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1

Sensor soft fault detection method of autonomous underwater vehicle  

Microsoft Academic Search

Operating in complex ocean environment, the condition monitoring and fault diagnosis of sensors have great impact on the safety of autonomous underwater vehicle (AUV). When the sensor soft fault of AUV is detected by the traditional method of observer based on the means of close-loop control and close-loop detection, the sensor measured value with fault information is fed into the

Mingjun Zhang; Juan Wu; Yujia Wang

2009-01-01

2

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

3

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

4

Detection of Induction Motor Faults: A Comparison of Stator Current, Vibration and Acoustic Methods  

Microsoft Academic Search

In this paper we present the comparison results of induction motor fault detection using stator current, vibration, and acoustic methods. A broken rotor bar fault and a combination of bearing faults (inner race, outer race, and rolling element faults) were induced into variable speed three-phase induction motors. Both healthy and faulty signatures were acquired under different speed and load conditions.

WEIDONG LI; CHRIS K. MECHEFSKE

2006-01-01

5

A Statistical, Rule-Based Fault Detection and Diagnostic Method for Vapor Compression Air Conditioners  

Microsoft Academic Search

This paper presents a method for automated detection and diagnosis of faults in vapor compression air conditioners that only requires temperature measurements, and one humidity measurement. The differences between measured thermodynamic states and predicted states obtained from models for normal performance (residuals) are used as performance indices for both fault detection and diagnosis. For fault detection, statistical properties of the

Todd M. Rossi; James E. Braun

1997-01-01

6

Applying Sampling Methods to Fault-Prone Module Detection  

Microsoft Academic Search

To improve the prediction performance of fault-proneness models, this paper experimentally evaluates the effect of over and under sampling methods, which are preprocessing procedures for a fit dataset. The sampling methods are expected to improve the prediction performance when the fit dataset is imbalanced, i.e. there exists a large bias between the number of fault- prone modules and the number

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

2007-01-01

7

Update of an Early Warning Fault Detection Method Using Artificial Intelligence Techniques  

Microsoft Academic Search

This presentation describes a research investigation to access the feasibility of using an Artificial Intelligence (AI) method to predict and detect faults at an early stage in power systems. An AI based detector has been developed to monitor and predict faults at an early stage on particular sections of power systems. The detector for this early warning fault detection device

K C P Wong; H M Ryan; J Tindle

1997-01-01

8

Network Fault Detection: Classifier Training Method for Anomaly Fault Detection in a Production Network Using Test Network Information  

Microsoft Academic Search

We have prototyped a hierarchical, multi-tier, multi-window, soft fault detection system, namely the Generalized Anomaly and Fault Threshold (GAFT) system, which uses statistical models and neural network based classifiers to detect anomalous network conditions. In installing and operating GAFT, while both normal and fault data may be available in a test network, only normal data may be routinely available in

Jun Li; Constantine N. Manikopoulos

2002-01-01

9

Solar system fault detection  

DOEpatents

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

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

1984-05-14

10

A new method for early fault detection and diagnosis of broken rotor bars  

Microsoft Academic Search

A new method has been developed for the detection and diagnosis of broken rotor bars faults in three-phase induction motors under no-load conditions. Early detection of faults is made by using a sliding window constructed by Hilbert transforms of one of the phases of the thee-phase currents and the size of a fault is diagnosed by motor current signature analysis

Ilhan Aydin; Mehmet Karakose; Erhan Akin

2011-01-01

11

A new fault detection and diagnosis method based on principal component analysis in multivariate continuous processes  

Microsoft Academic Search

The fault detection and diagnosis methods based on principal component analysis (PCA) have been developed widely because they need no detailed information about the process mechanism model and really can detect faults promptly. However the existing diagnosis algorithms such as expert systems or contribution plots, etc. still have some trouble when they are applied in real industrial processes, which leads

Yang Yinghua; Lu Ningyun; Wang Fuli; Ma Liling

2002-01-01

12

A Method for Residential Series Arc Fault Detection and Identification  

Microsoft Academic Search

Because of electrical problems such as aging cables and loose connections, arc faults occur. Generating high temperature and discharging molten metal, arc faults finally lead to electrical fires. Every year such fires bring great loss and damage. It is identified that conventional protecting technique is unable to break a circuit in the situation when a brief arc fault occurs and

Dongwei Li; Zhengxiang Song; Jianhua Wang; Yingsan Geng; Huilin Chen; Li Yu; Bo Liu

2009-01-01

13

A new fault detection method of conveyer belt based on machine vision  

NASA Astrophysics Data System (ADS)

A new fault detection and measurement method of conveyer belt based on machine vision is proposed. The conveyer belt used in coal mine transportation usually goes two kinds of faults: joint's elongation and local rust. Under this engineering background, the system focuses on detecting the state of conveyer belt and measuring the fault size. This paper brings forward a modified BP neural network to detect and classify different faults. The new BP algorithm's detecting speed is rapid, and the correct recognition rate of the joint and erosion has a great improvement. The measurements of joint's length and erosion's area are realized on the machine vision platform which built by LabVIEW IMAQ Vision module. And the measurements have a high accuracy. The results demonstrate that the new method is effective and efficiency.

Shen, Bingxia; Ma, Muyan; Leng, Junmin

2010-12-01

14

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

NASA Astrophysics Data System (ADS)

The Møre-Trøndelag Fault Complex (MTFC) is one of the most prominent fault complexes in Scandinavia and perhaps on Earth. The MTFC appears to have controlled the tectonic evolution of central Norway and its shelf for the past 400 Myr, at least, and has experienced repeated reactivation during Paleozoic (Devonian to Permian), Mesozoic (Jurassic) and Cenozoic times. Despite its pronounced signature in the landscape its deep structure has remained unresolved until now. We acquired multiple geophysical data sets across a segment of the MTFC composed of two main faults (i.e. the Tjellefjorden and Fannefjorden faults). The faults are partly exposed and their respective traces can be seen as prominent topographic escarpments. However their exact locations (i.e. below Quaternary sediments), extents and dips are less clear, and have not been studied systematically by geophysical methods. To detect the fault zones and their structural attributes, a series of magnetic, resistivity, shallow refraction and deep reflection seismics profiles were measured across these fault zones. In addition, 265 new gravity points have been established in a region of 4x4 km. Interpretation of the magnetic data shows the distinctive signature of near-vertical faults (~80°-85° towards the south), trending NNE-SSW. Quantitative interpretation of the data points to a width of 90 to 150 m for the Tjellefjorden Fault and 200 to 400 m for the Fannefjorden Fault. Inversion of 2D resistivity data reveals a three-layered subsurface until 130 m depth. The layers represent the thin low resistive topsoil underlain by weathered bedrock, and the resistive bedrock. Within the resistive bedrock distinct low resistivity zones can be observed, which can be associated with highly fractured bedrock. These low resistive zones correlate to low velocity zones in the shallow refraction profile. The aim of using deep reflection seismic was to image structures in the upper crust down to a depth of 4 km. Processing of the seismic data has been challenging. Reflections in the upper 3 km that can be correlated to strong topographic lineament on the surface have been found. The faults are expected to be steep and might therefore be difficult to image directly. Offsets in bedrock structure can then be used for tracing the faults at depth.

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

2009-12-01

15

An adaptive noise-cancellation method for detecting generalized roughness bearing faults under dynamic load conditions  

Microsoft Academic Search

This paper proposes an adaptive noise-cancellation (ANC) method for detecting incipient bearing faults, i.e., generalized roughness, with a special focus on dynamic motor operations, including variable-load and variable-frequency conditions. The correlated frequency components in the motor stator current are treated as ldquonoiserdquo to the bearing fault detection and estimated using an adaptive Wiener filter. These estimated noise components are then

Bin Lu; Michael Nowak; Stefan Grubic; Thomas G. Habetler

2009-01-01

16

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

2008-06-03

17

Fault Detection and Classification  

NASA Astrophysics Data System (ADS)

Plasma processes are used widely in the manufacture of semiconductor devices. Recent trends in this industry have focussed on methods for automated process control. For limiting processes such as plasma etch, an emerging focus is on real time Fault Detection and Classification (FDC). Simply put, the aim is to provide a system that not only detects faults but also identifies the root cause. For example, semiconductor production fabs regularly encounter faults that result in unscheduled tool downtime and reduced yield. Among these are real-time process and tool faults, post maintenance recovery problems and tool mis-matching at start-up and process transfer. The objective of any FDC scheme should be to reduce this product loss and tool downtime by identifying the core problem as rapidly as possible, and replace the usual "trial-and-error" approach to fault identification. There are a couple of key requirements in any control system. Firstly, an estimation of the process state, and secondly, a scheme for providing real-time control. This paper focuses on methods for addressing both problems on plasma etch tools. A non-intrusive high-resolution RF sensor is used to provide in situ process-state and tool-state data. Examples will be presented on how such a sensor can give a repeatable fingerprint of any plasma process. The challenge then becomes the manipulation of this data into usable information. The process control scheme presented is knowledge-based, in that it is trained and does not rely on statistical methods with underlying assumptions of Gaussian data spread. A fingerprint of known fault states is the knowledge set and real-time control is provided by comparison of the sensor fingerprint to the fault fingerprints.

Scanlan, John

2004-09-01

18

A Probabilistic Fault Detection Approach: Application to Bearing Fault Detection  

Microsoft Academic Search

This paper introduces a method to detect a fault associated with critical components\\/subsystems of an engineered system. It is required, in this case, to detect the fault condition as early as possible, with specified degree of confidence and a prescribed false alarm rate. Innovative features of the enabling technologies include a Bayesian estimation algorithm called par- ticle filtering, which employs

Bin Zhang; Chris Sconyers; Carl Byington; Romano Patrick; Marcos E. Orchard; George Vachtsevanos

2011-01-01

19

A High-Resolution Frequency Estimation Method for Three-Phase Induction Machine Fault Detection  

Microsoft Academic Search

Fault detection in alternating-current electrical machines that is based on frequency analysis of stator current has been the interest of many researchers. Several frequency estimation techniques have been developed and are used to help the induction machine fault detection and diagnosis. This paper presents a technique to improve the fault detection technique by using the classical multiple signal classification (MUSIC)

Shahin Hedayati Kia; Humberto Henao; Gérard-André Capolino

2007-01-01

20

A new vibration signal processing method for gearbox fault detection  

Microsoft Academic Search

In this paper, a new vibration signal processing method, an adaptive narrow-band interference cancellation is developed to remove the periodic signals and background noises from the vibration signals. Narrow-band interference cancellation techniques are widely applied in signal processing of communication systems to remove the narrow-band interferences. The vibration signals of a gearbox with a damaged gear tooth contain periodic signals

David He; Ruoyu Li

2011-01-01

21

A Self-organizing Map Method for Optical Fiber Fault Detection and Location  

Microsoft Academic Search

\\u000a As optical fiber is subject to faults, normal communication will be affected. An intelligent method of detection and location\\u000a for communication optical fiber is put forward in this paper. According to spatial characters of geographic distributing of\\u000a optical fiber network, nodes and links topo model of the network is built. Adopting the ANN algorithm in this paper, the nodes\\u000a are

Yi Chai; Wenzhou Dai; Maoyun Guo; Shangfu Li; Zhifen Zhang

2005-01-01

22

A subspace-based rejection method for detecting bearing fault in asynchronous motor  

Microsoft Academic Search

Fault detection and diagnosis of asynchronous machine is became a central problem for industrial domain since the past decade. A solution to tackle this problem is to use stator current for a great condition monitoring, as referred to the ldquoMCSArdquo (Motor Current Signal Analysis). Indeed, it is known that due to the motor structure, mechanical spectral signature fault, as for

Guillaume Bouleux; Ali Ibrahim; François Guillet; Rémy Boyer

2008-01-01

23

A New Bearing Fault Detection Method in Induction Machines Based on Instantaneous Power Factor  

Microsoft Academic Search

Fault detection and diagnosis of asynchronous machine has become a central problem in industry over the past decade. A solution to tackle this problem is to use stator current for a condition monitoring, referred to as motor current signature analysis. This paper argues that bearing faults would have a negligible effect on motor currents and instead argues that the more

Ali Ibrahim; Mohamed El Badaoui; FranÇois Guillet; FrÉdÉric Bonnardot

2008-01-01

24

A New Method for Node Fault Detection in Wireless Sensor Networks  

PubMed Central

Wireless sensor networks (WSNs) are an important tool for monitoring distributed remote environments. As one of the key technologies involved in WSNs, node fault detection is indispensable in most WSN applications. It is well known that the distributed fault detection (DFD) scheme checks out the failed nodes by exchanging data and mutually testing among neighbor nodes in this network., but the fault detection accuracy of a DFD scheme would decrease rapidly when the number of neighbor nodes to be diagnosed is small and the node's failure ratio is high. In this paper, an improved DFD scheme is proposed by defining new detection criteria. Simulation results demonstrate that the improved DFD scheme performs well in the above situation and can increase the fault detection accuracy greatly.

