Note: This page contains sample records for the topic fault detection method from Science.gov.
While these samples are representative of the content of Science.gov,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of Science.gov
to obtain the most current and comprehensive results.
Last update: August 15, 2014.
1

A Survey of Fault Detection, Isolation, and Reconfiguration Methods  

Microsoft Academic Search

Fault detection, isolation, and reconfiguration (FDIR) is an important and challenging problem in many engineering applications and continues to be an active area of research in the control community. This paper presents a survey of the various model-based FDIR methods developed in the last decade. In the paper, the FDIR problem is divided into the fault detection and isolation (FDI)

Inseok Hwang; Sungwan Kim; Youdan Kim; Chze Eng Seah

2010-01-01

2

Fault-Tolerant Structure and Modulation Strategies With Fault Detection Method for Matrix Converters  

Microsoft Academic Search

This paper proposes a fault-tolerant matrix converter with reconfigurable structure and modified switch control schemes, along with a fault diagnosis technique for open-circuited switch failures. The proposed fault recognition method can detect and locate a failed bidirectional switch with voltage error signals dedicated to each switch, based on a direct comparison of the input and the output voltages. Following the

Sangshin Kwak

2010-01-01

3

Detecting Faults In Helicopter Gearboxes By The MVIM Method  

NASA Technical Reports Server (NTRS)

Multivalued influence-matrix (MVIM) method potential utility as theoretical basis of proposed automated monitoring systems detecting faults in helicopter gearboxes. Applied to recognize patterns in vibration measurements. Fault-recognition system required to operate continuously while helicopter airborne, analyzing measurements of vibrations for signs of trouble to provide real-time warning of any dangerous or potentially dangerous fault like cracked case or fractured gear tooth. System also required not to give false alarms to prevent unnecessary emergency landings.

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

1996-01-01

4

Comparison of Outlier Detection Methods in Fault-proneness Models  

Microsoft Academic Search

In this paper, we experimentally evaluated the effect of outlier detection methods to improve the prediction performance of fault-proneness models. Detected outliers were removed from a fit dataset before building a model. In the experiment, we compared three outlier detection methods (Mahalanobis outlier analysis (MOA), local outlier factor method (LOFM) and rule based modeling (RBM)) each applied to three well-known

Shinsuke MATSUMOTO; Yasutaka KAMEI; Akito MONDEN; Ken-ichi MATSUMOTO

2007-01-01

5

Comparison of Outlier Detection Methods in Fault-proneness Models  

Microsoft Academic Search

In this paper, we experimentally evaluated the effect of outlier detection methods to improve the prediction perfor- mance of fault-proneness models. Detected outliers were removed from a fit dataset before building a model. In the experiment, we compared three outlier detection methods (Mahalanobis outlier analysis (MOA), local outlier factor method (LOFM) and rule based modeling (RBM)) each ap- plied to

Shinsuke Matsumoto; Yasutaka Kamei; Akito Monden; Ken-ichi Matsumoto

2007-01-01

6

A Method of Insulator Fault Detection from Airborne Images  

Microsoft Academic Search

In this paper, a new method of insulator fault detection by texture feature sequence is proposed. Morphology, Hough transform line detection and statistic texture feature are applied to this method. Because there are some noises during image shooting, it is necessary that the insulator image should be preprocessed and corrected. The preprocessing includes image grayness, image enhancement and morphological processing.

Xinye Zhang; Jubai An; Fangming Chen

2010-01-01

7

An adaptive high and low impedance fault detection method  

SciTech Connect

An integrated high impedance fault (HIF) and low impedance fault (LIF) detection method is proposed in this paper. For a HIF detection, the proposed technique is based on a number of characteristics of the HIF current. These characteristics are: fault current magnitude, magnitude of the 3rd harmonic current, magnitude of the 5th harmonic current, the angle of the third harmonic current, the angle difference between the third harmonics current and the fundamental voltage, negative sequence current of HIF. These characteristics are identified by modeling the distribution feeders in EMTP. Apart from these characteristics, the above ambient (average) negative sequence current is also considered. An adjustable block out region around the average load current is provided. The average load current is calculated at every 18,000 cycles (5 minutes) interval. This adaptive feature will not only make the proposed scheme more sensitive to the low fault current, but it will also prevent the relay from tripping during the normal load current. In this paper, the logic circuit required for implementing the proposed HIF detection methods is also included. With minimal modifications, the logic developed for the HIF detection can be applied for the low impedance fault (LIF) detection. A complete logic circuit which detects both the HIF and LIF is proposed. Using this combined logic, the need of installing separate devices for HIF and LIF detection can be eliminated.

Yu, D.C. (Univ. of Wisconsin, Milwaukee, WI (United States)); Khan, S.H. (Puget Sound Power and Light Co., Bellevue, WA (United States))

1994-10-01

8

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

9

High impedance fault detection  

US Patent & Trademark Office Database

An apparatus, system, and method for detecting high impedance faults in electrical power lines using a composite high impedance fault detection system having a voter logic that samples the logical outputs from a plurality of independent high impedance detection systems and determines a high impedance fault if any two of the plurality of independent high impedance detection systems indicates a high impedance fault. Preferably, the plurality of high impedance detection systems include a wavelet based high impedance fault detection system having a first logical output, a higher order statistics based high impedance fault detection system having a second logical output, and a neural net based high impedance fault detection system having a third logical output. Preferably, each of the plurality of high impedance fault detection systems includes an independent high impedance fault detection application that independently detects a high impedance fault on the electrical power line.

2006-06-27

10

Visual printed wiring board fault detection by a geometrical method  

Microsoft Academic Search

The algorithm described in this paper uses the geometric distance between conductor boundaries as the criterion for a printed wiring board fault detection. A paging scheme is used so that only small parts of the picture need be stored in core. This also makes the method easily amenable to parallelism.

Larry Krakauer; T. Pavlidis

1979-01-01

11

Numerically reliable methods for optimal design of fault detection filters  

Microsoft Academic Search

The design problem of fault detection and isolation filters is formulated as a model matching problem and solved using an H2-or H?-norm optimization approach. A systematic procedure is proposed to choose appropriate filter specifications which guarantee the existence of proper and stable solutions of the model matching problem. This selection is integral part of numerically reliable computational methods to design

A. Varga

2005-01-01

12

Improved Hidden-Markov-Model Method Of Detecting Faults  

NASA Technical Reports Server (NTRS)

Method of automated, continuous monitoring to detect faults in complicated dynamic system based on hidden-Markov-model (HMM) approach. Simpler than another, recently proposed HMM method, but retains advantages of that method, including low susceptibility to false alarms, no need for mathematical model of dynamics of system under normal or faulty conditions, and ability to detect subtle changes in characteristics of monitored signals. Examples of systems monitored by use of this method include motors, turbines, and pumps critical in their applications; chemical-processing plants; powerplants; and biomedical systems.

Smyth, Padhraic J.

1994-01-01

13

Fault detection in electromagnetic suspension systems with state estimation methods  

SciTech Connect

High-speed maglev vehicles need a high level of safety that depends on the whole vehicle system's reliability. There are many ways of attaining high reliability for the system. Conventional method uses redundant hardware with majority vote logic circuits. Hardware redundancy costs more, weigh more and occupy more space than that of analytically redundant methods. Analytically redundant systems use parameter identification and state estimation methods based on the system models to detect and isolate the fault of instruments (sensors), actuator and components. In this paper the authors use the Luenberger observer to estimate three state variables of the electromagnetic suspension system: position (airgap), vehicle velocity, and vertical acceleration. These estimates are compared with the corresponding sensor outputs for fault detection. In this paper, they consider FDI of the accelerometer, the sensor which provides the ride quality.

Sinha, P.K.; Zhou, F.B.; Kutiyal, R.S. (Univ. of Reading (United Kingdom). Dept. of Engineering)

1993-11-01

14

Fault Detection in an Air-Handling Unit Using Residual and Recursive Parameter Identification Methods.  

National Technical Information Service (NTIS)

A scheme for detecting faults in an air-handling unit using residual and parameter identification methods is presented. Faults can be detected by comparing the normal or expected operating condition data with the abnormal. measured data using residuals. F...

C. Park G. E. Kelly W. Y. Lee

1996-01-01

15

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

16

Comparison of Outlier Detection Methods in Fault-Prone Module Detection  

Microsoft Academic Search

The goal of this paper is to improve the prediction performance of fault-proneness models by removing outliers from a dataset used for model construction. We experimentally eval- uated the effect of four outlier removal methods; Mahalanobis Outlier Analysis (MOA) and Local Outlier Factor Method (LOFM) which are well-known outlier detection methods for a single sample, and Rule-Based Modeling (RBM) suitable

Shinsuke Matsumoto; Yasutaka Kamei; Akito Monden; Ken-ichi Matsumoto

2008-01-01

17

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, Robert B. (Wheatridge, CO); Pruett, Jr., James C. (Lakewood, CO)

1986-01-01

18

A Low Overhead Fault Detection and Recovery Method for the Faults in Clock Generators  

Microsoft Academic Search

In many synchronous digital systems especially those used in mobile applications, the system is exposed to sever shaking that may lead to a failure in the clock generator. In this paper we present an effective method to tolerate the faults on the clock signal that are due to defects in external oscillators. Our technique utilizes no Phase-Lock Loops (PLL), no

Nima Karimpour Darav; Mohammad Amin Amiri; Alireza Ejlali

2009-01-01

19

Fault Detection Using Resistivity Image Profiling Method at Taoyuan and Hsinchu, Taiwan  

NASA Astrophysics Data System (ADS)

As Taiwan is located in the Neotectonic belt along the western Pacific Ocean, the detection of active faults is important for it provides the information for the analysis of earthquake risk. In addition, some active faults in Taiwan lie typically at the bases of urban or industrial area, their identifications are often challengeable because of environmental changes and interferences, etc. The Taoyuan and Hsinchu county are most important high technology sites in Taiwan. Based on previous geophysical and geologic surveys, the well-known active Hukou fault right crosses the site, although the exact location of active fault zone remains unclear. The detection of an active fault can be done by different geophysical methods. However, a successful recognition of a fault depends on the physical properties such as density contrast acoustic impedance and reisitivity contrast, etc. of the targets and its surroundings. Due to a large resistivity contrast between the hanging wall (low resistivity Choulan shale) and the footwall (high resistivity Toukoshan gravel beds) of the Hsinchen fault, geoelectrical sounding may well be one of the best ways to trace this fault. For the above reasons, the resistivity image profiling method was used to investigate the fault and to relate these resistivity measurements to the fault parameters. All of the field measurements to be discussed were made during the period of 2003 and 2004. Fifteen RIP survey lines were deployed in the study area. RIP results indicate that the thickness of the high resistivity gravel layer is increased between the northern cliff of the Hu-Kou terrace and southern edge of Yangmei graben. An obvious difference of altitude is found among low resistivity zones. It may associate with the disturbance or dislocation of layers in the past. Combined the RIP sounding results to the local topographic maps, geologic data, and formal open pits information, fault zones are being recognized. Keywords: active fault; resistivity change; Hukou fault; Taiwan

Hsung-Chang, L.; Chieh-Hou, Y.; Yan-Hao, H.

2005-12-01

20

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

21

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

22

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

23

Wavelet based method for fault detection in Medium Voltage DC shipboard power systems  

Microsoft Academic Search

This paper proposes a wavelet transform (WT) based multi-resolution analysis (MRA) method to obtain the features of different fault types in Medium Voltage DC (MVDC) shipboard power systems. DC topology is under consideration for future all-electric ships. One of the new challenges related to this architecture is fault detection. WT-based MRA method, as well as its properties, are studied and

Weilin Li; Min Luo; Antonello Monti; Ferdinanda Ponci

2012-01-01

24

A Survey of Methods for Detection of Stator-Related Faults in Induction Machines  

Microsoft Academic Search

As evidenced by industrial surveys, stator-related failures account for a large percentage of faults in induction machines. The objective of this paper is to provide a survey of existing techniques for detection of stator-related faults, which include stator winding turn faults, stator core faults, temperature monitoring and thermal protection, and stator winding insulation testing. The root causes of fault inception,

Rangarajan M. Tallam; Sang Bin Lee; Greg C. Stone; Gerald B. Kliman; Jiyoon Yoo; Thomas G. Habetler; Ronald G. Harley

2007-01-01

25

Feedback bridging fault detection using current monitoring  

Microsoft Academic Search

Feedback bridging faults in CMOS circuits are difficult to detect by monitoring logic values. The authors study the possibility of detecting feedback bridging faults by using current monitoring. It is shown that by monitoring current, the feedback bridging faults that cause a metastable state can be detected. Using the same method, the feedback bridging faults can also be detected that

D. Lu; C. Q. Tong

1992-01-01

26

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

NASA Technical Reports Server (NTRS)

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

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

1993-01-01

27

A Method Based on Multi-Sensor Data Fusion for Fault Detection of Planetary Gearboxes  

PubMed Central

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

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

2012-01-01

28

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

29

Fault detection and isolation  

NASA Astrophysics Data System (ADS)

In order for a current satellite-based navigation system (such as the Global Positioning System, GPS) to meet integrity requirements, there must be a way of detecting erroneous measurements, without help from outside the system. This process is called Fault Detection and Isolation (FDI). Fault detection requires at least one redundant measurement, and can be done with a parity space algorithm. The best way around the fault isolation problem is not necessarily isolating the bad measurement, but finding a new combination of measurements which excludes it.

Bernath, Greg

1994-02-01

30

Fault detection and isolation  

NASA Technical Reports Server (NTRS)

In order for a current satellite-based navigation system (such as the Global Positioning System, GPS) to meet integrity requirements, there must be a way of detecting erroneous measurements, without help from outside the system. This process is called Fault Detection and Isolation (FDI). Fault detection requires at least one redundant measurement, and can be done with a parity space algorithm. The best way around the fault isolation problem is not necessarily isolating the bad measurement, but finding a new combination of measurements which excludes it.

Bernath, Greg

1994-01-01

31

Vibration based fault detection and identification in an aircraft skeleton structure via a stochastic functional model based method  

Microsoft Academic Search

The problem of vibration based fault detection, identification (localization) and estimation in a scale aircraft skeleton structure is considered via a stochastic functional model based method (FMBM). The method is based on the novel class of stochastic Functionally Pooled models, which are capable of accurately representing the structure in a faulty state for the state's continuum of fault magnitudes, as

J. S. Sakellariou; S. D. Fassois

2008-01-01

32

A Wavelet-Based Method for Detection and Classification of Single and Crosscountry Faults in Transmission Lines  

Microsoft Academic Search

This paper presents a discrete wavelet transform approach to detect and classify faults in transmission lines by the analysis of oscillographic records. Most of the existing methods treat the fault as a single type. Thus, the performance of these methods might be limited for real applications in power systems. In this framework, the proposed approach overcomes this problem by the

B. A. Souza; N. S. D. Brito

2009-01-01

33

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

34

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

35

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

36

On fault detection in CMOS logic networks  

Microsoft Academic Search

This paper considers the problem of detecting faults in CMOS combinational networks. Effects of open and short faults in CMOS networks are analyzed. It is shown that the test sequence must be properly organized if the effects of all open faults are to be observable at the network output terminal. A simple and efficient heuristic method for organizing the test

Kuang-Wei Chiang; Zvonko G. Vranesic

1983-01-01

37

Row fault detection system  

DOEpatents

An apparatus, program product and method checks for nodal faults in a row of nodes by causing each node in the row to concurrently communicate with its adjacent neighbor nodes in the row. The communications are analyzed to determine a presence of a faulty node or connection.

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

2008-10-14

38

Row fault detection system  

DOEpatents

An apparatus, program product and method check for nodal faults in a row of nodes by causing each node in the row to concurrently communicate with its adjacent neighbor nodes in the row. The communications are analyzed to determine a presence of a faulty node or connection.

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

2012-02-07

39

Classification of Aircraft Maneuvers for Fault Detection  

Microsoft Academic Search

Ensemble classifiers tend to outperform their component base classifiers when the training data are subject to variability.\\u000a This intuitively makes ensemble classifiers useful for application to the problem of aircraft fault detection. Automated fault\\u000a detection is an increasingly important problem in aircraft maintenance and operation. Standard methods of fault detection\\u000a assume the availability of data produced during all possible faulty

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

2003-01-01

40

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

41

Parity space methods for autonomous fault detection and exclusion using GPS carrier phase  

Microsoft Academic Search

Kinematic carrier phase positioning provides navigation integrity. The sub-centimeter precision of carrier phase measurements can be used to leverage receiver autonomous integrity monitoring (RAIM) in the sense that extremely tight fault detection thresholds can be set on the least-squares residual (ensuring navigation integrity) without incurring high false alarm rates. In addition, the high precision of carrier phase, when compared with

Boris S. Pervan; David G. Lawrence; Clark E. Cohen; B. W. Parkinson

1996-01-01

42

Cooling Mode Fault Detection and Diagnosis Method for a Residential Heat Pump.  

National Technical Information Service (NTIS)

This research addresses the need for fault detection and diagnosis (FDD) in residential-style, air conditioner, and heat pump systems in an attempt to make these systems more trouble free and energy efficient over their entire lifetime. This work is one o...

M. Kim P. A. Domanski S. H. Yoon W. V. Payne

2008-01-01

43

Fault Detection in Routing Protocols  

Microsoft Academic Search

Routing protocol faults cause problems ranging from an inability to communicate to excessive routing overhead. This paper proposes a system for detecting a wide range of routing protocol faults. Our system deploys virtual routers called RouteMonitors to monitor a routing protocol. We de- ployed RouteMonitors in the MBone's DVMRP infrastruc- ture and uncovered a number of faults. We were also

Daniel Massey; Bill Fenner

1999-01-01

44

Fault detection methods using direct stiffness matrix correction formulations for use with laser data  

NASA Astrophysics Data System (ADS)

In this paper, direct stiffness correction methods (Berman-Baruch methods) are revisited for use as a tool for localizing structural faults based on spatially dense mode shapes obtained experimentally using laser Doppler velocimeters. Besides the standard Berman-Baruch formulation and a recently proposed iterative formulation which preserves sparsity, three other alternative formulations are proposed by the authors. The methods are evaluated using both numerically simulated and experimental data. The numerical example results (clamped-free beam) show that some of the formulations indicated clearly the fault location. With the experimental example (free-free beam), however, the fault localization wasn't so evident. The experimental modal test was done with conventional instrumentation. The authors expect that better results can be obtained using laser data.

Arruda, Jose R.; Mendes Vercosa, Carlson A.

1994-09-01

45

Method of Load\\/Fault Detection for Loosely Coupled Planar Wireless Power Transfer System With Power Delivery Tracking  

Microsoft Academic Search

A method to determine various operating modes of a high-efficiency inductive wireless power transfer system which is capable of supporting more than one receiver is proposed. The three operating modes are no-load, safe, and fault modes. The detection scheme probes the transmitter circuitry periodically to determine the operating mode. For power saving, the transmitter is powered down when there is

Zhen Ning Low; J. J. Casanova; P. H. Maier; J. A. Taylor; R. A. Chinga; Jenshan Lin

2010-01-01

46

Method of locating ground faults  

NASA Technical Reports Server (NTRS)

The present invention discloses a method of detecting and locating current imbalances such as ground faults in multiwire systems using the Faraday effect. As an example, for 2-wire or 3-wire (1 ground wire) electrical systems, light is transmitted along an optical path which is exposed to magnetic fields produced by currents flowing in the hot and neutral wires. The rotations produced by these two magnetic fields cancel each other, therefore light on the optical path does not read the effect of either. However, when a ground fault occurs, the optical path is exposed to a net Faraday effect rotation due to the current imbalance thereby exposing the ground fault.

Patterson, Richard L. (inventor); Rose, Allen H. (inventor); Cull, Ronald C. (inventor)

1994-01-01

47

Arc burst pattern analysis fault detection system  

NASA Technical Reports Server (NTRS)

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

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

1997-01-01

48

Ground-Fault Feeder Detection With Fault-Current and Fault-Resistance Measurement in Mine Power Systems  

Microsoft Academic Search

Many mine power systems operate with a floating neutral or are high-resistance grounded, and earth fault current is no more than a few tens of amperes. Traditional earth-fault-detection methods based on zero-sequence current have poor sensitivity in this case. For improvement, a fault-detection scheme with fault-current and fault-resistance measurement is presented in this paper, which is capable of detecting high-impedance

Xiangjun Zeng; K. K. Li; W. L. Chan; Sheng Su; Yuanyuan Wang

2008-01-01

49

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.

Jha, Kamal N. (Bethel Park, PA)

1999-01-01

50

Maneuver Classification for Aircraft 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, identifying all possible faulty and proper operating modes is clearly impossible. We envision a system for online fault detection in aircraft, one part of which is a classifier that predicts the maneuver being performed by the aircraft as a function of vibration data and other available data. To develop such a system, we use flight data collected under a controlled test environment, subject to many sources of variability. We explain where our classifier fits into the envisioned fault detection system as well as experiments showing the promise of this classification subsystem.

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

2003-01-01

51

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

52

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

53

Fast Protection of Strong Power Systems With Fault Current Limiters and PLL-Aided Fault Detection  

Microsoft Academic Search

In this paper, a new method is proposed that can be used to discriminate faults from switching transients. The method is primarily intended for use in systems where fast fault detection and fast fault clearing before the first peak of the fault current are required. An industrial system, in which high short-circuit power is desired but in which high short-circuit

Magnus Ohrstrom; Lennart Soder

2011-01-01

54

Fault Detection of Rectifier based on Residuals  

NASA Astrophysics Data System (ADS)

For diagnosing failure and sick rectifying elements, a fault detection and prediction method of rectifier was presented in this paper. The output voltage of rectifier was contrasted with normal simulation signal in phase to obtain the difference signal. After it was processed according to the set threshold, the coding of the difference signal was achieved. The signal coding was adopted to diagnose failure elements or sick elements. In simulation test, the fault code tables of rectifier with different control angle were given. The simulation results show the validity of the fault detection method presented in this paper.

Qingfeng, Liu; Zhaoxia, Leng; Jinkun, Sun; Huamin, Wang

55

Row fault detection system  

DOEpatents

An apparatus and program product check for nodal faults in a row of nodes by causing each node in the row to concurrently communicate with its adjacent neighbor nodes in the row. The communications are analyzed to determine a presence of a faulty node or connection.

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

2010-02-23

56

Dynamic Fault Detection Chassis  

Microsoft Academic Search

The high frequency switching megawatt-class High Voltage Converter Modulator (HVCM) developed by Los Alamos National Laboratory for the Oak Ridge National Laboratory's Spallation Neutron Source (SNS) is now in operation. One of the major problems with the modulator systems is shoot-thru conditions that can occur in a IGBTs H-bridge topology resulting in large fault currents and device failure in a

Mize; Jeffery J

2007-01-01

57

Cell boundary fault detection system  

DOEpatents

A method determines 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) [Rochester, MN; Pinnow, Kurt Walter (Rochester, MN) [Rochester, MN; Ratterman, Joseph D. (Rochester, MN) [Rochester, MN; Smith, Brian Edward (Rochester, MN) [Rochester, MN

2009-05-05

58

A time-frequency method for multiple fault detection in three-phase induction machines  

Microsoft Academic Search

It is well known that induction machine stator current is a nonstationary signal and its properties change with respect to operating conditions. The computed spectrum using the fast Fourier transform (FFT) does not provide accurate time-domain information about the operating conditions. As a result, the FFT spectrum analysis makes difficult to recognize fault conditions from the normal operation of the

K. Bacha; M. Gossa; H. Henao; G. A. Capolino

2005-01-01

59

Bisectional fault detection system  

SciTech Connect

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

60

Bisectional fault detection system  

DOEpatents

An apparatus, program product and method logically divide 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)

2012-02-14

61

Implementation of a model based fault detection and diagnosis technique for actuation faults of the SSME  

NASA Astrophysics Data System (ADS)

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.

62

Implementation of a model based fault detection and diagnosis technique for actuation faults of the SSME  

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.

1991-01-01

63

Optical fiber method for detection of single-phasing faults in three-phase induction motors used in underground mines  

NASA Astrophysics Data System (ADS)

In this paper, a brief description of fiber optic based system for detection of single-phasing faults in 3-phase induction motors used in underground coal mines has been given. The system has an alarm facility which start sounding in absence of power. It also consists of three light emitting diodes of different colors to show the absence of power in a particular phase along with the alarm. Optical fiber, being a dielectric, non-metallic, and non-sparking is an intrinsically safe media and is ideally suited for single phasing faults detection of 3-phase motors used in underground mines or in any other hazardous environment.

Kumar, Virendra; Chandra, Dinesh

1998-09-01

64

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

65

Signal injection as a fault detection technique.  

PubMed

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

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

2011-01-01

66

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

67

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

68

Using SPC and template monitoring method for fault detection and prediction in discrete event manufacturing systems  

Microsoft Academic Search

The behavior of manufacturing systems with discrete I\\/O signals can be characterized by the timing and sequencing of changes (events) in these I\\/O. In this paper, we present a method to monitor these signals to alarm when faulty sequencing or timing behavior occurs, and also to warn when the timing starts to deviate from its normal behavior. This is accomplished

H. K. Fadel; Lawrence E. Holloway

1999-01-01

69

Surveillance System and Method having an Adaptive Sequential Probability Fault Detection Test  

NASA Technical Reports Server (NTRS)

System and method providing surveillance of an asset such as a process and/or apparatus by providing training and surveillance procedures that numerically fit a probability density function to an observed residual error signal distribution that is correlative to normal asset operation and then utilizes the fitted probability density function in a dynamic statistical hypothesis test for providing improved asset surveillance.

Bickford, Randall L. (Inventor); Herzog, James P. (Inventor)

2008-01-01

70

Surveillance system and method having an adaptive sequential probability fault detection test  

NASA Technical Reports Server (NTRS)

System and method providing surveillance of an asset such as a process and/or apparatus by providing training and surveillance procedures that numerically fit a probability density function to an observed residual error signal distribution that is correlative to normal asset operation and then utilizes the fitted probability density function in a dynamic statistical hypothesis test for providing improved asset surveillance.

Herzog, James P. (Inventor); Bickford, Randall L. (Inventor)

2005-01-01

71

Surveillance system and method having an adaptive sequential probability fault detection test  

NASA Technical Reports Server (NTRS)

System and method providing surveillance of an asset such as a process and/or apparatus by providing training and surveillance procedures that numerically fit a probability density function to an observed residual error signal distribution that is correlative to normal asset operation and then utilizes the fitted probability density function in a dynamic statistical hypothesis test for providing improved asset surveillance.

Bickford, Randall L. (Inventor); Herzog, James P. (Inventor)

2006-01-01

72

Negative Selection Algorithm for Aircraft Fault Detection  

Microsoft Academic Search

We investigated a real-valued Negative Selection Algorithm (NSA) for fault detection in man-in-the-loop aircraft operation. The de- tection 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

D. Dasgupta; K. Krishnakumar; D. Wong; M. Berry

2004-01-01

73

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

74

Detection of faults and software reliability analysis  

NASA Technical Reports Server (NTRS)

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

Knight, J. C.

1986-01-01

75

Detecting Latent Faults In Digital Flight Controls  

NASA Technical Reports Server (NTRS)

Report discusses theory, conduct, and results of tests involving deliberate injection of low-level faults into digital flight-control system. Part of study of effectiveness of techniques for detection of and recovery from faults, based on statistical assessment of inputs and outputs of parts of control systems. Offers exceptional new capability to establish reliabilities of critical digital electronic systems in aircraft.

Mcgough, John; Mulcare, Dennis; Larsen, William E.

1992-01-01

76

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

77

Fault detection in metallic grid scattering.  

