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1

RICE UNIVERSITY Fault Detection and Fault Tolerance Methods for  

E-print Network

RICE UNIVERSITY Fault Detection and Fault Tolerance Methods for Robotics by Monica L. Visinsky for their contributions to the dragon. Thanks are also due to Larry, J.D. and Dr. Johnson for their constant help

Cavallaro, Joseph R.

2

Fault Detection and Diagnosis Method for VAV Terminal Units  

E-print Network

This paper proposes two fault detection and diagnosis methods for VAV units without a sensor of supply air volume, and the results of applying these methods to a real building are presented. One method detects faults by applying a statistical method...

Miyata, M.; Yoshida, H.; Asada, M.; Wang, F.; Hashiguchi, S.

2004-01-01

3

Supervision, fault-detection and fault-diagnosis methods — An introduction  

Microsoft Academic Search

The operation of technical processes requires increasingly advanced supervision and fault diagnosis to improve reliability, safety and economy. This paper gives an introduction to the field of fault detection and diagnosis. It begins with a consideration of a knowledge-based procedure that is based on analytical and heuristic information. Then different methods of fault detection are considered, which extract features from

R. Isermann

1997-01-01

4

Incipient mechanical fault detection based on multifractal and MTS methods  

Microsoft Academic Search

An incipient mechanical fault detection method, combining multifractal theory and Mahalanobis-Taguchi system (MTS), which\\u000a is based on statistical technology, is proposed in this paper. Multifractal features of vibration signals obtained from machine\\u000a state monitoring are extracted by multifractal spectrum analysis and generalized fractal dimensions. Considering the situation\\u000a of mass samples of normal mechanical running state and few fault states, the

Jinqiu Hu; Laibin Zhang; Wei Liang; Zhaohui Wang

2009-01-01

5

A Comparison of Fault Detection Methods For a Transcritical Refrigeration System  

E-print Network

useful information. The same tests are performed on a subcritical air-conditioner showing little value in dynamic fault detection. A static component based method of fault detection which has been applied to subcritical systems is also tested for all...

Janecke, Alex Karl

2012-10-19

6

High resolution seismics methods in application to fault zone detection  

NASA Astrophysics Data System (ADS)

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 about geological structure of mentioned zone. Correlation between geophysical and geological results seems to be very effective in reconstruction the forming processes of fault zones. Better understanding phenomena, which rules of young fault activities, reduce incorporated hazards and simultaneously bring information about presence geodynamics processes.

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

2014-05-01

7

A lightweight fault detection method for sensor networks based on anomaly execution statistics  

NASA Astrophysics Data System (ADS)

Fault detection of deployed senor networks is difficult due to server constrained resources and limited access to the networks. A lightweight fault detection method is proposed to address the problem of unknown software fault detection in post-deployment phase. By analyzing characteristics of node programs, a statistical model and corresponding test statistic are devised to detect unknown fault at runtime. Evaluation on typical sensor network applications shows that the storage and runtime overhead are acceptable. A case study further demonstrates the effectiveness of the proposed method.

Ma, Junyan; Zhao, Xiangmo; Hui, Fei; Shi, Xin; Yang, Lan

2014-10-01

8

Solar system fault detection  

DOEpatents

A fault detecting apparatus and method are provided for use with an active solar system. The apparatus provides an indication as to whether one or more predetermined faults have occurred in the solar system. The apparatus includes a plurality of sensors, each sensor being used in determining whether a predetermined condition is present. The outputs of the sensors are combined in a pre-established manner in accordance with the kind of predetermined faults to be detected. Indicators communicate with the outputs generated by combining the sensor outputs to give the user of the solar system and the apparatus an indication as to whether a predetermined fault has occurred. Upon detection and indication of any predetermined fault, the user can take appropriate corrective action so that the overall reliability and efficiency of the active solar system are increased.

Farrington, R.B.; Pruett, J.C. Jr.

1984-05-14

9

Time-series methods for fault detection and identification in vibrating structures.  

PubMed

An overview of the principles and techniques of time-series methods for fault detection, identification and estimation in vibrating structures is presented, and certain new methods are introduced. The methods are classified, and their features and operation are discussed. Their practicality and effectiveness are demonstrated through brief presentations of three case studies pertaining to fault detection, identification and estimation in an aircraft panel, a scale aircraft skeleton structure and a simple nonlinear simulated structure. PMID:17255046

Fassois, Spilios D; Sakellariou, John S

2007-02-15

10

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

DOEpatents

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.

Zhou, Wei (Los Angeles, CA); Lu, Bin (Kenosha, WI); Habetler, Thomas G. (Snellville, GA); Harley, Ronald G. (Lawrenceville, GA); Theisen, Peter J. (West Bend, WI)

2010-08-17

11

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

DOEpatents

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.

Zhou, Wei (Los Angeles, CA); Lu, Bin (Kenosha, WI); Nowak, Michael P. (Menomonee Falls, WI); Dimino, Steven A. (Wauwatosa, WI)

2010-12-07

12

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

DOEpatents

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 in 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.

Almasi, Gheorghe (Ardsley, NY) [Ardsley, NY; Blumrich, Matthias Augustin (Ridgefield, CT) [Ridgefield, CT; Chen, Dong (Croton-On-Hudson, NY) [Croton-On-Hudson, NY; Coteus, Paul (Yorktown, NY) [Yorktown, NY; Gara, Alan (Mount Kisco, NY) [Mount Kisco, NY; Giampapa, Mark E. (Irvington, NY) [Irvington, NY; Heidelberger, Philip (Cortlandt Manor, NY) [Cortlandt Manor, NY; Hoenicke, Dirk I. (Ossining, NY) [Ossining, NY; Singh, Sarabjeet (Mississauga, CA) [Mississauga, CA; Steinmacher-Burow, Burkhard D. (Wernau, DE) [Wernau, DE; Takken, Todd (Brewster, NY) [Brewster, NY; Vranas, Pavlos (Bedford Hills, NY) [Bedford Hills, NY

2008-06-03

13

Method of detecting a fault of an exhaust gas recirculation system  

Microsoft Academic Search

This patent describes a method of detecting a fault of an exhaust gas recirculation system of an internal combustion engine, wherein a temperature relating to a temperature of the exhaust gas recirculating through the exhaust gas recirculation system is detected when the exhaust gas recirculation system is in a condition in which the system should be operated to return part

T. Hashimoto; A. Takahashi; T. Imaizuma; S. Saito; H. Tanaka; T Jimbo

1989-01-01

14

Sensor noise fault detection  

Microsoft Academic Search

Current sensor FDIR (fault detection, isolation, & recovery) generally focuses on sensor bias and drift anomalies, which require models. However, dead sensors and excessive noise faults are more common in practice. The latter two faults are interesting in that they can be detected using only the measurements from each sensor. The objective of this paper is to show a few

Steve Rogers

2003-01-01

15

ACTUATOR FAULT DETECTION, ISOLATION METHOD AND STATE ESTIMATOR DESIGN FOR HOT ROLLING MILL MONITORING  

E-print Network

. The plate thickness is reduced by pulling the plate between two parallel rolls at a specific rolling speedACTUATOR FAULT DETECTION, ISOLATION METHOD AND STATE ESTIMATOR DESIGN FOR HOT ROLLING MILL and a profitable plant operation. Sensor or actuator failure, equipment fouling, feedstock variations, product

Paris-Sud XI, Université de

16

Demonstration of Fault Detection and Diagnosis Methods for Air-Handling Units  

Microsoft Academic Search

Results are presented from controlled field tests of two methods for detecting and diagnosing faults in HVAC equipment. The tests were conducted in a unique research building that featured two air-handling units serving matched sets of unoccupied rooms with adjustable internal loads. Tests were also conducted in the same building on a third air handler serving areas used for instruction

L. K. Norford; J. A. Wright; R. A. Buswell; D. Luo; C. J. Klaassen; A. Suby

2002-01-01

17

Randomness fault detection system  

NASA Technical Reports Server (NTRS)

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.

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

1996-01-01

18

Fault detection and fault tolerance in robotics  

NASA Technical Reports Server (NTRS)

Robots are used in inaccessible or hazardous environments in order to alleviate some of the time, cost and risk involved in preparing men to endure these conditions. In order to perform their expected tasks, the robots are often quite complex, thus increasing their potential for failures. If men must be sent into these environments to repair each component failure in the robot, the advantages of using the robot are quickly lost. Fault tolerant robots are needed which can effectively cope with failures and continue their tasks until repairs can be realistically scheduled. Before fault tolerant capabilities can be created, methods of detecting and pinpointing failures must be perfected. This paper develops a basic fault tree analysis of a robot in order to obtain a better understanding of where failures can occur and how they contribute to other failures in the robot. The resulting failure flow chart can also be used to analyze the resiliency of the robot in the presence of specific faults. By simulating robot failures and fault detection schemes, the problems involved in detecting failures for robots are explored in more depth.

Visinsky, Monica; Walker, Ian D.; Cavallaro, Joseph R.

1992-01-01

19

Survey of artificial intelligence methods for detection and identification of component faults in nuclear power plants  

Microsoft Academic Search

A comprehensive survey of computer-based systems that apply artificial intelligence methods to detect and identify component faults in nuclear power plants is presented. Classification criteria are established that categorize artificial intelligence diagnostic systems according to the types of computing approaches used (e.g., computing tools, computer languages, and shell and simulation programs), the types of methodologies employed (e.g., types of knowledge,

Reifman

1997-01-01

20

Fault detection for modern Diesel engines using signal- and process model-based methods  

Microsoft Academic Search

Modern Diesel engines with direct fuel injection and turbo charging have shown a significant progress in fuel consumption, emissions and driveability. Together with exhaust gas recirculation and variable geometry turbochargers they became complicated and complex processes. Therefore, fault detection and diagnosis is not easily done and need to be improved. This contribution shows a systematic development of fault detection and

Frank Kimmich; Anselm Schwarte; Rolf Isermann

2005-01-01

21

Flight elements: Fault detection and fault management  

NASA Technical Reports Server (NTRS)

Fault management for an intelligent computational system must be developed using a top down integrated engineering approach. An approach proposed includes integrating the overall environment involving sensors and their associated data; design knowledge capture; operations; fault detection, identification, and reconfiguration; testability; causal models including digraph matrix analysis; and overall performance impacts on the hardware and software architecture. Implementation of the concept to achieve a real time intelligent fault detection and management system will be accomplished via the implementation of several objectives, which are: Development of fault tolerant/FDIR requirement and specification from a systems level which will carry through from conceptual design through implementation and mission operations; Implementation of monitoring, diagnosis, and reconfiguration at all system levels providing fault isolation and system integration; Optimize system operations to manage degraded system performance through system integration; and Lower development and operations costs through the implementation of an intelligent real time fault detection and fault management system and an information management system.

Lum, H.; Patterson-Hine, A.; Edge, J. T.; Lawler, D.

1990-01-01

22

Survey of artificial intelligence methods for detection and identification of component faults in nuclear power plants  

SciTech Connect

A comprehensive survey of computer-based systems that apply artificial intelligence methods to detect and identify component faults in nuclear power plants is presented. Classification criteria are established that categorize artificial intelligence diagnostic systems according to the types of computing approaches used (e.g., computing tools, computer languages, and shell and simulation programs), the types of methodologies employed (e.g., types of knowledge, reasoning and inference mechanisms, and diagnostic approach), and the scope of the system. The major issues of process diagnostics and computer-based diagnostic systems are identified and cross-correlated with the various categories used for classification. Ninety-five publications are reviewed.

Reifman, J. [Argonne National Lab., IL (United States). Reactor Analysis Div.

1997-07-01

23

Discrete Data Qualification System and Method Comprising Noise Series Fault Detection  

NASA Technical Reports Server (NTRS)

A Sensor Data Qualification (SDQ) function has been developed that allows the onboard flight computers on NASA s launch vehicles to determine the validity of sensor data to ensure that critical safety and operational decisions are not based on faulty sensor data. This SDQ function includes a novel noise series fault detection algorithm for qualification of the output data from LO2 and LH2 low-level liquid sensors. These sensors are positioned in a launch vehicle s propellant tanks in order to detect propellant depletion during a rocket engine s boost operating phase. This detection capability can prevent the catastrophic situation where the engine operates without propellant. The output from each LO2 and LH2 low-level liquid sensor is a discrete valued signal that is expected to be in either of two states, depending on whether the sensor is immersed (wet) or exposed (dry). Conventional methods for sensor data qualification, such as threshold limit checking, are not effective for this type of signal due to its discrete binary-state nature. To address this data qualification challenge, a noise computation and evaluation method, also known as a noise fault detector, was developed to detect unreasonable statistical characteristics in the discrete data stream. The method operates on a time series of discrete data observations over a moving window of data points and performs a continuous examination of the resulting observation stream to identify the presence of anomalous characteristics. If the method determines the existence of anomalous results, the data from the sensor is disqualified for use by other monitoring or control functions.

Fulton, Christopher; Wong, Edmond; Melcher, Kevin; Bickford, Randall

2013-01-01

24

Vibration Fault Detection and Diagnosis Method of Power System Generator Based on Wavelet Fractal Network  

Microsoft Academic Search

A novel fault diagnosis method for turbo-generator set based on fractal exponent theory and wavelet network is presented. When faults occur, they usually produce nonstationary vibration signals. The wavelet transform is used to localizes the characteristics of vibration signal in the time frequency domains and in a view of the inter relationship of wavelet transform between fractal theory, the whole

Kang Shanlin; Liang Baoshe; Fan Feng; Shen Songhua

2007-01-01

25

Applications of Fault Detection in Vibrating Structures  

NASA Technical Reports Server (NTRS)

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.

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

2012-01-01

26

Fault detection methods for vapor-compression air conditioners using electrical measurements  

E-print Network

(cont.) This method was experimentally tested and validated on a commercially available air handler and duct system. In the second class of faults studied, liquid refrigerant, rather than vapor, enters the cylinder of a ...

Laughman, Christopher Reed.

2008-01-01

27

CMOS Bridging Fault Detection  

Microsoft Academic Search

The authors compare the performance of two test generation techniques, stuck fault testing and current testing, when applied to CMOS bridging faults. Accurate simulation of such faults mandated the development of several new design automation tools, including an analog-digital fault simulator. The results of this simulation are analyzed. It is shown that stuck fault test generation, while inherently incapable of

Thomas M. Storey; Wojciech Maly

1990-01-01

28

Multiple Sensor Faults detection of steam condensers  

Microsoft Academic Search

This paper deals with the Fault Detection and Isolation (FDI) on industrial systems such as steam generator process whose model is non linear. The method is based on Analytical Redundancy Relations which are generated from a bipartite graph These relations are used to detect and isolate Sensor Fault using structural analysis, based on the elimination of the unmeasured variables of

A. Aïtouche; F. Busson; B. Ould Bouamama; M. Staroswiecki

1999-01-01

29

A comparison of bridging fault simulation methods  

Microsoft Academic Search

This study provides bridging fault simulation data obtained from the AMD-K6 microprocessor. It shows that: (1) high stuck-at fault coverage (99.5%) implies high bridging fault coverage; (2) coverage of a bridging fault by both wired-AND and wired-OR behavior does not guarantee detection of that fault when compared against a more accurate (transistor-level simulation) modeling method. A set of netname pairs

R. Scott Fetherston; Imtiaz P. Shaik; Siyad C. Ma

1999-01-01

30

Polynomially Complete Fault Detection Problems  

Microsoft Academic Search

We look at several variations of the single fault detection problem for combinational logic circuits and show that deciding whether single faults are detectable by input-output (I\\/O) experiments is polynomially complete, i.e., there is a polynomial time algorithm to decide if these single faults are detectable if and only if there is a polynomial time algorithm for problems such as

Oscar H. Ibarra; Sartaj Sahni

1975-01-01

31

Simultaneous Fault Detection and Classification for Semiconductor Manufacturing Tools  

E-print Network

Simultaneous Fault Detection and Classification for Semiconductor Manufacturing Tools Brian E detection of equipment and process faults to maintain high process yields and rapid fault classification treat fault detection and classification as a two-step process. We present a novel method

Boning, Duane S.

32

Combination of geophysical methods for fault detection: a case study from the Møre-Trøndelag Fault Complex, Mid-Norway  

Microsoft Academic Search

The Møre-Trøndelag Fault Complex (MTFC) is one of the most prominent fault complexes in Scandinavia and perhaps on Earth. The MTFC appears to have controlled the tectonic evolution of central Norway and its shelf for the past 400 Myr, at least, and has experienced repeated reactivation during Paleozoic (Devonian to Permian), Mesozoic (Jurassic) and Cenozoic times. Despite its pronounced signature

A. Nasuti; E. Dalsegg; J. Ebbing; E. Lundberg; J. Tonnesen; C. Pascal

2009-01-01

33

Arc fault detection system  

DOEpatents

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.

Jha, K.N.

1999-05-18

34

Classification of Aircraft Maneuvers for Fault Detection  

NASA Technical Reports Server (NTRS)

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.

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

2002-01-01

35

Classification of Aircraft Maneuvers for Fault Detection  

NASA Technical Reports Server (NTRS)

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.

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

2002-01-01

36

EMA fault detection using fuzzy inference tools  

Microsoft Academic Search

The present work shows a condition monitoring system applied to detect Fault Condition in EMA Systems. Removal of the engine hydraulic pumps requires fully-operative electrical power actuators and mastery of the flight control architecture. However, unexpected faults and lack of safety hinder the massive use of EMAs in flight control actuators and force to develop new systems and methods for

J. Cusido; M. Delgado; L. Navarro; V. M. Sala; L. Romeral

2010-01-01

37

Scalable robot fault detection and identification  

Microsoft Academic Search

Experience has shown that even carefully designed and tested robots may encounter anomalous situations. It is therefore important for robots to monitor their state so that anomalous situations may be detected in a timely manner. Robot fault diagnosis typically requires tracking a very large number of possible faults in complex non-linear dynamic systems with noisy sensors. Traditional methods either ignore

Vandi Verma; Reid G. Simmons

2006-01-01

38

Fault detection using genetic programming  

NASA Astrophysics Data System (ADS)

Genetic programming (GP) is a stochastic process for automatically generating computer programs. GP has been applied to a variety of problems which are too wide to reasonably enumerate. As far as the authors are aware, it has rarely been used in condition monitoring (CM). In this paper, GP is used to detect faults in rotating machinery. Featuresets from two different machines are used to examine the performance of two-class normal/fault recognition. The results are compared with a few other methods for fault detection: Artificial neural networks (ANNs) have been used in this field for many years, while support vector machines (SVMs) also offer successful solutions. For ANNs and SVMs, genetic algorithms have been used to do feature selection, which is an inherent function of GP. In all cases, the GP demonstrates performance which equals or betters that of the previous best performing approaches on these data sets. The training times are also found to be considerably shorter than the other approaches, whilst the generated classification rules are easy to understand and independently validate.

Zhang, Liang; Jack, Lindsay B.; Nandi, Asoke K.

2005-03-01

39

Detecting Faults in Computational Grids  

Microsoft Academic Search

In this paper we will first present a basic definition and a brief history of grid computing since its inception during the last decade. We will then look at a review of the most common faults occurring within the grid environment as identified by a survey of grid computing users. Two papers addressing fault detection are then reviewed for comparison.

Russ Wakefield

40

Method of detecting the direction of arcing faults on power distribution feeders  

E-print Network

to the difference in load current, has been proposed by Benner [7]. This algorithm requires increase of 60 Hz fault current, which is not the case always associated with high impedance arcing faults. Another directionality algorithm using the "in... and the second based on the "in-between" harmonic frequency current correlation to the voltage of the faulted feeder [8]. Benner has proposed the correlation of voltage to the difference in line current, caused due to an arcing high impedance fault...

Fernando, W. Anand Krisantha

2012-06-07

41

Discriminative Pattern Mining in Software Fault Detection Giuseppe Di Fatta  

E-print Network

of containing a fault. The ranking sug- gests an order in which to examine the functions during fault analysis to the goal of locating software faults by proposing an automated data analysis method working on large setsDiscriminative Pattern Mining in Software Fault Detection Giuseppe Di Fatta Department of Computer

Reiterer, Harald

42

Application of a Subspace-Based Fault Detection Method to Industrial Structures  

NASA Astrophysics Data System (ADS)

Early detection and localization of damage allow increased expectations of reliability, safety and reduction of the maintenance cost. This paper deals with the industrial validation of a technique to monitor the health of a structure in operating conditions (e.g. rotating machinery, civil constructions subject to ambient excitations, etc.) and to detect slight deviations in a modal model derived from in-operation measured data. In this paper, a statistical local approach based on covariance-driven stochastic subspace identification is proposed. The capabilities and limitations of the method with respect to health monitoring and damage detection are discussed and it is explained how the method can be practically used in industrial environments. After the successful validation of the proposed method on a few laboratory structures, its application to a sports car is discussed. The example illustrates that the method allows the early detection of a vibration-induced fatigue problem of a sports car.

Mevel, L.; Hermans, L.; van der Auweraer, H.

1999-11-01

43

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

NASA Technical Reports Server (NTRS)

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.

Joshi, Suresh M.

2012-01-01

44

INDUCTION MOTOR FAULT DIAGNOSTIC AND MONITORING METHODS  

E-print Network

INDUCTION MOTOR FAULT DIAGNOSTIC AND MONITORING METHODS by Aderiano M. da Silva, B.S. A Thesis;i Abstract Induction motors are used worldwide as the "workhorse" in industrial applications material. However, induction motor faults can be detected in an initial stage in order to prevent

Povinelli, Richard J.

45

Exogenous Fault Detection in a Collective Robotic Task  

E-print Network

- nous fault detection in autonomous robots. We present a concrete method for obtaining components function which ham- pers or disturbs normal operation, causing unacceptable deterioration in perfor- mance

Birattari, Mauro

46

All row, planar fault detection system  

DOEpatents

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.

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

2013-07-23

47

Bisectional fault detection system  

DOEpatents

An apparatus, program product and method logically divides a group of nodes and causes node pairs comprising a node from each section to communicate. Results from the communications may be analyzed to determine performance characteristics, such as bandwidth and proper connectivity.

Archer, Charles Jens (Rochester, MN); Pinnow, Kurt Walter (Rochester, MN); Ratterman, Joseph D. (Rochester, MN); Smith, Brian Edward (Rochester, MN)

2008-11-11

48

The Fault Detection Problem Andreas Haeberlen1  

E-print Network

The Fault Detection Problem Andreas Haeberlen1 and Petr Kuznetsov2 1 Max Planck Institute challenges in distributed com- puting is ensuring that services are correct and available despite faults. Recently it has been argued that fault detection can be factored out from computation, and that a generic

Pennsylvania, University of

49

The Fault Detection Problem Andreas Haeberlen  

E-print Network

The Fault Detection Problem Andreas Haeberlen Petr Kuznetsov Abstract One of the most important challenges in distributed computing is ensuring that services are correct and available despite faults. Recently it has been argued that fault detection can be factored out from computation, and that a generic

Pennsylvania, University of

50

COMPARATIVE ANALYSIS OF DATA-DRIVEN ANOMALY DETECTION METHODS ON SOLID ROCKET MOTOR FAULTS  

Microsoft Academic Search

This paper provides a review of three different advanced machine learning algorithms for anom- aly detection in continuous data streams from a ground-test firing of a subscale Solid Rocket Motor (SRM). This study compares Orca, one-class support vector machines, and the Inductive Monitoring System (IMS) for anomaly detection on the data streams. We measure the performance of the algorithm with

BRYAN MATTHEWS; ASHOK N. SRIVASTAVA

51

Planetary Gearbox Fault Detection Using Vibration Separation Techniques  

NASA Technical Reports Server (NTRS)

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.

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

2011-01-01

52

Detection of a static eccentricity fault in a closed loop driven induction motor by using the angular domain order tracking analysis method  

NASA Astrophysics Data System (ADS)

In this study, a new method was presented for the detection of a static eccentricity fault in a closed loop operating induction motor driven by inverter. Contrary to the motors supplied by the line, if the speed and load, and therefore the amplitude and frequency, of the current constantly change then this also causes a continuous change in the location of fault harmonics in the frequency spectrum. Angular Domain Order Tracking analysis (AD-OT) is one of the most frequently used fault diagnosis methods in the monitoring of rotating machines and the analysis of dynamic vibration signals. In the presented experimental study, motor phase current and rotor speed were monitored at various speeds and load levels with a healthy and static eccentricity fault in the closed loop driven induction motor with vector control. The AD-OT method was applied to the motor current and the results were compared with the traditional FFT and Fourier Transform based Order Tracking (FT-OT) methods. The experimental results demonstrate that AD-OT method is more efficient than the FFT and FT-OT methods for fault diagnosis, especially while the motor is operating run-up and run-down. Also the AD-OT does not incur any additional cost for the user because in inverter driven systems, current and speed sensor coexist in the system. The main innovative parts of this study are that AD-OT method was implemented on the motor current signal for the first time.

Akar, Mehmet

2013-01-01

53

Fault detection and diagnosis capabilities of test sequence selection  

E-print Network

Review Fault detection and diagnosis capabilities of test sequence selection methods based on the FSM model T Ramalingam*, Anindya Dast and K ThuIasiraman* Different test sequence selection methods resolution in diagnosing the fault. The test sequence selection methods are then compared based on the length

Thulsiraman, Krishnaiyan

54

Model-Based Methods for Textile Fault Detection J. G. Campbell,1  

E-print Network

. Int J Imaging Syst Technol, 10, 339­346, 1999 I. FLAW DETECTION IN TEXTILE FABRIC Obstacles to machine cutting and excising. In the context of automated manufacturing, there is clearly significant scope for in then defined as significant deviation from "normal." In addition, consid- ering extended patterns (clusters

Raftery, Adrian

55

Signal Injection as a Fault Detection Technique  

PubMed Central

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

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

2011-01-01

56

Fault detection and diagnosis in rotating machinery  

Microsoft Academic Search

The detection and diagnosis of mechanical faults in rotating machinery using a model-based approach is studied. For certain types of faults, for example raceway faults in rolling element bearings, increase in mass unbalance and changes in stiffness and damping, algorithms suitable for real-time implementation are developed and tested

Kenneth A. Loparo; Nader Afshari; Mohammed Abdel-Magied

1998-01-01

57

Fault detection and diagnosis of rotating machinery  

Microsoft Academic Search

A model-based approach to the detection and diagnosis of mechanical faults in rotating machinery is studied in this paper. For certain types of faults, for example, raceway faults in rolling element bearings, an increase in mass unbalance, and changes in stiffness and damping, algorithms suitable for real-time implementation are developed and evaluated using computer simulation

Kenneth A. Loparo; M. L. Adams; Wei Lin; M. Farouk Abdel-Magied; Nadar Afshari

2000-01-01

58

A novel extension method for transformer fault diagnosis  

Microsoft Academic Search

Dissolved gas analysis (DGA) is one of the most useful techniques to detect incipient faults in power transformers. However, the identification of the faulted location by the traditional method is not always an easy task due to the variability of gas data and operational variables. In this paper, a novel extension method is presented for fault diagnosis of power transformers,

Mang-Hui Wang

2003-01-01

59

Faults Detection on the LHC Beam Dump Kicker System  

E-print Network

This report describes a proposal for fault detection on the LHC beam dump kicker system. As a result of a fault analysis two fault detection modules are proposed; A off-line test and a continuous surveillance. The fault detection, needing continues data, and the requirements to the data acquisition is given special attention. The off-line test declares the system, including stand-by components, fault tree prior to beam injection. the test comprises parameter estimation using the sensitivity approach requiring an ADC with better than 7 bit precision and a sampling frequency above 133kHz. The continuous surveillance comprises a model based fault detection method, based on analytical redundancy. The system requirements are a 14 bit DAC and an 16 bit ADC with a sample frequency above 1.54Hz.

Dissing, T; Dieperink, J H

1999-01-01

60

Low cost fault detection system for railcars and tracks  

E-print Network

to identifying a wheel flat by similar fault detection techniques is by using the bearing fault detection method of Dr. A. K. Chan [4], at Texas A&M University, where the signals meant to analyze the bearing fault are used to identify wheel flats. This method.... Kaul [5], for a train protection warning system does use the concept of sending certain frequency signals to a box (with receivers to analyze signals) placed in each of the cars. This system aims at stopping a train for certain faults and does...

Vengalathur, Sriram T.

2004-09-30

61

Method and apparatus for generating motor current spectra to enhance motor system fault detection  

DOEpatents

A method and circuitry are disclosed for sampling periodic amplitude modulations in a nonstationary periodic carrier wave to determine frequencies in the amplitude modulations. The method and circuit are described in terms of an improved motor current signature analysis. The method insures that the sampled data set contains an exact whole number of carrier wave cycles by defining the rate at which samples of motor current data are collected. The circuitry insures that a sampled data set containing stationary carrier waves is recreated from the analog motor current signal containing nonstationary carrier waves by conditioning the actual sampling rate to adjust with the frequency variations in the carrier wave. After the sampled data is transformed to the frequency domain via the Discrete Fourier Transform, the frequency distribution in the discrete spectra of those components due to the carrier wave and its harmonics will be minimized so that signals of interest are more easily analyzed. 29 figs.

Linehan, D.J.; Bunch, S.L.; Lyster, C.T.

1995-10-24

62

Method and apparatus for generating motor current spectra to enhance motor system fault detection  

DOEpatents

A method and circuitry for sampling periodic amplitude modulations in a nonstationary periodic carrier wave to determine frequencies in the amplitude modulations. The method and circuit are described in terms of an improved motor current signature analysis. The method insures that the sampled data set contains an exact whole number of carrier wave cycles by defining the rate at which samples of motor current data are collected. The circuitry insures that a sampled data set containing stationary carrier waves is recreated from the analog motor current signal containing nonstationary carrier waves by conditioning the actual sampling rate to adjust with the frequency variations in the carrier wave. After the sampled data is transformed to the frequency domain via the Discrete Fourier Transform, the frequency distribution in the discrete spectra of those components due to the carrier wave and its harmonics will be minimized so that signals of interest are more easily analyzed.

Linehan, Daniel J. (Knoxville, TN); Bunch, Stanley L. (Oak Ridge, TN); Lyster, Carl T. (Knoxville, TN)

1995-01-01

63

A Game Theoretic Fault Detection Filter  

NASA Technical Reports Server (NTRS)

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.

Chung, Walter H.; Speyer, Jason L.

1995-01-01

64

NEURAL NETWORKS FOR PNEUMATIC ACTUATOR FAULT DETECTION  

E-print Network

NEURAL NETWORKS FOR PNEUMATIC ACTUATOR FAULT DETECTION J.F. Gomes de Freitas \\Lambda , I.M. Mac in pneumatic control valve actuators is investigated. Specifically, the ability of a neural network to act offsets. Key Words. Fault detection; neural networks; system identification; control valves; pneumatic 1

Drummond, Tom

65

Fault detection in finite frequency domain for Takagi-Sugeno fuzzy systems with sensor faults.  

PubMed

This paper is concerned with the fault detection (FD) problem in finite frequency domain for continuous-time Takagi-Sugeno fuzzy systems with sensor faults. Some finite-frequency performance indices are initially introduced to measure the fault/reference input sensitivity and disturbance robustness. Based on these performance indices, an effective FD scheme is then presented such that the generated residual is designed to be sensitive to both fault and reference input for faulty cases, while robust against the reference input for fault-free case. As the additional reference input sensitivity for faulty cases is considered, it is shown that the proposed method improves the existing FD techniques and achieves a better FD performance. The theory is supported by simulation results related to the detection of sensor faults in a tunnel-diode circuit. PMID:24184791

Li, Xiao-Jian; Yang, Guang-Hong

2014-08-01

66

Lithography light source fault detection  

NASA Astrophysics Data System (ADS)

High productivity is a key requirement for today's advanced lithography exposure tools. Achieving targets for wafers per day output requires consistently high throughput and availability. One of the keys to high availability is minimizing unscheduled downtime of the litho cell, including the scanner, track and light source. From the earliest eximer laser light sources, Cymer has collected extensive performance data during operation of the source, and this data has been used to identify the root causes of downtime and failures on the system. Recently, new techniques have been developed for more extensive analysis of this data to characterize the onset of typical end-of-life behavior of components within the light source and allow greater predictive capability for identifying both the type of upcoming service that will be required and when it will be required. The new techniques described in this paper are based on two core elements of Cymer's light source data management architecture. The first is enhanced performance logging features added to newer-generation light source software that captures detailed performance data; and the second is Cymer OnLine (COL) which facilitates collection and transmission of light source data. Extensive analysis of the performance data collected using this architecture has demonstrated that many light source issues exhibit recognizable patterns in their symptoms. These patterns are amenable to automated identification using a Cymer-developed model-based fault detection system, thereby alleviating the need for detailed manual review of all light source performance information. Automated recognition of these patterns also augments our ability to predict the performance trending of light sources. Such automated analysis provides several efficiency improvements for light source troubleshooting by providing more content-rich standardized summaries of light source performance, along with reduced time-to-identification for previously classified faults. Automation provides the ability to generate metrics based on a single light source, or multiple light sources. However, perhaps the most significant advantage is that these recognized patterns are often correlated to known root cause, where known corrective actions can be implemented, and this can therefore minimize the time that the light source needs to be offline for maintenance. In this paper, we will show examples of how this new tool and methodology, through an increased level of automation in analysis, is able to reduce fault identification time, reduce time for root cause determination for previously experienced issues, and enhance our light source performance predictability.

Graham, Matthew; Pantel, Erica; Nelissen, Patrick; Moen, Jeffrey; Tincu, Eduard; Dunstan, Wayne; Brown, Daniel

2010-04-01

67

Transient fault detection via simultaneous multithreading  

Microsoft Academic Search

Smaller feature sizes, reduced voltage levels, higher transistor counts, and reduced noise margins make future generations of microprocessors increasingly prone to transient hardware faults. Most commercial fault-tolerant computers use fully replicated hardware components to detect microprocessor faults. The components are lockstepped (cycle-by-cycle synchronized) to ensure that, in each cycle, they perform the same operation on the same inputs, producing the

Steven K. Reinhardt; Shubhendu S. Mukherjee

2000-01-01

68

Fault detection of univariate non-Gaussian data with Bayesian network  

E-print Network

Fault detection of univariate non-Gaussian data with Bayesian network Sylvain Verron, Teodor.verron@univ-angers.fr Abstract--The purpose of this article is to present a new method for fault detection with Bayesian network. The interest of this method is to propose a new structure of Bayesian network allowing to detect a fault

Paris-Sud XI, Université de

69

Negative Selection Algorithm for Aircraft Fault Detection  

NASA Technical Reports Server (NTRS)

We investigated a real-valued Negative Selection Algorithm (NSA) for fault detection in man-in-the-loop aircraft operation. The detection algorithm uses body-axes angular rate sensory data exhibiting the normal flight behavior patterns, to generate probabilistically a set of fault detectors that can detect any abnormalities (including faults and damages) in the behavior pattern of the aircraft flight. We performed experiments with datasets (collected under normal and various simulated failure conditions) using the NASA Ames man-in-the-loop high-fidelity C-17 flight simulator. The paper provides results of experiments with different datasets representing various failure conditions.

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

2004-01-01

70

SIMULTANEOUS FAULT DETECTION AND CLASSIFICATION FOR SEMICONDUCTOR MANUFACTURING TOOLS  

E-print Network

SIMULTANEOUS FAULT DETECTION AND CLASSIFICATION FOR SEMICONDUCTOR MANUFACTURING TOOLS Brian E, accurate, and sensitive detection of equipment and process faults to maintain high process yields and rapid fault classification (diagnosis) of the cause to minimize tool downtime in semiconductor manufacturing

Boning, Duane S.

71

Trends in the application of model-based fault detection and diagnosis of technical processes  

Microsoft Academic Search

After a short overview of the historical development of model-based fault detection, some proposals for the terminology in the field of supervision, fault detection and diagnosis are stated, based on the work within the IFAC SAFEPROCESS Technical Committee. Some basic fault-detection and diagnosis methods are briefly considered. Then, an evaluation of publications during the last 5 years shows some trends

R. Isermann; P. Ballé

1997-01-01

72

Predicting Fault Detection Effectiveness J. A. Morgan & G. J. Knafl W. E. Wong  

E-print Network

Predicting Fault Detection Effectiveness J. A. Morgan & G. J. Knafl W. E. Wong School of Computer Regression methods are used to model fault detection effectiveness in terms of several product and testing process measures. The relative importance of these product/process measures for predicting fault detection

Morgan, Joseph

73

Outlier Detection Rules for Fault Detection in Solar Photovoltaic Arrays  

E-print Network

Outlier Detection Rules for Fault Detection in Solar Photovoltaic Arrays Ye Zhao, Brad Lehman Abstract-- Solar photovoltaic (PV) arrays are unique power sources that may have uncleared fault current of solar photovoltaic (PV) systems. Different from traditional power sources, solar PV array is unique

Lehman, Brad

74

Fault Detection and Diagnosis of 3Phase Inverter System  

Microsoft Academic Search

This paper describes a method of detection and identification of transistor base drive open-circuit fault of 3-phase voltage source inverter (VSI), feeding a fuzzy logic controlled induction motor. The detection mechanism is based on a novel technique of wavelet transform. In this method, the stator currents will be used as an input to the system. No direct access to the

M. S. Khanniche; M. R. Mamat-Ibrahim

2001-01-01

75

Cell boundary fault detection system  

DOEpatents

An apparatus and program product determine a nodal fault along the boundary, or face, of a computing cell. Nodes on adjacent cell boundaries communicate with each other, and the communications are analyzed to determine if a node or connection is faulty.

