progression of cardiovascular disease, and possibly reverse remodeling.

Automatic Fault Characterization via Abnormality-Enhanced Classification

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

Bronevetsky, G; Laguna, I; de Supinski, B R

Enterprise and high-performance computing systems are growing extremely large and complex, employing hundreds to hundreds of thousands of processors and software/hardware stacks built by many people across many organizations. As the growing scale of these machines increases the frequency of faults, system complexity makes these faults difficult to detect and to diagnose. Current system management techniques, which focus primarily on efficient data access and query mechanisms, require system administrators to examine the behavior of various system services manually. Growing system complexity is making this manual process unmanageable: administrators require more effective management tools that can detect faults and help tomore » identify their root causes. System administrators need timely notification when a fault is manifested that includes the type of fault, the time period in which it occurred and the processor on which it originated. Statistical modeling approaches can accurately characterize system behavior. However, the complex effects of system faults make these tools difficult to apply effectively. This paper investigates the application of classification and clustering algorithms to fault detection and characterization. We show experimentally that naively applying these methods achieves poor accuracy. Further, we design novel techniques that combine classification algorithms with information on the abnormality of application behavior to improve detection and characterization accuracy. Our experiments demonstrate that these techniques can detect and characterize faults with 65% accuracy, compared to just 5% accuracy for naive approaches.« less

A regenerating ultrasensitive electrochemical impedance immunosensor for the detection of adenovirus.

PubMed

Lin, Donghai; Tang, Thompson; Jed Harrison, D; Lee, William E; Jemere, Abebaw B

2015-06-15

We report on the development of a regenerable sensitive immunosensor based on electrochemical impedance spectroscopy for the detection of type 5 adenovirus. The multi-layered immunosensor fabrication involved successive modification steps on gold electrodes: (i) modification with self-assembled layer of 1,6-hexanedithiol to which gold nanoparticles were attached via the distal thiol groups, (ii) formation of self-assembled monolayer of 11-mercaptoundecanoic acid onto the gold nanoparticles, (iii) covalent immobilization of monoclonal anti-adenovirus 5 antibody, with EDC/NHS coupling reaction on the nanoparticles, completing the immunosensor. The immunosensor displayed a very good detection limit of 30 virus particles/ml and a wide linear dynamic range of 10(5). An electrochemical reductive desorption technique was employed to completely desorb the components of the immunosensor surface, then re-assemble the sensing layer and reuse the sensor. On a single electrode, the multi-layered immunosensor could be assembled and disassembled at least 30 times with 87% of the original signal intact. The changes of electrode behavior after each assembly and desorption processes were investigated by cyclic voltammetry, electrochemical impedance spectroscopy and X-ray photoelectron spectroscopy techniques. Copyright © 2014 Elsevier B.V. All rights reserved.

High Impedance Comparator for Monitoring Water Resistivity.

ERIC Educational Resources Information Center

Holewinski, Paul K.

1984-01-01

A high-impedance comparator suitable for monitoring the resistivity of a deionized or distilled water line supplying water in the 50 Kohm/cm-2 Mohm/cm range is described. Includes information on required circuits (with diagrams), sensor probe assembly, and calibration techniques. (JN)

Aircraft applications of fault detection and isolation techniques

NASA Astrophysics Data System (ADS)

Marcos Esteban, Andres

In this thesis the problems of fault detection & isolation and fault tolerant systems are studied from the perspective of LTI frequency-domain, model-based techniques. Emphasis is placed on the applicability of these LTI techniques to nonlinear models, especially to aerospace systems. Two applications of Hinfinity LTI fault diagnosis are given using an open-loop (no controller) design approach: one for the longitudinal motion of a Boeing 747-100/200 aircraft, the other for a turbofan jet engine. An algorithm formalizing a robust identification approach based on model validation ideas is also given and applied to the previous jet engine. A general linear fractional transformation formulation is given in terms of the Youla and Dual Youla parameterizations for the integrated (control and diagnosis filter) approach. This formulation provides better insight into the trade-off between the control and the diagnosis objectives. It also provides the basic groundwork towards the development of nested schemes for the integrated approach. These nested structures allow iterative improvements on the control/filter Youla parameters based on successive identification of the system uncertainty (as given by the Dual Youla parameter). The thesis concludes with an application of Hinfinity LTI techniques to the integrated design for the longitudinal motion of the previous Boeing 747-100/200 model.

Method and system for early detection of incipient faults in electric motors

DOEpatents

Parlos, Alexander G; Kim, Kyusung

2003-07-08

A method and system for early detection of incipient faults in an electric motor are disclosed. First, current and voltage values for one or more phases of the electric motor are measured during motor operations. A set of current predictions is then determined via a neural network-based current predictor based on the measured voltage values and an estimate of motor speed values of the electric motor. Next, a set of residuals is generated by combining the set of current predictions with the measured current values. A set of fault indicators is subsequently computed from the set of residuals and the measured current values. Finally, a determination is made as to whether or not there is an incipient electrical, mechanical, and/or electromechanical fault occurring based on the comparison result of the set of fault indicators and a set of predetermined baseline values.

Admittance detector for high impedance systems: design and applications.

PubMed

Zhang, Min; Stamos, Brian N; Dasgupta, Purnendu K

2014-12-02

We describe an admittance detector for high impedance systems (small capillary bore and/or low solution specific conductance). Operation in the low frequency range (≤1 kHz, much lower than most relevant publications) provides optimum response to conductance changes in capillaries ≤20 μm in bore. The detector design was based on studies described in a preceding companion paper ( Zhang, M.; Stamos, B. N.; Amornthammarong, N.; Dasgupta, P. K. Anal. Chem. 2014, 8 , DOI 10.1021/ac503245a.). The highest S/N for detecting 100 μM KCl (5.5 μM peak concentration, ∼0.8 μS/cm) injected into water flowing through a capillary of 7.5 μm inner radius (r) was observed at 500-750 Hz. A low bias current operational amplifier in the transimpedance configuration permitted high gain (1 V/nA) to measure pA-nA level currents in the detection cell. Aside from an oscillator, an offset-capable RMS-DC converter formed the complete detection circuitry. Limits of detection (LODs) of KCl scaled inversely with the capillary cross section and were 2.1 and 0.32 μM injected KCl for r = 1 and 2.5 μm capillaries, respectively. When used as a detector on an r = 8 μm bore poly(methyl methacrylate) capillary in a split effluent stream from a suppressed ion chromatograph, the LOD was 27 nM bromide (Vex 22 V p-p), compared to 14 nM observed with a commercial bipolar pulse macroscale conductivity detector with an actively thermostated cell. We also show applications of the detector in electrophoresis in capillaries with r = 1 and 2.5 μm. Efficient heat dissipation permits high concentrations of the background electrolyte and sensitive detection because of efficient electrostacking.

A new spinner magnetometer using high sensitivity magneto-impedance sensor

NASA Astrophysics Data System (ADS)

Kodama, Kazuto

2016-04-01

A sensitive spinner magnetometer was developed using a pair of high-resolution Magneto-Impedance sensors. The MI sensor generally utilizes the MI effect of amorphous wire whose impedance changes by the application of a small magnetic field. Various kinds of MI sensors are currently used in many electric devices, for example, a magnetic compass chip built-in smart phones and car navigations. The MI sensor employed in this study is a pico-Tesla MI sensor, an especially sensitive MI sensor originally manufactured for industrial use to detect contamination of small magnetic particles in industrial materials such as fabrics. To detect weak magnetic signals from natural samples and avoid DC drift, a gradiometer system was employed that consists of a pair of the MI sensors and the electronics with analog filter and pre-amplification circuit. This MI gradiometer system was equipped to a commercial spinner magnetometer (SMD-88, Natsuhara Giken, Osaka) with the spinning rate of 5 Hz. It is demonstrated that this new spinner magnetometer is capable of measuring weak magnetic samples of 10-6 mAm2, with the highest resolution being 10-8 mAm2, approximately two orders of magnitude better than the previous one using a ring-core flux-gate sensor. One of the advantages of the MI spinner magnetometer is that it can be easily modified to accommodate samples of any shape and size. Moreover the slow-rotating speed (5 Hz) allows to measure samples for archeomagnetic studies that are usually irregular and fragile. Because the irregularity of shape increases errors in measuring the dipole component of the total magnetization, it is necessary to increase the distance between the sample and sensor, resulting in poorer sensitivity. The high-sensitivity MI sensor enables to measure the NRM of such irregular-shaped samples from an appropriate distance to the sample, with no significant loss of sensitivity.