PubMed

The canonical problem of detecting and localizing missing scatterers (faults) inside a known grid of small cross section perfect electric conducting cylinders is dealt with. The case of a TM scalar two-dimensional geometry is considered. The scattering by a fault is modeled as the radiation of a proper magnetic current, by exploiting the Green's function of the complete grid. An approximated linear model of the scattering is proposed and discussed in terms of the achievable probability of detection, also in the case of two faults, and checked against model error and noisy synthetic data. PMID:22193272

Brancaccio, Adriana; Leone, Giovanni; Solimene, Raffaele

2011-12-01

78

About Random Fault Detection of Combinational Networks  

Microsoft Academic Search

Fault detection by applying a random input sequence simultaneously to a network under test and to a reference network is conside-red. A distinction between testing quality and detection quality is given. The detection surface is introduced as a characteristic parameter of a combinational network. The results are applied to TTL combinational circuits.

René David; Gérard Blanchet

1976-01-01

79

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

80

Fault Detection on Transmission Lines Using a Microphone Array and an Infrared Thermal Imaging Camera  

Microsoft Academic Search

This paper proposes a hierarchical fault detection method for transmission lines using a microphone array to detect the location of a fault and thermal imaging and charge coupled device (CCD) cameras to verify the fault and store the image, respectively. There are partial arc discharges on faulty insulators which generate specific patterns of sound. By detecting these patterns using the

Hyunuk Ha; Sunsin Han; Jangmyung Lee

2012-01-01

81

Framework for modeling software reliability, using various testing-efforts and fault-detection rates  

Microsoft Academic Search

This paper proposes a new scheme for constructing software reliability growth models (SRGM) based on a nonhomogeneous Poisson process (NHPP). The main focus is to provide an efficient parametric decomposition method for software reliability modeling, which considers both testing efforts and fault detection rates (FDR). In general, the software fault detection\\/removal mechanisms depend on previously detected\\/removed faults and on how

Sy-Yen Kuo; Chin-Yu Huang; Michael R. Lyu

2001-01-01

82

Statistical process control based fault detection of CHP units  

Microsoft Academic Search

This paper describes a fault diagnosis method that provides early detection of fouling of the heat recovery system of combined heat and power units. Early detection of fouling build-up is difficult from basic data analysis methods due to limited instrumentation, and a unit can operate for many months with a reduced heat transfer rate before an unplanned shut down. This

M. Thomson; P. M. Twigg; B. A. Majeed; N. Ruck

2000-01-01

83

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

2011-04-19

84

Immunity-Based Aircraft Fault Detection System  

NASA Technical Reports Server (NTRS)

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

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

2004-01-01

85

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

86

Fault detection and classification in transmission lines based on wavelet transform and ANN  

Microsoft Academic Search

This paper proposes a novel method for transmission-line fault detection and classification using oscillographic data. The fault detection and its clearing time are determined based on a set of rules obtained from the current waveform analysis in time and wavelet domains. The method is able to single out faults from other power-quality disturbances, such as voltage sags and oscillatory transients,

K. M. Silva; B. A. Souza; N. S. D. Brito

2006-01-01

87

Online tribology ball bearing fault detection and identification  

NASA Astrophysics Data System (ADS)

We present a feasibility analysis for the development of an online ball bearing fault detection and identification system. This system can effectively identify various fault stages related to the evolution of friction within the contact in the coated ball bearings. Data are collected from laboratory experiments involving forces, torque and acceleration sensors. To detect the ball bearing faulty stages, we have developed a new bispectrum and entropy analysis methods to capture the faulty transient signals embedded in the measurements. Test results have shown that these methods can detect the small abnormal transient signals associated with the friction evolution. To identify the fault stages, we have further developed a set of stochastic models using hidden Markov model (HMM). Instead of using the discrete sequences, our HMM models can incorporate the feature vectors modeled as Gaussian mixtures. To facilitate online fault identification, we build an HMM model for each fault stage. At each evaluation time, all HMM models are evaluated and the final detection is refined based on individual detections. Test results using laboratory experiment data have shown that our system can identify coated ball bearing faults in near real-time.

Ling, B.; Khonsari, M. M.

2007-05-01

88

Detecting Faults By Use Of Hidden Markov Models  

NASA Technical Reports Server (NTRS)

Frequency of false alarms reduced. Faults in complicated dynamic system (e.g., antenna-aiming system, telecommunication network, or human heart) detected automatically by method of automated, continuous monitoring. Obtains time-series data by sampling multiple sensor outputs at discrete intervals of t and processes data via algorithm determining whether system in normal or faulty state. Algorithm implements, among other things, hidden first-order temporal Markov model of states of system. Mathematical model of dynamics of system not needed. Present method is "prior" method mentioned in "Improved Hidden-Markov-Model Method of Detecting Faults" (NPO-18982).

Smyth, Padhraic J.

1995-01-01

89

Decision tree-based methodology for high impedance fault detection  

Microsoft Academic Search

This paper presents a high impedance fault (HIF) detection method based on decision trees (DTs). The features of HIF, which are the inputs of DTs, are those well-known ones, including current [in root mean square (rms)], magnitudes of the second, third, and fifth harmonics, and the phase of the third harmonics. The only measurements needed in the proposed method are

Yong Sheng; Steven M. Rovnyak

2004-01-01

90

An adaptive statistical time-frequency method for detection of broken bars and bearing faults in motors using stator current  

Microsoft Academic Search

It is well known that motor current is a nonstationary signal, the properties of which vary with respect to the time-varying normal operating conditions of the motor. As a result, Fourier analysis makes it difficult to recognize fault conditions from the normal operating conditions of the motor. Time-frequency analysis, on the other hand, unambiguously represents the motor current which makes

B. Yazici; G. B. Kliman

1999-01-01

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).

Lee, Wonhee; Park, Chan Gook

2014-01-01

92

Wind tunnel test of UAV fault detection using principal component based aerodynamic model  

Microsoft Academic Search

In our previous work the fault detection using aerodynamic model was proposed as more directly method to detect the fault such as configuration damage of the UAV. In this paper the wind tunnel test is performed with the object of verifying the capability of this method to detect the damage during flight. The result shows that by observing the residual

Annop Ruangwiset; Banterng Suwantragul

2008-01-01

93

Linear and bilinear fault detection and diagnosis based on mass and energy balance equations  

Microsoft Academic Search

Processes combining heat and material flows involve non-linear relationships that complicate fault detection and diagnosis (FDD) procedures. This paper proposes two model-based methods for detecting and diagnosing faults in process models as well as in measurements. The models involved in both methods consist of stationary mass and energy conservation equations. The ?2 detection test and the generalized likelihood ratio diagnosis

Antoine Berton; Daniel Hodouin

2003-01-01

94

Detection of multiple faults using SSFTS in CMOS logic circuits  

Microsoft Academic Search

With the increasing density of CMOS VLSI circuits, it is necessary to test for the combinations of different multiple faults. This paper studies the possibility of using single stuck-at fault test set (SSFTS) to detect multiple faults and their combinations. The paper shows that a single stuck-at fault test set can detect single and multiple self-feedback bridging faults, combinations of

Carol Q. Tong; D. Lu

1993-01-01

95

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

96

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

NASA Technical Reports Server (NTRS)

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

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

1991-01-01

97

Fault Detection and Isolation with Robust Principal Component Analysis  

Microsoft Academic Search

Principal component analysis (PCA) is a powerful fault detection and isolation method. However, the classical PCA, which is based on the estimation of the sample mean and covariance matrix of the data, is very sensitive to outliers in the training data set. Usually robust principal component analysis is applied to remove the effect of outliers on the PCA model. In

Yvon Tharrault; Gilles Mourot; José Ragot; Didier Maquin

2008-01-01

98

Fault Detection and Isolation in the Water Tank World  

Microsoft Academic Search

A flexible, model based fault detection and isolation (FDI) system for an arbitrary configuration of a water tank world has been designed and implemented in MATLAB, SIMULINK and dSPACE. The fault detection is performed with local change detection algorithms, and the fault isolation is performed with residual patterns automatically generated from the total configuration.

Niclas Bergman; Magnus Larsson

99

Multi-directional fault detection system  

DOEpatents

An apparatus, program product and method checks for nodal faults in a group of nodes comprising a center node and all adjacent nodes. The center node concurrently communicates with the immediately adjacent nodes in three dimensions. The communications are analyzed to determine a presence of a faulty node or connection.

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

2009-03-17

100

Multi-directional fault detection system  

DOEpatents

An apparatus, program product and method checks for nodal faults in a group of nodes comprising a center node and all adjacent nodes. The center node concurrently communicates with the immediately adjacent nodes in three dimensions. The communications are analyzed to determine a presence of a faulty node or connection.

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

2010-11-23

101

Adaptive Sensor Fault Detection and Identification Using Particle Filter Algorithms  

Microsoft Academic Search

Sensor fault detection and identification (FDI) is a process of detecting and validating sensor's fault status. Because FDI guarantees system reliable performance, it has received much attention recently. In this paper, we address the problem of online sensor fault identification and validation. For a physical sensor validation system, it contains transitions between sensor normal and faulty states, change of system

Tao Wei; Yufei Huang; C. L. Philip Chen

2009-01-01

102

Fault detection and diagnosis using neural network approaches  

NASA Technical Reports Server (NTRS)

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

Kramer, Mark A.

1992-01-01

103

Automated Monitoring with a BSP Fault-Detection Test  

NASA Technical Reports Server (NTRS)

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

Bickford, Randall L.; Herzog, James P.

2003-01-01

104

Study Hukou fault by using DC resistivity and CSAMT methods  

NASA Astrophysics Data System (ADS)

Geoelectric methods are widely used in the geophysical exploration. They did well in groundwater prospecting, mapping the changes of depositional environment, fault identification, and mineral detection etc. Two common electrical methods used in the field are the direct current resistivity (DC resistivity) method, and the controlled source audio-magnetic telluric (CSAMT) method. A successful survey depends on the features of the surveyed targets, man-made noise, and topography. The purpose of this study is using DC and CSAMT methods to investigate the Hu-kou fault in the northwestern of Taiwan. The Ho-kou fault is a thrust fault, extending from the Ping-Jen to the south of Ho-kou with a length of 23 km. The strike is in the north-northeastern direction. Ku(1963) differentiates the fault with a vertical displacement of 30 m by photogeologic study. A total of 40 vertical electric sounding (VES) locations and 5 CSAMT lines were deployed in the study area, the surveyed results are as following-G 1. The VES results provide shallower layer information. The resistivity of the layers from the surface to a depth of 50 m ranges from 10 to 600 ohm-m. The geoelctrical layer is K-type. The resistivity of the southern part of the Ho-kou fault is generally higher than that of the northern part. 2. The CSAMT results indicate that the resistivity of the layers is increased with depth. The highest resistivity among the layers is more than one thousand ohm-m. The resistivity of the layers in the southern part of Hu-kou fault is higher than the northern part at the depth 100 meters to 200 meter Combined the DC with the CSAMT results, it indicates that the position and features of the fault Hukou fault can be pointed out. In addition, the resistivity structures from the shallower to deeper layer are also be delineated.

Yi, Y. C.

2005-12-01

105

Causal fault detection and isolation based on a set-membership approach  

Microsoft Academic Search

This paper presents a diagnostic methodology relying on a set-membership approach for fault detection and on a causal model for fault isolation. Set-membership methods are a promising approach to fault detection because they take into account a priori knowledge of model uncertainties and measurement errors. Every uncertain model parameter and\\/or measurement is represented by a bounded variable. In this paper,

Ioana Fagarasan; Stéphane Ploix; Sylviane Gentil

2004-01-01

106

Non-robust tests for stuck-fault detection using signal waveform analysis: feasibility and advantages  

Microsoft Academic Search

In this paper we propose to use an output signal waveform analysis method called signal waveform integration for detection of stuck-at failures in combinational circuits. Non-robust tests are applied at-speed or faster to achieve high fault coverage, low test application time and detectability of redundant faults using directed random test generation techniques

Abhijit Chatterjee; Rathish Jayabharathi; Pankaj Pant; Jacob A. Abraham

1996-01-01

107

Rapid detection of faults for safety critical aircraft operation  

Microsoft Academic Search

Fault diagnosis typically assumes a sufficiently large fault signature and enough time for a reliable decision to be reached. However, for a class of safety critical faults on commercial aircraft engines, prompt detection is paramount within a millisecond range to allow accommodation to avert undesired engine behavior. At the same time, false positives must be avoided to prevent inappropriate control

Kai Goebel; Neil Eklund; Brent Brunell

2004-01-01

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

VCSEL fault location apparatus and method  

DOEpatents

An apparatus for locating a fault within an optical fiber is disclosed. The apparatus, which can be formed as a part of a fiber-optic transmitter or as a stand-alone instrument, utilizes a vertical-cavity surface-emitting laser (VCSEL) to generate a test pulse of light which is coupled into an optical fiber under test. The VCSEL is subsequently reconfigured by changing a bias voltage thereto and is used as a resonant-cavity photodetector (RCPD) to detect a portion of the test light pulse which is reflected or scattered from any fault within the optical fiber. A time interval .DELTA.t between an instant in time when the test light pulse is generated and the time the reflected or scattered portion is detected can then be used to determine the location of the fault within the optical fiber.

Keeler, Gordon A. (Albuquerque, NM); Serkland, Darwin K. (Albuquerque, NM)

2007-05-15

111

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

112

Experimental Study of Fault Arc Protection Based on UV Pulse Method in High Voltage Switchgear  

NASA Astrophysics Data System (ADS)

Based on the relationship between electrical equipment discharge and ultraviolet radiation, this paper proposed the use of UV pulse method to detect switchgear arcing faults. Switchgear protection system based on this new technique detects arcing faults by analyzing the ultraviolet produced by electric arc. This technique was implemented and tested in laboratory, and the performance of the protection module was verified: it is capable of calculating the number of UV pulses quickly and precisely, which indicates the intensity of fault arc, and therefore it can be applied to arcing faults protection system for detecting faults.

Wang, Jingang; Xu, Cheng; Sun, Jiaxiang

2014-06-01

113

Fault diagnosis method for machinery in unsteady operating condition by instantaneous power spectrum and genetic programming  

Microsoft Academic Search

This paper proposes a fault diagnosis method for plant machinery in an unsteady operating condition using instantaneous power spectrum (IPS) and genetic programming (GP). IPS is used to extract feature frequencies of each machine state from measured vibration signals for distinguishing faults by relative crossing information. Excellent symptom parameters for detecting faults are automatically generated by the GP. The excellent

Peng Chen; Masatoshi Taniguchi; Toshio Toyota; Zhengja He

2005-01-01

114

Development of a Surge Type Fault Locator using the Hybrid Detection Type Fault Recorder  

Microsoft Academic Search

We have proposed the new surge type FL using hybrid detection type fault recorder to measure the location of a line fault precisely in the power system. This new recorder has a feature that the starting detection of the recorder is not a instantanceous value of a high speed data but a effective value of low sampling data. This new

Shoichi Urano; Takeshi Yamada; Yoshifumi Ooura; Youheng Xu; Tatsuya Makimura; Yasutaka Yamaguchi

2009-01-01

115

Detection of faults and software reliability analysis  

NASA Technical Reports Server (NTRS)

Specific topics briefly addressed include: the consistent comparison problem in N-version system; analytic models of comparison testing; fault tolerance through data diversity; and the relationship between failures caused by automatically seeded faults.

Knight, J. C.

1987-01-01

116

Detecting intrusion faults in remotely controlled systems  

Microsoft Academic Search

In this paper, we propose a method to detect an unauthorized control signal being sent to a remote-controlled system (deemed an ldquointrusion faultrdquo or ldquointrusionrdquo) despite attempts to conceal the intrusion. We propose adding a random perturbation to the control signal and using signal detection techniques to determine the presence of that signal in observations of the system. Detection of

Salvatore Candido; Seth Hutchinson

2009-01-01

117

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

118

Online tribology ball bearing fault detection and identification  

Microsoft Academic Search

We present a feasibility analysis for the development of an online ball bearing fault detection and identification system. This system can effectively identify various fault stages related to the evolution of friction within the contact in the coated ball bearings. Data are collected from laboratory experiments involving forces, torque and acceleration sensors. To detect the ball bearing faulty stages, we

B. Ling; M. M. Khonsari

2007-01-01

119

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

120

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

National Technical Information Service (NTIS)

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...

M. C. Gonzalez R. M. Button

2003-01-01

121

Application of DA-Preconditioned FINN for Electric Power System Fault Detection  

Microsoft Academic Search

This paper proposes a hybrid method of Deterministic Annealing (DA) and Fuzzy Inference Neural Network (FINN) for electric power system fault detection. It extracts features of input data with two-staged precondition of Fast Fourier Transform (FFT) and DA. FFT is useful for extracting the features of fault currents while DA plays a key role to classify input data into clusters

Tadahiro Itagaki; Hiroyuki Mori; Takeshi Yamada; Shoichi Urano

2006-01-01

122

Application of fault detection and identification (FDI) techniques in power regulating systems of nuclear reactors  

Microsoft Academic Search

Application of failure detection and identification (FDI) algorithms have essentially been limited to identification of a global fault in the system, and no further attempts have been made to locate subcomponent faults for root cause analysis. This paper presents Kalman filter-based methods for FDI in power regulating systems of nuclear reactors. The attempt here is to explain how the behavior

Kallol Roy; R. N. Banavar; S. Thangasamy

1998-01-01

123

Incipient fault detection and isolation of sensors and field devices  

NASA Astrophysics Data System (ADS)

The purpose of this research is to develop a robust fault detection and isolation method, for detecting faults in process sensors, actuators, controllers and other field devices. The approach to the solution to this problem is summarized below. A novel approach for the validation of control system components and sensors was developed in this research. The process is composed of detecting a system anomaly, isolating the faulty component (such as sensors, actuators, and controllers), computing its deviation from expected value for a given system's normal condition, and finally reconstructing its output when applicable. A variant of the Group Method of Data Handling (GMDH) was developed in this research for generating analytical redundancy from relationships among different system components. A rational function approximation was used for the data-driven modeling scheme. This analytical redundancy is necessary for detecting system anomalies and isolating faulty components. A rule-base expert system was developed in order to isolate the faulty component. The rule-based was established from model-simulated data. A fuzzy-logic estimator was implemented to compute the magnitude of the loop component fault so that the operator or the controller might take corrective actions. This latter engine allows the system to be operated in a normal condition until the next scheduled shutdown, even if a critical component were detected as degrading. The effectiveness of the method developed in this research was demonstrated through simulation and by implementation to an experimental control loop. The test loop consisted of a level control system, flow, pressure, level and temperature measuring sensors, motor-operated valves, and a pump. Commonly observed device faults were imposed in different system components such as pressure transmitters, pumps, and motor-operated valves. This research has resulted in a framework for system component failure detection and isolation, allowing easy implementation of this method in any process control system (power plants, chemical industry, and other manufacturing industry). The technique would also aid the plant personnel in defining the minimal number of sensors to be installed in a process system, necessary for reliable component validation.

Ferreira, Paulo Brasko

124

Complex Demodulation for Bearing Fault Detection.  

National Technical Information Service (NTIS)

Vibration analysis using the high frequency resonance technique has been used successfully to detect incipient failure in rolling element bearings. This memo outlines a new method of obtaining the demodulated narrow band envelope of a bearing vibration si...

I. M. Howard

1989-01-01

125

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.

Moghadas, Amin A.; Shadaram, Mehdi

2010-01-01

126

Fiber Bragg grating sensor for fault detection in high voltage overhead transmission lines  

NASA Astrophysics Data System (ADS)

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) sensors. 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 signals. 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 sensors 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.

Moghadas, Amin

127

Fiber Bragg Grating sensor for fault detection in radial and network transmission lines.  

PubMed

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

128

Bearing Fault Detection in Induction Motor-Gearbox Drivetrain  

NASA Astrophysics Data System (ADS)

The main contribution in the hereby presented paper is to investigate the fault detection capability of a motor current signature analysis by expanding its scope to include the gearbox, and not only the induction motor. Detecting bearing faults outside the induction motor through the stator current analysis represents an interesting alternative to traditional vibration analysis. Bearing faults cause changes in the stator current spectrum that can be used for fault diagnosis purposes. A time-domain simulation of the drivetrain model is developed. The drivetrain system consists of a loaded single stage gearbox driven by a line-fed induction motor. Three typical bearing faults in the gearbox are addressed, i.e. defects in the outer raceway, the inner raceway, and the rolling element. The interaction with the fault is modelled by means of kinematical and mechanical relations. The fault region is modelled in order to achieve gradual loss and gain of contact. A bearing fault generates an additional torque component that varies at the specific bearing defect frequency. The presented dynamic electromagnetic dq-model of an induction motor is adjusted for diagnostic purpose and considers such torque variations. The bearing fault is detected as a phase modulation of the stator current sine wave at the expected bearing defect frequency.

Cibulka, Jaroslav; Ebbesen, Morten K.; Robbersmyr, Kjell G.

2012-05-01

129

Guaranteed robust fault detection and isolation techniques for small satellites  

NASA Astrophysics Data System (ADS)

The paper presents two generic fault detection and isolation (FDI) techniques which have shown remarkable robustness when applied to the SIMULINK model of a small satellite for thruster failures. While fundamentally different in their design approach, they both generate ?structured residuals? which accurately capture the failure mode. The diagnosis criterion in both methods relies on residuals direction rather than magnitude, which avoids the delays and expense of setting accurate thresholds for residuals magnitudes. Most importantly, this fact can account for the enhanced robustness to disturbances and sensor noise, as well as to significant parametric variations. Extensive Monte Carlo simulations are presented validating the robust performance of the two algorithms.

Valavani, L.; Tantouris, N.

2013-12-01

130

A Triple Redundant Controller which Adopts the TimeSharing Fault Recovery Method and its Application to a Power Converter Controller  

Microsoft Academic Search

A novel fault recovery method, in which memory copy from a normal system to a fault detected system is executed in time-sharing fashion, has been implemented in a triple redundant controller. This method reduces data copy bandwidth required for recovery of the fault detected system, and allows non-stop fault recovery with only a little hardware overhead, even when the controller

Kotaro Shimamura; Yuichiro Morita; Yoshitaka Takahashi; Takashi Hotta; Shigeta Ueda; Mikiya Nohara; Mitsuyasu Kido; Seji Tanaka; Kazuhiro Imaie; Koji Sakamoto; Tatsuhito Nakajima

1998-01-01

131

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

132

A novel KFCM based fault diagnosis method for unknown faults in satellite reaction wheels.  

PubMed

Reaction wheels are one of the most critical components of the satellite attitude control system, therefore correct diagnosis of their faults is quintessential for efficient operation of these spacecraft. The known faults in any of the subsystems are often diagnosed by supervised learning algorithms, however, this method fails to work correctly when a new or unknown fault occurs. In such cases an unsupervised learning algorithm becomes essential for obtaining the correct diagnosis. Kernel Fuzzy C-Means (KFCM) is one of the unsupervised algorithms, although it has its own limitations; however in this paper a novel method has been proposed for conditioning of KFCM method (C-KFCM) so that it can be effectively used for fault diagnosis of both known and unknown faults as in satellite reaction wheels. The C-KFCM approach involves determination of exact class centers from the data of known faults, in this way discrete number of fault classes are determined at the start. Similarity parameters are derived and determined for each of the fault data point. Thereafter depending on the similarity threshold each data point is issued with a class label. The high similarity points fall into one of the 'known-fault' classes while the low similarity points are labeled as 'unknown-faults'. Simulation results show that as compared to the supervised algorithm such as neural network, the C-KFCM method can effectively cluster historical fault data (as in reaction wheels) and diagnose the faults to an accuracy of more than 91%. PMID:22035775

Hu, Di; Sarosh, Ali; Dong, Yun-Feng

2012-03-01

133

Robust fuzzy fault detection and isolation approach applied to surge in centrifugal compressor modeling and control  

Microsoft Academic Search

This work presents the results of applying an advanced fault detection and isolation technique to centrifugal compressor;\\u000a this advanced technique uses physics models of the centrifugal compressor with a fuzzy modeling and control solution method.\\u000a The fuzzy fault detection and isolation has become an issue of primary importance in modern process engineering automation\\u000a as it provides the prerequisites for the

Ahmed Hafaifa; Kouider Laroussi; Ferhat Laaouad

2010-01-01

134

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

SciTech Connect

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

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

1994-02-01

135

Soft Computing Application in Fault Detection of Induction Motor  

SciTech Connect

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. Dr. [Electrical Engineering Department, BESUS, Shibpur (India)

2010-10-26

136

Estimation of fault parameters of stratified structures based on wavelet packet algorithm in free-oscillation testing method  

Microsoft Academic Search

Stratified structures have a widely usage in aerospace technologies. Free oscillation testing method (FOM) used for testing of stratified structures with large acoustic decay coefficient. Early faults detection was performed by analysis of energy spectrum of recorded mechanical oscillations.But sizes and depths of faults cannot be estimated using this method. For the first time estimation of fault's size and depth

Alexander M. Akhmetshin; Andrew S. Sendetski

1997-01-01

137

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

138

A fault detection service for wide area distributed computations.  

SciTech Connect

The potential for faults in distributed computing systems is a significant complicating factor for application developers. While a variety of techniques exist for detecting and correcting faults, the implementation of these techniques in a particular context can be difficult. Hence, we propose a fault detection service designed to be incorporated, in a modular fashion, into distributed computing systems, tools, or applications. This service uses well-known techniques based on unreliable fault detectors to detect and report component failure, while allowing the user to tradeoff timeliness of reporting against false positive rates. We describe the architecture of this service, report on experimental results that quantify its cost and accuracy, and describe its use in two applications, monitoring the status of system components of the GUSTO computational grid testbed and as part of the NetSolve network-enabled numerical solver.

Stelling, P.

1998-06-09

139

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

140

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

141

Bearing Localized Fault Detection Based on Hilbert-Huang Transformation  

Microsoft Academic Search

The Hilbert-Huang transform and its marginal spectrum are applied to bearing fault diagnosis of ball bearing. The principle of Empirical mode decomposition (EMD), Hilbert-Huang transformation (HHT) and marginal spectrum is introduced. Firstly, the vibration signals of bearing fault are separated into several intrinsic mode functions (IMFs) using EMD method. Secondly, the marginal spectrum of each IMF is calculated. In the

Hui Li; Yuping Zhang

2007-01-01

142

APPLICATION OF WAVELET TRANSFORM TO DETECT FAULTS IN ROTATING MACHINERY  

Microsoft Academic Search

The field of fault diagnostic in rotating machinery is vast, including the diagnosis of items such as rotating shafts, rolling element bearings, couplings, gears and so on. The different types of faults that are observed in these areas and the methods of their diagnosis are accordingly great, including vibration analysis, model-based techniques, statistical analysis and artificial intelligence techniques. However, they

Robson Pederiva

143

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

144

Aircraft Fault Detection and Classification Using MultiLevel Immune Learning Detection  

Microsoft Academic Search

This work is an extension of a recently developed software tool called MILD (Multi-level Immune Learning Detection), which implements a negative selection algorithm for anomaly and fault detection that is inspired by the human immune system. The immunity-based approach can detect a broad spectrum of known and unforeseen faults. We extend MILD by applying a neural network classifier to identify

Derek Wong; Scott Poll

145

A new fault localizing method for the program debugging process  

Microsoft Academic Search

A large amount of effort is spent on fault localization in the program debugging process. So, it is necessary to develop effective fault-localizing methods. Dynamic slicing is a technique for narrowing down where a fault is likely to exist. However, dynamic slicing requires a large amount of run time due to the tracing information that is collected during the program's

Lin Lian; Shinji Kusumoto; Tohru Kikuno; Ken-ichi Matsumoto; Koji Torii

1997-01-01

146

Development of a Surge Type Fault Locator using the Hybrid Detection Type Fault Recorder  

NASA Astrophysics Data System (ADS)

We have proposed the new surge type FL using hybrid detection type fault recorder to measure the location of a line fault precisely in the power system. This new recorder has a feature that the starting detection of the recorder is not a instantanceous value of a high speed data but a effective value of low sampling data. This new recorder has a high speed sampling part and a low speed sampling part. A high speed sampling part works a recording of surge data. On the other hand, a low speed sampling part works a detecting of trasmission line fault. The authors carried out field tests with this new recorder installed at plants and substation in the 275kV power transmission system of TEPCO (Tokyo Electric Power Company). And we obtained good results. This paper presents these results.