Archer, Charles Jens (Rochester, MN); Pinnow, Kurt Walter (Rochester, MN); Ratterman, Joseph D. (Rochester, MN); Smith, Brian Edward (Rochester, MN)

2011-04-19

76

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

NASA Technical Reports Server (NTRS)

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.

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

1992-01-01

77

Space shuttle main engine fault detection using neural networks  

NASA Technical Reports Server (NTRS)

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.

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

1991-01-01

78

Reset Tree-Based Optical Fault Detection  

PubMed Central

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

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

2013-01-01

79

Incipient bearing fault detection via wind generator stator current and wavelet filter  

Microsoft Academic Search

Bearing faults constitute a significant portion of all faults in rotating machines, including wind turbine generators (WTGs). Current-based bearing fault detection has significant advantages over traditional vibration-based methods in terms of cost, implementation, and system reliability. This paper proposes a new wavelet filter-based method for incipient bearing fault detection using electric machine stator currents. The proposed method can dramatically increase

Xiang Gong; Wei Qiao; Wei Zhou

2010-01-01

80

Instrument fault detection in systems with uncertainties  

Microsoft Academic Search

We demonstrate how to detect instrument faults in non-linear time-varying processes that include uncertainties such as modelling error, parameter ambiguity, and input and output noise. The design of state estimation filters with minimum sensitivity to the uncertainties and maximum sensitivity to the instrument faults is described together with existence conditions for such filters. Simulations based on a non-linear chemical reactor

K. WATANABE; D. M. HIMMELBLAU

1982-01-01

81

Sliding mode observers for fault detection and isolation  

Microsoft Academic Search

This paper considers the application of a particular sliding mode observer to the problem of fault detection and isolation. The novelty lies in the application of the equivalent output injection concept to explicitly reconstruct fault signals. Previous work in the area of fault detection using sliding mode observers has used disruption of the sliding motion to detect faults. A design

Christopher Edwards; Sarah K. Spurgeon; Ronald J. Patton

2000-01-01

82

Fault Detection and Isolation in Multiple MEMS-IMUs Configurations  

Microsoft Academic Search

This research presents methods for detecting and isolating faults in multiple micro-electro-mechanical system inertial measurement unit (MEMS-IMU) configurations. First, geometric configurations with $n$ sensor triads are investigated. It is proved that the relative orientation between sensor triads is irrelevant to system optimality in the absence of failures. Then, the impact of sensor failure or decreased performance is investigated. Three fault

Stephane Guerrier; Adrian Waegli; Jan Skaloud; Maria-Pia Victoria-Feser

2012-01-01

83

Application of extended kalman filtering to chemical reactor fault detection  

Microsoft Academic Search

In this paper, we present a method for detecting faults that can appear in some parts of a chemical plant. This method is based on statistical information generated by the Extended Kalman Filter (EKF) and is designed to reveal any drift from the normal behavior of the process. Although this method was originally developed for linear systems, our contribution consists

Y. Chetouani; N. Mouhab; J. M. Cosmao; L. Estel

2002-01-01

84

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

NASA Technical Reports Server (NTRS)

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.

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

2010-01-01

85

MULTIPLE FAULT DETECTION AND ISOLATION Weber P. , Gentil S. , Ripoll P.  

E-print Network

MULTIPLE FAULT DETECTION AND ISOLATION Weber P. , Gentil S. , Ripoll P. TTTT , Foulloy L. TTTT CNRS 40 (ripoll@esia.univ-savoie.fr, foulloy@esia.univ-savoie.fr) Abstract: Model-based fault detection methods allow the generation of residuals as fault indicators. Isolation is generally based

Paris-Sud XI, Université de

86

Fault Detection and Isolation in Manufacturing Systems with an Identified Discrete Event Model  

E-print Network

Fault Detection and Isolation in Manufacturing Systems with an Identified Discrete Event Model) In this paper a generic method for fault detection and isolation (FDI) in manufacturing systems considered and controller built on the basis of observed fault free system behavior. An identification algorithm known from

Paris-Sud XI, Université de

87

Hierarchical fault detection and diagnosis for unmanned ground vehicles  

Microsoft Academic Search

This paper presents a fault detection and diagnosis (FDD) method for unmanned ground vehicles (UGVs) operating in multi agent systems. The hierarchical FDD method consisting of three layered software agents is proposed: Decentralized FDD (DFDD), centralized FDD (CFDD), and supervisory FDD (SFDD). Whereas the DFDD is based on modular characteristics of sensors, actuators, and controllers connected or embedded to a

Sunho Lee; Seunghan Yang; Bongsob Song

2009-01-01

88

The Detection of Fault-Prone Programs  

Microsoft Academic Search

The use of the statistical technique of discriminant analysis as a tool for the detection of fault-prone programs is explored. A principal-components procedure was employed to reduce simple multicollinear complexity metrics to uncorrelated measures on orthogonal complexity domains. These uncorrelated measures were then used to classify programs into alternate groups, depending on the metric values of the program. The criterion

John C. Munson; Taghi M. Khoshgoftaar

1992-01-01

89

Imbalance Fault Detection of Direct-Drive Wind Turbines Using Generator Current Signals  

Microsoft Academic Search

Imbalance faults constitute a significant portion of all faults in wind turbine generators (WTGs). WTG imbalance fault detection using generator current measurements has advantages over traditional vibration-based methods in terms of cost, implementation, and system reliability. However, there are challenges in using current signals for imbalance fault detection due to low signal-to-noise ratio of the useful information in current signals

Xiang Gong; Wei Qiao

2012-01-01

90

Double fault detection of cone-shaped redundant IMUs using wavelet transformation and EPSA.  

PubMed

A model-free hybrid fault diagnosis technique is proposed to improve the performance of single and double fault detection and isolation. This is a model-free hybrid method which combines the extended parity space approach (EPSA) with a multi-resolution signal decomposition by using a discrete wavelet transform (DWT). Conventional EPSA can detect and isolate single and double faults. The performance of fault detection and isolation is influenced by the relative size of noise and fault. In this paper; the DWT helps to cancel the high frequency sensor noise. The proposed technique can improve low fault detection and isolation probability by utilizing the EPSA with DWT. To verify the effectiveness of the proposed fault detection method Monte Carlo numerical simulations are performed for a redundant inertial measurement unit (RIMU). PMID:24556675

Lee, Wonhee; Park, Chan Gook

2014-01-01

91

Double Fault Detection of Cone-Shaped Redundant IMUs Using Wavelet Transformation and EPSA  

PubMed Central

A model-free hybrid fault diagnosis technique is proposed to improve the performance of single and double fault detection and isolation. This is a model-free hybrid method which combines the extended parity space approach (EPSA) with a multi-resolution signal decomposition by using a discrete wavelet transform (DWT). Conventional EPSA can detect and isolate single and double faults. The performance of fault detection and isolation is influenced by the relative size of noise and fault. In this paper; the DWT helps to cancel the high frequency sensor noise. The proposed technique can improve low fault detection and isolation probability by utilizing the EPSA with DWT. To verify the effectiveness of the proposed fault detection method Monte Carlo numerical simulations are performed for a redundant inertial measurement unit (RIMU). PMID:24556675

Lee, Wonhee; Park, Chan Gook

2014-01-01

92

Maximum correlated Kurtosis deconvolution and application on gear tooth chip fault detection  

NASA Astrophysics Data System (ADS)

In this paper a new deconvolution method is presented for the detection of gear and bearing faults from vibration data. The proposed maximum correlated Kurtosis deconvolution method takes advantage of the periodic nature of the faults as well as the impulse-like vibration behaviour associated with most types of faults. The results are compared to the standard minimum entropy deconvolution method on both simulated and experimental data. The experimental data is from a gearbox with gear chip fault, and the results are compared between healthy and faulty vibrations. The results indicate that the proposed maximum correlated Kurtosis deconvolution method performs considerably better than the traditional minimum entropy deconvolution method, and often performs several times better at fault detection. In addition to this improved performance, deconvolution of separate fault periods is possible; allowing for concurrent fault detection. Finally, an online implementation is proposed and shown to perform well and be computationally achievable on a personal computer.

McDonald, Geoff L.; Zhao, Qing; Zuo, Ming J.

2012-11-01

93

Robust Fault Detection and Isolation for Stochastic Systems  

NASA Technical Reports Server (NTRS)

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.

George, Jemin; Gregory, Irene M.

2010-01-01

94

Distributed Fault Detection Using Consensus of Markov Chains  

E-print Network

Distributed Fault Detection Using Consensus of Markov Chains Dejan P. Jovanovi and Philip K. Pollett Abstract We propose a fault detection procedure appropriate for use in a variety of industrial Models. Index Terms Fault detection, consensus algorithm, mixtures of Markov chains, the EM algorithm

Pollett, Phil

95

On-Line System for Fault Detection in Induction Machines Based on Wavelet Convolution  

Microsoft Academic Search

Motor current signature analysis has been successfully used in induction machines for fault diagnosis. The method however does not always achieve good results when the load torque is not constant. For proper results temporal analysis on determined frequency harmonics is needed. This paper proposes an automatic system for fault analysis based on wavelet functions, which allows on-line fault detection on

J. Cusido; J. A. Rosero; M. Cusido; A. Garcia; J. A. Ortega; L. Romeral

2007-01-01

96

Detection of Transmission Line Faults by Wavelet Based Transient Extraction  

E-print Network

Abstract — In this paper, a novel technique is applied to detect fault in the transmission line using wavelet transform. Three phase currents are monitored at both ends of the transmission line using global positioning system synchronizing clock. Wavelet transform, which is very fast and sensitive to noise, is used to extract transients in the line currents for fault detection. Fault index is calculated based on the sum of local and remote end detail coefficients and compared with threshold value to detect the fault. Proposed technique is tested for various faults and fault inception angles. Simulation results are presented showing the selection of proper threshold value for fault detection. Index Terms — Wavelet transform, transmission line faults, power system protection, fault transients, multiresolution analysis

P. Venugopal Rao; Shaik Abdul Gafoor; C. Venkatesh

97

Design of unknown input observers and robust fault detection filters  

Microsoft Academic Search

Fault detection filters are a special class of observers that can generate directional residuals for the purpose of fault isolation. This paper proposes a new approach to design robust (in the disturbance de-coupling sense) fault detection filters which ensure that the residual vector, generated by this filter, has both robust and directional properties. This is done by combining the unknown

JIE CHEN; RON J. PATTON; HONG-YUE ZHANG

1996-01-01

98

Detrended fluctuation analysis of vibration signals for bearing fault detection  

Microsoft Academic Search

Rolling element bearings are widely used in various rotary machines. Accordingly, a reliable bearing fault detection technique is critically needed in industries to prevent these machines' performance degradation, malfunction, or even catastrophic failures. Although a number of approaches have been reported in the literature, bearing fault detection, however, still remains a very challenging task because most of the bearing fault

Jie Liu

2011-01-01

99

Fault detection by using the innovation signal: application to an exothermic reaction  

Microsoft Academic Search

Plants in the chemical and biochemical industries are becoming larger and more complex. The growing safety and environmental demands are forcing industry to look for new and more powerful techniques for the detection of process faults. In this paper, we present a method for detecting faults that can appear in some parts of a chemical plant. This method is based

Yahya Chetouani

2004-01-01

100

Neural net application to transmission line fault detection and classification  

E-print Network

the new neural net system that can perform both on-line and off-line fault detection and classification. Fault analysis is conceptualized as a pattern classification problem which involves the association of input patterns representing the power system...

Rikalo, Igor

2012-06-07

101

Fault-tolerant adaptive FIR filters using variable detection threshold  

NASA Astrophysics Data System (ADS)

Adaptive filters are widely used in many digital signal processing applications, where tap weight of the filters are adjusted by stochastic gradient search methods. Block adaptive filtering techniques, such as block least mean square and block conjugate gradient algorithm, were developed to speed up the convergence as well as improve the tracking capability which are two important factors in designing real-time adaptive filter systems. Even though algorithm-based fault tolerance can be used as a low-cost high level fault-tolerant technique to protect the aforementioned systems from hardware failures with minimal hardware overhead, the issue of choosing a good detection threshold remains a challenging problem. First of all, the systems usually only have limited computational resources, i.e., concurrent error detection and correction is not feasible. Secondly, any prior knowledge of input data is very difficult to get in practical settings. We propose a checksum-based fault detection scheme using two-level variable detection thresholds that is dynamically dependent on the past syndromes. Simulations show that the proposed scheme reduces the possibility of false alarms and has a high degree of fault coverage in adaptive filter systems.

Lin, L. K.; Redinbo, G. R.

1994-10-01

102

Probabilistic model of fault detection in quantum circuits  

E-print Network

It is shown that the fault testing for quantum circuits does not follow conventional classical techniques. If probabilistic gate like Hadamard gate is included in a circuit then the classical notion of test vector is shown to fail. We have reported several new and distinguishing features of quantum fault and also presented a general methodology for detection of functional faults in a quantum circuit. The technique can generate test vectors for detection of different kinds of fault. Specific examples are given and time complexity of the proposed quantum fault detection algorithm is reported.

Anindita Banerjee; Anirban Pathak

2009-05-12

103

Fault detection, identification and reconstruction for gyroscope in satellite based on independent component analysis  

NASA Astrophysics Data System (ADS)

Although satellites are designed with high reliability, faults do occur when satellites are in orbit. To avoid the important services being affected, redundancy is used in satellites. There are many sensors in satellites. In order to reduce the cost, space, weight and power consumption, redundant sensors should be added to satellite as few as possible. Analytical redundancy is an efficient way to optimize the application of redundant. The gyroscope is the attitude determination sensor of the satellite. The minimum redundant structure of the gyroscope system is as follows: three gyroscopes installed in three-axis orthogonally and one gyroscope installed with slantwise for redundancy(3o+1S). To achieve fault detection, identification and reconstruction, hypothesis of statistical independence between the three-axis angular rates and hypothesis of statistical independence between the angular rates and fault are proposed. The scenario that only one sensor is faulting and there are only additive fault and full fault is supposed. Under these assumptions, firstly a threshold method is used for fault detection. After a fault is detected, independent component analysis (ICA) based algorithm for fault identification is employed. To overcome the ambiguities of ICA, correlation coefficients and prior information of the mixed matrix are used. Finally, the reconstruction matrix is obtained. By using this matrix fault signal is extracted so that the yaw, roll and pitch axes (three-axis) angular rates of the satellite can be recovered. Numerical simulations show this method can fulfill fault detection, identification and reconstruction of the gyroscope system.

Li, Zhizhou; Liu, Guohua; Zhang, Rui; Zhu, Zhencai

2011-04-01

104

Estimating the latent time of fault detection in finite automaton tested in real time  

Microsoft Academic Search

The notions of potential and real latent times of fault detection in finite automata were introduced. The potential latent\\u000a time is the minimal theoretical time of automaton fault detection, the real time is defined as the time of fault manifestation\\u000a at a certain point. A method for determination of the statistical characteristics of both times for the automaton tested in

R. Goot; I. Levin

2008-01-01

105

Phase-Sensitive Detection of Motor Fault Signatures in the Presence of Noise  

Microsoft Academic Search

In this paper, a digital signal processor-based phase-sensitive motor fault signature detection technique is presented. The implemented method has a powerful line current noise suppression capability while detecting the fault signatures. Because the line current of inverter-driven motors involve low-order harmonics, high-frequency switching disturbances, and the noise generated by harsh industrial environment, the real-time fault analyses yield erroneous or fluctuating

Bilal Akin; Umut Orguner; Hamid A. Toliyat; Mark Rayner

2008-01-01

106

A Case Study on the Comparison of Non-parametric Spectrum Methods for Broken Rotor Bar Fault Detection  

E-print Network

standards. The failure of induction motors can result in a total loss of the machine itself, in addition to the other two methods. A statistical hypothesis test applied to the results of the three methods depicts to a likely costly downtime of the whole plant. More important, these failures may even result in the loss

Chow, Mo-Yuen

107

Bearing Fault Detection in DFIG-Based Wind Turbines Using the First Intrinsic Mode Function  

E-print Network

Bearing Fault Detection in DFIG-Based Wind Turbines Using the First Intrinsic Mode Function Y become a focal point in the research of renewable energy sources. In order to make the DFIG-based wind for bearing fault detection in DFIG-based wind turbines. The proposed method uses the first Intrinsic Mode

Boyer, Edmond

108

Fault detection of large scale wind turbine systems  

Microsoft Academic Search

Fault diagnosis of large scale wind turbine systems has received much attention in the recent years. Effective fault prediction would allow for scheduled maintenance and for avoiding catastrophic failures. Thus the availability of wind turbines can be enhanced and the cost for maintenance can be reduced. In this paper, we consider the sensor and actuator fault detection issue for large

Xiukun Wei; Lihua Liu

2010-01-01

109

Detection of faults and software reliability analysis  

NASA Technical Reports Server (NTRS)

Multi-version or N-version programming is 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. These versions are executed in parallel in the application environment; each receives identical inputs and each produces its version of the required outputs. The outputs are collected by a voter and, in principle, they should all be the same. In practice there may be some disagreement. If this occurs, the results of the majority are taken to be the correct output, and that is the output used by the system. A total of 27 programs were produced. Each of these programs was then subjected to one million randomly-generated test cases. The experiment yielded a number of programs containing faults that are useful for general studies of software reliability as well as studies of N-version programming. Fault tolerance through data diversity and analytic models of comparison testing are discussed.

Knight, John C.

1987-01-01

110

The automatic selection of an optimal wavelet filter and its enhancement by the new sparsogram for bearing fault detection. Part 2 of the two related manuscripts that have a joint title as "Two automatic vibration-based fault diagnostic methods using the novel sparsity measurement—Parts 1 and 2"  

NASA Astrophysics Data System (ADS)

Rolling element bearings are the most important components used in machinery. Bearing faults, once they have developed, quickly become severe and can result in fatal breakdowns. Envelope spectrum analysis is one effective approach to detect early bearing faults through the identification of bearing fault characteristic frequencies (BFCFs). To achieve this, it is necessary to find a band-pass filter to retain a resonant frequency band for the enhancement of weak bearing fault signatures. In Part 1 paper, the wavelet packet filters with fixed center frequencies and bandwidths used in a sparsogram may not cover a whole bearing resonant frequency band. Besides, a bearing resonant frequency band may be split into two adjacent imperfect orthogonal frequency bands, which reduce the bearing fault features. Considering the above two reasons, a sparsity measurement based optimal wavelet filter is required to be designed for providing more flexible center frequency and bandwidth for covering a bearing resonant frequency band. Part 2 paper presents an automatic selection process for finding the optimal complex Morlet wavelet filter with the help of genetic algorithm that maximizes the sparsity measurement value. Then, the modulus of the wavelet coefficients obtained by the optimal wavelet filter is used to extract the envelope. Finally, a non-linear function is introduced to enhance the visual inspection ability of BFCFs. The convergence of the optimal filter is fastened by the center frequencies and bandwidths of the optimal wavelet packet nodes established by the new sparsogram. Previous case studies including a simulated bearing fault signal and real bearing fault signals were used to show that the effectiveness of the optimal wavelet filtering method in detecting bearing faults. Finally, the results obtained from comparison studies are presented to verify that the proposed method is superior to the other three popular methods.

Tse, Peter W.; Wang, Dong

2013-11-01

111

A new model-free method performing closed-loop fault diagnosis  

E-print Network

A new model-free method performing closed-loop fault diagnosis for an aeronautical system Julien), CNRS-SUPELEC-Univ Paris-Sud, France, eric.walter@lss.supelec.fr Abstract: Fault diagnosis for a closed detection and isolation, fault diagnosis, guidance and control. 1. INTRODUCTION In-flight securement

Paris-Sud XI, Université de

112

A Probability Extension of PCA to Detect and Diagnose Sensor Faults in Air Handling Units  

E-print Network

Due to sensor faults, it is a challenge to successfully detect and diagnose component faults in HVAC systems. The Principal Component Analysis (PCA) method has become a popular method to tackle this problem in recent years, but PCA is not capable...

Li, Z.

2011-01-01

113

On Finding a Nearly Minimal Set of Fault Detection Tests for Combinational Logic Nets  

Microsoft Academic Search

A procedure is described for finding, by shortcut methods, a near-minimal set of tests for detecting all single faults in a combinational logic net. The procedure should prove useful for nets which are too large to be treated by more exact methods [2]. The set of tests so found also appears useful for diagnosing (i.e., locating) faults. The class of

D. B. Armstrong

1966-01-01

114

The detection of high impedance faults using random fault behavior  

E-print Network

and with random intensity. The new algorithm presented attempts to utilize this random behavior as well as time to discriminate the pres- ence of high impedance arcing faults from normal system operations which may also generate a, high frequency current signal... overcurrent setting or fuse rating. This scenario would correspond to a feeder which is possibly heavily loaded during the day and lightly loaded at night with the fault occurring at night. The proposed A-system detector also has an enable signal generated...

Carswell, Patrick Wayne

2012-06-07

115

Early fault detection in automotive ball bearings using the minimum variance cepstrum  

NASA Astrophysics Data System (ADS)

Ball bearings in automotive wheels play an important role in a vehicle. They enable an automobile to run and simultaneously support the vehicle. Once faults are generated, even if they are small, they often grow fast even under normal driving condition and cause vibration and noise. Therefore, it is critical to detect faults as early as possible to prevent bearings from generating harsh noise and vibration. How early faults can be detected is associated with how well a detecting method finds the information of early faults from measured signal. Incipient faults are so small that the fault signal is inherently buried by noise. Minimum variance cepstrum (MVC) has been introduced for the observation of periodic impulse signal under noisy environments. We are particularly focusing on the definition of MVC that goes back to the original definition by Bogert et al. in comparison with the recently prevalent definition of cepstral analysis. In this work, the MVC is, therefore, obtained by liftering a logarithmic power spectrum, and the lifter bank is designed by the minimum variance algorithm. Furthermore, it is also shown how efficient the method is for detecting periodic fault signal made by early faults by using automotive ball bearings, with which an automobile is equipped under running conditions. We were able to detect incipient faults in 4 out of 12 normal bearings which passed acceptance test as well as in bearings that were recalled due to noise and vibration. In addition, we compared the results of the proposed method with results obtained using other older well-established early fault detection methods that were chosen from 4 groups of methods which were classified by the domain of observation. The results demonstrated that MVC determined bearing fault periods more clearly than other methods under the given condition.

Park, Choon-Su; Choi, Young-Chul; Kim, Yang-Hann

2013-07-01

116

Toward Reducing Fault Fix Time: Understanding Developer Behavior for the Design of Automated Fault Detection Tools, the Full Report  

E-print Network

Toward Reducing Fault Fix Time: Understanding Developer Behavior for the Design of Automated Fault}@csc.ncsu.edu Abstract The longer a fault remains in the code from the time it was injected, the more time it will take to fix the fault. Increasingly, automated fault detection (AFD) tools are providing developers

Young, R. Michael

117

Online Fault Detection and Tolerance for Photovoltaic Energy Harvesting Systems  

E-print Network

effects of fossil fuels, human society is in desperate need of renewable energy sources (e.g., solar, wind shorten the PV system lifespan. Manual PV cell fault detection and elimination are expensive and nearly PV systems (e.g., PV systems for satellites), manual fault detection and elimination is expensive

Pedram, Massoud

118

Observer-based fault detection and isolation: Robustness and applications  

Microsoft Academic Search

This paper studies the observer-based fault detection and isolation problem with an emphasis on robustness and applications. After introducing some basic definitions, the problem of model-based fault detection and isolation is introduced. This is followed by a summary of the basic ideas behind the use of observers in generating diagnostic residual signals. The robustness issues are then defined and ideas

R. J. Patton; J. Chen

1997-01-01

119

Fault Detection, Identification and Accommodation for an Electro-hydraulic  

E-print Network

Fault Detection, Identification and Accommodation for an Electro-hydraulic System: An Adaptive in electro-hydraulic systems. It is well known fact that any realistic model of a hydraulic system suffers, such a scheme becomes a natural choice for designing robust fault detection algorithms for electro-hydraulic

Yao, Bin

120

Detection of Rooftop Cooling Unit Faults Based on Electrical Measurements  

Microsoft Academic Search

Nonintrusive 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 rooftop cooling units. Use of the NILM for fault detection and diagnosis (FDD)

Peter R. Armstrong; Christopher R. Laughman; Steven B. Leeb; Leslie K. Norford

2006-01-01

121

Distributed fault detection and isolation resilient to network model uncertainties.  

PubMed

The ability to maintain state awareness in the face of unexpected and unmodeled errors and threats is a defining feature of a resilient control system. Therefore, in this paper, we study the problem of distributed fault detection and isolation (FDI) in large networked systems with uncertain system models. The linear networked system is composed of interconnected subsystems and may be represented as a graph. The subsystems are represented by nodes, while the edges correspond to the interconnections between subsystems. Considering faults that may occur on the interconnections and subsystems, as our first contribution, we propose a distributed scheme to jointly detect and isolate faults occurring in nodes and edges of the system. As our second contribution, we analyze the behavior of the proposed scheme under model uncertainties caused by the addition or removal of edges. Additionally, we propose a novel distributed FDI scheme based on local models and measurements that is resilient to changes outside of the local subsystem and achieves FDI. Our third contribution addresses the complexity reduction of the distributed FDI method, by characterizing the minimum amount of model information and measurements needed to achieve FDI and by reducing the number of monitoring nodes. The proposed methods can be fused to design a scalable and resilient distributed FDI architecture that achieves local FDI despite unknown changes outside the local subsystem. The proposed approach is illustrated by numerical experiments on the IEEE 118-bus power network benchmark. PMID:25222962

Teixeira, Andre; Shames, Iman; Sandberg, Henrik; Johansson, Karl H

2014-11-01

122

Research on Fault Detection and Diagnosis of Scrolling Chiller with ANN  

E-print Network

ICEBO2006, Shenzhen, China Co ntrol Systems for Energy Efficiency and Comfort, Vol. V-5-3 Research on Fault Detection and Diagnosis of Scrolling Chiller with ANN1 Yuli ZHOU Jie ZHENG Zhiju LIU Chaojie YANG Peng PENG... ZHENG, Yuli ZHOU.HVAC The Analysis Of Fault Characteristics And The Establishment Of Diagnosis System Journal of Guizhou Industry University 2003.Vol.32.add .175-178 [4] Srinivas Katipamula, PhD Michael R. Brambley, PhD Methods for Fault...

Zhou, Y.; Zheng, J.; Liu, Z.; Yang, C.; Peng, P.

2006-01-01

123

Data-driven and adaptive statistical residual evaluation for fault detection with an automotive application  

NASA Astrophysics Data System (ADS)

An important step in model-based fault detection is residual evaluation, where residuals are evaluated with the aim to detect changes in their behavior caused by faults. To handle residuals subject to time-varying uncertainties and disturbances, which indeed are present in practice, a novel statistical residual evaluation approach is presented. The main contribution is to base the residual evaluation on an explicit comparison of the probability distribution of the residual, estimated online using current data, with a no-fault residual distribution. The no-fault distribution is based on a set of a priori known no-fault residual distributions, and is continuously adapted to the current situation. As a second contribution, a method is proposed for estimating the required set of no-fault residual distributions off-line from no-fault training data. The proposed residual evaluation approach is evaluated with measurement data on a residual for fault detection in the gas-flow system of a Scania truck diesel engine. Results show that small faults can be reliably detected with the proposed approach in cases where regular methods fail.

Svärd, Carl; Nyberg, Mattias; Frisk, Erik; Krysander, Mattias

2014-03-01

124

Advanced Fault Diagnosis Methods in Molecular Networks  

PubMed Central

Analysis of the failure of cell signaling networks is an important topic in systems biology and has applications in target discovery and drug development. In this paper, some advanced methods for fault diagnosis in signaling networks are developed and then applied to a caspase network and an SHP2 network. The goal is to understand how, and to what extent, the dysfunction of molecules in a network contributes to the failure of the entire network. Network dysfunction (failure) is defined as failure to produce the expected outputs in response to the input signals. Vulnerability level of a molecule is defined as the probability of the network failure, when the molecule is dysfunctional. In this study, a method to calculate the vulnerability level of single molecules for different combinations of input signals is developed. Furthermore, a more complex yet biologically meaningful method for calculating the multi-fault vulnerability levels is suggested, in which two or more molecules are simultaneously dysfunctional. Finally, a method is developed for fault diagnosis of networks based on a ternary logic model, which considers three activity levels for a molecule instead of the previously published binary logic model, and provides equations for the vulnerabilities of molecules in a ternary framework. Multi-fault analysis shows that the pairs of molecules with high vulnerability typically include a highly vulnerable molecule identified by the single fault analysis. The ternary fault analysis for the caspase network shows that predictions obtained using the more complex ternary model are about the same as the predictions of the simpler binary approach. This study suggests that by increasing the number of activity levels the complexity of the model grows; however, the predictive power of the ternary model does not appear to be increased proportionally. PMID:25290670

Habibi, Iman; Emamian, Effat S.; Abdi, Ali

2014-01-01

125

Machine-learning Based Automated Fault Detection in Seismic Chiyuan Zhang and Charlie Frogner (MIT),  

E-print Network

Machine-learning Based Automated Fault Detection in Seismic Traces Chiyuan Zhang and Charlie no seismic data has been migrated. Our novel method is based on machine learning tech- niques and can a machine learning approach: We generate a set of seismic traces from velocity models containing faults

Poggio, Tomaso

126

Remote Fault Detection of Building HVAC System Using a Global Optimization Program  

E-print Network

fault detection method using the global optimization program Solver® (Frontline Systems, 2000) coupled to a simplified simulation program, which is a coding of the ASHRAE 'Simplified Energy Analysis Procedure' (Knebel, 1983). This approach uses...

Lee, S. U.; Claridge, D. E.

2004-01-01

127

Detection of feed-through faults in CMOS storage elements  

NASA Technical Reports Server (NTRS)

In testing sequential circuits, internal faults in the storage elements (SE's) are sometimes modeled as stuck-at faults in the combinational circuits surrounding the SE. The detection of some transistor-level faults that cannot be modeled as stuck-at are considered. These feed-through faults cause the cell to become either data-feed-through, which makes the cell combinational, or clock-feed-through, which causes the clock signal or its complement to appear at the output. Under such faults, the cell does not function as a memory element. Here it is shown that such faults may or may not be detected depending on delays involved. Conditions under which race-ahead occurs are identified.

Al-Assadi, Waleed K.; Malaiya, Yashwant K.; Jayasumana, Anura P.

1992-01-01

128

A Fault Analytic Method against HB+  

E-print Network

The search for lightweight authentication protocols suitable for low-cost RFID tags constitutes an active and challenging research area. In this context, a family of protocols based on the LPN problem has been proposed: the so-called HB-family. Despite the rich literature regarding the cryptanalysis of these protocols, there are no published results about the impact of fault analysis over them. The purpose of this paper is to fill this gap by presenting a fault analytic method against a prominent member of the HB-family: HB+ protocol. We demonstrate that the fault analysis model can lead to a flexible and effective attack against HB-like protocols, posing a serious threat over them.

Carrijo, Jose; Nascimento, Anderson C A

2010-01-01

129

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

PubMed Central

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

Moghadas, Amin A.; Shadaram, Mehdi

2010-01-01

130

Novel Identification Method of Stator Single Phase-to-Ground Fault for Cable-Wound Generators  

Microsoft Academic Search

A new criterion to detect the stator single phase-to-ground fault for Powerformer is proposed in this paper, which is based on the direction of zero-sequence compositive power flow. By virtue of the analysis of new fault characteristics of Powerformer and the comparison with conventional methods, a novel identification scheme is put forward. The proposed approach detects the ground fault by

Yan Gao; Xiangning Lin; Qing Tian; Pei Liu

2008-01-01

131

Incipient fault detection and identification in process systems using artificial neural networks  

E-print Network

signatures. During such faults, the inherent limitation of pattern recognition based FDI methods becomes apparent. Alternate, more sophisticated FDI methods become necessary to address such problems. Nevertheless, even though the effective- ness of pattern... . IV. 3 Estimation Methods. . . . . . . . . IV. 4 Pattern Recognition Methods IV. 5 Fault Detection using Artificial Neural Networks . 44 44 46 48 49 PHYSICAL MODELING OF THE PROCESS USED STUDY, , IN THE FDI 51 V. I Introduction V. 2...

Muthusami, Jayakumar

2012-06-07

132

Vehicle localization in outdoor woodland environments with sensor fault detection  

Microsoft Academic Search

Abstract— This paper,describes,a 2D localization method for a differential drive mobile,vehicle on real forested paths. The mobile vehicle is equipped with two rotary encoders, Crossbow’s NAV420CA Inertial Measurement,Unit (IMU) and a NAVCOM SF-2050M GPS receiver (used in StarFire-DGPS dual,mode). Loosely-coupled multisensor,fusion,and,sensor fault detection issues are discussed as well. An extended,Kalman Filter (EKF) is used for sensor fusion estimation where,a GPS

Yoichi Morales Saiki; Eijiro Takeuchi; Takashi Tsubouchi

2008-01-01

133

Generating Minimal Fault Detecting Test Suites for Boolean Expressions  

Microsoft Academic Search

New coverage criteria for Boolean expressions are regularly introduced with two goals: to detect specific classes of realistic faults and to produce as small as possible test suites. In this paper we investigate whether an approach targeting specific fault classes using several reduction policies can achieve that less test cases are generated than by previously introduced testing criteria. In our

Gordon Fraser; Angelo Gargantini

2010-01-01

134

Fault Detection and Diagnosis Techniques for Liquid-Propellant Rocket Propellant Engines  

NASA Astrophysics Data System (ADS)

Fault detection and diagnosis plays a pivotal role in the health-monitoring techniques for liquid- propellant rocket engines. This paper firstly gives a brief summary on the techniques of fault detection and diagnosis utilized in liquid-propellant rocket engines. Then, the applications of fault detection and diagnosis algorithms studied and developed to the Long March Main Engine System(LMME) are introduced. For fault detection, an analytical model-based detection algorithm, a time-series-analysis algorithm and a startup- transient detection algorithm based on nonlinear identification developed and evaluated through ground-test data of the LMME are given. For fault diagnosis, neural-network approaches, nonlinear-static-models based methods, and knowledge-based intelligent approaches are presented. Keywords: Fault detection; Fault diagnosis; Health monitoring; Neural networks; Fuzzy logic; Expert system; Long March main engines Contact author and full address: Dr. Jianjun Wu Department of Astronautical Engineering School of Aerospace and Material Engineering National University of Defense Technology Changsha, Hunan 410073 P.R.China Tel:86-731-4556611(O), 4573175(O), 2219923(H) Fax:86-731-4512301 E-mail:jjwu@nudt.edu.cn

Wua, Jianjun; Tanb, Songlin

2002-01-01

135

ASCS online fault detection and isolation based on an improved MPCA  

NASA Astrophysics Data System (ADS)

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.

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

2014-07-01

136

Non-intrusive fault detection in reciprocating compressors  

E-print Network

This thesis presents a set of techniques for non-intrusive sensing and fault detection in reciprocating compressors driven by induction motors. The procedures developed here are "non-intrusive" because they rely only on ...

Schantz, Christopher James

2011-01-01

137

Fault diagnosis of ball bearings using machine learning methods  

Microsoft Academic Search

Ball bearings faults are one of the main causes of breakdown of rotating machines. Thus, detection and diagnosis of mechanical faults in ball bearings is very crucial for the reliable operation. This study is focused on fault diagnosis of ball bearings using artificial neural network (ANN) and support vector machine (SVM). A test rig of high speed rotor supported on

P. K. Kankar; Satish C. Sharma; S. P. Harsha

2011-01-01

138

Fault detection in rotary blood pumps using motor speed response.  

PubMed

Clinical acceptance of ventricular assist devices (VADs) as long-term heart failure therapy requires safe and effective circulatory support for a minimum of 5 years. Yet, VAD failure beyond 2 years of support is still a concern. Currently, device controllers cannot consistently predict VAD failure modes, and undetected VAD faults may lead to catastrophic device failure. To minimize this risk, a model-based algorithm for reliable VAD fault detection that only requires VAD revolutions per minute (rpm) was developed. The algorithm was tested using computer models of the human cardiovascular system simulating heart failure and axial flow (AF) or centrifugal flow (CF) VADs. Ventricular assist device rpm was monitored after a step down of motor current for normal and simulated fault conditions (>750 faults). The ability to detect fault conditions with 1%, 5%, and 10% rpm measurement noise was evaluated. All failure modes affected the VAD rpm responses to the motor current step down. Fault detection rates were >95% for AF and >89% for CF VADs, even with 10% rpm measurement noise. The VAD rpm responses were significantly altered by blood viscosity (3.5-6.2 cP), which should be accounted for in clinical application. The proposed VAD fault detection algorithm may deliver a convenient and nonintrusive way to minimize catastrophic device failures. PMID:23820281

Soucy, Kevin G; Koenig, Steven C; Sobieski, Michael A; Slaughter, Mark S; Giridharan, Guruprasad A

2013-01-01

139

Soft Computing Application in Fault Detection of Induction Motor  

NASA Astrophysics Data System (ADS)

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.