Fault Diagnosis for Centre Wear Fault of Roll Grinder Based on a Resonance Demodulation Scheme

NASA Astrophysics Data System (ADS)

Wang, Liming; Shao, Yimin; Yin, Lei; Yuan, Yilin; Liu, Jing

2017-05-01

Roll grinder is one of the important parts in the rolling machinery, and the grinding precision of roll surface has direct influence on the surface quality of steel strip. However, during the grinding process, the centre bears the gravity of the roll and alternating stress. Therefore, wear or spalling faults are easily observed on the centre, which will lead to an anomalous vibration of the roll grinder. In this study, a resonance demodulation scheme is proposed to detect the centre wear fault of roll grinder. Firstly, fast kurtogram method is employed to help select the sub-band filter parameters for optimal resonance demodulation. Further, the envelope spectrum are derived based on the filtered signal. Finally, two health indicators are designed to conduct the fault diagnosis for centre wear fault. The proposed scheme is assessed by analysing experimental data from a roll grinder of twenty-high rolling mill. The results show that the proposed scheme can effectively detect the centre wear fault of the roll grinder.

An autonomous fault detection, isolation, and recovery system for a 20-kHz electric power distribution test bed

NASA Technical Reports Server (NTRS)

Quinn, Todd M.; Walters, Jerry L.

1991-01-01

Future space explorations will require long term human presence in space. Space environments that provide working and living quarters for manned missions are becoming increasingly larger and more sophisticated. Monitor and control of the space environment subsystems by expert system software, which emulate human reasoning processes, could maintain the health of the subsystems and help reduce the human workload. The autonomous power expert (APEX) system was developed to emulate a human expert's reasoning processes used to diagnose fault conditions in the domain of space power distribution. APEX is a fault detection, isolation, and recovery (FDIR) system, capable of autonomous monitoring and control of the power distribution system. APEX consists of a knowledge base, a data base, an inference engine, and various support and interface software. APEX provides the user with an easy-to-use interactive interface. When a fault is detected, APEX will inform the user of the detection. The user can direct APEX to isolate the probable cause of the fault. Once a fault has been isolated, the user can ask APEX to justify its fault isolation and to recommend actions to correct the fault. APEX implementation and capabilities are discussed.

Operations management system advanced automation: Fault detection isolation and recovery prototyping

NASA Technical Reports Server (NTRS)

Hanson, Matt

1990-01-01

The purpose of this project is to address the global fault detection, isolation and recovery (FDIR) requirements for Operation's Management System (OMS) automation within the Space Station Freedom program. This shall be accomplished by developing a selected FDIR prototype for the Space Station Freedom distributed processing systems. The prototype shall be based on advanced automation methodologies in addition to traditional software methods to meet the requirements for automation. A secondary objective is to expand the scope of the prototyping to encompass multiple aspects of station-wide fault management (SWFM) as discussed in OMS requirements documentation.

Detection of faults and software reliability analysis

NASA Technical Reports Server (NTRS)

Knight, J. C.

1986-01-01

Multiversion or N-version programming was proposed as a method of providing fault tolerance in software. The approach requires the separate, independent preparation of multiple versions of a piece of software for some application. Specific topics addressed are: failure probabilities in N-version systems, consistent comparison in N-version systems, descriptions of the faults found in the Knight and Leveson experiment, analytic models of comparison testing, characteristics of the input regions that trigger faults, fault tolerance through data diversity, and the relationship between failures caused by automatically seeded faults.

Simultaneous fault detection and control design for switched systems with two quantized signals.

PubMed

Li, Jian; Park, Ju H; Ye, Dan

2017-01-01

The problem of simultaneous fault detection and control design for switched systems with two quantized signals is presented in this paper. Dynamic quantizers are employed, respectively, before the output is passed to fault detector, and before the control input is transmitted to the switched system. Taking the quantized errors into account, the robust performance for this kind of system is given. Furthermore, sufficient conditions for the existence of fault detector/controller are presented in the framework of linear matrix inequalities, and fault detector/controller gains and the supremum of quantizer range are derived by a convex optimized method. Finally, two illustrative examples demonstrate the effectiveness of the proposed method. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Real time automatic detection of bearing fault in induction machine using kurtogram analysis.

PubMed

Tafinine, Farid; Mokrani, Karim

2012-11-01

A proposed signal processing technique for incipient real time bearing fault detection based on kurtogram analysis is presented in this paper. The kurtogram is a fourth-order spectral analysis tool introduced for detecting and characterizing non-stationarities in a signal. This technique starts from investigating the resonance signatures over selected frequency bands to extract the representative features. The traditional spectral analysis is not appropriate for non-stationary vibration signal and for real time diagnosis. The performance of the proposed technique is examined by a series of experimental tests corresponding to different bearing conditions. Test results show that this signal processing technique is an effective bearing fault automatic detection method and gives a good basis for an integrated induction machine condition monitor.

Fault Detection and Correction for the Solar Dynamics Observatory Attitude Control System

NASA Technical Reports Server (NTRS)

Starin, Scott R.; Vess, Melissa F.; Kenney, Thomas M.; Maldonado, Manuel D.; Morgenstern, Wendy M.

2007-01-01

The Solar Dynamics Observatory is an Explorer-class mission that will launch in early 2009. The spacecraft will operate in a geosynchronous orbit, sending data 24 hours a day to a devoted ground station in White Sands, New Mexico. It will carry a suite of instruments designed to observe the Sun in multiple wavelengths at unprecedented resolution. The Atmospheric Imaging Assembly includes four telescopes with focal plane CCDs that can image the full solar disk in four different visible wavelengths. The Extreme-ultraviolet Variability Experiment will collect time-correlated data on the activity of the Sun's corona. The Helioseismic and Magnetic Imager will enable study of pressure waves moving through the body of the Sun. The attitude control system on Solar Dynamics Observatory is responsible for four main phases of activity. The physical safety of the spacecraft after separation must be guaranteed. Fine attitude determination and control must be sufficient for instrument calibration maneuvers. The mission science mode requires 2-arcsecond control according to error signals provided by guide telescopes on the Atmospheric Imaging Assembly, one of the three instruments to be carried. Lastly, accurate execution of linear and angular momentum changes to the spacecraft must be provided for momentum management and orbit maintenance. In thsp aper, single-fault tolerant fault detection and correction of the Solar Dynamics Observatory attitude control system is described. The attitude control hardware suite for the mission is catalogued, with special attention to redundancy at the hardware level. Four reaction wheels are used where any three are satisfactory. Four pairs of redundant thrusters are employed for orbit change maneuvers and momentum management. Three two-axis gyroscopes provide full redundancy for rate sensing. A digital Sun sensor and two autonomous star trackers provide two-out-of-three redundancy for fine attitude determination. The use of software to maximize

Real World Experience With Ion Implant Fault Detection at Freescale Semiconductor

NASA Astrophysics Data System (ADS)

Sing, David C.; Breeden, Terry; Fakhreddine, Hassan; Gladwin, Steven; Locke, Jason; McHugh, Jim; Rendon, Michael

2006-11-01

The Freescale automatic fault detection and classification (FDC) system has logged data from over 3.5 million implants in the past two years. The Freescale FDC system is a low cost system which collects summary implant statistics at the conclusion of each implant run. The data is collected by either downloading implant data log files from the implant tool workstation, or by exporting summary implant statistics through the tool's automation interface. Compared to the traditional FDC systems which gather trace data from sensors on the tool as the implant proceeds, the Freescale FDC system cannot prevent scrap when a fault initially occurs, since the data is collected after the implant concludes. However, the system can prevent catastrophic scrap events due to faults which are not detected for days or weeks, leading to the loss of hundreds or thousands of wafers. At the Freescale ATMC facility, the practical applications of the FD system fall into two categories: PM trigger rules which monitor tool signals such as ion gauges and charge control signals, and scrap prevention rules which are designed to detect specific failure modes that have been correlated to yield loss and scrap. PM trigger rules are designed to detect shifts in tool signals which indicate normal aging of tool systems. For example, charging parameters gradually shift as flood gun assemblies age, and when charge control rules start to fail a flood gun PM is performed. Scrap prevention rules are deployed to detect events such as particle bursts and excessive beam noise, events which have been correlated to yield loss. The FDC system does have tool log-down capability, and scrap prevention rules often use this capability to automatically log the tool into a maintenance state while simultaneously paging the sustaining technician for data review and disposition of the affected product.