Urano, Shoichi; Yamada, Takeshi; Ooura, Yoshifumi; Xu, Youheng; Makimura, Tatsuya; Yamaguchi, Yasutaka

147

Sensor fault detection using the Mahalanobis distance  

SciTech Connect

A method is described by which a localized sensor abnormality can be detected using the Mahalanobis distance. The Mahalanobis distance is approximately the weighted distance from the hyperplane formed by the principal components to the particular observation. Qualitatively, the principal components correspond to the physical laws that govern the behavior of the systems and constraints placed on the system. If there are more sensors than principal components, there are redundant measurements. This redundancy can be used to detect abnormalities that are due either to sensor failure or a localized change in the system being measured. The method compares the distribution of the Mahalanobis distance during normal operation with the distribution during the current operation. A likelihood ratio test is then used to determine if a sensor has gone bad or if operations in the reactor are different from normal. The sensor whose value is not normal is identified by comparing Mahalanobis distances computed with one sensor masked. When the abnormal sensor is masked, the Mahalanobis distance for this subset of sensors will be within prespecified bounds. The method is demonstrated on 20 subassembly output thermocouples in the core of Experimental Breeder Reactor II.

White, A.M.; Gross, K.C. (Argonne National Lab., IL (United States)); Kubic, W.L (Los Alamos National Lab., NM (United States))

1993-01-01

148

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

149

Soft-Fault Detection Technologies Developed for Electrical Power Systems  

NASA Technical Reports Server (NTRS)

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

Button, Robert M.

2004-01-01

150

Intelligent method for diagnosing structural faults of rotating machinery using ant colony optimization.  

PubMed

Structural faults, such as unbalance, misalignment and looseness, etc., often occur in the shafts of rotating machinery. These faults may cause serious machine accidents and lead to great production losses. This paper proposes an intelligent method for diagnosing structural faults of rotating machinery using ant colony optimization (ACO) and relative ratio symptom parameters (RRSPs) in order to detect faults and distinguish fault types at an early stage. New symptom parameters called "relative ratio symptom parameters" are defined for reflecting the features of vibration signals measured in each state. Synthetic detection index (SDI) using statistical theory has also been defined to evaluate the applicability of the RRSPs. The SDI can be used to indicate the fitness of a RRSP for ACO. Lastly, this paper also compares the proposed method with the conventional neural networks (NN) method. Practical examples of fault diagnosis for a centrifugal fan are provided to verify the effectiveness of the proposed method. The verification results show that the structural faults often occurring in the centrifugal fan, such as unbalance, misalignment and looseness states are effectively identified by the proposed method, while these faults are difficult to detect using conventional neural networks. PMID:22163833

Li, Ke; Chen, Peng

2011-01-01

151

Intelligent Method for Diagnosing Structural Faults of Rotating Machinery Using Ant Colony Optimization  

PubMed Central

Structural faults, such as unbalance, misalignment and looseness, etc., often occur in the shafts of rotating machinery. These faults may cause serious machine accidents and lead to great production losses. This paper proposes an intelligent method for diagnosing structural faults of rotating machinery using ant colony optimization (ACO) and relative ratio symptom parameters (RRSPs) in order to detect faults and distinguish fault types at an early stage. New symptom parameters called “relative ratio symptom parameters” are defined for reflecting the features of vibration signals measured in each state. Synthetic detection index (SDI) using statistical theory has also been defined to evaluate the applicability of the RRSPs. The SDI can be used to indicate the fitness of a RRSP for ACO. Lastly, this paper also compares the proposed method with the conventional neural networks (NN) method. Practical examples of fault diagnosis for a centrifugal fan are provided to verify the effectiveness of the proposed method. The verification results show that the structural faults often occurring in the centrifugal fan, such as unbalance, misalignment and looseness states are effectively identified by the proposed method, while these faults are difficult to detect using conventional neural networks.

Li, Ke; Chen, Peng

2011-01-01

152

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.

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

2012-01-01

153

Statistical characterization of the GLR based fault detection  

Microsoft Academic Search

This paper is mainly focused on providing the probabilistic performance criteria for generalized likelihood ratio (GLR) test based fault detection schemes. Analytical expressions regarding probability distribution of the detection delay and time between false alarms are presented, which are validated by simulation. The results can be applied to important industrial application, such as abnormal signal monitoring (magnitude or energy), targeting

Shuonan Yang; Qing Zhao

2011-01-01

154

Fault Detection and Analysis of Distributed Power System Short-circuit Using Wavelet Fractal Network  

Microsoft Academic Search

A novel method based on wavelet network and fractal theory for detecting short-circuit fault is proposed. To increase the signal-noise-ratio of the fault signal, the signal denoising technology using the statistic rule is brought forward to determine the threshold and the decomposition level of each order of wavelet space. On the basis of the inter relationship of wavelet transform and

Song Yuhai; Wang Guangjian; Chen Xiangguo

2007-01-01

155

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

156

Fuzzy Detection and Diagnosis of Fault Modes in a Voltage-Fed PWM Inverter Induction Motor  

Microsoft Academic Search

This paper describes a fuzzy-based method of fault detection and diagnosis in a PWM inverter feeding an induction motor. The proposed fuzzy approach is a sensor-based technique using the mains current measurement to detect intermittent loss of firing pulses in the inverter switches. A localization domain made with seven patterns is built with the stator Concordia current vector. One is

F. Zidani; D. Diallo; M. E. H. Benbouzid; R. Nait-Said

2005-01-01

157

High Resolution Seismic Imaging of Fault Zones: Methods and Examples From The San Andreas Fault  

NASA Astrophysics Data System (ADS)

Seismic imaging of fault zones at shallow depths is challenging. Conventional seismic reflection methods do not work well in fault zones that consist of non-planar strata or that have large variations in velocity structure, two properties that occur in most fault zones. Understanding the structure and geometry of fault zones is important to elucidate the earthquake hazard associated with fault zones and the barrier effect that faults impose on subsurface fluid flow. In collaboration with the San Francisco Public Utilities Commission (SFPUC) at San Andreas Lake on the San Francisco peninsula, we acquired combined seismic P-wave and S-wave reflection, refraction, and guided-wave data to image the principal strand of the San Andreas Fault (SAF) that ruptured the surface during the 1906 San Francisco earthquake and additional fault strands east of the rupture. The locations and geometries of these fault strands are important because the SFPUC is seismically retrofitting the Hetch Hetchy water delivery system, which provides much of the water for the San Francisco Bay area, and the delivery system is close to the SAF at San Andreas Lake. Seismic reflection images did not image the SAF zone well due to the brecciated bedrock, a lack of layered stratigraphy, and widely varying velocities. Tomographic P-wave velocity images clearly delineate the fault zone as a low-velocity zone at about 10 m depth in more competent rock, but due to soil saturation above the rock, the P-waves do not clearly image the fault strands at shallower depths. S-wave velocity images, however, clearly show a diagnostic low-velocity zone at the mapped 1906 surface break. To image the fault zone at greater depths, we utilized guided waves, which exhibit high amplitude seismic energy within fault zones. The guided waves appear to image the fault zone at varying depths depending on the frequency of the seismic waves. At higher frequencies (~30 to 40 Hz), the guided waves show strong amplification at the 1906 surface break and at about 20 m to the east, but at lower frequencies (2-5 Hz), the guided waves show strong amplification approximately 10 m east of the 1906 surface break. We attribute the difference in amplification of guided waves to an east-dipping fault strand that merges with other strands below about 10 m depth. Vp/Vs and Poisson's ratios clearly delineate multiple fault strands about 2 km north of the mapped 1906 surface break at the SFPUC intake structure. Combining these fault-imaging methods provide a powerful set of tools for mapping fault zones in the shallow subsurface in areas of complex geology.

Catchings, R. D.; Rymer, M. J.; Goldman, M.; Prentice, C. S.; Sickler, R. R.; Criley, C.

2011-12-01

158

Method and apparatus for fault tolerance  

NASA Technical Reports Server (NTRS)

A method and apparatus for achieving fault tolerance in a computer system having at least a first central processing unit and a second central processing unit. The method comprises the steps of first executing a first algorithm in the first central processing unit on input which produces a first output as well as a certification trail. Next, executing a second algorithm in the second central processing unit on the input and on at least a portion of the certification trail which produces a second output. The second algorithm has a faster execution time than the first algorithm for a given input. Then, comparing the first and second outputs such that an error result is produced if the first and second outputs are not the same. The step of executing a first algorithm and the step of executing a second algorithm preferably takes place over essentially the same time period.

Masson, Gerald M. (Inventor); Sullivan, Gregory F. (Inventor)

1993-01-01

159

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

NASA Technical Reports Server (NTRS)

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

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

1985-01-01

160

Fault Detection for T-S Fuzzy Discrete Systems in Finite-Frequency Domain.  

PubMed

This paper investigates the problem of fault detection for Takagi-Sugeno (T-S) fuzzy discrete systems in finite-frequency domain. By means of the T-S fuzzy model, both a fuzzy fault detection filter system and the dynamics of filtering error generator are constructed. Two finite-frequency performance indices are introduced to measure fault sensitivity and disturbance robustness. Faults are considered in a middle frequency domain, while disturbances are considered in another certain finite-frequency domain interval. By using the generalized Kalman-Yakubovi [Formula: see text]-Popov Lemma in a local linear system model, the design methods are presented in terms of solutions to a set of linear matrix inequalities, which can be readily solved via standard numerical software. The design problem is formulated as a two-objective optimization algorithm. A numerical example is given to illustrate the effectiveness and potential of the developed techniques. PMID:21257383

Yang, Hongjiu; Xia, Yuanqing; Liu, Bo

2011-01-20

161

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

PubMed

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

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

2014-01-01

162

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

163

Optimization-based tuning of LPV fault detection filters for civil transport aircraft  

NASA Astrophysics Data System (ADS)

In this paper, a two-step optimal synthesis approach of robust fault detection (FD) filters for the model based diagnosis of sensor faults for an augmented civil aircraft is suggested. In the first step, a direct analytic synthesis of a linear parameter varying (LPV) FD filter is performed for the open-loop aircraft using an extension of the nullspace based synthesis method to LPV systems. In the second step, a multiobjective optimization problem is solved for the optimal tuning of the LPV detector parameters to ensure satisfactory FD performance for the augmented nonlinear closed-loop aircraft. Worst-case global search has been employed to assess the robustness of the fault detection system in the presence of aerodynamics uncertainties and estimation errors in the aircraft parameters. An application of the proposed method is presented for the detection of failures in the angle-of-attack sensor.

Ossmann, D.; Varga, A.

2013-12-01

164

Gear fault detection using multi-scale morphological filters  

Microsoft Academic Search

This work gives a thorough exploration of the capacity of multi-scale morphological filters for gear fault detection. Eight types of multi-scale morphological filters are designed based on the mathematical morphology theory. A characteristic frequency intensity coefficient (CFIC) is defined as a quantity criterion for assessing the effectiveness of the filters. Both simulated signal and practical vibration signal measured from a

Bing Li; Pei-lin Zhang; Zheng-jun Wang; Shuang-shan Mi; Ying-tang Zhang

2011-01-01

165

Fault detection and isolation for stochastic linear hybrid systems  

Microsoft Academic Search

A model-based fault detection and isolation (FDI) scheme is proposed for a stochastic linear hybrid system (SLHS) which has both discrete state dynamics and linear continuous state dynamics. We first propose a residual generation filter for the SLHS. It is shown that this filter generates a residual vector with zero mean and a known covariance when the SLHS matches the

Chze Eng Seah; Inseok Hwang

2009-01-01

166

Fault Tolerance in Collaborative Sensor Networks for Target Detection  

Microsoft Academic Search

Collaboration in sensor networks must be fault tolerant dueto the harsh environmental conditions in which such networks can be deployed. This paper focuses on finding algorithms for collaborative target detection that are efficient in terms of communicatio n cost, precision, accuracy, and number of faulty sensors tolerable in the network. Two algorithms, na mely value fusion and decision fusion are

Thomas Clouqueur; Kewal K. Saluja; Parameswaran Ramanathan

2004-01-01

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

An intelligent decision-making system for detecting high impedance faults  

SciTech Connect

High impedance faults do not draw sufficient fault current to be detected by such a conventional protective scheme. Arcing is usually associated with these faults, which may result in a fire hazard. The harmonic currents characterized by an arc are variable, transitory, and random in their behavior. This research concentrates on designing an intelligent decision making system which uses multiple detection techniques incorporated with an appropriate detection reasoning method and a learning ability to provide a more effective solution for high impedance fault detection. Major parts of this system are a technique selection, a technique combination, and an induction process. The method of decision making under incomplete knowledge is used to select appropriate techniques because the information on the performance of techniques are available but not complete. With these selected techniques, the Dempster-Shafer theory is adopted to find a final belief about the system status by combining the belief from each technique. Inductive reasoning with minimum entropy is applied to find decision rules and thus to adjust the technique selection process. A learning detection system which combines all three major parts is proposed to realize this intelligent decision making system. The learning detection system synthesizes the final belief of the combined techniques, the status output of a decision tree from the inductive reasoning process, and an event detector output to detect and identify the system status. The intelligent decision making system makes a smart decision on an example execution with a complex test set of sample data.

Kim, Changjong.

1989-01-01

169

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

170

Spare capacity as a means of fault detection and diagnosis in multiprocessor systems  

SciTech Connect

A technique is described for detecting and diagnosing faults at the processor level in a multiprocessor system. In this method, a process is assigned whenever possible to two processors: the processor that it would normally be assigned to (primary) and an additional processor which would otherwise be idle (secondary). Two strategies are described and analyzed: one which is preemptive and another which is nonpreemptive. It is shown that for moderately loaded systems, a sufficient percentage of processes can be performed redundantly using the system's spare capacity to provide a basis for fault detection and diagnosis with virtually no degradation of response time. A multiprocessor is described which uses the approach for detecting faults at the processor level.

Dahbura, A.T.; Sabnani, K.K.

1989-06-01

171

Main Propulsion Functional Path Analysis for Performance Monitoring Fault Detection and Annunciation.  

National Technical Information Service (NTIS)

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. Som...

E. L. Keesler

1974-01-01

172

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

173

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.

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

2009-01-01

174

Art2 and multiscale art-2 for on-line process fault detection — Validation via industrial case studies and Monte Carlo simulation  

Microsoft Academic Search

Data from most industrial processes contain contributions at multiple scales in time and frequency. In contrast, most existing methods for fault detection are best for detecting events at only one scale. This paper provides experimental validation and insight into a new method of process fault detection based on the integration of multiscale signal representation and scale-specific clustering-based diagnosis. The multiscale

H. B. Aradhye; J. F. Davis; B. R. Bakshi

2002-01-01

175

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

PubMed

Measured data or states for a nonlinear dynamic system is usually contaminated by outliers. Identifying and removing outliers will make the data (or system states) more trustworthy and reliable since outliers in the measured data (or states) can cause missed or false alarms during fault diagnosis. In addition, faults can make the system states nonstationary needing a novel analytical model-based fault detection (FD) framework. In this paper, an online outlier identification and removal (OIR) scheme is proposed for a nonlinear dynamic system. Since the dynamics of the system can experience unknown changes due to faults, traditional observer-based techniques cannot be used to remove the outliers. The OIR scheme uses a neural network (NN) to estimate the actual system states from measured system states involving outliers. With this method, the outlier detection is performed online at each time instant by finding the difference between the estimated and the measured states and comparing its median with its standard deviation over a moving time window. The NN weight update law in OIR is designed such that the detected outliers will have no effect on the state estimation, which is subsequently used for model-based fault diagnosis. In addition, since the OIR estimator cannot distinguish between the faulty or healthy operating conditions, a separate model-based observer is designed for fault diagnosis, which uses the OIR scheme as a preprocessing unit to improve the FD performance. The stability analysis of both OIR and fault diagnosis schemes are introduced. Finally, a three-tank benchmarking system and a simple linear system are used to verify the proposed scheme in simulations, and then the scheme is applied on an axial piston pump testbed. The scheme can be applied to nonlinear systems whose dynamics and underlying distribution of states are subjected to change due to both unknown faults and operating conditions. PMID:24808037

Ferdowsi, Hasan; Jagannathan, Sarangapani; Zawodniok, Maciej

2014-05-01

176

Towards In-Flight Detection and Accommodation of Faults in Aircraft Engines  

Microsoft Academic Search

To effectively accommodate safety critical faults in-flight it is necessary to rapidly detect them and to have a means to accommodate the fault. We present results on model-based fault detection using sensor residuals from an extended Kalman filter with an embedded real-time engine model to characterize un-faulted behavior over the flight envelope. Thereafter, we present an approach for online fault

Randal Rausch; Daniel E. Viassolo; Aditya Kumar; Kai Goebel; Neil Eklund; Brent Brunell; Pierino Bonanni

2004-01-01

177

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

178

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

179

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

180

Speed sensorless AC drive with inverter output filter and fault detection using load torque signal  

Microsoft Academic Search

In this paper, a sensorless induction motor (IM) drive using speed observer system is presented. The system includes load torque computation for gear fault detection. Nonlinear control method is adopted for controlling the motor over a wide speed range. An LC filter for smoothing current and voltage waveforms is used at the output of the voltage inverter. The use of

Jaroslaw Guzinski; Haitham Abu-Rub; Hamid A. Toliyat

2010-01-01

181

Structured residual vector-based approach to sensor fault detection and isolation  

Microsoft Academic Search

This paper proposes a novel approach to detection and isolation of faulty sensors in multivariate dynamic systems. After formulating the problem of sensor fault detection and isolation in a dynamic system represented by a state space model, we develop the optimal design of a primary residual vector for fault detection and a set of structured residual vectors for fault isolation

Weihua Li; Sirish Shah

2002-01-01

182

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

183

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

184

Application of DA-Preconditioned FINN for Electric Power System Fault Detection  

NASA Astrophysics Data System (ADS)

This paper proposes a hybrid method of Deterministic Annealing (DA) and Fuzzy Inference Neural Network (FINN) for electric power system fault detection. It extracts features of input data with two-staged precondition of Fast Fourier Transform (FFT) and DA. FFT is useful for extracting the features of fault currents while DA plays a key role to classify input data into clusters in a sense of global classification. FINN is a more accurate estimation model than the conventional artificial neural networks (ANNs). The proposed method is successfully applied to data obtained by the Tokyo Electric Power Company (TEPCO) power simulator.

Itagaki, Tadahiro; Mori, Hiroyuki; Yamada, Takeshi; Urano, Shoichi

185

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

186

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

187

Robust detection and isolation of process faults using neural networks  

Microsoft Academic Search

The problem of robust model-based diagnosis of process faults is addressed by means of artificial neural networks. Different structures and learning methods are investigated for both approaches to function approximation and pattern recognition. Main emphasis is placed upon static and dynamic neural nets that are used as predictors of nonlinear models for symptom generation. Dynamic neural networks are properly integrated

T. Marcu; L. Mirea

1997-01-01

188

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

189

A robust fault-detection approach with application in a rolling-mill process  

Microsoft Academic Search

This paper proposes a new approach to robust fault detection. The proposed scheme adopts an observer-based fault-detection scheme and is characterized by a structure of two observers. One observer estimates the plant output driven by the plant normal input. The other observer estimates the output driven by the fault. To demonstrate the proposed fault-detection scheme, a rolling mill case study

Da-Wei Gu; Fu Wah Poon

2003-01-01

190

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

191

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

192

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

NASA Astrophysics Data System (ADS)

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 generally possesses a low signal-to-noise ratio, where the classical signal processing methods cannot be effectively applied and the extracted features are usually submerged into the severe background noise. In this paper, a novel random and nonstationary vibratory signature analysis (R&N-VSA) technique is presented to address this challenge. The original vibration signal is decomposed into fault-related and non-fault-related signal segments, and multi-level exponential moving average power filtering is suggested to guide this decomposition. Instead of analyzing the whole vibratory signal, the developed Shannon wavelet spectrum analysis is more efficiently applied on the truncated fault-related signal segments so as to enhance the features' characteristics. The effectiveness of the proposed technique is examined through a series of tests with two experimental setups, and the investigation results show that the developed R&N-VSA technique is an effective signal processing technique for incipient machine fault detection.

Liu, Jie

2012-05-01

193

Simulation of secondary fault shear displacements - method and application  

NASA Astrophysics Data System (ADS)

We present an earthquake simulation method to calculate dynamically and statically induced shear displacements on faults near a large earthquake. Our results are aimed at improved safety assessment of underground waste storage facilities, e.g. a nuclear waste repository. For our simulations, we use the distinct element code 3DEC. We benchmark 3DEC by running an earthquake simulation and then compare the displacement waveforms at a number of surface receivers with the corresponding results obtained from the COMPSYN code package. The benchmark test shows a good agreement in terms of both phase and amplitude. In our application to a potential earthquake near a storage facility, we use a model with a pre-defined earthquake fault plane (primary fault) surrounded by numerous smaller discontinuities (target fractures) representing faults in which shear movements may be induced by the earthquake. The primary fault and the target fractures are embedded in an elastic medium. Initial stresses are applied and the fault rupture mechanism is simulated through a programmed reduction of the primary fault shear strength, which is initiated at a pre-defined hypocenter. The rupture is propagated at a typical rupture propagation speed and arrested when it reaches the fault plane boundaries. The primary fault residual strength properties are uniform over the fault plane. The method allows for calculation of target fracture shear movements induced by static stress redistribution as well as by dynamic effects. We apply the earthquake simulation method in a model of the Forsmark nuclear waste repository site in Sweden with rock mass properties, in situ stresses and fault geometries according to the description of the site established by the Swedish Nuclear Fuel and Waste Management Co (SKB). The target fracture orientations are based on the Discrete Fracture Network model developed for the site. With parameter values set to provide reasonable upper bound estimates of target fracture displacements, the model generates primary fault slip and slip velocities that are both high compared to those found in real earthquakes. The calculated target fracture movements reach some tens of millimetres on 300 m diameter fractures. We also present results indicating the sensitivity of primary fault slip and target fracture movements to e.g. variation of primary fault residual strength, change of hypocenter location and variations in the initial stress field.

Fälth, Billy; Hökmark, Harald; Lund, Björn; Mai, P. Martin; Munier, Raymond

2014-05-01

194

Documentation of the current fault detection, isolation and reconfiguration software of the AIPS fault-tolerant processor  

NASA Technical Reports Server (NTRS)

Documentation is presented of the December 1986 version of the ADA code for the fault detection, isolation, and reconfiguration (FDIR) functions of the Advanced Information processing System (AIPS) Fault-Tolerant Processor (FTP). Because the FTP is still under development and the software is constantly undergoing changes, this should not be considered final documentation of the FDIR software of the FTP.

Lanning, David T.; Shepard, Allen W.; Johnson, Sally C.

1987-01-01

195

A coupled rotor-fuselage vibration analysis for helicopter rotor system fault detection  

NASA Astrophysics Data System (ADS)

A coupled rotor-fuselage vibration analysis for helicopter rotor system fault detection is developed. The coupled rotor/fuselage/vibration absorbers (bifilar type) system incorporates consistent structural, aerodynamic and inertial couplings. The aeroelastic analysis is based on finite element methods in space and time. The coupled rotor, absorbers and fuselage equations are transformed into the modal space and solved in the fixed coordinate system. A coupled trim procedure is used to solve the responses of rotor, fuselage and vibration absorber, rotor trim control and vehicle orientation simultaneously. Rotor system faults are modeled by changing blade structural, inertial and aerodynamic properties. Both adjustable and component faults, such as misadjusted trim-tab, misadjusted pitch-control rod (PCR), imbalanced mass and pitch-control bearing freeplay, are investigated. Detailed SH-60 helicopter fuselage NASTRAN model is integrated into the analysis. Validation study was performed using SH-60 helicopter flight test data. The prediction of fuselage natural frequencies show fairly large error compared to shake test data. Analytical predictions of fuselage baseline (without fault) 4/rev vibration and fault-induced 1/rev vibration and blade displacement deviations are compared with SH-60 flight test (with prescribed fault) data. The fault-induced 1/rev fuselage vibration (magnitude and phase) predicted by present analysis generally capture the trend of the flight test data, although prediction under-predicts. The large discrepancy of fault-induced 1/rev vibration magnitude at hover between prediction and flight test data partially comes from the variation of flight condition (not perfect hover) and partially due to the effect of the rotor-fuselage aerodynamic interaction (wake effect) at low speed which is not considered in the analysis. Also the differences in the phase prediction is not clear since only the magnitude and phase information were given instead of the original vibration time-history. The imbalanced mass fault causes higher 1/rev roll vibration that is insensitive to the airspeed. The misadjusted trim-tab fault induced 1/rev vertical vibration increases with airspeed. The misadjusted pitch-control rod fault causes high vibration at hover. A parametric study was conducted to identify key factors that affect the fault-induced fuselage vibration. Analysis show that elastic fuselage model and precise hub modeling (inclusion of vibration absorbers) are essential to the vibration pre diction. The analysis shows that a compound fault can be expressed as a linear combination of individual faults involved. Aircraft operational parameters, such as gross-weight; center of gravity location, flight speed, flight path and aircraft configuration, have significant impact on the fault-induced 1/rev vibration. Prediction show that there are certain patterns in the fault-induced 1/rev hub-loads. Thus measuring both fuselage vibration and hub loads may benefit rotor system fault detection.

Yang, Mao

196

Application of fault detection techniques to spiral bevel gear fatigue data  

NASA Technical Reports Server (NTRS)

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

197

Investigation of Active Fault Scarps by Means of Geophysical Prospecting Methods, Javakheti Fault Case, Georgia  

NASA Astrophysics Data System (ADS)

Current presentation concerns investigation of Javakheti seismically active fault (Georgia, South Caucasus region) by means of Geophysical prospecting methods, carried out during the past two years. The named fault represents the major seismo tectonic structure at Javakhety volcanic highland. Fault segments at some places are well expressed on surface and several of those were mapped even during the Geologic surveys carried in 60-70's of previous century, though not recognized as a single structure. Detailed study of seismically active faults is an important component for proper seismic hazard assessment. Fault scarps, an evidence of fault's activity, are expressed on the earth surface as a result of accumulated rapid displacements due to earthquakes. Geomorphologic studies could provide us with rather general information about the fault, while much more information can be derived from paleo trenching and borehole coring. Unfortunately these methods are quite expensive and time consuming, requiring significant technical and man resources. Shallow Geophysical prospecting methods seems to be a valuable addition to above mentioned techniques. In our case extensive Geophysical prospecting surveys, preceded by Geomorphologic and Geologic Surveys have provided valuable information, first of all for correct identification of fault but also regarding the fault dynamics and internal structure of scarps. During this year geophysical studies were followed by paleo trenching at two locations, preliminary selected based on Geophysical data. Both trenches appeared to be successful, were revealed tracks of several paleo earthquakes currently under processing. Studies were also focused on development of Geophysical prospecting techniques and Interpretation of the results. During the past two years fault scarps were studied by means of Seismic prospecting methods (refracted waves, 2D tomography and surface waves), electric resistivity and Ground Penetrating Radar (200 and 80 MHz antennas). Al these rather inexpensive methods were applied along the same profiles, supplementing each other and providing favorable conditions for analysis and interpretation. As mentioned above, two of the profiles were excavated providing ground truth data and giving more confidence two our interpretations. Presumably, the approaches developed and accumulated experience could be of interest for future studies.

Elashvili, M.; Sakhelashvili, G.; Gigiberia, M.; Maisaia, I.; Godoladze, T.; Javakhishvili, Z.; Durgaryan, R.; Gevorgyan, M.