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

2010-10-01

140

Detecting Hidden Faults and Other Lineations with UAVSAR  

NASA Astrophysics Data System (ADS)

Jay Parker, Margaret Glasscoe, Andrea Donnellan Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA The M7.2 El Mayor Cucapah Earthquake of April 4, 2010 is the main earthquake to date observed by the NASA UAVSAR. By observing with repeat passes (October 2009, April 2010 captures the coseismic strain pattern, and subsequent flights capture the postseismic process) over the adjoining portion of California, the interferometric phase maps of geodetic displacements are exceptionally high definition (pixel size is roughly 7 m) records of the extended deformation field from the earthquake process, including revelation of a rich network of plate parallel and conjugate faulting, apparently slipping sympathetically to the earthquake-induced quasistatic changes in stress. While the most significant of these faults have been documented by cooperative use of UAVSAR maps and field research, a subsequent opportunity arises: to use this data to develop and validate an automated approach to detecting faults and other lineations directly from the UAVSAR unwrapped phase product that corresponds to a single-component deformation map. The Canny edge detection algorithm is employed, after a preparation stage to clean the data. This preprocessing step is tailored to the nature of the radar phase data: data dropouts in single pixels and extended areas (blown sand dunes, farms) are a much larger problem than background white noise. Blocks of typically 3x3 pixels are currently reduced to a single value, the average after bad pixels are discarded. The smoothing methods typically used with the Canny method are minimized (smoothing makes data drop-out problems worse). The aperture size that determines a gradient estimation is chosen large (7 vs. the typical 3), as this is found to produce continuous (rather than dashed) lineations. The main Canny threshold is chosen to correspond to a user selected slip threshold in mm. Reasonable maps of lineations in the Salton Trough occur with a threshold of 3mm: higher values result in a loss of interesting lineations; lower ones produce excess clutter. Lineation detection from InSAR phase will miss faults parallel to the aircraft flight line. But because it relies on phase changes over small (~20 m) distances the lineations are unaffected by most atmospheric water vapor effects, uncompensated aircraft motion, and distributed tectonic deformation

Parker, J. W.; Glasscoe, M. T.; Donnellan, A.

2013-12-01

141

Modification of the Weighted Checksum Method for Deriving Fault Tolerant Versions of the Main Linear Algebra Algorithms  

Microsoft Academic Search

The modified weighted checksum method is proposed, which can be used for deriving fault tolerant versions of most linear algebra algorithms. The purpose is the detection and correction of calculation errors occurred due to transient hardware faults during algorithm execution. Using the proposed method, the fault-tolerant versions of Jordan-Gauss and Faddeeva algorithms are designed. The computational complexity of new algorithms

Oleg Maslennikov

2002-01-01

142

Auxiliary signal design in fault detection and diagnosis  

NASA Astrophysics Data System (ADS)

Fault-detection and diagnosis schemes for systems represented by linear MIMO stochastic models are developed analytically, with a focus on on the design and application of auxiliary signals. The basic principles of optimal-input design are reviewed, and consideration is given to the sequential probability ratio test (SPRT), auxiliary signals for improving SPRT fault detection, and the extension of the SPRT to multiple-hypothesis testing. Two chapters are devoted to the application of the SPRT to a model chemical plant (producing anhydrous caustic soda), including model derivation, model identification, detection of type I and type II faults, and the fault-diagnosis decision-making mechanism. Numerical results are presented in graphs and briefly characterized.

Zhang, Xue Jun

143

Sparse representation based latent components analysis for machinery weak fault detection  

NASA Astrophysics Data System (ADS)

Weak machinery fault detection is a difficult task because of two main reasons (1) At the early stage of fault development, signature of fault related component performs incompletely and is quite different from that at the apparent failure stage. In most instances, it seems almost identical with the normal operating state. (2) The fault feature is always submerged and distorted by relatively strong background noise and macro-structural vibrations even if the fault component already performs completely, especially when the structure of fault components and interference are close. To solve these problems, we should penetrate into the underlying structure of the signal. Sparse representation provides a class of algorithms for finding succinct representations of signal that capture higher-level features in the data. With the purpose of extracting incomplete or seriously overwhelmed fault components, a sparse representation based latent components decomposition method is proposed in this paper. As a special case of sparse representation, shift-invariant sparse coding algorithm provides an effective basis functions learning scheme for capturing the underlying structure of machinery fault signal by iteratively solving two convex optimization problems: an L1-regularized least squares problem and an L2-constrained least squares problem. Among these basis functions, fault feature can be probably contained and extracted if optimal latent component is filtered. The proposed scheme is applied to analyze vibration signals of both rolling bearings and gears. Experiment of accelerated lifetime test of bearings validates the proposed method's ability of detecting early fault. Besides, experiments of fault bearings and gears with heavy noise and interference show the approach can effectively distinguish subtle differences between defect and interference. All the experimental data are analyzed by wavelet shrinkage and basis pursuit de-noising (BPDN) method for comparison.

Tang, Haifeng; Chen, Jin; Dong, Guangming

2014-06-01

144

Enhanced Fault Detection of Rolling Element Bearing Based on Cepstrum Editing and Stochastic Resonance  

NASA Astrophysics Data System (ADS)

By signal pre-whitening based on cepstrum editing,the envelope analysis can be done over the full bandwidth of the pre-whitened signal, and this enhances the bearing characteristic frequencies. The bearing faults detection could be enhanced without knowledge of the optimum frequency bands to demodulate, however, envelope analysis over full bandwidth brings more noise interference. Stochastic resonance (SR), which is now often used in weak signal detection, is an important nonlinear effect. By normalized scale transform, SR can be applied in weak signal detection of machinery system. In this paper, signal pre-whitening based on cepstrum editing and SR theory are combined to enhance the detection of bearing fault. The envelope spectrum kurtosis of bearing fault characteristic components is used as indicators of bearing faults. Detection results of planted bearing inner race faults on a test rig show the enhanced detecting effects of the proposed method. And the indicators of bearing inner race faults enhanced by SR are compared to the ones without enhancement to validate the proposed method.

Zhang, Xiaofei; Hu, Niaoqing; Hu, Lei; Fan, Bin; Cheng, Zhe

2012-05-01

145

Fault Detection in Induction Machines Using Power Spectral Density in Wavelet Decomposition  

Microsoft Academic Search

Motor-current-signature analysis has been successfully used in induction machines for fault diagnosis. The method, however, does not always achieve good results when the speed or the load torque is not constant, because this causes variations on the motor-slip and fast Fourier transform problems appear due to a nonstationary signal. This paper proposes a new method for motor fault detection, which

Luis Romeral; Juan A. Ortega; Javier A. Rosero

2008-01-01

146

Similarity Ratio Analysis for Early Stage Fault Detection with Optical Emission Spectrometer in Plasma Etching Process  

PubMed Central

A Similarity Ratio Analysis (SRA) method is proposed for early-stage Fault Detection (FD) in plasma etching processes using real-time Optical Emission Spectrometer (OES) data as input. The SRA method can help to realise a highly precise control system by detecting abnormal etch-rate faults in real-time during an etching process. The method processes spectrum scans at successive time points and uses a windowing mechanism over the time series to alleviate problems with timing uncertainties due to process shift from one process run to another. A SRA library is first built to capture features of a healthy etching process. By comparing with the SRA library, a Similarity Ratio (SR) statistic is then calculated for each spectrum scan as the monitored process progresses. A fault detection mechanism, named 3-Warning-1-Alarm (3W1A), takes the SR values as inputs and triggers a system alarm when certain conditions are satisfied. This design reduces the chance of false alarm, and provides a reliable fault reporting service. The SRA method is demonstrated on a real semiconductor manufacturing dataset. The effectiveness of SRA-based fault detection is evaluated using a time-series SR test and also using a post-process SR test. The time-series SR provides an early-stage fault detection service, so less energy and materials will be wasted by faulty processing. The post-process SR provides a fault detection service with higher reliability than the time-series SR, but with fault testing conducted only after each process run completes. PMID:24755865

Yang, Jie; McArdle, Conor; Daniels, Stephen

2014-01-01

147

Automated Fault Detection for DIII-D Tokamak Experiments  

SciTech Connect

An automated fault detection software system has been developed and was used during 1999 DIII-D plasma operations. The Fault Identification and Communication System (FICS) executes automatically after every plasma discharge to check dozens of subsystems for proper operation and communicates the test results to the tokamak operator. This system is now used routinely during DIII-D operations and has led to an increase in tokamak productivity.

Walker, M.L.; Scoville, J.T.; Johnson, R.D.; Hyatt, A.W.; Lee, J.

1999-11-01

148

Composite Bending Box section Modal Vibration fault Detection  

Microsoft Academic Search

Abstract: 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

Rudy Werlink

149

Investigation of advanced fault insertion and simulator methods  

NASA Technical Reports Server (NTRS)

The cooperative agreement partly supported research leading to the open-literature publication cited. Additional efforts under the agreement included research into fault modeling of semiconductor devices. Results of this research are presented in this report which is summarized in the following paragraphs. As a result of the cited research, it appears that semiconductor failure mechanism data is abundant but of little use in developing pin-level device models. Failure mode data on the other hand does exist but is too sparse to be of any statistical use in developing fault models. What is significant in the failure mode data is that, unlike classical logic, MSI and LSI devices do exhibit more than 'stuck-at' and open/short failure modes. Specifically they are dominated by parametric failures and functional anomalies that can include intermittent faults and multiple-pin failures. The report discusses methods of developing composite pin-level models based on extrapolation of semiconductor device failure mechanisms, failure modes, results of temperature stress testing and functional modeling. Limitations of this model particularly with regard to determination of fault detection coverage and latency time measurement are discussed. Indicated research directions are presented.

Dunn, W. R.; Cottrell, D.

1986-01-01

150

Robust Fault Detection System for Insulin Pump Therapy Using Continuous Glucose Monitoring  

PubMed Central

Background The popularity of continuous subcutaneous insulin infusion (CSII), or insulin pump therapy, as a way to deliver insulin more physiologically and achieve better glycemic control in diabetes patients has increased. Despite the substantiated therapeutic advantages of using CSII, its use has also been associated with an increased risk of technical malfunctioning of the device, which leads to an increased risk of acute metabolic complications, such as diabetic ketoacidosis. Current insulin pumps already incorporate systems to detect some types of faults, such as obstructions in the infusion set, but are not able to detect other types of fault such as the disconnection or leakage of the infusion set. Methods In this article, we propose utilizing a validated robust model-based fault detection technique, based on interval analysis, for detecting disconnections of the insulin infusion set. For this purpose, a previously validated metabolic model of glucose regulation in type 1 diabetes mellitus (T1DM) and a continuous glucose monitoring device were used. As a first step to assess the performance of the presented fault detection system, a Food and Drug Administration-accepted T1DM simulator was employed. Results Of the 100 in silico tests (10 scenarios on 10 subjects), only two false negatives and one false positive occurred. All faults were detected before plasma glucose concentration reached 300 mg/dl, with a mean plasma glucose detection value of 163 mg/dl and a mean detection time of 200 min. Conclusions Interval model-based fault detection has been proven (in silico) to be an effective tool for detecting disconnection faults in sensor-augmented CSII systems. Proper quantification of the uncertainty associated with the employed model has been observed to be crucial for the good performance of the proposed approach. PMID:23063040

Herrero, Pau; Calm, Remei; Vehí, Josep; Armengol, Joaquim; Georgiou, Pantelis; Oliver, Nick; Tomazou, Christofer

2012-01-01

151

Fault Tree Analysis, Methods, and Applications ? A Review  

Microsoft Academic Search

This paper reviews and classifies fault-tree analysis methods developed since 1960 for system safety and reliability. Fault-tree analysis is a useful analytic tool for the reliability and safety of complex systems. The literature on fault-tree analysis is, for the most part, scattered through conference proceedings and company reports. We have classified the literature according to system definition, fault-tree construction, qualitative

W. S. Lee; D. L. Grosh; F. A. Tillman; C. H. Lie

1985-01-01

152

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

Microsoft Academic Search

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

Hacene Habbi; Madjid Kidouche; Michel Kinnaert; Mimoun Zelmat

2011-01-01

153

Broken rotor bar fault detection in induction motors using Wavelet Transform  

Microsoft Academic Search

The Fast Fourier Transform (FFT) method is successfully used for the broken rotor bar fault detection purpose in the induction machines. It is based on the common-steady state analysis of the motor. This method is successfully used with Motor Current Signature Analysis (MCSA) technique for last three decades. However, this method is suffered from some serious drawbacks such as; it

Khadim Moin Siddiqui; V. K. Giri

2012-01-01

154

ARX model-based gearbox fault detection and localization under varying load conditions  

NASA Astrophysics Data System (ADS)

The development of the fault detection schemes for gearbox systems has received considerable attention in recent years. Both time series modeling and feature extraction based on wavelet methods have been considered, mostly under constant load. Constant load assumption implies that changes in vibration data are caused only by deterioration of the gearbox. However, most real gearbox systems operate under varying load and speed which affect the vibration signature of the system and in general make it difficult to recognize the occurrence of an impending fault. This paper presents a novel approach to detect and localize the gear failure occurrence for a gearbox operating under varying load conditions. First, residual signal is calculated using an autoregressive model with exogenous variables (ARX) fitted to the time-synchronously averaged (TSA) vibration data and filtered TSA envelopes when the gearbox operated under various load conditions in the healthy state. The gear of interest is divided into several sections so that each section includes the same number of adjacent teeth. Then, the fault detection and localization indicator is calculated by applying F-test to the residual signal of the ARX model. The proposed fault detection scheme indicates not only when the gear fault occurs, but also in which section of the gear. Finally, the performance of the fault detection scheme is checked using full lifetime vibration data obtained from the gearbox operating from a new condition to a breakdown under varying load.

Yang, Ming; Makis, Viliam

2010-11-01

155

Automatic Fault Extraction at Mid-Ocean Ridges: Effects of Bathymetry Resolution and Extraction Method  

NASA Astrophysics Data System (ADS)

High-angle normal faults at mid-ocean ridges are important indicators of the processes driving oceanic crust formation. Fault size and distribution are currently either estimated in the field or scarp outlines are painstakingly digitized by hand following a cruise. Some attempts have been made to automate this process using techniques from the fields of geomorphometry and image analysis, such as slope gradient and curvature thresholding and wavelet filtering. However, little assessment of the accuracy of these techniques has been made. Additionally, these techniques require manual threshold selection and thus cannot be equally applied to areas with different length scales of deformation. This study presents a fully-automatic method of fault extraction consisting of two major steps: fault identification and error removal. Fault scarps are initially extracted using slope gradient thresholding, profile curvature thresholding and the Canny edge detection algorithm. The extracted set of faults is then refined by removing small noise objects, eliminating other steep seafloor features with an aspect ratio threshold, and finally by focusing on a single fault population using an azimuth threshold. Terrain thresholds are automatically determined from digital bathymetric model (DBM) gradient and curvature histograms using the Jenks natural breaks algorithm, and error removal thresholds are standardized based on DBM resolution. DBMs at a variety of resolutions (1 m - 150 m pixels) and at a variety of spreading locations are used to test the three methods. Results show that automatic extraction accuracy varies widely and is affected most by the linearity of fault lines and the smoothness of fault upper and lower boundaries rather than by resolution or extraction method. Assessed visually, the gradient method gives better results for large, smooth, linear faults located far from the axis. The curvature method gives better results for small, sharp, complex faults located adjacent to the axis. The best overall results are achieved by the edge detection method, which maximizes fault line continuity and detects a large number of faults overall. The main disadvantage of this method is that it produces fault lines rather than polygons. These initial results are promising and suggest that with further work automatic fault extraction can be sufficiently optimized to be useful for rapid initial analysis of fault patterns.

Schnur, S.; Escartin, J.; Purves, R. S.; Frueh-Green, G. L.; Soule, S. A.

2011-12-01

156

Detection of Rooftop Cooling Unit Faults Based on Electrical Measurements  

SciTech Connect

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. This paper describes changes in the power signatures of fans and compressors that were found, experimentally and theoretically, to be useful for fault detection.

Armstrong, Peter R.; Laughman, C R.; Leeb, S B.; Norford, L K.

2006-01-31

157

Experimental analysis of change detection algorithms for multitooth machine tool fault detection  

NASA Astrophysics Data System (ADS)

This paper describes an industrial application of fault diagnosis method for a multitooth machine tool. Different statistical approaches have been used to detect and diagnose insert breakage in multitooth tools based on the analysis of electrical power consumption of the tool drives. Great effort has been made to obtain a robust method, able to avoid any needed re-calibration process, after, for example, a maintenance operation. From the point of view of maintenance costs, these multitooth tools are the most critical part of the machine tools used for mass production in the car industry. These tools integrate different kinds of machining operations and cutting conditions.

Reñones, Aníbal; de Miguel, Luis J.; Perán, José R.

2009-10-01

158

Fault Detection on Multicell Converter Based on Output Voltage Frequency Analysis  

Microsoft Academic Search

Multilevel converters use a large amount of semiconductors, allowing the reconfigurate of the converter to work even on internal fault condition. This paper presents a method to detect faulty cells in a cascaded multicell converter requiring just one voltage measurement per output phase. The method is based on high-frequency harmonic analysis, using a dynamic prediction of their behavior, avoiding erroneous

Pablo Lezana; Ricardo Aguilera; José Rodríguez

2009-01-01

159

Adaptive redundant multiwavelet denoising with improved neighboring coefficients for gearbox fault detection  

NASA Astrophysics Data System (ADS)

Gearbox fault detection under strong background noise is a challenging task. It is feasible to make the fault feature distinct through multiwavelet denoising. In addition to the advantage of multi-resolution analysis, multiwavelet with several scaling functions and wavelet functions can detect the different fault features effectively. However, the fixed basis functions not related to the given signal may lower the accuracy of fault detection. Moreover, the multiwavelet transform may result in Gibbs phenomena in the step of reconstruction. Furthermore, both traditional term-by-term threshold and neighboring coefficients do not consider the direct spatial dependency of wavelet coefficients at adjacent scale. To overcome these deficiencies, adaptive redundant multiwavelet (ARM) denoising with improved neighboring coefficients (NeighCoeff) is proposed. Based on symmetric multiwavelet lifting scheme (SMLS), taking kurtosis—partial envelope spectrum entropy as the evaluation objective and genetic algorithms as the optimization method, ARM is proposed. Considering the intra-scale and inter-scale dependency of wavelet coefficients, the improved NeighCoeff method is developed and incorporated into ARM. The proposed method is applied to both the simulated signal and the practical gearbox vibration signal under different conditions. The results show its effectiveness and reliance for gearbox fault detection.

Chen, Jinglong; Zi, Yanyang; He, Zhengjia; Wang, Xiaodong

2013-07-01

160

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

NASA Technical Reports Server (NTRS)

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.

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

2010-01-01

161

Early Oscillation Detection for DC/DC Converter Fault Diagnosis  

NASA Technical Reports Server (NTRS)

The electrical power system of a spacecraft plays a very critical role for space mission success. Such a modern power system may contain numerous hybrid DC/DC converters both inside the power system electronics (PSE) units and onboard most of the flight electronics modules. One of the faulty conditions for DC/DC converter that poses serious threats to mission safety is the random occurrence of oscillation related to inherent instability characteristics of the DC/DC converters and design deficiency of the power systems. To ensure the highest reliability of the power system, oscillations in any form shall be promptly detected during part level testing, system integration tests, flight health monitoring, and on-board fault diagnosis. The popular gain/phase margin analysis method is capable of predicting stability levels of DC/DC converters, but it is limited only to verification of designs and to part-level testing on some of the models. This method has to inject noise signals into the control loop circuitry as required, thus, interrupts the DC/DC converter's normal operation and increases risks of degrading and damaging the flight unit. A novel technique to detect oscillations at early stage for flight hybrid DC/DC converters was developed.

Wang, Bright L.

2011-01-01

162

SENSOR CLASSIFICATION FOR THE FAULT DETECTION AND ISOLATION PROBLEM  

E-print Network

SENSOR CLASSIFICATION FOR THE FAULT DETECTION AND ISOLATION PROBLEM Christian Commault Jean is solvable with the existing sensors, we will classify these sensors according to their importance for the solvability of the considered FDI problem. The sensors will be classified into essential sensors, useless

Paris-Sud XI, Université de

163

Backlash Fault Detection in Mechatronic R. Merzoukia,1  

E-print Network

between input and output system positions. Thus, an important dead zone affects the system performance, and can be classified in three classes: those where the main interest is the control of such systems (eBacklash Fault Detection in Mechatronic System R. Merzoukia,1 , K. Medjaherb , M. A. Djeziric and B

Boyer, Edmond

164

Detection and Diagnosis of HVAC Faults via Electrical Load Monitoring  

Microsoft Academic Search

Detection and diagnosis of faults (FDD) in HVAC equipment have typically relied on measurements of variables available to a control system, including temperatures, flows, pressures, and actuator control signals. Electrical power at the level of a fan, pump, or chiller has been generally ignored because power meters are rarely installed at individual loads. This paper presents two techniques for using

S. R. Shaw; L. K. Norford; D. D. Luo; S. B. Leeb

2002-01-01

165

Fault Detection and Elimination for Galileo-GPS Vertical Guidance  

E-print Network

Fault Detection and Elimination for Galileo-GPS Vertical Guidance Alexandru Ene, Juan Blanch, J focus is software simulation in the area of combined GPS/Galileo signals, positioning error threat space, such as Galileo and GPS block III, a series of new developments has taken place in the field of Receiver

Stanford University

166

Multiple Sensor Fault Detection in Heat Exchanger Systems  

E-print Network

Multiple Sensor Fault Detection in Heat Exchanger Systems Abdelwahab Aïtouche* , Didier Maquin strategy is presented for a heat exchanger system for which the process model consists of a set of linear equations, and can be found in heat exchangers. The increasing importance of heat exchangers in the industry

Paris-Sud XI, Université de

167

A neural network approach for the real-time detection of faults  

Microsoft Academic Search

Fault detection is an essential part of the operation of any chemical plant. Early detection of faults is important in chemical\\u000a industry since a lot of damage and loss can result before a fault present in the system is detected. Even though fault detection\\u000a algorithms are designed and implemented for quickly detecting incidents, most these algorithms do not have an

Yahya Chetouani

2008-01-01

168

Decomposition Methods for Fault Tree Analysis  

Microsoft Academic Search

Some kinds of fault tree analysis are described for which cut set enumeration is inadequate. Modularization leads to more efficient computer programs, and also identifies subsystems which are intuitively meaningful. The problem of finding all modules of a fault tree is formulated as as extension of the problem of finding all ``cut-points'' of an undirected graph. The major result is

Arnon Rosenthal

1980-01-01

169

Using Operating Deflection Shapes to Detect Faults in Rotating Equipment  

Microsoft Academic Search

\\u000a This paper is the third in a series where an operating deflection shape (ODS) is used as the means of detecting faults in\\u000a rotating machinery [1] [2]. In this paper, ODS comparison is used as a means of detecting unbalance and misalignment in a\\u000a rotating machine. Our purpose is to use significant changes in the ODS as an early warning

Arul Muthukumarasamy; Tom Wolff; Mark Richardson

170

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

NASA Technical Reports Server (NTRS)

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.

Tejada, Arturo

2009-01-01

171

Fault detection and bypass in a sequence information signal processor  

NASA Technical Reports Server (NTRS)

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.

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

1992-01-01

172

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

PubMed Central

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

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

2009-01-01

173

Probabilistic approaches to fault detection in networked discrete event systems.  

PubMed

In this paper, we consider distributed systems that can be modeled as finite state machines with known behavior under fault-free conditions, and we study the detection of a general class of faults that manifest themselves as permanent changes in the next-state transition functionality of the system. This scenario could arise in a variety of situations encountered in communication networks, including faults occurred due to design or implementation errors during the execution of communication protocols. In our approach, fault diagnosis is performed by an external observer/diagnoser that functions as a finite state machine and which has access to the input sequence applied to the system but has only limited access to the system state or output. In particular, we assume that the observer/diagnoser is only able to obtain partial information regarding the state of the given system at intermittent time intervals that are determined by certain synchronizing conditions between the system and the observer/diagnoser. By adopting a probabilistic framework, we analyze ways to optimally choose these synchronizing conditions and develop adaptive strategies that achieve a low probability of aliasing, i.e., a low probability that the external observer/diagnoser incorrectly declares the system as fault-free. An application of these ideas in the context of protocol testing/classification is provided as an example. PMID:16252815

Athanasopoulou, Eleftheria; Hadjicostis, Christoforos N

2005-09-01

174

Incipient fault detection study for advanced spacecraft systems  

NASA Technical Reports Server (NTRS)

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.

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

1986-01-01

175

Fault Detection and Isolation for Hydraulic Control  

NASA Technical Reports Server (NTRS)

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

1987-01-01

176

Real-time fault detection and isolation in biological wastewater treatment plants  

E-print Network

aspect in the domain of advanced control of Waste Water Treatment Plants (WWTP) (Olsson & Newell 1999 through the plant. In particular, Fault Detection and Isolation (FDI) tech- niques are now emerging, many popular FDI methods doi: 10.2166/wst.2009.723 2949 Q IWA Publishing 2009 Water Science

177

Shannon wavelet spectrum analysis on truncated vibration signals for machine incipient fault detection  

Microsoft Academic Search

Although a variety of methods have been proposed in the literature for machine fault detection, it still remains a challenge to extract prominent features from random and nonstationary vibratory signals, a typical representative of which are the resonance signatures generated by incipient defects on the rolling elements of ball bearings. Due to its random and nonstationary nature, the involved signal

Jie Liu

2012-01-01

178

IMPLEMENTION AND TESTING OF A FAULT DETECTION SOFTWARE TOOL FOR IMPROVING CONTROL SYSTEM  

E-print Network

IMPLEMENTION AND TESTING OF A FAULT DETECTION SOFTWARE TOOL FOR IMPROVING CONTROL SYSTEM detect faults in the controlled process. We present results from the first phase of tests being carried demonstrates that the proposed scheme can detect three important faults in the air-handling unit tested. 2

Diamond, Richard

179

Novel Fiber Bragg Grating sensor applicable for fault detection in high voltage transformers  

Microsoft Academic Search

In this paper, a fiber optic based sensor capable of fault detection in the high voltage transformers is investigated. Bragg wavelength shift is used to detect fault in power systems. Magnetic fields generated by fault currents in the transformer cause a strain in magnetostrictive material which is then detected by Fiber Bragg Grating (FBG). Fiber Bragg interrogator senses the reflected

Amin Moghadas; Mehdi Shadaram

2010-01-01

180

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

NASA Technical Reports Server (NTRS)

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.

Keesler, E. L.

1974-01-01

181

Development of Fault Detection System using Wavelength Division Multiplexing Transmission of Optical Fiber Current Sensor  

Microsoft Academic Search

A fault detection system is applied to power lines consisting of both overhead power line and underground power cable in order to detect a fault on the underground power cable section and prevent the automatic reclosing. The fault detection system using optical fiber current sensor has two subjects. The fist subject is that we have to use wound-type current transformer

Masahiro Kayaki; Toshinari Hirata; Kiyoshi Kurosawa; Reishi Kondo; Toshiharu Yamada; Eiji Itakura

2010-01-01

182

Seismic slip propagation along a fault in the Shimanto accretionary prism detected by vitrinite reflectance studies  

NASA Astrophysics Data System (ADS)

Quantitative assessment of heat generation along faults during fault movement is of primary importance in understanding the dynamics of earthquakes. Last several years localized heat anomaly in a fault zone due to rapid seismic sliding has been detected by various analyses of fault zone materials, such as ferromagnetic resonance signal (Fukuchi et al., 2005), trace elements and isotopes (e.g., Ishikawa et al., 2008) and mineralogical change of clay (e.g., Hirono et al., 2008) and vitrinite reflectance (O'Hara, 2004). Here we report a heat anomaly found in a fault zone in the Shimanto accretionary complex by vitrinite reflectance measurements. Mature faults in nature mostly experience multiple seismic events, resulting in integrated heat anomaly. Thus, in addition to vitrinite reflectance measurements across natural faults, we performed high-velocity friction experiments on a mixture of quartz and vitrinite grains to evaluate how multiple rapid-slip events affect vitrinite reflectance in a fault zone. A localized heat anomaly is found in one of fault zones which are developed within a mélange unit in the Cretaceous Shimanto belt, SW Japan. A principle slip zone with thickness of ~5 mm forms within cataclastic damage zone with thickness of ~3 m. The slip zone is mainly composed of well-foliated clay minerals. Host rocks are characterized by a block-in-matrix texture: aligned sandstone and chert blocks embedded in mudstone matrix. We measured vitrinite reflectance across the fault zone by the same method as reported in Sakaguchi et al., (2011). The measurement reveals that the principle slip zone underwent localized temperature of more than 220°C, while background temperature of both damage zone and host rocks is ~170°C. Since fault motion along most active faults occurs seismological, that inevitably generates frictional heat, the localized heat anomaly is possibly caused by the rapid seismic slip. In order to evaluate the change in vitrinite reflectance by coseismic sliding, we conducted friction experiments on a mixture of 90 wt% quartz and 10 wt% vitrinite at slip rates of 1.3 mm/s and 1.3 m/s, normal stress of 1.0 MPa and displacement of 15 m under anoxic, nitrogen atmosphere. A series of slide-hold-slide tests are also performed to reproduce multiple seismic-slip events. Our preliminary observation of recovered specimens indicated that significant heat anomaly, especially at shear localized zone in the simulated gouge zone, can be detected by vitrinite reflectance measurement. Detailed results will be reported in our presentation.

Kitamura, M.; Mukoyoshi, H.; Hirose, T.

2011-12-01

183

Inversion method of seismic forces at fault using finite element  

NASA Astrophysics Data System (ADS)

Fault slip inversion using seismic dislocation model has been discussed a lot. In this model, seismogenic fault is considered as an interface. However, geological surveys and seismic channel waves reveal that the fault usually possesses thickness. Rock compression tests also show that micro-cracks develop into a belt in which shear fracture plane takes place. Therefore, to simulate the fault as a narrow belt may be more reasonable to reflect mechanical behavior of earthquake source. This study proposes a method to inverse seismic forces at the fault with thickness. The fault is modeled by transversely isotropic material. Three-dimensional finite element models (FEMs) is used to calculate numerical Green's functions for displacements. The Green's functions are generated by imposing unit couples directly to the node pairs at the fault instead of dislocation. The unit couples are added separately in x, y, z directions of the finite element global coordinate system. A pure thrust earthquake is modeled by reducing shear modulus under tectonic stress field. Selected surface displacements induced by this earthquake are used as 'observation data' of the inversion. We combine numerical Green's functions with standard linear inverse methods with Laplace smoothing constraints to estimate seismic forces at the fault. The earthquake which is simulated by damage of shear modulus has the fault model with transversely isotropic material, therefore there exist no normal forces. When the fault material is isotropic and the earthquake is caused by the reduction of shear or Young's modulus, there are normal forces at the fault. This study shows that we can directly inverse three-dimensional seismic forces with the surface deformation caused by earthquakes. This method is feasible for heterogeneous materials and complicated geometry model. [1] Xie, Zhoumin, Inversion method of seismic stress drop by finite element scheme, Doctor Thesis, Peking University, 2013. [2] Hu, C., Zhou, Y., & Cai, Y., A new finite element model in studying earthquake triggering and continuous evolution of stress field, Science in China Series D: Earth Sciences, 2009

Liu, D.; Xie, Z.; Geng, W.; Cai, Y.

2013-12-01

184

Crustal deformation detected by GPS observation network across the Sumatran fault system in northwestern Sumatra, Indonesia  

NASA Astrophysics Data System (ADS)

We have deployed Aceh GPS network for the Sumatran fault system (AGNeSS) in the northwestern part of Sumatra Island, Indonesia to evaluate regional earthquake generation potential in parallel to the decaying process of postseismic deformation after the 2004 Sumatra-Andaman earthquake (Mw 9.2). The AGNeSS consists of seven continuous and 17 campaign sites deployed mostly along two main roads spanning approximately 200 km x 200 km area across the fault. Using horizontal displacement data up to 2010, we detected postseismic deformation exceeding 80 cm in about five years after the 2004 event and also inferred shallow creep/locking distribution along the Sumatran fault (Ito et al., 2012). On January 22 and July 2, 2013 two M6.1 earthquakes occurred in the AGNeSS. Hypocenter location and mechanism of the first earthquake strongly suggest a right-lateral strike-slip event on the NW-SE trending Sumatran fault. The second earthquake occurred when GPS campaign observation was being conducted in the vicinity of the source region. While the epicenter is about 25 km departed from the main trace of the Sumatran fault, source mechanism is very similar to that of the first one. However, coseismic displacement field from the nearby GPS sites clearly show a left-lateral strike-slip motion on a NE-SW trending fault plane. So far no evidence has been obtained that supports the existence of conjugate faults that are perpendicular to the Sumatran fault system. We are planning to conduct supplementary geomorphologic survey and microearthquake observation. Preliminary results of fault parameter estimation using a Markov Chain Monte Carlo method are very consistent with the observations.

Tabei, T.; Ito, T.; Kimata, F.; Ohta, Y.; Gunawan, E.; Ismail, N.; Sugiyanto, D.; Nurdin, I.

2013-12-01

185

Fault Diagnosis of Bearing Based on Fractal Method  

Microsoft Academic Search

Fractal geometry is a new method to apply in analyzing fault signals. After researching the characteristic of rolling bearings, a new quantificational definition about fault signals of rolling bearings is proposed. Based on fractal theory and the conception of box dimension it can describe both non-stationary and non-linear signals of vibration signals generated by rolling bearings. Experiment results shows that

Lu Shuang; Liu Jing

2006-01-01

186

Interval methods for fault-tree analysis in robotics  

Microsoft Academic Search

This paper describes a novel technique, based on interval methods, for estimating reliability using fault trees. The approach encodes inherent uncertainty in the input data by modeling these data in terms of intervals. Appropriate interval arithmetic is then used to propagate the data through standard fault trees to generate output distributions which reflect the uncertainty in the input data. Through

Carlos Carreras; Ian D. Walker

2001-01-01

187

Dynamic Structural Fault Detection and Identification  

NASA Technical Reports Server (NTRS)

Aircraft structures are designed to guarantee safety of flight in some required operational envelope. When the aircraft becomes structurally impaired, safety of flight may not be guaranteed within that previously safe operational envelope. In this case the safe operational envelope must be redefined in-flight and a means to prevent excursion from this new envelope must be implemented. A specific structural failure mode that may result in a reduced safe operating envelope, the exceedance of which could lead to catastrophic structural failure of the aircraft, will be addressed. The goal of the DFEAP program is the detection of this failure mode coupled with flight controls adaptation to limit critical loads in the damaged aircraft structure. The DFEAP program is working with an F/A-18 aircraft model. The composite wing skins are bonded to metallic spars in the wing substructure. Over time, it is possible that this bonding can deteriorate due to fatigue. In this case, the ability of the wing spar to transfer loading between the wing skins is reduced. This failure mode can translate to a reduced allowable compressive strain on the wing skin and could lead to catastrophic wing buckling if load limiting of the wing structure is not applied. The DFEAP program will make use of a simplified wing strain model for the healthy aircraft. The outputs of this model will be compared in real-time to onboard strain measurements at several locations on the aircraft wing. A damage condition is declared at a given location when the strain measurements differ sufficiently from the strain model. Parameter identification of the damaged structure wing strain parameters will be employed to provide load limiting control adaptation for the aircraft. This paper will discuss the simplified strain models used in the implementation and their interaction with the strain sensor measurements. Also discussed will be the damage detection and identification schemes employed and the means by which the damaged aircraft parameters will be used to provide load limiting that keeps the aircraft within the safe operational envelope.

Smith, Timothy; Reichenbach, Eric; Urnes, James M.

2009-01-01

188

Bearing fault detection in induction motor using pattern recognition techniques  

Microsoft Academic Search

In this paper a procedure based on pattern recognition technique is presented for fault diagnosis of rolling element bearings through artificial neural networks (ANN). The artificial neural networks are trained with a subset of the experimental data for known machine conditions. The networks are tested using the remaining set of data. In this method the characteristic features of time and

J. Zarei; J. Poshtan; M. Poshtan

2008-01-01

189

Detection of High-Impedance Arcing Faults in Radial Distribution DC Systems  

NASA Technical Reports Server (NTRS)

High voltage, low current arcing faults in DC power systems have been researched at the NASA Glenn Research Center in order to develop a method for detecting these 'hidden faults', in-situ, before damage to cables and components from localized heating can occur. A simple arc generator was built and high-speed and low-speed monitoring of the voltage and current waveforms, respectively, has shown that these high impedance faults produce a significant increase in high frequency content in the DC bus voltage and low frequency content in the DC system current. Based on these observations, an algorithm was developed using a high-speed data acquisition system that was able to accurately detect high impedance arcing events induced in a single-line system based on the frequency content of the DC bus voltage or the system current. Next, a multi-line, radial distribution system was researched to see if the arc location could be determined through the voltage information when multiple 'detectors' are present in the system. It was shown that a small, passive LC filter was sufficient to reliably isolate the fault to a single line in a multi-line distribution system. Of course, no modification is necessary if only the current information is used to locate the arc. However, data shows that it might be necessary to monitor both the system current and bus voltage to improve the chances of detecting and locating high impedance arcing faults

Gonzalez, Marcelo C.; Button, Robert M.