Jiang, Peng

2009-01-01

25

A Method of Fault Detection in Power System by using Multi-agent Approach  

NASA Astrophysics Data System (ADS)

In this paper, we propose a new decentralized multi-agent approach for detecting fault equipment in power system. The proposed method consists of several Substation agents (SSAGs), Distribution substations (DSAGs) and Line agents (LAGs). SSAG is installed each substation and controls its substation. DSAG is installed each distribution substation and receives instruction from SSAG or LAG. LAG is installed any substation and controls the transmission line. In order to demonstrate the capability of proposed multi-agent system, it has been applied to a model power system that has 7 substations and 8 distribution substations. The simulation results show that the proposed multi-agent approach is effective and promising.

Fukunaga, Shinnosuke; Nagata, Takeshi; Tani, Kazuhiro; Shimada, Ikuhiko

26

Solar system fault detection  

SciTech Connect

This patent describes an apparatus for detecting predetermined faults in a variety of active, different solar systems. Each of the different solar systems uses a heat transfer fluid and has a tank for receiving fluid or a heat exchanger to transfer heat from the heat transfer fluid to a tank, and at least one collector and one pipe through which fluid flows. The different solar systems each has different predetermined operating conditions associated with a given type of fault, comprising: a. sensing means for sensing the presence of different predetermined operating conditions associated with each of the solar systems. Each of the sensing means includes a switch that changes in state in response to a change in a predetermined operating condition in at least one of the fluid, tank or heat exchanger, collector, and pipe; b. means in communication with each of the sensing means for determining whether one or more predetermined faults have occurred in one of the solar systems, the means for determining including combining means. The combining means includes logic gates at least one of which is actuated by logic gate actuating voltages via the associated states of at least two of the switches to produce an output signal indicative of whether a predetermined fault is present in the one solar system; and c. indicating means responsive to the output signal for indicating the presence and identity of the one predetermined fault in the one solar system.

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

1986-12-02

27

Fault Detection and Identification Methods Used for the LHC Cryomagnets and Related Cabling  

Microsoft Academic Search

Several methods for electrical fault location have been developed and tested. As part of the electrical quality assurance program for the LHC, certain wires have to be subjected to a (high) DC voltage for the testing of the insulation. With the time difference of spark-induced electromagnetic signals measured with an oscilloscope, fault localization within ± 10 cm has been achieved.

D Bozzini; Friedhelm Caspers; V Chareyre; Y Duse; T Kroyer; R López; A Poncet; Stephan Russenschuck

2006-01-01

28

Intelligent High-Voltage Discharge Fault Detection and Its Diagnosis Methods Based on ANN  

Microsoft Academic Search

In order to prevent the harm of corona, the power sector needs to detect and analyze the fault of corona discharge. This paper put forward a single-channel structure corona detection system based on solar-blind UV detection technology, which is able to locate corona discharge effectively. And the absolute discharge area formula has been derived to quantify the corona discharge intensity.

Ru-jun Xu; Li-xin Ma; Bo Hu; He-ran Ma; Bo-hao Tao

2011-01-01

29

Row fault detection system  

SciTech Connect

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

30

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

31

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

32

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

33

Arc fault detection system  

DOEpatents

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

Jha, K.N.

1999-05-18

34

Game Theoretic Fault Detection Filter.  

National Technical Information Service (NTIS)

The fault detection process is modeled 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 ...

W. H. Chung J. L. Speyer

1995-01-01

35

Rotor Resistance Estimation of an Induction Motor to Detect Broken Bars Fault Using HH Method  

Microsoft Academic Search

This paper presents a new approach, using a new technique we have called “H-H method,” for on-line broken bars detection in induction motors based on rotor parameters estimation from reactive power processing. The hypothesis, on which the detection is based, is that the apparent rotor resistance increases when a rotor bar breaks. To detect broken bars, the processing of reactive

N. NAIT-SAID

2004-01-01

36

Intelligent Agents for Proactive Fault Detection  

Microsoft Academic Search

As the Internet becomes a critical component of our society, a key challenge is to maintain network availability and reliability. Intelligent processing agents that reside at network nodes use an adaptive learning method to detect abnormal network behavior before a fault actually occurs. In a test at Rensselaer Polytechnic Institute, an agent on a router detected a file server failure

Cynthia S. Hood; Chuanyi Ji

1998-01-01

37

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

NASA Astrophysics Data System (ADS)

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

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

1999-11-01

38

A system for incipient fault detection and fault diagnosis based on MCSA  

Microsoft Academic Search

The paper describes a system for automated detection of incipient faults in induction machines. The system has been based on the Motor Current Signature Analysis method (MCSA) and aimed to be applied in a thermal electric power plant in south Brazil. First, the mechanism of fault evolution is introduced and clarified regarding the most common induction motor faults: stator winding

Daniel da S. Gazzana; Luis Alberto Pereira; Denis Fernandes

2010-01-01

39

In-situ fault detection apparatus and method for an encased energy storing device  

DOEpatents

An apparatus and method for detecting a breach in an electrically insulating surface of an electrically conductive power system enclosure within which a number of series connected energy storing devices are disposed. The energy storing devices disposed in the enclosure are connected to a series power connection. A detector is coupled to the series connection and detects a change of state in a test signal derived from the series connected energy storing devices. The detector detects a breach in the insulating layer of the enclosure by detecting a state change in the test signal from a nominal state to a non-nominal state. A voltage detector detects a state change of the test signals from a nominal state, represented by a voltage of a selected end energy storing device, to a non-nominal state, represented by a voltage that substantially exceeds the voltage of the selected opposing end energy storing device. Alternatively, the detector may comprise a signal generator that produces the test signal as a time-varying or modulated test signal and injects the test signal into the series connection. The detector detects the state change of the time-varying or modulated test signal from a nominal state, represented by a signal substantially equivalent to the test signal, to a non-nominal state, representative by an absence of the test signal.

Hagen, Ronald A. (Stillwater, MN); Comte, Christophe (Montreal, CA); Knudson, Orlin B. (Vadnais Heights, MN); Rosenthal, Brian (Stillwater, MN); Rouillard, Jean (Saint-Luc, CA)

2000-01-01

40

All row, planar fault detection system  

DOEpatents

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

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

2013-07-23

41

Bisectional fault detection system  

SciTech Connect

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

42

A new method for grinder dressing fault mitigation using real-time peak detection  

Microsoft Academic Search

To facilitate the implementation of machine monitoring algorithms on the shop floor, signal processing and decision-making\\u000a strategies must be developed, which account for the difficulties associated with monitoring a machine in an industrial environment.\\u000a Therefore, this paper focuses on introducing a new method for dresser contact detection, which takes into account sensor and\\u000a data acquisition system costs, computational limitations of

Adam Brzezinski; Lin Li; Xianli Qiao; Jun Ni

2009-01-01

43

Detection of arcing faults on distribution feeders  

NASA Astrophysics Data System (ADS)

The problem of detecting high impedance faults is examined from the perspective of current utility protection practices and it is shown why conventional overcurrent protection systems may not detect such faults. A microcomputer based prototype of an arcing, high impedance fault detector was tested. The fault detection technique is based on an increase in the high frequency component of distribution feeder current caused by the arcing associated with many high impedance faults. This theory is supported by field data measurements and analysis of a large number of staged distribution primary faults and normal system conditions. The design and demonstration of the prototype is explained. The device successfully detected many faults of greater than 5 to 10 A on a typical distribution feeder without false trips. General application of this fault detection techniques is considered.

Russell, B. D.

1982-12-01

44

EXPERIMENTAL FAULT DETECTION AND ACCOMMODATION FOR AN AGRICULTURAL MOBILE ROBOT  

Microsoft Academic Search

This paper presents a systematic procedure to achieve fault tolerant capability for a four-wheel driven, four-wheel steered mobile robot moving in outdoor terrain. The procedure is exemplified through the paper by applying on a compass module. Detailed methods for fault detection and fault accommodation for the compass faults are discussed and the results are verified through field tests.Copyright c 2005

K. Østergaard; D. Vinther; M. Bisgaard; R. Izadi-Zamanabadi; J. D. Bendtsen

45

Fault Detection Effectiveness of Weighted Random Patterns  

Microsoft Academic Search

Performance results are given for use of a weighted random pattern test generator, WRP, on ten benchmark designs. Deterministic (DET) and WRP tests created for single stuck faults are compared in their ability to detect shorts and transition faults. The WRP is able to generate a test for all the single stuck faults detected with a state-of-the-art deterministic pattern generator;

John A. Waicukauski; Eric Lindbloom

1988-01-01

46

Fault detection schemes for a diesel engine turbocharger  

Microsoft Academic Search

In this paper two model based methods for real time fault detection of Diesel engine turbochargers are presented and compared. Fault detection schemes which are based on residual generation between the measured and some estimated process states require precise mathematical models of the process. One approach is utilizing parametric nonlinear dynamic models, whereas the other method uses artificial neural networks

C. Ludwig; M. Ayoubi

1995-01-01

47

Fault detection and diagnosis of rotating machinery  

Microsoft Academic Search

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

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

2000-01-01

48

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

2011-03-21

49

Signal Injection as a Fault Detection Technique  

PubMed Central

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

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

2011-01-01

50

A Statistical Method for the Detection of Sensor Abrupt Faults in Aircraft Control Systems  

Microsoft Academic Search

Aircraft sensors are important for proper operation and safety, and their condition is conventionally monitored based upon the hardware redundancy principle. In this work a statistical method capable of independently monitoring a single sensor, and thus enhancing reliability and overall system safety, is introduced. The method's main advantages are simplicity, applicability to a wide variety of aircraft operating conditions, the

Paraskevi A. Samara; George N. Fouskitakis; John S. Sakellariou; Spilios D. Fassois

2008-01-01

51

High impedance fault detection device tester  

Microsoft Academic Search

High impedance or down conductor fault detection devices are now commercially available for evaluation. However, security and dependability of these devices can not be tested using conventional relay test apparatus and procedures. This paper presents a test apparatus and procedures for testing high impedance fault detection devices. The apparatus is capable of playing back in real-time waveforms selected from a

V. L. Buchholz; M. Nagpal; J. B. Neilson; R. Parsi-Feraidoonian; W. Zarecki

1996-01-01

52

Fault detection in CMOS manufacturing using MBPCA  

NASA Astrophysics Data System (ADS)

This paper describes the application of model-based principal component analysis (MBPCA) to the identification and isolation of faults in CMOS manufacture. Some of the CMOS fabrication processing steps are well understood, with first principles mathematical models available which can describe the physical and chemical phenomena that takes place. The fabrication of the device using a known industrial process is therefore first modeled 'ideally', using ATHENA and MATLAB. Detailed furnace models are used to investigate the effect of errors in furnace control on the device fabrication and the subsequent effect on the device electrical properties. This models the distribution of device properties resulting from processing a stack of wafers in a furnace, and allows faults and production errors to be simulated for analysis. The analysis is performed using MBPCA. which has been shown to improve fault-detection resolution for batch processes. The diagnosis method is demonstrated on an industrial NMOS transistor fabrication process with faults introduced in places where they might realistically occur.