2011-12-01

198

Real-Time Fault Detection and Diagnostics Using FPGA-based Architectures  

Microsoft Academic Search

A new methodology for radiation induced real-time fault detection and diagnosis, utilizing FPGA-based architectures was developed. The methodology includes a full test platform to evaluate a circuit while under radiation and an algorithm to detect and diagnose fault locations within a circuit using Triple Design Triple Modular Redundancy (TDTMR). An analysis of the system was established using a fault injection.

Nathan Naber; Thomas Getz; Yong Kim; James Petrosky

2010-01-01

199

Concurrent Structure-Independent Fault Detection Schemes for the Advanced Encryption Standard  

Microsoft Academic Search

The Advanced Encryption Standard (AES) has been lately accepted as the symmetric cryptography standard for confidential data transmission. However, the natural and malicious injected faults reduce its reliability and may cause confidential information leakage. In this paper, we study concurrent fault detection schemes for reaching a reliable AES architecture. Specifically, we propose low-cost structure-independent fault detection schemes for the AES

Mehran Mozaffari-Kermani; Arash Reyhani-Masoleh

2010-01-01

200

Distributed Bayesian Algorithms for Fault-Tolerant Event Region Detection in Wireless Sensor Networks  

Microsoft Academic Search

We propose a distributed solution for a canonical task in wireless sensor networks—the binary detection of interesting environmental events. We explicitly take into account the possibility of sensor measurement faults and develop a distributed Bayesian algorithm for detecting and correcting such faults. Theoretical analysis and simulation results show that 85-95 percent of faults can be corrected using this algorithm, even

Bhaskar Krishnamachari; S. Sitharama Iyengar

2004-01-01

201

A new three-dimensional method of fault reactivation analysis  

NASA Astrophysics Data System (ADS)

A 3-D method to evaluate the reactivation potential of fault planes is proposed. The method can be applied to cohesive or noncohesive faults whatever their orientation 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 shape ratio (? = (?2 - ?3)/(?1 - ?3)), the coefficient of static friction ?s of the fault, and the fault cohesion C0. The method is 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 proposed 3-D fault reactivation analysis appears complementary to geophysical investigations.

Leclère, Henri; Fabbri, Olivier

2013-03-01

202

Migrating Fault Trees To Decision Trees For Real Time Fault Detection On International Space Station  

Microsoft Academic Search

Fault Tree Analysis shows the possible causes of a system malfunction by enumerating the suspect components and their respective failure modes that may have induced the problem. Complex systems often use fault trees to analyze the faults. Fault diagnosis, when error occurs, is performed by engineers and analysts performing extensive examination of all data gathered during the mission. International Space

Charles Lee; Richard L. Alena; Peter Robinson

2005-01-01

203

A novel concurrent fault simulation method for mixed-signal circuits  

Microsoft Academic Search

Fault simulation is critical in test development and fault diagnosis for mixed-signal systems. In this paper we present a novel concurrent fault simulation method for analog\\/digital mixed-signal circuits. A prototype mixed-signal fault simulation system is developed based on two existing digital and analog fault simulators. The key issue of fault list propagation between digital and analog fault simulators is addressed.

Junwei Hout; William H. Kao; Abhijit Chatterjeet

1999-01-01

204

A methodology for real time fault detection, isolation and correction  

NASA Astrophysics Data System (ADS)

Mission critical timelines and availability requirements of large, complex ground stations demand some form of a distributed real time system with an embedded rule-based expert advisor for recognizing and responding to changes within the system. To require a central command center to handle all status monitoring directly places immense processing requirements on the command center. An alternate approach is to develop unique sets of status values which are known to indicate specific faults in equipment strings. The live status returned from the segment hardware is processed to form a set of values, or signature vector for each equipment string. The signature vector is compared to the signature that occurs when the equipment string is operational. If the processed status signatures do not match the signature that indicates the equipment string is operational, the expert advisor notifies the command center that a fault was detected. The expert advisor continues processing until it has found a match from the pool of preengineered failure-mode signature vectors. Based on the match, Boolean logic is used to perform fault isolation and correction, with results provided to the command center.

Pensick, Ellen C.; Mulholland, John E.

1993-07-01

205

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

206

Comparing the effectiveness of several modeling methods for fault prediction  

Microsoft Academic Search

We compare the effectiveness of four modeling methods—negative binomial regression, recursive partitioning, random forests\\u000a and Bayesian additive regression trees—for predicting the files likely to contain the most faults for 28 to 35 releases of\\u000a three large industrial software systems. Predictor variables included lines of code, file age, faults in the previous release,\\u000a changes in the previous two releases, and programming

Elaine J. Weyuker; Thomas J. Ostrand; Robert M. Bell

2010-01-01

207

Fault detection techniques for complex cable shield topologies  

NASA Astrophysics Data System (ADS)

This document presents the results of a basic principles study which investigated technical approaches for developing fault detection techniques for use on cables with complex shielding topologies. The study was limited to those approaches which could realistically be implemented on a fielded cable, i.e., approaches which would require partial disassembly of a cable were not pursued. The general approach used was to start with present transfer impedance measurement techniques and modify their use to achieve the best possible measurement range. An alternative test approach, similar to a sniffer type test, was also investigated.

Coonrod, Kurt H.; Davis, Stuart L.; McLemore, Donald P.

1994-09-01

208

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) perpendicular to x), 1 less than or equal to i is less 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)

1993-01-01

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

Seismogenic Fault Detection by Different Hypocenter Location Algorithms in the Southern Tyrrhenian Sea, Italy  

NASA Astrophysics Data System (ADS)

We investigated the seismicity occurring in the last few decades along the continental margin of the southern Tyrrhenian region. In this portion of the Nubia-Europe contact belt the Tindari fault (TF) is a regional structure capable of up to 6 magnitude earthquakes linking the ongoing contractional and extensional crustal compartments of Western and Eastern Sicily, respectively. According to several investigators, TF represents the northwestward propagation of the Malta escarpment, a normal fault linking Eastern Sicily to Malta island which produced magnitude 7 earthquakes in the last centuries. West of TF in the Tyrrhenian sea the Sisifo fault crosses the compressional compartment and generates seismicity of maximum magnitude over 6. The prevailing off-shore location of these faults has made the data acquisition slow and the definition of the geophysical and geological features of these structures quite problematic. We applied several hypocenter location algorithms to seismometric data collected in the study region by the national and local seismic networks in the last 25 years with the main purpose of improving the accuracy of the local fault detection. Clear improvement in the knowledge of the fault geometry has been obtained applying the Bayesian location method by Presti et al. (BSSA, 2004) to earthquake sequences and swarms recorded between 1978 and 2003. In our investigation of hypocenter locations, we also performed synthetic earthquake simulations to test the significance of the main hypocenter trends found, i.e. we established whether a seismolineament or cluster really reflects fault activity or is a fictitious product of the recording network geometry. The results have been evaluated in the light of the geophysical and geological information available in the literature for the study region.

Neri, G.; Presti, D.; de Natale, G.; Troise, C.

2004-12-01

211

Inferring stress from faulting: From early concepts to inverse methods  

NASA Astrophysics Data System (ADS)

We review the evolution of concepts on and methods of estimating the state of stress from fault movements. Theories of failure in isotropic materials suggested a simple geometrical construction of optimal principal stress directions from a fault plane and its associated slip. These optimal directions align shear stress and slip directions and maximize the difference between shear stress and frictional resistance on the fault plane. Optimal stress directions for calcite twinning are obtained by a similar construction, with the difference that they maximize shear stress. Force representation of seismic sources independently introduced pressure, P, and tension, T, axes at positions that also maximize shear stress on both nodal planes. Frictional slip theory and the constraint that slip and shear stress directions be parallel allowed to address reactivation of pre-existing faults. This suggested that stress could also be inverted from reactivated fault and slip data or earthquake focal mechanisms. Early methods relied on geometrical constructions as a substitute for calculations, whereas later methods relied on software as these calculations became tractable with the help of computers. Similar methods were developed for the inversion of stress from crystal twin gliding with non-optimal geometry, with a different criterion that relies on a threshold of the component of shear stress along the gliding line. Even though these methods seek a common stress tensor compatible with fault and slip data, their main use is to separate polyphase data into homogeneous subsets and help deciphering complex tectonic histories. Fault and slip data can also be analyzed to constrain the strain rather than the stress tensor. In most cases this involves a summation and yields an average strain for the considered rock volume. Stress inversion thus appears better suited for differentiating heterogeneous data whereas strain analysis appears better suited for homogenizing them.

Célérier, Bernard; Etchecopar, Arnaud; Bergerat, Françoise; Vergely, Pierre; Arthaud, François; Laurent, Philippe

2012-12-01

212

Fault Detection and Isolation of a Cryogenic Rocket Engine Combustion Chamber Using a Parity Space Approach  

Microsoft Academic Search

This paper presents a parity space (PS) approach for fault detection and isolation (FDI) of a cryogenic rocket engine combustion chamber. Nominal and non-nominal simulation data for three engine set points have been provided. The PS approach uses three measurements to generate residuals and a spherical transformation to map these residuals to faults. The radial co-ordinate is used for fault

Paul van Gelder; A. Bos

2009-01-01

213

Power system fault detection and state estimation using Kalman filter with hypothesis testing  

SciTech Connect

This paper describes an algorithm for detecting power system faults and estimating the pre- and post-fault steady state values of the voltages and currents. The proposed algorithm is based on the Kalman filter and hypothesis testing. It is shown that a power system fault is ideally suited for single sample hypothesis testing. Test results are included.

Chowdhury, F.N. (Louisiana State Univ., Baton Rouge, LA (United States). Dept. of Chemistry); Christensen, J.P.; Aravena, J.L. (Louisiana State Univ., Baton Rouge, LA (United States). Dept. of Electrical and Computer Engineering)

1991-07-01

214

Abrupt change detection of fault in power system using independent component analysis  

Microsoft Academic Search

This paper proposes a novel fault detector for digital relaying based on independent component analysis (leA). The index for effective detection is derived from independent components of fault current. The proposed fault detector reduces the computational burden for real time applications and is therefore more accurate and robust as compared to other approaches. Further, a comparative assessment is carried out

Harish C. Dubey; Soumya R. Mohanty; Nand Kishore

2011-01-01

215

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

216

A coupled rotor-fuselage vibration analysis for helicopter rotor system fault detection  

Microsoft Academic Search

A coupled rotor-fuselage vibration analysis for helicopter rotor system fault detection is developed. The coupled rotor\\/fuselage\\/vibration absorbers (bifilar type) system incorporates consistent structural, aerodynamic and inertial couplings. The aeroelastic analysis is based on finite element methods in space and time. The coupled rotor, absorbers and fuselage equations are transformed into the modal space and solved in the fixed coordinate system.

Mao Yang

2003-01-01

217

An Integrated Approach to Detect Fault-Prone Modules Using Complexity and Text Feature Metrics  

Microsoft Academic Search

\\u000a Early detection of fault-prone products is necessary to assure the quality of software product. Therefore, fault-prone module\\u000a detection is one of the major and traditional area of software engineering. Although there are many approaches to detect fault-prone\\u000a modules, they have their own pros and cons. Consequently, it is recommended to use appropriate approach on the various situations.\\u000a This paper tries

Osamu Mizuno; Hideaki Hata

2010-01-01

218

Investigations on sensitivity of FRA method in diagnosis of interturn faults in transformer winding  

Microsoft Academic Search

This paper presents sensitivity of Frequency Response Analysis (FRA) method applied to detection of interturn faults. Frequency response has been carried out on a special Reduced Scale Traction Transformer (RSTT). The RSTT has the wound iron core and eight coils arranged in the \\

Andrzej Wilk; Dominik Adamczyk

2011-01-01

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

FINDS: A fault inferring nonlinear detection system. User's guide  

NASA Technical Reports Server (NTRS)

The computer program FINDS is written in FORTRAN-77, and is intended for operation on a VAX 11-780 or 11-750 super minicomputer, using the VMS operating system. The program detects, isolates, and compensates for failures in navigation aid instruments and onboard flight control and navigation sensors of a Terminal Configured Vehicle aircraft in a Microwave Landing System environment. In addition, FINDS provides sensor fault tolerant estimates for the aircraft states which are then used by an automatic guidance and control system to land the aircraft along a prescribed path. FINDS monitors for failures by evaluating all sensor outputs simultaneously using the nonlinear analytic relationships between the various sensor outputs arising from the aircraft point mass equations of motion. Hence, FINDS is an integrated sensor failure detection and isolation system.

Lancraft, R. E.; Caglayan, A. K.

1983-01-01

221

Fault detection of open-switch damage in voltage-fed PWM motor drive systems  

Microsoft Academic Search

This paper investigates the use of different techniques for fault detection in voltage-fed asynchronous machine drive systems. With the proposed techniques it is possible to detect and identify the power switch in which the fault has occurred. Such detection requires the measurement of some voltages and is based on the analytical model of the voltage source inverter. Simulation and experimental

R. L. de Araujo Ribeiro; C. B. Jacobina; E. R. Cabral da Silva; A.M. Nogueira Lima

2003-01-01

222

Hidden Markov Models and Neural Networks for Fault Detection in Dynamic Systems.  

National Technical Information Service (NTIS)

Neural networks plus hidden Markov models (HMM) can provide excellent detection and false alarm rate performance in fault detection applications, as shown in this viewgraph presentation. Modified models allow for novelty detection. Key contributions of ne...

P. Smyth

1994-01-01

223

A new three-dimensional method of fault reactivation analysis  

NASA Astrophysics Data System (ADS)

A 3-D method to evaluate the reactivation potential of fault planes is proposed. The method can be applied to cohesive or non cohesive faults whatever their orientation and without any condition on the regional stress field. It allows to compute 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 which consists in plotting poles of fault planes on stereoplots on which the boundaries separating the three domains corresponding to favorable orientations, unfavorable orientations and severe misorientations cases are drawn. The delineation of these domains is based on the value of the ?3'/?1' ratio which itself depends on the orientation of the fault plane with respect to the principal stress axis orientations, the stress shape ratio (? = (?2 - ?3)/(?1- ?3)), the coefficient of static friction ?s of the fault, and the fault cohesion C0. The method is applied on 145 focal mechanisms of the 2011 March 11th Tohoku-Oki (Japan) earthquake sequence. This application allows to delineate, along or in the vicinity of the plate interface, three types of domains characterized by favorable orientations, unfavorable orientations or severe misorientations of mainshock/aftershock fault planes. The 'severe misorientation' domains likely correspond to parts of the plate interface characterized by pore fluid pressures exceeding the magnitude of the regional least principal stress component. Stereoplots for application of the 3-D fault reactivation analysis. The stereoplots at the summits of the central triangle correspond to the three possible Andersonian stress tensors (one vertical principal stress axis, successively ?1 ,?2 and ?3). The three other triangles shearing two tops with the central triangle are characterized by non-Andersonian stress tensors with one horizontal principal stress axis and two titled principal stress axes. These non-Andersonian stress tensors correspond to rotations of 45° around one horizontal stress axis of the Andersonian tensors. For the six stress tensors plotting on each summits, seven stereoplots are computed by varying the values of C0/?1, ?s and ?. Each of the 42 stereoplots displays the location of the favorable orientation, unfavorable orientation and severely misorientation domains.

Leclere, H.; Fabbri, O.

2012-12-01

224

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

225

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

226

Fault Analysis of Space Station DC Power Systems-Using Neural Network Adaptive Wavelets to Detect Faults  

NASA Technical Reports Server (NTRS)

This paper describes the application of neural network adaptive wavelets for fault diagnosis of space station power system. The method combines wavelet transform with neural network by incorporating daughter wavelets into weights. Therefore, the wavelet transform and neural network training procedure become one stage, which avoids the complex computation of wavelet parameters and makes the procedure more straightforward. The simulation results show that the proposed method is very efficient for the identification of fault locations.

Momoh, James A.; Wang, Yanchun; Dolce, James L.

1997-01-01

227

Nonlinear sliding mode high-gain observers for fault detection  

Microsoft Academic Search

A robust high gain observer for state and faults estimations for a special class of nonlinear systems is developed in this article. Ensuring the observability of the faults with respect to the outputs, the faults can be estimated from the sliding surface. Under a Lipschitz condition for the nonlinear part, the high gain observers are designed under some regularity assumptions.

K. C. Veluvolu; F. Zhe; Y. C. Soh

2010-01-01

228

A neuro-fuzzy online fault detection and diagnosis algorithm for nonlinear and dynamic systems  

Microsoft Academic Search

This paper presents a new fault detection and diagnosis approach for nonlinear dynamic plant systems with a neuro-fuzzy based\\u000a approach to prevent developing of fault as soon as possible. By comparison of plants and neuro-fuzzy estimator outputs in\\u000a the presence of noise, residual signal is generated and compared with a predefined threshold, the fault can be detected. To\\u000a diagnose the

Mohsen Shabanian; Mohsen Montazeri

2011-01-01

229

Parity-Based Fault Detection Architecture of S-box for Advanced Encryption Standard  

Microsoft Academic Search

In this paper, the authors present parity-based fault detection architecture of the S-box for designing high performance fault detection structures of the advanced encryption standard. Instead of using look-up tables for the S-box and its parity prediction, logical gate implementations based on the composite field are utilized. After analyzing the error propagation for injected single faults, the authors modify the

Mehran Mozaffari Kermani; Arash Reyhani-masoleh

2006-01-01

230

A Feature Extraction Method Based on Information Theory for Fault Diagnosis of Reciprocating Machinery  

PubMed Central

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.

Wang, Huaqing; Chen, Peng

2009-01-01

231

DEM Response A nalysis of Buried Pipelines Crossing Faults and Proposal for a Simplified Method to Estimate Allowable Fault Displacements  

Microsoft Academic Search

This paper investigates the behavior of polyvinyl chlo- ride and ductile iron pipelines in relation to surface fault displacements using the Discrete Element Method (DEM) and proposes a method to estimate the allowable fault displacements. When modeling pipes and joints, the nonlinear material properties and joint characteristics (allowing detachment at the joints) are considered. Under a given set of various

Yasuko Kuwata; Shiro Takada; Radan Ivanov

2007-01-01

232

A Continuous Fault Countermeasure for AES Providing a Constant Error Detection Rate  

Microsoft Academic Search

Many implementations of cryptographic algorithms have shown to be susceptible to fault attacks. For some of them, countermeasures against specific fault models have been proposed. However, for symmetric algorithms like AES, the main focus of available countermeasures lies on performance so that their achieved error detection rates are rather low or not determinable at all. Even worse, those error detection

Marcel Medwed; Jörn-Marc Schmidt

2010-01-01

233

Fiber bragg grating sensor for differential fault detection in overhead power transmission lines  

Microsoft Academic Search

In this paper, a fiber optic based sensor capable of differential fault detection in power systems is investigated. Bragg wavelength shift, is used to measure fault current in power systems. Magnetic fields generated by currents in overhead tran smission lines cause a strain in a magnetostrictive material which is then detected by a Fiber Bragg Grating (FBG). Optical Spectrum Analyzers

Amin Moghadas; Ronald Barnes; Mehdi Shadaram

2011-01-01

234

A joint wavelet lifting and independent component analysis approach to fault detection of rolling element bearings  

Microsoft Academic Search

Though wavelet transforms have been used to extract bearing fault signatures from vibration signals in the literature, detection results often rely on a proper wavelet function and deep wavelet decomposition. The selection of a proper wavelet function is time consuming and deep decomposition demands more computing effort. This is unsuitable for on-line fault detection. As such, we propose a joint

Xianfeng Fan; Ming Liang; Tet H. Yeap; Bob Kind

2007-01-01

235

A new technique for detection and location of arcing faults in power system apparatus  

Microsoft Academic Search

A technique that detects an arcing fault in power apparatus is presented in this paper. It uses a PC based data acquisition system for detection of the arcing faults. It is shown that it is possible to determine its location in three dimensional space. The technique was implemented and tested in the laboratory. Some test results are also included in

T. S. Sidhu; G. Singh; M. S. Sachdev

1998-01-01

236

Fault Detection and Monitoring of Length Loop Control System in Pickling Process  

Microsoft Academic Search

Modern manufacturing facilities are large scale, highly complex, and operate with large number of variables under closed loop control. Early and accurate fault detection and diagnosis for these plants can minimise down time, increase the safety of plant operations, and reduce manufacturing costs. Fault detection and isolation is more complex particularly in the case of the faulty analog control systems.

S. Bouhouche; M. Lahreche; S. Ziani; J. Bast

2005-01-01

237

Detection of Creep displacement along the North Anatolian Fault by SAR Interferometry  

NASA Astrophysics Data System (ADS)

North Anatolian Fault (NAF) has several records of a huge earthquake occurrence in the last one century, which is well-known as a risky active fault. Some signs indicating a creep displacement could be observed on the Ismetpasa segment. It is reported so far that the San Andreas fault in California, the Longitudinal Valley fault in Taiwan and the Valley Fault System in Metro Manila also exhibit fault creep. The fault with creep deformation is aseismic and never generate the large scale earthquakes. But the scale and rate of fault creep are important factors to watch the fault behavior and to understand the cycle of earthquake. The purpose of this study is to investigate the distribution of spatial and temporal change on the ground motion due to fault creep in the surrounding of the Ismetpasa, NAF. DInSAR is capable to catch a subtle land displacement less than a centimeter and observe a wide area at a high spatial resolution. We applied InSAR time series analysis using PALSAR data in order to measure long-term ground deformation from 2007 until 2011. As a result, the land deformation that the northern and southern parts of the fault have slipped to east and west at a rate of 7.5 and 6.5 mm/year in line of sight respectively were obviously detected. In addition, it became clear that the fault creep along the NAF extended 61 km in east to west direction.

Deguchi, Tomonori; Kutoglu, Hakan

2012-07-01

238

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

239

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

PubMed Central

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.

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

2014-01-01

240

Multigrid contact detection method  

NASA Astrophysics Data System (ADS)

Contact detection is a general problem of many physical simulations. This work presents a O(N) multigrid method for general contact detection problems (MGCD). The multigrid idea is integrated with contact detection problems. Both the time complexity and memory consumption of the MGCD are O(N) . Unlike other methods, whose efficiencies are influenced strongly by the object size distribution, the performance of MGCD is insensitive to the object size distribution. We compare the MGCD with the no binary search (NBS) method and the multilevel boxing method in three dimensions for both time complexity and memory consumption. For objects with similar size, the MGCD is as good as the NBS method, both of which outperform the multilevel boxing method regarding memory consumption. For objects with diverse size, the MGCD outperform both the NBS method and the multilevel boxing method. We use the MGCD to solve the contact detection problem for a granular simulation system based on the discrete element method. From this granular simulation, we get the density property of monosize packing and binary packing with size ratio equal to 10. The packing density for monosize particles is 0.636. For binary packing with size ratio equal to 10, when the number of small particles is 300 times as the number of big particles, the maximal packing density 0.824 is achieved.

He, Kejing; Dong, Shoubin; Zhou, Zhaoyao

2007-03-01

241

Accountability Method Makes Failure the Teacher's Fault  

ERIC Educational Resources Information Center

Report of a recent leadership conference for improvement of teaching co-sponsored by the Western Interstate Commission for Higher Education and Eastern Montana College, presents an accountability method" of teaching and grading based on specifically defined objectives, new learning technics and result judging. (IR)

Coll Univ Bus, 1970

1970-01-01

242

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

243

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

244

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

NASA Technical Reports Server (NTRS)

When setting out to model and/or simulate a complex mechanical or electrical system, a modeler is faced with a vast array of tools, software, equations, algorithms and techniques that may individually or in concert aid in the development of the model. Mature requirements and a well understood purpose for the model may considerably shrink the field of possible tools and algorithms that will suit the modeling solution. Is the model intended to be used in an offline fashion or in real-time? On what platform does it need to execute? How long will the model be allowed to run before it outputs the desired parameters? What resolution is desired? Do the parameters need to be qualitative or quantitative? Is it more important to capture the physics or the function of the system in the model? Does the model need to produce simulated data? All these questions and more will drive the selection of the appropriate tools and algorithms, but the modeler must be diligent to bear in mind the final application throughout the modeling process to ensure the model meets its requirements without needless iterations of the design. The purpose of this paper is to describe the considerations and techniques used in the process of creating a functional fault model of a liquid hydrogen (LH2) system that will be used in a real-time environment to automatically detect and isolate failures.

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

2009-01-01

245

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

NASA Astrophysics Data System (ADS)

This dissertation summarizes experimental validation and co-design studies conducted to optimize the fault detection capabilities and overheads in hybrid computer systems (e.g., using CPUs and Graphics Processing Units, or GPUs), and consequently to improve the scalability of parallel computer systems using computational accelerators. The experimental validation studies were conducted to help us understand the failure characteristics of CPU-GPU hybrid computer systems under various types of hardware faults. The main characterization targets were faults that are difficult to detect and/or recover from, e.g., faults that cause long latency failures (Ch. 3), faults in dynamically allocated resources (Ch. 4), faults in GPUs (Ch. 5), faults in MPI programs (Ch. 6), and microarchitecture-level faults with specific timing features (Ch. 7). The co-design studies were based on the characterization results. One of the co-designed systems has a set of source-to-source translators that customize and strategically place error detectors in the source code of target GPU programs (Ch. 5). Another co-designed system uses an extension card to learn the normal behavioral and semantic execution patterns of message-passing processes executing on CPUs, and to detect abnormal behaviors of those parallel processes (Ch. 6). The third co-designed system is a co-processor that has a set of new instructions in order to support software-implemented fault detection techniques (Ch. 7). The work described in this dissertation gains more importance because heterogeneous processors have become an essential component of state-of-the-art supercomputers. GPUs were used in three of the five fastest supercomputers that were operating in 2011. Our work included comprehensive fault characterization studies in CPU-GPU hybrid computers. In CPUs, we monitored the target systems for a long period of time after injecting faults (a temporally comprehensive experiment), and injected faults into various types of program states that included dynamically allocated memory (to be spatially comprehensive). In GPUs, we used fault injection studies to demonstrate the importance of detecting silent data corruption (SDC) errors that are mainly due to the lack of fine-grained protections and the massive use of fault-insensitive data. This dissertation also presents transparent fault tolerance frameworks and techniques that are directly applicable to hybrid computers built using only commercial off-the-shelf hardware components. This dissertation shows that by developing understanding of the failure characteristics and error propagation paths of target programs, we were able to create fault tolerance frameworks and techniques that can quickly detect and recover from hardware faults with low performance and hardware overheads.

Yim, Keun Soo

246

Hidden Markov Models for Fault Detection in Dynamic Systems  

NASA Technical Reports Server (NTRS)

Continuous monitoring of complex dynamic systems is an increasingly important issue in diverse areas such as nuclear plant safety, production line reliability, and medical health monitoring systems. Recent advances in both sensor technology and computational capabilities have made on-line permanent monitoring much more feasible than it was in the past. In this paper it is shown that a pattern recognition system combined with a finite-state hidden Markov model provides a particularly useful method for modelling temporal context in continuous monitoring. The parameters of the Markov model are derived from gross failure statistics such as the mean time between failures. The model is validated on a real-world fault diagnosis problem and it is shown that Markov modelling in this context offers significant practical benefits.

Smyth, Padhraic

1994-01-01

247

Fault Detection and Recovery in a Transactional Agent Model  

Microsoft Academic Search

Servers can be fault-tolerant through replication and checkpointing technologies in the client server model. However, application programs cannot be performed and servers might block in the two-phase commitment protocol due to the client fault. In this paper, we discuss the transactional agent model to make application programs fault-tolerant by taking advantage of mobile agent technologies where a program can move

Youhei Tanaka; Naohiro Hayashibara; Tomoya Enokido; Makoto Takizawa

2007-01-01

248

An improved PCA method with application to boiler leak detection.  