Detection, isolation and diagnosability analysis of intermittent faults in stochastic systems

NASA Astrophysics Data System (ADS)

Yan, Rongyi; He, Xiao; Wang, Zidong; Zhou, D. H.

2018-02-01

Intermittent faults (IFs) have the properties of unpredictability, non-determinacy, inconsistency and repeatability, switching systems between faulty and healthy status. In this paper, the fault detection and isolation (FDI) problem of IFs in a class of linear stochastic systems is investigated. For the detection and isolation of IFs, it includes: (1) to detect all the appearing time and the disappearing time of an IF; (2) to detect each appearing (disappearing) time of the IF before the subsequent disappearing (appearing) time; (3) to determine where the IFs happen. Based on the outputs of the observers we designed, a novel set of residuals is constructed by using the sliding-time window technique, and two hypothesis tests are proposed to detect all the appearing time and disappearing time of IFs. The isolation problem of IFs is also considered. Furthermore, within a statistical framework, the definition of the diagnosability of IFs is proposed, and a sufficient condition is brought forward for the diagnosability of IFs. Quantitative performance analysis results for the false alarm rate and missing detection rate are discussed, and the influences of some key parameters of the proposed scheme on performance indices such as the false alarm rate and missing detection rate are analysed rigorously. The effectiveness of the proposed scheme is illustrated via a simulation example of an unmanned helicopter longitudinal control system.

RCS propulsion functional path analysis for performance monitoring fault detection and annunciation

NASA Technical Reports Server (NTRS)

Keesler, E. L.

1974-01-01

The operational flight instrumentation required for performance monitoring and fault detection are presented. Measurements by the burn through monitors are presented along with manifold and helium source pressures.

An Inexpensive, Very High Impedance Digital Voltmeter for Selective Electrodes.

ERIC Educational Resources Information Center

Caceci, Marco S.

1984-01-01

Describes a compact, digital voltmeter which exceeds, both in accuracy and input impedance, most commercial pH meters and potentiometers. The instrument consists of two parts: a very high impedance hybrid operational amplifier used as a voltage follower (ICH8500/A, Intersil) and a four and one-half digits LED display panel meter (RP-4500,…

Cryogenic low noise and low dissipation multiplexing electronics, using HEMT+SiGe ASICs, for the readout of high impedance sensors: New version

NASA Astrophysics Data System (ADS)

de la Broïse, Xavier; Lugiez, Francis; Bounab, Ayoub; Le Coguie, Alain

2015-07-01

High Electron Mobility Transistors (HEMTs), optimized by CNRS/LPN laboratory for ultra-low noise at very low temperature, have demonstrated their capacity to be used in place of Si JFETs when working temperatures below 100 K are required. We associated them with specific SiGe ASICs that we developed, to implement a complete readout channel able to read highly segmented high impedance detectors within a framework of very low thermal dissipation. Our electronics is dimensioned to read 4096 detection channels, of typically 1 MΩ impedance, and performs 32:1 multiplexing and amplifying, dissipating only 6 mW at 2.5 K and 100 mW at 15 K thanks to high impedance commuting of input stage, with a typical noise of 1 nV/√Hz at 1 kHz.

Fault detection and diagnosis for non-Gaussian stochastic distribution systems with time delays via RBF neural networks.

PubMed

Yi, Qu; Zhan-ming, Li; Er-chao, Li

2012-11-01

A new fault detection and diagnosis (FDD) problem via the output probability density functions (PDFs) for non-gausian stochastic distribution systems (SDSs) is investigated. The PDFs can be approximated by radial basis functions (RBFs) neural networks. Different from conventional FDD problems, the measured information for FDD is the output stochastic distributions and the stochastic variables involved are not confined to Gaussian ones. A (RBFs) neural network technique is proposed so that the output PDFs can be formulated in terms of the dynamic weighings of the RBFs neural network. In this work, a nonlinear adaptive observer-based fault detection and diagnosis algorithm is presented by introducing the tuning parameter so that the residual is as sensitive as possible to the fault. Stability and Convergency analysis is performed in fault detection and fault diagnosis analysis for the error dynamic system. At last, an illustrated example is given to demonstrate the efficiency of the proposed algorithm, and satisfactory results have been obtained. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Delineating Concealed Faults within Cogdell Oil Field via Earthquake Detection

NASA Astrophysics Data System (ADS)

Aiken, C.; Walter, J. I.; Brudzinski, M.; Skoumal, R.; Savvaidis, A.; Frohlich, C.; Borgfeldt, T.; Dotray, P.

2016-12-01

Cogdell oil field, located within the Permian Basin of western Texas, has experienced several earthquakes ranging from magnitude 1.7 to 4.6, most of which were recorded since 2006. Using the Earthscope USArray, Gan and Frohlich [2013] relocated some of these events and found a positive correlation in the timing of increased earthquake activity and increased CO2 injection volume. However, focal depths of these earthquakes are unknown due to 70 km station spacing of the USArray. Accurate focal depths as well as new detections can delineate subsurface faults and establish whether earthquakes are occurring in the shallow sediments or in the deeper basement. To delineate subsurface fault(s) in this region, we first detect earthquakes not currently listed in the USGS catalog by applying continuous waveform-template matching algorithms to multiple seismic data sets. We utilize seismic data spanning the time frame of 2006 to 2016 - which includes data from the U.S. Geological Survey Global Seismographic Network, the USArray, and the Sweetwater, TX broadband and nodal array located 20-40 km away. The catalog of earthquakes enhanced by template matching reveals events that were well recorded by the large-N Sweetwater array, so we are experimenting with strategies for optimizing template matching using different configurations of many stations. Since earthquake activity in the Cogdell oil field is on-going (a magnitude 2.6 occurred on May 29, 2016), a temporary deployment of TexNet seismometers has been planned for the immediate vicinity of Cogdell oil field in August 2016. Results on focal depths and detection of small magnitude events are pending this small local network deployment.

Detection of an explosive simulant via electrical impedance spectroscopy utilizing the UiO-66-NH2 metal-organic framework.

PubMed

Peterson, G W; McEntee, M; Harris, C R; Klevitch, A D; Fountain, A W; Soliz, J R; Balboa, A; Hauser, A J

2016-11-01

Electrical impedance spectroscopy, in conjunction with the metal-organic framework (MOF) UiO-66-NH 2 , is used to detect trace levels of the explosive simulant 2,6-dinitrotoluene. The combination of porosity and functionality of the MOF provides an effective dielectric structure, resulting in changes of impedance magnitude and phase angle. The promising data indicate that MOFs may be used in low-cost, robust explosive detection devices.

A DEMO relevant fast wave current drive high harmonic antenna exploiting the high impedance technique

NASA Astrophysics Data System (ADS)

Milanesio, D.; Maggiora, R.

2015-12-01

Ion Cyclotron (IC) antennas are routinely adopted in most of the existing nuclear fusion experiments, even though their main goal, i.e. to couple high power to the plasma (MW), is often limited by rather severe drawbacks due to high fields on the antenna itself and on the unmatched part of the feeding lines. In addition to the well exploited auxiliary ion heating during the start-up phase, some non-ohmic current drive (CD) at the IC range of frequencies may be explored in view of the DEMO reactor. In this work, we suggest and describe a compact high frequency DEMO relevant antenna, based on the high impedance surfaces concept. High-impedance surfaces are periodic metallic structures (patches) usually displaced on top of a dielectric substrate and grounded by means of vertical posts embedded inside the dielectric, in a mushroom-like shape. These structures present a high impedance, within a given frequency band, such that the image currents are in-phase with the currents of the antenna itself, thus determining a significant efficiency increase. After a general introduction on the properties of high impedance surfaces, we analyze, by means of numerical codes, a dielectric based and a full metal solution optimized to be tested and benchmarked on the FTU experiment fed with generators at 433MHz.

A DEMO relevant fast wave current drive high harmonic antenna exploiting the high impedance technique

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

Milanesio, D., E-mail: daniele.milanesio@polito.it; Maggiora, R.