Lachman-Shalem, Sivan; Haimovitch, Nir; Shauly, Eitan N.; Lewin, Daniel R.

2000-08-01

53

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

54

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

55

Output-Only Techniques for Fault Detection  

NASA Astrophysics Data System (ADS)

Fault detection is relevant to many applications, including structural health monitoring and machine health monitoring. Furthermore, output measurement data may be the only information known about a system. Hence we develop and demonstrate techniques for output-only fault detection. We also investigate implementation issues, including computational complexity and output noise. First, we consider real-time detection of an abrupt change in a noisy signal. Existing techniques exhibit sensitivity to gradual (incipient) changes in the data, as well as detection delays, false alarms, and missed detections. Hence, we propose an adjacent moving window peak detection (AMWPD) approach that uses an approximate low-pass filter and statistical process control techniques to determine whether an abrupt change has occurred. We compare the AMWPD approach with existing techniques for change detection and show that the AMWPD approach exhibits comparable detection speed and number of missed detections while providing fewer false alarms. Second, we consider feature extraction and clustering for classification. For industrial applications, existing methods provide insufficient classification accuracy and require significant training time. Hence, we propose new features that improve classification accuracy and apply a modified tabu search and probabilistic neural network (mTS + PNN) approach to select and cluster the features and thereby classify the data. We compare the mTS + PNN approach with an existing feature selection and clustering technique that employs principal component analysis and a multi-layer perceptron neural network. Using an application example, we demonstrate that the mTS + PNN approach provides higher classification accuracy while requiring less training and classification time. Finally, we consider identification of output-to-output relationships in linear system dynamics. Existing approaches, including operational modal analysis, assume that the excitation signal is a realization of a white random process, which may not be true. Hence, we define and characterize pseudo transfer functions (PTFs), which relate output measurements, and we use changes in the identified PTF to detect faults. We demonstrate the effects of non-zero initial conditions, non-white excitation, unknown model order, and output noise on the accuracy of the identification and fault detection results.

Brzezinski, Adam John

56

All-to-all sequenced fault detection system  

DOEpatents

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

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

2010-11-02

57

Parametric uncertainty in sensor fault detection for turbofan jet engine  

Microsoft Academic Search

A method for detecting sensor faults in a turbofan engine is presented. The proposed method consists of an observer with integral action and an adaptive detection threshold. The threshold is computed with the assumption of parametric uncertainty in the process model. Successful simulations with sensor data from an RM12 jet engine shows that the method is capable of detecting even

Andreas Johansson; Torbjorn Norlander

2003-01-01

58

Using unknown input observers to detect and isolate sensor faults in a turbofan engine  

Microsoft Academic Search

An observer based fault detection and isolation method is presented. The method involves combining the unknown input observer theory with the Beard fault detection filter theory to generate a residual signal that has both disturbance decoupling and unidirectional properties. This robust, in the sense of disturbances, residual was used to detect and isolate sensor faults in a turbofan engine model.

S. K. Dassanake; Gary J. Balas; J. Bokor

2000-01-01

59

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

PubMed

Reliable, automated detection and diagnosis of abnormal behavior within vapor compression refrigeration cycle (VCRC) equipment is extremely desirable for equipment owners and operators. The specific type of VCRC equipment studied in this paper is a 70-ton helical rotary, air-cooled chiller. The fault detection and diagnostic (FDD) tool developed as part of this research analyzes chiller operating data and detects faults through recognizing trends or patterns existing within the data. The FDD method incorporates a neural network (NN) classifier to infer the current state given a vector of observables. Therefore the FDD method relies upon the availability of normal and fault empirical data for training purposes and therefore a fault library of empirical data is assembled. This paper presents procedures for conducting sophisticated fault experiments on chillers that simulate air-cooled condenser, refrigerant, and oil related faults. The experimental processes described here are not well documented in literature and therefore will provide the interested reader with a useful guide. In addition, the authors provide evidence, based on both thermodynamics and empirical data analysis, that chiller performance is significantly degraded during fault operation. The chiller's performance degradation is successfully detected and classified by the NN FDD classifier as discussed in the paper's final section. PMID:12858981

Bailey, Margaret B; Kreider, Jan F

2003-07-01

60

High impedance fault detection device tester  

SciTech Connect

High impedance or down conductor fault detection devices are now commercially available for evaluation. However, security and dependability of these devices can not be tested using conventional relay test apparatus and procedures. This paper presents a test apparatus and procedures for testing high impedance fault detection devices. The apparatus is capable of playing back in real-time waveforms selected from a data library, which includes seventy seven field recordings of high-impedance faults and feeder loads. Each recording is approximately five minutes long and stored in the form of digitized data sampled at 20 kHz.

Buchholz, V.L.; Nagpal, M.; Neilson, J.B.; Parsi-Feraidoonian, R.; Zarecki, W. [Powertech Labs Inc., Surrey, British Columbia (Canada)

1996-01-01

61

Design of arc fault detection system based on CAN bus  

Microsoft Academic Search

Arc fault detection system (AFDS) is a device intended to protect the power system against the arc fault that may cause fire. When there is an arc fault, the scale of fault current is lower than the initialization of most of the protection devices installed in the lowers, hence AFDS is an effective device to detect the arc fault successfully

Zong Ming; Yang Tian; Fengge Zhang

2009-01-01

62

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

63

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

64

LEARNING BAYESIAN NETWORKS FOR FAULT DETECTION: APPLICATION TO THE 747 LONGITUDINAL MOTION  

Microsoft Academic Search

The correct detection of a fault can save worthy resources or even prevent the destruction of key equipment, but, mainly, the correct detection of a single fault can save lives, as, for example, in the case of spaceships, aircraft and nuclear plants. In this work a new fault detection method, based on the learning of a Bayesian network, is applied

Jackson Paul Matsuura; Takashi Yoneyama; Roberto Kawakami; Harrop Galvão

65

Intelligent gear fault detection based on relevance vector machine with variance radial basis function kernel  

Microsoft Academic Search

Detecting machine faults at an early stage is very important. In this study, an intelligent fault detection method based on relevance vector machine (RVM) is proposed for incipient fault detection of gear. First, by combining wavelet packet transform with Fisher criterion, it is able to adaptively find the optimal decomposition level and select the global optimal features from all node

Chuangxin He; Chengliang Liu; Yanming Li; Jianfeng Tao

2010-01-01

66

Fault detection and management system for fault tolerant switched reluctance motor drives  

Microsoft Academic Search

Fault-tolerance characteristics of the switched reluctance motor are discussed, and winding fault detectors are presented which recognize shorted motor windings. Logic circuitry in the inverter blocks the power switch gating signals of the affected phase at the receipt of a fault-detection signal from one of the fault detectors. The fault detectors were implemented on a laboratory drive system to demonstrate

C. M. Stephens

1989-01-01

67

Reset tree-based optical fault detection.  

PubMed

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

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

2013-05-21

68

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

69

Sliding mode observers for fault detection and isolation  

Microsoft Academic Search

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

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

2000-01-01

70

Gear fault detection using customized multiwavelet lifting schemes  

NASA Astrophysics Data System (ADS)

Fault symptoms of running gearboxes must be detected as early as possible to avoid serious accidents. Diverse advanced methods are developed for this challenging task. However, for multiwavelet transforms, the fixed basis functions independent of the input dynamic response signals will possibly reduce the accuracy of fault diagnosis. Meanwhile, for multiwavelet denoising technique, the universal threshold denoising tends to overkill important but weak features in gear fault diagnosis. To overcome the shortcoming, a novel method incorporating customized (i.e., signal-based) multiwavelet lifting schemes with sliding window denoising is proposed in this paper. On the basis of Hermite spline interpolation, various vector prediction and update operators with the desirable properties of biorthogonality, symmetry, short support and vanishing moments are constructed. The customized lifting-based multiwavelets for feature matching are chosen by the minimum entropy principle. Due to the periodic characteristics of gearbox vibration signals, sliding window denoising favorable to retain valuable information as much as possible is employed to extract and identify the fault features in gearbox signals. The proposed method is applied to simulation experiments, gear fault diagnosis and normal gear detection to testify the efficiency and reliability. The results show that the method involving the selection of appropriate basis functions and the proper feature extraction technique could act as an effective and promising tool for gear fault detection.

Yuan, Jing; He, Zhengjia; Zi, Yanyang

2010-07-01

71

Design of nonlinear observers for detecting faults in hydraulic sub-sea pipelines  

Microsoft Academic Search

Firstly, a general nonlaminar model is considered for pipeline dynamics, including a treatment of faults caused by pipe restrictions. For three cases results are given for stability, robustness and fault detectability of a combined observer and residual (fault detection signal). An efficient numerical design algorithm is proposed. The method is applied to an actual experimental pipeline (rig system) which is

D. N. Shields; S. A. Ashton; S. Daley

2001-01-01

72

Model-based fault detection in induction Motors  

Microsoft Academic Search

In this paper a model-based fault detection method for induction Motors is presented. A new filtering technique based on Unscented Kalman filters and Extended Kalman filters, is utilized as a state estimation tool in broken bars detection of induction motors. Using the merits of these recent nonlinear estimation tools UKF and EKF, rotor resistance of an induction motor is estimated

F. Karami; J. Poshtan; M. Poshtan

2010-01-01

73

ROBUST FAULT DETECTION AND ISOLATION FOR UNCERTAIN LINEAR RETARDED SYSTEMS  

Microsoft Academic Search

A robust fault detection and isolation scheme is proposed for un- certain continuous linear systems with discrete state delays for both additive and multiplicative faults. Model uncertainties, disturbances and noises are represented as unstructured unknown inputs. The pro- posed scheme consists of a Luenberger observer for fault detection and a group of adaptive observers, one for each class of faults,

Canghua Jiang; Donghua Zhou; Furong Gao

2006-01-01

74

Fault detection and diagnosis of photovoltaic systems  

NASA Astrophysics Data System (ADS)

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

Wu, Xing

75

Fault detection and management system for fault-tolerant switched reluctance motor drives  

Microsoft Academic Search

The superior fault tolerance characteristics of the switched reluctance motor (SRM) have been proved in a working laboratory drive system. The program started by defining the performance effects of various types of motor winding faults. Motor winding fault detection devices were developed, along with control circuitry, to isolate a faulted winding by blocking the gating signals to the semiconductor power

C. M. Stephens

1991-01-01

76

Fault Detection in Multivariate Signals With Applications to Gas Turbines  

Microsoft Academic Search

This paper proposes a fault detection method for multivariate signals. The method assesses whether or not the multivariate autocovariance functions of two independently sampled system signals coincide. If the first signal is known to be sampled from a well-functioning system, then rejection of signal equality is tantamount to concluding that the second signal is sampled from a faulty system. The

Hany Bassily; Robert Lund; John Wagner

2009-01-01

77

A probabilistic approach to residual processing for vehicle fault detection  

Microsoft Academic Search

This paper presents a probabilistic method for processing and analyzing residuals for the purpose of fault detection. The method incorporates residuals from multiple models using a hybrid dynamic Bayesian network in order to yield a low-cost, complete, diagnostic system. Continuous residuals are used as evidence directly in the network, and this paper discusses options for representing their probability distributions. The

Matthew L. Schwall; J. Christian Gerdes

2002-01-01

78

Catastrophic fault diagnosis in dynamic systems using bond graph methods  

SciTech Connect

Detection and diagnosis of faults has become a critical issue in high performance engineering systems as well as in mass-produced equipment. It is particularly helpful when the diagnosis can be made at the initial design level with respect to a prospective fault list. A number of powerful methods have been developed for aiding in the general fault analysis of designs. Catastrophic faults represent the limit case of complete local failure of connections or components. They result in the interruption of energy transfer between corresponding points in the system. In this work the conventional approach to fault detection and diagnosis is extended by means of bond-graph methods to a wide variety of engineering systems. Attention is focused on catastrophic fault diagnosis. A catastrophic fault dictionary is generated from the system model based on topological properties of the bond graph. The dictionary is processed by existing methods to extract a catastrophic fault report to aid the engineer in performing a design analysis.