PubMed

Principal component analysis (PCA) is a popular fault detection technique. It has been widely used in process industries, especially in the chemical industry. In industrial applications, achieving a sensitive system capable of detecting incipient faults, which maintains the false alarm rate to a minimum, is a crucial issue. Although a lot of research has been focused on these issues for PCA-based fault detection and diagnosis methods, sensitivity of the fault detection scheme versus false alarm rate continues to be an important issue. In this paper, an improved PCA method is proposed to address this problem. In this method, a new data preprocessing scheme and a new fault detection scheme designed for Hotelling's T2 as well as the squared prediction error are developed. A dynamic PCA model is also developed for boiler leak detection. This new method is applied to boiler water/steam leak detection with real data from Syncrude Canada's utility plant in Fort McMurray, Canada. Our results demonstrate that the proposed method can effectively reduce false alarm rate, provide effective and correct leak alarms, and give early warning to operators. PMID:16082787

Sun, Xi; Marquez, Horacio J; Chen, Tongwen; Riaz, Muhammad

2005-07-01

249

Virtual prototype and experimental research on gear multi-fault diagnosis using wavelet-autoregressive model and principal component analysis method  

NASA Astrophysics Data System (ADS)

Gear systems are an essential element widely used in a variety of industrial applications. Since approximately 80% of the breakdowns in transmission machinery are caused by gear failure, the efficiency of early fault detection and accurate fault diagnosis are therefore critical to normal machinery operations. Reviewed literature indicates that only limited research has considered the gear multi-fault diagnosis, especially for single, coupled distributed and localized faults. Through virtual prototype simulation analysis and experimental study, a novel method for gear multi-fault diagnosis has been presented in this paper. This new method was developed based on the integration of Wavelet transform (WT) technique, Autoregressive (AR) model and Principal Component Analysis (PCA) for fault detection. The WT method was used in the study as the de-noising technique for processing raw vibration signals. Compared with the noise removing method based on the time synchronous average (TSA), the WT technique can be performed directly on the raw vibration signals without the need to calculate any ensemble average of the tested gear vibration signals. More importantly, the WT can deal with coupled faults of a gear pair in one operation while the TSA must be carried out several times for multiple fault detection. The analysis results of the virtual prototype simulation prove that the proposed method is a more time efficient and effective way to detect coupled fault than TSA, and the fault classification rate is superior to the TSA based approaches. In the experimental tests, the proposed method was compared with the Mahalanobis distance approach. However, the latter turns out to be inefficient for the gear multi-fault diagnosis. Its defect detection rate is below 60%, which is much less than that of the proposed method. Furthermore, the ability of the AR model to cope with localized as well as distributed gear faults is verified by both the virtual prototype simulation and experimental studies.

Li, Zhixiong; Yan, Xinping; Yuan, Chengqing; Peng, Zhongxiao; Li, Li

2011-10-01

250

Detection of high impedance arcing faults using a multi-layer perceptron  

Microsoft Academic Search

A feed-forward three-layer perceptron was trained by high impedance fault, fault-like load, and normal load current patterns, using the back-propagation training algorithm. This paper reports that the neural network parameters were embodied in a high impedance arcing faults detection algorithm, which uses a simple preprocessing technique to prepare the information input to the network. The algorithm was tested by traces

F. F. Sultan; G. W. Swift; D. J. Fedirchuk

1992-01-01

251

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

252

Early detection for short-circuit fault in low-voltage systems based on fractal exponent wavelet analysis  

Microsoft Academic Search

By combining wavelet transform (WT ) with fractal theory, a novel approach is put forward to detect early short-circuit fault. The application of signal denoising based on the statistic rule is brought forward to determine the threshold of each order of wavelet space, and an effective method is proposed to determine the decomposition adaptively, increasing the signal-noise-ratio (SNR). In a

PU HAN; WEI LIAO; WU ZHONG LI

2007-01-01

253

Hierarchical fault detection, isolation and recovery applied to cof and atv avionics  

NASA Astrophysics Data System (ADS)

The avionics architecture of in-orbit infrastructure elements is driven by safety. Safety of the crew inside the Columbus Orbital Facility (COF) laboratory module, safety of the Space Station as a whole for the automated transfer vehicle (ATV) when performing a rendezvous manoeuvre. The design answers on safety requirements, methods and tools used for the development stem from a common concept. The paper first describes the COF Data Management System architecture, basically organised in two layers with a strict hierarchical relationship. The vital layer is in charge of COF initial activation, safety supervision and emergency modes management. The nominal layer is a distributed system, organised around a local area Ethernet network. Under normal conditions, it is in charge of its own fault management supported by management agents distributed in the system. Fault detection criteria are derived from an FMECA (failure mode, effect and criticality analysis) and also from a SEEA (software error effect analysis). Recovery actions are allocated to various decision levels in the hierarchy depending on their time criticality. In ATV, the same principles apply, but the implementation is adapted to the peculiarities of an automated vehicle. The nominal layer, because of the time constraints bearing upon any reconfiguration, implements fault masking (majority voting) instead of fault detection and recovery.The vital layer is allocated the very critical task of monitoring the spacecraft attitude and velocity, and performing if necessary a collision avoidance manoeuvre. An end-to-end comprehensive methodology is put in place to be able to demonstrate the compliance of the systems to technical, product assurance and safety requirements.

Durou, O.; Godet, V.; Mangane, L.; Pérarnaud, D.; Roques, R.

2002-05-01

254

Exoplanet Detection Methods  

NASA Astrophysics Data System (ADS)

This chapter reviews various methods of detecting planetary companions to stars from an observational perspective, focusing on radial velocities, astrometry, direct imaging, transits, and gravitational microlensing. For each method, this chapter first derives or summarizes the basic observable phenomena that are used to infer the existence of planetary companions as well as the physical properties of the planets and host stars that can be derived from the measurement of these signals. This chapter then outlines the general experimental requirements to robustly detect the signals using each method, by comparing their magnitude to the typical sources of measurement uncertainty. This chapter goes on to compare the various methods to each other by outlining the regions of planet and host star parameter space where each method is most sensitive, stressing the complementarity of the ensemble of the methods at our disposal. Finally, there is a brief review of the history of the young exoplanet field, from the first detections to current state-of-the-art surveys for rocky worlds.

Wright, Jason T.; Gaudi, B. Scott

255

Research on AMU fault detection algorithm based on immune danger theory  

Microsoft Academic Search

From danger theory of the biological immunology , a new kind of AMU fault detection algorithm based on immune danger theory was presented. In this paper of the new algorithm, System only respond to danger signal and analyze whether there is the existence of fault signal by analysis of the danger extent . The result of the experiment shows that

Zhou Dexin; Fan Zhicheng; Zhang Wenlin

2011-01-01

256

Doubly Fed Induction Generator Model-Based Sensor Fault Detection and Control Loop Reconfiguration  

Microsoft Academic Search

Fault tolerance is gaining interest as a means to increase the reliability and availability of distributed energy systems. In this paper, a voltage-oriented doubly fed induction generator, which is often used in wind turbines, is examined. Furthermore, current, voltage, and position sensor fault detection, isolation, and reconfiguration are presented. Machine operation is not interrupted. A bank of observers provides residuals

Kai Rothenhagen; Friedrich Wilhelm Fuchs

2009-01-01

257

A Structure-independent Approach for Fault Detection Hardware Implementations of the Advanced Encryption Standard  

Microsoft Academic Search

The Advanced Encryption Standard, which is used extensively for secure communications, has been accepted recently as a symmetric cryptography standard. However, occurrence of the internal faults by intrusion of the attackers may cause confidential information leak to reveal the secret key. For this reason, several schemes for fault detection of the transformations and rounds in the encryption and decryption of

Mehran Mozaffari-Kermani; Arash Reyhani-Masoleh

2007-01-01

258

A fault detection and diagnosis scheme for discrete nonlinear system using output probability density estimation  

Microsoft Academic Search

In this paper, a fault detection and diagnosis (FDD) scheme for a class of discrete nonlinear system fault using output probability density estimation is presented. Unlike classical FDD problems, the measured output of the system is viewed as a stochastic process and its square root probability density function (PDF) is modeled with B-spline functions, which leads to a deterministic space-time

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

2008-01-01

259

Hierarchical Error Detection in a Software Implemented Fault Tolerance (SIFT) Environment  

Microsoft Academic Search

In this paper, we propose a hierarchical framework for providi ng fault tolerance to the SIFT layer of a distributed system, and extending it to the applications executing in such an environment. The detection hierarchy is proposed in the context of Chameleon, a software env ironment for providing adaptive fault- tolerance in a COTS environment to off-the-shelf software. A flex

Saurabh Bagchi; Balaji Srinivasan; Keith Whisnant; Zbigniew Kalbarczyk; Ravishankar K. Iyer

2000-01-01

260

A Combined Logistic and Model Based Approach for Fault Detection and Identification in a Climbing Robot  

Microsoft Academic Search

This paper presents a combined logistic and model based approach for fault detection and identification (FDI) in the suction foot control of a climbing robot. For this control system, some fault models are easily given by kinematics equations. Moreover, the logic relations of the system states have been known in advance. Based on the combination of the logic reasoning and

Yong Jiang; Hongguang Wang; Lijin Fang; Mingyang Zhao

2006-01-01

261

A Novel Approach to Fault Detection and Identification in Suction Foot Control of a Climbing Robot  

Microsoft Academic Search

This paper presents a multiple-model and Boolean logic reasoning (MMBLR) approach to detect and identify faults in the suction foot control of a climbing robot. For this control system, some fault models are easily given by kinematics equations. Moreover, the logic relations of the system states have been known in advance. Based on the combination of the multiple-model adaptive estimation

Yong Jiang; Hongguang Wang; Lijin Fang; Mingyang Zhao

2006-01-01

262

Fault detection and classification in chemical processes based on neural networks with feature extraction.  

PubMed

Feed forward neural networks are investigated here for fault diagnosis in chemical processes, especially batch processes. The use of the neural model prediction error as the residual for fault diagnosis of sensor and component is analyzed. To reduce the training time required for the neural process model, an input feature extraction process for the neural model is implemented. An additional radial basis function neural classifier is developed to isolate faults from the residual generated, and results are presented to demonstrate the satisfactory detection and isolation of faults using this approach. PMID:14582888

Zhou, Yifeng; Hahn, Juergen; Mannan, M Sam

2003-10-01

263

Detection of high impedance arcing faults using a multi-layer perceptron  

SciTech Connect

A feed-forward three-layer perceptron was trained by high impedance fault, fault-like load, and normal load current patterns, using the back-propagation training algorithm. This paper reports that the neural network parameters were embodied in a high impedance arcing faults detection algorithm, which uses a simple preprocessing technique to prepare the information input to the network. The algorithm was tested by traces of normal load current disturbed by currents of faults on dry and wet soil, an arc welder, computers, and fluorescent lights.

Sultan, F.F.; Swift, G.W. (Univ. of Manitoba, Dept. of Electrical and Computer Engineering, Winnipeg, Manitoba R3T 2N2 (Canada)); Fedirchuk, D.J. (Manitoba Hydro, System Operation Dept., Winnipeg, Manitoba R3C 2P4 (Canada))

1992-10-01

264

Bearings fault detection in helicopters using frequency readjustment and cyclostationary analysis  

NASA Astrophysics Data System (ADS)

The objective of this paper is to propose a vibration-based automated framework dealing with local faults occurring on bearings in the transmission of a helicopter. The knowledge of the shaft speed and kinematic computation provide theoretical frequencies that reveal deteriorations on the inner and outer races, on the rolling elements or on the cage. In practice, the theoretical frequencies of bearing faults may be shifted. They may also be masked by parasitical frequencies because the numerous noisy vibrations and the complexity of the transmission mechanics make the signal spectrum very profuse. Consequently, detection methods based on the monitoring of the theoretical frequencies may lead to wrong decisions. In order to deal with this drawback, we propose to readjust the fault frequencies from the theoretical frequencies using the redundancy introduced by the harmonics. The proposed method provides the confidence index of the readjusted frequency. Minor variations in shaft speed may induce random jitters. The change of the contact surface or of the transmission path brings also a random component in amplitude and phase. These random components in the signal destroy spectral localization of frequencies and thus hide the fault occurrence in the spectrum. Under the hypothesis that these random signals can be modeled as cyclostationary signals, the envelope spectrum can reveal that hidden patterns. In order to provide an indicator estimating fault severity, statistics are proposed. They make the hypothesis that the harmonics at the readjusted frequency are corrupted with an additive normally distributed noise. In this case, the statistics computed from the spectra are chi-square distributed and a signal-to-noise indicator is proposed. The algorithms are then tested with data from two test benches and from flight conditions. The bearing type and the radial load are the main differences between the experiences on the benches. The fault is mainly visible in the spectrum for the radially constrained bearing and only visible in the envelope spectrum for the "load-free" bearing. Concerning results in flight conditions, frequency readjustment demonstrates good performances when applied on the spectrum, showing that a fully automated bearing decision procedure is applicable for operational helicopter monitoring.

Girondin, Victor; Pekpe, Komi Midzodzi; Morel, Herve; Cassar, Jean-Philippe

2013-07-01

265

An enhanced Kurtogram method for fault diagnosis of rolling element bearings  

NASA Astrophysics Data System (ADS)

The Kurtogram is based on the kurtosis of temporal signals that are filtered by the short-time Fourier transform (STFT), and has proved useful in the diagnosis of bearing faults. To extract transient impulsive signals more effectively, wavelet packet transform is regarded as an alternative method to STFT for signal decomposition. Although kurtosis based on temporal signals is effective under some conditions, its performance is low in the presence of a low signal-to-noise ratio and non-Gaussian noise. This paper proposes an enhanced Kurtogram, the major innovation of which is kurtosis values calculated based on the power spectrum of the envelope of the signals extracted from wavelet packet nodes at different depths. The power spectrum of the envelope of the signals defines the sparse representation of the signals and kurtosis measures the protrusion of the sparse representation. This enhanced Kurtogram helps to determine the location of resonant frequency bands for further demodulation with envelope analysis. The frequency signatures of the envelope signal can then be used to determine the type of fault that has affected a bearing by identifying its characteristic frequency. In many cases, discrete frequency noise always exists and may mask the weak bearing faults. It is usually preferable to remove such discrete frequency noise by using autoregressive filtering before the enhanced Kurtogram is performed. At last, we used a number of simulated bearing fault signals and three real bearing fault signals obtained from an experimental motor to validate the efficiency of these proposed modifications. The results show that both the proposed method and the enhanced Kurtogram are effective in the detection of various bearing faults.

Wang, Dong; Tse, Peter W.; Tsui, Kwok Leung

2013-02-01

266

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

267

Method for detecting biomolecules  

DOEpatents

A method for detecting and measuring the concentration of biomolecules in solution, utilizing a conducting electrode in contact with a solution containing target biomolecules, with a film with controllable pore size distribution characteristics applied to at least one surface of the conducting electrode. The film is functionalized with probe molecules that chemically interact with the target biomolecules at the film surface, blocking indicator molecules present in solution from diffusing from the solution to the electrode, thereby changing the electrochemical response of the electrode

Huo, Qisheng (Albuquerque, NM) [Albuquerque, NM; Liu, Jun (Albuquerque, NM) [Albuquerque, NM

2008-08-12

268

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

269

Fault Detection and Location Using IDD Waveform Analysis  

Microsoft Academic Search

This paper investigates online testing for faultlocalization in CMOS circuits using IDD waveform analysis.The methods investigated in this paper are applicable bothto static as well as dynamic CMOS circuits. We show thatnot only can IDD waveform analysis detect a number of defectsthat are otherwise undetectable by IDDQ testing, itcan also be applied to online testing and diagnosis of CMOScircuits. In

Khurram Muhammad; Kaushik Roy

2001-01-01

270

Fault Detection and Location Using IDD Waveform Analysis  

Microsoft Academic Search

This paper investigates online testing for faultlocalization in CMOS circuits using IDD waveform analysis.The methods investigated in this paper are applicable bothto static as well as dynamic CMOS circuits. We show thatnot only can IDD waveform analysis detect a number of defectsthat are otherwise undetectable by IDDQ testing, itcan also be applied to online testing and diagnosis of CMOScircuits. In

K. Muhammad; M. E. Amyeen; K. Roy

1998-01-01

271

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

272

A. Higher Radix Technique for Fault Detection in Many-Valued Multithreshold Networks  

Microsoft Academic Search

A technique for fault detection of many-valued multithreshold switching networks is presented. An arbitrary network, implemented with R-valued multithreshold gates, called MT(R), can be transformed into an MT(R + 1) or an MT(R + 2) network which uses additional truth values for fault detection purposes. The technique leads to reduced test sets, which are usually simpler to derive.

A. Druzeta; Zvonko G. Vranesic

1978-01-01

273

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

274

Fault detection and accommodation testing on an F100 engine in an F-15 airplane. [digital engine control system  

NASA Technical Reports Server (NTRS)

The fault detection and accommodation (FDA) methods that can be used for digital engine control systems are presently subjected to a flight test program in the case of the F-15 fighter's F100 engine electronic controls, inducing selected faults and then evaluating the resulting digital engine control responses. In general, flight test results were found to compare well with both ground tests and predictions. It is noted that the inducement of dual-pressure failures was not feasible, since FDA logic was not designed to accommodate them.

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

1985-01-01

275

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

276

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

277

Intermittent/transient fault phenomena in digital systems  

NASA Technical Reports Server (NTRS)

An overview of the intermittent/transient (IT) fault study is presented. An interval survivability evaluation of digital systems for IT faults is discussed along with a method for detecting and diagnosing IT faults in digital systems.

Masson, G. M.

1977-01-01

278

A separable method for incorporating imperfect fault-coverage into combinatorial models  

Microsoft Academic Search

This paper presents a new method for incorporating imperfect FC (fault coverage) into a combinatorial model. Imperfect FC, the probability that a single malicious fault can thwart automatic recovery mechanisms, is important to accurate reliability assessment of fault-tolerant computer systems. Until recently, it was thought that the consideration of this probability necessitated a Markov model rather than the simpler (and

S. V. Amari; J. B. Dugan; R. B. Misra

1999-01-01

279

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

NASA Technical Reports Server (NTRS)

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

Smyth, Padhraic

1994-01-01

280

Pumping system fault detection and diagnosis utilizing pattern recognition and fuzzy inference techniques  

Microsoft Academic Search

An integrated fault detection and diagnostic system with a capability of providing extremely early detection of disturbances in a process through the analysis of the stochastic content of dynamic signals is described. The sequential statistical analysis of the signal noise (a pattern-recognition technique) that is employed has been shown to provide the theoretically shortest sampling time to detect disturbances and

R. M. Singer; K. C. Gross; K. E. Humenik

1991-01-01

281

Statistic-based spectral indicator for bearing fault detection in permanent-magnet synchronous machines using the stator current  

NASA Astrophysics Data System (ADS)

In this paper, an original method for bearing fault detection in high speed synchronous machines is presented. This method is based on the statistical process of Welch's periodogram of the stator currents in order to obtain stable and normalized fault indicators. The principle of the method is to statistically compare the current spectrum to a healthy reference so as to quantify the changes over the time. A statistic-based indicator is then constructed by monitoring specific harmonic family. The proposed method was tested on two experimental test campaigns for four different speeds and compared to a vibration indicator. The method was evaluated using a rigorous performance evaluation metric. A threshold evaluation was performed and shows that the proposed method is very tolerant to the machine speed. Thus, the use of a unique fault threshold whatever the speed can be considered. Results showed excellent agreement as compared with the vibration indicator, with an overall correlation of r=0.74 and only 4% of false alarms. Performance demonstrated by this novel method was superior to those of a classical energy-based indicator in terms of correlation with the vibration indicator and detection stability. Moreover, results also showed a better robustness of the proposed method since good performance can be obtained with the same detection threshold whatever the speed or the measure campaign whereas it needs to be redefined for each case with the classical indicator. This work shows the advantages of a statistic-based approach in order to increase the robustness of bearing fault detection in permanent-magnet synchronous machines.

Picot, A.; Obeid, Z.; Régnier, J.; Poignant, S.; Darnis, O.; Maussion, P.

2014-06-01

282

Fault detection and isolation of aircraft air data/inertial system  

NASA Astrophysics Data System (ADS)

A method for failure detection and isolation (FDI) for redundant aircraft sensors is presented. The outputs of the concerned sensors are involved in the computation of flight control laws, and the objective is to eliminate any fault before propagation in the control loop when selecting a unique flight parameter among a set (generally, three) of redundant measurements. The particular case of an oscillatory failure is investigated. The proposed method allows an accurate FDI of erroneous sensor and computes a consolidated parameter based on the fusion of data from remaining valid sensors. The benefits of the presented method are to enhance the data fusion process with FDI techniques which improve the performance of the fusion when only few sources (less than three) are initially valid.

Berdjag, D.; Cieslak, J.; Zolghadri, A.

2013-12-01

283

Advanced monitoring of water systems using in situ measurement stations: data validation and fault detection.  

PubMed

In situ continuous monitoring at high frequency is used to collect water quality information about water bodies. However, it is crucial that the collected data be evaluated and validated for the appropriate interpretation of the data so as to ensure that the monitoring programme is effective. Software tools for data quality assessment with a practical orientation are proposed. As water quality data often contain redundant information, multivariate methods can be used to detect correlations, pertinent information among variables and to identify multiple sensor faults. While principal component analysis can be used to reduce the dimensionality of the original variable data set, monitoring of some statistical metrics and their violation of confidence limits can be used to detect faulty or abnormal data and can help the user apply corrective action(s). The developed algorithms are illustrated with automated monitoring systems installed in an urban river and at the inlet of a wastewater treatment plant. PMID:24037152

Alferes, Janelcy; Tik, Sovanna; Copp, John; Vanrolleghem, Peter A

2013-01-01

284

On complex network approach for fault detection in power grids  

Microsoft Academic Search

The latest developments in complex network theory have provided a new direction for power system research. Based on this theory a power system can be modeled as a graph with nodes and vertices and further analysis can help in addressing typical problems such as identifying the vulnerable lines and pole fires, and locating faults. This paper reports some of our

Xinghuo Yu; Ajendra Dwivedi; Peter Sokolowski

2009-01-01

285

Detecting matrix multiplication faults in many-core systems  

Microsoft Academic Search

Many-core systems are characterized by a large number of components based on ever-shrinking circuit geometries. System reliability becomes an issue because of the system complexity, the large number of components and nanoscale issues due to soft errors. While information redundancy techniques can be used for fault tolerance, they occupy too much memory space and increase the memory and network bandwidth.

Fadi N. Sibai

2011-01-01

286

Integrating Actuator Fault and Wheel Slippage Detections within FDI Framework  

Microsoft Academic Search

We have witnessed a significant advancement in the field of mobile robot applications in the past two decades. From performing mission critical tasks such as in planetary exploration to simply doing household chores, this type of robots requires availability, reliability and safety of its operations. Consequently, there is a growing demand for fault tolerant control system (FTCS) for mobile robots

NAIM SIDEK; NILANJAN SARKAR

287

Analysis methods for fault trees that contain secondary failures  

Microsoft Academic Search

The fault tree methodology is appropriate when the component level failures (basic events) occur independently. One situation where the conditions of independence are not met occurs when secondary failure events appear in the fault tree structure. Guidelines for fault tree construction that have been utilized for many years encourage the inclusion of secondary failures along with primary failures and command

S Dunnett; J D Andrews

2004-01-01

288

Identifiability of Additive Actuator and Sensor Faults by State Augmentation  

NASA Technical Reports Server (NTRS)

A class of fault detection and identification (FDI) methods for bias-type actuator and sensor faults is explored in detail from the point of view of fault identifiability. The methods use state augmentation along with banks of Kalman-Bucy filters for fault detection, fault pattern determination, and fault value estimation. A complete characterization of conditions for identifiability of bias-type actuator faults, sensor faults, and simultaneous actuator and sensor faults is presented. It is shown that FDI of simultaneous actuator and sensor faults is not possible using these methods when all sensors have unknown biases. The fault identifiability conditions are demonstrated via numerical examples. The analytical and numerical results indicate that caution must be exercised to ensure fault identifiability for different fault patterns when using such methods.

Joshi, Suresh; Gonzalez, Oscar R.; Upchurch, Jason M.

2014-01-01

289

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

290

High-gain observation with disturbance attenuation and application to robust fault detection  

Microsoft Academic Search

One approach to the problem of residual generation in a purpose of fault detection is to use an observer. One particular difficulty is to distinguish between faults and disturbances. Various observers have already been inspected in that direction, generally based on exact decoupling w.r.t. unknown disturbances. Here the use of high-gain observer techniques is inspected, with a purpose of attenuation

Gildas Besançon

2003-01-01

291

Rotor inter-turn short circuit fault detection in wound rotor induction machines  

Microsoft Academic Search

The aim of this paper is to develop a technique for detecting a real rotor inter-turn short-circuit fault in a wound rotor induction machine working as generator by using the spectral and the bispectral analysis. The stator currents provide interesting signatures since the rotor inter-turn short-circuit fault introduces new harmonics in the stator windings. Hence, in this paper, it is

A. Yazidi; H. Henao; G. A. Capolino; F. Betin

2010-01-01

292

Detecting remotely triggered temporal changes around the Parkfield section of the San Andreas fault  

Microsoft Academic Search

Detecting temporal changes in fault zone properties at seismogenic depth have been a long-sought goal in the seismological\\u000a community for many decades. Recent studies based on waveform analysis of repeating earthquakes have found clear temporal changes\\u000a in the shallow crust and around active fault zones associated with the occurrences of large nearby and teleseismic earthquakes.\\u000a However, repeating earthquakes only occur

Peng Zhao; Zhigang Peng; Karim Ghazi Sabra

2010-01-01

293

Multi-Unmanned Aerial Vehicle (UAV) Cooperative Fault Detection Employing Differential Global Positioning (DGPS), Inertial and Vision Sensors.  

PubMed

This paper presents a method to increase the reliability of Unmanned Aerial Vehicle (UAV) sensor Fault Detection and Identification (FDI) in a multi-UAV context. Differential Global Positioning System (DGPS) and inertial sensors are used for sensor FDI in each UAV. The method uses additional position estimations that augment individual UAV FDI system. These additional estimations are obtained using images from the same planar scene taken from two different UAVs. Since accuracy and noise level of the estimation depends on several factors, dynamic replanning of the multi-UAV team can be used to obtain a better estimation in case of faults caused by slow growing errors of absolute position estimation that cannot be detected by using local FDI in the UAVs. Experimental results with data from two real UAVs are also presented. PMID:22400008

Heredia, Guillermo; Caballero, Fernando; Maza, Iván; Merino, Luis; Viguria, Antidio; Ollero, Aníbal

2009-01-01

294

Multi-Unmanned Aerial Vehicle (UAV) Cooperative Fault Detection Employing Differential Global Positioning (DGPS), Inertial and Vision Sensors  

PubMed Central

This paper presents a method to increase the reliability of Unmanned Aerial Vehicle (UAV) sensor Fault Detection and Identification (FDI) in a multi-UAV context. Differential Global Positioning System (DGPS) and inertial sensors are used for sensor FDI in each UAV. The method uses additional position estimations that augment individual UAV FDI system. These additional estimations are obtained using images from the same planar scene taken from two different UAVs. Since accuracy and noise level of the estimation depends on several factors, dynamic replanning of the multi-UAV team can be used to obtain a better estimation in case of faults caused by slow growing errors of absolute position estimation that cannot be detected by using local FDI in the UAVs. Experimental results with data from two real UAVs are also presented.