Ion Cyclotron (IC) antennas are routinely adopted in most of the existing nuclear fusion experiments, even though their main goal, i.e. to couple high power to the plasma (MW), is often limited by rather severe drawbacks due to high fields on the antenna itself and on the unmatched part of the feeding lines. In addition to the well exploited auxiliary ion heating during the start-up phase, some non-ohmic current drive (CD) at the IC range of frequencies may be explored in view of the DEMO reactor. In this work, we suggest and describe a compact high frequency DEMO relevant antenna,more » based on the high impedance surfaces concept. High-impedance surfaces are periodic metallic structures (patches) usually displaced on top of a dielectric substrate and grounded by means of vertical posts embedded inside the dielectric, in a mushroom-like shape. These structures present a high impedance, within a given frequency band, such that the image currents are in-phase with the currents of the antenna itself, thus determining a significant efficiency increase. After a general introduction on the properties of high impedance surfaces, we analyze, by means of numerical codes, a dielectric based and a full metal solution optimized to be tested and benchmarked on the FTU experiment fed with generators at 433MHz.« less

Online Detection of Broken Rotor Bar Fault in Induction Motors by Combining Estimation of Signal Parameters via Min-norm Algorithm and Least Square Method

NASA Astrophysics Data System (ADS)

Wang, Pan-Pan; Yu, Qiang; Hu, Yong-Jun; Miao, Chang-Xin

2017-11-01

Current research in broken rotor bar (BRB) fault detection in induction motors is primarily focused on a high-frequency resolution analysis of the stator current. Compared with a discrete Fourier transformation, the parametric spectrum estimation technique has a higher frequency accuracy and resolution. However, the existing detection methods based on parametric spectrum estimation cannot realize online detection, owing to the large computational cost. To improve the efficiency of BRB fault detection, a new detection method based on the min-norm algorithm and least square estimation is proposed in this paper. First, the stator current is filtered using a band-pass filter and divided into short overlapped data windows. The min-norm algorithm is then applied to determine the frequencies of the fundamental and fault characteristic components with each overlapped data window. Next, based on the frequency values obtained, a model of the fault current signal is constructed. Subsequently, a linear least squares problem solved through singular value decomposition is designed to estimate the amplitudes and phases of the related components. Finally, the proposed method is applied to a simulated current and an actual motor, the results of which indicate that, not only parametric spectrum estimation technique.

Optimal Sensor Location Design for Reliable Fault Detection in Presence of False Alarms

PubMed Central

Yang, Fan; Xiao, Deyun; Shah, Sirish L.

2009-01-01

To improve fault detection reliability, sensor location should be designed according to an optimization criterion with constraints imposed by issues of detectability and identifiability. Reliability requires the minimization of undetectability and false alarm probability due to random factors on sensor readings, which is not only related with sensor readings but also affected by fault propagation. This paper introduces the reliability criteria expression based on the missed/false alarm probability of each sensor and system topology or connectivity derived from the directed graph. The algorithm for the optimization problem is presented as a heuristic procedure. Finally, a boiler system is illustrated using the proposed method. PMID:22291524

Ground Deformation near active faults in the Kinki district, southwest Japan, detected by InSAR

NASA Astrophysics Data System (ADS)

Hashimoto, M.; Ozawa, T.

2016-12-01

The Kinki district, southwest Japan, consists of ranges and plains between which active faults reside. The Osaka plain is in the middle of this district and is surrounded by the Rokko, Arima-Takatsuki, Ikoma, Kongo and Median Tectonic Line fault zones in the clockwise order. These faults are considered to be capable to generate earthquakes of larger magnitude than 7. The 1995 Kobe earthquake is the most recent activity of the Rokko fault (NE-SW trending dextral fault). Therefore the monitoring of ground deformation with high spatial resolution is essential to evaluate seismic hazards in this area. We collected and analyzed available SAR images such as ERS-1/2, Envisat, JERS-1, TerraSAR-X, ALOS/PALSAR and ALOS-2/PALSAR-2 to reveal ground deformation during these 20 years. We made DInSAR and PSInSAR analyses of these images using ASTER-GDEM ver.2. We detected three spots of subsidence along the Arima-Takatsuki fault (ENE-WSW trending dextral fault, east neighbor of the Rokko fault) after the Kobe earthquake, which continued up to 2010. Two of them started right after the Kobe earthquake, while the easternmost one was observed after 2000. However, we did not find them in the interferograms of ALOS-2/PALSAR-2 acquired during 2014 - 2016. Marginal uplift was recognized along the eastern part of the Rokko fault. PS-InSAR results of ALOS/PALSAR also revealed slight uplift north of the Rokko Mountain that uplift by 20 cm coseismically. These observations suggest that the Rokko Mountain might have uplifted during the postseismic period. We found subsidence on the eastern frank of the Kongo Mountain, where the Kongo fault (N-S trending reverse fault) exits. In the southern neighbor of the Median Tectonic Line (ENE-WSW trending dextral fault), uplift of > 5 mm/yr was found by Envisat and ALOS/PALSAR images. This area is shifted westward by 4 mm/yr as well. Since this area is located east of a seismically active area in the northwestern Wakayama prefecture, this deformation

Detection of thoracic vascular structures by electrical impedance tomography: a systematic assessment of prominence peak analysis of impedance changes.

PubMed

Wodack, K H; Buehler, S; Nishimoto, S A; Graessler, M F; Behem, C R; Waldmann, A D; Mueller, B; Böhm, S H; Kaniusas, E; Thürk, F; Maerz, A; Trepte, C J C; Reuter, D A

2018-02-28

Electrical impedance tomography (EIT) is a non-invasive and radiation-free bedside monitoring technology, primarily used to monitor lung function. First experimental data shows that the descending aorta can be detected at different thoracic heights and might allow the assessment of central hemodynamics, i.e. stroke volume and pulse transit time. First, the feasibility of localizing small non-conductive objects within a saline phantom model was evaluated. Second, this result was utilized for the detection of the aorta by EIT in ten anesthetized pigs with comparison to thoracic computer tomography (CT). Two EIT belts were placed at different thoracic positions and a bolus of hypertonic saline (10 ml, 20%) was administered into the ascending aorta while EIT data were recorded. EIT images were reconstructed using the GREIT model, based on the individual's thoracic contours. The resulting EIT images were analyzed pixel by pixel to identify the aortic pixel, in which the bolus caused the highest transient impedance peak in time. In the phantom, small objects could be located at each position with a maximal deviation of 0.71 cm. In vivo, no significant differences between the aorta position measured by EIT and the anatomical aorta location were obtained for both measurement planes if the search was restricted to the dorsal thoracic region of interest (ROIs). It is possible to detect the descending aorta at different thoracic levels by EIT using an intra-aortic bolus of hypertonic saline. No significant differences in the position of the descending aorta on EIT images compared to CT images were obtained for both EIT belts.

Self-triggering superconducting fault current limiter

DOEpatents

Yuan, Xing [Albany, NY; Tekletsadik, Kasegn [Rexford, NY

2008-10-21

A modular and scaleable Matrix Fault Current Limiter (MFCL) that functions as a "variable impedance" device in an electric power network, using components made of superconducting and non-superconducting electrically conductive materials. The matrix fault current limiter comprises a fault current limiter module that includes a superconductor which is electrically coupled in parallel with a trigger coil, wherein the trigger coil is magnetically coupled to the superconductor. The current surge doing a fault within the electrical power network will cause the superconductor to transition to its resistive state and also generate a uniform magnetic field in the trigger coil and simultaneously limit the voltage developed across the superconductor. This results in fast and uniform quenching of the superconductors, significantly reduces the burnout risk associated with non-uniformity often existing within the volume of superconductor materials. The fault current limiter modules may be electrically coupled together to form various "n" (rows).times."m" (columns) matrix configurations.

Fault detection and accommodation testing on an F100 engine in an F-15 airplane

NASA Technical Reports Server (NTRS)

Myers, L. P.; Baer-Riedhart, J. L.; Maxwell, M. D.