Yarom, Tamar.

1990-01-01

79

Dynamic sensor-based fault detection for robots  

NASA Astrophysics Data System (ADS)

Fault detection and fault tolerance are increasingly important for robots in space or hazardous environments due to the dangerous and often inaccessible nature of these environs. We have previously developed algorithms to enable robots to autonomously cope with failures of critical sensors and motors. Typically, the detection thresholds used in such algorithms to mask out model and sensor errors are empirically determined and are based on a specific robot trajectory. We have noted, however, that the effect of model and sensor inaccuracy fluctuates dynamically as the robot moves and as failures occur. The thresholds, therefore, need to be more dynamic and respond to the changes in the robot system so as to maintain an optimal bound for sensing real failures in the system versus misalignment due to modeling errors. In this paper, we analyze the reachable measurement intervals method of computing dynamic thresholds and explore its applicability to robotic fault detection.

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

1993-12-01

80

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

81

Fast Transient Fault-Current Detection Based on PQR Transformation Technique for a Solid-State Fault Current Limiter  

Microsoft Academic Search

This paper describes analysis, modeling and simulation of electrical transient fault-current detection in power systems. The proposed modeling is based on simple numerical integration only, which is able to efficiently handle some sophisticated calculation. The proposed fault detector methods are sliding root mean square (SRMS) and PQR transformation technique. In this paper, an abnormal condition is situated by simply adding

B. BORIBUN; T. KULWORAWANICHPONG

2007-01-01

82

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

83

An automated system for incipient fault detection and diagnosis in induction motors based on MCSA  

Microsoft Academic Search

The paper describes a system for automated detection of incipient faults in induction machines. The system is based on the Motor Current Signature Analysis method (MCSA) and aimed to be applied in a thermal electric power plant in south Brazil. First, the mechanism of fault evolution is introduced and clarified regarding the most common induction motor faults: stator winding short-circuits,

Daniel da Silva Gazzana; LuAlberto Pereira; D. Fernandes

2010-01-01

84

Fault diagnosis of airborne equipment based on grey correlation fault tree identification method  

Microsoft Academic Search

In order to diagnosis the complex airborne equipment faults with small samples and feebleness condition, a grey correlation fault tree identification method is proposed by combining the grey system theory with fault tree analysis method. Firstly, on the basis of the fault tree qualitative and quantitative analysis by using binary decision diagram (BDD), the standard fault modes are constructed based

Wei Tian

2008-01-01

85

A neural network approach to instrument fault detection and isolation  

Microsoft Academic Search

An instrument fault detection and isolation (IFDI) technique based on the use of an artificial neural network (ANN) is proposed. The ANN input layer is fed by instrument outputs, and its output layer gives information for instrument diagnosis. The method adopted is described in detail and tested on a complex automatic measurement station for induction motor testing. The performance of

Andrea Bernieri; Giovanni Betta; Antonio Pietrosanto; Carlo Sansone

1995-01-01

86

The process chemometrics approach to process monitoring and fault detection  

Microsoft Academic Search

Chemometrics, the application of mathematical and statistical methods to the analysis of chemical data, is finding ever widening applications in the chemical process environment. This article reviews the chemometrics approach to chemical process monitoring and fault detection. These approaches rely on the formation of a mathematical\\/statistical model that is based on historical process data. New process data can then be

Barry M. Wise; Neal B. Gallagher

1996-01-01

87

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

Microsoft Academic Search

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

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

1994-01-01

88

Automatic fault detection in Friction Stir Welding  

Microsoft Academic Search

Friction Stir Welding (FSW) is a relatively new welding technique where metals are joined through mechanical stirring. Due to its numerous advantages over older welding methods, it has been implemented in an increasing number of industries. However, there are remaining challenges to be overcome in FSW. One of the most serious is its reliance on accurate weld parameters. Additionally, faults

P. A. Fleming; K. A. Fleming; D. Lammlein; D. M. Wilkes; T. Bloodworth; G. Cook; T. Lienert; M. Bement

89

Concurrent Detection of Software and Hardware Data-Access Faults  

Microsoft Academic Search

A new approach allows low-cost concurrent detection of two important types of faults, software and hardware data-access faults, using an extension of the existing signature monitoring approach. The proposed approach detects data-access faults using a new type of redundant data structure that contains an embedded signature. Low-cast fault detection is achieved using simple architecture support and compiler support that exploit

Kent D. Wilken; Timothy Kong

1997-01-01

90

Fault detection via optimally robust detection filters  

Microsoft Academic Search

An approach is presented for using optimally robust detection filters to generate analytic redundancy. By introducing an appropriate criterion the design of the filter is formulated as an optimization problem. Its solution shows that the optimally robust detection filter consists of a bandpass filter and a linear system which is obtained by solving a general eigenvalue problem. The algorithm for

X. Ding; P. M. Frank

1989-01-01

91

Detection and extraction of fault surfaces in 3D seismic data  

Microsoft Academic Search

We propose an efficient method for detecting and extract- ing fault surfaces in 3D-seismic volumes. The seismic data aretransformedintoavolumeoflocal-fault-extractionLFE estimatesthatrepresentsthelikelihoodthatagivenpointlies onafaultsurface.Wepartitionthefaultsurfacesintorelative- lysmalllinearportions,whichareidentifiedbyanalyzingtilt- ed and rotated subvolumes throughout the region of interest. Directional filtering and thresholding further enhance the seismic discontinuities that are attributable to fault surfaces. Subsequently, the volume of LFE estimates is skeletonized, and individual fault surfaces are extracted

Israel Cohen; Nicholas Coult; Anthony A. Vassiliou

2006-01-01

92

Observer and Data-Driven-Model-Based Fault Detection in Power Plant Coal Mills  

Microsoft Academic Search

This paper presents and compares model-based and data-driven fault detection approaches for coal mill systems. The first approach detects faults with an optimal unknown input observer developed from a simplified energy balance model. Due to the time-consuming effort in developing a first principles model with motor power as the controlled variable, data-driven methods for fault detection are also investigated. Regression

Peter Fogh Odgaard; Bao Lin; Sten Bay Jorgensen

2008-01-01

93

Detecting low-voltage arc fault based on lifting multiwavelet  

Microsoft Academic Search

Arc fault is one of the prime reasons causing electrical fire accidents. It is difficult to detect the arc faults' features by traditional circuit protections. An algorithm using lifting multiwavelet transform for arc fault detecting was presented in this paper. First, experiments were conducted according to UL1699 standard and data were collected by LabView. The high frequency band information of

Weiyan Zheng; Weilin Wu

2009-01-01

94

Envelope order tracking for fault detection in rolling element bearings  

NASA Astrophysics Data System (ADS)

An envelope order tracking analysis scheme is proposed in the paper for the fault detection of rolling element bearing (REB) under varying-speed running condition. The developed method takes the advantages of order tracking, envelope analysis and spectral kurtosis. The fast kurtogram algorithm is utilized to obtain both optimal center frequency and bandwidth of the band-pass filter based on the maximum spectral kurtosis. The envelope containing vibration features of the incipient REB fault can be extracted adaptively. The envelope is re-sampled by the even-angle sampling scheme, and thus the non-stationary signal in the time domain is represented as a quasi-stationary signal in the angular domain. As a result, the frequency-smear problem can be eliminated in order spectrum and the fault diagnosis of REB in the varying-speed running condition of the rotating machinery is achieved. Experiments are conducted to verify the validity of the proposed method.

Guo, Yu; Liu, Ting-Wei; Na, Jing; Fung, Rong-Fong

2012-12-01

95

Modelling and Analysis of Fault Behaviour of Inverter Microgrids to Aid Future Fault Detection  

Microsoft Academic Search

This paper investigates the fault behaviour of an inverter-only supplied microgrid by computer simulation and numerical analysis. The purpose of this study is to give a qualitative and quantitative understanding of the dynamics involved in a microgrid under fault conditions in order to supply a tool to help the design of a suitable fault detection strategy. After considering first the

M. Brucoli; T. C. Green; J. D. F. McDonald

2007-01-01

96

Identification of multiple transient faults based on the adaptive spectral kurtosis method  

Microsoft Academic Search

This paper proposes a multi-fault detection method based on the adaptive spectral kurtosis (ASK) analysis of the vibration signal from single sensor. A theoretical model of multiple bearing faults is established in this paper. Compared with the kurtogram and protrugram techniques, the proposed method can more effectively extract signatures of multiple bearing faults even in the presence of strong background

Yanxue Wang; Ming Liang

2012-01-01

97

Detecting delay faults using power supply transient signal analysis  

Microsoft Academic Search

A delay-fault testing strategy based on the analysis of power supply transient signals is presented. The method is an extension to a Go\\/No-Go device testing method called Transient Signal Analysis (TSA) (1). TSA detects defects through the analysis of a set of power supply transient waveforms in the time or frequency domain, e.g., Fourier phase components. A recent extension to

Abhishek Singh; Chintan Patel; Shirong Liao; James F. Plusquellic; Anne E. Gattiker

2001-01-01

98

Detection of arcing faults on distribution feeders. Final report  

SciTech Connect

Some distribution primary faults draw very little fault current and are therefore difficult to detect with existing overcurrent protection systems. The problem of detecting high impedance faults is examined from the perspective of current utility protection practices and it is shown why conventional overcurrent protection systems may not detect such faults. Research by Texas A and M resulted in the design and testing of a microcomputer-based prototype of an arcing, high impedance fault detector. The fault detection technique is based on an increase in the high frequency (2 to 10 kHz) component of distribution feeder current caused by the arcing associated with many high impedance faults. The proposed fault detection system is explained in theory. This theory is supported by field data measurements and analysis of a large number of staged distribution primary faults and normal system conditions. The design and demonstration of the prototype is then explained. The device successfully detected many faults of greater than 5 to 10 A on a typical distribution feeder without false trips. General application of this fault detection technique is also considered, particularly with regard to its strengths and limitations.

Russell, B.D.

1982-12-01

99

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

Microsoft Academic Search

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

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

2008-01-01

100

High impedance fault detection on radial distribution and utilization systems  

Microsoft Academic Search

The paper presents a simple relaying detection scheme for high impedance faults (HIF) in radial utilization and distribution feeders. The scheme is based on the concept of quasistatic ripple harmonics, sub and super harmonic frequencies usually associated with low level currents during arcing faults due to high impedance type (HIF) faults

A. M. Sharaf; R. M. El-Sharkawy; R. Al-Fatih; M. Al-Ketbi

1996-01-01

101

Identification of multiple transient faults based on the adaptive spectral kurtosis method  

NASA Astrophysics Data System (ADS)

This paper proposes a multi-fault detection method based on the adaptive spectral kurtosis (ASK) analysis of the vibration signal from single sensor. A theoretical model of multiple bearing faults is established in this paper. Compared with the kurtogram and protrugram techniques, the proposed method can more effectively extract signatures of multiple bearing faults even in the presence of strong background noise. The performance of the proposed method in fault detection of the rolling element bearings is validated using simulation data and experimental signals from a bearing with multiple faults and two faulty bearings.

Wang, Yanxue; Liang, Ming

2012-01-01

102

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

103

New Method for Abbreviating the Fault Tree Graphical Representation.  

National Technical Information Service (NTIS)

Fault tree analysis is being widely used for reliability and safety analysis of systems encountered in the nuclear industry and elsewhere. A disadvantage of the fault tree method is the voluminous fault tree graphical representation that conventionally re...