Heredia, Guillermo; Caballero, Fernando; Maza, Ivan; Merino, Luis; Viguria, Antidio; Ollero, Anibal

2009-01-01

295

System design that minimizes both missed detections and false alarms: a case study in arc fault detection  

Microsoft Academic Search

This paper considers several components in the architecture and design of systems to discriminate conditions and fuse the data. It focuses on the problems of missing detections and reducing the possibility of generating false positive alarms. It uses a case study of a protective system that detects arcing faults in power switchboards on board ships. The results in this paper

Kim R. Fowler

2004-01-01

296

Nonlinear Geometric Approach to Fault Detection and Isolation in an Aircraft Nonlinear Longitudinal Model  

Microsoft Academic Search

In this paper, aircraft actuator fault detection and isolation (FDI) is investigated and designed using a nonlinear geometric FDI approach based on a nonlinear longitudinal aircraft model. Two detection filters are designed for the throttle position and the elevator angle, respectively, which are the two main actuation signals in the longitudinal aircraft model. In nonlinear geometric FDI approach the objective

N. Meskin; T. Jiang; E. Sobhani; K. Khorasani; C. A. Rabbath

2007-01-01

297

An innovative Fiber Bragg Grating sensor capable of fault detection in radial power systems  

Microsoft Academic Search

In this paper, a fiber optic based sensor capable of fault detection in power systems is presented. This sensor uses Bragg wavelength shift to measure current in power systems. Magnetic fields generated by currents in power transmission lines cause a strain in magnetostrictive material which is then detected by Fiber Bragg Grating (FBG). Interrogators sense the reflected FBG signals, and

Amin Moghadas; Ronald Barnes; Mehdi Shadaram

2010-01-01

298

Fault Detection Using Principal Components-Based Gaussian Mixture Model for Semiconductor Manufacturing Processes  

Microsoft Academic Search

Fault detection has been recognized in the semi- conductor industry as an effective component of advanced process control framework in increasing yield and product qual- ity. Recently, conventional process monitoring-based principal component analysis (PCA) has been applied to semiconductor manufacturing by quickly detecting when the process abnormal- ities have occurred. However, the unique characteristics of the semiconductor processes, nonlinearity in

Jianbo Yu

2011-01-01

299

An intelligent fault identification method of rolling bearings based on LSSVM optimized by improved PSO  

NASA Astrophysics Data System (ADS)

This paper presents an intelligent fault identification method of rolling bearings based on least squares support vector machine optimized by improved particle swarm optimization (IPSO-LSSVM). The method adopts a modified PSO algorithm to optimize the parameters of LSSVM, and then the optimized model could be established to identify the different fault patterns of rolling bearings. Firstly, original fault vibration signals are decomposed into some stationary intrinsic mode functions (IMFs) by empirical mode decomposition (EMD) method and the energy feature indexes extraction based on IMF energy entropy is analyzed in detail. Secondly, the extracted energy indexes serve as the fault feature vectors to be input to the IPSO-LSSVM classifier for identifying different fault patterns. Finally, a case study on rolling bearing fault identification demonstrates that the method can effectively enhance identification accuracy and convergence rate.

Xu, Hongbo; Chen, Guohua

2013-02-01

300

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

301

Dynamic Source Rupture Simulation of Dipping Faults With a 3D Finite-Difference Method  

NASA Astrophysics Data System (ADS)

The finite-difference method (FDM) has been widely used for numerical modeling of seismic source problems, including investigation on the dynamic source processes. Owing to both conceptual and computational constraints of FDM, fault models have largely been limited to the cases that the fault planes are parallel to the FDM grid. However, recent observation and kinematic inversion results discover that more complex fault geometry models, such as bending faults or curved faults, are needed to explain some earthquake phenomena. Thus, we need to develop an approach of FDM to treat a fault planes slanted with respect to the FDM grid. In this study, we propose a method to analyze the dynamic source problems of nonvertical faults, using a 3D FDM with nonuniform grid spacing (Pitarka, 1999). This approach does not require aligning the fault plane to the FDM grid for implementation of FDM. We estimate the shear stress on the nonvertical fault plane from the six stress components obtained in FDM calculation with respect to the force balance condition and the coordination transformation. This method can be used to deal with a more realistically complex fault geometry model. We validate our method by studying two cases of the dynamic source problems which have been analyzed by Madariaga et al. (1998). One is the instantaneous rupture model of a circular fault embedded in a homogeneous elastic medium; another is the spontaneous rupture model of a rectangular fault which starts from a local circular asperity on the fault plane. We analyze the inclined fault models against the space grid coordination for both of the rupture problems and compare our simulations with previous results obtained by Madariaga et al. (1998) using the horizontal fault plane model. Our simulations gave similar results with those of Madariaga et al. (1998). Thus, our method can be used to analyze the dynamic rupture processes of dipping fault models. This implementation was used to compute the dynamic source problems of the 1999 Chi-Chi, Taiwan, earthquake by Zhang et al. (2003, 2004). We found that the rupture process of this event is more complex than that described in the kinematic model. Our dynamic model revealed that for a large earthquake such as the Chi-Chi earthquake, the rupture propagation can be discontinuous, as suggested by some numerical simulations (Das and Aki, 1977; Day, 1982). In this study, we apply the proposed method to analyze the dynamics of the 2003 Tokachi-Oki, Japan, earthquake. The fault model of this earthquake is a dipping fault with a dip angle of 18 degree. We rebuild the dynamic rupture process of this event and simulate the near source ground motions based on the dynamic source model.

Zhang, W.; Iwata, T.

2004-12-01

302

Online Motor Fault Detection and Diagnosis Using a Hybrid FMM-CART Model.  

PubMed

In this brief, a hybrid model combining the fuzzy min-max (FMM) neural network and the classification and regression tree (CART) for online motor detection and diagnosis tasks is described. The hybrid model, known as FMM-CART, exploits the advantages of both FMM and CART for undertaking data classification and rule extraction problems. To evaluate the applicability of the proposed FMM-CART model, an evaluation with a benchmark data set pertaining to electrical motor bearing faults is first conducted. The results obtained are equivalent to those reported in the literature. Then, a laboratory experiment for detecting and diagnosing eccentricity faults in an induction motor is performed. In addition to producing accurate results, useful rules in the form of a decision tree are extracted to provide explanation and justification for the predictions from FMM-CART. The experimental outcome positively shows the potential of FMM-CART in undertaking online motor fault detection and diagnosis tasks. PMID:24807956

Seera, Manjeevan; Chee Peng Lim

2014-04-01

303

A neural network approach to the detection of incipient faults on power distribution feeders  

SciTech Connect

A high-impedence fault is an abnormal event on an electric power distribution feeder which can not be easily detected by conventional overcurrent protective devices. This paper describes a neural network strategy for the detection of this type of incipient fault. Neural networks are particularly well-suited for solving difficult signal processing and pattern recognition problems. An optimization technique allows a network to learn rules for solving a problem by processing a set of example cases. The data preprocessing required to set up the training cases and the implementation of the neural network itself are described. The potential of the neural network approach is demonstrated by applying the detection scheme to high- impedence faults simulated on a model distribution system.

Ebron, S.; Lubkeman, D.L.; White, M. (Electric Power Research Center, College of Engineering, North Carolina State Univ., Raleigh, NC (US))

1990-04-01

304

Generalized method of analysis of simultaneous faults in electric power systems  

Microsoft Academic Search

This paper describes two methods to analyze any combination of simultaneous balanced and unbalanced faults in a power system. The first method can be used to calculate the symmetrical components and phase components for any bus voltage and branch current of a faulted power system. Using the second method, an equivalent network connected to the positive sequence network can be

Ham

1982-01-01

305

Generalized Method of Analysis of Simultaneous Faults in Electric Power System  

Microsoft Academic Search

This paper describes two methods to analyze any combination of simultaneous balanced and unbalanced faults in a power system. The first method can be used to calculate the symmetrical components and phase components for any bus voltage and branch current of a faulted power system. Using the second method, an equivalent network connected to the positive sequence network can be

Z. X. Han

1982-01-01

306

Tuning and comparing fault diagnosis methods for aeronautical systems via kriging-based optimization  

NASA Astrophysics Data System (ADS)

Many approaches address fault detection and isolation (FDI) based on analytical redundancy. To rank them, it is necessary to define performance indices and realistic sets of test cases on which they will be evaluated. For the ranking to be fair, each of the methods under consideration should have its internal parameters tuned optimally. The work presented uses a combination of tools developed in the context of computer experiments to achieve this tuning from a limited number of numerical evaluations. The methodology is then extended so as to provide a robust tuning in the worst-case sense.

Marzat, J.; Piet-Lahanier, H.; Damongeot, F.; Walter, E.

2013-12-01

307

Geophysical imaging of near subsurface layers to detect fault and fractured zones in the Tournemire Experimental Platform, France.  

NASA Astrophysics Data System (ADS)

IRSN (the French Institute for Radiological Protection and Nuclear Safety) is in charge of the expertise of the safety report of the French deep geological disposal site project in the East of France. With the goal of understanding the various transport and mechanical properties of clay-rocks, IRSN has conducted several research programs at the Tournemire Experimental Platform (TEP, in the Department of Aveyron in the South of France). Three major sub-horizontal layers characterize the sedimentary Jurassic formations of the TEP. At the base of the stratigraphic column, we find a sequence of limestones and dolomites, that is overlain by an argillaceous formation composed of a 250 m thick clay-rock layer. Above this layer, there is another sequence of limestones and dolomites. The TEP is characterized by a 2 km long tunnel, which allows in situ access to the Toarcian clay- rock layer. In addition to the main Cernon fault, secondary fault zones affect the clay-rock formation and have been observed in the galleries and also identified in several underground boreholes. These sub-vertical fault zones or fracture network display mainly subhorizontal offset (decametric scale) and a small vertical one (meter scale). In the upper limestone, these fault zones widen and fracturing becomes more scattered. In an attempt to detect fault zones in clay-rock layers such as the one described above, IRSN carried out in 2001 a 3D high-resolution seismic survey from the surface in collaboration with CGG. A sub-vertical fault was successfully picked out by the seismic data at the interface between the clay-rock formation and the underlying limestones. This fault is interpreted as the downward continuation of one of the fault zones identified in the tunnel. However, because of the weak seismic impedance contrast in the clay-rock layer and the small vertical offset of sub-vertical fault zones, these fault zones could not be identified in the clay-rock formation. No fault or fracture zone could either be detected in the upper limestone formation because of the acquisition geometry. In order to better image the clay-rock and upper limestone layers, IRSN, Mines ParisTech and UPPA conducted large-scale 2D and 3D very high-resolution seismic surveys in 2010 and 2011 from the surface in the framework of the GNR TRASSE. We analyze this new dataset with the first arrival traveltime tomography method in order to assess its potential to detect fault and fracture zones in near subsurface layers. For this purpose, we develop a new fast inversion algorithm that allows introducing a priori information and choosing a specific model parameterization. We validate our approach based on the Simultaneous Iterative Reconstruction Technique with synthetic data and present the first results of the new real dataset processing. We finally compare these results to a 2D high-resolution electrical resistivity profile acquired at the same location. These electrical resistivity data could also be considered as some a priori information in our inversion scheme.

Nhu Ba, Elise, Vi; Noble, Mark; Gélis, Céline; Gesret, Alexandrine; Cabrera, Justo

2013-04-01

308

Keys and pitfalls in mesoscale fault analysis and paleostress reconstructions, the use of Angelier's methods  

NASA Astrophysics Data System (ADS)

Whereas most of the stress inversion methods using fault slip data only minimize the angle between the measured striation and a computed shear stress to find the best fitting reduced stress tensor, Angelier (1990) proposed an alternative method named INVD that also takes into account the relative shear stress magnitude which allows the fault to move. Using artificial datasets and particular fault geometries we compare this method with one of the classical methods based on the minimization of the shear-slip angles (R4DT; Angelier, 1984) and we show that in most cases the new method has improved the quality of the results. Furthermore, as proposed by Angelier, we point out that the quality of the stress inversion primarily depends on the quality of the field data. We give advice and warn about some pitfalls concerning determination of sense of slip on fault planes, recognition of successive faulting events and their chronology, drawer (or wedge) faults, stress permutations, faults in vertical bedding. We also argue that, in case of tilted sequences, fault diagrams should not be presented without bedding planes. But we show that stress inversions, when realized with caution and with the correct method, can have much more applications than reconstructing stress fields, like for determining: the paleo-horizontal, the nature and the sense of motion of large faults, the chronology and age of large structures.

Hippolyte, Jean-Claude; Bergerat, Françoise; Gordon, Mark B.; Bellier, Olivier; Espurt, Nicolas

2012-12-01

309

The Marshall Space Flight Center Fault Detection Diagnosis and Recovery Laboratory  

NASA Technical Reports Server (NTRS)

The Fault Detection Diagnosis and Recovery Lab (FDDR) has been developed to support development of,fault detection algorithms for the flight computer aboard the Ares I and follow-on vehicles. It consists of several workstations using Ethernet and TCP/IP to simulate communications between vehicle sensors, flight computers, and ground based support computers. Isolation of tasks between workstations was set up intentionally to limit information flow and provide a realistic simulation of communication channels within the vehicle and between the vehicle and ground station.

Burchett, Bradley T.; Gamble, Jonathan; Rabban, Michael

2008-01-01

310

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

NASA Astrophysics Data System (ADS)

Subsidence has been a common occurrence in several cities in central Mexico for the past three decades. This process causes substantial damage to the urban infrastructure and housing in several cities and it is a major factor to be considered when planning urban development, land-use zoning and hazard mitigation strategies. Since the early 1980's the city of Morelia in Central Mexico has experienced subsidence associated with groundwater extraction in excess of natural recharge from rainfall. Previous works have focused on the detection and temporal evolution of the subsidence spatial distribution. The most recent InSAR analysis confirms the permanence of previously detected rapidly subsiding areas such as the Rio Grande Meander area and also defines 2 subsidence patches previously undetected in the newly developed suburban sectors west of Morelia at the Fraccionamiento Del Bosque along, south of Hwy. 15 and another patch located north of Morelia along Gabino Castañeda del Rio Ave. Because subsidence-induced, shallow faulting develops at high horizontal strain localization, newly developed a subsidence areas are particularly prone to faulting and fissuring. Shallow faulting increases groundwater vulnerability because it disrupts discharge hydraulic infrastructure and creates a direct path for transport of surface pollutants into the underlying aquifer. Other sectors in Morelia that have been experiencing subsidence for longer time have already developed well defined faults such as La Colina, Central Camionera, Torremolinos and La Paloma faults. Local construction codes in the vicinity of these faults define a very narrow swath along which housing construction is not allowed. In order to better characterize these fault systems and provide better criteria for future municipal construction codes we have surveyed the La Colina and Torremolinos fault systems in the western sector of Morelia using seismic tomographic techniques. Our results indicate that La Colina Fault include secondary faults at depths up to 4-8m below the surface and located up to 24m away from the main fault trace. The Torremolinos fault system includes secondary faults, which are present up to 8m deep and 12-18m away from the main fault trace. Even though the InSAR analysis provides an unsurpassed synoptic view, a higher temporal resolution observation of fault movement has been pursued using the MOIT continuously operating GPS station, which is located within 100 m from the La Colina main fault trace. GPS data is also particularly useful to decompose horizontal and vertical motion in the absence of both ascending and descending SAR data acquisitions. Observations since July 2009 show a total general displacement trend of -39mm/yr and a total horizontal differential motion of 41.8 mm/yr and -4.7mm/yr in its latitudinal and Longitudinal components respectively in respect to the motion observed at the MOGA GPS station located 5.0 km to the SSE within an area which is not affected by subsidence. In addition to the overall trend, high amplitude excursions at the MOIT station with individual residual amplitudes up to 20mm, 25mm, and 60mm in its latitudinal, longitudinal and vertical components respectively vertical are observed. The correlation of fault motion excursions in relationship to the rainfall records will be analyzed.

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

2013-12-01

311

Protecting RSA against Fault Attacks: The Embedding Method  

Microsoft Academic Search

Fault attacks constitute a major threat toward cryptographic products supporting RSA-based technologies. Most often, the public exponent is unknown, turning resistance to fault attacks into an intricate problem. Over the past few years, several techniques for secure implementations have been published, but none of them is fully satisfactory. We propose a completely different approach by embedding the public exponent into

Marc Joye

2009-01-01

312

Detection of fault structure under a near-surface low velocity layer by seismic tomography: synthetics studies  

NASA Astrophysics Data System (ADS)

We have developed a new method to detect a fault structure under a near-surface low velocity layer (LVL) by seismic tomography. The field study showed that the tomography image reconstructed using borehole-surface configuration had a different result from that of using a crosshole configuration. The image reconstructed by using a borehole-surface configuration showed a decrease in seismic velocities along boreholes, and also the tomogram result using both configurations can not detect the subsurface fault structure. These phenomena are caused by the low velocity layer (LVL) at the top of investigation area. The basic idea hard is based on a downward continuation principle. By knowing the thickness of the LVL and the top of bedrock enables us to place 'virtual receiver' and/or 'virtual source' below the LVL. In this way, we can reconstruct the image by various tomographic methodologies. As an advantage, this method is easy to be use with the aid of ray tracing methodology. It can also reduce the effect of the near-surface LVL and can maximize the reconstructed image. The final result of our synthetic images by ILST, SIRT, and modified SIRT shows high accuracy and resolution for detection of fault structure under the low velocity layer.

Sanny, Teuku A.; Sassa, Koichi

1996-09-01

313

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...

314

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

315

Fault-prone module detection using large-scale text features based on spam filtering  

Microsoft Academic Search

This paper proposes an approach using large-scale text features for fault-prone module detection inspired by spam filtering.\\u000a The number of every text feature in the source code of a module is counted and used as data for training detection models.\\u000a In this paper, we prepared a naive Bayes classifier and a logistic regression model as detection models. To show the

Hideaki Hata; Osamu Mizuno; Tohru Kikuno

2010-01-01

316

An Intelligent Fault Detection and Isolation Architecture for Antenna Arrays  

NASA Astrophysics Data System (ADS)

This article describes a general architecture for fault modeling, diagnosis, and isolation of the DSN antenna array based on computationally intelligent techniques(neural networks and fuzzy logic). It encompasses a suite of intelligent test and diagnosis algorithms in software. By continuously monitoring the health of the highly complex and nonlinear array observables, the automated diagnosis software will be able to identify and isolate the most likely causes of system failure in cases of faulty operation. Furthermore, it will be able to recommend a series of corresponding corrective actions and effectively act as an automated real-time and interactive system supervisor. In so doing, it will enhance the array capability by reducing the operational workload, increasing science information availability, reducing the overall cost of operation by reducing system downtimes, improving risk management, and making mission planning much more reliable. Operation of this architecture is illustrated using examples from observables available from the 34-meter arraying task.

Rahnamai, K.; Arabshahi, P.; Yan, T.-Y.; Pham, T.; Finley, S. G.

1997-10-01

317

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

Microsoft Academic Search

Time-domain reflectometry (TDR) is one of the stan- dard methods for diagnosing faults in electrical wiring and inter- connect systems, with a long-standing history focused mainly on hardware development of both high-fidelity systems for laboratory use and portable handheld devices for field deployment. While these devices can easily assess distance to hard faults such as sus- tained opens or shorts,

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

2011-01-01

318

A model-based probabilistic inversion framework for wire fault detection using TDR  

Microsoft Academic Search

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

Stefan R. Schuet; D. A. Timucin; K. R. Wheeler

2010-01-01

319

Decentralized Detection of a Class of Non-Abrupt Faults With Application to Formations of Unmanned Airships  

Microsoft Academic Search

We propose a decentralized non-abrupt fault detection (DNaFD) scheme for leader-to-follower formations of unmanned airships. Non-abrupt faults are those that result in slow performance degradation and in undesirable drift, which can propagate from one vehicle to another, and therefore can adversely affect mission integrity, potentially destabilizing multivehicle formations, while being difficult to detect. As opposed to model-based fault detectors, which

N. Lechevin; C. A. Rabbath

2009-01-01

320

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

321

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

322

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

323

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

324

A kurtosis-guided adaptive demodulation technique for bearing fault detection based on tunable-Q wavelet transform  

NASA Astrophysics Data System (ADS)

This paper presents an adaptive demodulation technique for bearing fault detection. It is implemented via the tunable-Q wavelet transform (TQWT). With the TQWT, the bearing vibration signal is decomposed into sub-signals corresponding to different band-pass filters of the TQWT. Kurtosis as an effective indicator of signal impulsiveness is adopted to guide the merging of the sub-signals leading to a signal component which contains information most relevant to the bearing fault. The purpose of the proposed approach is to adaptively search for the best filter for envelope demodulation analysis. In fact, the implementation of the proposed method can be interpreted as the process to obtain the optimal filter for the Hilbert demodulation analysis by two steps of merging of the band-pass filters of the TQWT. The effectiveness of the proposed method has been demonstrated by both simulation and experimental analyses.

Luo, Jiesi; Yu, Dejie; Liang, Ming

2013-05-01

325

Soft-Error Detection through Software Fault-Tolerance Techniques  

Microsoft Academic Search

The paper describes a systematic approach for automatically introducing data and code redundancy into an existing program written using a high-level language. The transformations aim at making the program able to detect most of the soft-errors affecting data and code, independently of the Error Detection Mechanisms (EDMs) possibly implemented by the hardware. Since the transformations can be automatically applied as

Maurizio Rebaudengo; Matteo Sonza Reorda; Marco Torchiano; Massimo Violante

1999-01-01

326

The use of soil mercury and radon gas surveys to assist the detection of concealed faults in Fuzhou City, China  

NASA Astrophysics Data System (ADS)

Soil gas approaches have been proven useful for detecting buried faults in field survey. How about their applicability in urban area? A trial soil gas survey has been conducted in an attempt to evaluate this in Fuzhou City, Southeastern China. The detection was performed by measuring the adsorbed mercury, free mercury and radon gases in soil in the sites such as crop soil, refilled soil and those with shallow groundwater levels. The resulting distributions show that anomalous concentrations of soil gases over faults are generally two to four times as much as those in the surrounding areas. The locations of peak values of absorbed and free mercury could possibly be applied to assist to determine the trend of faults. The background values of free mercury seems to be more stable and the anomalous zones narrower than those of radon gas, therefore, the free mercury method seems to be good for detection at this area, especially in those sites with shallow groundwater levels. The false gas anomalies may occur in such a site as refilled with external soil, refilled pond and abandoned construction bases.

Wang, Guangcai; Liu, Chenglong; Wang, Jihua; Liu, Wuzhou; Zhang, Peiren

2006-10-01

327

Combined expert system/neural networks method for process fault diagnosis  

DOEpatents

A two-level hierarchical approach for process fault diagnosis of an operating system employs a function-oriented approach at a first level and a component characteristic-oriented approach at a second level, where the decision-making procedure is structured in order of decreasing intelligence with increasing precision. At the first level, the diagnostic method is general and has knowledge of the overall process including a wide variety of plant transients and the functional behavior of the process components. An expert system classifies malfunctions by function to narrow the diagnostic focus to a particular set of possible faulty components that could be responsible for the detected functional misbehavior of the operating system. At the second level, the diagnostic method limits its scope to component malfunctions, using more detailed knowledge of component characteristics. Trained artificial neural networks are used to further narrow the diagnosis and to uniquely identify the faulty component by classifying the abnormal condition data as a failure of one of the hypothesized components through component characteristics. Once an anomaly is detected, the hierarchical structure is used to successively narrow the diagnostic focus from a function misbehavior, i.e., a function oriented approach, until the fault can be determined, i.e., a component characteristic-oriented approach. 9 figs.

Reifman, J.; Wei, T.Y.C.

1995-08-15

328

Combined expert system/neural networks method for process fault diagnosis  

DOEpatents

A two-level hierarchical approach for process fault diagnosis is an operating system employs a function-oriented approach at a first level and a component characteristic-oriented approach at a second level, where the decision-making procedure is structured in order of decreasing intelligence with increasing precision. At the first level, the diagnostic method is general and has knowledge of the overall process including a wide variety of plant transients and the functional behavior of the process components. An expert system classifies malfunctions by function to narrow the diagnostic focus to a particular set of possible faulty components that could be responsible for the detected functional misbehavior of the operating system. At the second level, the diagnostic method limits its scope to component malfunctions, using more detailed knowledge of component characteristics. Trained artificial neural networks are used to further narrow the diagnosis and to uniquely identify the faulty component by classifying the abnormal condition data as a failure of one of the hypothesized components through component characteristics. Once an anomaly is detected, the hierarchical structure is used to successively narrow the diagnostic focus from a function misbehavior, i.e., a function oriented approach, until the fault can be determined, i.e., a component characteristic-oriented approach.

Reifman, Jaques (Westchester, IL); Wei, Thomas Y. C. (Downers Grove, IL)

1995-01-01

329

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

PubMed Central

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

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

2012-01-01

330

A robust model-based information system for monitoring and fault detection of large scale belt conveyor systems  

Microsoft Academic Search

In this paper an information system is presented, which is developed to meet the requirements on fault detection and online monitoring of large scale belt conveyor systems. The core of this information system consists of a mathematical model, observer and fault detection system.

T. Jeinsch; M. Sader; R. Noack; K. Barber; S. X. Ding; P. Zang; M. Zhong

2002-01-01

331

Software Fault Tree and Colored Petri Net Based Specification, Design and Implementation of Agent-Based Intrusion Detection Systems  

Microsoft Academic Search

The integration of Software Fault Tree Analysis (SFTA) (to describe intrusions) and Colored Petri Nets (CPNs) (to specify design) is examined for an Intrusion Detection System (IDS). The IDS under development is a collection of mobile agents that detect, classify, and correlate system and network activities. Software Fault Trees (SFTs), augmented with nodes that describe trust, temporal, and contextual relationships,

Guy Helmer; Johnny Wong; Mark Slagell; Vasant Honavar; Les Miller; Yanxin Wang; Xia Wang; Natalia Stakhanova

2001-01-01

332

Design and application of Rogowski coil current sensor without integrator for fault detection in induction motors  

Microsoft Academic Search

This paper presents the study, design and application of a Rogowski coil current sensor without the integrator circuit that is typically used. This sensor is used as current probe for fault detection in induction motors by means of motor current signal analysis (MCSA).

O. Poncelas; J. A. Rosero; J. Cusido; J. A. Ortega; L. Romeral

2008-01-01

333

Gear fault detection using artificial neural networks and support vector machines with genetic algorithms  

Microsoft Academic Search

A study is presented to compare the performance of gear fault detection using artificial neural networks (ANNs) and support vector machines (SMVs). The time-domain vibration signals of a rotating machine with normal and defective gears are processed for feature extraction. The extracted features from original and preprocessed signals are used as inputs to both classifiers based on ANNs and SVMs

B. Samanta

2004-01-01

334

A fuzzy expert system for fault detection in statistical process control of industrial processes  

Microsoft Academic Search

Little work has previously been reported on the use of fuzzy logic within statistical process control when this is used for fault detection as part of quality control systems in industrial manufacturing processes. Therefore, the paper investigates the potential use of fuzzy logic to enhance the performance of statistical process control (SPC). The cumulative sum of the deviation in the

Shendy M. El-shal; Alan S. Morris

2000-01-01

335

On thruster allocation, fault detection and accommodation issues for underwater robotic vehicles  

Microsoft Academic Search

The use of mono-directional thrusters on under- water vehicle poses interesting issues on actuator allocation, fault detection and accommodation. Preliminary results rel- ative to the horizontal motion of an unhabited underwater vehicle (UUV) are presented. Index Terms— Underwater remotely operated vehicles, con- trol allocation. I. INTRODUCTION The use of shallow water unhabited underwater vehicle (UUV) systems for environment monitoring is

Giovanni Indiveri; Gianfranco Parlangeli

336

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

337

Simulation (model) based fault detection and diagnosis of a spacecraft electrical power system  

Microsoft Academic Search

Model-based artificial intelligence approaches to diagnosis require encoding a reasonable facsimile of the problem domain. The model is encoded as a classical engineering simulation of the domain, a spacecraft electrical power system (EPS). Portions of the reasoning system thus become comparators between the expected behavior and the EPS. The diagnostic problem is partitioned into six discrete steps including: fault detection,

Peter J. Adamovits; Bernard Pagurek

1993-01-01

338

Fault detection and diagnosis of aircraft actuators using fuzzy-tuning IMM filter  

Microsoft Academic Search

This paper proposes a new interacting multiple model (IMM) filter for actuator fault detection. Since each individual filter of the IMM filter uses the combined information of the estimation values from all the operating filters, it can effectively estimate system parameter variations, thereby it can diagnose the actuator damage with an unknown magnitude. In this study, to diagnose the actuator

Seungkeun Kim; Jiyoung Choi; Youdan Kim

2008-01-01

339

Combined dynamic data analysis and process variable prediction approach for system fault detection  

Microsoft Academic Search

A fault detection approach based on the combination of the Generalized Consistency Check and the Sequential Probability Ratio Test is developed and applied for validation of signals from process sensors. The basic methodology requires at least triple redundancy of a given measurement from like sensors and analytical measurements. The separate measurement of the signal mean value and the random fluctuation

B. R. Upadhyaya; O. Glockler; F. Wolvaardt

1987-01-01

340

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

341

Actuator fault detection and isolation in nonlinear systems using LMIs and LMEs  

Microsoft Academic Search

An actuator fault detection and isolation scheme for a class of continuous-time nonlinear systems is presented. A bank of unknown-input observers is used for this purpose. Only linear matrix equations and inequalities are used in the design which makes it particularly attractive from a computational viewpoint

Edwin Engin Yaz; Asad Azemi

1998-01-01

342

Faults Detection Using Gaussian Mixture Models, Mel-Frequency Cepstral Coefficients and Kurtosis  

Microsoft Academic Search

Most machines failures can be associated with mechanical failures on bearing failures. This paper proposes a novel approach to detect and classify three types of common faults in rolling element bearings. The approach proposed here makes use Gaussian mixture model to classify, Mel-frequency cepstral coefficients (MFCC) and kurtosis are extracted from the bearing vibration signal and are used as features.