1985-01-01

The fault detection and accommodation (FDA) methodology for digital engine-control systems may range from simple comparisons of redundant parameters to the more complex and sophisticated observer models of the entire engine system. Evaluations of the various FDA schemes are done using analytical methods, simulation, and limited-altitude-facility testing. Flight testing of the FDA logic has been minimal because of the difficulty of inducing realistic faults in flight. A flight program was conducted to evaluate the fault detection and accommodation capability of a digital electronic engine control in an F-15 aircraft. The objective of the flight program was to induce selected faults and evaluate the resulting actions of the digital engine controller. Comparisons were made between the flight results and predictions. Several anomalies were found in flight and during the ground test. Simulation results showed that the inducement of dual pressure failures was not feasible since the FDA logic was not designed to accommodate these types of failures.

Train axle bearing fault detection using a feature selection scheme based multi-scale morphological filter

NASA Astrophysics Data System (ADS)

Li, Yifan; Liang, Xihui; Lin, Jianhui; Chen, Yuejian; Liu, Jianxin

2018-02-01

This paper presents a novel signal processing scheme, feature selection based multi-scale morphological filter (MMF), for train axle bearing fault detection. In this scheme, more than 30 feature indicators of vibration signals are calculated for axle bearings with different conditions and the features which can reflect fault characteristics more effectively and representatively are selected using the max-relevance and min-redundancy principle. Then, a filtering scale selection approach for MMF based on feature selection and grey relational analysis is proposed. The feature selection based MMF method is tested on diagnosis of artificially created damages of rolling bearings of railway trains. Experimental results show that the proposed method has a superior performance in extracting fault features of defective train axle bearings. In addition, comparisons are performed with the kurtosis criterion based MMF and the spectral kurtosis criterion based MMF. The proposed feature selection based MMF method outperforms these two methods in detection of train axle bearing faults.

Constraining the Distribution of Vertical Slip on the South Heli Shan Fault (Northeastern Tibet) From High-Resolution Topographic Data

NASA Astrophysics Data System (ADS)

Bi, Haiyun; Zheng, Wenjun; Ge, Weipeng; Zhang, Peizhen; Zeng, Jiangyuan; Yu, Jingxing

2018-03-01

Reconstruction of the along-fault slip distribution provides an insight into the long-term rupture patterns of a fault, thereby enabling more accurate assessment of its future behavior. The increasing wealth of high-resolution topographic data, such as Light Detection and Ranging and photogrammetric digital elevation models, allows us to better constrain the slip distribution, thus greatly improving our understanding of fault behavior. The South Heli Shan Fault is a major active fault on the northeastern margin of the Tibetan Plateau. In this study, we built a 2 m resolution digital elevation model of the South Heli Shan Fault based on high-resolution GeoEye-1 stereo satellite imagery and then measured 302 vertical displacements along the fault, which increased the measurement density of previous field surveys by a factor of nearly 5. The cumulative displacements show an asymmetric distribution along the fault, comprising three major segments. An increasing trend from west to east indicates that the fault has likely propagated westward over its lifetime. The topographic relief of Heli Shan shows an asymmetry similar to the measured cumulative slip distribution, suggesting that the uplift of Heli Shan may result mainly from the long-term activity of the South Heli Shan Fault. Furthermore, the cumulative displacements divide into discrete clusters along the fault, indicating that the fault has ruptured in several large earthquakes. By constraining the slip-length distribution of each rupture, we found that the events do not support a characteristic recurrence model for the fault.

Microstructural characterization of high-manganese austenitic steels with different stacking fault energies

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

Sato, Shigeo, E-mail: s.sato@imr.tohoku.ac.jp; Kwon, Eui-Pyo; Imafuku, Muneyuki

Microstructures of tensile-deformed high-manganese austenitic steels exhibiting twinning-induced plasticity were analyzed by electron backscatter diffraction pattern observation and X-ray diffraction measurement to examine the influence of differences in their stacking fault energies on twinning activity during deformation. The steel specimen with the low stacking fault energy of 15 mJ/m{sup 2} had a microstructure with a high population of mechanical twins than the steel specimen with the high stacking fault energy (25 mJ/m{sup 2}). The <111> and <100> fibers developed along the tensile axis, and mechanical twinning occurred preferentially in the <111> fiber. The Schmid factors for slip and twinning deformationsmore » can explain the origin of higher twinning activity in the <111> fiber. However, the high stacking fault energy suppresses the twinning activity even in the <111> fiber. A line profile analysis based on the X-ray diffraction data revealed the relationship between the characteristics of the deformed microstructures and the stacking fault energies of the steel specimens. Although the variation in dislocation density with the tensile deformation is not affected by the stacking fault energies, the effect of the stacking fault energies on the crystallite size refinement becomes significant with a decrease in the stacking fault energies. Moreover, the stacking fault probability, which was estimated from a peak-shift analysis of the 111 and 200 diffractions, was high for the specimen with low stacking fault energy. Regardless of the difference in the stacking fault energies of the steel specimens, the refined crystallite size has a certain correlation with the stacking fault probability, indicating that whether the deformation-induced crystallite-size refinement occurs depends directly on the stacking fault probability rather than on the stacking fault energies in the present steel specimens. - Highlights: {yields} We studied effects of stacking fault

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.

Magnetometric and gravimetric surveys in fault detection over Acambay System

NASA Astrophysics Data System (ADS)

García-Serrano, A.; Sanchez-Gonzalez, J.; Cifuentes-Nava, G.

2013-05-01

In commemoration of the centennial of the Acambay intraplate earthquake of November 19th 1912, we carry out gravimetric and magnetometric surveys to define the structure of faults caused by this event. The study area is located approximately 11 km south of Acambay, in the Acambay-Tixmadeje fault system, where we performed two magnetometric surveys, the first consisting of 17 lines with a spacing of 35m between lines and 5m between stations, and the second with a total of 12 lines with the same spacing, both NW. In addition to these two lines we performed gravimetric profiles located in the central part of each magnetometric survey, with a spacing of 25m between stations, in order to correlate the results of both techniques, the lengths of such profiles were of 600m and 550m respectively. This work describes the data processing including directional derivatives, analytical signal and inversion, by means of which we obtain results of magnetic variations and anomaly traits highly correlated with those faults. It is of great importance to characterize these faults given the large population growth in the area and settlement houses on them, which involves a high risk in the security of the population, considering that these are active faults and cannot be discard earthquakes associated with them, so it is necessary for the authorities and people have relevant information to these problem.

Transthoracic Electrical Impedance in Cases of High-altitude Hypoxia

PubMed Central

Roy, Sujoy B.; Balasubramanian, V.; Khan, M. R.; Kaushik, V. S.; Manchanda, S. C.; Guha, S. K.

1974-01-01

Changes in transthoracic electrical impedance (T.E.I.) due to high-altitude hypoxia (3,658 m) have been measured in 20 young, healthy Indian soldiers. They were first studied at sea level (198 m) and then rapidly transported by air to 3,658 m, where they were studied daily from day 1 to day 5 and then on days 8 and 10. The mean (±S.D.) T.E.I. at sea level (34·6±0·6Ω) fell sharply to 29·6±0·8Ω, 30·3±0·9Ω, and 30·5±1·1Ω on days 1, 2, and 3 (P <0·001) and levelled off at 31·5±0·7Ω on day 10, which was comparable to the mean value obtained in 13 persons permanently resident at high altitude (32·2±0·7Ω). Five sea-level residents who had acute mountain sickness (A.M.S.) or high-altitude pulmonary oedema (H.A.P.O.) had a still lower mean value (22·5±1·1Ω). One normal healthy subject who at sea level had a T.E.I. of 34·7Ω developed H.A.P.O. when the T.E.I. fell to 21·1Ω. Ninety minutes after the administration of 80 mg of intravenous frusemide the value increased to 35·5Ω. In another subject with A.M.S. who received 40 mg of frusemide intravenously the T.E.I. rose from 21·9 to 33·2Ω. Since the study was non-invasive the changes in impedance could not be correlated objectively with alterations in either pulmonary blood volume or pulmonary extravascular water space. In the subject, however, with x-ray evidence of H.A.P.O. and a low T.E.I. intravenous frusemide produced a marked rise in T.E.I. together with clearing of the chest x-ray picture within 24 hours, indicating an inverse relationship between impedance and thoracic fluid volume. It is suggested that with further objective verification in man the measurement of T.E.I. may be a potentially promising technique for the early detection of increased pulmonary fluid volume. ImagesFIG. 3FIG. 4 PMID:4416705

Acoustic Treatment Design Scaling Methods. Volume 2; Advanced Treatment Impedance Models for High Frequency Ranges

NASA Technical Reports Server (NTRS)

Kraft, R. E.; Yu, J.; Kwan, H. W.