M. E. Stewart J. B. Fussell R. J. Crump

1974-01-01

104

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

105

Operational Fault Detection in cellular wireless base-stations  

Microsoft Academic Search

The goal of this work is to improve availability of operational base-stations in a wireless mobile network through non-intrusive fault detection methods. Since revenue is generated only when actual customer calls are processed, we develop a scheme to minimize revenue loss by monitoring real-time mobile user call processing activity. The mobile user call load profile experienced by a base-station displays

Sudarshan Rao

2006-01-01

106

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

107

An improved principal component analysis scheme for sensor fault detection and isolation : Application to a three tanks system  

Microsoft Academic Search

In this paper a sensor fault detection and isolation procedure based on principal component analysis (PCA) is proposed to monitor a three interconnected tanks system. The PCA model is built to maximize fault detection sensitivity using a new index. The localization procedure is carried out using two methods. The first is based on the variables contribution to the fault index.

Mohamed Guerfel; Anissa Ben Aicha; Kamel Ben Othman; Mohamed Benrejeb

2009-01-01

108

Detection of Rotor Faults in Synchronous Generators  

Microsoft Academic Search

Synchronous generators are subject to a variety of failures which may occur in various parts of their structure. Furthermore, these faults may be categorized as partial failure or catastrophic faults. One may note that most partial faults can eventually result in a permanent lack of service. The present digest deals with a class of failures which may happen in the

M. Kiani; W.-J. Lee; R. Kenarangui; B. Fahimi

2007-01-01

109

Fault Detection and Handling for Longitudinal Control  

Microsoft Academic Search

The purpose of this project is to extend and integrate existing results on fault diagnostics and fault management for passenger vehicles used in automated highway systems (AHS). These re-sults have been combined to form a fault diagnostic and management system for the longitudinal control system of the automated vehicles which has a heirarchical framework that complements the established PATH control

Jingang Yi; Adam Howell; Roberto Horowitz; Karl Hedrick; Luis Alvarez

2001-01-01

110

Detection of high-impedance faults in power distribution systems  

Microsoft Academic Search

When overhead power lines in solid or low-impedance grounded systems lose supports and fall on poorly conductive surfaces, they generate high-impedance faults (HIFs). These faults are a great public safety concern because the fault currents are generally too small for detection by conventional overcurrent relays. This concern has generated great interest in the detection of downed conductor-related HIFs at the

Daqing Hou

2007-01-01

111

A NEW SENSITIVE DETECTION ALGORITHM FOR LOW AND HIGH IMPEDANCE EARTH FAULTS IN COMPENSATED MV NETWORKS BASED ON THE ADMITTANCE METHOD  

Microsoft Academic Search

Since the majority of all electrical faults in distribution networks are single line to earth faults, these events have a significant impact on the overall quality of power supply. The resonant earthing approach allows to limit the fault current in case of single pole earth faults (ground faults) and leads to a significant increased rise time of the recovery voltage.

Thomas SCHINERL

2005-01-01

112

DEVELOPMENT OF A FAULT DETECTION SYSTEM FOR WIND ENERGY CONVERTERS  

Microsoft Academic Search

Unforeseen failure of components of a wind turbine can have a significant impact on the turbine economy. A promising approach to avoid such failures is the concept of on-line fault detection. By continuous supervision of the dynamic behaviour of a WEC incipient faults can be detected at a very early stage. Thus, secondary defects and major breakdowns can be avoided.

P. Caselitz; J. Giebhardt; T. Krüger; M. Mevenkamp

113

Detecting Faults in Four Symmetric Key Block Ciphers  

Microsoft Academic Search

Fault detection in encryption algorithms is gaining in importance since fault attacks may compromise even recently developed cryptosystems. We analyze the different operations used by various symmetric ciphers and propose possible detection codes and frequency of checking. Several examples (i.e., AES, RC5, DES and IDEA) are presented to illustrate our analysis.

Luca Breveglieri; Israel Koren; Paolo Maistri

2004-01-01

114

Model based fault detection in a centrifugal pump application  

Microsoft Academic Search

A model based approach for fault detection in a centrifugal pump, driven by an induction motor, is proposed in this paper. The fault detection algorithm is derived using a combination of structural analysis, observer design and Analytical Redundancy Relation (ARR) design. Structural considerations on the system is used to divide it into two cascaded connected subsystems, giving an example on

C. S. Kallesoe; V. Cocquempot; R. Izadi-Zamanabadi

2006-01-01

115

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

116

A method for reducing the target fault list of crosstalk faults in synchronous sequential circuits  

Microsoft Academic Search

We describe a method of identifying a set of target crosstalk faults which may need to be tested in synchronous sequential circuits. Our method classifies the pairs of aggressor and victim lines, using topological and timing information, to deduce a set of target crosstalk faults. In this process, our method also identifies the false crosstalk faults that need not (and\\/or

Hiroshi Takahashi; Keith J. Keller; Kim T. Le; Kewal K. Saluja; Yuzo Takamatsu

2005-01-01

117

Development of fault section detecting system for gas insulated transmission lines  

SciTech Connect

A fault section detecting system using optical magnetic field sensors developed for gas insulated transmission lines (GIL) is reported. A bismuth silicon oxide (Bi/sub 12/SiO/sub 20/, or BSO) single crystal was adopted for the optical magnetic field sensor. A method of mounting the sensors to GIL which enables the sensors to detect the conductor current from outside the enclosure was developed. With the developed fault detector, faults occurring inside a section of GIL between sensors are detected by discriminating the phases of conductor currents detected by the sensors. The system was confirmed to have sufficient performance for application to commerical GILS.

Nakamura, E.; Uchida, K.; Koshilishi, M.; Mitsui, T.; Miyamoto, S.; Nakamura, K.; Itaka, K.; Hara, T.; Yoda, T.

1986-01-01

118

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

119

Diagnostic system for on-line detection of rotor faults in induction motor drives  

Microsoft Academic Search

? Abstract -- The paper presents an on-line condition monitoring and diagnostic system for induction motor drives. It enables detection of many different faults, which may arise during the lifetime of the motor, although special attention was devoted to identify broken rotor bars at an early stage of the fault propagation. The method is based on the analysis of stator

R. Fiser; H. Lavric; V. Ambrozic; M. Bugeza

2011-01-01

120

Concepts and methods in fault-tolerant control  

Microsoft Academic Search

Faults in automated processes will often cause undesired reactions and shut-down of a controlled plant, and the consequences could be damage to technical parts of the plant, to personnel or the environment. Fault-tolerant control combines diagnosis with control methods to handle faults in an intelligent way. The aim is to prevent that simple faults develop into serious failure and hence

M. Blanke; Marcel Staroswiecki; N. E. Wu

2001-01-01

121

Predictive Fault Detection for Missile Defense Mission Equipment and Structures  

Microsoft Academic Search

\\u000a Equipment failures in defense systems result in loss or reduction of operational capability, impacting system readiness. Faults\\u000a in critical equipment can impact system performance and reliability, as can structural failures. Predictive fault detection\\u000a (PFD) provides prognostic capability to identify components and internal structures that exhibit either degradation or increased\\u000a variability of parameters, in advance of actual faults occurrences. It has

Jeffrey S. Yalowitz; Roger K. Youree; Aaron Corder; Teng K. Ooi

122

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

123

Fault detection in a ball bearing system using minimum variance cepstrum  

NASA Astrophysics Data System (ADS)

The signals that can be obtained from rotating machines convey information on a machine operating condition. For example, if the machine has faults, it generates a signal that is usually composed of pulse signals. This paper addresses the way in which we can find the faults for periodic pulse signals. Specifically, we have an interest in the case that it is embedded in noise. How well we can detect the fault signal in noise directly determines the quality of fault diagnosis of rotating machines. We propose a signal processing method to detect fault signals in noisy environments. The proposed method is 'minimum variance cepstrum' because it minimizes the variance of the signal power in its cepstrum representation. To test the performance of this technique, various experiments have been performed for ball bearing elements that have man-made faults. Results show that the proposed technique is quite powerful in the detection of faults in noisy environments. In other words, it is possible to detect faults earlier than with conventional methods (McFadden and Smith 1984 J. Sound Vib. 96 69-82, Ho and Randall 1999 6th Int. Congress on Sound and Vibration pp 2943-50, Lee and White 1998 J. Sound Vib. 217 485-505, Kim et al 1991 Mech. Syst. Signal Process. 5 461-73, Staszewski and Tomlinson 1997 Mech. Syst. Signal Process. 11 331-50).

Choi, Young-Chul; Kim, Yang-Hann

2007-05-01

124

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

125

Design the Fault Identification\\/Detection Filter via a Simplified Transfer Matrix Approach  

Microsoft Academic Search

A simplified method to design the fault identification\\/detection filter (FIDF) is presented in this paper. Based on a decoupling technique of the transfer matrix approach, it leads to a neat parameterization set of achievable FIDFs.

Shao-Kung Chang; Pau-Lo Hsu

1992-01-01

126

Optimal robust fault detection for linear discrete time systems  

Microsoft Academic Search

This paper considers robust fault detection problems for linear discrete time systems. It is shown that the optimal robust detection filters for several well-recognized robust fault detection problems, such as H-\\/Hinfin, H2\\/Hinfin, and Hinfin\\/Hinfin problems, are the same and can be obtained by solving a standard algebraic Riccati equation. Moreover, the optimal filters for those problems do not depend on

Nike Liu; Kemin Zhou

2007-01-01

127

Motor Fault Detection Using a Rogowski Sensor Without an Integrator  

Microsoft Academic Search

This paper presents a new approach for the current acquisition system in motor fault detection applications. This paper includes the study, design, and implementation of a Rogowski-coil current sensor without the integrator circuit that is typically used. The circuit includes an autotuning block able to adjust to different motor speeds. Equalizing the amplitudes of the fundamental and fault harmonics leads

Oscar Poncelas; Javier A. Rosero; Jordi Cusido; Juan Antonio Ortega; Luis Romeral

2009-01-01

128

ARCING HIGH IMPEDANCE FAULT DETECTION USING REAL CODED GENETIC ALGORITHM  

Microsoft Academic Search

Safety and reliability are two of the most important aspects of electric power supply systems. Sensitivity and robustness to detect and isolate faults can influence the safety and reliability of such systems. Overcurrent relays are generally used to protect the high voltage feeders in distribution systems. Downed conductors, tree branches touching conductors, and failing insulators often cause high-impedance faults in

Naser Zamanan; Jan Sykulski; A. K. Al-Othman

129

Construction and selection of lifting-based multiwavelets for mechanical fault detection  

NASA Astrophysics Data System (ADS)

The essence of wavelet transforms is a similar measurement between the signal and the wavelet basis functions. Thus, the construction and selection of the proper wavelet basis functions similar to the fault feature and possessing good properties such as vanishing moments have vital importance to the effective fault diagnosis. In this paper, the construction of lifting-based adaptive multiwavelets with various vanishing moments and the selection rules for different mechanical fault detection are proposed. On the basis of the fixed cubic Hermite multiwavelets, lifting schemes are adopted to construct new changeable multiwavelets with diverse vanishing moments. Then, the defined local spectral entropy minimization rules are proposed to determine the optimum multiwavelets providing the proper vanishing moments, classified into the typical shaft faults, gear faults and rolling bearing faults. The proposed method is applied to incipient fault diagnosis of rolling bearing and gearbox fault diagnosis of rolling mill to verify its effectiveness and feasibility in comparison with different wavelet transforms and spectral kurtosis. The results show that the proposed method can act as a promising tool for mechanical fault detection.

Yuan, Jing; He, Zhengjia; Zi, Yanyang; Wei, Ying

2013-11-01

130

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

2011-10-28

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

Extended Heartbeat Mechanism for Fault Detection Service Methodology  

NASA Astrophysics Data System (ADS)

Fault detection methodology is a crucial part in providing a scalable, dependable and high availability of grid computing environment. The most popular technique that used in detecting fault is heartbeat mechanism where it monitors the grid resources in a very short interval. However, this technique has its weakness as it requires a period of times before the node is realized to be faulty and therefore delaying the recovery actions to be taken. This is due to unindexed status for each transaction and need to wait for a certain time interval before realizing the nodes has failed. In this paper, fault detection mechanism and service using extended heartbeat mechanism is proposed. This technique introduced the use of index server for indexing the transaction and utilizing pinging service for pushing mechanism. The model outperformed the existing techniques by reducing the time taken to detect fault in approximately 30%. Also, the mechanism provides a basis for customizable recovery actions to be deployed.