2003-01-01

190

Detection of High-impedance Arcing Faults in Radial Distribution DC Systems  

NASA Technical Reports Server (NTRS)

High voltage, low current arcing faults in DC power systems have been researched at the NASA Glenn Research Center in order to develop a method for detecting these 'hidden faults', in-situ, before damage to cables and components from localized heating can occur. A simple arc generator was built and high-speed and low-speed monitoring of the voltage and current waveforms, respectively, has shown that these high impedance faults produce a significant increase in high frequency content in the DC bus voltage and low frequency content in the DC system current. Based on these observations, an algorithm was developed using a high-speed data acquisition system that was able to accurately detect high impedance arcing events induced in a single-line system based on the frequency content of the DC bus voltage or the system current. Next, a multi-line, radial distribution system was researched to see if the arc location could be determined through the voltage information when multiple 'detectors' are present in the system. It was shown that a small, passive LC filter was sufficient to reliably isolate the fault to a single line in a multi-line distribution system. Of course, no modification is necessary if only the current information is used to locate the arc. However, data shows that it might be necessary to monitor both the system current and bus voltage to improve the chances of detecting and locating high impedance arcing faults

Gonzalez, Marcelo C.; Button, Robert M.

2003-01-01

191

Fault detection of multivariable system using its directional properties  

E-print Network

properties of the MIMO systems such as the transmission zeros, input zero direction, output zero direction etc was utilized. Neither were the directional properties of MIMO systems utilized in the various previously developed popular fault detection... Invariant Zeros System Zeros 13 However throughout this present work the zeros refer to transmission zero satisfying the definitions provided by the MacFarlane and Karcanias in 1976. One fundamental difference between SISO and the MIMO system...

Pandey, Amit Nath

2006-04-12

192

Detection of stator core faults in large turbo-generators  

Microsoft Academic Search

Many large turbo-generators today are now operating beyond their design lifetime, with careful condition-based maintenance and operation having extended their life expectancy. Monitoring the health of large turbo-generators is now an integral part of their operation. This paper describes the use of non-invasive electromagnetic sensors to detect core inter-lamination insulation faults in the stator cores of large turbo-generators before they

A. C. Smith; D. Bertenshaw; C. W. Ho; T. Chan; M. Sasic

2009-01-01

193

Fault detection based on fractional order models: Application to diagnosis of thermal systems  

NASA Astrophysics Data System (ADS)

The aim of this paper is to propose diagnosis methods based on fractional order models and to validate their efficiency to detect faults occurring in thermal systems. Indeed, it is first shown that fractional operator allows to derive in a straightforward way fractional models for thermal phenomena. In order to apply classical diagnosis methods, such models could be approximated by integer order models, but at the expense of much higher involved parameters and reduced precision. Thus, two diagnosis methods initially developed for integer order models are here extended to handle fractional order models. The first one is the generalized dynamic parity space method and the second one is the Luenberger diagnosis observer. Proposed methods are then applied to a single-input multi-output thermal testing bench and demonstrate the methods efficiency for detecting faults affecting thermal systems.

Aribi, Asma; Farges, Christophe; Aoun, Mohamed; Melchior, Pierre; Najar, Slaheddine; Abdelkrim, Mohamed Naceur

2014-10-01

194

Two Trees: Migrating Fault Trees to Decision Trees for Real Time Fault Detection on International Space Station  

NASA Technical Reports Server (NTRS)

We started from ISS fault trees example to migrate to decision trees, presented a method to convert fault trees to decision trees. The method shows that the visualizations of root cause of fault are easier and the tree manipulating becomes more programmatic via available decision tree programs. The visualization of decision trees for the diagnostic shows a format of straight forward and easy understands. For ISS real time fault diagnostic, the status of the systems could be shown by mining the signals through the trees and see where it stops at. The other advantage to use decision trees is that the trees can learn the fault patterns and predict the future fault from the historic data. The learning is not only on the static data sets but also can be online, through accumulating the real time data sets, the decision trees can gain and store faults patterns in the trees and recognize them when they come.

Lee, Charles; Alena, Richard L.; Robinson, Peter

2004-01-01

195

Marketability requirements for fault detection and diagnostics in commercial buildings  

SciTech Connect

Fault Detection and Diagnostics (FDD) is a technology that has a great potential for improving performance and reducing energy consumed in commercial buildings, and is rapidly becoming feasible for the buildings sector. Scientists have developed algorithms for FDD, and are making plans for field-testing and demonstration of these methods in real buildings. These efforts will provide a sound technical basis for FDD product offerings. FDD has the potential to dramatically improve the quality of operation of buildings. However, progress on technical issues is only one step towards implementing FDD in the market. FDD cannot be expected to have a major impact on buildings unless market issues are addressed. Many questions will have to be answered regarding the users of FDD systems, the usability of the product, the market for FDD, and the nature of possible FDD offerings. It is crucial to consider marketing issues in parallel with the more technical issues. Constraints and opportunities that will be faced in marketing the products must be recognized early in technology development, and addressed and integrated into designs to ensure an appropriate system design. This paper identified a number of key questions that will arise in addressing marketability issues. These questions will have to be answered individually by technology developers and entities intending to market FDD. This paper presents some of the considerations that must go into the answering the questions, and provides a framework for analyzing the market requirements.

Heinemeier, K.H.

1998-07-01

196

Sensor configuration and test for fault diagnoses of subway braking system based on signed digraph method  

NASA Astrophysics Data System (ADS)

Fault diagnosis of various systems on rolling stock has drawn the attention of many researchers. However, obtaining an optimized sensor set of these systems, which is a prerequisite for fault diagnosis, remains a major challenge. Available literature suggests that the configuration of sensors in these systems is presently dependent on the knowledge and engineering experiences of designers, which may lead to insufficient or redundant development of various sensors. In this paper, the optimization of sensor sets is addressed by using the signed digraph (SDG) method. The method is modified for use in braking systems by the introduction of an effect-function method to replace the traditional quantitative methods. Two criteria are adopted to evaluate the capability of the sensor sets, namely, observability and resolution. The sensors configuration method of braking system is proposed. It consists of generating bipartite graphs from SDG models and then solving the set cover problem using a greedy algorithm. To demonstrate the improvement, the sensor configuration of the HP2008 braking system is investigated and fault diagnosis on a test bench is performed. The test results show that SDG algorithm can improve single-fault resolution from 6 faults to 10 faults, and with additional four brake cylinder pressure (BCP) sensors it can cover up to 67 double faults which were not considered by traditional fault diagnosis system. SDG methods are suitable for reducing redundant sensors and that the sensor sets thereby obtained are capable of detecting typical faults, such as the failure of a release valve. This study investigates the formal extension of the SDG method to the sensor configuration of braking system, as well as the adaptation supported by the effect-function method.

Zuo, Jianyong; Chen, Zhongkai

2014-05-01

197

Design methods for fault-tolerant finite state machines  

NASA Technical Reports Server (NTRS)

VLSI electronic circuits are increasingly being used in space-borne applications where high levels of radiation may induce faults, known as single event upsets. In this paper we review the classical methods of designing fault tolerant digital systems, with an emphasis on those methods which are particularly suitable for VLSI-implementation of finite state machines. Four methods are presented and will be compared in terms of design complexity, circuit size, and estimated circuit delay.

Niranjan, Shailesh; Frenzel, James F.

1993-01-01

198

Application of fault detection techniques to spiral bevel gear fatigue data  

NASA Astrophysics Data System (ADS)

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.

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

1994-01-01

199

Adaptive observers based fault detection and isolation for an alcoholic fermentation process  

Microsoft Academic Search

The paper deals with fault detection and isolation in an alcoholic fermentation process. The dynamics involved are nonlinear and the faults are modelled as changes in the system parameters. The fault detection scheme requires combined state and parameter estimation. For this purpose a model reference based estimator is used to develop adaptive observers

N. Kabbaj; M. Polit; B. Dahhou; G. Roux

2001-01-01

200

Fundamental Fault Detection Limitations in Linear Non-Gaussian Systems Gustaf Hendeby  

E-print Network

Fundamental Fault Detection Limitations in Linear Non-Gaussian Systems Gustaf Hendeby Division Linköpings universitet, SE-581 83 Linköping, SWEDEN fredrik@isy.liu.se Abstract-- Sophisticated fault detection (FD) algorithms often include nonlinear mappings of observed data to fault decisions

Gustafsson, Fredrik

201

Sensor Analysis for Fault Detection in Tightly-Coupled Multi-Robot Team Tasks  

Microsoft Academic Search

This paper presents a sensor analysis based fault detection approach (which we call SAFDetection) that is used to monitor tightly-coupled multi-robot team tasks. Our approach aims at detecting both physical and logic faults of a robot system with little prior knowledge on the system. We do not need the motion model or a priori knowledge of the possible fault types

Xingyan Li; Lynne E. Parker

2007-01-01

202

Current\\/Voltage-Based Detection of Faults in Gears Coupled to Electric Motors  

Microsoft Academic Search

Gears form a critical part of many electromechanical systems. Since gear faults cause vibrations, and vibration-based diagnostics are very reliable, this has traditionally been the most commonly used approach to detecting gear faults. However, it is expensive due to the use of high-priced accelerometers and sensor wiring. This paper proposes an alternative way of detecting faults in gears coupled to

Satish Rajagopalan; Thomas G. Habetler; Ronald G. Harley; Tomy Sebastian; Bruno Lequesne

2006-01-01

203

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

NASA Technical Reports Server (NTRS)

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.

Hanson, Matt

1990-01-01

204

Detecting tangential dislocations on planar faults from traction free surface observations  

NASA Astrophysics Data System (ADS)

We propose in this paper robust reconstruction methods for tangential dislocations on planar faults. We assume that only surface observations are available, and that a traction free condition applies at that surface. This study is an extension to the full three dimensions of Ionescu and Volkov (2006 Inverse Problems 22 2103). We also explore in this present paper the possibility of detecting slow slip events (such as silent earthquakes, or earthquake nucleation phases) from GPS observations. Our study uses extensively an asymptotic estimate for the observed surface displacement. This estimate is first used to derive what we call the moments reconstruction method. Then it is also used for finding necessary conditions for a surface displacement field to have been caused by a slip on a fault. These conditions lead to the introduction of two parameters: the activation factor and the confidence index. They can be computed from the surface observations in a robust fashion. They indicate whether a measured displacement field is due to an active fault. We also infer a second, combined, reconstruction technique blending least square minimization and the moments method. We carefully assess how our reconstruction method is affected by the sensitivity of the observation apparatus and the stepsize for the grid of surface observation points. The maximum permissible stepsize for such a grid is computed for different values of fault depth and orientation. Finally we present numerical examples of reconstruction of faults. We demonstrate that our combined method is sharp, robust and computationally inexpensive. We also note that this method performs satisfactorily for shallow faults, despite the fact that our asymptotic formula deteriorates in that case.

Ionescu, Ioan R.; Volkov, Darko

2009-01-01

205

Latest Progress of Fault Detection and Localization in Complex Electrical Engineering  

NASA Astrophysics Data System (ADS)

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.

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

2014-01-01

206

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

NASA Technical Reports Server (NTRS)

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.

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

2010-01-01

207

Exact Computation of Maximally Dominating Faults and Its Application to -Detection Tests  

E-print Network

Exact Computation of Maximally Dominating Faults and Its Application to -Detection Tests Ilia, IN 47907, USA Abstract £ -detection test sets for stuck-at faults have been shown to be useful in detecting an important role in controlling the increase in the size of an £ -detection test set as £ is increased

Polian, Ilia

208

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

PubMed

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. PMID:23145702

Tafinine, Farid; Mokrani, Karim

2012-11-01

209

Hidden Markov models for fault detection in dynamic systems  

NASA Technical Reports Server (NTRS)

The invention is a system failure monitoring method and apparatus which learns the symptom-fault mapping directly from training data. The invention first estimates the state of the system at discrete intervals in time. A feature vector x of dimension k is estimated from sets of successive windows of sensor data. A pattern recognition component then models the instantaneous estimate of the posterior class probability given the features, p(w(sub i) (vertical bar)/x), 1 less than or equal to i isless than or equal to m. Finally, a hidden Markov model is used to take advantage of temporal context and estimate class probabilities conditioned on recent past history. In this hierarchical pattern of information flow, the time series data is transformed and mapped into a categorical representation (the fault classes) and integrated over time to enable robust decision-making.

Smyth, Padhraic J. (inventor)

1995-01-01

210

Detecting Intra-Word Faults in Word-Oriented Memories Said Hamdioui  

E-print Network

the existence of many new coupling faults [2, 4]. In [5] the transformation of BOM tests into WOM tests has beenDetecting Intra-Word Faults in Word-Oriented Memories Said Hamdioui½ ¾ Ad J. van de Goor¾ Mike of the art in testing word oriented memories. It first presents a complete set of fault models for intra

Kuzmanov, Georgi

211

Wavelet Decomposition for the Detection and Diagnosis of Faults in Rolling Element Bearings  

Microsoft Academic Search

Condition monitoring and fault diagnosis of equipment and processes are of great concern in industries. Early fault detection in machineries can save millions of dollars in emergency maintenance costs. This paper presents a wavelet-based analysis technique for the diagnosis of faults in rotating machinery from its mechanical vibrations. The choice between the discrete wavelet transform and the discrete wavelet packet

J. Chebil; G. Noel; M. Mesbah; M. Deriche

2009-01-01

212

Cause-Effect Analysis for Multiple Fault Detection in Combinational Networks  

Microsoft Academic Search

The important problem of generating test patterns to detect multiple faults has received little attention, mainly due to their computational complexity. The theoretical results of this paper show that near minimal tests for multiple faults can be generated with complexity of computation comparable to that of single faults.

D. C. Bossen; Se June Hong

1971-01-01

213

Limitations for detecting small-scale faults using the coherency analysis of seismic data  

E-print Network

%. Therefore, this study suggests that coherency has the ability to detect a fault as long as the frequency of the data imaging that fault has a period no greater than one order of magnitude to the traveltime through the fault and that the signal can easily...

Barnett, David Benjamin

2006-08-16

214

Sensor Analysis for Fault Detection in Tightly-Coupled Multi-Robot Team Tasks  

E-print Network

transitions from a history of sensor data during the normal operational mode of the robot. FaultsSensor Analysis for Fault Detection in Tightly-Coupled Multi-Robot Team Tasks Xingyan Li and Lynne on Robotics and Automation, Rome, Italy, 2007. Abstract-- This paper presents a sensor analysis based fault

Parker, Lynne E.

215

OPEN ACCESS Detection of Fault Location in Transmission Lines using Wavelet Transform  

E-print Network

Abstract-This paper presents a technique to detect the location of the different faults on a transmission lines for quick and reliable operation of protection schemes. The simulation is developed in MATLAB to generate the fundamental component of the transient voltage and current simultaneously both in time and frequency domain. One cycle of waveform, covering pre-fault and post-fault information is abstracted for analysis. The discrete wavelet transform (DWT) is used for data preprocessing. It is applied for decomposition of fault transients, because of its ability to extract information from the transient signal, simultaneously both in time and frequency domain. MATLAB software is used to simulate different operating and fault conditions on high voltage transmission line, namely single phase to ground fault, line to line fault, double line to ground and three phase short circuit. Keywords- Simulink, Transmission line Fault Detection, Wavelet, Discrete Wavelet Transform, I.

Shilpi Sahu (m. E. Student

216

Understanding Vibration Spectra of Planetary Gear Systems for Fault Detection  

NASA Technical Reports Server (NTRS)

An understanding of the vibration spectra is very useful for any gear fault detection scheme based upon vibration measurements. The vibration measured from planetary gears is complicated. Sternfeld noted the presence of sidebands about the gear mesh harmonics spaced at the planet passage frequency in spectra measured near the ring gear of a CH-47 helicopter. McFadden proposes a simple model of the vibration transmission that predicts high spectral amplitudes at multiples of the planet passage frequency, for planetary gears with evenly spaced planets. This model correctly predicts no strong signal at the meshing frequency when the number of teeth on the ring gear is not an integer multiple of the number of planets. This paper will describe a model for planetary gear vibration spectra developed from the ideas started in reference. This model predicts vibration to occur only at frequencies that are multiples of the planet repetition passage frequency and clustered around gear mesh harmonics. Vibration measurements will be shown from tri-axial accelerometers mounted on three different planetary gear systems and compared with the model. The model correctly predicts the frequencies with large components around the first several gear mesh harmonics in measurements for systems with uniformly and nonuniformly spaced planet gears. Measurements do not confirm some of the more detailed features predicted by the model. Discrepancies of the ideal model to the measurements are believed due to simplifications in the model and will be discussed. Fault detection will be discussed applying the understanding will be discussed.

Mosher, Marianne

2003-01-01

217

GLRT Based Fault Detection in Sensor Drift Monitoring System  

NASA Astrophysics Data System (ADS)

In a nuclear power plant (NPP), periodic sensor calibrations are required to assure sensors are operating correctly. However, only a few faulty sensors are found to be calibrated. For the safe operation of an NPP and the reduction of unnecessary calibration, on-line calibration monitoring is needed. This paper presents an on-line sensor drift monitoring technique, based on a Generalized Likelihood Ratio Test (GLRT), for detecting and estimating mean shifts in sensor signal. Also, principal component-based Auto-Associative support vector regression (AASVR) is proposed for the sensor signal validation of the NPP. Response surface methodology (RSM) is employed to efficiently determine the optimal values of SVR hyperparameters. The proposed model was confirmed with actual plant data of Kori NPP Unit 3. The results show that the accuracy of the model and the fault detection performance of the GLRT are very competitive.

Seo, In-Yong; Shin, Ho-Cheol; Park, Moon-Ghu; Kim, Seong-Jun

218

A Fault Diagnosis Method of Rolling Bearings Using Empirical Mode Decomposition and Hidden Markov Model  

Microsoft Academic Search

This paper describes a new approach to detect localized rolling bearing defects based on empirical mode decomposition (EMD) and hidden Markov model (HMM). In view of the non-stationary characteristics of bearing fault vibration signals, using EMD method, the original non-stationary vibration signal can be decomposed into a finite number of stationary signals. The stationary signal adapts itself better to the

Bin Wu; Changjian Feng; Minjie Wang

2006-01-01

219

Improving Model-Based Gas Turbine Fault Diagnosis Using Multi-Operating Point Method  

Microsoft Academic Search

A comprehensive gas turbine fault diagnosis system has been designed using a full nonlinear simulator developed in Turbotec company for the V94.2 industrial gas turbine manufactured by Siemens AG. The methods used for detection and isolation of faulty components are gas path analysis (GPA) and extended Kalman filter (EKF). In this paper, the main health parameter degradations namely efficiency and

Amin Salar; SeyedMehrdad Hosseini; Ali Khaki Sedigh; Behnam Rezaei Zangmolk

2010-01-01

220

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

NASA Technical Reports Server (NTRS)

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.

Keesler, E. L.

1974-01-01

221

Planetary gearbox fault diagnosis using an adaptive stochastic resonance method  

NASA Astrophysics Data System (ADS)

Planetary gearboxes are widely used in aerospace, automotive and heavy industry applications due to their large transmission ratio, strong load-bearing capacity and high transmission efficiency. The tough operation conditions of heavy duty and intensive impact load may cause gear tooth damage such as fatigue crack and teeth missed etc. The challenging issues in fault diagnosis of planetary gearboxes include selection of sensitive measurement locations, investigation of vibration transmission paths and weak feature extraction. One of them is how to effectively discover the weak characteristics from noisy signals of faulty components in planetary gearboxes. To address the issue in fault diagnosis of planetary gearboxes, an adaptive stochastic resonance (ASR) method is proposed in this paper. The ASR method utilizes the optimization ability of ant colony algorithms and adaptively realizes the optimal stochastic resonance system matching input signals. Using the ASR method, the noise may be weakened and weak characteristics highlighted, and therefore the faults can be diagnosed accurately. A planetary gearbox test rig is established and experiments with sun gear faults including a chipped tooth and a missing tooth are conducted. And the vibration signals are collected under the loaded condition and various motor speeds. The proposed method is used to process the collected signals and the results of feature extraction and fault diagnosis demonstrate its effectiveness.

Lei, Yaguo; Han, Dong; Lin, Jing; He, Zhengjia

2013-07-01

222

Failure detection and fault management techniques for flush airdata sensing systems  

NASA Technical Reports Server (NTRS)

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.

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

1992-01-01

223

Fault detection of planetary gearboxes using new diagnostic parameters  

NASA Astrophysics Data System (ADS)

Planetary gearboxes are commonly used in modern industry because of their large transmission ratio and strong load-bearing capacity. They generally work under heavy load and tough working environment and therefore their key components including sun gear, planet gears, ring gear, etc are subject to severe pitting and fatigue crack. Planetary gearboxes significantly differ from fixed-axis gearboxes and exhibit unique behavior, which invalidates the use of the diagnostic parameters developed and suitable for fixed-axis gearboxes. Therefore, there is a need to develop parameters specifically for detecting and diagnosing faults of planetary gearboxes. In this study, two diagnostic parameters are proposed based on the examination of the vibration characteristics of planetary gearboxes in both time and frequency domains. One is the root mean square of the filtered signal (FRMS) and the other is the normalized summation of positive amplitudes of the difference spectrum between the unknown signal and the healthy signal (NSDS). To test the proposed diagnostic parameters, we conducted experiments on a planetary gearbox test rig with sun gear faults including a cracked tooth and a pitted tooth. The vibration signals were measured under different motor speeds. The proposed parameters are compared with the existing parameters reported in the literature. The comparison results show the proposed diagnostic parameters perform better than others.

Lei, Yaguo; Kong, Detong; Lin, Jing; Zuo, Ming J.

2012-05-01

224

A real-time fault diagnosis method of SACS based on combination of offline identification and online observing  

NASA Astrophysics Data System (ADS)

A novel fault diagnosis method based on the combination of offline identification and online observing is proposed in this paper, which can meet the requirement of both model complexity and real-time need for the satellite attitude control system. Accurate neural network models, both normal mode and faulty mode, can be obtained by off-line identification based on the data of fault simulation in different fault modes. With a parallel estimator derived from all models With all, fault determination based on threshold logic is designed for online fault detecting and isolating. Real-time simulation results, on the embedded fault simulation platform of satellite attitude control system, illustrate the effectiveness and superiority.

Cen, Zhao-Hui; Wei, Jiao-Long; Jiang, Rui; Liu, Xiong

2009-12-01

225

Gyro-based Maximum-Likelihood Thruster Fault Detection and Identification  

NASA Technical Reports Server (NTRS)

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,

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

2002-01-01

226

CARRIJO, TONICELLI AND NASCIMENTO 1 A Fault Analytic Method against HB+  

E-print Network

method against a prominent member of the HB-family: HB+ protocol. We demonstrate that the fault analysisCARRIJO, TONICELLI AND NASCIMENTO 1 A Fault Analytic Method against HB+ Jos´e Carrijo, Rafael of fault analysis over them. The purpose of this paper is to fill this gap by presenting a fault analytic

227

Nonlinear observer for signal and parameter fault detection in ship propulsion control  

Microsoft Academic Search

This chapter has analyzed fault detection and isolation, and re-configuration possibilities for a ship propulsion system with\\u000a a main engine and a controllable pitch propeller: It was demonstrated how fault-tolerance could be achieved against critical\\u000a sensor failure and cylinder malfunction of the prime mover engine. A non-linear adaptive observer was designed for fault detection\\u000a and re-configuration, and filters for efficient

Mogens Blanke; Roozbeh Izadi-Zamanabadi

228

Current\\/Voltage Based Detection of Faults in Gears Coupled to Electric Motors  

Microsoft Academic Search

Gears form a critical part of many electro-mechanical systems. Since gear faults cause vibrations, and vibration-based diagnostics is very reliable, this has traditionally been the most commonly used approach to detecting gear faults. However, it is expensive due to the use of high-priced accelerometers and sensor wiring. This paper proposes an alternative way of detecting faults in gears coupled to

S. Rajagopalan; T. G. Habetler; R. G. Harley; T. Sebastian; B. Lequesne

2005-01-01

229

Accumulation-based concurrent fault detection for linear digital state variable systems  

Microsoft Academic Search

An algorithmic fault detection scheme for linear digital state variable systems is proposed. The proposed scheme eliminates the necessity of observing the internal states of the system for concurrent fault detection by utilizing an accumulation-based approach. Observation merely of the inputs and the outputs results in significantly reduced area overhead and no performance penalty. Experimental re- sults verify that 100%

Ismet Bayraktaroglu; Alex Orailoglu

2000-01-01

230

FAULT DETECTION AND STATE EVALUATION OF ROTOR BLADES Yuri Petryna, Andreas Knzel, Matthias Kannenberg  

E-print Network

FAULT DETECTION AND STATE EVALUATION OF ROTOR BLADES Yuri Petryna, Andreas K�nzel, Matthias an approach for cost-effective, serial integrity tests of rotor blades. At that, manufacturing faults shall be automatically detected, localized and assessed with respect to their impact on the integrity of rotor blades

Boyer, Edmond

231

ROBUST FAULT DETECTION BASED ON MULTIPLE FUNCTIONAL SERIES TAR MODELS FOR STRUCTURES WITH TIME-DEPENDENT  

E-print Network

, analyzed and compared within the problem of vibration based fault detection on operating wind turbines-stationarity, uncertain operating conditions, functional series TARMA, fault detection. INTRODUCTION Vibration for engineering structures based on the features of the vibration response signals measured along the structure

Boyer, Edmond

232

Inchoate Fault Detection Framework: Adaptive Selection of Wavelet Nodes and Cumulant Orders  

Microsoft Academic Search

Inchoate fault detection for machine health monitoring (MHM) demands high level of fault classification accuracy under poor signal-to-noise ratio (SNR) which persists in most industrial environment. Vibration signals are extensively used in signature matching for abnormality detection and diagnosis. In order to guarantee improved performance under poor SNR, feature extraction based on statistical parameters which are immune to Gaussian noise

M. F. Yaqub; Iqbal Gondal; Joarder Kamruzzaman

2012-01-01

233

FAULT DETECTION IN HVAC SYSTEMS USING MODEL-BASED FEEDFORWARD CONTROL  

E-print Network

1 FAULT DETECTION IN HVAC SYSTEMS USING MODEL- BASED FEEDFORWARD CONTROL T. I. Salsbury, Ph.D. R. C how a model-based, feedforward control scheme can improve control performance over traditional PID and detect faults in the controlled process. The scheme uses static simulation models of the system under

Diamond, Richard

234

A hybrid approach for detecting and isolating faults in nuclear power plant interacting systems  

Microsoft Academic Search

A fault detection and isolation (FDI) system is presented that can detect and isolate nuclear power plant (NPP) faults occurring in interacting systems. The proposed methodology combines two tools, observer-based residual generation and neural network pattern matching, into a powerful, hybrid diagnostic system. A computer-based model of a commercial boiling water reactor (BWR) is used as the reference plant. Two

J. Wesley Hines; Don W. Miller; Brian K. Hajek

1996-01-01

235

A Comparative Study of Time-Frequency Representations for Fault Detection in Wind Turbine  

E-print Network

A Comparative Study of Time-Frequency Representations for Fault Detection in Wind Turbine El of wind energy, minimization and prediction of maintenance operations in wind turbine is of key importance and the easiness of interpretation. Index Terms--Wind turbine, fault detection, broken-rotor bars, signal

Paris-Sud XI, Université de

236

New Dynamic Model-Based Fault Detection Thresholds for Robot Manipulators  

Microsoft Academic Search

Autonomous robotic fault detection is becoming increasingly important as robots are used in more inaccessible and hazardous environments. Detection algorithms, however, are adversely effected by the model simplification, parameter uncertainty, and computational inaccuracy inherent in robotic control, leading to an unacceptable number of false alarms and overzealous fault tolerance. The algorithms must use thresholds to mask out these errors. Typically,

M. L. Visinsky; Ian D. Walker; Joseph R. Cavallaro

1994-01-01

237

Fault detection of large scale wind turbine systems: A mixed H?\\/H? index observer approach  

Microsoft Academic Search

This paper addresses the fault detection issue of large scale wind turbine systems. The underlying problem is very critical to enhance the reliability and reduce the cost of maintenance of wind turbines. In this work, mixed Hinfin\\/H- index observer is utilized to generate the residual for fault detection purpose. The employed observer is optimal in the sense that it is

Xiukun Wei; Michel Verhaegen

2008-01-01

238

A feature extraction method based on information theory for fault diagnosis of reciprocating machinery.  

PubMed

This paper proposes a feature extraction method based on information theory for fault diagnosis of reciprocating machinery. A method to obtain symptom parameter waves is defined in the time domain using the vibration signals, and an information wave is presented based on information theory, using the symptom parameter waves. A new way to determine the difference spectrum of envelope information waves is also derived, by which the feature spectrum can be extracted clearly and machine faults can be effectively differentiated. This paper also compares the proposed method with the conventional Hilbert-transform-based envelope detection and with a wavelet analysis technique. Practical examples of diagnosis for a rolling element bearing used in a diesel engine are provided to verify the effectiveness of the proposed method. The verification results show that the bearing faults that typically occur in rolling element bearings, such as outer-race, inner-race, and roller defects, can be effectively identified by the proposed method, while these bearing faults are difficult to detect using either of the other techniques it was compared to. PMID:22574021

Wang, Huaqing; Chen, Peng

2009-01-01

239

A new hybrid method for fault tree analysis  

Microsoft Academic Search

This paper describes a new method for determining the significant minimal cut sets of complex fault trees. It can be classified as hybrid, being based on the application of both Top Down and Bottom Up reduction approaches. This solution has been adopted particularly to accurately estimate the truncation error when the probabilistic cut-off technique is applied. Experimental results on real

S. Contini

1995-01-01

240

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

PubMed

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

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

2014-01-01

241

A compound fault diagnosis for rolling bearings method based on blind source separation and ensemble empirical mode decomposition.  

PubMed

A Compound fault signal usually contains multiple characteristic signals and strong confusion noise, which makes it difficult to separate week fault signals from them through conventional ways, such as FFT-based envelope detection, wavelet transform or empirical mode decomposition individually. In order to improve the compound faults diagnose of rolling bearings via signals' separation, the present paper proposes a new method to identify compound faults from measured mixed-signals, which is based on ensemble empirical mode decomposition (EEMD) method and independent component analysis (ICA) technique. With the approach, a vibration signal is firstly decomposed into intrinsic mode functions (IMF) by EEMD method to obtain multichannel signals. Then, according to a cross correlation criterion, the corresponding IMF is selected as the input matrix of ICA. Finally, the compound faults can be separated effectively by executing ICA method, which makes the fault features more easily extracted and more clearly identified. Experimental results validate the effectiveness of the proposed method in compound fault separating, which works not only for the outer race defect, but also for the rollers defect and the unbalance fault of the experimental system. PMID:25289644

Wang, Huaqing; Li, Ruitong; Tang, Gang; Yuan, Hongfang; Zhao, Qingliang; Cao, Xi

2014-01-01

242

A Compound Fault Diagnosis for Rolling Bearings Method Based on Blind Source Separation and Ensemble Empirical Mode Decomposition  

PubMed Central

A Compound fault signal usually contains multiple characteristic signals and strong confusion noise, which makes it difficult to separate week fault signals from them through conventional ways, such as FFT-based envelope detection, wavelet transform or empirical mode decomposition individually. In order to improve the compound faults diagnose of rolling bearings via signals’ separation, the present paper proposes a new method to identify compound faults from measured mixed-signals, which is based on ensemble empirical mode decomposition (EEMD) method and independent component analysis (ICA) technique. With the approach, a vibration signal is firstly decomposed into intrinsic mode functions (IMF) by EEMD method to obtain multichannel signals. Then, according to a cross correlation criterion, the corresponding IMF is selected as the input matrix of ICA. Finally, the compound faults can be separated effectively by executing ICA method, which makes the fault features more easily extracted and more clearly identified. Experimental results validate the effectiveness of the proposed method in compound fault separating, which works not only for the outer race defect, but also for the rollers defect and the unbalance fault of the experimental system. PMID:25289644

Wang, Huaqing; Li, Ruitong; Tang, Gang; Yuan, Hongfang; Zhao, Qingliang; Cao, Xi

2014-01-01

243

On the use of Prony method to locate faults in loop systems by utilizing modal parameters of fault current  

Microsoft Academic Search

A method utilizing prony algorithm and artificial neural networks (ANNs) is presented to locate faults on loop systems. Fault simulation is implemented using the ATP-EMTP. The loop system is represented by a line with generator units on both ends. The proposed method accounts for the anticipated changes in the traveling-wave characteristics. Proposed modifications are limited to the type of ANN

M. M. Tawfik; M. M. Morcos

2005-01-01

244

Condition-based fault tree analysis (CBFTA): A new method for improved fault tree analysis (FTA), reliability and safety calculations  

Microsoft Academic Search

Condition-based maintenance methods have changed systems reliability in general and individual systems in particular. Yet, this change does not affect system reliability analysis. System fault tree analysis (FTA) is performed during the design phase. It uses components failure rates derived from available sources as handbooks, etc. Condition-based fault tree analysis (CBFTA) starts with the known FTA. Condition monitoring (CM) methods

Dan M. Shalev; Joseph Tiran

2007-01-01

245

Phase Lock-In Reflectometry for Detection and Characterization of Wiring System Faults  

NASA Astrophysics Data System (ADS)

This paper describes the preliminary stage in the development of a Phase Lock-in Reflectometry (PLR) technique for detecting, locating and characterizing faults in electrical wiring systems. Results from the more-traditional techniques, e.g. Time-Domain Reflectometry (TDR) and Frequency-Domain Reflectometry (FDR) for detection and location of wiring-system faults are presented and compared with results from the PLR technique. The potential of PLR for characterizing wiring-system faults is briefly discussed. A methodology for combining wiring system models with experimental results to improve the characterization of faults as well as to improve the fundamental understanding of failure mechanisms is also presented.

Ambalam, Harikrishna; Reibel, Richard; Sathish, Shamachary; Frock, Brian

2006-03-01

246

Fault-Detection Tool Has Companies 'Mining' Own Business  

NASA Technical Reports Server (NTRS)

A successful launching of NASA's Space Shuttle hinges heavily on the three Space Shuttle Main Engines (SSME) that power the orbiter. These critical components must be monitored in real time, with sensors, and compared against expected behaviors that could scrub a launch or, even worse, cause in- flight hazards. Since 1981, SSME faults have caused 23 scrubbed launches and 29 percent of total Space Shuttle downtime, according to a compilation of analysis reports. The most serious cases typically occur in the last few seconds before ignition; a launch scrub that late in the countdown usually means a period of investigation of a month or more. For example, during the launch attempt of STS-41D in 1984, an anomaly was detected in the number three engine, causing the mission to be scrubbed at T-4 seconds. This not only affected STS-41D, but forced the cancellation of another mission and caused a 2-month flight delay. In 2002, NASA s Kennedy Space Center, the Florida Institute of Technology, and Interface & Control Systems, Inc., worked together to attack this problem by creating a system that could automate the detection of mechanical failures in the SSMEs fuel control valves.

2005-01-01

247

Method and system for fault accommodation of machines  

NASA Technical Reports Server (NTRS)

A method for multi-objective fault accommodation using predictive modeling is disclosed. The method includes using a simulated machine that simulates a faulted actual machine, and using a simulated controller that simulates an actual controller. A multi-objective optimization process is performed, based on specified control settings for the simulated controller and specified operational scenarios for the simulated machine controlled by the simulated controller, to generate a Pareto frontier-based solution space relating performance of the simulated machine to settings of the simulated controller, including adjustment to the operational scenarios to represent a fault condition of the simulated machine. Control settings of the actual controller are adjusted, represented by the simulated controller, for controlling the actual machine, represented by the simulated machine, in response to a fault condition of the actual machine, based on the Pareto frontier-based solution space, to maximize desirable operational conditions and minimize undesirable operational conditions while operating the actual machine in a region of the solution space defined by the Pareto frontier.

Goebel, Kai Frank (Inventor); Subbu, Rajesh Venkat (Inventor); Rausch, Randal Thomas (Inventor); Frederick, Dean Kimball (Inventor)

2011-01-01

248

Error detection method  

DOEpatents

An apparatus, program product, and method that run an algorithm on a hardware based processor, generate a hardware error as a result of running the algorithm, generate an algorithm output for the algorithm, compare the algorithm output to another output for the algorithm, and detect the hardware error from the comparison. The algorithm is designed to cause the hardware based processor to heat to a degree that increases the likelihood of hardware errors to manifest, and the hardware error is observable in the algorithm output. As such, electronic components may be sufficiently heated and/or sufficiently stressed to create better conditions for generating hardware errors, and the output of the algorithm may be compared at the end of the run to detect a hardware error that occurred anywhere during the run that may otherwise not be detected by traditional methodologies (e.g., due to cooling, insufficient heat and/or stress, etc.).