1999-01-01

The primary purpose of this study is to develop improved models for the acoustic impedance of treatment panels at high frequencies, for application to subscale treatment designs. Effects that cause significant deviation of the impedance from simple geometric scaling are examined in detail, an improved high-frequency impedance model is developed, and the improved model is correlated with high-frequency impedance measurements. Only single-degree-of-freedom honeycomb sandwich resonator panels with either perforated sheet or "linear" wiremesh faceplates are considered. The objective is to understand those effects that cause the simple single-degree-of- freedom resonator panels to deviate at the higher-scaled frequency from the impedance that would be obtained at the corresponding full-scale frequency. This will allow the subscale panel to be designed to achieve a specified impedance spectrum over at least a limited range of frequencies. An advanced impedance prediction model has been developed that accounts for some of the known effects at high frequency that have previously been ignored as a small source of error for full-scale frequency ranges.

High-density CMOS Microelectrode Array System for Impedance Spectroscopy and Imaging of Biological Cells.

PubMed

Vijay, Viswam; Raziyeh, Bounik; Amir, Shadmani; Jelena, Dragas; Alicia, Boos Julia; Axel, Birchler; Jan, Müller; Yihui, Chen; Andreas, Hierlemann

2017-01-26

A monolithic measurement platform was implemented to enable label-free in-vitro electrical impedance spectroscopy measurements of cells on multi-functional CMOS microelectrode array. The array includes 59,760 platinum microelectrodes, densely packed within a 4.5 mm × 2.5 mm sensing region at a pitch of 13.5 μm. The 32 on-chip lock-in amplifiers can be used to measure the impedance of any arbitrarily chosen electrodes on the array by applying a sinusoidal voltage, generated by an on-chip waveform generator with a frequency range from 1 Hz to 1 MHz, and measuring the respective current. Proof-of-concept measurements of impedance sensing and imaging are shown in this paper. Correlations between cell detection through optical microscopy and electrochemical impedance scanning were established.

Impedance biosensor based on interdigitated electrode array for detection of E.coli O157:H7 in food products

NASA Astrophysics Data System (ADS)

Ghosh Dastider, Shibajyoti; Barizuddin, Syed; Dweik, Majed; Almasri, Mahmoud F.

2012-05-01

An impedance biosensor was designed, fabricated and tested for detection of viable Escherichia coli O157:H7 in food samples. This device consists of interdigitated microelectrode array (IDEA) fabricated using thin layer of sputtered gold, embedded under a polydimethylsiloxane (PDMS) microchannel. The array of electrodes is designed to detect viable EColi in different food products. The active surface area of the detection array was modified using goat anti-E.coli polyclonal IgG antibody. Contaminated food samples were tested by infusing the supernatant containing bacteria over the IDEA's, through the microchannel. Antibody-antigen binding on the electrodes results in impedance change. Four serial concentrations of E.coli contaminated food samples (3x102 CFUmL-1 to 3x105 CFUmL-1) were tested. The biosensor successfully detected the E.coli samples, with the lower detection limit being 3x103 CFUmL-1 (up to 3cells/μl). Comparing the test results with an IDEA impedance biosensor without microchannel (published elsewhere) indicates that this biosensor have two order of magnitude times higher sensitivity. The proposed biosensor provides qualitative and quantitative detection, and potentially could be used for detection of other type of bacteria by immobilizing the specific type of antibody.

Fault Detection of Aircraft System with Random Forest Algorithm and Similarity Measure

PubMed Central

Park, Wookje; Jung, Sikhang

2014-01-01

Research on fault detection algorithm was developed with the similarity measure and random forest algorithm. The organized algorithm was applied to unmanned aircraft vehicle (UAV) that was readied by us. Similarity measure was designed by the help of distance information, and its usefulness was also verified by proof. Fault decision was carried out by calculation of weighted similarity measure. Twelve available coefficients among healthy and faulty status data group were used to determine the decision. Similarity measure weighting was done and obtained through random forest algorithm (RFA); RF provides data priority. In order to get a fast response of decision, a limited number of coefficients was also considered. Relation of detection rate and amount of feature data were analyzed and illustrated. By repeated trial of similarity calculation, useful data amount was obtained. PMID:25057508

Real-time management of faulty electrodes in electrical impedance tomography.

PubMed

Hartinger, Alzbeta E; Guardo, Robert; Adler, Andy; Gagnon, Hervé

2009-02-01

Completely or partially disconnected electrodes are a fairly common occurrence in many electrical impedance tomography (EIT) clinical applications. Several factors can contribute to electrode disconnection: patient movement, perspiration, manipulations by clinical staff, and defective electrode leads or electronics. By corrupting several measurements, faulty electrodes introduce significant image artifacts. In order to properly manage faulty electrodes, it is necessary to: 1) account for invalid data in image reconstruction algorithms and 2) automatically detect faulty electrodes. This paper presents a two-part approach for real-time management of faulty electrodes based on the principle of voltage-current reciprocity. The first part allows accounting for faulty electrodes in EIT image reconstruction without a priori knowledge of which electrodes are at fault. The method properly weights each measurement according to its compliance with the principle of voltage-current reciprocity. Results show that the algorithm is able to automatically determine the valid portion of the data and use it to calculate high-quality images. The second part of the approach allows automatic real-time detection of at least one faulty electrode with 100% sensitivity and two faulty electrodes with 80% sensitivity enabling the clinical staff to fix the problem as soon as possible to minimize data loss.

Nuclear radiation-warning detector that measures impedance

DOEpatents

Savignac, Noel Felix; Gomez, Leo S; Yelton, William Graham; Robinson, Alex; Limmer, Steven

2013-06-04

This invention is a nuclear radiation-warning detector that measures impedance of silver-silver halide on an interdigitated electrode to detect light or radiation comprised of alpha particles, beta particles, gamma rays, X rays, and/or neutrons. The detector is comprised of an interdigitated electrode covered by a layer of silver halide. After exposure to alpha particles, beta particles, X rays, gamma rays, neutron radiation, or light, the silver halide is reduced to silver in the presence of a reducing solution. The change from the high electrical resistance (impedance) of silver halide to the low resistance of silver provides the radiation warning that detected radiation levels exceed a predetermined radiation dose threshold.

The Novel Immunobiosensors for Detection of Escherichia coli O157:H7 Using Electrochemical Impedance Spectroscopy.

PubMed

Zhang, Deng; Chen, Songyue; Qin, Lifeng; Li, Rong; Wang, Ping; Li, Yanbin

2005-01-01

Immunobiosensors were developed for detection of Escherichia coli O157:H7 based on the surface immobilization of monoclone antibodies onto indium tin oxide (ITO) electrodes. The immobilization of antibodies onto ITO chips was carried out by silanization. The effects of epoxysilane monolayer, the antibody layer on the electrochemical properties of the electrode, and the combined target bacteria were analyzed through cyclic voltammetry and electrochemical impedance spectroscopy. By using Randles model as the equivalent circuit, the concentration of the target bacteria can be quantitatively analyzed in terms of the change of electron transfer resistance. The biosensor could detect the target bacteria with a detection limit of 4×10³CFU/mL. A linear response was found between 4×10³- 4×10⁶CFU/mL. This biosensor was characterized with high sensitivity, excellent selectivity, short detection time and easy operation It has a promising application in clinical laboratory diagnoses, environmental detection and food safety.

Highly efficient all-dielectric optical tensor impedance metasurfaces for chiral polarization control.

PubMed

Kim, Minseok; Eleftheriades, George V

2016-10-15

We propose a highly efficient (nearly lossless and impedance-matched) all-dielectric optical tensor impedance metasurface that mimics chiral effects at optical wavelengths. By cascading an array of rotated crossed silicon nanoblocks, we realize chiral optical tensor impedance metasurfaces that operate as circular polarization selective surfaces. Their efficiencies are maximized through a nonlinear numerical optimization process in which the tensor impedance metasurfaces are modeled via multi-conductor transmission line theory. From rigorous full-wave simulations that include all material losses, we show field transmission efficiencies of 94% for right- and left-handed circular polarization selective surfaces at 800 nm.