Mohd. Noor, Ahmad Shukri; Mat Deris, Mustafa

133

Fault Location Methods for Ungrounded Distribution Systems Using Local Measurements  

NASA Astrophysics Data System (ADS)

This article presents novel fault location algorithms for ungrounded distribution systems. The proposed methods are capable of locating faults by using obtained voltage and current measurements at the local substation. Two types of fault location algorithms, using line to neutral and line to line measurements, are presented. The network structure and parameters are assumed to be known. The network structure needs to be updated based on information obtained from utility telemetry system. With the help of bus impedance matrix, local voltage changes due to the fault can be expressed as a function of fault currents. Since the bus impedance matrix contains information about fault location, superimposed voltages at local substation can be expressed as a function of fault location, through which fault location can be solved. Simulation studies have been carried out based on a sample distribution power system. From the evaluation study, it is evinced that very accurate fault location estimates are obtained from both types of methods.

Xiu, Wanjing; Liao, Yuan

2013-08-01

134

A fuzzy dissolved gas analysis method for the diagnosis of multiple incipient faults in a transformer  

Microsoft Academic Search

Dissolved gas analysis (DGA) of transformer oil has been one of the most useful techniques to detect the incipient faults. Various methods, such as the IEC codes, have been developed to interpret DGA results directly obtained from a chromatographer. Although these methods are widely used in the world, they sometimes fail to diagnose, especially when more than one fault exists

Q. Su; C. Mi; L. L. Lai; P. Austin

2000-01-01

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

Soft Computing Application in Fault Detection of Induction Motor  

NASA Astrophysics Data System (ADS)

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

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

2010-10-01

137

Optimal solutions to multi-objective robust fault detection problems  

Microsoft Academic Search

This paper will give complete, analytic, and optimal solutions to several robust fault detection problems that have been considered in the research community in the last twenty years. It is shown that several well-recognized robust fault detection problems, such as H-\\/Hinfin, H2\\/Hinfin, and Hinfin\\/Hinfin problems, have a very simple optimal solution in an observer form by solving a standard algebraic

Nike Liu; Kemin Zhou

2007-01-01

138

Current monitoring circuit for fault detection in CMOS integrated circuit  

Microsoft Academic Search

This article presents a built-in current sensor (BICS), which detects faults using the current testing technique in CMOS integrated circuits. This circuit employs cross-coupled PMOS transistors, which are used as current comparators. The proposed circuit has a negligible impact on the performance of the circuit under test (CUT). In addition, no extra power dissipation and high-speed fault detection are achieved.

Jeong Beom Kim

2008-01-01

139

Algorithm comparison for high impedance fault detection based on staged fault test  

SciTech Connect

Four developed high impedance fault detection algorithms: proportional relaying algorithm, ratio ground relaying algorithm, second-order harmonic current relaying algorithm and third-order harmonic current relaying algorithm, were simulated by mathematical models. Relaying performances for these algorithms based on a staged fault data were then compared. The operations of a ground overcurrent delay 51N and a ratio ground delay CGRS were also checked in the test. Results of the comparison are presented and discussed in this paper. It can be used as a reference for the development of a reliable high impedance fault detector.

Huang, C.L.; Chu, H.Y.; Chen, M.T. (Dept. of Electrical Engineering, National Cheng Kung Univ., Tainan (TW))

1988-10-01

140

Observer and data-driven-model-based fault detection in power plant coal mills  

SciTech Connect

This paper presents and compares model-based and data-driven fault detection approaches for coal mill systems. The first approach detects faults with an optimal unknown input observer developed from a simplified energy balance model. Due to the time-consuming effort in developing a first principles model with motor power as the controlled variable, data-driven methods for fault detection are also investigated. Regression models that represent normal operating conditions (NOCs) are developed with both static and dynamic principal component analysis and partial least squares methods. The residual between process measurement and the NOC model prediction is used for fault detection. A hybrid approach, where a data-driven model is employed to derive an optimal unknown input observer, is also implemented. The three methods are evaluated with case studies on coal mill data, which includes a fault caused by a blocked inlet pipe. All three approaches detect the fault as it emerges. The optimal unknown input observer approach is most robust, in that, it has no false positives. On the other hand, the data-driven approaches are more straightforward to implement, since they just require the selection of appropriate confidence limit to avoid false detection. The proposed hybrid approach is promising for systems where a first principles model is cumbersome to obtain.

Odgaard, P.F.; Lin, B.; Jorgensen, S.B. [University of Aalborg, Aalborg (Denmark). Dept. of Electrical Systems

2008-06-15

141

A fault detection and isolation filter for discrete linear systems.  

PubMed

The problem of fault and/or abrupt disturbances detection and isolation for discrete linear systems is analyzed in this work. A strategy for detecting and isolating faults and/or abrupt disturbances is presented. The strategy is an extension of an already existing result in the continuous time domain to the discrete domain. The resulting detection algorithm is a Kalman filter with a special structure. The filter generates a residuals vector in such a way that each element of this vector is related with one fault or disturbance. Therefore the effects of the other faults, disturbances, and measurement noises in this element are minimized. The necessary stability and convergence conditions are briefly exposed. A numerical example is also presented. PMID:14582887

Giovanini, L; Dondo, R

2003-10-01

142

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

143

Predictive unsupervised organisation in marine engine fault detection  

Microsoft Academic Search

This paper utilises topological learners, the self organising map in combination with the k means algorithm to organise potential engine faults and the respective location of faults, focussing on a 12 cylinder 2 stroke marine diesel engine. This method is applied to reduce the numerosity of the data presented to a user by selecting representative samples from a number of

Ian Morgan; Honghai Liu; George Turnbull; David Brown

2008-01-01

144

Fault Tree Analysis, Methods, and Applications ? A Review  

Microsoft Academic Search

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

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

1985-01-01

145

The sparsogram: A new and effective method for extracting bearing fault features  

Microsoft Academic Search

Rolling element bearing is the most frequently failed component in rotary machine. Its failure could cause unexpected machine breakdown. This paper presents a novel fault diagnostic method called sparsogram that can enable early bearing fault detection in a prompt manner. The main concept of sparsogram is derived from the sparsity measurement commonly used for analyzing ultrasonic signals. Sparsogram is capable

Peter W. Tse; Dong Wang

2011-01-01

146

Faults  

NSDL National Science Digital Library

This site explains the three types of faults that result from plate movement. Animated diagrams are used to demonstrate strike-slip faults, normal faults, and reverse faults. There are also four photographs that show the results of actual earthquakes.

147

Automated Fault Detection for DIII-D Tokamak Experiments  

SciTech Connect

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

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

1999-11-01

148

On-line fault detection of sensor measurements  

Microsoft Academic Search

On-line fault detection in sensor networks is of paramount importance due to the convergence of a variety of challenging technological, application, conceptual, and safety related factors. We introduce a taxonomy for classification of faults in sensor networks and the first on-line model-based testing technique. The approach is generic in the sense that it can be applied on an arbitrary system

Farinaz Koushanfar; Miodrag Potkonjak; Alberto Sangiovanni-Vincentelli

2003-01-01

149

Using Model Checking to Generate Fault Detecting Tests  

Microsoft Academic Search

We present a technique which generates from Abstract State Machines specifications a set of test sequences capable to uncover\\u000a specific fault classes. The notion of test goal is introduced as a state predicate denoting the detection condition for a particular fault. Tests are generated by forcing\\u000a a model checker to produce counter examples which cover the test goals. We introduce

Angelo Gargantini

2007-01-01

150

Results from Field Testing of Embedded Air Handling Unit and Variable Air Volume Box Fault Detection Tools.  

National Technical Information Service (NTIS)

Fault detection and diagnostic (FDD) methods that can detect common mechanical faults and control errors in air-handling units (AHUs) and variable-air-volume (VAV) boxes were developed and commercialized. The tools are sufficiently simple that they can be...

J. Schein

2006-01-01

151

Results from Laboratory Testing of Embedded Air Handling Unit and Variable Air Volume Box Fault Detection Tools.  

National Technical Information Service (NTIS)

The purpose of the research effort described in this report is to develop, test, and demonstrate fault detection and diagnostics (FDD) methods that can detect common mechanical faults and control errors in air-handling units (AHUs) and variable-air-volume...

J. Schein S. T. Bushby

2002-01-01

152

Nonlinear Fault Detection and Isolation in a Three-Tank Heating System  

Microsoft Academic Search

We consider the fault detection and isolation (FDI) problem for a nonlinear dynamic plant (the IFATIS Heating System Benchmark) affected by actuator and\\/or sensor faults. A general procedure is proposed for modeling faults of sensors that measure the state of a nonlinear system, so that each sensor fault is typically associated to a set of (always concurrent) fault inputs and

Raffaella Mattone; Alessandro De Luca

2006-01-01

153

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

154

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

NASA Astrophysics Data System (ADS)

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

Yang, Ming; Makis, Viliam

2010-11-01

155

Application of Dynamic Safety Margin in Robust Fault Detection and Fault Tolerant Control  

Microsoft Academic Search

The Dynamic Safety Margin (DSM) is defined as a performance index, whose independent variable is the distance from a predefined safety boundary, which is described in the state space by a set of inequality constraints, to the current system state. Robustness is an important issue for fault detection and isolation (FDI) system. In this work, design a robust FDI system

M. Abdel-Geliel; E. Badredden; A. Gambier

2006-01-01

156

Pattern recognition-a technique for induction machines rotor fault detection “broken bar fault  

Microsoft Academic Search

A pattern recognition technique based on Bayes minimum error classifier is developed to detect broken rotor bar faults in induction motors at the steady state. The proposed algorithm uses only stator currents as input without the need for any other variables. First rotor speed is estimated from the stator currents, then appropriate features are extracted. The produced feature vector is

Masoud Haji; Hamid A. Toliyat

2001-01-01

157

Pattern recognition-a technique for induction machines rotor fault detection “eccentricity and broken bar fault  

Microsoft Academic Search

A pattern recognition technique based on Bayes minimum error classifier is developed to detect broken rotor bar faults and static eccentricity in induction motors at the steady state. The proposed algorithm uses stator currents as input without any other sensors. First, rotor speed is estimated from stator currents, then appropriate features are extracted. The produced feature vector is normalized and

Masoud Haji; Hamid A. Toliyat

2001-01-01

158

Remote sensing techniques in active faults surveying. Case study: detecting active faulting zones NW of Damascus, Syria  

Microsoft Academic Search

In this paper, an effective method is presented to identify active faults from different sources of remote sensing images. First, it was compared the capability of some satellite sensors in active faults survey. Then, it was discussed a few digital image processing approaches used for information enhancement and feature extraction related to faults. Those methods include band ratio, PCA (Principal

Moutaz Dalati

2005-01-01

159

Detection, identification, and quantification of sensor fault in a sensor network  

NASA Astrophysics Data System (ADS)

In structural health monitoring (SHM) and control, the structure can be instrumented with an array of sensors forming a redundant sensor network, which can be utilized in sensor fault diagnosis. In this study, the objective is to detect, identify, and quantify a sensor fault using the structural response data measured with the sensor network. Seven different sensor fault types are investigated and modelled: bias, gain, drifting, precision degradation, complete failure, noise, and constant with noise. The sensor network is modelled as a Gaussian process and each sensor in the network is estimated in turn using the minimum mean square error (MMSE) estimation The sensor fault is identified and quantified using the multiple hypothesis test utilizing the generalized likelihood ratio (GLR). The proposed approach is experimentally verified with an array of accelerometers assembled on a wooden bridge. Different sensor faults are simulated by modifying a single sensor. The method is able to detect a sensor fault, identify and correct the faulty sensor, as well as identify and quantify the fault type.