Olson, Eric J.

2013-06-11

249

A Hardware-Based Approach for Fault Detection in RTOS-Based Embedded Systems  

Microsoft Academic Search

This paper presents a new hardware-based approach able to monitor the execution flow of the Real-Time Operating System (RTOS) in order to detect faults changing the tasks' execution flow in embedded systems. Results obtained during experiments performed according to the IEC 61000-4-29 standard demonstrate that the proposed approach is able to provide higher fault coverage with respect to the fault

D. Silva; K. Stangherlin; L. Bolzani; F. Vargas

2011-01-01

250

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

NASA Technical Reports Server (NTRS)

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.

Litt, Jonathan; Kurtkaya, Mehmet; Duyar, Ahmet

1994-01-01

251

Exoplanet Detection: Transit Method  

NSDL National Science Digital Library

The Exoplanet Detection: Transit Method model simulates the detection of exoplanets by using the transit method of detecting exoplanets. In this method, the light curve from a star, and how it changes over time due to exoplanet transits, is observed and then analyzed. In this simulation the exoplanet orbits the star (sun-sized) in circular motion via Kepler's third law.  When the exoplanet passes in front of the star (transits), it blocks part of the starlight. This decrease in starlight is shown on the graph.  If the exoplanet is close enough to the central star, and has sufficient reflectivity, or albedo, it can reflect enough of the starlight to be seen on the light curve. In the simulation the star-exoplanet system is shown as seen from Earth (edge on view) but magnified greatly, and with the star and planet sizes not shown to the scale of the orbit. The radius of the central star (relative to the radius of Sun),semi-major axis of the exoplanet (in AU), radius of the exoplanet (relative to the radius of Jupiter), the exoplanet's albedo (reflectivity), and the inclination of the system relative to Earth can be changed. The simulation uses Java 3D, if installed, to render the view the star and exoplanet. If Java 3D is not installed, the simulation will default to simple 3D using Java.

Belloni, Mario

2010-06-29

252

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

PubMed

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. PMID:24439843

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

2014-09-01

253

Experimental Validation of a Real-Time Model-Based Sensor Fault Detection and Isolation System for Unmanned Ground Vehicles  

Microsoft Academic Search

This paper presents experimental validation and implementation issues of a model-based sensor fault detection and isolation (FDI) system applied to unmanned ground vehicles (UGVs). Enhanced structural analysis is followed to build the residual generation module, followed by different residual evaluation modules capable of detecting single and multiple sensor faults. The overall proposed sensor fault detection and isolation system (SFDIS) has

A. Monteriu; P. Asthana; K. Valavanis; S. Longhi

2006-01-01

254

Analog system-level fault diagnosis based on symbolic method in the frequency domain  

E-print Network

into the pattern recognition, the parameter identification, the fault verification, and the approximation techniques. Two basic methods of analog fault diagnosis are the simulation ? before ? test ( SBT) and the simulation ? after ? test ( SAT ) [2]. Fig. I... of only signal hard fault. The Fault diagnosis techni ues SBT techni ues SAT techni ues Fault dictionary techniques Probabilistic techniques Limited measure techniques Sufficient measure techniques Pattern recognition techniques...

You, Zhihong

2012-06-07

255

Nucleic Acid Detection Methods  

DOEpatents

The invention relates to methods for rapidly determining the sequence and/or length a target sequence. The target sequence may be a series of known or unknown repeat sequences which are hybridized to an array of probes. The hybridized array is digested with a single-strand nuclease and free 3'-hydroxyl groups extended with a nucleic acid polymerase. Nuclease cleaved heteroduplexes can be easily distinguish from nuclease uncleaved heteroduplexes by differential labeling. Probes and target can be differentially labeled with detectable labels. Matched target can be detected by cleaving resulting loops from the hybridized target and creating free 3-hydroxyl groups. These groups are recognized and extended by polymerases added into the reaction system which also adds or releases one label into solution. Analysis of the resulting products using either solid phase or solution. These methods can be used to detect characteristic nucleic acid sequences, to determine target sequence and to screen for genetic defects and disorders. Assays can be conducted on solid surfaces allowing for multiple reactions to be conducted in parallel and, if desired, automated.

Smith, Cassandra L. (Boston, MA); Yaar, Ron (Brookline, MA); Szafranski, Przemyslaw (Boston, MA); Cantor, Charles R. (Boston, MA)

1998-05-19

256

Nucleic acid detection methods  

DOEpatents

The invention relates to methods for rapidly determining the sequence and/or length a target sequence. The target sequence may be a series of known or unknown repeat sequences which are hybridized to an array of probes. The hybridized array is digested with a single-strand nuclease and free 3{prime}-hydroxyl groups extended with a nucleic acid polymerase. Nuclease cleaved heteroduplexes can be easily distinguish from nuclease uncleaved heteroduplexes by differential labeling. Probes and target can be differentially labeled with detectable labels. Matched target can be detected by cleaving resulting loops from the hybridized target and creating free 3-hydroxyl groups. These groups are recognized and extended by polymerases added into the reaction system which also adds or releases one label into solution. Analysis of the resulting products using either solid phase or solution. These methods can be used to detect characteristic nucleic acid sequences, to determine target sequence and to screen for genetic defects and disorders. Assays can be conducted on solid surfaces allowing for multiple reactions to be conducted in parallel and, if desired, automated. 18 figs.

Smith, C.L.; Yaar, R.; Szafranski, P.; Cantor, C.R.

1998-05-19

257

On-Line Fault Detection and Compensation of Hydraulic Driven Machines Using Modelling Techniques  

E-print Network

robotics and aerospace to heavy industrial systems. Electro-hydraulic drive systems are related for the industrial maintenance processes. Hydraulic motors are subject to a fault in a system that is oftenOn-Line Fault Detection and Compensation of Hydraulic Driven Machines Using Modelling Techniques C

Thawonmas, Ruck

258

Tracking Probabilistic Correlation of Monitoring Data for Fault Detection in Complex Systems  

Microsoft Academic Search

Abstract Due to their growing complexity, it becomes extremely,difficult to detect ,and ,isolate faults in complex,systems. While large amount ,of monitoring data can be collected ,from ,such systems for fault analysis, one challenge is how to correlate the data effectively across distributed systems and observation time. Much of the ,internal monitoring ,data reacts to the volume ,of user ,requests accordingly

Zhen Guo; Guofei Jiang; Haifeng Chen; Kenji Yoshihira

2006-01-01

259

Effective fault detection & isolation using bond graph-based Domain decomposition  

Microsoft Academic Search

The problem of fault detection and isolation in complex chemical\\/biochemical plants can be effectively addressed by a hierarchical strategy involving successive narrowing of the search space of potential faults. A bond graph network is one means of achieving a decomposition based on a separation of the physical domains such as mechanical, electrical, etc. In this work, bond graph theory is

Xi Zhang; Karlene A. Hoo

2009-01-01

260

Fault detection and isolation system design for omnidirectional soccer-playing robots  

Microsoft Academic Search

A mobile robot has been constructed for entry in the Latinamerican RoboCup robot soccer contests. To improve the robot's robustness and availability, fault detection and isolation functions are required for major faults causing battery voltage drops or motor encoder decoupling. This article presents the design for such an FDI system. The omnidirectional robot and its models are described, and four

Cristóbal Valdivieso; Aldo Cipriano

2006-01-01

261

Gain-Scheduled Robust Fault Detection on Time-Delay Stochastic Nonlinear Systems  

Microsoft Academic Search

This paper studies the problem of continuous gain-scheduled robust fault detection (RFD) on a class of time- delay stochastic nonlinear systems with partially known jump rates. By means of gradient linearization procedure, stochastic linear models and filter-based residual signal generators are con- structed in the vicinity of selected operating states. Furthermore, in order to guarantee the sensitivity to faults and

Yanyan Yin; Peng Shi; Fei Liu

2011-01-01

262

Advanced Signal Processing Techniques for Fault Detection and Diagnosis in a Wind Turbine  

E-print Network

Advanced Signal Processing Techniques for Fault Detection and Diagnosis in a Wind Turbine Induction rotor bars and bearing damages. Index Terms--Wind turbines, motor current signature analy- sis, time of maintenance in offshore environment, teledetection of wind turbine faults is becoming a crucial issue

Paris-Sud XI, Université de

263

Electromagnetic detection of plate hydration due to bending faults at the Middle America Trench  

E-print Network

Electromagnetic detection of plate hydration due to bending faults at the Middle America Trench bending faults on the incoming oceanic plate of the Middle America Trench offshore Nicaragua have been and serpentinization of the upper mantle. Low seismic velocities observed in the uppermost mantle of the incoming plate

Constable, Steve

264

Current Sensor Fault Detection, Isolation, and Reconfiguration for Doubly Fed Induction Generators  

Microsoft Academic Search

Fault tolerance is gaining growing interest to increase the reliability and availability of distributed energy sources. Current sensor fault detection, isolation, and reconfiguration are presented for a voltage-oriented controlled doubly fed induction generator, which is mainly used in wind turbines. The focus of this analysis is on the isolation of the faulty sensor and the actual reconfiguration. During a short

Kai Rothenhagen; Friedrich Wilhelm Fuchs

2009-01-01

265

Broken rotor bar fault detection in induction motors using starting current analysis  

Microsoft Academic Search

Fault detection based on a common steady-state analysis technique, such as FFT, is known to be significantly dependant on the loading conditions of induction motors. At light load, it is difficult to distinguish between healthy and faulty rotors because the characteristic broken rotor bar fault frequencies are very close to the fundamental component and their amplitudes are small in comparison.

Randy Supangat; Nesimi Ertugrul; Wen L. Soong; Douglas A. Gray; Colin Hansen; Jason Grieger

2005-01-01

266

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

NASA Technical Reports Server (NTRS)

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.

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

2010-01-01

267

Identification of seismogenic structures on faults: Generation and detection of asperities  

NASA Astrophysics Data System (ADS)

Following the definition first given by Lay and Kanamori (1981), asperities are areas of largest co-seismic slip. This makes them particularly interesting for seismic risk and hazard studies. However, the slip distributions on fault planes of large earthquakes can differ significantly from each other when determined by different methods. Therefore, a better insight into asperity generating processes is desirable and proper comparison of results could give an idea of the physics behind the driving mechanism. In our talk we would like to present results from aftershock data sets in subduction as well as crustal faults using the correlation of various parameter distributions on the faults as a method for asperity detection. The correlations of these distributions with geological and tectonic data give the hint that material inhomogeneities play a major role in asperity generating processes. We compare these results to asperities identified by geodetic data and try to discuss the discrepancies which might give some ideas about the reflection of structural inhomogeneities in the deformational field at depth of a fault and at the Earths' surface. Further important questions with consequences for future earthquakes are the spatial stationarity and temporal persistency of asperities which involves the discussion whether repeatable earthquakes are possible or whether the earthquake process is in general a rather random process. Here we will show an example from a segment boundary between two large subduction zone earthquakes which seems to be a persistent feature since 400.000 years and therefore recurrently survived more than one seismic cycle. Although a segment boundary determines nucleation and stopping phase of an earthquake rather than areas of large slip, these type of features are most important in terms of the expected size of an earthquake.

Sobiesiak, Monika; Eggert, Silke

2010-05-01

268

Development, Implementation, and Testing of Fault Detection Strategies on the National Wind Technology Center's Controls Advanced Research Turbines  

SciTech Connect

The National Renewable Energy Laboratory's National Wind Technology Center dedicates two 600 kW turbines for advanced control systems research. A fault detection system for both turbines has been developed, analyzed, and improved across years of experiments to protect the turbines as each new controller is tested. Analysis of field data and ongoing fault detection strategy improvements have resulted in a system of sensors, fault definitions, and detection strategies that have thus far been effective at protecting the turbines. In this paper, we document this fault detection system and provide field data illustrating its operation while detecting a range of failures. In some cases, we discuss the refinement process over time as fault detection strategies were improved. The purpose of this article is to share field experience obtained during the development and field testing of the existing fault detection system, and to offer a possible baseline for comparison with more advanced turbine fault detection controllers.

Johnson, K. E.; Fleming, P. A.

2011-06-01

269

Detecting and Tolerating Byzantine Faults in Database Systems  

E-print Network

This thesis describes the design, implementation, and evaluation of a replication scheme to handle Byzantine faults in transaction processing database systems. The scheme compares answers from queries and updates on multiple ...

Vandiver, Benjamin Mead

2008-06-30

270

Detecting and tolerating Byzantine faults in database systems  

E-print Network

This thesis describes the design, implementation, and evaluation of a replication scheme to handle Byzantine faults in transaction processing database systems. The scheme compares answers from queries and updates on multiple ...

Vandiver, Benjamin Mead, 1978-

2008-01-01

271

Building method of diagnostic model of Bayesian networks based on fault tree  

NASA Astrophysics Data System (ADS)

Fault tree (FT) is usually a reliability and security analysis and diagnoses decision model. It is also in common use that expressing fault diagnosis question with fault tree model. But it will not be changed easily if fault free model was built, and it could not accept and deal with new information easily. It is difficult to put the information which have nothing to do with equipment fault but can be used to fault diagnosis into diagnostic course. Bayesian Networks (BN) can learn and improve its network architecture and parameters at any time by way of practice accumulation, and raises the ability of fault diagnosis. The method of building BN based on FT is researched on this article, this method could break through the limitations of FT itself, make BN be more extensively applied to the domain of fault diagnosis and gains much better ability of fault analysis and diagnosis.

Liu, Xiao; Li, Haijun; Li, Lin

2008-10-01

272

System for detecting and limiting electrical ground faults within electrical devices  

DOEpatents

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.

Gaubatz, Donald C. (Cupertino, CA)

1990-01-01

273

Model-based monitoring and fault diagnosis of fossil power plant process units using Group Method of Data Handling.  

PubMed

This paper presents an incipient fault diagnosis approach based on the Group Method of Data Handling (GMDH) technique. The GMDH algorithm provides a generic framework for characterizing the interrelationships among a set of process variables of fossil power plant sub-systems and is employed to generate estimates of important variables in a data-driven fashion. In this paper, ridge regression techniques are incorporated into the ordinary least squares (OLS) estimator to solve regression coefficients at each layer of the GMDH network. The fault diagnosis method is applied to feedwater heater leak detection with data from an operating coal-fired plant. The results demonstrate the proposed method is capable of providing an early warning to operators when a process fault or an equipment fault occurs in a fossil power plant. PMID:19084227

Li, Fan; Upadhyaya, Belle R; Coffey, Lonnie A

2009-04-01

274

Final Technical Report Recovery Act: Online Nonintrusive Condition Monitoring and Fault Detection for Wind Turbines  

SciTech Connect

The penetration of wind power has increased greatly over the last decade in the United States and across the world. The U.S. wind power industry installed 1,118 MW of new capacity in the first quarter of 2011 alone and entered the second quarter with another 5,600 MW under construction. By 2030, wind energy is expected to provide 20% of the U.S. electricity needs. As the number of wind turbines continues to grow, the need for effective condition monitoring and fault detection (CMFD) systems becomes increasingly important [3]. Online CMFD is an effective means of not only improving the reliability, capacity factor, and lifetime, but it also reduces the downtime, energy loss, and operation and maintenance (O&M) of wind turbines. The goal of this project is to develop novel online nonintrusive CMFD technologies for wind turbines. The proposed technologies use only the current measurements that have been used by the control and protection system of a wind turbine generator (WTG); no additional sensors or data acquisition devices are needed. Current signals are reliable and easily accessible from the ground without intruding on the wind turbine generators (WTGs) that are situated on high towers and installed in remote areas. Therefore, current-based CMFD techniques have great economic benefits and the potential to be adopted by the wind energy industry. Specifically, the following objectives and results have been achieved in this project: (1) Analyzed the effects of faults in a WTG on the generator currents of the WTG operating at variable rotating speed conditions from the perspective of amplitude and frequency modulations of the current measurements; (2) Developed effective amplitude and frequency demodulation methods for appropriate signal conditioning of the current measurements to improve the accuracy and reliability of wind turbine CMFD; (3) Developed a 1P-invariant power spectrum density (PSD) method for effective signature extraction of wind turbine faults with characteristic frequencies in the current or current demodulated signals, where 1P stands for the shaft rotating frequency of a WTG; (4) Developed a wavelet filter for effective signature extraction of wind turbine faults without characteristic frequencies in the current or current demodulated signals; (5) Developed an effective adaptive noise cancellation method as an alternative to the wavelet filter method for signature extraction of wind turbine faults without characteristic frequencies in the current or current demodulated signals; (6) Developed a statistical analysis-based impulse detection method for effective fault signature extraction and evaluation of WTGs based on the 1P-invariant PSD of the current or current demodulated signals; (7) Validated the proposed current-based wind turbine CMFD technologies through extensive computer simulations and experiments for small direct-drive WTGs without gearboxes; and (8) Showed, through extensive experiments for small direct-drive WTGs, that the performance of the proposed current-based wind turbine CMFD technologies is comparable to traditional vibration-based methods. The proposed technologies have been successfully applied for detection of major failures in blades, shafts, bearings, and generators of small direct-drive WTGs. The proposed technologies can be easily integrated into existing wind turbine control, protection, and monitoring systems and can be implemented remotely from the wind turbines being monitored. The proposed technologies provide an alternative to vibration-sensor-based CMFD. This will reduce the cost and hardware complexity of wind turbine CMFD systems. The proposed technologies can also be combined with vibration-sensor-based methods to improve the accuracy and reliability of wind turbine CMFD systems. When there are problems with sensors, the proposed technologies will ensure proper CMFD for the wind turbines, including their sensing systems. In conclusion, the proposed technologies offer an effective means to achieve condition-based smart maintenance for wind turbines and have a gre

Wei Qiao

2012-05-29

275

Comparison of Chiller Models for Use in Model-Based Fault Detection  

E-print Network

Selecting the model is an important and essential step in model based fault detection and diagnosis (FDD). Factors that are considered in evaluating a model include accuracy, training data requirements, calibration effort, generality...

Sreedhara, P.; Haves, P.

2001-01-01

276

Detecting Intrusion Faults in Remotely Controlled Systems Salvatore Candido and Seth Hutchinson  

E-print Network

Detecting Intrusion Faults in Remotely Controlled Systems Salvatore Candido and Seth Hutchinson Engineering, University of Illinois, Urbana, IL 61801, USA candido@illinois.edu S. Hutchinson is a Professor

Hutchinson, Seth

277

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

SciTech Connect

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 that 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.

Zhao Jinsong [College of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029 (China)], E-mail: jinsongzhao@mail.tsinghua.edu.cn; Huang Jianchao [College of Information Science and Technology, Beijing Institute of Technology, Beijing 10086 (China); Sun Wei [College of Chemical Engineering, Beijing University of Chemical Technology, Beijing 100029 (China)

2008-11-15

278

Lessons Learned on Implementing Fault Detection, Isolation, and Recovery (FDIR) in a Ground Launch Environment  

NASA Technical Reports Server (NTRS)

This paper's main purpose is to detail issues and lessons learned regarding designing, integrating, and implementing Fault Detection Isolation and Recovery (FDIR) for Constellation Exploration Program (CxP) Ground Operations at Kennedy Space Center (KSC).

Ferell, Bob; Lewis, Mark; Perotti, Jose; Oostdyk, Rebecca; Goerz, Jesse; Brown, Barbara

2010-01-01

279

Fault Detection Algorithm for Telephone Systems Based on the Danger Theory  

Microsoft Academic Search

\\u000a This work is aimed at presenting a fault detection algorithm composed of multiple interconnected modules, and operating according\\u000a to the paradigm supported by the danger theory in immunology. This algorithm attempts to achieve significant features that\\u000a a fault detection system is supposed to have when monitoring a telephone profile system. These features would basically be\\u000a adaptability due to the strong

José Carlos L. Pinto; Fernando J. Von Zuben

2005-01-01

280

Model-based nuclear power plant monitoring and fault detection: Theoretical foundations  

Microsoft Academic Search

The theoretical basis and validation studies of a real-time, model-based process monitoring and fault detection system is presented. Through use of a non-linear state estimation technique coupled with a probabilistically-based statistical hypothesis test, it is possible to detect and identify sensor, component and process faults at extremely early times from changes in the stochastic characteristics of measured signals. Data from

R. M. Singer; K. C. Gross; J. P. Herzog; R. W. King; S. Wegerich

1997-01-01

281

Probability of detecting single faults in Hadamard and SWAP gates of a quantum computer after several operations  

E-print Network

, Hadamard gate, Quantum decoherence, undetectable faults, quan- tum computer hardware INTRODUCTIONc DRAFT Probability of detecting single faults in Hadamard and SWAP gates of a quantum computer is the main factor which causes fault in a quantum computer. In this article, the probability of detecting

282

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

NASA Technical Reports Server (NTRS)

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.

Collins, Emmanuel G.

2000-01-01

283

Detection of stator winding faults in induction machines using flux and vibration analysis  

NASA Astrophysics Data System (ADS)

This work aims at presenting the detection and diagnosis of electrical faults in the stator winding of three-phase induction motors using magnetic flux and vibration analysis techniques. A relationship was established between the main electrical faults (inter-turn short circuits and unbalanced voltage supplies) and the signals of magnetic flux and vibration, in order to identify the characteristic frequencies of those faults. The experimental results showed the efficiency of the conjugation of these techniques for detection, diagnosis and monitoring tasks. The results were undoubtedly impressive and can be adapted and used in real predictive maintenance programs in industries.

Lamim Filho, P. C. M.; Pederiva, R.; Brito, J. N.

2014-01-01

284

Method for detecting objects  

US Patent & Trademark Office Database

A method for detecting objects, wherein two images of a surrounding (1) are taken and a disparity image is determined by means of stereo image processing, wherein a depth map of the surrounding (1) is determined from the determined disparities, wherein a free space delimiting line (2) is identified, delimiting an unobstructed region of the surrounding (1), wherein outside and along the free space delimiting line (1) the depth card is segmented by segments (3) of a suitable width formed by pixels of the same or similar distance to an image plane, wherein a height of each segment (3) is estimated as part of an object (4.1 to 4.6) located outside of the unobstructed region in a way, such that each segment (3) is characterized by the two-dimensional position of the base (for example the distance and angle to the longitudinal axis of the vehicle) and the height thereof.

2013-10-01

285

Fault detection and diagnosis of induction motors using motor current signature analysis and a hybrid FMM-CART model.  

PubMed

In this paper, a novel approach to detect and classify comprehensive fault conditions of induction motors using a hybrid fuzzy min-max (FMM) neural network and classification and regression tree (CART) is proposed. The hybrid model, known as FMM-CART, exploits the advantages of both FMM and CART for undertaking data classification and rule extraction problems. A series of real experiments is conducted, whereby the motor current signature analysis method is applied to form a database comprising stator current signatures under different motor conditions. The signal harmonics from the power spectral density are extracted as discriminative input features for fault detection and classification with FMM-CART. A comprehensive list of induction motor fault conditions, viz., broken rotor bars, unbalanced voltages, stator winding faults, and eccentricity problems, has been successfully classified using FMM-CART with good accuracy rates. The results are comparable, if not better, than those reported in the literature. Useful explanatory rules in the form of a decision tree are also elicited from FMM-CART to analyze and understand different fault conditions of induction motors. PMID:24808459

Seera, Manjeevan; Lim, Chee Peng; Ishak, Dahaman; Singh, Harapajan

2012-01-01

286

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

NASA Astrophysics Data System (ADS)

Fault detection and diagnosis is critical to many applications in order to ensure proper operation and performance over time. Positron emission tomography (PET) systems that require regular calibrations by qualified scanner operators are good candidates for such continuous improvements. Furthermore, for scanners employing one-to-one coupling of crystals to photodetectors to achieve enhanced spatial resolution and contrast, the calibration task is even more daunting because of the large number of independent channels involved. To cope with the additional complexity of the calibration and quality control procedures of these scanners, an intelligent system (IS) was designed to perform fault detection and diagnosis (FDD) of malfunctioning channels. The IS can be broken down into four hierarchical modules: parameter extraction, channel fault detection, fault prioritization and diagnosis. Of these modules, the first two have previously been reported and this paper focuses on fault prioritization and diagnosis. The purpose of the fault prioritization module is to help the operator to zero in on the faults that need immediate attention. The fault diagnosis module will then identify the causes of the malfunction and propose an explanation of the reasons that lead to the diagnosis. The FDD system was implemented on a LabPET avalanche photodiode (APD)-based digital PET scanner. Experiments demonstrated a FDD Sensitivity of 99.3 % (with a 95% confidence interval (CI) of: [98.7, 99.9]) for major faults. Globally, the Balanced Accuracy of the diagnosis for varying fault severities is 92 %. This suggests the IS can greatly benefit the operators in their maintenance task.

Charest, Jonathan; Beaudoin, Jean-Francois; Cadorette, Jules; Lecomte, Roger; Brunet, Charles-Antoine; Fontaine, Rejean

2014-10-01

287

H? mode-dependent fault detection filter design for stochastic Markovian jump systems with time-varying delays and parameter uncertainties.  

PubMed

This paper deals with the problem of robust H? fault detection for a class of stochastic Markovian jump systems (SMJSs) The aim is to design a linear mode-dependent fault detection filter such that the fault detection system is not only stochastically asymptotically stable in the large, but also satisfies a prescribed H?-norm level for all admissible uncertainties. By using Lyapunov stability theory and generalized Itô formula, some novel mode-dependent and delay-dependent sufficient conditions in terms of linear matrix inequality (LMI) are proposed to insure the existence of the desired fault detection filter. A simulation example and an industrial nonisothermal continuous stirred tank reactor (CSTR) system are employed to show the effectiveness of the proposed method. PMID:24929630

Zhuang, Guangming; Xia, Jianwei; Chu, Yuming; Chen, Fu

2014-07-01

288

A Fuzzy Reasoning Design for Fault Detection and Diagnosis of a Computer-Controlled System.  

PubMed

A Fuzzy Reasoning and Verification Petri Nets (FRVPNs) model is established for an error detection and diagnosis mechanism (EDDM) applied to a complex fault-tolerant PC-controlled system. The inference accuracy can be improved through the hierarchical design of a two-level fuzzy rule decision tree (FRDT) and a Petri nets (PNs) technique to transform the fuzzy rule into the FRVPNs model. Several simulation examples of the assumed failure events were carried out by using the FRVPNs and the Mamdani fuzzy method with MATLAB tools. The reasoning performance of the developed FRVPNs was verified by comparing the inference outcome to that of the Mamdani method. Both methods result in the same conclusions. Thus, the present study demonstratrates that the proposed FRVPNs model is able to achieve the purpose of reasoning, and furthermore, determining of the failure event of the monitored application program. PMID:19255619

Ting, Y; Lu, W B; Chen, C H; Wang, G K

2008-03-01

289

Fault Detection, Isolation and Control Reconfiguration of Three-Phase PMSM Drives  

E-print Network

faults are single-phase open-circuit and current sensor outage. The method is based on the monitoring the condition of the current sensors is detailed. In case of current sensor fault, observers are used composed of a four- leg inverter and a three-phase permanent magnet synchronous machine. The considered

Paris-Sud XI, Université de

290

The fault diagnosis method of rolling bearing based on wavelet packet transform and zooming envelope analysis  

Microsoft Academic Search

The fault of rolling bearing is one of familiar faults in rotaries. In accordance with the defects of traditional envelope analysis to specify the resonant frequency band manually, a new fault diagnosis method based on wavelet packet transform and zooming envelope analysis is proposed. Firstly, the modulated frequency of resonant frequency band is extracted for rolling bearing, and the original

Shu-Ting Wan; Lu-Yong Lv

2007-01-01

291

Automatic and Scalable Fault Detection for Mobile Applications  

E-print Network

, implementation, and evaluation of VanarSena, an automated fault finder for mobile applications ("apps- ability. For mobile apps, improving reliability is less about making sure that "mission critical" software of reviews on mo- bile app stores shows that an app that crashes is likely to garner poor reviews. Mobile app

Gummadi, Ramakrishna

292

Robust Asynchronous Algorithms in Networks with a Fault Detection Ring  

Microsoft Academic Search

In this paper we study asynchronous networks, in which processors may fail and recover several times during an execution. Upon recovery a processor rejoins the execution as a passive processor, with all variables initialized, except for a fault flag, which is updated by the system. In addition to the regular communication links connecting pairs of processors, the processors are connected

Moshe Molcho; Shmuel Zaks

1994-01-01

293

A Behaviour-Based Method for Fault Tree Generation Andrew Rae; University of Queensland; Brisbane, Queensland, Australia  

E-print Network

: fault tree, hazard analysis Abstract This paper presents a new theory of fault trees for complex systems analysis, Fault Tree Analysis (ref. 6). Fault tree analysis is widely used by industry for both reliabilityA Behaviour-Based Method for Fault Tree Generation Andrew Rae; University of Queensland; Brisbane

Lindsay, Peter

294

Tacholess Envelope Order Analysis and Its Application to Fault Detection of Rolling Element Bearings with Varying Speeds  

PubMed Central

Vibration analysis is an effective tool for the condition monitoring and fault diagnosis of rolling element bearings. Conventional diagnostic methods are based on the stationary assumption, thus they are not applicable to the diagnosis of bearings working under varying speed. This constraint limits the bearing diagnosis to the industrial application significantly. In order to extend the conventional diagnostic methods to speed variation cases, a tacholess envelope order analysis technique is proposed in this paper. In the proposed technique, a tacholess order tracking (TLOT) method is first introduced to extract the tachometer information from the vibration signal itself. On this basis, an envelope order spectrum (EOS) is utilized to recover the bearing characteristic frequencies in the order domain. By combining the advantages of TLOT and EOS, the proposed technique is capable of detecting bearing faults under varying speeds, even without the use of a tachometer. The effectiveness of the proposed method is demonstrated by both simulated signals and real vibration signals collected from locomotive roller bearings with faults on inner race, outer race and rollers, respectively. Analyzed results show that the proposed method could identify different bearing faults effectively and accurately under speed varying conditions. PMID:23959244

Zhao, Ming; Lin, Jing; Xu, Xiaoqiang; Lei, Yaguo

2013-01-01

295

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

NASA Technical Reports Server (NTRS)

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.

Russell, B. Don

1989-01-01

296

Laser ultrasound technology for fault detection on carbon fiber composites  

NASA Astrophysics Data System (ADS)

The marching in of carbon fiber reinforced polymers (CFRPs) to mass production in the aeronautic and automotive industry requires reliable quality assurance methods. Laser ultrasound (LUS) is a promising nondestructive testing technique for sample inspection. The benefits compared to conventional ultrasound (US) testing are couplant free measurements and an easy access to complex shapes due to remote optical excitation and detection. Here the potential of LUS is present on composite test panels with relevant testing scenarios for industry. The results are evaluated in comparison to conventional ultrasound used in the aeronautic industry.

Seyrkammer, Robert; Reitinger, Bernhard; Grün, Hubert; Sekelja, Jakov; Burgholzer, Peter

2014-05-01

297

A universal, fault-tolerant, non-linear analytic network for modeling and fault detection  

SciTech Connect

The similarities and differences of a universal network to normal neural networks are outlined. The description and application of a universal network is discussed by showing how a simple linear system is modeled by normal techniques and by universal network techniques. A full implementation of the universal network as universal process modeling software on a dedicated computer system at EBR-II is described and example results are presented. It is concluded that the universal network provides different feature recognition capabilities than a neural network and that the universal network can provide extremely fast, accurate, and fault-tolerant estimation, validation, and replacement of signals in a real system.

Mott, J.E. (Advanced Modeling Techniques Corp., Idaho Falls, ID (United States)); King, R.W.; Monson, L.R.; Olson, D.L.; Staffon, J.D. (Argonne National Lab., Idaho Falls, ID (United States))

1992-03-06

298

Occupancy Based Fault Detection on Building Level - a Feasibility Study  

E-print Network

technical installation and constant comfort requirements, energy consumption only changes due to the outdoor conditions and building use (passive user behavior). We assumed that for a specific situation, users behave in a learnable way. Thus..., the building performance will only change in time due to changes in outdoor conditions, the number of users, and faults in the system. To predict the range of expected building performance we measured outdoor conditions and the delta CO2 over the supply...

Tuip, B.; Houten, M.; Trcka, M.; Hensen, M.

2010-01-01

299

WETLAND DETECTION METHODS INVESTIGATION  

EPA Science Inventory

The purpose of this investigation was to research and document the application of remote sensing technology for wetlands detection. arious sensors and platforms are evaluated for: suitability to monitor specific wetland systems; effectiveness of detailing wetland extent and capab...

300

Applications of pattern recognition techniques to online fault detection  

SciTech Connect

A common problem to operators of complex industrial systems is the early detection of incipient degradation of sensors and components in order to avoid unplanned outages, to orderly plan for anticipated maintenance activities and to assure continued safe operation. In such systems, there usually are a large number of sensors (upwards of several thousand is not uncommon) serving many functions, ranging from input to control systems, monitoring of safety parameters and component performance limits, system environmental conditions, etc. Although sensors deemed to measure important process conditions are generally alarmed, the alarm set points usually are just high-low limits and the operator`s response to such alarms is based on written procedures and his or her experience and training. In many systems this approach has been successful, but in situations where the cost of a forced outage is high an improved method is needed. In such cases it is desirable, if not necessary, to detect disturbances in either sensors or the process prior to any actual failure that could either shut down the process or challenge any safety system that is present. Recent advances in various artificial intelligence techniques have provided the opportunity to perform such functions of early detection and diagnosis. In this paper, the experience gained through the application of several pattern-recognition techniques to the on-line monitoring and incipient disturbance detection of several coolant pumps and numerous sensors at the Experimental Breeder Reactor-II (EBR-II) which is located at the Idaho National Engineering Laboratory is presented.

Singer, R.M.; Gross, K.C. [Argonne National Lab., IL (United States); King, R.W. [Argonne National Lab., Idaho Falls, ID (United States)

1993-11-01

301

Bearings Fault Detection and Diagnosis Using Envelope Spectrum of Laplace Wavelet Transform  

Microsoft Academic Search

Envelope spectrum analysis is widely used to detection bearing localized fault. In order to overcome the shortcomings in the traditional envelope analysis in which manually specifying a resonant frequency band is required, a new approach based on the fusion of the Laplace wavelet transform and envelope spectrum is proposed for detection and diagnosis defects in rolling element bearings. This approach

Hui Li; Lihui Fu; Haiqi Zheng

2009-01-01

302

A review of induction motors signature analysis as a medium for faults detection  

Microsoft Academic Search

This paper is intended as a tutorial overview of induction motors signature analysis as a medium for fault detection. The purpose is to introduce in a concise manner the fundamental theory, main results, and practical applications of motor signature analysis for the detection and the localization of abnormal electrical and mechanical conditions that indicate, or may lead to, a failure

Mohamed El Hachemi Benbouzid

2000-01-01

303

An improved distributed Bayesian algorithm for fault-tolerant detection in electromagnetic spectrum monitoring sensor networks  

Microsoft Academic Search

Electromagnetic spectrum monitoring sensor networks (ESMSNs) have become a new distributed solution for the electromagnetic spectrum monitoring and attracted a large scholars' attention due to its better detection performance. However, the detection performance of ESMSNs will decrease rapidly when the faults occur to the monitoring sensor nodes, which result from the node device itself and the harsh or hostile environment

Zhang Yu; Zhao Hangsheng; Liu Qiongli

2011-01-01

304

Fault detection, isolation and control reconfiguration of three-phase PMSM drives  

Microsoft Academic Search

This paper deals with on-line software fault de- tection and isolation method for a drive composed of a four- leg inverter and a three-phase permanent magnet synchronous machine. The considered faults are single-phase open-circuit and current sensor outage. The method is based on the monitoring of the abc currents with phase-locked loops and the 'CUSUM' algorithm for the decision system.

Fabien Meinguet; Xavier Kestelynx; Eric Semailx; Johan Gyselinck

2011-01-01

305

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

NASA Technical Reports Server (NTRS)

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

Boyle, Devin K.

2014-01-01

306

Statistical Fault Detection for Parallel Applications with AutomaDeD  

SciTech Connect

Today's largest systems have over 100,000 cores, with million-core systems expected over the next few years. The large component count means that these systems fail frequently and often in very complex ways, making them difficult to use and maintain. While prior work on fault detection and diagnosis has focused on faults that significantly reduce system functionality, the wide variety of failure modes in modern systems makes them likely to fail in complex ways that impair system performance but are difficult to detect and diagnose. This paper presents AutomaDeD, a statistical tool that models the timing behavior of each application task and tracks its behavior to identify any abnormalities. If any are observed, AutomaDeD can immediately detect them and report to the system administrator the task where the problem began. This identification of the fault's initial manifestation can provide administrators with valuable insight into the fault's root causes, making it significantly easier and cheaper for them to understand and repair it. Our experimental evaluation shows that AutomaDeD detects a wide range of faults immediately after they occur 80% of the time, with a low false-positive rate. Further, it identifies weaknesses of the current approach that motivate future research.

Bronevetsky, G; Laguna, I; Bagchi, S; de Supinski, B R; Ahn, D; Schulz, M

2010-03-23

307

A consensus-based multi-agent approach for estimation in robust fault detection.  