Fulufhelo V. Nelwamondo; T. Marwala

2006-01-01

343

A neural network model for fault detection in conjunction with a programmable logic controller  

Microsoft Academic Search

This paper discusses the feasibility of using neural networks as a tool in the fault detection process. A neural network is integrated with a state language programmable logic controller, an important device in an automatic control system. Time series data related to time spent in a state is gathered and used as input into a neural network, for the purpose

Barbara A. Osyk; Ming S. Hung; Gregory R. Madey

1994-01-01

344

Model-integrated toolset for fault detection, isolation and recovery (FDIR)  

Microsoft Academic Search

Fault detection, isolation and recovery (FDIR) functions are essential components of complex engineering systems. The design, validation, implementation, deployment and maintenance of FDIR systems are extremely information intensive tests requiring in-depth knowledge of the engineering system. The paper gives an overview of a model-integrated toolset supporting FDIR from design, into post deployment. The toolset is used for development of large,

J. R. Carnes; Amit Misra; Janos Sztipanovits

1996-01-01

345

Fault detection in railway track using piezoelectric impedance  

NASA Astrophysics Data System (ADS)

In this research, piezoelectric transducers are incorporated in an impedance-based damage detection approach for railway track health monitoring. The impedance-based damage detection approach utilizes the direct relationship between the mechanical impedance of the track and electrical impedance of the piezoelectric transducer bonded. The effect of damage is shown in the change of a healthy impedance curve to an altered, damaged curve. Using a normalized relative difference outlier analysis, the occurrences of various damages on the track are determined. Furthermore, the integration of inductive circuitry with the piezoelectric transducer is found to be able to considerably increase overall damage detection sensitivity.

Cremins, M.; Shuai, Qi; Xu, Jiawen; Tang, J.

2014-04-01

346

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

347

New method of fiber Bragg grating demodulation technique and applied in detection of equipment  

Microsoft Academic Search

Numbers of temperature signal and both dynamic and static strain signal in different places should be detected in fault diagnosis of some equipment system. Fiber Bragg Grating sensor was provided usefully as detection instrument for fault diagnosis of equipment system, but the demodulation technique in existence couldn't satisfy multi-dots and multi-parameters detection of the system. F-P scan method amalgamated non-balance

Bing Zhao; Zhi-Li Zhang; Qi-Yuan Zhong; Hongliang Tu; Lilong Tan

2009-01-01

348

Quantitative Methods of Edge Detection.  

National Technical Information Service (NTIS)

Most local operators used in edge detection can be modelled by one of two methods: edge enhancement/thresholding and edge fitting. This dissertation presents a quantitative design and performance evaluation of these methods. The design techniques are base...

I. E. Abdou

1978-01-01

349

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

350

Dynamic Source Rupture Simulation of Dipping Faults With a 3D Finite-Difference Method  

Microsoft Academic Search

The finite-difference method (FDM) has been widely used for numerical modeling of seismic source problems, including investigation on the dynamic source processes. Owing to both conceptual and computational constraints of FDM, fault models have largely been limited to the cases that the fault planes are parallel to the FDM grid. However, recent observation and kinematic inversion results discover that more

W. Zhang; T. Iwata

2004-01-01

351

Fault detection for salinity sensors in the Columbia estuary  

NASA Astrophysics Data System (ADS)

Sensors deployed in the Columbia River estuary gather information on physical dynamics and changes in estuary habitat. Of these sensors, conductivity sensors are particularly susceptible to biofouling, which gradually degrades sensor response and corrupts critical data. Several weeks may pass before degradation is visibly detected. Since the onset time of biofouling is unknown, an indeterminate amount of measurement data is corrupted. To speed detection and minimize data loss, we develop automatic biofouling detectors based on machine learning approaches for these conductivity sensors. We demonstrate that our detectors identify biofouling at least as reliably as human experts. In addition, these detectors provide accurate estimates of biofouling onset time. Real-time detectors installed during the summer of 2001 produced no false alarms yet detected all episodes of sensor degradation before the field staff.

Archer, Cynthia; Baptista, Antonio; Leen, Todd K.

2003-03-01

352

Fault Detection and Monitoring of a Ball Bearing Benchtest and a Production Machine via Autoregressive Spectrum Analysis  

NASA Astrophysics Data System (ADS)

This paper deals with the implementation of parametric spectrum analysis using the high-resolution technique in setting up conditional maintenance via vibration analysis on a forming press. To achieve this, the resolution power of signal-modelling-based parametric techniques is shown through spectrum assessment computation. The processing of the experimental results enabled (i) various AR spectrum analysis methods and especially Burg's algorithm to be tested, and (ii) conventional spectrum analysis techniques such as the correlogram to be compared with parametric methods at a detection level as well as for mechanical component fault monitoring, especially ball bearing defects. Among various possible models, the AR model was retained along with Burg's algorithm and the AIC criterion. A detection and spotting methodology of faults likely to occur on rotating machinery was developed on the basis of the results which were obtained. This methodology, supplementing other analysis techniques, relies on the understanding of component spectrum behaviour and various constraints to be mastered such as component access availability and problems due to industrial measuring device spectrum resolution, as well as static properties of the power spectrum density assessors of a random signal. The results show that parametric methods are particularly worthwhile in the early detection of component defects, especially when two typical frequencies are close to one another. However, the complexity of these techniques necessitates many precautions when they are implemented; consequently, they should not replace conventional methods, but supplement them.

Dron, J. P.; Rasolofondraibe, L.; Couet, C.; Pavan, A.

1998-12-01

353

Fault Detection of DC Electric Motors Using the Bispectral Analysis  

Microsoft Academic Search

The two major advantages of bispectral analysis are: resistance to noise and the ability to detect nonlinearities, like quadratic\\u000a phase coupling. The first aim was to study some of the theoretical aspects of bispectral estimation. A lot of attention was\\u000a paid to the influence of noise, the number of segments, the influence of one or several harmonic deterministic components\\u000a and

Miha Boltežar; Janko Slavi?

2006-01-01

354

Detection of incipient fault using fuzzy agglomerative clustering algorithm  

Microsoft Academic Search

This paper depicts an adaptive diagnostic system based on a fuzzy pattern recognition approach. The proposed system is designed to operate on-line and to deal with the following characteristics: on-line adaptation of classes, detection of slow or abrupt changes and stabilization in a new state, on-line creation of new classes. To meet these requirements, classes are constructed sequentially with a

Nassim Boudaoud; M. Masson

1999-01-01

355

Application of a high gain observer to fault detection  

Microsoft Academic Search

It is well known that model uncertainty in dynamic systems can be expressed in terms of unknown inputs. The purpose of designing a robust observer is then to find a gain matrix which will attenuate the effect of the unknown input. During the last few years many methods have been developed to achieve this. One such method is the high

S. Daley; H. Wang

1993-01-01

356

Fault Detection and Protection of Induction Motors Using Sensors  

Microsoft Academic Search

Protection of an induction motor (IM) against possible problems, such as overvoltage, overcurrent, overload, overtemperature, and undervoltage, occurring in the course of its operation is very important, because it is used intensively in industry as an actuator. IMs can be protected using some components, such as timers, contactors, voltage, and current relays. This method is known as the classical method

Ramazan Bayindir; I. Sefa; I. Colak; Askin Bektas

2008-01-01

357

Adaptive Fault Detection on Liquid Propulsion Systems with Virtual Sensors: Algorithms and Architectures  

NASA Technical Reports Server (NTRS)

Prior to the launch of STS-119 NASA had completed a study of an issue in the flow control valve (FCV) in the Main Propulsion System of the Space Shuttle using an adaptive learning method known as Virtual Sensors. Virtual Sensors are a class of algorithms that estimate the value of a time series given other potentially nonlinearly correlated sensor readings. In the case presented here, the Virtual Sensors algorithm is based on an ensemble learning approach and takes sensor readings and control signals as input to estimate the pressure in a subsystem of the Main Propulsion System. Our results indicate that this method can detect faults in the FCV at the time when they occur. We use the standard deviation of the predictions of the ensemble as a measure of uncertainty in the estimate. This uncertainty estimate was crucial to understanding the nature and magnitude of transient characteristics during startup of the engine. This paper overviews the Virtual Sensors algorithm and discusses results on a comprehensive set of Shuttle missions and also discusses the architecture necessary for deploying such algorithms in a real-time, closed-loop system or a human-in-the-loop monitoring system. These results were presented at a Flight Readiness Review of the Space Shuttle in early 2009.

Matthews, Bryan L.; Srivastava, Ashok N.

2010-01-01

358

Fault Detection in Process Machinery by Vibration Analysis,  

National Technical Information Service (NTIS)

The report describes the methods of malfunction diagnosis of rotating machinery by vibration analysis. The frequency analysis of vibration signals is a very effective tool for diagnosing mechanical problems in rotating machinery and the use of this techni...

S. A. Ansari S. K. Ayazuddin

1984-01-01

359

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

360

Study on Fault Diagnostics of a Turboprop Engine Using Inverse Performance Model and Artificial Intelligent Methods  

NASA Astrophysics Data System (ADS)

Recently, the health monitoring system of major gas path components of gas turbine uses mostly the model based method like the Gas Path Analysis (GPA). This method is to find quantity changes of component performance characteristic parameters such as isentropic efficiency and mass flow parameter by comparing between measured engine performance parameters such as temperatures, pressures, rotational speeds, fuel consumption, etc. and clean engine performance parameters without any engine faults which are calculated by the base engine performance model. Currently, the expert engine diagnostic systems using the artificial intelligent methods such as Neural Networks (NNs), Fuzzy Logic and Genetic Algorithms (GAs) have been studied to improve the model based method. Among them the NNs are mostly used to the engine fault diagnostic system due to its good learning performance, but it has a drawback due to low accuracy and long learning time to build learning data base if there are large amount of learning data. In addition, it has a very complex structure for finding effectively single type faults or multiple type faults of gas path components. This work builds inversely a base performance model of a turboprop engine to be used for a high altitude operation UAV using measured performance data, and proposes a fault diagnostic system using the base engine performance model and the artificial intelligent methods such as Fuzzy logic and Neural Network. The proposed diagnostic system isolates firstly the faulted components using Fuzzy Logic, then quantifies faults of the identified components using the NN leaned by fault learning data base, which are obtained from the developed base performance model. In leaning the NN, the Feed Forward Back Propagation (FFBP) method is used. Finally, it is verified through several test examples that the component faults implanted arbitrarily in the engine are well isolated and quantified by the proposed diagnostic system.

Kong, Changduk; Lim, Semyeong

2011-12-01

361

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

SciTech Connect

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

Zhang Yumin; Lum, Kai-Yew [Temasek Laboratories, National University of Singapore, Singapore 117508 (Singapore); Wang Qingguo [Depa. Electrical and Computer Engineering, National University of Singapore, Singapore 117576 (Singapore)

2009-03-05

362

Research of high-resolution vibration signal detection technique and application to mechanical fault diagnosis  

NASA Astrophysics Data System (ADS)

Bilinear time-frequency transformation can possess a simultaneous high resolution both in the time domain and the frequency domain. It can be utilised to detect weak transient vibration signals generated by early mechanical faults in complex background and thus is of great importance to early mechanical fault diagnoses. It has been found that the spectrogram has low resolution, and there is strong cross-terms in Wigner-Ville distribution and frequency aliasing and information loss in Choi-Williams distribution (CWD). Hence, they cannot achieve satisfied transient signal detection results. To enhance the capability of detecting transient vibration signals, based on the analysis of exponent distribution, this paper presents some novel alias-free time-frequency distributions. These distributions can avoid the information loss in CWD while suppressing the cross-terms. Moreover, they have high simultaneous resolutions in both the time and frequency domain. Digital simulation and gearbox fault diagnosis experiments prove that these new distributions can effectively detect transient components from complicated mechanical vibration signals.

Fan, Y. S.; Zheng, G. T.

2007-02-01

363

A robust data fusion scheme for integrated navigation systems employing fault detection methodology augmented with fuzzy adaptive filtering  

NASA Astrophysics Data System (ADS)

Integrated navigation systems for various applications, generally employs the centralized Kalman filter (CKF) wherein all measured sensor data are communicated to a single central Kalman filter. The advantage of CKF is that there is a minimal loss of information and high precision under benign conditions. But CKF may suffer computational overloading, and poor fault tolerance. The alternative is the federated Kalman filter (FKF) wherein the local estimates can deliver optimal or suboptimal state estimate as per certain information fusion criterion. FKF has enhanced throughput and multiple level fault detection capability. The Standard CKF or FKF require that the system noise and the measurement noise are zero-mean and Gaussian. Moreover it is assumed that covariance of system and measurement noises remain constant. But if the theoretical and actual statistical features employed in Kalman filter are not compatible, the Kalman filter does not render satisfactory solutions and divergence problems also occur. To resolve such problems, in this paper, an adaptive Kalman filter scheme strengthened with fuzzy inference system (FIS) is employed to adapt the statistical features of contributing sensors, online, in the light of real system dynamics and varying measurement noises. The excessive faults are detected and isolated by employing Chi Square test method. As a case study, the presented scheme has been implemented on Strapdown Inertial Navigation System (SINS) integrated with the Celestial Navigation System (CNS), GPS and Doppler radar using FKF. Collectively the overall system can be termed as SINS/CNS/GPS/Doppler integrated navigation system. The simulation results have validated the effectiveness of the presented scheme with significantly enhanced precision, reliability and fault tolerance. Effectiveness of the scheme has been tested against simulated abnormal errors/noises during different time segments of flight. It is believed that the presented scheme can be applied to the navigation system of aircraft or unmanned aerial vehicle (UAV).

Ushaq, Muhammad; Fang, Jiancheng

2013-10-01

364

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

365

Wigner-Ville distributions for detection of rotor faults in brushless DC (BLDC) motors operating under non-stationary conditions  

Microsoft Academic Search

Electric motors often operate under operating conditions that are constantly changing with time. Most of such applications demand high reliability from the motor. Early detection of developing motor faults could help provide this needed reliability. While diagnostics of faults in motors operating under steady state conditions is straight forward due to the use of the well known Fourier transformation, diagnostics

S. Rajagopalan; J. A. Restrepo; J. M. Aller; T. G. Habetler; R. G. Harley

2005-01-01

366

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

Microsoft Academic Search

In this paper, a H-infinity fault detection and diagnosis (FDD) scheme for a class of discrete nonlinear system fault using output probability density estimation is presented. Unlike classical FDD problems, the measured output of the system is viewed as a stochastic process and its square root probability density function (PDF) is modeled with B-spline functions, which leads to a deterministic

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

2009-01-01

367

Handling Software Faults with Redundancy  

Microsoft Academic Search

Software engineering methods can increase the dependability of software systems, and yet some faults escape even the most\\u000a rigorous and methodical development process. Therefore, to guarantee high levels of reliability in the presence of faults,\\u000a software systems must be designed to reduce the impact of the failures caused by such faults, for example by deploying techniques\\u000a to detect and compensate

Antonio Carzaniga; Alessandra Gorla; Mauro Pezzè

2008-01-01

368

A Dynamic Finite Element Method for Simulating the Physics of Faults Systems  

NASA Astrophysics Data System (ADS)

We introduce a dynamic Finite Element method using a novel high level scripting language to describe the physical equations, boundary conditions and time integration scheme. The library we use is the parallel Finley library: a finite element kernel library, designed for solving large-scale problems. It is incorporated as a differential equation solver into a more general library called escript, based on the scripting language Python. This library has been developed to facilitate the rapid development of 3D parallel codes, and is optimised for the Australian Computational Earth Systems Simulator Major National Research Facility (ACcESS MNRF) supercomputer, a 208 processor SGI Altix with a peak performance of 1.1 TFlops. Using the scripting approach we obtain a parallel FE code able to take advantage of the computational efficiency of the Altix 3700. We consider faults as material discontinuities (the displacement, velocity, and acceleration fields are discontinuous at the fault), with elastic behavior. The stress continuity at the fault is achieved naturally through the expression of the fault interactions in the weak formulation. The elasticity problem is solved explicitly in time, using the Saint Verlat scheme. Finally, we specify a suitable frictional constitutive relation and numerical scheme to simulate fault behaviour. Our model is based on previous work on modelling fault friction and multi-fault systems using lattice solid-like models. We adapt the 2D model for simulating the dynamics of parallel fault systems described to the Finite-Element method. The approach uses a frictional relation along faults that is slip and slip-rate dependent, and the numerical integration approach introduced by Mora and Place in the lattice solid model. In order to illustrate the new Finite Element model, single and multi-fault simulation examples are presented.

Saez, E.; Mora, P.; Gross, L.; Weatherley, D.

2004-12-01

369

Detecting tangential dislocations on planar faults from traction free surface observations  

Microsoft Academic Search

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

Ioan R. Ionescu; Darko Volkov

2009-01-01

370

Design of automatic equipment for detecting faults in electronic measuring equipment  

Microsoft Academic Search

1.There are many theoretical and experimental papers on automatic fault location in electronic systems; individual representatives of such equipment have been designed, but these have specific purposes, while they are also of considerable complexity, so they have not found general use in servicing or repair of complex equipment.2.A major advance in this region may be obtained from contactless methods of

N. I. Vlasov

1973-01-01

371

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

PubMed Central

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.

Park, Wookje; Jung, Sikhang

2014-01-01

372

Research on fault pattern recognition for aircraft fuel system with its performance simulation  

Microsoft Academic Search

This paper presents application research on fault pattern recognition for aircraft fuel system based on its performance simulation. Fault pattern recognition method is used to perform fault detection, fault isolation, fault prognostics and so on in complicated system, which is basic research contents of prognostics and health management (PHM). Since the hardware of fuel system for an aircraft is too

Haifeng Wang; Bifeng Song; Fangyi Wan

2011-01-01

373

Fault diagnosis of power electronic circuits based on neural network and waveform analysis  

Microsoft Academic Search

Based on neural network theory, a new fault diagnosis method for power electronic circuits is presented. By keeping the relations between faults and waveforms in a neural network, the neural network can be trained to detect faults. So automation of fault diagnosis can be realized. In this paper, the fault diagnosis of a three-phase SCR rectifier circuit will be taken

Hao Ma; Dehong Xu; Yim-Shu Lee

1999-01-01

374

A new impedance-based fault location method for radial distribution systems  

Microsoft Academic Search

A new impedance-based fault location method suitable for radial distribution systems is presented in this paper. The method uses the fundamental phasor components of voltage and current signals available at the distribution substation end only. Considering the unbalanced nature of the distribution network with single-phase and two-phase laterals, and unbalanced loads the fault location algorithm is derived using phase-component analysis.

K. Ramar; E. E. Ngu

2010-01-01

375

Improvement in the Fault Boundary Conditions for a Staggered Grid Finite-difference Method  

Microsoft Academic Search

The staggered grid finite-difference method is a powerful tool in seismology and is commonly used to study earthquake source\\u000a dynamics. In the staggered grid finite-difference method stress and particle velocity components are calculated at different\\u000a grid points, and a faulting problem is a mixed boundary problem, therefore different implementations of fault boundary conditions\\u000a have been proposed. Viriuex and Madariaga (1982)

Takashi Miyatake; Takeshi Kimura

2006-01-01

376

Improvement in the Fault Boundary Conditions for a Staggered Grid Finite-difference Method  

Microsoft Academic Search

The staggered grid finite-difference method is a powerful tool in seismology and is commonly used to study earthquake source\\u000a dynamics. In the staggered grid finite-difference method stress and particle velocity components are calculated at different\\u000a grid points, and a faulting problem is a mixed boundary problem, therefore different implementations of fault boundary conditions\\u000a have been proposed. (1982) chose the shear

Takashi Miyatake; Takeshi Kimura

377

Fault detection in digital and analog circuits using an i(DD) temporal analysis technique  

NASA Technical Reports Server (NTRS)

An i(sub DD) temporal analysis technique which is used to detect defects (faults) and fabrication variations in both digital and analog IC's by pulsing the power supply rails and analyzing the temporal data obtained from the resulting transient rail currents is presented. A simple bias voltage is required for all the inputs, to excite the defects. Data from hardware tests supporting this technique are presented.

Beasley, J.; Magallanes, D.; Vridhagiri, A.; Ramamurthy, Hema; Deyong, Mark

1993-01-01

378

Integrated vs decoupled fault detection filter & flight control law designs for a re-entry vehicle  

Microsoft Academic Search

An integrated design of a robust fault detection filter and control system for a re-entry vehicle is presented. The integrated architecture is based on the four-block Youla parametrization which allows to better and directly trade-off filter and control design objectives in the face of disturbances and uncertainties. Hinfin -optimization techniques are used to design the integrated controller\\/filter system for a

Helena Castro; Samir Bennani; Andres Marcos

2006-01-01

379

Similarity-based modeling of vibration features for fault detection and identification  

Microsoft Academic Search

Purpose – To provide an overview of the similarity-based modeling (SBM) technology and review its application to condition monitoring of rotating equipment using features calculated from vibration sensor signals. Design\\/methodology\\/approach – Concentrates on the practical capabilities and underlying technology of SBM. Examines the effectiveness of it as an approach to detect and diagnose faults in an electric motor-driven shaft during

Stephan Wegerich

2005-01-01

380

Effects of time-varying loads on rotor fault detection in induction machines  

Microsoft Academic Search

The authors address the problem of motor current spectral analysis for the detection of nonidealities in the airgap flux density in the presence of an oscillation or position-varying load torque. An analysis of the effects of position-varying loads on the current harmonic spectrum is presented. The load torque-induced harmonics are shown to be coincidental with rotor fault-induced harmonics when the

Randy R. Schoen; Thomas G. Habetler

1993-01-01

381

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

382

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

383

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

384

An analysis and discussion of the voltage and current spectrum of claw-pole alternators for fault detection purposes  

Microsoft Academic Search

The 'claw-pole' type synchronous alternator is the heart of virtually all automotive Electric Power Generation and Storage (EPGS) system. Timely and accurate detection of alternator faults will not only decrease \\

Siwei Cheng; Thomas G. Habetler

2011-01-01

385

New close-region detection method using region growing  

NASA Astrophysics Data System (ADS)

A new detecting algorithm for close region, which has rectangle or parallelogram shape (e.g. airfield track), is developed in this paper. The traditional detecting algorithms for this kind of close region have some faults: long operating time and high demand for image quality. Mainly based on gray level shifting characteristic and size characteristic of close region, this proposed detecting algorithm for close region is not needed to extract line and search parallel lines. In this algorithm, a new terminology-edge dot couple, which is used as parameter of close region detection, is expressed and the method to extract it is described. A new technology-region growing, which use edge dot couple as growing base, is developed to search out close region. The author applies this algorithm to detect airfield track. The experiment result shows that this method is good for the close region detection.

Tu, Dan; Yan, Hong; Shen, Zhenkang

1997-10-01

386

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

387

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

NASA Astrophysics Data System (ADS)

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

Zeng, Hongqing; Vukovic, Alex; Huang, Changcheng

2005-09-01

388

New fault location system for power transmission lines using composite fiber-optic overhead ground wire (OPGW)  

Microsoft Academic Search

A new fault location (FL) method using composite fiber-optic overhead ground wires (OPGWs) is developed to find out where electrical faults occur on overhead power transmission lines. This method locates the fault section by detecting the current induced in the ground wire (GW), i.e. OPGW in this system. Since detected fault information is essentially uncertain, the new FL method treats

K. Urasawa; K. Kanemaru; S. Toyota; K. Sugiyama

1989-01-01

389

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.

2014-05-01

390

Fault/fracture density and mineralization: a contouring method for targeting in gold exploration  

NASA Astrophysics Data System (ADS)

A widely observed correlation between high fracture density and mineralization throughout terranes and geological time indicates a fundamental underlying ore-forming process. In Archaean greenstone-hosted deposits, high-density fracturing was accompanied by enhanced fluid flow during fault/fracture network development, producing regional-scale fluid pressure gradients that focussed hydrothermal fluids into preferentially fractured areas. Fracture density is both increased and decreased during faulting and fault healing, and fracture density accumulates over time, in zones of high palaeo-fluid flow. Localised zones where the density of fracturing is increased by deformation, become permeability nodes for migrating hydrothermal fluids leading to large zones of alteration and gold precipitation. The Ora Banda mining centre in Western Australia contains significant gold deposits that appear to demonstrate a close association between high-density fracturing and gold precipitation. Fracture density in the Ora Banda mines was enhanced by fault-fault intersections, fault-contact intersections and changes in fault geometry. The mine-scale relationships between fracture density and gold mineralization are repeated at smaller and larger scales, hence these relationships may be used in targeting for gold exploration. Contouring the density of fracturing in a region provides a semi-quantitative way to rank areas for exploration and uses data from mapping, drilling and high-quality geophysical data as a basis for analyses. Fracture density contouring is complementary to other prospectivity-analysis methods.

Tripp, Gerard I.; Vearncombe, Julian R.

2004-06-01

391

A Novel Method for the Diagnosis of the Incipient Faults in Analog Circuits Based on LDA and HMM  

Microsoft Academic Search

Diagnosis of incipient faults for electronic systems, especially for analog circuits, is very important, yet very difficult.\\u000a The methods reported in the literature are only effective on hard faults, i.e., short-circuit or open-circuit of the components.\\u000a For a soft fault, the fault can only be diagnosed under the occurrence of large variation of component parameters. In this\\u000a paper, a novel

Lijia Xu; Jianguo Huang; Houjun Wang; Bing Long

2010-01-01

392

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) [1614 NW. 106th St., Vancouver, WA 98665

1986-01-01

393

Application of the EEMD method to rotor fault diagnosis of rotating machinery  

NASA Astrophysics Data System (ADS)

Empirical mode decomposition (EMD) is a self-adaptive analysis method for nonlinear and non-stationary signals. It may decompose a complicated signal into a collection of intrinsic mode functions (IMFs) based on the local characteristic time scale of the signal. The EMD method has attracted considerable attention and been widely applied to fault diagnosis of rotating machinery recently. However, it cannot reveal the signal characteristic information accurately because of the problem of mode mixing. To alleviate the mode mixing problem occurring in EMD, ensemble empirical mode decomposition (EEMD) is presented. With EEMD, the components with truly physical meaning can be extracted from the signal. Utilizing the advantage of EEMD, this paper proposes a new EEMD-based method for fault diagnosis of rotating machinery. First, a simulation signal is used to test the performance of the method based on EEMD. Then, the proposed method is applied to rub-impact fault diagnosis of a power generator and early rub-impact fault diagnosis of a heavy oil catalytic cracking machine set. Finally, by comparing its application results with those of the EMD method, the superiority of the proposed method based on EEMD is demonstrated in extracting fault characteristic information of rotating machinery.