Kullaa, Jyrki

2013-10-01

160

A new arcing fault modeling and detection technique for navy IPS power system  

Microsoft Academic Search

Smooth and uninterrupted operation in the ship electric power system requires very efficient fault protection schemes for the electrical apparatus and components in the network. Detection and identification of fault therefore become necessary in order to provide protection for the network in events of a fault. This paper presents modeling and detection and identification of arcing fault for the navy

J. A. Momoh; Ayodele S. Ishola-Salawu

2006-01-01

161

Application of the Digraph Method in System Fault Diagnostics  

Microsoft Academic Search

There is an increasing demand for highly reliable systems in the safety conscious climate of today's world. When a fault does occur there are two desirable outcomes. Firstly, detection is required to discover whether functionality at a pre-determined level can be maintained and secondly, a necessary repair strategy is sought to minimise system disruption. Traditional focus on fault diagnosis has

E. M. Kelly; L. M. Bartlett

2006-01-01

162

A Novel Fault-Detection Technique for The Parallel Multipliers and Dividers  

Microsoft Academic Search

A new fault-detection technique, ?-scan, for a specific interconnection of the parallel Braun-multiplier and the parallel divider is presented. The fault-detection model, Pair Faults (pf), and the concept of Multiple Fault Boundaries (MFBs) are generalized with new supporting lemmas. The new technique's application is used to detect all multiple stuck-at faults of the carry save adder (CSA) tree and the

Chanyutt Arjhan; Raghvendra G. Deshmukh

1999-01-01

163

Decomposition Methods for Fault Tree Analysis  

Microsoft Academic Search

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

Arnon Rosenthal

1980-01-01

164

Fault detection of networked control systems with limited communication  

Microsoft Academic Search

Fault detection (FD) of networked control systems (NCS) with limited communication is addressed in this article. In periodic communication sequence-based NCS, at each time instant only parts of the actuators and sensors are allowed to communicate with the central FD system, which leads to incomplete plant information at the central station. In this article, a parity space based multi-solution FD

Yongqiang Wang; Hao Ye; Steven X. Ding; Yue Cheng; Ping Zhang; Guizeng Wang

2009-01-01

165

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

Microsoft Academic Search

Generally, fault detection is the process of monitoring a physical dynamic system accompanied by conformation and assessment of any degradation of system performance. These systems are modelled and terms that are representative of a specific fault are identified and monitored for detection. In this paper, a fault detection algorithm is developed to isolate and detect friction changes in a high

W. B. Dunbar; R. A. de Callafon; J. B. Kosmatka

2001-01-01

166

Fault classification performance of induction motor bearing using AI methods  

Microsoft Academic Search

This paper presents an approach of intelligent fault classification of induction motor bearing (IMB) using several artificial intelligent (AI) methods. The most common AI methods are FeedForward Neural Network (FFNN), Elman Network (EN), Radial Basis Function Network (RBFN) and Adaptive Neuro-Fuzzy Inference System (ANFIS). The data of IMB fault is obtained from Case Western Reserve University website in form of

Abd Kadir Mahamad; Takashi Hiyama

2010-01-01

167

A Method of Locating Open Faults on Incompletely Identified Pass/Fail Information  

NASA Astrophysics Data System (ADS)

In order to reduce the test cost, built-in self test (BIST) is widely used. One of the serious problems of BIST is that the compacted signature in BIST has very little information for fault diagnosis. Especially, it is difficult to determine which tests detect a fault. Therefore, it is important to develop an efficient fault diagnosis method by using incompletely identified pass/fail information. Where the incompletely identified pass/fail information means that a failing test block consists of at least one failing test and some passing tests, and all of the tests in passing test blocks are the passing test. In this paper, we propose a method to locate open faults by using incompletely identified pass/fail information. Experimental results for ISCAS'85 and ITC'99 benchmark circuits show that the number of candidate faults becomes less than 5 in many cases.

Yamazaki, Koji; Takamatsu, Yuzo

168

Optimizing automated gas turbine fault detection using statistical pattern recognition  

NASA Astrophysics Data System (ADS)

A method enabling the automated diagnosis of Gas Turbine Compressor blade faults, based on the principles of statistical pattern recognition is initially presented. The decision making is based on the derivation of spectral patterns from dynamic measurements data and then the calculation of discriminants with respect to reference spectral patterns of the faults while it takes into account their statistical properties. A method of optimizing the selection of discriminants using dynamic measurements data is also presented. A few scalar discriminants are derived, in such a way that the maximum available discrimination potential is exploited. In this way the success rate of automated decision making is further improved, while the need for intuitive discriminant selection is eliminated. The effectiveness of the proposed methods is demonstrated by application to data coming from an Industrial Gas Turbine while extension to other aspects of Fault Diagnosis is discussed.

Loukis, E.; Mathioudakis, K.; Papailiou, K.

1992-06-01

169

State Variable Method of Fault Tree Analysis.  

National Technical Information Service (NTIS)

The current technique of Fault Tree Analysis (FTA) generally employs computer codes that calculate the minimal cut sets of the Boolean function, where each cut set comprises basic initiator events (roots) whose intersection implies the occurrence of a TOP...

R. J. Bartholomew H. K. Knudsen G. A. Whan

1984-01-01

170

Application of wavelet to gearbox vibration signals for fault detection  

Microsoft Academic Search

The method of de-noising by wavelet transformation and the basic theory of wavelet transformation based on threshold de-noising are introduced in this paper, the characteristics of noise under the wavelet decomposition are discussed, and the gear fault diagnosis of a gearbox is studied through the wavelet analysis. Experiment result demonstrates that this method can remove the strong noise and extract

Yanping Cai; Yanping He; Aihua Li; Jinru Zhao; Tao Wang

2010-01-01

171

Fault detection of networked control systems with network-induced delay  

Microsoft Academic Search

Problems related to the fault detection of networked control systems are studied. The influence of network-induced delay on conventional observer based fault detection systems designed without considering it is first evaluated, then a parity relation based fault detection system robust to that kind of delay is proposed and studied.

Hao Ye; S. X. Ding

2004-01-01

172

Comparison of different fault detection algorithms for active body control components: automotive suspension system  

Microsoft Academic Search

Fault detection is increasingly an essential part of vehicle development. Integrating such fault detection subsystems raises the reliability, maintainability, and safety of automobile components. Until now, the suspension system was not a safety-critical component, but with the introduction of global chassis control systems this system is getting more important. Therefore, the paper presents fault detection algorithms for the suspension system.

Marcus Borner; Mina Zele; Rolf Isermann

2001-01-01

173

A Fault Line-Selection Method of Hybrid Cable-Overhead Line in Distribution Network Based on Morphology Filter and Hilbert-Huang Transform  

Microsoft Academic Search

While the hybrid transmission lines of distribution network occur the single line to ground faults, a fault line detecting method with HHT detective then compare the phase relation based on the phase relation of zero sequence current between fault line and unfault line is reverse. A morphological filter is first developed to filter noise in transient zero sequence currents. Applying

Shu Hong-Chun; Zhao Wen-Yuan

2009-01-01

174

Detection of Rotor Faults in Brushless DC Motors Operating Under Nonstationary Conditions  

Microsoft Academic Search

There are several applications where the motor is operating in continuous nonstationary operating conditions. Actuators and servo motors in the aerospace and transportation industries are examples of this kind of operation. Detection of faults in such applications is, however, challenging because of the need for complex signal processing techniques. Two novel methods using windowed Fourier ridges and Wigner-Ville-based distributions are

Satish Rajagopalan; José M. Aller; José A. Restrepo; Thomas G. Habetler; Ronald G. Harley

2006-01-01

175

Application of model-based fault detection to a brushless DC motor  

Microsoft Academic Search

In comparison to classical DC motors, brushless DC motors are very reliable, Nevertheless, they can also fail, caused by, e.g., overheating or mechanical wear. This paper proposes a parameter estimation technique for fault detection on this type of motor. Simply by measuring the motor's input and output signals, its parameters can be estimated. This method is based on a mathematical

Olaf Moseler; Rolf Isermann

2000-01-01

176

An unsupervised, on-line system for induction motor fault detection using stator current monitoring  

Microsoft Academic Search

A new method for online induction motor fault detection is presented in this paper. This system utilizes artificial neural networks to learn the spectral characteristics of a good motor operating online. This learned spectrum may contain many harmonics due to the load which correspond to normal operating conditions. In order to reduce the number of harmonics which are continuously monitored

R. R. Schoen; B. K. Lin; T. G. Habetler; J. H. Schlag; S. Farag

1995-01-01

177

Insulation fault detection in a PWM controlled induction motor-experimental design and preliminary results  

Microsoft Academic Search

To investigate feature extraction methods for early detection of insulation degradation in low voltage (under 600 V), 3-phase, PWM controlled induction motors, a series of seeded fault tests was planned on a 50 HP, 440 V motor. In this paper, the background and rationale for the test plan are described. The instrumentation and test plan are then detailed. Finally, preliminary

J. Wang; S. McInerny; T. Haskew

2000-01-01

178

Detection of incipient and low current faults in electric distribution systems  

NASA Astrophysics Data System (ADS)

Research at Texas A & M in incipient fault detection is reviewed, and the digital and analytical techniques used to discriminate faults from normal system activity are described. The results of staged fault tests are reviewed and detection approaches are presented. The application of these techniques to spaceborne power systems is discussed. It is concluded that the application of these approaches to spaceborne power system fault detection is possible and valuable.

Aucoin, B. Michael; Russell, B. Don

179

Fiber-Optics-Based Fault Detection in Power Systems  

Microsoft Academic Search

A fiber-optics-based sensing network applicable for fault detection in power system is presented. The proposed scheme is secure and immune from interferences. At each monitoring location, passive rugged fiber-Bragg-grating-based sensors are deployed. They use fast and compact magnetostrictive transducers instead of current or potential transformers to translate current-induced magnetic field into optical signal. These sensors can be compensated for temperature

Chiu T. Law; Kalu Bhattarai; David C. Yu

2008-01-01

180

Recent case studies in bearing fault detection and prognosis  

Microsoft Academic Search

This paper updates current efforts by the authors to develop fully-automated, online incipient fault detection and prognosis algorithms for drivetrain and engine bearings. The authors have developed and evolved ImpactEnergytrade, a feature extraction and analysis driven system that integrates high frequency vibration\\/acoustic emission data, collected using accelerometers and other sensors such as a laser interferometer to assess the health of

Carl S. Byington; P. E. Rolf Orsagh; Pattada Kallappa; Jeremy Sheldon; Michael DeChristopher; Sanket Amin; Jason Hines

2006-01-01

181

Performance metrics for fault detection and isolation filters  

Microsoft Academic Search

Fault detection and isolation (FDI) filters are typically synthesized for open-loop or closed-loop systems. The controller affects the FDI filter performance in the closed-loop. Performance metrics for FDI filters are proposed to assess filter performance and controller-filter interaction in the presence of uncertain dynamics in the closed-loop. The role of controller's robustness to plant uncertainty in FDI filter performance is

Rohit Pandita; Jozsef Bokor; Gary Balas

2011-01-01

182

Information criteria for residual generation and fault detection and isolation  

Microsoft Academic Search

Using an information point of view, we discuss deterministic versus stochastic tools for residual generation and evaluation for fault detection and isolation (FDI) in linear time-invariant (LTI) state-space systems. In both types of approaches to off-line FDI, residual generation can be viewed as the design of a linear transformation of a Gaussian vector (the finite-window input-adjusted observations). Several statistical isolation

Michéle Basseville

1997-01-01

183

Fault Detection of Gearbox from Inverter Signals Using Advanced Signal Processing Techniques  

NASA Astrophysics Data System (ADS)

The gear faults are time-localized transient events so time-frequency analysis techniques (such as the Short-Time Fourier Transform, Wavelet Transform, motor current signature analysis) are widely used to deal with non-stationary and nonlinear signals. Newly developed signal processing techniques (such as empirical mode decomposition and Teager Kaiser Energy Operator) enabled the recognition of the vibration modes that coexist in the system, and to have a better understanding of the nature of the fault information contained in the vibration signal. However these methods require a lot of computational power so this paper presents a novel approach of gearbox fault detection using the inverter signals to monitor the load, rather than the motor current. The proposed technique could be used for continuous monitoring as well as on-line damage detection systems for gearbox maintenance.