PubMed

This paper is devoted to distributed estimation in robust fault detection for sensor networks with networked-induced delays and packet dropouts by using a consensus-based multi-agent approach. Utilizing the information interaction and coordination among the neighboring networks based on multi-agent theory, we design novel and multiple agent-based robust fault detection filters (RFDFs) subject to only partial estimated and measured information. Asymptotically stable sufficient conditions for the innovative constructed filters are derived in the form of linear matrix inequality (LMI) and the threshold fit for each agent-based RFDF is determined. An illustrative example is given to demonstrate the effectiveness of the consensus-based multi-agent approach for the estimation in robust fault detection. PMID:24962935

Jiang, Yulian; Liu, Jianchang; Wang, Shenquan

2014-09-01

308

Fault and dyke detectability in high resolution seismic surveys for coal: a view from numerical modelling*  

NASA Astrophysics Data System (ADS)

Modern underground coal mining requires certainty about geological faults, dykes and other structural features. Faults with throws of even just a few metres can create safety issues and lead to costly delays in mine production. In this paper, we use numerical modelling in an ideal, noise-free environment with homogeneous layering to investigate the detectability of small faults by seismic reflection surveying. If the layering is horizontal, faults with throws of 1/8 of the wavelength should be detectable in a 2D survey. In a coal mining setting where the seismic velocity of the overburden ranges from 3000 m/s to 4000 m/s and the dominant seismic frequency is ~100 Hz, this corresponds to a fault with a throw of 4-5 m. However, if the layers are dipping or folded, the faults may be more difficult to detect, especially when their throws oppose the trend of the background structure. In the case of 3D seismic surveying we suggest that faults with throws as small as 1/16 of wavelength (2-2.5 m) can be detectable because of the benefits offered by computer-aided horizon identification and the improved spatial coherence in 3D seismic surveys. With dykes, we find that Berkhout's definition of the Fresnel zone is more consistent with actual experience. At a depth of 500 m, which is typically encountered in coal mining, and a 100 Hz dominant seismic frequency, dykes less than 8 m in width are undetectable, even after migration.

Zhou, Binzhong 13Hatherly, Peter

2014-10-01

309

Methods of DNA methylation detection  

NASA Technical Reports Server (NTRS)

The present invention provides for methods of DNA methylation detection. The present invention provides for methods of generating and detecting specific electronic signals that report the methylation status of targeted DNA molecules in biological samples.Two methods are described, direct and indirect detection of methylated DNA molecules in a nano transistor based device. In the direct detection, methylated target DNA molecules are captured on the sensing surface resulting in changes in the electrical properties of a nano transistor. These changes generate detectable electronic signals. In the indirect detection, antibody-DNA conjugates are used to identify methylated DNA molecules. RNA signal molecules are generated through an in vitro transcription process. These RNA molecules are captured on the sensing surface change the electrical properties of nano transistor thereby generating detectable electronic signals.

Maki, Wusi Chen (Inventor); Filanoski, Brian John (Inventor); Mishra, Nirankar (Inventor); Rastogi, Shiva (Inventor)

2010-01-01

310

Comparative analysis of neural network and regression based condition monitoring approaches for wind turbine fault detection  

NASA Astrophysics Data System (ADS)

This paper presents the research results of a comparison of three different model based approaches for wind turbine fault detection in online SCADA data, by applying developed models to five real measured faults and anomalies. The regression based model as the simplest approach to build a normal behavior model is compared to two artificial neural network based approaches, which are a full signal reconstruction and an autoregressive normal behavior model. Based on a real time series containing two generator bearing damages the capabilities of identifying the incipient fault prior to the actual failure are investigated. The period after the first bearing damage is used to develop the three normal behavior models. The developed or trained models are used to investigate how the second damage manifests in the prediction error. Furthermore the full signal reconstruction and the autoregressive approach are applied to further real time series containing gearbox bearing damages and stator temperature anomalies. The comparison revealed all three models being capable of detecting incipient faults. However, they differ in the effort required for model development and the remaining operational time after first indication of damage. The general nonlinear neural network approaches outperform the regression model. The remaining seasonality in the regression model prediction error makes it difficult to detect abnormality and leads to increased alarm levels and thus a shorter remaining operational period. For the bearing damages and the stator anomalies under investigation the full signal reconstruction neural network gave the best fault visibility and thus led to the highest confidence level.

Schlechtingen, Meik; Ferreira Santos, Ilmar

2011-07-01

311

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

PubMed Central

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

Huang, Rimao; Qiu, Xuesong; Rui, Lanlan

2011-01-01

312

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

NASA Technical Reports Server (NTRS)

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.

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

2010-01-01

313

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

NASA Technical Reports Server (NTRS)

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.

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

2009-01-01

314

A Nitsche-extended finite element method for earthquake rupture on complex fault systems  

E-print Network

, 200 S.W. Mudd Bldg, 500 W 120th St., New York, NY 10027, USA b Lamont Doherty Earth ObservatoryA Nitsche-extended finite element method for earthquake rupture on complex fault systems E.T. Coon Keywords: XFEM Nitsche's method Earthquakes Fault systems a b s t r a c t The extended finite element

Shaw, Bruce E.

315

Local method for detecting communities  

NASA Astrophysics Data System (ADS)

We propose a method of community detection that is computationally inexpensive and possesses physical significance to a member of a social network. This method is unlike many divisive and agglomerative techniques and is local in the sense that a community can be detected within a network without requiring knowledge of the entire network. A global application of this method is also introduced. Several artificial and real-world networks, including the famous Zachary karate club, are analyzed.

Bagrow, James P.; Bollt, Erik M.

2005-10-01

316

Regional methods for mapping major faults in areas of uniform low relief, as used in the London Basin, UK  

NASA Astrophysics Data System (ADS)

Most of the London Basin, south-eastern UK, is underlain by the Palaeogene London Clay Formation, comprising a succession of rather uniform marine clay deposits up to 150 m thick, with widespread cover of Quaternary deposits and urban development. Therefore, in this area faults are difficult to delineate (or to detect) by conventional geological surveying methods in the field, and few are shown on the geological maps of the area. However, boreholes and excavations, especially those for civil engineering works, indicate that faults are probably widespread and numerous in the London area. A representative map of fault distribution and patterns of displacement is a pre-requisite for understanding the tectonic development of a region. Moreover, faulting is an important influence on the design and execution of civil engineering works, and on the hydrogeological characteristics of the ground. This paper reviews methods currently being used to map faults in the London Basin area. These are: the interpretation of persistent scatterer interferometry (PSI) data from time-series satellite-borne radar measurements; the interpretation of regional geophysical fields (Bouguer gravity anomaly and aeromagnetic), especially in combination with a digital elevation model; and the construction and interpretation of 3D geological models. Although these methods are generally not as accurate as large-scale geological field surveys, due to the availability of appropriate data in the London Basin they provide the means to recognise and delineate more faults, and with more confidence, than was possible using traditional geological mapping techniques. Together they reveal regional structures arising during Palaeogene crustal extension and subsidence in the North Sea, followed by inversion of a Mesozoic sedimentary basin in the south of the region, probably modified by strike-slip fault motion associated with the relative northward movement of the African Plate and the Alpine orogeny. This work is distributed under the Creative Commons Attribution 3.0 Unported License together with an NERC copyright. This license does not conflict with the regulations of the Crown Copyright.

Haslam, Richard; Aldiss, Donald

2013-04-01

317

Model-Based Sensor Fault Detection and Isolation System for Unmanned Ground Vehicles: Experimental Validation (part II)  

Microsoft Academic Search

This paper presents implementation details of a model-based sensor fault detection and isolation system (SFDIS) applied to unmanned ground vehicles (UGVs). Structural analysis, applied to the nonlinear model of the UGV, is followed to build the residual generation module, followed by a residual evaluation module capable of detecting single and multiple sensor faults, as detailed in part I (Monteriu et

Andrea Monteriu; Prateek Asthan; Kimon P. Valavanis; Sauro Longhi

2007-01-01

318

Abstract --With the increasing scale and complexity of data centers, detecting and localizing performance faults in real-time  

E-print Network

and effective in real- world systems, one needs to develop techniques that are "more effective" with "less, fault detection and localization, operating and distributed systems. I. INTRODUCTION defining analysis processes, localizing performance faults often takes hours (and at times, even days). Detecting

Vin, Harrick M.

319

Implementation and Testing of a Fault Detection Software Tool for Improving Control System Performance in a Large Commercial Building  

E-print Network

Implementation and Testing of a Fault Detection Software Tool for Improving Control System that can detect faults in the controlled process and improve control performance over traditional PID control. The tool uses static simulation models of the system under control to generate feed

320

A Software Fault Tolerance Method for Safety-Critical Systems: Effectiveness and Drawbacks  

Microsoft Academic Search

An automatic software technique suitable for on-line detection of transient errors dues to the effects of the environment (radiation, EMC, ?) is presented. The proposed approach, particularly well suited for low-cost safety-critical microprocessor-based applications, has been validated through fault injection experiments and radiation testing campaigns. The experimental results demonstrate the effectiveness of the approach in terms of fault detection capabilities.

B. Nicolescu; R. Velazco; M. Sonza-Reorda; M. Rebaudengo; M. Violante

2002-01-01

321

Fault Detection of Broken Rotor Bars in Induction Motor using a Global Fault Index  

E-print Network

in induction motor. Stator voltage and current in an induction motor were measured and employed for computation, play an important part in the field of electromechanical energy conversion. It is well machine is based on the monitoring of the stator current to detect sidebands around the supply frequency

Boyer, Edmond

322

Multi-Fault Detection of Rolling Element Bearings under Harsh Working Condition Using IMF-Based Adaptive Envelope Order Analysis.  

PubMed

When operating under harsh condition (e.g., time-varying speed and load, large shocks), the vibration signals of rolling element bearings are always manifested as low signal noise ratio, non-stationary statistical parameters, which cause difficulties for current diagnostic methods. As such, an IMF-based adaptive envelope order analysis (IMF-AEOA) is proposed for bearing fault detection under such conditions. This approach is established through combining the ensemble empirical mode decomposition (EEMD), envelope order tracking and fault sensitive analysis. In this scheme, EEMD provides an effective way to adaptively decompose the raw vibration signal into IMFs with different frequency bands. The envelope order tracking is further employed to transform the envelope of each IMF to angular domain to eliminate the spectral smearing induced by speed variation, which makes the bearing characteristic frequencies more clear and discernible in the envelope order spectrum. Finally, a fault sensitive matrix is established to select the optimal IMF containing the richest diagnostic information for final decision making. The effectiveness of IMF-AEOA is validated by simulated signal and experimental data from locomotive bearings. The result shows that IMF-AEOA could accurately identify both single and multiple faults of bearing even under time-varying rotating speed and large extraneous shocks. PMID:25353982

Zhao, Ming; Lin, Jing; Xu, Xiaoqiang; Li, Xuejun

2014-01-01

323

Validation Methods for Fault-Tolerant avionics and control systems, working group meeting 1  

NASA Technical Reports Server (NTRS)

The proceedings of the first working group meeting on validation methods for fault tolerant computer design are presented. The state of the art in fault tolerant computer validation was examined in order to provide a framework for future discussions concerning research issues for the validation of fault tolerant avionics and flight control systems. The development of positions concerning critical aspects of the validation process are given.

1979-01-01

324

Fault current limiting method using a SFCL in a neutral line of a three-phase power system  

Microsoft Academic Search

In this paper, we suggested the fault current limiting method using superconducting fault current limiter (SFCL) in a neutral line of a power system. Generally, the occurrence frequency of the single line-to-ground fault is highest among three-phase fault types in a power system. Therefore, since it can cover most of faults in a power system, this limiting method using one

Sung-Hun Lim; Jong-Fil Moon; Jae-Chul Kim

2007-01-01

325

Detection and Diagnosis of Recurrent Faults in Software Systems by Invariant Analysis  

Microsoft Academic Search

A correctly functioning enterprise-software system exhibits long-term, stable correlations between many of its monitoring metrics. Some of these correlations no longer hold when there is an error in the system, potentially enabling error detection and fault diagnosis. However, existing approaches are inefficient, requiring a large number of metrics to be monitored and ignoring the relative discriminative properties of different metric

Miao Jiang; Mohammad Ahmad Munawar; Thomas Reidemeister; Paul A. S. Ward

2008-01-01

326

Real-Time Building Energy Modeling, fault Detection and Diagnostic for a DoD Building  

E-print Network

ME 4343 HVAC Design Real-Time Building Energy Modeling and Fault Detection and Diagnostics for a DoD Building Bing Dong1, Zheng O’Neill2 1 University of Texas, San Antonio, TX, USA 2 University of Alabama, AL, USA The work was done at the United...

Dong, B.

2013-01-01

327

Robust fault detection using eigenstructure assignment: a tutorial consideration and some new results  

Microsoft Academic Search

Developments in the eigenstructure assignment approach to robust fault detection are discussed. By suitable assignment of the eigenstructure of an observer, the residual signal is decoupled from disturbances. The main contribution of this work is the novel use of right eigenvector assignment of observers, which gives more freedom for achieving disturbance decoupling. It is shown that, when decoupling conditions are

R. J. Patton; J. Chen

1991-01-01

328

Model Based Fault Detection of an Electro-Hydraulic Cylinder Phanindra Garimella and Bin Yao  

E-print Network

of the proposed scheme. I. INTRODUCTION Hydraulic systems are widely used in industrial appli- cations because- sion control [3], [4], material testing [5], industrial hydraulic systems [6] and hydraulic brakingModel Based Fault Detection of an Electro-Hydraulic Cylinder Phanindra Garimella and Bin Yao

Yao, Bin

329

Modelling of gearbox dynamics under time-varying nonstationary load for distributed fault detection and diagnosis  

Microsoft Academic Search

Fault detection and diagnosis in mechanical systems during their time-varying nonstationary operation is one of the most challenging issues. In the last two decades or so researches have noticed that machines work in nonstationary load\\/speed conditions during their normal operation. Diagnostic features for gearboxes were found to be load dependent. This was experimentally confirmed by a smearing effect in the

Walter Bartelmus; Fakher Chaari; Radoslaw Zimroz; Mohamed Haddar

2010-01-01

330

APPLICATION OF WAVELET PACKET ANALYSIS FOR FAULT DETECTION IN ELECTROMECHANICAL SYSTEMS BASED ON TORSIONAL VIBRATION MEASUREMENT  

Microsoft Academic Search

This paper primarily focuses on detecting electrical faults in turbine generator sets by monitoring torsional vibrations with the help of the non-contact measurement technique and analysing the data acquired from torsional vibration meter. Torsional vibrations in shaft trains can be excited by periodic excitation due to a variety of electromagnetic disturbances or unsteady flow in large steam turbine generator sets

X. Li; L. Qu; G. Wen; C. Li

2003-01-01

331

Coulomb and viscous friction fault detection with application to a pneumatic actuator  

E-print Network

Coulomb and viscous friction fault detection with application to a pneumatic actuator W.B. Dunbar changes. The procedure is illustrated on a high precision servo pneumatic cylinder that drives in this pa- per is designed and illustrated on a servo pneumatic cylin- der that drives an air bearing mass

Dunbar, William

332

Disturbance Attenuation Observer in Time-Delay Nonlinear Systems with Application to Automotive Engine Fault Detection  

Microsoft Academic Search

A Time Delay Observer (TDO) is proposed in order to attenuate the effects of system and output disturbances on estimation error dynamics. This is an important issue in robust fault detection because the effect of disturbances on the error dynamics could lead to false alarms which must be avoided as much as possible. The principle here is that the output

Wen Chen; Mehrdad Saif

2003-01-01

333

Synchronous Machine Faults Detection and Diagnosis for Electro-mechanical Actuators  

E-print Network

Synchronous Machine Faults Detection and Diagnosis for Electro-mechanical Actuators in Aeronautics not require additional material or sensors since they are based on the signals already monitored that becomes more and more popular in aeronautics, and on a 9-slots 8-poles PMSM used in critical application

Boyer, Edmond

334

Fault detection and diagnostics for non-intrusive monitoring using motor harmonics  

Microsoft Academic Search

Harmonic analysis of motor current has been used to track the speed of motors for sensorless control. Algorithms exist that track the speed of a motor given a dedicated stator current measurement, for example. Harmonic analysis has also been applied for diagnostic detection of electro-mechanical faults such as damaged bearings and rotor eccentricity. This paper demonstrates the utility of harmonic

Uzoma A. Orji; Z. Remscrim; C. Laughman; S. B. Leeb; W. Wichakool; C. Schantz; R. Cox; J. L. Kirtley; L. K. Norford

2010-01-01

335

Non-Stationary Spectral Estimation for Wind Turbine Induction Generator Faults Detection  

E-print Network

and performance and reduce wind turbine operating and maintenance costs. They are one of the huge issues that faceNon-Stationary Spectral Estimation for Wind Turbine Induction Generator Faults Detection El Houssin- rine current turbine farms implies to minimize and predict maintenance operations. In direct

Paris-Sud XI, Université de

336

Kalman Filter Innovation Sequence Based Fault Detection in LEO Satellite Attitude Determination and Control System  

Microsoft Academic Search

In this paper, fault detection algorithm for LEO satellite attitude determination and control system using an approach for checking the statistical characteristics of Extended Kalman filter (EKF) innovation sequence is proposed. It is based on given statistics for the mathematical expectation of the spectral norm of the normalized innovation matrix of the EKF. The attitude dynamics of the LEO satellite

A. Okatan; Ch. Hajiyev; U. Hajiyeva

2007-01-01

337

An ILP formulation to Unify Power Efficiency and Fault Detection at Register-Transfer Level  

Microsoft Academic Search

As the integration level and clock speed of VLSI devices keep rising, power consumption of those devices increases dramatically. At the same time, shrinking size of transistors that enables denser and smaller chips running at faster clock speeds makes devices more susceptible to environment-induced faults. Both power reduction and concurrent error detection are becoming enabling technologies in very deep sub

Yu Liu; Kaijie Wu

2009-01-01

338

Characterization of fault recovery through fault injection on FTMP  

NASA Technical Reports Server (NTRS)

The development of fault-injection procedures and statistical analysis techniques to characterize the fault recovery of fault-tolerant systems is described. Pin-level fault-injection was conducted on a fault-tolerant microprocessor computer in order to generate data to assess the utility of current fault-injection sampling methods. The validity of common reliability-modeling assumptions concerning the statistical distribution of recovery times is investigated. A multiple comparison analysis for detecting behavior variations, and a distribution fitting for determining the best fit for the data were conducted. It is observed that the detection behavior is not homogeneous across all data sets, and that none of the factors under experimental control can account for the observed groupings of behavior. It is determined that no single distribution fits all the data sets, and that stratified random sampling and statistically robust parameter-estimation techniques are required to characterize fault detection time.

Finelli, George B.

1987-01-01

339

Model-based adaptive frequency estimator for gear crack fault detection  

Microsoft Academic Search

Detection of gear cracks from vibration data is a difficult task. This paper investigates an alternative to the linear predictor residual fault detection based on the nonlinear adaptive control system concept of frequency esti- mators. The frequency estimator model takes advantage of the sinusoidal nature of vibration and adapts the system model during operation. The low-computational requirements, no-priori knowledge, sinusoidal-based

Geoff McDonald; Qing Zhao

2011-01-01

340

Evaluation of error detection schemes using fault injection by heavy-ion radiation  

Microsoft Academic Search

Several concurrent error detection schemes suitable for a watch-dog processor were evaluated by fault injection. Soft errors were induced into a MC6809E microprocessor by heavy-ion radiation from a Californium-252 source. Recordings of error behavior were used to characterize the errors as well as to determine coverage and latency for the various error detection schemes. The error recordings were used as

U. Gunneflo; Johan Karlsson; Jan Torin

1989-01-01

341

Method for Detection of Mycoplasma.  

National Technical Information Service (NTIS)

A method is described for detecting mycoplasma infection in a sample by contacting the sample with labeled oligonucleotides, then measuring incorporation (if any) of the label into mycoplasma RNA. One preferred embodiment of the invention relates to a met...

D. Geselowitz, L. Neckers, L. Olsen

1992-01-01

342

An experiment in software fault elimination and fault tolerance  

SciTech Connect

Three primary approaches have been taken in developing methods to improve software reliability: fault avoidance, fault elimination and fault tolerance. This study investigates the error detection obtained by application of two of these approaches, fault tolerance and fault elimination, on a set of independently developed versions of a program. Different fault detection techniques following each approach are used to provide a broad exposure of each approach on the versions. The fault detection techniques chosen were multi-version voting, programmer-inserted run-time assertions, testing, code reading of uncommented code by stepwise abstraction and static data flow analysis. Voting and run-time assertions are most commonly associated with fault tolerance. Testing, code reading and static data flow analysis are most commonly associated with fault elimination. After application of the techniques following each approach, the errors detected and the circumstances of detection were analyzed as a means of characterizing the differences between the approaches. The results of this study provide insight on a series of research questions. The results demonstrate weaknesses in the fault tolerance approach and specifically in the multi-version voting method. In particular, the results demonstrate that voting of untested software may produce an insufficient improvement in the probability of producing a correct result to consider such use in systems where reliability is important. Voting is not to be a substitute for testing. Examination of the faults detected in this experiment show that the majority of faults were detected by only one technique. The results of this study suggest a series of questions for further research. For example, research is needed on how to broaden the classes of faults detected by each technique.

Shimeall, T.J.

1989-01-01

343

A Parametric Spectral Estimator for Faults Detection in Induction Machines  

E-print Network

), and is a set of parameters that must be estimated in order to determine the induction machine health condition class contains several algorithms like the Prony and Pisarenko methods. The use of these methods

Boyer, Edmond

344

A ball bearing fault diagnosis method based on wavelet and EMD energy entropy mean  

Microsoft Academic Search

According to the non-stationary characteristics of ball bearing fault vibration signals, a ball bearing fault diagnosis method based on wavelet and empirical mode decomposition (EMD), energy entropy mean is put forward in this paper. Firstly, original acceleration vibration signals are decomposed into a finite number of stationary intrinsic mode functions (IMFs) and wavelet components, then the concept of energy entropy

Farshid Tavakkoli; Mohammad Teshnehlab

2007-01-01

345

A Safety Analysis Method Using Fault Tree Analysis and Petri Nets  

Microsoft Academic Search

In this paper, we describe a safety analysis method that utilizes two models, namely, Petri nets to model the behavioral aspects of a system, and fault tree analysis to model failure and hence unacceptable behaviors of a system. Using petri nets and fault tree analysis, we should be able to perform both forward and backward reachability analyses that are related

Hassan Reza; Malvika Pimple; Varun Krishna; Jared Hildle

2009-01-01

346

An expert system for fault detection and diagnosis  

E-print Network

Major Subject: Electrical Engineering AN EXPERT SYSTEM FOR I AIJLT DETECTION AND DIAGNOSIS A Thesis by PREDRAG SPASOJEVIC Approv d as to style and content by; (, . I Mladen Kezunovic (Chair of ommitt R. Don Russell Ali Abur (Member) / /$t.... Current Research Status B. Thesis Approach C. Thesis Organize. tion . DESIGN CONCEPT A. The Problem Formulation B. Design Requirements C. Proposed Expert System Organization D. Design Approach E. Conclusion KNOWLEDGE ACQUISITION (KA) A...

Spasojevic, Predrag

2012-06-07

347

Enhancement of signal denoising and multiple fault signatures detecting in rotating machinery using dual-tree complex wavelet transform  

NASA Astrophysics Data System (ADS)

In order to enhance the desired features related to some special type of machine fault, a technique based on the dual-tree complex wavelet transform (DTCWT) is proposed in this paper. It is demonstrated that DTCWT enjoys better shift invariance and reduced spectral aliasing than second-generation wavelet transform (SGWT) and empirical mode decomposition by means of numerical simulations. These advantages of the DTCWT arise from the relationship between the two dual-tree wavelet basis functions, instead of the matching of the used single wavelet basis function to the signal being analyzed. Since noise inevitably exists in the measured signals, an enhanced vibration signals denoising algorithm incorporating DTCWT with NeighCoeff shrinkage is also developed. Denoising results of vibration signals resulting from a crack gear indicate the proposed denoising method can effectively remove noise and retain the valuable information as much as possible compared to those DWT- and SGWT-based NeighCoeff shrinkage denoising methods. As is well known, excavation of comprehensive signatures embedded in the vibration signals is of practical importance to clearly clarify the roots of the fault, especially the combined faults. In the case of multiple features detection, diagnosis results of rolling element bearings with combined faults and an actual industrial equipment confirm that the proposed DTCWT-based method is a powerful and versatile tool and consistently outperforms SGWT and fast kurtogram, which are widely used recently. Moreover, it must be noted, the proposed method is completely suitable for on-line surveillance and diagnosis due to its good robustness and efficient algorithm.

Wang, Yanxue; He, Zhengjia; Zi, Yanyang

2010-01-01

348

Fault Detection in Dynamic Systems Using the Largest Lyapunov Exponent  

E-print Network

A complete method for calculating the largest Lyapunov exponent is developed in this thesis. For phase space reconstruction, a time delay estimator based on the average mutual information is discussed first. Then, embedding dimension is evaluated...

Sun, Yifu

2012-10-19

349

Fault detection, isolation, and recovery for autonomous parafoils  

E-print Network

Autonomous precision airdrop systems are widely used to deliver supplies to remote locations. This aerial delivery method provides a safety and logistical advantage over traditional ground- or helicopter-based payload ...

Stoeckle, Matthew Robert

2014-01-01

350

Disk Crack Detection for Seeded Fault Engine Test  

NASA Technical Reports Server (NTRS)

Work was performed to develop and demonstrate vibration diagnostic techniques for the on-line detection of engine rotor disk cracks and other anomalies through a real engine test. An existing single-degree-of-freedom non-resonance-based vibration algorithm was extended to a multi-degree-of-freedom model. In addition, a resonance-based algorithm was also proposed for the case of one or more resonances. The algorithms were integrated into a diagnostic system using state-of-the- art commercial analysis equipment. The system required only non-rotating vibration signals, such as accelerometers and proximity probes, and the rotor shaft 1/rev signal to conduct the health monitoring. Before the engine test, the integrated system was tested in the laboratory by using a small rotor with controlled mass unbalances. The laboratory tests verified the system integration and both the non-resonance and the resonance-based algorithm implementations. In the engine test, the system concluded that after two weeks of cycling, the seeded fan disk flaw did not propagate to a large enough size to be detected by changes in the synchronous vibration. The unbalance induced by mass shifting during the start up and coast down was still the dominant response in the synchronous vibration.

Luo, Huageng; Rodriguez, Hector; Hallman, Darren; Corbly, Dennis; Lewicki, David G. (Technical Monitor)

2004-01-01

351

Automatic Channel Fault Detection and Diagnosis System for a Small Animal APD-Based Digital PET Scanner  

E-print Network

Fault detection and diagnosis is critical to many applications in order to ensure proper operation and performance over time. Positron emission tomography (PET) systems that require regular calibrations by qualified scanner operators are good candidates for such continuous improvements. Furthermore, for scanners employing one-to-one coupling of crystals to photodetectors to achieve enhanced spatial resolution and contrast, the calibration task is even more daunting because of the large number of independent channels involved. To cope with the additional complexity of the calibration and quality control procedures of these scanners, an intelligent system (IS) was designed to perform fault detection and diagnosis (FDD) of malfunctioning channels. The IS can be broken down into four hierarchical modules: parameter extraction, channel fault detection, fault prioritization and diagnosis. Of these modules, the first two have previously been reported and this paper focuses on fault prioritization and diagnosis. The ...

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

2014-01-01

352

NMESys: An expert system for network fault detection  

NASA Technical Reports Server (NTRS)

The problem of network management is becoming an increasingly difficult and challenging task. It is very common today to find heterogeneous networks consisting of many different types of computers, operating systems, and protocols. The complexity of implementing a network with this many components is difficult enough, while the maintenance of such a network is an even larger problem. A prototype network management expert system, NMESys, implemented in the C Language Integrated Production System (CLIPS). NMESys concentrates on solving some of the critical problems encountered in managing a large network. The major goal of NMESys is to provide a network operator with an expert system tool to quickly and accurately detect hard failures, potential failures, and to minimize or eliminate user down time in a large network.

Nelson, Peter C.; Warpinski, Janet

1991-01-01

353

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

NASA Technical Reports Server (NTRS)

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.

Lancraft, R. E.

1985-01-01

354

The application of modern signal processing techniques to rotor fault detection and location within three phase induction motors  

Microsoft Academic Search

Previous work at The Robert Gordon University has shown that faults within the rotors of large three phase induction motors, such as broken rotor bars, can be detected by monitoring and analysing the line current taken by the machine during a no-load starting transient. This line current has been shown to contain frequency components which are indicative of these fault

R. Burnett; J. F. Watson; S. Elder

1995-01-01

355

Detection of Generalized-Roughness Bearing Fault by Spectral-Kurtosis Energy of Vibration or Current Signals  

Microsoft Academic Search

Generalized roughness is the most common damage occurring to rolling bearings. It produces a frequency spreading of the characteristic fault frequencies, thus making it difficult to detect with spectral or envelope analysis. A statistical analysis of typical bearing faults is proposed here in order to identify the spreading bandwidth related to specific conditions, relying on current or vibration measurements only.

Fabio Immovilli; Marco Cocconcelli; Alberto Bellini; Riccardo Rubini

2009-01-01

356

Fault detection of aircraft system with random forest algorithm and similarity measure.  

PubMed

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

Lee, Sanghyuk; Park, Wookje; Jung, Sikhang

2014-01-01

357

Test Suite Reduction for Fault Detection and Localization: A Combined Approach  

E-print Network

, we investigate the effect of different test reduction methods on the performance of fault of test suites with various reduction sizes, followed by how reduced test suites perform with actual. But the repetitive use and continuous maintenance of test suites used for regression testing is hard since these test

Beszedes, Árpád

358

Fault detection using a two-model test for changes in the parameters of an autoregressive time series  

NASA Technical Reports Server (NTRS)

This article describes an investigation of a statistical hypothesis testing method for detecting changes in the characteristics of an observed time series. The work is motivated by the need for practical automated methods for on-line monitoring of Deep Space Network (DSN) equipment to detect failures and changes in behavior. In particular, on-line monitoring of the motor current in a DSN 34-m beam waveguide (BWG) antenna is used as an example. The algorithm is based on a measure of the information theoretic distance between two autoregressive models: one estimated with data from a dynamic reference window and one estimated with data from a sliding reference window. The Hinkley cumulative sum stopping rule is utilized to detect a change in the mean of this distance measure, corresponding to the detection of a change in the underlying process. The basic theory behind this two-model test is presented, and the problem of practical implementation is addressed, examining windowing methods, model estimation, and detection parameter assignment. Results from the five fault-transition simulations are presented to show the possible limitations of the detection method, and suggestions for future implementation are given.

Scholtz, P.; Smyth, P.

1992-01-01

359

Self-organizing maps for automatic fault detection in a vehicle cooling system  

Microsoft Academic Search

A telematic based system for enabling automatic fault detection of a population of vehicles is proposed. To avoid sending huge amounts of data over the telematics gateway, the idea is to use low-dimensional representations of sensor values in sub-systems in a vehicle. These low-dimensional representations are then compared between similar systems in a fleet. If a representation in a vehicle

Magnus Svensson; Stefan Byttner; Thorsteinn Rögnvaldsson

2008-01-01

360

Chaotic Extension Neural Network Theory-Based XXY Stage Collision Fault Detection Using a Single Accelerometer Sensor.  

PubMed

The collision fault detection of a XXY stage is proposed for the first time in this paper. The stage characteristic signals are extracted and imported into the master and slave chaos error systems by signal filtering from the vibratory magnitude of the stage. The trajectory diagram is made from the chaos synchronization dynamic error signals E1 and E2. The distance between characteristic positive and negative centers of gravity, as well as the maximum and minimum distances of trajectory diagram, are captured as the characteristics of fault recognition by observing the variation in various signal trajectory diagrams. The matter-element model of normal status and collision status is built by an extension neural network. The correlation grade of various fault statuses of the XXY stage was calculated for diagnosis. The dSPACE is used for real-time analysis of stage fault status with an accelerometer sensor. Three stage fault statuses are detected in this study, including normal status, Y collision fault and X collision fault. It is shown that the scheme can have at least 75% diagnosis rate for collision faults of the XXY stage. As a result, the fault diagnosis system can be implemented using just one sensor, and consequently the hardware cost is significantly reduced. PMID:25405512

Hsieh, Chin-Tsung; Yau, Her-Terng; Wu, Shang-Yi; Lin, Huo-Cheng

2014-01-01

361

Comparison of chiller models for use in model-based fault detection  

SciTech Connect

Selecting the model is an important and essential step in model based fault detection and diagnosis (FDD). Factors that are considered in evaluating a model include accuracy, training data requirements, calibration effort, generality, and computational requirements. The objective of this study was to evaluate different modeling approaches for their applicability to model based FDD of vapor compression chillers. Three different models were studied: the Gordon and Ng Universal Chiller model (2nd generation) and a modified version of the ASHRAE Primary Toolkit model, which are both based on first principles, and the DOE-2 chiller model, as implemented in CoolTools{trademark}, which is empirical. The models were compared in terms of their ability to reproduce the observed performance of an older, centrifugal chiller operating in a commercial office building and a newer centrifugal chiller in a laboratory. All three models displayed similar levels of accuracy. Of the first principles models, the Gordon-Ng model has the advantage of being linear in the parameters, which allows more robust parameter estimation methods to be used and facilitates estimation of the uncertainty in the parameter values. The ASHRAE Toolkit Model may have advantages when refrigerant temperature measurements are also available. The DOE-2 model can be expected to have advantages when very limited data are available to calibrate the model, as long as one of the previously identified models in the CoolTools library matches the performance of the chiller in question.

Sreedharan, Priya; Haves, Philip

2001-06-07

362

Bridge Fault Simulation Strategies for CMOS Integrated Circuits Brian Chess  

E-print Network

circuit. The bridge fault transforms the two gates for which the bridged wires are outputs into a singleBridge Fault Simulation Strategies for CMOS Integrated Circuits Brian Chess Tracy Larrabee \\Lambda present a theorem for detecting feedback bridge faults. We discuss two different methods of bridge fault

Larrabee, Tracy

363

Fault Detection in Distributed Climate Sensor Networks using Dynamic Bayesian Networks  

SciTech Connect

The Atmospheric Radiation Measurement program operated by U.S. Department of Energy is one of the largest climate research programs dedicated to the collection of long-term continuous measurements of cloud properties and other key components of the earth’s climate system. Given the critical role that collected ARM data plays in the analysis of atmospheric processes and conditions and in the enhancement and evaluation of global climate models, the production and distribution of high-quality data is one of ARM’s primary mission objectives. Fault detection in ARM’s distributed sensor network is one critical ingredient towards maintaining high quality and useful data. We are modeling ARM’s distributed sensor network as a dynamic Bayesian network where key measurements are mapped to Bayesian network variables. We then define the conditional dependencies between variables by discovering highly correlated variable pairs from historical data. The resultant dynamic Bayesian network provides an automated approach to identifying whether certain sensors are malfunctioning or failing in the distributed sensor network. A potential fault or failure is detected when an observed measurement is not consistent with its expected measurement and the observed measurements of other related sensors in the Bayesian network. We present some of our experiences and promising results with the fault detection dynamic Bayesian network.

Chin, George; Choudhury, Sutanay; Kangas, Lars J.; McFarlane, Sally A.; Marquez, Andres

2010-12-07

364

A method of multi-class faults classification based-on Mahalanobis-Taguchi system using vibration signals  

Microsoft Academic Search

In this paper, an improved Mahalanobis-Taguchi system based fault diagnosis scheme is presented, vibration signals are used as the signal resource. Mahalanobis-Taguchi System is utilized for fault clustering method in order to classify faults into different categories, Lipschitz Exponents are used to extract characteristic vectors. Firstly, the procedure of implementing Mahalanobis-Taguchi System is introduced, a multi-class faults classification method is

Jiangtao Ren; Yuanwen Cai; Xiaochen Xing; Jing Chen

2011-01-01

365

Comparing Detection Methods for Software Requirements Inspections: A Replicated Experiment  

Microsoft Academic Search

Software requirements specifications (SRS) are often validated manually. One such process is inspection, in which several reviewers independently analyze all or part of the specification and search for faults. These faults are then collected at a meeting of the reviewers and author(s). Usually, reviewers use Ad Hoc or Checklist methods to uncover faults. These methods force all reviewers to rely

Adam A. Porter; Lawrence G. Votta; Victor R. Basili

1995-01-01

366

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

NASA Technical Reports Server (NTRS)

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 chances of recovery from any hardware or software fault is detailed. A generic fault detection and correction software structure is used, allowing additions, deletions, and adjustments to fault detection and correction rules. This software structure is fed by in-line fault tests that are also able to take appropriate actions to avoid corruption of the data stream.

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

2007-01-01

367

Efficient Detection on Stochastic Faults in PLC Based Automated Assembly Systems With Novel Sensor Deployment and Diagnoser Design  

E-print Network

In this dissertation, we proposed solutions on novel sensor deployment and diagnoser design to efficiently detect stochastic faults in PLC based automated systems First, a fuzzy quantitative graph based sensor deployment was called upon to model...