Lei, Yaguo; He, Zhengjia; Zi, Yanyang

2009-05-01

394

Fault Diagnosis on Multiple Fault Models by Using Pass/Fail Information  

NASA Astrophysics Data System (ADS)

In general, we do not know which fault model can explain the cause of the faulty values at the primary outputs in a circuit under test before starting diagnosis. Moreover, under Built-In Self Test (BIST) environment, it is difficult to know which primary output has a faulty value on the application of a failing test pattern. In this paper, we propose an effective diagnosis method on multiple fault models, based on only pass/fail information on the applied test patterns. The proposed method deduces both the fault model and the fault location based on the number of detections for the single stuck-at fault at each line, by performing single stuck-at fault simulation with both passing and failing test patterns. To improve the ability of fault diagnosis, our method uses the logic values of lines and the condition whether the stuck-at faults at the lines are detected or not by passing and failing test patterns. Experimental results show that our method can accurately identify the fault models (stuck-at fault model, AND/OR bridging fault model, dominance bridging fault model, or open fault model) for 90% faulty circuits and that the faulty sites are located within two candidate faults.

Takamatsu, Yuzo; Takahashi, Hiroshi; Higami, Yoshinobu; Aikyo, Takashi; Yamazaki, Koji

395

Wire detecting apparatus and method  

Microsoft Academic Search

This invention is comprised of an apparatus and method that combines a signal generator and a passive signal receiver to detect and record the path of partially or completely concealed electrical wiring without disturbing the concealing surface. The signal generator applies a series of electrical pulses to the selected wiring of interest. The applied pulses create a magnetic field about

Kronberg

1991-01-01

396

Hybrid Latent Nesting Method: A fault diagnosis case study in the wind turbine subsets  

Microsoft Academic Search

This paper describes the formalization and use of Latent Nesting Method (LNM) using Coloured Petri Nets (CPNs) for fault diagnosis and recovery in hybrid and com- plex systems. The method presented here will expand the initial proposed using Hybrid Petri Nets (HPNs) for adding the continuous dynamic. This method is illustrated with a comprehensive example of a lubrication and cooling

Leonardo Rodriguez U; Emilio Garcia M; Francisco Morant A; Antonio Correcher S

2011-01-01

397

Application of an RF Biased Langmuir Probe to Etch Reactor Chamber Matching, Fault Detection and Process Control  

NASA Astrophysics Data System (ADS)

Semiconductor device manufacturing typically occurs in an environment of both increasing equipment costs and per unit sale price shrinkage. Profitability in such a conflicted economic environment depends critically on yield, throughput and cost-of-ownership. This has resulted in increasing interest in improved fault detection, process diagnosis, and advanced process control. Achieving advances in these areas requires an integrated understanding of the basic physical principles driving the processes of interest and the realities of commercial manufacturing. Following this trend, this work examines the usefulness of an RF-biased planar Langmuir probe^1. This method delivers precise real-time (10 Hz) measurements of ion flux and tail weighted electron temperature. However, it is also mechanically non-intrusive, reliable and insensitive to contamination and deposition on the probe. Since the measured parameters are closely related to physical processes occurring at the wafer-plasma interface, significant improvements in process control, chamber matching and fault detection are achieved. Examples illustrating the improvements possible will be given. ^1J.P. Booth, N. St. J. Braithwaite, A. Goodyear and P. Barroy, Rev.Sci.Inst., Vol.71, No.7, July 2000, pgs. 2722-2727.

Keil, Douglas; Booth, Jean-Paul; Benjamin, Neil; Thorgrimsson, Chris; Brooks, Mitchell; Nagai, Mikio; Albarede, Luc; Kim, Jung

2008-10-01

398

Estimating the detectability of faults in 3D-seismic data - A valuable input to Induced Seismic Hazard Assessment (ISHA)  

NASA Astrophysics Data System (ADS)

In the past several years, some geotechnical operations that inject fluid into the deep subsurface, such as oil and gas development, waste disposal, and geothermal energy development, have been found or suspected to cause small to moderate sized earthquakes. In several cases the largest events occurred on previously unmapped faults, within or in close vicinity to the operated reservoirs. The obvious conclusion drawn from this finding, also expressed in most recently published best practice guidelines and recommendations, is to avoid injecting into faults. Yet, how certain can we be that all faults relevant to induced seismic hazard have been identified, even around well studied sites? Here we present a probabilistic approach to assess the capability of detecting faults by means of 3D seismic imaging. First, we populate a model reservoir with seed faults of random orientation and slip direction. Drawing random samples from a Gutenberg-Richter distribution, each seed fault is assigned a magnitude and corresponding size using standard scaling relations based on a circular rupture model. We then compute the minimum resolution of a 3D seismic survey for given acquisition parameters and frequency bandwidth. Assuming a random distribution of medium properties and distribution of image frequencies, we obtain a probability that a fault of a given size is detected, or respectively overlooked, by the 3D seismic. Weighting the initial Gutenberg-Richter fault size distribution with the probability of imaging a fault, we obtain a modified fault size distribution in the imaged volume from which we can constrain the maximum magnitude to be considered in the seismic hazard assessment of the operation. We can further quantify the value of information associated with the seismic image by comparing the expected insured value loss between the image-weighted and the unweighted hazard estimates.

Goertz, A.; Kraft, T.; Wiemer, S.; Spada, M.

2012-12-01

399

The Enhancement of Impulsive Noise and Vibration Signals for Fault Detection in Rotating and Reciprocating Machinery  

NASA Astrophysics Data System (ADS)

Impulsive sound and vibration signals in machinery are often caused by the impacting of components and are commonly associated with faults. It has long been recognized that these signals can be gainfully used for fault detection. However, it tends to be difficult to make objective measurements of impulsive signals because of the high levels of background noise. This paper presents an enhancement scheme to aid the measurement and characterization of such impulsive sounds, called a two-stage Adaptive Line Enhancer (ALE), which exploits two adaptive filter structures in series. The resulting enhancer signals are analyzed in the time-frequency domain to obtain simultaneous spectral and temporal information. In order to apply the two-stage ALE successfully, the filter parameters and adaptive algorithms should be chosen carefully. Conditions for the choice of these parameters are presented and suggestions are made for suitable adaptive algorithms. Finally, the techniques developed are applied to the diagnosis of faults within an internal combustion engine and to data from an industrial gearbox.

Lee, S. K.; White, P. R.

1998-10-01

400

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

401

Fout-Tolerante Computersystem een Overzicht van Enkele Methoden en Technieken (Fault-Tolerant Computer Systems: A Survey of Some Methods and Techniques).  

National Technical Information Service (NTIS)

A global survey of methods and techniques for the realization of fault tolerance using multiprocessor systems is given. The reliability of systems, the profits and costs, error detection and error recovery, redundancy in a system, and repairable and non-r...

L. J. M. Nieuwenhuis

1988-01-01

402

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.

Andrews, Lowell B. (2181-13th Ave. SW., Largo, FL 34640)

1998-01-01

403

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

404

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

NASA Technical Reports Server (NTRS)

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

Smyth, Padhraic

1994-01-01

405

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

406

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

NASA Technical Reports Server (NTRS)

This paper summarizes the modifications made 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. 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 an update frequency, are also presented.

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

1986-01-01

407

Evaluation of a dual processor implementation for a fault inferring nonlinear detection system  

NASA Technical Reports Server (NTRS)

The design of a modified fault inferring nonlinear detection system (FINDS) algorithm for a dual-processor configured flight computer is described. The algorithm was changed in order to divide it into its translational dynamics and rotational kinematics and to use it for parallel execution on the flight computer. The FINDS consists of: (1) a no-fail filter (NFF), (2) a set of test-of-mean detection tests, (3) a bank of first order filters to estimate failure levels in individual sensors, and (4) a decision function. NFF filter performance using flight recorded sensor data is analyzed using a filter autoinitialization routine. The failure detection and isolation capability of the partitioned algorithm is evaluated. A multirate implementation for the bias-free and bias filter gain and covariance matrices is discussed.

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

1987-01-01

408

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

409

Application of time–frequency entropy method based on Hilbert–Huang transform to gear fault diagnosis  

Microsoft Academic Search

When faults occur in the gear, energy distribution of gear vibration signals measured in time–frequency plane would be different from the distribution under the normal state. Therefore, it is possible to detect a fault by comparing the energy distribution of gear vibration signals with and without fault conditions. Hilbert–Huang transform can offer a complete and accurate energy–frequency–time distribution. On the

Dejie Yu; Yu Yang; Junsheng Cheng

2007-01-01

410

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

Microsoft Academic Search

This paper deals with fault detection and isolation (FDI) in sensors applied to a concentric-pipe counter-flow heat exchanger. The proposed FDI is based on the analytical redundancy implementing nonlinear high-gain observers which are used to generate residuals when a sensor fault is presented (as software sensors). By evaluating the generated residual, it is possible to switch between the sensor and

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

2011-01-01

411

Detecting temporal changes around the Parkfield section of the San Andreas Fault associated with large teleseismic earthquakes  

Microsoft Academic Search

Detecting temporal changes in fault zone properties at seismogenic depth has been a long-sought goal in the seismological community for many decades. Recent studies based on waveform analysis of repeating earthquakes have found clear temporal changes in the shallow crust and around active fault zones associated with the occurrences of large nearby (e.g, Peng and Ben-Zion, PAGEOPH, 2006) and teleseismic

P. Zhao; Z. Peng; K. G. Sabra

2009-01-01

412

Fault-tolerant automatic routing method with two photorefractive double phase conjugate mirrors  

Microsoft Academic Search

We propose a fault-tolerant automatic routing method with two photorefractive double phase conjugate mirrors for a free space optical communication. This method offers automatic routing of a signal beam from the main line to the backup line for the cutoff of the main line by obstacles. The link between the transmitter and the receiver is kept efficiently without any complex

Hayato Kato; Atsushi Okamoto; Masatoshi Bunsen

2003-01-01

413

Hybrid Method to Assess Sensitive Process Interruption Costs Due to Faults in Electric Power Distribution Networks  

Microsoft Academic Search

This paper shows a new hybrid method for risk assessment regarding interruptions in sensitive processes due to faults in electric power distribution systems. This method determines indices related to long duration interruptions and short duration voltage variations (SDVV), such as voltage sags and swells in each customer supplied by the distribution network. Frequency of such occurrences and their impact on

Juan C. Cebrian; Nelson Kagan

2010-01-01

414

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

415

Natural roller bearing fault detection by angular measurement of true instantaneous angular speed  

NASA Astrophysics Data System (ADS)

The challenge in many production activities involving large mechanical devices like power transmissions consists in reducing the machine downtime, in managing repairs and in improving operating time. Most online monitoring systems are based on conventional vibration measurement devices for gear transmissions or bearings in mechanical components. In this paper, we propose an alternative way of bearing condition monitoring based on the instantaneous angular speed measurement. By the help of a large experimental investigation on two different applications, we prove that localized faults like pitting in bearing generate small angular speed fluctuations which are measurable with optical or magnetic encoders. We also emphasize the benefits of measuring instantaneous angular speed with the pulse timing method through an implicit angular sampling which ensures insensitivity to speed fluctuation. A wide range of operating conditions have been tested for the two applications with varying speed, load, external excitations, gear ratio, etc. The tests performed on an automotive gearbox or on actual operating vehicle wheels also establish the robustness of the proposed methodology. By the means of a conventional Fourier transform, angular frequency channels kinematically related to the fault periodicity show significant magnitude differences related to the damage severity. Sideband effects are evidently seen when the fault is located on rotating parts of the bearing due to load modulation. Additionally, slip effects are also suspected to be at the origin of enlargement of spectrum peaks in the case of double row bearings loaded in a pure radial direction.

Renaudin, L.; Bonnardot, F.; Musy, O.; Doray, J. B.; Rémond, D.

2010-10-01

416

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

417

Performance analysis of a fault inferring nonlinear detection system algorithm with integrated avionics flight data  

NASA Technical Reports Server (NTRS)

This paper presents the performance analysis results of a fault inferring nonlinear detection system (FINDS) using integrated avionics sensor flight data for the NASA ATOPS B-737 aircraft in a Microwave Landing System (MLS) environment. First, an overview of the FINDS algorithm structure is given. Then, aircraft state estimate time histories and statistics for the flight data sensors are discussed. This is followed by an explanation of modifications made to the detection and decision functions in FINDS to improve false alarm and failure detection performance. Next, the failure detection and false alarm performance of the FINDS algorithm are analyzed by injecting bias failures into fourteen sensor outputs over six repetitive runs of the five minutes of flight data. Results indicate that the detection speed, failure level estimation, and false alarm performance show a marked improvement over the previously reported simulation runs. In agreement with earlier results, detection speed is faster for filter measurement sensors such as MLS than for filter input sensors such as flight control accelerometers. Finally, the progress in modifications of the FINDS algorithm design to accommodate flight computer constraints is discussed.

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

1985-01-01

418

Evaluation of chiller modeling approaches and their usability for fault detection  

SciTech Connect

Selecting the model is an important and essential step in model based fault detection and diagnosis (FDD). Several factors must be considered in model evaluation, including accuracy, training data requirements, calibration effort, generality, and computational requirements. All modeling approaches fall somewhere between pure first-principles models, and empirical models. The objective of this study was to evaluate different modeling approaches for their applicability to model based FDD of vapor compression air conditioning units, which are commonly known as chillers. Three different models were studied: two are based on first-principles and the third is empirical in nature. The first-principles models are 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. The DOE-2 chiller model as implemented in CoolTools{trademark} was selected for the empirical category. The models were compared in terms of their ability to reproduce the observed performance of an older chiller operating in a commercial building, and a newer chiller in a laboratory. The DOE-2 and Gordon-Ng models were calibrated by linear regression, while a direct-search method was used to calibrate the Toolkit model. The ''CoolTools'' package contains a library of calibrated DOE-2 curves for a variety of different chillers, and was used to calibrate the building chiller to the DOE-2 model. 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

2001-05-01

419

Bacteria detection instrument and method  

NASA Technical Reports Server (NTRS)

A method and apparatus for screening a sample fluid for bacterial presence are disclosed wherein the fluid sample is mixed with culture media of sufficient quantity to permit bacterial growth in order to obtain a test solution. The concentration of oxygen dissolved in the test solution is then monitored using the potential difference between a reference electrode and a noble metal electrode which are in contact with the test solution. The change in oxygen concentration which occurs during a period of time as indicated by the electrode potential difference is compared with a detection criterion which exceeds the change which would occur absent bacteria.

Renner, W.; Fealey, R. D. (inventors)

1972-01-01

420

Detecting seismogenic stress evolution and constraining fault zone rheology in the San Andreas Fault following the 2004 Parkfield earthquake  

Microsoft Academic Search

We investigate temporal changes in seismic scatterer properties at seismogenic depth attributed to the 2004 M 6 Parkfield earthquake, making use of the San Andreas Fault Observatory at Depth repeating-earthquake target sequences, as well as nearby similar-earthquake aftershock clusters. We use a two-step process: (1) observing temporal variations in the decorrelation index, D(t), reflecting changes in the scattered wavefield of

Taka'aki Taira; Paul G. Silver; Fenglin Niu; Robert M. Nadeau

2008-01-01

421

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

422

Fault section detection system for 66-kV underground branch transmission lines using optical magnetic field sensors  

SciTech Connect

This paper reports on a fault section detection system, which uses optical magnetic field sensors and instantly detects the section in which a ground fault occurred, that was developed for 66-kV underground multi-terminal systems having Y-branch joint boxes. The optical magnetic field sensor, which is based on Faraday effect in Bi-doped YIG ((BiYbGd){sub 3}Fe{sub 5}O{sub 12}) having a large verdet constant, detects cable conductor currents of 0 to 2000 A at high precision with the use of a laminated magnetic ring core of silicon steel plates. Sensors and a fault section detector/indicator of a system are connected with optical fibers capable of non-repeated transmission of over 6 km.

Katsuta, G.; Muraoka, K. (Tokyo Electric Power Co., Inc., Tokyo (JP)); Inoue, N.; Sakai, S.; Tsunekage, T.; Ando, K. (Mitsubishi Cable Industries, Ltd., Tokyo (JP))

1992-01-01

423

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

424

Research on Method of Fault Diagnosis about Vehicle Wiper DC Motor  

Microsoft Academic Search

Based on the urgent needs of some domestic manufacturers of vehicle motor, this paper studies the generating mechanism of types of faults of wiper DC motors. A new method that extracting the speed signal from the cepstrum of vibration signal is proposed. It is compared that the advantages and disadvantages of the two time-frequency analysis -- short-time Fourier analysis and

Kaihua Yang; Bing Yan; Chuanbing Li; Yingfeng Lei; Guowang Dou

2012-01-01

425

A novel condenser fault diagnosis method based on KPCA and multiclass SVMs  

Microsoft Academic Search

A novel fault diagnosis method of condenser based on kernel principle component analysis (KPCA) and multi-class support vector machines (MSVMs) is proposed in this paper. KPCA is applied to MSVMs for feature extraction. It firstly maps data from the original input space into high dimensional feature space via nonlinear kernel function and then extract optimal feature vector as the inputs

Tao Wang; Xiaoxia Wang

2010-01-01

426

A steam turbine-generator vibration fault diagnosis method based on rough set  

Microsoft Academic Search

According to turbine-generator vibration characteristic spectrum, a discretized generator fault attribute decision table and condition. attribute set reduction method based on rough set theory are presented in this paper, though the key character which influences classifying is picked up. BP network input dimension is reduced and training time is saved. Experiment shows that the result is effective.

Ou Jian; Sun Cai-xin; Bi Weimin; Zhang Bide; Liao Ruijin

2002-01-01

427

A new electromagnetic transient simulation method for faults in complex power system  

Microsoft Academic Search

The study of the digital simulation of electromagnetic transients has been an everlasting issue in power systems. Especially, after improvement by Dommel, the time-domain Bergeron model has been successfully applied in EMTP. But the pre-processing before simulating transients caused by various faults and operations are quite troublesome. This paper presents a new electromagnetic transients simulation method which can be generally

Shu Hongchun; Si Dajun; Chen Xueyun

2002-01-01

428

A Method for Fault Classification in Transmission Lines Based on ANN and Wavelet Coefficients Energy  

Microsoft Academic Search

This paper proposes a novel method for transmission lines fault classification using oscillographic data. The scheme is based on the analysis of the current wavelet coefficients energy using an artificial neural network. In order to validate the proposed approach, both simulated and actual oscillographic data were used.

Flavio Bezerra Costa; Kleber Melo Silva; Benemar Alencar Souza; Karcius Marcelus Colaco Dantas; Nubia Silva Dantas Brito

2006-01-01

429

Acoustic detection of gas emissions within the submerged section of the North Anatolian Fault Zone in the Sea of Marmara  

NASA Astrophysics Data System (ADS)

The 38 kHz, single beam, echo-sounder SIMRAD EK-60 was operated during the Marnaut cruise (May-June 2007) onboard the RV L'Atalante to detect acoustic anomalies related to the presence of gas bubbles in the water column. In the south Cinarcik Basin, strong acoustic anomalies have been found along N140 normal faults within a 3 km wide swath oriented N100. The swath trend corresponds to the orientation of a buried fault system identified in MCS data (Carton and Singh, 2007). Ground-truthing of these anomalies with Nautile submersible enables the founding of gas seeps and bubbles emissions at seafloor. Acoustic anomalies are apparently weaker on the main fault scarp on the northern side of the Cinarcik Basin. In the Central High and Kumburgaz Basin, no acoustic anomalies were detected along the main fault trace. Instead, a cluster with very strong amplitude anomalies was identified at about 1 km away from the fault, on top of a broad anticline. On the Western High, a cluster of acoustic anomalies characterizes the top of an anticline located near 40°49'N, 28°46.8'E, where shallow gas hydrates have been sampled at unexpected water depth of 660 m, well outside the methane hydrate stability field. In the Tekirdag and Central basins, EK-60 lines were implemented along the fault scarps and the acoustic records indicate the presence of gas seeps at fault escarpments. This new set of data confirms previous results obtained with RV Le Suroit in September 2000 with a 112 kHz side-scan sonar towed 200 m above seafloor. Most active sites identified in 2000 were still active in 2007. We note that the only place where no acoustic anomaly was found on the main fault trace corresponds to the Central High and Kumburgaz Basin area. This segment did not rupture during the last century.

Géli, L.; Henry, P.; Dupré, S.; Voelker, D.; Zitter, T.; Le Pichon, X.; Tryon, M.; Cagatay, N.; Shipboard Science Party, M.

2007-12-01

430

Mine geophysics methods in studying the coal bearing rock mass condition in low magnitude tectonic fault zones  

NASA Astrophysics Data System (ADS)

Disjunctive type tectonic faults are quite serious problem at underground coal winning. In the fault adjacent areas both coal seam and coal bearing rocks are usually essentially fractured that makes them less stable in coalfaces at underground mining. Some researchers have pointed out to enhanced stress state in these areas as well provided that loosening zones are absent. Coal seams are mostly inclined to disjunctive faults in Central region of Donets Coal Basin where tectonic processes were very intense. There are a lot of small faults with magnitudes close to seam thickness about 2 m in this region along with large thrust or fault disjunctives with stratigraphic magnitudes over 10 m (Dyleyev, Northern, Brunvald, Bulavin faults and others). Highest disjunctive dislocation is typical for coalfields near mines "Toretskaya" and "Novodzerzhinskaya", Coal Production Co. "Dzerzhinskugol", where dislocation density reaches about 8.5 faults per 1 km across the field. Small disjunctive faults often coincide with sites of sudden coal and gas outbursts, longwall inrushes, and poor support condition in development workings. It is known that affected zones on either side accommodate each disjunctive fault, these zones being distinctive for increased fissuring, higher stresses, coal and rocks differing strength. Affected zone width dependence on the fault parameters was determined using geological approach. Mine electrical survey and acoustical probing methods were used to study rock mass faulted condition in the vicinity of development workings and stopes intercepting low magnitude (below 5 m) disjunctive faults in coal field of mine "Toretskaya". These findings have allowed to establish a new fault magnitude dependence of rupture tectonic dislocation's affected zone width in the form of B = 3.2 H, where B is dislocation's affected zone width (m); H is the dislocation's stratigraphic magnitude (m). It was established as well that stress level in rock mass near disjunctive fault is 2 to 2.5 times higher than in undisturbed rock mass.

Alexeev, A. D.; Zhitlyonok, D. M.; Pitalenko, E. I.

2003-04-01

431

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

432

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

433

Model based approach in fault detection and diagnosis for DC motor  

Microsoft Academic Search

? Abstract -- Recent advances in microelectronic circuit have enabled the application of process diagnostics to a variety of systems to improve performances and the reliability. Failure detection and isolation strategies monitor a system for degradations and if detected, classify the failure source. One of the most important methods for failure detection and diagnosis is the analysis of the variations

P. Dobra; M. Trusca; I. V. Sita; R. A. Munteanu; M. Munteanu

2011-01-01

434

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

435

Methodology for validation of safety parameters and fault detection and isolation  

SciTech Connect

In this paper a methodology for instrument data validation as well as fault detection and isolation, based on analytic redundancy, is presented. This work differs from previously reported work on analytic redundancy in that validation of all the main parameters of the plant heat transport loops is sought by using plant-wide instrument information. An LMFBR plant is used as a reference, and validation of the following plant parameters is considered: reactor power (Q), reactor inlet (T/sub IC/) and reactor outlet (T/sub OC/) coolant temperatures, intermediate heat exchanger (IHX) inlet (T/sub IS/) and outlet (T/sub OS/) secondary coolant temperatures, steam generator feedwater temperature (T/sub w/), steam temperature (T/sub s/) and pressure (P/sub s/), as well as primary (G/sub p/), intermediate (G/sub I/), and feedwater (G/sub w/) flow. In this paper, only validation at steady state conditions will be discussed.

Tzanos, C.P.

1984-01-01

436

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

437

Fault-tolerant quantum computation with a soft-decision decoder for error correction and detection by teleportation.  

PubMed

Fault-tolerant quantum computation with quantum error-correcting codes has been considerably developed over the past decade. However, there are still difficult issues, particularly on the resource requirement. For further improvement of fault-tolerant quantum computation, here we propose a soft-decision decoder for quantum error correction and detection by teleportation. This decoder can achieve almost optimal performance for the depolarizing channel. Applying this decoder to Knill's C4/C6 scheme for fault-tolerant quantum computation, which is one of the best schemes so far and relies heavily on error correction and detection by teleportation, we dramatically improve its performance. This leads to substantial reduction of resources. PMID:23784512

Goto, Hayato; Uchikawa, Hironori

2013-01-01

438

Robust observer-based fault diagnosis for an unmanned aerial vehicle  

Microsoft Academic Search

In this paper, a new robust fault detection and isolation (FDI) methodology for an unmanned aerial vehicle (UAV) is proposed. The fault diagnosis scheme is constructed based on observer-based techniques according to fault models corresponding to each component (actuator, sensor, and struc- ture). The proposed fault diagnosis method takes advantage of the structural perturbation of the UAV model due to

M. M. Tousi; K. Khorasani

2011-01-01

439

Fault detection algorithms for real-time diagnosis in large-scale systems  

NASA Astrophysics Data System (ADS)

In this paper, we present a review of different real-time capable algorithms to detect and isolate component failures in large-scale systems in the presence of inaccurate test results. A sequence of imperfect test results (as a row vector of 1's and 0's) are available to the algorithms. In this case, the problem is to recover the uncorrupted test result vector and match it to one of the rows in the test dictionary, which in turn will isolate the faults. In order to recover the uncorrupted test result vector, one needs the accuracy of each test. That is, its detection and false alarm probabilities are required. In this problem, their true values are not known and, therefore, have to be estimated online. Other major aspects in this problem are the large-scale nature and the real-time capability requirement. Test dictionaries of sizes up to 1000 x 1000 are to be handled. That is, results from 1000 tests measuring the state of 1000 components are available. However, at any time, only 10-20% of the test results are available. Then, the objective becomes the real-time fault diagnosis using incomplete and inaccurate test results with online estimation of test accuracies. It should also be noted that the test accuracies can vary with time --- one needs a mechanism to update them after processing each test result vector. Using Qualtech's TEAMS-RT (system simulation and real-time diagnosis tool), we test the performances of 1) TEAMS-RT's built-in diagnosis algorithm, 2) Hamming distance based diagnosis, 3) Maximum Likelihood based diagnosis, and 4) Hidden Markov Model based diagnosis.

Kirubarajan, Thiagalingam; Malepati, Venkatesh N.; Deb, Somnath; Ying, Jie

2001-07-01

440

Detection of combined faults in induction machines with stator parallel branches through the DWT of the startup current  

NASA Astrophysics Data System (ADS)

The main objective of this paper is to diagnose the presence of combined faults in induction machines. For this purpose, a methodology based on the application of the Discrete Wavelet Transform (DWT) to the stator startup current is used. This approach was applied in previous works with success to the diagnosis of rotor asymmetries and mixed eccentricities in motors with different sizes and conditions. However, as most of the diagnosis methods hitherto developed, the application of the proposed approach was circumscribed to situations in which a single fault was present in the machine. In addition, the influence of other phenomena such as load torque oscillations or voltage fluctuations was studied, but without considering the combination of these phenomena and the fault in the machine. This work is intended, first, to apply the proposed transient-based methodology to several cases in which different faults (rotor asymmetries, mixed eccentricities and inter-turn and inter-coil stator short-circuits) are simultaneously present in the machine and, second, to apply it to cases regarding faults combined with other phenomena making difficult the diagnosis, such as load torque oscillations. Interesting considerations regarding the preponderance of the effects of some of the faults are also done in the paper. The application of the methodology is focused on induction machines with stator parallel branches; in this sense, the suitability of the use either of the phase current or of the branch current for the diagnosis of each particular fault is analysed