Fault detection for discrete-time LPV systems using interval observers

NASA Astrophysics Data System (ADS)

Zhang, Zhi-Hui; Yang, Guang-Hong

2017-10-01

This paper is concerned with the fault detection (FD) problem for discrete-time linear parameter-varying systems subject to bounded disturbances. A parameter-dependent FD interval observer is designed based on parameter-dependent Lyapunov and slack matrices. The design method is presented by translating the parameter-dependent linear matrix inequalities (LMIs) into finite ones. In contrast to the existing results based on parameter-independent and diagonal Lyapunov matrices, the derived disturbance attenuation, fault sensitivity and nonnegative conditions lead to less conservative LMI characterisations. Furthermore, without the need to design the residual evaluation functions and thresholds, the residual intervals generated by the interval observers are used directly for FD decision. Finally, simulation results are presented for showing the effectiveness and superiority of the proposed method.

A novel micro-Raman technique to detect and characterize 4H-SiC stacking faults

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

Piluso, N., E-mail: nicolo.piluso@imm.cnr.it; Camarda, M.; La Via, F.

A novel Micro-Raman technique was designed and used to detect extended defects in 4H-SiC homoepitaxy. The technique uses above band-gap high-power laser densities to induce a local increase of free carriers in undoped epitaxies (n < 10{sup 16} at/cm{sup −3}), creating an electronic plasma that couples with the longitudinal optical (LO) Raman mode. The Raman shift of the LO phonon-plasmon-coupled mode (LOPC) increases as the free carrier density increases. Crystallographic defects lead to scattering or recombination of the free carriers which results in a loss of coupling with the LOPC, and in a reduction of the Raman shift. Given that the LOmore » phonon-plasmon coupling is obtained thanks to the free carriers generated by the high injection level induced by the laser, we named this technique induced-LOPC (i-LOPC). This technique allows the simultaneous determination of both the carrier lifetime and carrier mobility. Taking advantage of the modifications on the carrier lifetime induced by extended defects, we were able to determine the spatial morphology of stacking faults; the obtained morphologies were found to be in excellent agreement with those provided by standard photoluminescence techniques. The results show that the detection of defects via i-LOPC spectroscopy is totally independent from the stacking fault photoluminescence signals that cover a large energy range up to 0.7 eV, thus allowing for a single-scan simultaneous determination of any kind of stacking fault. Combining the i-LOPC method with the analysis of the transverse optical mode, the micro-Raman characterization can determine the most important properties of unintentionally doped film, including the stress status of the wafer, lattice impurities (point defects, polytype inclusions) and a detailed analysis of crystallographic defects, with a high spectral and spatial resolution.« less

Label-Free Aptasensor for Lysozyme Detection Using Electrochemical Impedance Spectroscopy.

PubMed

Ortiz-Aguayo, Dionisia; Del Valle, Manel

2018-01-26

This research develops a label-free aptamer biosensor (aptasensor) based on graphite-epoxy composite electrodes (GECs) for the detection of lysozyme protein using Electrochemical Impedance Spectroscopy (EIS) technique. The chosen immobilization technique was based on covalent bonding using carbodiimide chemistry; for this purpose, carboxylic moieties were first generated on the graphite by electrochemical grafting. The detection was performed using [Fe(CN)₆] 3- /[Fe(CN)₆] 4- as redox probe. After recording the frequency response, values were fitted to its electric model using the principle of equivalent circuits. The aptasensor showed a linear response up to 5 µM for lysozyme and a limit of detection of 1.67 µM. The sensitivity of the established method was 0.090 µM -1 in relative charge transfer resistance values. The interference response by main proteins, such as bovine serum albumin and cytochrome c, has been also characterized. To finally verify the performance of the developed aptasensor, it was applied to wine analysis.

Label-Free Aptasensor for Lysozyme Detection Using Electrochemical Impedance Spectroscopy

PubMed Central

2018-01-01

This research develops a label-free aptamer biosensor (aptasensor) based on graphite-epoxy composite electrodes (GECs) for the detection of lysozyme protein using Electrochemical Impedance Spectroscopy (EIS) technique. The chosen immobilization technique was based on covalent bonding using carbodiimide chemistry; for this purpose, carboxylic moieties were first generated on the graphite by electrochemical grafting. The detection was performed using [Fe(CN)6]3−/[Fe(CN)6]4− as redox probe. After recording the frequency response, values were fitted to its electric model using the principle of equivalent circuits. The aptasensor showed a linear response up to 5 µM for lysozyme and a limit of detection of 1.67 µM. The sensitivity of the established method was 0.090 µM−1 in relative charge transfer resistance values. The interference response by main proteins, such as bovine serum albumin and cytochrome c, has been also characterized. To finally verify the performance of the developed aptasensor, it was applied to wine analysis. PMID:29373502

Detection of faults in rotating machinery using periodic time-frequency sparsity

NASA Astrophysics Data System (ADS)

Ding, Yin; He, Wangpeng; Chen, Binqiang; Zi, Yanyang; Selesnick, Ivan W.

2016-11-01

This paper addresses the problem of extracting periodic oscillatory features in vibration signals for detecting faults in rotating machinery. To extract the feature, we propose an approach in the short-time Fourier transform (STFT) domain where the periodic oscillatory feature manifests itself as a relatively sparse grid. To estimate the sparse grid, we formulate an optimization problem using customized binary weights in the regularizer, where the weights are formulated to promote periodicity. In order to solve the proposed optimization problem, we develop an algorithm called augmented Lagrangian majorization-minimization algorithm, which combines the split augmented Lagrangian shrinkage algorithm (SALSA) with majorization-minimization (MM), and is guaranteed to converge for both convex and non-convex formulation. As examples, the proposed approach is applied to simulated data, and used as a tool for diagnosing faults in bearings and gearboxes for real data, and compared to some state-of-the-art methods. The results show that the proposed approach can effectively detect and extract the periodical oscillatory features.

Electrochemical noise and impedance of Au electrode/electrolyte interfaces enabling extracellular detection of glioma cell populations

NASA Astrophysics Data System (ADS)

Rocha, Paulo R. F.; Schlett, Paul; Kintzel, Ulrike; Mailänder, Volker; Vandamme, Lode K. J.; Zeck, Gunther; Gomes, Henrique L.; Biscarini, Fabio; de Leeuw, Dago M.

2016-10-01

Microelectrode arrays (MEA) record extracellular local field potentials of cells adhered to the electrodes. A disadvantage is the limited signal-to-noise ratio. The state-of-the-art background noise level is about 10 μVpp. Furthermore, in MEAs low frequency events are filtered out. Here, we quantitatively analyze Au electrode/electrolyte interfaces with impedance spectroscopy and noise measurements. The equivalent circuit is the charge transfer resistance in parallel with a constant phase element that describes the double layer capacitance, in series with a spreading resistance. This equivalent circuit leads to a Maxwell-Wagner relaxation frequency, the value of which is determined as a function of electrode area and molarity of an aqueous KCl electrolyte solution. The electrochemical voltage and current noise is measured as a function of electrode area and frequency and follow unambiguously from the measured impedance. By using large area electrodes the noise floor can be as low as 0.3 μVpp. The resulting high sensitivity is demonstrated by the extracellular detection of C6 glioma cell populations. Their minute electrical activity can be clearly detected at a frequency below about 10 Hz, which shows that the methodology can be used to monitor slow cooperative biological signals in cell populations.

Fault detection method for railway wheel flat using an adaptive multiscale morphological filter

NASA Astrophysics Data System (ADS)

Li, Yifan; Zuo, Ming J.; Lin, Jianhui; Liu, Jianxin

2017-02-01

This study explores the capacity of the morphology analysis for railway wheel flat fault detection. A dynamic model of vehicle systems with 56 degrees of freedom was set up along with a wheel flat model to calculate the dynamic responses of axle box. The vehicle axle box vibration signal is complicated because it not only contains the information of wheel defect, but also includes track condition information. Thus, how to extract the influential features of wheels from strong background noise effectively is a typical key issue for railway wheel fault detection. In this paper, an algorithm for adaptive multiscale morphological filtering (AMMF) was proposed, and its effect was evaluated by a simulated signal. And then this algorithm was employed to study the axle box vibration caused by wheel flats, as well as the influence of track irregularity and vehicle running speed on diagnosis results. Finally, the effectiveness of the proposed method was verified by bench testing. Research results demonstrate that the AMMF extracts the influential characteristic of axle box vibration signals effectively and can diagnose wheel flat faults in real time.