Wu, Zhenhua

2012-07-16

368

A hybrid system for fault detection and sensor fusion based on fuzzy clustering and artificial immune systems  

E-print Network

the sensor signals is generated by the fusion engine. The information provided from the previous two phases is used for fault detection in the third phase based on the Artificial Immune System (AIS) negative selection mechanism. The simulations...

Jaradat, Mohammad Abdel Kareem Rasheed

2007-04-25

369

Fault-tolerant linear optics quantum computation by error-detecting quantum state transfer  

E-print Network

A scheme for linear optical implementation of fault-tolerant quantum computation is proposed, which is based on an error-detecting code. Each computational step is mediated by transfer of quantum information into an ancilla system embedding error-detection capability. Photons are assumed to be subjected to both photon loss and depolarization, and the threshold region of their strengths for scalable quantum computation is obtained, together with the amount of physical resources consumed. Compared to currently known results, the present scheme reduces the resource requirement, while yielding a comparable threshold region.

Jaeyoon Cho

2006-12-11

370

Feature Extraction using Wavelet Transform for Multi-class Fault Detection of Induction Motor  

NASA Astrophysics Data System (ADS)

In this paper the theoretical aspects and feature extraction capabilities of continuous wavelet transform (CWT) and discrete wavelet transform (DWT) are experimentally verified from the point of view of fault diagnosis of induction motors. Vertical frame vibration signal is analyzed to develop a wavelet based multi-class fault detection scheme. The redundant and high dimensionality information of CWT makes it computationally in-efficient. Using greedy-search feature selection technique (Greedy-CWT) the redundancy is eliminated to a great extent and found much superior to the widely used DWT technique, even in presence of high level of noise. The results are verified using MLP, SVM, RBF classifiers. The feature selection technique has enabled determination of the most relevant CWT scales and corresponding coefficients. Thus, the inherent limitations of CWT like proper selection of scales and redundant information are eliminated. In the present investigation `db8' is found as the best mother wavelet, due to its long period and higher number of vanishing moments, for detection of motor faults.

Chattopadhyay, P.; Konar, P.

2014-01-01

371

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

NASA Technical Reports Server (NTRS)

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.

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

2010-01-01

372

Paleostress reconstruction from calcite twin and fault-slip data using the multiple inverse method in the East Walanae fault zone: Implications for the Neogene contraction in South Sulawesi, Indonesia  

NASA Astrophysics Data System (ADS)

A new approach for paleostress analysis using the multiple inverse method with calcite twin data including untwinned e-plane was performed in the East Walanae fault (EWF) zone in South Sulawesi, Indonesia. Application of untwinned e-plane data of calcite grain to constrain paleostress determination is the first attempt for this method. Stress states caused by the collision of the south-east margin of Sundaland with the Australian microcontinents during the Pliocene were successfully detected from a combination of calcite-twin data and fault-slip data. This Pliocene NE-SW-to-E-W-directed maximum compression activated the EWF as a reverse fault with a dextral component of slip with pervasive development of secondary structures in the narrow zone between Bone Mountain and Walanae Depression.

Jaya, Asri; Nishikawa, Osamu

2013-10-01

373

Analysis of Space Shuttle Ground Support System Fault Detection, Isolation, and Recovery Processes and Resources  

NASA Technical Reports Server (NTRS)

As part of the FDIR (Fault Detection, Isolation, and Recovery) Project for the Constellation Program, a task was designed within the context of the Constellation Program FDIR project called the Legacy Benchmarking Task to document as accurately as possible the FDIR processes and resources that were used by the Space Shuttle ground support equipment (GSE) during the Shuttle flight program. These results served as a comparison with results obtained from the new FDIR capability. The task team assessed Shuttle and EELV (Evolved Expendable Launch Vehicle) historical data for GSE-related launch delays to identify expected benefits and impact. This analysis included a study of complex fault isolation situations that required a lengthy troubleshooting process. Specifically, four elements of that system were considered: LH2 (liquid hydrogen), LO2 (liquid oxygen), hydraulic test, and ground special power.

Gross, Anthony R.; Gerald-Yamasaki, Michael; Trent, Robert P.

2009-01-01

374

Survey of Anomaly Detection Methods  

SciTech Connect

This survey defines the problem of anomaly detection and provides an overview of existing methods. The methods are categorized into two general classes: generative and discriminative. A generative approach involves building a model that represents the joint distribution of the input features and the output labels of system behavior (e.g., normal or anomalous) then applies the model to formulate a decision rule for detecting anomalies. On the other hand, a discriminative approach aims directly to find the decision rule, with the smallest error rate, that distinguishes between normal and anomalous behavior. For each approach, we will give an overview of popular techniques and provide references to state-of-the-art applications.

Ng, B

2006-10-12

375

Method for detecting toxic gases  

DOEpatents

A method is disclosed which is capable of detecting low concentrations of a pollutant or other component in air or other gas. This method utilizes a combination of a heating filament having a catalytic surface of a noble metal for exposure to the gas and producing a derivative chemical product from the component. An electrochemical sensor responds to the derivative chemical product for providing a signal indicative of the product. At concentrations in the order of about 1-100 ppm of tetrachloroethylene, neither the heating filament nor the electrochemical sensor is individually capable of sensing the pollutant. In the combination, the heating filament converts the benzyl chloride to one or more derivative chemical products which may be detected by the electrochemical sensor. 6 figures.

Stetter, J.R.; Zaromb, S.; Findlay, M.W. Jr.

1991-10-08

376

Application of data fusion method to fault diagnosis of nuclear power plant  

NASA Astrophysics Data System (ADS)

The work condition of nuclear power plant (NPP) is very bad, which makes it has faults easily. In order to diagnose the faults real time, the fusion diagnosis system is built. The data fusion fault diagnosis system adopts data fusion method and divides the fault diagnosis into three levels, which are data fusion level, feature level and decision level. The feature level uses three parallel neural networks whose structures are the same. The purpose of using neural networks is mainly to get basic probability assignment (BPA) of D-S evidence theory, and the neural networks in feature level are used for local diagnosis. D-S evidence theory is adopted to integrate the local diagnosis results in decision level. The reactor coolant system is the study object and we choose 2# steam generator U-tubes break of the reactor coolant system as a diagnostic example. The experiments prove that the fusion diagnosis system can satisfy the fault diagnosis requirement of complicated system, and verify that the fusion fault diagnosis system can realize the fault diagnosis of NPP on line timely.

Xie, Chun-Li; Xia, Hong; Liu, Yong-Kuo

2005-03-01

377

Automatic Channel Fault Detection and Diagnosis System for a Small Animal APD-Based Digital PET Scanner  

E-print Network

Fault detection and diagnosis is critical to many applications in order to ensure proper operation and performance over time. Positron emission tomography (PET) systems that require regular calibrations by qualified scanner operators are good candidates for such continuous improvements. Furthermore, for scanners employing one-to-one coupling of crystals to photodetectors to achieve enhanced spatial resolution and contrast, the calibration task is even more daunting because of the large number of independent channels involved. To cope with the additional complexity of the calibration and quality control procedures of these scanners, an intelligent system (IS) was designed to perform fault detection and diagnosis (FDD) of malfunctioning channels. The IS can be broken down into four hierarchical modules: parameter extraction, channel fault detection, fault prioritization and diagnosis. Of these modules, the first two have previously been reported and this paper focuses on fault prioritization and diagnosis. The purpose of the fault prioritization module is to help the operator to zero in on the faults that need immediate attention. The fault diagnosis module will then identify the causes of the malfunction and propose an explanation of the reasons that lead to the diagnosis. The FDD system was implemented on a LabPET avalanche photodiode (APD)-based digital PET scanner. Experiments demonstrated a FDD Sensitivity of 99.3 % (with a 95% confidence interval (CI) of: [98.7, 99.9]) for major faults. Globally, the Balanced Accuracy of the diagnosis for varying fault severities is 92 %. This suggests the IS can greatly benefit the operators in their maintenance task.

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

2014-06-16

378

Implementation and testing of a fault detection software tool for improving control system performance in a large commercial building  

SciTech Connect

This paper describes a model-based, feedforward control scheme that can detect faults in the controlled process and improve control performance over traditional PID control. The tool uses static simulation models of the system under control to generate feed-forward control action, which acts as a reference of correct operation. Faults that occur in the system cause discrepancies between the feedforward models and the controlled process. The scheme facilitates detection of faults by monitoring the level of these discrepancies. We present results from the first phase of tests on a dual-duct air-handling unit installed in a large office building in San Francisco. We demonstrate the ability of the tool to detect a number of preexisting faults in the system and discuss practical issues related to implementation.

Salsbury, T.I.; Diamond, R.C.

2000-05-01

379

Development of New Whole Building Fault Detection and Diagnosis Techniques for Commissioning Persistence  

E-print Network

and compared through tests in simulation and real buildings. The impacts of the factors including calibrated simulation model accuracy, fault severity, the time of fault occurrence, reference control change magnitude setting, and fault period length...

Lin, Guanjing

2012-12-07

380

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

NASA Astrophysics Data System (ADS)

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 < 1016 at/cm-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 LO 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.

Piluso, N.; Camarda, M.; La Via, F.

2014-10-01

381

Fault finder  

DOEpatents

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.

Bunch, Richard H. (1614 NW. 106th St., Vancouver, WA 98665)

1986-01-01

382

Bearing fault detection and diagnosis based on order tracking and Teager-Huang transform  

Microsoft Academic Search

The vibration signal of the run-up or run-down process is more complex than that of the stationary process. A novel approach\\u000a to fault diagnosis of roller bearing under run-up condition based on order tracking and Teager-Huang transform (THT) is presented.\\u000a This method is based on order tracking, empirical mode decomposition (EMD) and Teager Kaiser energy operator (TKEO) technique.\\u000a The nonstationary

Hui Li; Yuping Zhang; Haiqi Zheng

2010-01-01

383

Method for detecting toxic gases  

DOEpatents

A method capable of detecting low concentrations of a pollutant or other component in air or other gas, utilizing a combination of a heating filament having a catalytic surface of a noble metal for exposure to the gas and producing a derivative chemical product from the component, and an electrochemical sensor responsive to the derivative chemical product for providing a signal indicative of the product. At concentrations in the order of about 1-100 ppm of tetrachloroethylene, neither the heating filament nor the electrochemical sensor is individually capable of sensing the pollutant. In the combination, the heating filament converts the benzyl chloride to one or more derivative chemical products which may be detected by the electrochemical sensor.

Stetter, Joseph R. (Naperville, IL); Zaromb, Solomon (Hinsdale, IL); Findlay, Jr., Melvin W. (Bolingbrook, IL)

1991-01-01

384

Prony`s method: An efficient tool for the analysis of earth fault currents in Petersen-coil-protected networks  

SciTech Connect

Prony`s method is a technique for estimating the modal components present in a signal. Every modal component is defined by four parameters: frequency, magnitude, phase, and damping. This method is used to analyze earth fault currents in Petersen-coil-protected 20 kV networks. The variations of Prony`s parameters in terms of some of the power system characteristics (distance between the busbar and the fault, fault resistance and capacitive current of the whole network) are presented. It is shown that some of the Prony`s parameters relating to the fault current transient may be useful to determine what kind of fault occurred, and where it did.

Chaari, O.; Bastard, P.; Meunier, M. [Ecole Superieure D`Electricite, Gif-Sur-Yvette (France)] [Ecole Superieure D`Electricite, Gif-Sur-Yvette (France)

1995-07-01

385

Multiple tests for wind turbine fault detection and score fusion using two- level multidimensional scaling (MDS)  

NASA Astrophysics Data System (ADS)

Wind is an important renewable energy source. The energy and economic return from building wind farms justify the expensive investments in doing so. However, without an effective monitoring system, underperforming or faulty turbines will cause a huge loss in revenue. Early detection of such failures help prevent these undesired working conditions. We develop three tests on power curve, rotor speed curve, pitch angle curve of individual turbine. In each test, multiple states are defined to distinguish different working conditions, including complete shut-downs, under-performing states, abnormally frequent default states, as well as normal working states. These three tests are combined to reach a final conclusion, which is more effective than any single test. Through extensive data mining of historical data and verification from farm operators, some state combinations are discovered to be strong indicators of spindle failures, lightning strikes, anemometer faults, etc, for fault detection. In each individual test, and in the score fusion of these tests, we apply multidimensional scaling (MDS) to reduce the high dimensional feature space into a 3-dimensional visualization, from which it is easier to discover turbine working information. This approach gains a qualitative understanding of turbine performance status to detect faults, and also provides explanations on what has happened for detailed diagnostics. The state-of-the-art SCADA (Supervisory Control And Data Acquisition) system in industry can only answer the question whether there are abnormal working states, and our evaluation of multiple states in multiple tests is also promising for diagnostics. In the future, these tests can be readily incorporated in a Bayesian network for intelligent analysis and decision support.

Ye, Xiang; Gao, Weihua; Yan, Yanjun; Osadciw, Lisa A.

2010-04-01

386

Design considerations for flight test of a fault inferring nonlinear detection system algorithm for avionics sensors  

NASA Technical Reports Server (NTRS)

The modifications to the design of a fault inferring nonlinear detection system (FINDS) algorithm to accommodate flight computer constraints and the resulting impact on the algorithm performance are summarized. An overview of the flight data-driven FINDS algorithm is presented. This is followed by a brief analysis of the effects of modifications to the algorithm on program size and execution speed. Significant improvements in estimation performance for the aircraft states and normal operating sensor biases, which have resulted from improved noise design parameters and a new steady-state wind model, are documented. The aircraft state and sensor bias estimation performances of the algorithm's extended Kalman filter are presented as a function of update frequency of the piecewise constant filter gains. The results of a new detection system strategy and failure detection performance, as a function of gain update frequency, are also presented.

Caglayan, A. K.; Godiwala, P. M.; Morrell, F. R.

1986-01-01

387

Orbital maneuvering subsystem functional path analysis for performance monitoring fault detection and annunciation  

NASA Technical Reports Server (NTRS)

The functional paths of the Orbital Maneuver Subsystem (OMS) is defined. The operational flight instrumentation required for performance monitoring, fault detection, and annunciation is described. The OMS is a pressure fed rocket engine propulsion subsystem. One complete OMS shares each of the two auxiliary propulsion subsystem pods with a reaction control subsystem. Each OMS is composed of a pressurization system, a propellant tanking system, and a gimbaled rocket engine. The design, development, and operation of the system are explained. Diagrams of the system are provided.

Keesler, E. L.

1974-01-01

388

Identification Using the Algorithm of Singular Value DECOMPOSITION—AN Application to the Realisation of Dynamic Systems and to Fault Detection and Localisation  

NASA Astrophysics Data System (ADS)

A new algorithm—the generalised singular value decomposition (GSVD)—is used in the field of identification and fault detection and localisation. By using the GSVD a simultaneous factorisation of two matrices Aand Bis possible. Therefore, a state space realisation of a structure can be established from measured data of a real system. The measured data are arranged in Hankel matrices and the parameters of the state space equation can be found with a special procedure using the generalised singular value decomposition. Changes in the dynamic system behaviour that can be detected by new measurements and realisations can be used for fault detection and localisation. A sensitive method for this task is established, with the singular value decomposition in combination with dynamic influence coefficients, that result from a spectral decomposition of the weighting operator.

Lenzen, A.; Waller, H.

1997-05-01

389

Explosives detection system and method  

DOEpatents

A method of detecting explosives in a vehicle includes providing a first rack on one side of the vehicle, the rack including a neutron generator and a plurality of gamma ray detectors; providing a second rack on another side of the vehicle, the second rack including a neutron generator and a plurality of gamma ray detectors; providing a control system, remote from the first and second racks, coupled to the neutron generators and gamma ray detectors; using the control system, causing the neutron generators to generate neutrons; and performing gamma ray spectroscopy on spectra read by the gamma ray detectors to look for a signature indicative of presence of an explosive. Various apparatus and other methods are also provided.

Reber, Edward L. (Idaho Falls, ID); Jewell, James K. (Idaho Falls, ID); Rohde, Kenneth W. (Idaho Falls, ID); Seabury, Edward H. (Idaho Falls, ID); Blackwood, Larry G. (Idaho Falls, ID); Edwards, Andrew J. (Idaho Falls, ID); Derr, Kurt W. (Idaho Falls, ID)

2007-12-11

390

Exoplanet Detection: Radial Velocity Method  

NSDL National Science Digital Library

The Exoplanet Detection: The Radial Velocity Method model simulates the detection of exoplanets by using the radial velocity method and the Doppler effect. In this simulation the exoplanet orbits the star (sun-sized) in circular motion via Kepler's third law.  The radial velocity of the star is determined from the velocity of the exoplanet.  This velocity is then used to calculate the Doppler shift of the Fraunhofer lines of the star.  In practice it is the Doppler shift of the Fraunhofer lines of the star that are detected and from this the radial velocity is inferred.  From this the mass and orbital period and average exoplanet-star separation are determined.  In the simulation the star-exoplanet system is shown as seen from Earth (edge on view) and from space (overhead view), and with the star and exoplanet sizes not shown to the scale of the orbit.  In addition, the Fraunhofer lines are shown.  The radial velocites of stars are such that the Doppler shifts are small, to compensate you may snap to the Na line and use the right-hand side slider to zoom in on that line to see wavelength shift.  The mass of the exoplanet (relative to the mass of Jupiter), the average star-exoplant separation (in AU), and the inclination of the system relative to Earth can be changed. The simulation uses Java 3D, if installed, to render the view the star and exoplanet. If Java 3D is not installed, the simulation will default to simple 3D using Java.

Belloni, Mario

2010-06-29

391

Apparatus for and method of testing an electrical ground fault circuit interrupt device  

DOEpatents

An apparatus for testing a ground fault circuit interrupt device includes a processor, an input device connected to the processor for receiving input from an operator, a storage media connected to the processor for storing test data, an output device connected to the processor for outputting information corresponding to the test data to the operator, and a calibrated variable load circuit connected between the processor and the ground fault circuit interrupt device. The ground fault circuit interrupt device is configured to trip a corresponding circuit breaker. The processor is configured to receive signals from the calibrated variable load circuit and to process the signals to determine a trip threshold current and/or a trip time. A method of testing the ground fault circuit interrupt device includes a first step of providing an identification for the ground fault circuit interrupt device. Test data is then recorded in accordance with the identification. By comparing test data from an initial test with test data from a subsequent test, a trend of performance for the ground fault circuit interrupt device is determined. 17 figs.

Andrews, L.B.

1998-08-18

392

ABARIS: An Adaptable Fault Detection/Recovery Component Framework for Hideyuki Jitsumoto1  

E-print Network

of fault patterns, which could be numerous: for instance, if the fault is transient to a particular process is obviously different when a fault is transient soft- ware one confined in a single process, versus by the fault detector to be a node failure and unnecessary migra- tion might occur whereas it might turn out

393

The Amount and Preferred Orientation of Simple-shear in a Deformation Tensor: Implications for Detecting Shear Zones and Faults with GPS  

NASA Astrophysics Data System (ADS)

At the 2005 Fall Meeting of the American Geophysical Union, Griffiths and Johnson [2005] introduced a method of extracting from the deformation-gradient (and velocity-gradient) tensor the amount and preferred orientation of simple-shear associated with 2-D shear zones and faults. Noting the 2-D is important because the shear zones and faults in Griffiths and Johnson [2005] were assumed non-dilatant and infinitely long, ignoring the scissors- like action along strike associated with shear zones and faults of finite length. Because shear zones and faults can dilate (and contract) normal to their walls and can have a scissors-like action associated with twisting about an axis normal to their walls, the more general method of detecting simple-shear is introduced and called MODES "method of detecting simple-shear." MODES can thus extract from the deformation-gradient (and velocity- gradient) tensor the amount and preferred orientation of simple-shear associated with 3-D shear zones and faults near or far from the Earth's surface, providing improvements and extensions to existing analytical methods used in active tectonics studies, especially strain analysis and dislocation theory. The derivation of MODES is based on one definition and two assumptions: by definition, simple-shear deformation becomes localized in some way; by assumption, the twirl within the deformation-gradient (or the spin within the velocity-gradient) is due to a combination of simple-shear and twist, and coupled with the simple- shear and twist is a dilatation of the walls of shear zones and faults. The preferred orientation is thus the orientation of the plane containing the simple-shear and satisfying the mechanical and kinematical boundary conditions. Results from a MODES analysis are illustrated by means of a three-dimensional diagram, the cricket- ball, which is reminiscent of the seismologist's "beach ball." In this poster, we present the underlying theory of MODES and illustrate how it works by analyzing the three- dimensional displacements measured with the Global Positioning System across the 1999 Chi-Chi earthquake ground rupture in Taiwan. In contrast to the deformation zone in the upper several meters of the ground below the surface detected by Yu et al. [2001], MODES determines the orientation and direction of shift of a shear zone representing the earthquake fault within the upper several hundred or thousand meters of ground below the surface. Thus, one value of the MODES analysis in this case is to provide boundary conditions for dislocation solutions for the subsurface shape of the main rupture during the earthquake.

Johnson, A. M.; Griffiths, J. H.

2007-05-01

394

Fault Detection, Isolation and Recovery (FDIR) Portable Liquid Oxygen Hardware Demonstrator  

NASA Technical Reports Server (NTRS)

The Fault Detection, Isolation and Recovery (FDIR) hardware demonstration will highlight the effort being conducted by Constellation's Ground Operations (GO) to provide the Launch Control System (LCS) with system-level health management during vehicle processing and countdown activities. A proof-of-concept demonstration of the FDIR prototype established the capability of the software to provide real-time fault detection and isolation using generated Liquid Hydrogen data. The FDIR portable testbed unit (presented here) aims to enhance FDIR by providing a dynamic simulation of Constellation subsystems that feed the FDIR software live data based on Liquid Oxygen system properties. The LO2 cryogenic ground system has key properties that are analogous to the properties of an electronic circuit. The LO2 system is modeled using electrical components and an equivalent circuit is designed on a printed circuit board to simulate the live data. The portable testbed is also be equipped with data acquisition and communication hardware to relay the measurements to the FDIR application running on a PC. This portable testbed is an ideal capability to perform FDIR software testing, troubleshooting, training among others.

Oostdyk, Rebecca L.; Perotti, Jose M.

2011-01-01

395

Adaptive Online Testing for Efficient Hard Fault Detection Shantanu Gupta, Amin Ansari, Shuguang Feng and Scott Mahlke  

E-print Network

Adaptive Online Testing for Efficient Hard Fault Detection Shantanu Gupta, Amin Ansari, Shuguang defects. Periodic online testing is a popular technique to detect such failures; however, it tends to impose a heavy testing penalty. In this paper, we propose an adaptive online testing framework

Eustice, Ryan

396

Structural system reliability calculation using a probabilistic fault tree analysis method  

NASA Technical Reports Server (NTRS)

The development of a new probabilistic fault tree analysis (PFTA) method for calculating structural system reliability is summarized. The proposed PFTA procedure includes: developing a fault tree to represent the complex structural system, constructing an approximation function for each bottom event, determining a dominant sampling sequence for all bottom events, and calculating the system reliability using an adaptive importance sampling method. PFTA is suitable for complicated structural problems that require computer-intensive computer calculations. A computer program has been developed to implement the PFTA.

Torng, T. Y.; Wu, Y.-T.; Millwater, H. R.

1992-01-01

397

Immunofluorescence detection methods using microspheres  

NASA Astrophysics Data System (ADS)

Microsphere-based immunoassays were devised for compounds of agricultural and biomedical interest (e.g., digoxin, theophylline, and zearalenone). Commercially available microspheres with surface functional groups for chemical derivatization were used as solid carriers. After immobilizing the target substances, the surface of the haptenized microspheres was blocked by a protein to reduce aspecific binding. Competitive immunoassays were performed using the functionalized microspheres and antibodies labeled with horseradish peroxidase. Immunofluorescence signal amplification was achieved by enzyme-catalyzed reporter deposition (CARD). An epifluorescence microscope, a CCD camera interfaced with a computer, and microscopy image analysis software were employed for quantitative detection of fluorescent light emitted from individual microspheres. Integration of several such immunoassays and application of an optical encoding method enabled multianalyte determination. These immunoassays can also be utilized in an immunosensor array format. This immunoarray format could facilitate miniaturization and automation of multianalyte immunoassays.

Szurdoki, Ferenc; Michael, Karri L.; Agrawal, Divya; Taylor, Laura C.; Schultz, Sandra L.; Walt, David R.

1999-01-01

398

Paleostress Determination Based on Multiple-Inverse Method using Calcite Twins and Fault-Slip Data in the East Walanae Fault Zone South Sulawesi, Indonesia  

NASA Astrophysics Data System (ADS)

Paleostress reconstructions from calcite twin and fault-slip data were performed to constrain the activity of the East Walanae Fault (EWF) South Sulawesi, Indonesia. The multiple-inverse method, which has been widely used with fault-slip data, was applied to calcite twin data in this study. Both independent data sets yield consistent stress states and provides a reliable stress tensors (maximum and minimum principal stresses: ?1and ?3, and stress ratio: ?), a predominance of NE-SW trending ?1and vertical to moderately-south-plunging ?3 with generally low ?. These stress states could have activated the EWF as a reverse fault with a dextral shear component and account for contractional deformation structures and landform around the trace of the fault. Most of the calcite twins and mesoscale faults were activated during the latest stage of folding or later. Based on the morphology and width of twin lamellae in the carbonate rocks, twinning of calcite in the deformation zone along the EWF may have occurred under the temperature of 200° C or lower. Inferred paleostress states around the EWF were most likely generated under the tectonic conditions influenced by the collision of Sulawesi with the Australian fragments since the Late Miocene. Radiocarbon dating from sheared soil collected from the outcrop along a major fault yielded ages between 3050 cal BP and 3990 cal BP suggesting a present activity of the EWF.

Jaya, Asri; Nishikawa, Osamu

2013-04-01

399

Lessons Learned on Implementing Fault Detection, Isolation, and Recovery (FDIR) in a Ground Launch Environment  

NASA Technical Reports Server (NTRS)

This paper's main purpose is to detail issues and lessons learned regarding designing, integrating, and implementing Fault Detection Isolation and Recovery (FDIR) for Constellation Exploration Program (CxP) Ground Operations at Kennedy Space Center (KSC). Part of the0 overall implementation of National Aeronautics and Space Administration's (NASA's) CxP, FDIR is being implemented in three main components of the program (Ares, Orion, and Ground Operations/Processing). While not initially part of the design baseline for the CxP Ground Operations, NASA felt that FDIR is important enough to develop, that NASA's Exploration Systems Mission Directorate's (ESMD's) Exploration Technology Development Program (ETDP) initiated a task for it under their Integrated System Health Management (ISHM) research area. This task, referred to as the FDIIR project, is a multi-year multi-center effort. The primary purpose of the FDIR project is to develop a prototype and pathway upon which Fault Detection and Isolation (FDI) may be transitioned into the Ground Operations baseline. Currently, Qualtech Systems Inc (QSI) Commercial Off The Shelf (COTS) software products Testability Engineering and Maintenance System (TEAMS) Designer and TEAMS RDS/RT are being utilized in the implementation of FDI within the FDIR project. The TEAMS Designer COTS software product is being utilized to model the system with Functional Fault Models (FFMs). A limited set of systems in Ground Operations are being modeled by the FDIR project, and the entire Ares Launch Vehicle is being modeled under the Functional Fault Analysis (FFA) project at Marshall Space Flight Center (MSFC). Integration of the Ares FFMs and the Ground Processing FFMs is being done under the FDIR project also utilizing the TEAMS Designer COTS software product. One of the most significant challenges related to integration is to ensure that FFMs developed by different organizations can be integrated easily and without errors. Software Interface Control Documents (ICDs) for the FFMs and their usage will be addressed as the solution to this issue. In particular, the advantages and disadvantages of these ICDs across physically separate development groups will be delineated.

Ferrell, Bob A.; Lewis, Mark E.; Perotti, Jose M.; Brown, Barbara L.; Oostdyk, Rebecca L.; Goetz, Jesse W.

2010-01-01

400

Realizing the fault diagnostic system in maglev suspension train system (MSTS) based on fuzzy comprehensive evaluation method  

Microsoft Academic Search

Since maglev train system is a large system, it is difficult to diagnose the fault to the whole train extent by traditional method of fault diagnosing. The fuzzy comprehensive evaluation method is usually applied to most large systems, which can consider many factors of a large system. Firstly the principle of fuzzy comprehensive evaluation method is introduced, then concerned about

Zhiqiang Long; Zhiguo Lv; Huajie Hong

2002-01-01

401

Real-time fault detection and isolation in biological wastewater treatment plants.  

PubMed

Automatic fault detection is becoming increasingly important in wastewater treatment plant operation, given the stringent treatment standards and the need to protect the investment costs from the potential damage of an unchecked fault propagating through the plant. This paper describes the development of a real-time Fault Detection and Isolation (FDI) system based on an adaptive Principal Component Analysis (PCA) algorithm, used to compare the current plant operation with a correct performance model based on a reference data set and the output of three ion-specific sensors (Hach-Lange gmbh, Düsseldorf, Germany): two Nitratax NOx UV sensors, in the denitrification tank and downstream of the oxidation tanks, where an Amtax ammonium-N sensor was also installed. The algorithm was initially developed in the Matlab environment and then ported into the LabView 8.20 (National Instruments, Austin, TX, USA) platform for real-time operation using a compact Field Point, a Programmable Automation Controller by National Instruments. The FDI was tested with a large set of operational data with 1 min sampling time from August 2007 through May 2008 from a full-scale plant. After describing the real-time version of the PCA algorithm, this was tested with nine months of operational data which were sequentially processes by the algorithm in order to simulate an on-line operation. The FDI performance was assessed by organizing the sequential data in two differing moving windows: a short-horizon window to test the response to single malfunctions and a longer time-horizon to simulate multiple unrepaired failures. In both cases the algorithm performance was very satisfactory, with a 100% failure detection in the short window case, which decreased to 84% in the long window setting. The short-window performance was very effective in isolating sensor failures and short duration disturbances such as spikes, whereas the long term horizon provided accurate detection of long-term drifts and proved robust enough to allow for some delay in failure recovery. The system robustness is based on the use of multiple statistics which proved instrumental in discriminating among the various causes of malfunctioning. PMID:19934517

Baggiani, F; Marsili-Libelli, S

2009-01-01

402

Fault detection using spectral methods: Wavelets and correlation techniques  

Microsoft Academic Search

Oxides of nitrogen (NOx), particulate matter (PM) and hydrocarbon (HC) emissions are closely regulated by the Environmental Protection Agency (EPA) and California Air Resources Board (ARB). Exhaust gas recirculation (EGR) is one of the in-cylinder NOx control strategies commonly used in diesel engines. EGR valve is an important component in the EGR loop and is used to precisely meter the

Ravindra V Kakade

2011-01-01

403

Analytic Confusion Matrix Bounds for Fault Detection and Isolation Using a Sum-of-Squared- Residuals Approach  

NASA Technical Reports Server (NTRS)

Given a system which can fail in 1 or n different ways, a fault detection and isolation (FDI) algorithm uses sensor data in order to determine which fault is the most likely to have occurred. The effectiveness of an FDI algorithm can be quantified by a confusion matrix, which i ndicates the probability that each fault is isolated given that each fault has occurred. Confusion matrices are often generated with simulation data, particularly for complex systems. In this paper we perform FDI using sums of squares of sensor residuals (SSRs). We assume that the sensor residuals are Gaussian, which gives the SSRs a chi-squared distribution. We then generate analytic lower and upper bounds on the confusion matrix elements. This allows for the generation of optimal sensor sets without numerical simulations. The confusion matrix bound s are verified with simulated aircraft engine data.

Simon, Dan; Simon, Donald L.

2009-01-01

404

Research on fast fault identification method of 10.5 kV/1.5 kA superconducting fault current limiter  

NASA Astrophysics Data System (ADS)

Superconducting fault current limiter (SFCL) is a prospective electric devices connected in series in power grid to limit short-circuit current. A 10.5 kV/1.5 kA 3-phase SFCL with HTS coil of 6.24 mH was developed at IEECAS in China in 2005, which was operated in a local power grid in Hunan province for more than 11,000 h, and integrated lately in a superconducting power substation in Baiyin city in 2011 and is still running safely and reliably. In order to reduce the fault response time and enhance the performance of the SFCL, we analyzed the structure characteristics of the SFCL and discussed the variation of currents and voltages of the HTS coil and the bridge during the fault time. The simulation and tests results of power system validate the feasibility of the fast fault identification method.

Zhang, Zhifeng; Sun, Qiang; Xiao, Liye; Liu, Daqian; Qiu, Ming; Qiu, Qinquan; Zhang, Guomin; Dai, Shaotao; Lin, Liangzhen

2014-09-01

405

Applied change of mean detection techniques for HVAC fault detection and diagnosis and power monitoring  

E-print Network

A signal processing technique, the detection of abrupt changes in a time-series signal, is implemented with two different applications related to energy use in buildings. The first application is a signal pre-processor for ...

Hill, Roger Owen

1995-01-01

406

A Theoretical Method for Computing Near-Fault Ground Motions in Layered Half-Spaces Considering Static Offset Due to Surface Faulting, with a Physical Interpretation of Fling Step and Rupture Directivity  

Microsoft Academic Search

An efficient mathematical method is presented for computing the near- fault strong ground motions in a layered half-space, giving explicit consideration to the static offset due to surface faulting. In addition, the combined effects of \\

Yoshiaki Hisada; Jacobo Bielak

2003-01-01

407

Motion-Based System Identification and Fault Detection and Isolation Technologies for Thruster Controlled Spacecraft  

NASA Technical Reports Server (NTRS)

By analyzing the motions of a thruster-controlled spacecraft, it is possible to provide on-line (1) thruster fault detection and isolation (FDI), and (2) vehicle mass- and thruster-property identification (ID). Technologies developed recently at NASA Ames have significantly improved the speed and accuracy of these ID and FDI capabilities, making them feasible for application to a broad class of spacecraft. Since these technologies use existing sensors, the improved system robustness and performance that comes with the thruster fault tolerance and system ID can be achieved through a software-only implementation. This contrasts with the added cost, mass, and hardware complexity commonly required by FDI. Originally developed in partnership with NASA - Johnson Space Center to provide thruster FDI capability for the X-38 during re-entry, these technologies are most recently being applied to the MIT SPHERES experimental spacecraft to fly on the International Space Station in 2004. The model-based FDI uses a maximum-likelihood calculation at its core, while the ID is based upon recursive least squares estimation. Flight test results from the SPHERES implementation, as flown aboard the NASA KC-1 35A 0-g simulator aircraft in November 2003 are presented.

Wilson, Edward; Sutter, David W.; Berkovitz, Dustin; Betts, Bradley J.; Kong, Edmund; delMundo, Rommel; Lages, Christopher R.; Mah, Robert W.; Papasin, Richard

2003-01-01

408

Fault Detection of a Roller-Bearing System through the EMD of a Wavelet Denoised Signal  

PubMed Central

This paper investigates fault detection of a roller bearing system using a wavelet denoising scheme and proper orthogonal value (POV) of an intrinsic mode function (IMF) covariance matrix. The IMF of the bearing vibration signal is obtained through empirical mode decomposition (EMD). The signal screening process in the wavelet domain eliminates noise-corrupted portions that may lead to inaccurate prognosis of bearing conditions. We segmented the denoised bearing signal into several intervals, and decomposed each of them into IMFs. The first IMF of each segment is collected to become a covariance matrix for calculating the POV. We show that covariance matrices from healthy and damaged bearings exhibit different POV profiles, which can be a damage-sensitive feature. We also illustrate the conventional approach of feature extraction, of observing the kurtosis value of the measured signal, to compare the functionality of the proposed technique. The study demonstrates the feasibility of wavelet-based de-noising, and shows through laboratory experiments that tracking the proper orthogonal values of the covariance matrix of the IMF can be an effective and reliable measure for monitoring bearing fault. PMID:25196008

Ahn, Jong-Hyo; Kwak, Dae-Ho; Koh, Bong-Hwan

2014-01-01

409

Fault Models for Quantum Mechanical Switching Networks  

E-print Network

The difference between faults and errors is that, unlike faults, errors can be corrected using control codes. In classical test and verification one develops a test set separating a correct circuit from a circuit containing any considered fault. Classical faults are modelled at the logical level by fault models that act on classical states. The stuck fault model, thought of as a lead connected to a power rail or to a ground, is most typically considered. A classical test set complete for the stuck fault model propagates both binary basis states, 0 and 1, through all nodes in a network and is known to detect many physical faults. A classical test set complete for the stuck fault model allows all circuit nodes to be completely tested and verifies the function of many gates. It is natural to ask if one may adapt any of the known classical methods to test quantum circuits. Of course, classical fault models do not capture all the logical failures found in quantum circuits. The first obstacle faced when using methods from classical test is developing a set of realistic quantum-logical fault models. Developing fault models to abstract the test problem away from the device level motivated our study. Several results are established. First, we describe typical modes of failure present in the physical design of quantum circuits. From this we develop fault models for quantum binary circuits that enable testing at the logical level. The application of these fault models is shown by adapting the classical test set generation technique known as constructing a fault table to generate quantum test sets. A test set developed using this method is shown to detect each of the considered faults.