Automated vehicle for railway track fault detection

NASA Astrophysics Data System (ADS)

Bhushan, M.; Sujay, S.; Tushar, B.; Chitra, P.

2017-11-01

For the safety reasons, railroad tracks need to be inspected on a regular basis for detecting physical defects or design non compliances. Such track defects and non compliances, if not detected in a certain interval of time, may eventually lead to severe consequences such as train derailments. Inspection must happen twice weekly by a human inspector to maintain safety standards as there are hundreds and thousands of miles of railroad track. But in such type of manual inspection, there are many drawbacks that may result in the poor inspection of the track, due to which accidents may cause in future. So to avoid such errors and severe accidents, this automated system is designed.Such a concept would surely introduce automation in the field of inspection process of railway track and can help to avoid mishaps and severe accidents due to faults in the track.

Discrete Wavelet Transform for Fault Locations in Underground Distribution System

NASA Astrophysics Data System (ADS)

Apisit, C.; Ngaopitakkul, A.

2010-10-01

In this paper, a technique for detecting faults in underground distribution system is presented. Discrete Wavelet Transform (DWT) based on traveling wave is employed in order to detect the high frequency components and to identify fault locations in the underground distribution system. The first peak time obtained from the faulty bus is employed for calculating the distance of fault from sending end. The validity of the proposed technique is tested with various fault inception angles, fault locations and faulty phases. The result is found that the proposed technique provides satisfactory result and will be very useful in the development of power systems protection scheme.

The buried active faults in southeastern China as revealed by the relocated background seismicity and fault plane solutions

NASA Astrophysics Data System (ADS)

Zhu, A.; Wang, P.; Liu, F.

2017-12-01

The southeastern China in the mainland corresponds to the south China block, which is characterized by moderate historical seismicity and low stain rate. Most faults are buried under thick Quaternary deposits, so it is difficult to detect and locate them using the routine geological methods. Only a few have been identified to be active in late Quaternary, which leads to relatively high potentially seismic risk to this region due to the unexpected locations of the earthquakes. We performed both hypoDD and tomoDD for the background seismicity from 2000 to 2016 to investigate the buried faults. Some buried active faults are revealed by the relocated seismicity and the velocity structure, no geologically known faults corresponding to them and no surface active evidence ever observed. The geometries of the faults are obtained by analyzing the hypocentral distribution pattern and focal mechanism. The focal mechanism solutions indicate that all the revealed faults are dominated in strike-slip mechanisms, or with some thrust components. While the previous fault investigation and detection results show that most of the Quaternary faults in southeastern China are dominated by normal movement. It suggests that there may exist two fault systems in deep and shallow tectonic regimes. The revealed faults may construct the deep one that act as the seismogenic faults, and the normal faults at shallow cannot generate the destructive earthquakes. The variation in the Curie-point depths agrees well with the structure plane of the revealed active faults, suggesting that the faults may have changed the deep structure.

Impedance-based detection of corrosion in post-tensioned cables : phase 2 extension of sensor development.

DOT National Transportation Integrated Search

2014-08-01

A proof of concept was established for a sensor capable of using indirect impedance spectroscopy to : detect the existence of corrosion in post-tensioned tendons. This development was supported by a : combination of bench-top experiments performed on...

Weighted low-rank sparse model via nuclear norm minimization for bearing fault detection

NASA Astrophysics Data System (ADS)

Du, Zhaohui; Chen, Xuefeng; Zhang, Han; Yang, Boyuan; Zhai, Zhi; Yan, Ruqiang

2017-07-01

It is a fundamental task in the machine fault diagnosis community to detect impulsive signatures generated by the localized faults of bearings. The main goal of this paper is to exploit the low-rank physical structure of periodic impulsive features and further establish a weighted low-rank sparse model for bearing fault detection. The proposed model mainly consists of three basic components: an adaptive partition window, a nuclear norm regularization and a weighted sequence. Firstly, due to the periodic repetition mechanism of impulsive feature, an adaptive partition window could be designed to transform the impulsive feature into a data matrix. The highlight of partition window is to accumulate all local feature information and align them. Then, all columns of the data matrix share similar waveforms and a core physical phenomenon arises, i.e., these singular values of the data matrix demonstrates a sparse distribution pattern. Therefore, a nuclear norm regularization is enforced to capture that sparse prior. However, the nuclear norm regularization treats all singular values equally and thus ignores one basic fact that larger singular values have more information volume of impulsive features and should be preserved as much as possible. Therefore, a weighted sequence with adaptively tuning weights inversely proportional to singular amplitude is adopted to guarantee the distribution consistence of large singular values. On the other hand, the proposed model is difficult to solve due to its non-convexity and thus a new algorithm is developed to search one satisfying stationary solution through alternatively implementing one proximal operator operation and least-square fitting. Moreover, the sensitivity analysis and selection principles of algorithmic parameters are comprehensively investigated through a set of numerical experiments, which shows that the proposed method is robust and only has a few adjustable parameters. Lastly, the proposed model is applied to the

Contrasting fault fluids along high-angle faults: a case study from Southern Apennines (Italy)

NASA Astrophysics Data System (ADS)

Sinisi, Rosa; Petrullo, Angela Vita; Agosta, Fabrizio; Paternoster, Michele; Belviso, Claudia; Grassa, Fausto

2016-10-01

This work focuses on two fault-controlled deposits, the Atella and Rapolla travertines, which are associated with high-angle extensional faults of the Bradano Trough, southern Apennines (Italy). The Atella travertine is along a NW-SE striking, deep-seated extensional fault, already described in literature, which crosscuts both Apulian carbonates and the overlying foredeep basin infill. The Rapolla travertine is on top of a NE-SW striking, shallow-seated fault, here described for the first time, which is interpreted as a tear fault associated with a shallow thrust displacing only the foredeep basin infill. The results of structural, sedimentological, mineralogical, and C and O isotope analyses are here reported and discussed to assess the provenance of mineralizing fluids, and to evaluate the control exerted by the aforementioned extensional faults on deep, mantle-derived and shallow, meteoric fluids. Sedimentological analysis is consistent with five lithofacies in the studied travertines, which likely formed in a typical lacustrine depositional environment. Mineralogical analysis show that travertines mainly consist of calcite, and minor quartz, feldspar and clay minerals, indicative of a terrigenous supply during travertine precipitation. The isotope signature of the two studied travertines shows different provenance for the mineralizing fluids. At the Atella site, the δ13CPDB values range between + 5.2 and + 5.7‰ and the δ18OPDB values between - 9.0 and - 7.3‰, which are consistent with a mantle-derived CO2 component in the fluid. In contrast, at the Rapolla site the δ13CPDB values vary from - 2.7 to + 1.5‰ and the δ18OPDB values from - 6.8 to - 5.4‰, suggesting a mixed CO2 source with both biogenic-derived and mantle-derived fluids. The results of structural analyses conducted along the footwall damage zone of the fault exposed at the Rapolla site, show that the whole damage zone, in which fractures and joints likely channeled the mixed fluids, acted

A single dynamic observer-based module for design of simultaneous fault detection, isolation and tracking control scheme

NASA Astrophysics Data System (ADS)

Davoodi, M.; Meskin, N.; Khorasani, K.

2018-03-01

The problem of simultaneous fault detection, isolation and tracking (SFDIT) control design for linear systems subject to both bounded energy and bounded peak disturbances is considered in this work. A dynamic observer is proposed and implemented by using the H∞/H-/L1 formulation of the SFDIT problem. A single dynamic observer module is designed that generates the residuals as well as the control signals. The objective of the SFDIT module is to ensure that simultaneously the effects of disturbances and control signals on the residual signals are minimised (in order to accomplish the fault detection goal) subject to the constraint that the transfer matrix from the faults to the residuals is equal to a pre-assigned diagonal transfer matrix (in order to accomplish the fault isolation goal), while the effects of disturbances, reference inputs and faults on the specified control outputs are minimised (in order to accomplish the fault-tolerant and tracking control goals). A set of linear matrix inequality (LMI) feasibility conditions are derived to ensure solvability of the problem. In order to illustrate and demonstrate the effectiveness of our proposed design methodology, the developed and proposed schemes are applied to an autonomous unmanned underwater vehicle (AUV).

Detection of Alzheimer’s disease amyloid-beta plaque deposition by deep brain impedance profiling