Jacob Biamonte; Jeff S. Allen; Marek A. Perkowski

2005-08-19

410

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

NASA Astrophysics Data System (ADS)

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.

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

2011-05-01

411

Fault Diagnosis of Continuous Systems Using Discrete-Event Methods Matthew Daigle, Xenofon Koutsoukos, and Gautam Biswas  

E-print Network

Fault Diagnosis of Continuous Systems Using Discrete-Event Methods Matthew Daigle, Xenofon.j.daigle,xenofon.koutsoukos,gautam.biswas@vanderbilt.edu Abstract-- Fault diagnosis is crucial for ensuring the safe operation of complex engineering systems. Although discrete- event diagnosis methods are used extensively, they do not easily apply to parametric

Koutsoukos, Xenofon D.

412

Application of black-box models to HVAC systems for fault detection  

SciTech Connect

This paper describes the application of black-box models for fault detection and diagnosis (FDD) in heating, ventilating, and air-conditioning (HVAC) systems. In this study, multiple-input/single-output (MISO) ARX models and artificial neural network (ANN) models are used. The ARX models are examined for different processes and subprocesses and compared with each other. Two types of models are established--system models and component models. In the case of system models, the HVAC system as a whole is regarded as a black box instead of as a collection of component models. With the component model type, the components of the HVAC system are regarded as separate black boxes.

Peitsman, H.C. [TNO Building and Construction Research, Delft (Netherlands). Dept. of Indoor Environment, Building Physics and Systems; Bakker, V.E. [Univ. of Twente, Enschede (Netherlands). Dept. of Computer Science

1996-11-01

413

Particle Filters for Real-Time Fault Detection in Planetary Rovers  

NASA Technical Reports Server (NTRS)

Planetary rovers provide a considerable challenge for robotic systems in that they must operate for long periods autonomously, or with relatively little intervention. To achieve this, they need to have on-board fault detection and diagnosis capabilities in order to determine the actual state of the vehicle, and decide what actions are safe to perform. Traditional model-based diagnosis techniques are not suitable for rovers due to the tight coupling between the vehicle's performance and its environment. Hybrid diagnosis using particle filters is presented as an alternative, and its strengths and weakeners are examined. We also present some extensions to particle filters that are designed to make them more suitable for use in diagnosis problems.

Dearden, Richard; Clancy, Dan; Koga, Dennis (Technical Monitor)

2001-01-01

414

On-line fault diagnosis of distribution substations using hybrid cause-effect network and fuzzy rule-based method  

Microsoft Academic Search

A correct and rapid inference is required for practical use of an online fault diagnosis in power substations. This paper proposes a novel approach for on-line fault section estimations and fault types identification using the hybrid cause-effect network\\/fuzzy rule-based method in distribution substations. A cause-effect network, which is well suited to parallel processing, represents the functions of protective relays and

Wen-Hui Chen; Chih-Wen Liu; Men-Shen Tsai

2000-01-01

415

Methodology for on-line incipient fault detection in single-phase squirrel-cage induction motors using artificial neural networks  

Microsoft Academic Search

A novel approach for online detection of incipient faults in single-phase squirrel-cage induction motors through the use of artificial neural networks is presented. The online incipient fault detector is composed of two parts: (1) a disturbance and noise filter artificial neural network to filter out the transient measurements while retaining the steady-state measurements, and (2) a high-order incipient fault detection

MO-yuen Chow; Sui Oi Yee

1991-01-01

416

High-Order Treatment of Fault Boundary Conditions Using Summation-By-Parts Finite Difference Methods  

NASA Astrophysics Data System (ADS)

High-order numerical methods are ideally suited for earthquake problems, which are primarily limited by available memory rather than CPU time, since they require fewer grid points to achieve the same solution accuracy as low-order methods. Though it is relatively straightforward to apply high-order methods in the interior of the domain, it can be challenging to maintain stability and accuracy near boundaries (e.g., the free surface) and internal interfaces (e.g., faults and layer interfaces). This is particularly problematic for earthquake models since numerical errors near faults degrade the global accuracy of the solution, including ground motion predictions. Despite several efforts to develop high-order fault boundary conditions, no codes have demonstrated greater than second-order accuracy for dynamic rupture problems, even on rate-and-state friction problems with smooth solutions. In this work we use summation-by-parts (SBP) finite difference methods along with a simultaneous approximation term (SAT) to achieve a truly high-order method for dynamic ruptures on faults with rate-and-state friction laws [Carpenter et al., JCP 1999; Nordström & Gustafsson JSC 2003; Nordström SISC 2007]. SBP methods use centered spatial differences in the interior and one-sided differences near the boundary. The transition to one-sided differences is done in a particular manner that permits one to provably maintain stability as well as high-order accuracy. In many methods the boundary conditions are strongly enforced by modifying the difference operator at the boundary so that the solution there exactly satisfies the boundary condition. This approach often results in instability when combined with high-order difference schemes. In contrast, the SAT method enforces the boundary conditions in a weak manner by adding a penalty term to the spatially discretized governing equations. Additional complications arise with rate-and-state friction laws, and several finite difference implementations [Bizzarri et al., GJI, 2001; Rojas et al., GJI, 2009] suffer from extreme stiffness that requires the use of implicit time integration schemes for fields on the fault. This is also the case for the SAT method unless the boundary condition is formulated in terms of characteristic variables (i.e., the combination of stresses and velocities associated with waves entering and exiting the fault). With this formulation, the solution can be advanced using fully explicit time-stepping methods.

Kozdon, J. E.; Dunham, E. M.; Nordström, J.

2009-12-01

417

Method For Detecting Biological Agents  

DOEpatents

A sensor is provided including a polymer capable of having an alterable measurable property from the group of luminescence and electrical conductivity, the polymer having an intermediate combination of a recognition element, a tethering element and a property-altering element bound thereto and capable of altering the measurable property, the intermediate combination adapted for subsequent separation from the polymer upon exposure to an agent having an affinity for binding to the recognition element whereupon the separation of the intermediate combination from the polymer results in a detectable change in the alterable measurable property, and, detecting said detectable change in the alterable measurable property.

Chen, Liaohai (Los Alamos, NM); McBranch, Duncan W. (Santa Fe, NM); Wang, Hsing-Lin (Los Alamos, NM); Whitten, David G. (Santa Fe, NM)

2005-12-27

418

Feature Extraction for Data-Driven Fault Detection in Nuclear Power Plants Xin Jin, Robert M. Edwards and Asok Ray  

E-print Network

Feature Extraction for Data-Driven Fault Detection in Nuclear Power Plants Xin Jin, Robert M monitoring of nuclear power plants (NPP) is one of the key issues addressed in nuclear energy safety research is performed during each nuclear power plant refueling outage, which may not be cost effective [1

Ray, Asok

419

Detection and identification of actuator faults in robotic systems based on multiple-model nonlinear state estimation  

Microsoft Academic Search

Modern robotic systems perform elaborate tasks in a complicated environment and have close interactions with humans. Therefore fault detection and isolation (FDI) systems must be carefully designed and implemented on robots in order to guarantee safe and reliable operations. In addition, many high performance robotic controllers require full state feedback; hence it is essential to implement state estimators whenever not

Tesheng Hsiao; Huei-jyun Haung

2009-01-01

420

FPGA-Based Online Detection of Multiple Combined Faults in Induction Motors Through Information Entropy and Fuzzy Inference  

Microsoft Academic Search

The development of monitoring systems for rotating machines is the ability to accurately detect different faults in an incipient state. The most popular rotating machine in industry is the squirrel-cage induction motor, and the failure on such motors may have severe consequences in costs, product quality, and safety. Most of the condition-monitoring techniques for induction motors focus on a single

Rene J. Romero-Troncoso; Ricardo Saucedo-Gallaga; Eduardo Cabal-Yepez; Arturo Garcia-Perez; Roque A. Osornio-Rios; Ricardo Alvarez-Salas; Homero Miranda-Vidales; Nicolas Huber

2011-01-01

421

Model-Based Sensor Fault Detection and Isolation System for Unmanned Ground Vehicles: Theoretical Aspects (part I)  

Microsoft Academic Search

This paper presents theoretical details of a model-based sensor fault detection and isolation system (SFDIS) applied to unmanned ground vehicles (UGVs). Structural analysis is applied to the nonlinear model of the vehicle for residual generation. Two different solutions have been proposed for developing the residual evaluation module. The vehicle sensor suite includes a global positioning system (GPS) antenna, an inertial

Andrea Monteriu; Prateek Asthan; Kimon P. Valavanis; Sauro Longhi

2007-01-01

422

IEEE TRANSACTIONS ON ROBOTICS AND AUTOMATION, VOL. 16, NO. 6, DECEMBER 2000 689 Fault Detection for Robot Manipulators with  

E-print Network

IEEE TRANSACTIONS ON ROBOTICS AND AUTOMATION, VOL. 16, NO. 6, DECEMBER 2000 689 Fault Detection for Robot Manipulators with Parametric Uncertainty: A Prediction-Error-Based Approach Warren E. Dixon, Member, IEEE, Ian D. Walker, Member, IEEE, Darren M. Dawson, Senior Member, IEEE, and John P. Hartranft

Dixon, Warren

423

Compositions and Methods for Detecting Treponema Pallidum.  

National Technical Information Service (NTIS)

Methods for the specific and highly sensitive detection of Treponema pallidum infection comprising the use of specific antigenic proteins and peptides unique to Treponema pallidum are provided. In particular, detection assays based recognition of acidic r...

B. Rodes, B. M. Steiner, H. Liu

2001-01-01

424

Application of statistics filter method and clustering analysis in fault diagnosis of roller bearings  

NASA Astrophysics Data System (ADS)

Condition diagnosis of roller bearings depends largely on the feature analysis of vibration signals. Spectrum statistics filter (SSF) method could adaptively reduce the noise. This method is based on hypothesis testing in the frequency domain to eliminate the identical component between the reference signal and the primary signal. This paper presents a statistical parameter namely similarity factor to evaluate the filtering performance. The performance of the method is compared with the classical method, band pass filter (BPF). Results show that statistics filter is preferable to BPF in vibration signal processing. Moreover, the significance level awould be optimized by genetic algorithms. However, it is very difficult to identify fault states only from time domain waveform or frequency spectrum when the effect of the noise is so strong or fault feature is not obvious. Pattern recognition is then applied to fault diagnosis in this study through system clustering method. This paper processes experiment rig data that after statistics filter, and the accuracy of clustering analysis increases substantially.

Song, L. Y.; Wang, H. Q.; Gao, J. J.; Yang, J. F.; Liu, W. B.; Chen, P.

2012-05-01

425

Feature Extraction Methods for Fault Classification of Rolling Element Bearing Based on Nonlinear Dimensionality Reduction and SVMs  

Microsoft Academic Search

Feature extraction is of great importance in condition monitoring and fault diagnosis of rolling machinery. Nonlinear dimensionality reduction (NDR) theories brought a new idea for recognizing and predicting the underlying nonlinear behavior. In this paper, we propose a NDR based feature extraction method for fault classification of rolling element bearing. Original feature spaces are constructed by time- and frequency-domain feature

Yizhuo Zhang; Guanghua Xu; Lin Liang; Jing Wang

2009-01-01

426

A high speed transceiver front-end design with fault detection for FlexRay-based automotive communication systems  

Microsoft Academic Search

This paper presents a high speed transceiver design with fault detection circuit compliant with FlexRay standards V2.1. An LVDS-like transmitter is utilized to drive the twisted pair of the bus. A current detector is included in the transceiver to detect the operating current so as to prevent over-current hazard. By contrast, a 3-comparator scheme is used to carry out the

Chua-Chin Wang; Chih-Lin Chen; Tai-Hao Yeh; Yi Hu; Gang-Neng Sung

2011-01-01

427

A new three-dimensional method of fault reactivation analysis : Application to the 2011 Tohoku-Oki earthquake sequence  

NASA Astrophysics Data System (ADS)

The determination of the state of stress around fault is of fundamental importance to understand fault reactivation and earthquake triggering. During the last decades, the determination of the stress state in the crust has been improved thanks to deep borehole stress measurements and the development of stress inversion methods. However, the influence of the stress tensor on the ability of faults to be reactivated remains unclear. The use of the reduced stress tensor given by most stress inversion methods to estimate the ability of fault to be reactivated is possible with only a few methods. We developed a new 3-D fault reactivation method to evaluate the reactivation potential of fault planes. The method is based on the Mohr-Coulomb theory and can be applied to cohesive or noncohesive faults whatever their orientations and without any conditions on the regional stress field. It allows computation of the effective stress ratio ?3'/?1' required to reactivate any fault plane and to determine whether the plane is favorably oriented, unfavorably oriented or severely misoriented with respect to the ambient stress field. The method also includes a graphical sorting tool that involves plotting poles of fault planes on stereoplots for which the boundaries separating the three domains corresponding to favorable orientations, unfavorable orientations and severe misorientations cases are shown. The delineation of these domains is based on the value of the ?3'/?1' ratio that depends on the orientation of the fault plane with respect to the principal stress axis orientations, the stress ellipsoid shape ratio, the coefficient of static friction ?s of the fault, and the fault cohesion C0. The method is then applied on 145 focal mechanisms of the 2011 March 11th Tohoku-Oki (Japan) earthquake sequence. This application delineates, along or in the vicinity of the Pacific-Okhotsk plate interface, three types of domains characterized by favorable orientations, unfavorable orientations or severe misorientations of mainshock/aftershock fault planes. Aftershock focal mechanisms that plot in the 'severe misorientation' domains are interpreted to have occurred because of pore fluid pressures exceeding the regional minimum principal stress at those locations. The distribution of these 'severe misorientation' domains partly overlaps the asperities or the low-velocity anomalies mapped on the plate interface off NE Japan. The 3-D fault reactivation analysis appears complementary to geophysical investigations.

Leclère, Henri; Fabbri, Olivier

2013-04-01

428

A Normal-faulting Paleostress in the Vicinity of Up-dip Limit of Seismogenic Zone Detected by Meso-scale Fault Analysis in a Tectonic Mélange  

NASA Astrophysics Data System (ADS)

The Mugi mélange in the Shimanto Belt, SW Japan, is a mixture of terrigenous and oceanic materials of late Cretaceous to Paleocene. Intermittent bedding planes trend ENE-WSW to E-W (subparallel to the Nankai trough axis) and dip steeply northward. The Mugi mélange consists of several duplex units accompanied by shear zones of basalt layers at their boundaries. Systematic shear fabrics and P-T conditions estimated from analyses of vitrinite reflectance and fluid inclusions indicate that the Mugi mélange had once been subducted to a significant depth (6-7 km below sea floor, which appears to coincide with the up-dip limit of the seismogenic zone), then underplated to the Shimanto accretionary prism, and is now exhumed on ground surface. In this study, for the purpose of determining paleostress fields related to the processes in which subducted materials were deformed, underplated and uplifted to surface, orientations of meso-scale faults and striations were analyzed. Stress inversion techniques including Angelier's Inversion, Multiple Inversion and Ginkgo Method were applied to fault-slip data obtained in each duplex unit of the Mugi mélange, and the results were almost consistent with each other. Most of the resultant ? 1 axes trend N-S horizontally, and are parallel to poles of shale cleavages, which are roughly parallel to bedding planes. Although the cleavages slightly vary their orientations according to later rotation, ? 1 axis changes together with them. This cleavage-controlled paleostress has a low Bishop's stress ratio (i.e. low magnitude of ? 2), therefore is an axial compressional stress normal to cleavages. The restored paleostress was probably exerted just before or at the same time of the formation of duplex structure and the rotation of bedding planes. The meso-scale faults appear to have been formed as normal ones due to overburden. P-T conditions estimated by analysis of fluid inclusions, which occur in the mineral veins sealing measured faults, and cross-cutting relationships between the faults and unit boundary shear zones indicate the simultaneity of these faulting and duplexing. The duplex structure is thought to be formed at the moment of underplating and be caused by stepdown of the décollement. A great variety of drastic changes in properties of material and circumstance such as stress field may occur at the very point of the stepdown, underplating of subducted material, and the up-dip limit of the seismogenic zone.

Sato, K.; Ikesawa, E.; Kimura, G.

2003-12-01

429

Fault Detection of Roller-Bearings Using Signal Processing and Optimization Algorithms  

PubMed Central

This study presents a fault detection of roller bearings through signal processing and optimization techniques. After the occurrence of scratch-type defects on the inner race of bearings, variations of kurtosis values are investigated in terms of two different data processing techniques: minimum entropy deconvolution (MED), and the Teager-Kaiser Energy Operator (TKEO). MED and the TKEO are employed to qualitatively enhance the discrimination of defect-induced repeating peaks on bearing vibration data with measurement noise. Given the perspective of the execution sequence of MED and the TKEO, the study found that the kurtosis sensitivity towards a defect on bearings could be highly improved. Also, the vibration signal from both healthy and damaged bearings is decomposed into multiple intrinsic mode functions (IMFs), through empirical mode decomposition (EMD). The weight vectors of IMFs become design variables for a genetic algorithm (GA). The weights of each IMF can be optimized through the genetic algorithm, to enhance the sensitivity of kurtosis on damaged bearing signals. Experimental results show that the EMD-GA approach successfully improved the resolution of detectability between a roller bearing with defect, and an intact system. PMID:24368701

Kwak, Dae-Ho; Lee, Dong-Han; Ahn, Jong-Hyo; Koh, Bong-Hwan

2014-01-01

430

Diagnosis of instrument fault  

Microsoft Academic Search

The diagnosis of faults in instrumentation equipment can often be confused with faults in the system. The correct diagnosis of instrument faults is of importance. Here it is described how to detect instrument faults in non-linearity. Time-varying processes that include uncertainties such as modelling error, parameter ambiguity, and input and output noise. The design of state estimation filters with zero

K. Watanabe; A. Komori; T. Kiyama

1994-01-01

431

Detection, isolation, and identification of sensor faults in nuclear power plants  

Microsoft Academic Search

This paper presents methods to detect, locate, and identify sensor degradations. The first method is based on simple redundancy and consists in generating residuals by comparison of measurements provided by physically redundant sensors. The second uses analytical redundancy. Residuals are generated by comparing each measurement with an estimate computed from models of the process. The efficiency of each method is

Richard Dorr; F. Kratz; J. Ragot; F. Loisy; J.-L. Germain

1996-01-01

432

Terrain Change Detection Using ASTER Optical Satellite Imagery Along the Kunlun fault, Tibet  

Microsoft Academic Search

Terrain changes are manifested in satellite images as pixel offsets, which represent the apparent difference in the position of corresponding pixels in two time-separated images of the same portion of the Earth's surface. We present terrain change detection results using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery. The change detection methods employed are Fourier analysis, image window cross-correlation

C. G. Schiek; J. M. Hurtado; A. A. Velasco; G. R. Keller; V. Kreinovich

2004-01-01

433

Fault Tolerant Recognition Method of Handwritten Chinese Characters Based on Double Weights Elliptical Neuron  

Microsoft Academic Search

\\u000a Applied Biomimetic Pattern Recognition to replace “differentiation” of characteristic sample by machine “cognition”, a novel\\u000a method of handwritten Chinese characters recognition is presented. A double weights elliptical neuron is used to cover four\\u000a basic kinds of handwritten Chinese characters stroke segment. The topological property among the stroke segment neurons is\\u000a analyzed. Nine style of Chinese characters stroke with fault tolerance

Jian-ping Wang; Wei-tao Li; Jin-ling Wang

2006-01-01

434

A novel method for graffiti detection using change detection algorithm  

Microsoft Academic Search

In recent decades vandal acts and graffiti drawing problem have increased and have required a lot of public funding. To face this problem the communal administrations have invested in automatic video surveillance systems. To deal with this problem through image processing techniques, this paper presents a method for graffiti detection based on change detection algorithm and motion vector. The aim

Daniele Angiati; Gianluca Gera; Stefano Piva; Carlo S. Regazzoni

2005-01-01

435

Evaluation of various boar taint detection methods.  

PubMed

The aim of this study was to evaluate the performance of various boar taint detection methods, measure the relationship between them and identify possible points of improvement for boar taint detection. The methods used to evaluate boar taint in the carcasses of 448 entire male pigs and 17 barrows were the hot iron method (n = 442), a standardised (n = 323) and home (n = 58) consumer meat-evaluation panel, an expert panel assessment of meat and fat (n = 464) and laboratory analysis of skatole, androstenone and indole in fat (n = 464). The axillary odour of a number of slaughtered entire male pigs was also investigated (n = 231). As correlation coefficients were generally weak, a positive result for one of these detection methods did not per se result in a positive result for all other methods. Results of one detection method could not be generalised. The choice to use one or more detection methods deserves consideration depending on the aim of the study. In this paper, we suggest some possible improvements for evaluating boar taint with a consumer panel based on our results and experience. The home consumer evaluation was correlated with the concentration of indole (r = 0.27) but not with skatole or androstenone. We therefore recommend that lab analyses include indole testing. The hot iron method seems to be an easy and fast detection method, which yields comparable or better correlation coefficients with the other detection methods than an expert panel evaluating fat samples. However, the reliability of the hot iron method depends on the training and reliability of one or two assessors. Efforts should be made to further optimise this method by evaluating the effect of testing conditions. The axillary odour score was moderately correlated with the other detection methods (up to 0.32). More research is needed to evaluate the possibilities of axillary odour as a boar taint detection method. PMID:22717070

Aluwé, M; Tuyttens, F A M; Bekaert, K M; De Smet, S; De Brabander, D L; Millet, S

2012-11-01

436

Fault Detection and Isolation of an Aircraft Using Set-Valued Observers  

E-print Network

, by deliberately generating hard and soft sensor/actuator faults. The results show that the faults take, in general and tested during the last decade ­ see, for instance, Blanke et al. (1997, 2001); Isermann (1997); Patton or not ­ see Patton and Chen (1997); Frank and Ding (1994); Este- ban (2004); Massoumnia (1986); Willsky (1976

Shamma, Jeff S.

437

Hidden Markov Models and Gaussian Mixture Models for Bearing Fault Detection Using Fractals  

Microsoft Academic Search

Bearing vibration signals features are extracted using time domain fractal based feature extraction technique. This technique uses multi-scale fractal dimension (MFD) estimated using box-counting dimension. The extracted features are then used to classify faults using Gaussian mixture models (GMM) and hidden Markov models (HMM). The results obtained show that the proposed feature extraction technique does extract fault specific information. Furthermore,

Tshilidzi Marwala; Unathi Mahola; Fulufhelo Vincent Nelwamondo

2006-01-01

438

Use of dependence probabilities to detect near-fault bias in earthquake triggering  

Microsoft Academic Search

Models of triggered seismicty, such as ETAS, do a good job of predicting observed earthquake patterns in time and space, excepting the largest events. However, these models are typically spatially isotropic and so far do not incorporate the fault structure that controls earthquake distribution. We have demonstrated that the average rate of small earthquakes decays with distance from strike-slip faults

P. M. Powers; T. H. Jordan

2007-01-01

439

Robust statistical methods for automated outlier detection  

NASA Technical Reports Server (NTRS)

The computational challenge of automating outlier, or blunder point, detection in radio metric data requires the use of nonstandard statistical methods because the outliers have a deleterious effect on standard least squares methods. The particular nonstandard methods most applicable to the task are the robust statistical techniques that have undergone intense development since the 1960s. These new methods are by design more resistant to the effects of outliers than standard methods. Because the topic may be unfamiliar, a brief introduction to the philosophy and methods of robust statistics is presented. Then the application of these methods to the automated outlier detection problem is detailed for some specific examples encountered in practice.

Jee, J. R.

1987-01-01

440

Comparison between different methodologies for detecting radon in soil along an active fault: the case of the Pernicana fault system, Mt. Etna (Italy).  

PubMed

Three different methodologies were used to measure Radon ((222)Rn) in soil, based on both passive and active detection system. The first technique consisted of solid-state nuclear track detectors (SSNTD), CR-39 type, and allowed integrated measurements. The second one consisted of a portable device for short time measurements. The last consisted of a continuous measurement device for extended monitoring, placed in selected sites. Soil (222)Rn activity was measured together with soil Thoron ((220)Rn) and soil carbon dioxide (CO(2)) efflux, and it was compared with the content of radionuclides in the rocks. Two different soil-gas horizontal transects were investigated across the Pernicana fault system (NE flank of Mount Etna), from November 2006 to April 2007. The results obtained with the three methodologies are in a general agreement with each other and reflect the tectonic settings of the investigated study area. The lowest (222)Rn values were recorded just on the fault plane, and relatively higher values were recorded a few tens of meters from the fault axis on both of its sides. This pattern could be explained as a dilution effect resulting from high rates of soil CO(2) efflux. Time variations of (222)Rn activity were mostly linked to atmospheric influences, whereas no significant correlation with the volcanic activity was observed. In order to further investigate regional radon distributions, spot measurements were made to identify sites having high Rn emissions that could subsequently be monitored for temporal radon variations. SSNTD measurements allow for extended-duration monitoring of a relatively large number of sites, although with some loss of temporal resolution due to their long integration time. Continuous monitoring probes are optimal for detailed time monitoring, but because of their expense, they can best be used to complement the information acquired with SSNTD in a network of monitored sites. PMID:18986811

Giammanco, S; Immè, G; Mangano, G; Morelli, D; Neri, M

2009-01-01

441

User's guide to the Fault Inferring Nonlinear Detection System (FINDS) computer program  

NASA Technical Reports Server (NTRS)

Described are the operation and internal structure of the computer program FINDS (Fault Inferring Nonlinear Detection System). The FINDS algorithm is designed to provide reliable estimates for aircraft position, velocity, attitude, and horizontal winds to be used for guidance and control laws in the presence of possible failures in the avionics sensors. The FINDS algorithm was developed with the use of a digital simulation of a commercial transport aircraft and tested with flight recorded data. The algorithm was then modified to meet the size constraints and real-time execution requirements on a flight computer. For the real-time operation, a multi-rate implementation of the FINDS algorithm has been partitioned to execute on a dual parallel processor configuration: one based on the translational dynamics and the other on the rotational kinematics. The report presents an overview of the FINDS algorithm, the implemented equations, the flow charts for the key subprograms, the input and output files, program variable indexing convention, subprogram descriptions, and the common block descriptions used in the program.

Caglayan, A. K.; Godiwala, P. M.; Satz, H. S.

1988-01-01

442

Accurate Monitoring and Fault Detection in Wind Measuring Devices through Wireless Sensor Networks.  

PubMed

Many wind energy projects report poor performance as low as 60% of the predicted performance. The reason for this is poor resource assessment and the use of new untested technologies and systems in remote locations. Predictions about the potential of an area for wind energy projects (through simulated models) may vary from the actual potential of the area. Hence, introducing accurate site assessment techniques will lead to accurate predictions of energy production from a particular area. We solve this problem by installing a Wireless Sensor Network (WSN) to periodically analyze the data from anemometers installed in that area. After comparative analysis of the acquired data, the anemometers transmit their readings through a WSN to the sink node for analysis. The sink node uses an iterative algorithm which sequentially detects any faulty anemometer and passes the details of the fault to the central system or main station. We apply the proposed technique in simulation as well as in practical implementation and study its accuracy by comparing the simulation results with experimental results to analyze the variation in the results obtained from both simulation model and implemented model. Simulation results show that the algorithm indicates faulty anemometers with high accuracy and low false alarm rate when as many as 25% of the anemometers become faulty. Experimental analysis shows that anemometers incorporating this solution are better assessed and performance level of implemented projects is increased above 86% of the simulated models. PMID:25421739

Khan, Komal Saifullah; Tariq, Muhammad

2014-01-01

443

Electromagnetic Methods of Lightning Detection  

NASA Astrophysics Data System (ADS)

Both cloud-to-ground and cloud lightning discharges involve a number of processes that produce electromagnetic field signatures in different regions of the spectrum. Salient characteristics of measured wideband electric and magnetic fields generated by various lightning processes at distances ranging from tens to a few hundreds of kilometers (when at least the initial part of the signal is essentially radiation while being not influenced by ionospheric reflections) are reviewed. An overview of the various lightning locating techniques, including magnetic direction finding, time-of-arrival technique, and interferometry, is given. Lightning location on global scale, when radio-frequency electromagnetic signals are dominated by ionospheric reflections, is also considered. Lightning locating system performance characteristics, including flash and stroke detection efficiencies, percentage of misclassified events, location accuracy, and peak current estimation errors, are discussed. Both cloud and cloud-to-ground flashes are considered. Representative examples of modern lightning locating systems are reviewed. Besides general characterization of each system, the available information on its performance characteristics is given with emphasis on those based on formal ground-truth studies published in the peer-reviewed literature.

Rakov, V. A.

2013-11-01

444

Sensor Fault Diagnosis Using Principal Component Analysis  

E-print Network

The purpose of this research is to address the problem of fault diagnosis of sensors which measure a set of direct redundant variables. This study proposes: 1. A method for linear senor fault diagnosis 2. An analysis of isolability and detectability...

Sharifi, Mahmoudreza

2010-07-14

445

Tractable particle filters for robot fault diagnosis  

Microsoft Academic Search

Experience has shown that even carefully designed and tested robots may encounter anomalous situations. It is therefore important for robots to monitor their state so that anomalous situations may be detected in a timely manner. Robot fault diagnosis typically requires tracking a very large number of possible faults in complex non-linear dynamic systems with noisy sensors. Traditional methods either ignore

Vandi Verma; GEOFF GORDON; REID SIMMONS; SEBASTIAN THRUN

2005-01-01

446

Fault knowledge management in aircraft maintenance  

Microsoft Academic Search

An aircraft is complex system with a great number of electronic products and mechanical equipments, and numerous faults failed to be inspected in aircraft maintenance. In most circumstance, it requires specialists to detect, diagnose and redress faults. The expert knowledge is an important aid in aircraft maintenance. This paper proposes a knowledge management method based on much maintenance experience and

Yang Zhou; Qing Li; Yingping Zuo

2009-01-01

447

Research on Fault Diagnosis Method of the Tower Crane Based on RBF Neural Network  

Microsoft Academic Search

As a result of the diversity of the tower crane faults, after the faults occurred, it is difficulty to accurately discriminate the fault type immediately. In this paper, the “clustering” of the RBF neural network effected on the input samples can be used to automatically realize the classification of the failure modes. Accordingly, the faults are diagnosed, and the specific

Xiaoyang Liu; Tingting Xue; Qing Jiang; Jian Li

2010-01-01

448

Modeling of a latent fault detector in a digital system  

NASA Technical Reports Server (NTRS)

Methods of modeling the detection time or latency period of a hardware fault in a digital system are proposed that explain how a computer detects faults in a computational mode. The objectives were to study how software reacts to a fault, to account for as many variables as possible affecting detection and to forecast a given program's detecting ability prior to computation. A series of experiments were conducted on a small emulated microprocessor with fault injection capability. Results indicate that the detecting capability of a program largely depends on the instruction subset used during computation and the frequency of its use and has little direct dependence on such variables as fault mode, number set, degree of branching and program length. A model is discussed which employs an analog with balls in an urn to explain the rate of which subsequent repetitions of an instruction or instruction set detect a given fault.

Nagel, P. M.

1978-01-01

449

The application of modern signal processing techniques for use in rotor fault detection and location within three-phase induction motors  

Microsoft Academic Search

A commonly used technique for the detection of faults which may occur in three-phase induction motors is to carry out a spectral analysis of the supply current to the motor under investigation. The presence of certain frequency components within the spectral analysis has been shown to be indicative of a fault condition (Hargis et al., 1982). Such techniques are becoming

R. Burnett; J. F. Watson; S. Elder

1996-01-01

450

Failure detection and identification and fault tolerant control using the IMM-KF with applications to the Eagle-Eye UAV  

Microsoft Academic Search

We describe a novel approach to sensor\\/actuator failure detection and identification and fault tolerant control based on the interacting multiple model (IMM) Kalman filter approach. Failures are mapped into different (and unique) state-space model representations. The IMM algorithm computes (online) the posterior probability of each failure model, that can be interpreted as a failure indicator. The fault tolerant control approach

C. Rago; Ravi Prasanth; Raman K. Mehra; Robert Fortenbaugh

1998-01-01

451

In:Safeprocess'09, 7th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, Barcelona, 2009. ISBN: 978-3-902661-46-3  

E-print Network

In:Safeprocess'09, 7th IFAC Symposium on Fault Detection, Supervision and Safety of Technical-based system that performs post-mortem fault localization of food packaging plants and, more specifically, and pallets being the most prominent ones. As a consequence, we had to develop a model that � includes

Cengarle, María Victoria

452

Evaluation of error detection coverage and fault-tolerance of digital plant protection system in nuclear power plants  

Microsoft Academic Search

Recently, traditional analog-based safety-related instrumentation and control (I&C) systems in nuclear power plants (NPPs) have been replaced with modern digital-based systems. Due to the digitalization of nuclear I&C systems, the safety assessment has become a major issue, as it is crucial to the system’s reliability. In the safety assessment of the digitalized system, evaluation of error detection coverage and fault-tolerance

Jun Seok Lee; Man Cheol Kim; Poong Hyun Seong; Hyun Gook Kang; Seung Cheol Jang

2006-01-01

453

Bacillus Spore Inactivation Methods Affect Detection Assays  

PubMed Central

Detection of biological weapons is a primary concern in force protection, treaty verification, and safeguarding civilian populations against domestic terrorism. One great concern is the detection of Bacillus anthracis, the causative agent of anthrax. Assays for detection in the laboratory often employ inactivated preparations of spores or nonpathogenic simulants. This study uses several common biodetection platforms to detect B. anthracis spores that have been inactivated by two methods and compares those data to detection of spores that have not been inactivated. The data demonstrate that inactivation methods can affect the sensitivity of nucleic acid- and antibody-based assays for the detection of B. anthracis spores. These effects should be taken into consideration when comparing laboratory results to data collected and assayed during field deployment. PMID:11472945

Dang, Jessica L.; Heroux, Karen; Kearney, John; Arasteh, Ameneh; Gostomski, Mark; Emanuel, Peter A.

2001-01-01

454

GMDD: a database of GMO detection methods  

PubMed Central

Background Since more than one hundred events of genetically modified organisms (GMOs) have been developed and approved for commercialization in global area, the GMO analysis methods are essential for the enforcement of GMO labelling regulations. Protein and nucleic acid-based detection techniques have been developed and utilized for GMOs identification and quantification. However, the information for harmonization and standardization of GMO analysis methods at global level is needed. Results GMO Detection method Database (GMDD) has collected almost all the previous developed and reported GMOs detection methods, which have been grouped by different strategies (screen-, gene-, construct-, and event-specific), and also provide a user-friendly search service of the detection methods by GMO event name, exogenous gene, or protein information, etc. In this database, users can obtain the sequences of exogenous integration, which will facilitate PCR primers and probes design. Also the information on endogenous genes, certified reference materials, reference molecules, and the validation status of developed methods is included in this database. Furthermore, registered users can also submit new detection methods and sequences to this database, and the newly submitted information will be released soon after being checked. Conclusion GMDD contains comprehensive information of GMO detection methods. The database will make the GMOs analysis much easier. PMID:18522755

Dong, Wei; Yang, Litao; Shen, Kailin; Kim, Banghyun; Kleter, Gijs A; Marvin, Hans JP; Guo, Rong; Liang, Wanqi; Zhang, Dabing

2008-01-01

455

Methods for detection of genetic disorders  

US Patent & Trademark Office Database

The invention provides a method useful for detection of genetic disorders. The method comprises determining the sequence of alleles of a locus of interest, and quantitating a ratio for the alleles at the locus of interest, wherein the ratio indicates the presence or absence of a chromosomal abnormality. The present invention also provides a non-invasive method for the detection of chromosomal abnormalities in a fetus. The invention is especially useful as a non-invasive method for determining the sequence of fetal DNA. The invention further provides methods of isolation of free DNA from a sample.

2008-10-28

456

A model-based solution for fault diagnosis of thruster faults: application to the rendezvous phase of the mars sample return mission  

NASA Astrophysics Data System (ADS)

This paper addresses the design of model-based fault diagnosis schemes to detect and isolate faults occurring in the orbiter thrusters of the Mars Sample Return (MSR) mission. The proposed fault diagnosis method is based on a H(0) filter with robust poles assignment to detect quickly any kind of thruster faults and a cross-correlation test to isolate them. Simulation results from the MSR "high-fidelity" nonlinear simulator provided by Thales Alenia Space demonstrate that the proposed method is able to diagnose thruster faults with a detection and isolation delay less than 1.1 s.

Henry, D.; Bornschlegl, E.; Olive, X.; Charbonnel, C.

2013-12-01

457

A Fault Detection and Isolation Scheme for Industrial Systems based on Multiple  

E-print Network

demand for safety and reliability, Preprint submitted to Elsevier Science 8 February 2006 hal-00158391 on a fuzzy logic systems has been proposed to model nonlinear systems in fault-free case with multiple linear

Paris-Sud XI, Université de

458

Lunar thrust faults in the Taurus-Littrow region. [detected by Apollo 17  

NASA Technical Reports Server (NTRS)

Evidence, suggesting that wrinkle ridges and similar looking one-sided scrapes in the Taurus-Littrow region are caused by anticlines and thrust faults resulting from sliding on a flowing surface, is given.

Howard, K. A.; Muehlberger, W. R.

1973-01-01