Pislaru, C.; Lane, M.; Ball, A. D.; Gu, F.

2012-05-01

184

Geophysical methods applied to fault characterization and earthquake potential assessment in the Lower Tagus Valley, Portugal  

NASA Astrophysics Data System (ADS)

The study region is located in the Lower Tagus Valley, central Portugal, and includes a large portion of the densely populated area of Lisbon. It is characterized by a moderate seismicity with a diffuse pattern, with historical earthquakes causing many casualties, serious damage and economic losses. Occurrence of earthquakes in the area indicates the presence of seismogenic structures at depth that are deficiently known due to a thick Cenozoic sedimentary cover. The hidden character of many of the faults in the Lower Tagus Valley requires the use of indirect methodologies for their study. This paper focuses on the application of high-resolution seismic reflection method for the detection of near-surface faulting on two major tectonic structures that are hidden under the recent alluvial cover of the Tagus Valley, and that have been recognized on deep oil-industry seismic reflection profiles and/or inferred from the surface geology. These are a WNW ESE-trending fault zone located within the Lower Tagus Cenozoic basin, across the Tagus River estuary (Porto Alto fault), and a NNE SSW-trending reverse fault zone that borders the Cenozoic Basin at the W (Vila Franca de Xira Lisbon fault). Vertical electrical soundings were also acquired over the seismic profiles and the refraction interpretation of the reflection data was carried out. According to the interpretation of the collected data, a complex fault pattern disrupts the near surface (first 400 m) at Porto Alto, affecting the Upper Neogene and (at least for one fault) the Quaternary, with a normal offset component. The consistency with the previous oil-industry profiles interpretation supports the location and geometry of this fault zone. Concerning the second structure, two major faults were detected north of Vila Franca de Xira, supporting the extension of the Vila Franca de Xira Lisbon fault zone northwards. One of these faults presents a reverse geometry apparently displacing Holocene alluvium. Vertical offsets of the Holocene sediments detected in the studied geophysical data of Porto Alto and Vila Franca de Xira Lisbon faults imply minimum slip rates of 0.15 0.30 mm/year, three times larger than previously inferred for active faults in the Lower Tagus Valley and maximum estimates of average return periods of 2000 5000 years for M 6.5 7 co-seismic ruptures.

Carvalho, João; Cabral, João; Gonçalves, Rui; Torres, Luís; Mendes-Victor, Luís

2006-06-01

185

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

186

Detecting Aseismic Fault Slip and Magmatic Intrusion From Seismicity Data  

NASA Astrophysics Data System (ADS)

Seismicity triggered by aseismic deformation, such as magmatic intrusions or afterslip, can be used to detect the occurrence of these otherwise difficult to observe processes. Recent studies suggest that aseismic deformation can trigger large amounts of seismicity in a variety of plate tectonic settings. We have developed a new technique that takes advantage of this triggered seismicity to estimate the time-history of aseismic stressing rate on a fault- zone by combining the rate and state dependent friction and the Epidemic Type Aftershock Sequence (ETAS) models of seismicity-rate [ Dieterich, 1994; Ogata, 1988]. In the rate-state model, the integration of an observed seismicity rate results in an estimate of the stress rate acting in a given space-time window. However, the seismicity rate observed in any catalog comes from 3 primary sources: coseismically-triggered seismicity (aftershocks), tectonically-triggered seismicity (i.e., from long-term tectonic loading), and aseismically-triggered seismicity (e.g., from dike intrusion, aseismic slip transients, or fluid migration). In catalogs dominated by directly triggered aftershocks (i.e., ETAS branching ratios >~0.7), the coseismically-triggered seismicity rate will be much larger than the aseismically-triggered rate and will dominate the estimate of stressing-rate, obscuring the aseismic transient of interest if the rate-state method is applied directly. The challenge therefore lies in isolating the aseismically-triggered seismicity rate from the coseismically-triggered seismicity rate. The ETAS model [ Ogata, 1988] provides a natural way to separate the aseismic and coseismic seismicity rates, as the ETAS parameter ? essentially reflects the aseismically-triggered rate (as well as the background tectonically-triggered rate). To develop a method that can resolve the magnitude and time history of aseismic stress transients even in high branching ratio regions, we combine the rate-state and ETAS models into a single data assimilation algorithm. For a given earthquake catalog, we produce maximum likelihood estimates of the ETAS parameters and use an extended Kalman filter to estimate the temporal evolution of the underlying state variables (stress, stress rate and ? in the Dieterich formulation). We have tested the algorithm with a number of synthetic catalogs and can successfully detect order-of-magnitude changes in stressing rate. Additionally, we can detect large fault creep events detected independently from geodetic data. Ultimately, we aim to map spatial as well as temporal variations in aseismic stressing rates from seismicity data. With this tool we can then identify the space-time evolution of such processes as afterslip, fluid migration, or magmatic intrusion. Moreover, algorithms that can detect when aseismic transients are occurring should have direct applications in real-time seismicity and hazard forecasts.

Llenos, A. L.; McGuire, J. J.

2007-12-01

187

Fault diagnosis using hybrid artificial intelligent methods  

Microsoft Academic Search

This paper presents genetic-based neural networks (GNNs) for fault diagnosis of power transformers. The GNNs automatically tune the network parameters, connection weights and bias terms of the neural networks, to yield the best model according to the proposed genetic algorithm. Due to the global search capabilities of the genetic algorithm and the highly nonlinear mapping nature of the neural networks,

Yann-Chang Huang; Chao-Ming Huang; Huo-Ching Sun; Yi-Shi Liao

2010-01-01

188

Dynamic threshold generators for robust fault detection in linear systems with parameter uncertainty  

Microsoft Academic Search

The problem of developing robust thresholds for fault detection is addressed. An inequality for the solution of a linear system with uncertain parameters is provided and is shown to be a valuable tool for developing dynamic threshold generators for fault detection. Such threshold generators are desirable for achieving robustness against model uncertainty in combination with sensitivity to small faults.The usefulness

Andreas Johansson; Michael Bask; Torbjörn Norlander

2006-01-01

189

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

Microsoft Academic Search

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

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

2001-01-01

190

Wavelet transform based relay algorithm for the detection of stochastic high impedance faults  

Microsoft Academic Search

High impedance faults (HIF) are faults which are difficult to detect by overcurrent protection relays. This paper presents a practical pattern recognition based algorithm for electric distribution high impedance fault detection. The scheme recognizes the distortion of the voltage and current waveforms caused by the arcs usually associated with HIF. The analysis using discrete wavelet transform (DWT) yields three phase

T. M. Lai; L. A. Snider; E. Lo

2006-01-01

191

A Low Cost circuit level fault detection technique to Full Adder design  

Microsoft Academic Search

This paper proposes a Low Cost circuit level Fault Detection technique called LCFD for a one-bit Full Adder (FA) as the basic element of adder circuits. To measure the fault detection coverage of the proposed technique, we conduct an exhaustive circuit level fault injection experiment on all susceptible nodes of a FA. Experimental results show that the LCDF technique can

S. H. Mozafari; M. Fazeli; S. Hessabi; S. G. Miremadi

2011-01-01

192

Feature Extraction Method in Fault Diagnosis Based on Wavelet Fuzzy Network for Power System Rotating Machinery  

Microsoft Academic Search

A new combined fault diagnosis approach for turbo-generator set based on wavelet fuzzy network is proposed. The wavelet transform is used to extract fault characteristics and neural network is used to diagnose the faults. To improve the performance of applying traditional fault diagnosis method to the vibrant faults, a novel method based on the statistic rule is brought forward to

Kang Shanlin; Pang Peilin; Fan Feng; Ding Guangbin

2007-01-01

193

Construction and evaluation of fault detection network for signal validation  

SciTech Connect

The paper presents a methodology which performs evaluation and construction of a sensor failure detection network for nuclear power plant signal validation. The network is arranged in a fault tree structure which consists of sensors, mathematical models for sensor relations and decision/estimators derived form parity relations. The evaluation scheme performs a logic state analysis to categorize critical signals and the associated sensors. The construction scheme cooperates with the evaluation scheme to build a detection network automatically using a rule-based algorithm. The package is implemented on a microcomputer and is demonstrated for the nuclear steam supply system of a PWR.

Ning, J.N.; Chou, H.P. (Dept. of Nuclear Engineering, National Tsing Hua Univ., Hsinchu (Taiwan, Province of China))

1992-08-01

194

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

195

Adaptive Monitoring, Fault Detection and Diagnostics, and Prognostics System for the IRIS Nuclear Plant.  

National Technical Information Service (NTIS)

Ideally, health monitoring of new, complex engineering systems should occur from initial operation to decommissioning. Health monitoring typically involves a suite of modules, including system monitoring, fault detection, fault diagnostics, and system pro...

J. Coble J. W. Hines M. Humberstone

2010-01-01

196

Application of an improved kurtogram method for fault diagnosis of rolling element bearings  

NASA Astrophysics Data System (ADS)

Kurtogram, due to the superiority of detecting and characterizing transients in a signal, has been proved to be a very powerful and practical tool in machinery fault diagnosis. Kurtogram, based on the short time Fourier transform (STFT) or FIR filters, however, limits the accuracy improvement of kurtogram in extracting transient characteristics from a noisy signal and identifying machinery fault. Therefore, more precise filters need to be developed and incorporated into the kurtogram method to overcome its shortcomings and to further enhance its accuracy in discovering characteristics and detecting faults. The filter based on wavelet packet transform (WPT) can filter out noise and precisely match the fault characteristics of noisy signals. By introducing WPT into kurtogram, this paper proposes an improved kurtogram method adopting WPT as the filter of kurtogram to overcome the shortcomings of the original kurtogram. The vibration signals collected from rolling element bearings are used to demonstrate the improved performance of the proposed method compared with the original kurtogram. The results verify the effectiveness of the method in extracting fault characteristics and diagnosing faults of rolling element bearings.

Lei, Yaguo; Lin, Jing; He, Zhengjia; Zi, Yanyang

2011-07-01

197

Time Series for Fault Detection in AN Industrial Pilot Plant  

NASA Astrophysics Data System (ADS)

Forecasting the evolution of industrial processes can be useful to discover faults. Several techniques based on analysis of time series are used to forecast the evolution of certain critical variables; however, the amount of variables makes difficult the analysis. In this way, the use of dimensionality reduction techniques such as the SOM (Self-Organizing Map) allows us to work with less data to determine the evolution of the process. SOM is a data mining technique widely used for supervision and monitoring. Since the SOM is projects data from a high dimensional space into a 2-D, the SOM reduces the number of variables. Thus, time series with the variables of the low dimensional projection can be created to make easier the prediction of future values in order to detect faults.

Morán, Antonio; Fuertes, Juan J.; Alonso, Serafín; Del Canto, Carlos; Domínguez, Manuel

2012-10-01

198

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

199

A Method for Constructing Fault Trees from AADL Models  

Microsoft Academic Search

\\u000a System safety analysis based on fault tree has been widely used for providing assurance to the stringent safety requirement\\u000a of safety-critical systems. Generating fault trees from models described in AADL, a promising standard language for modeling\\u000a complicated embedded system, would realize the automation of system safety analysis which is traditionally performed manually.\\u000a This paper proposes a whole method for constructing

Yue Li; Yi-an Zhu; Chun-yan Ma; Meng Xu

200

Aircraft applications of fault detection and isolation techniques  

NASA Astrophysics Data System (ADS)

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

Marcos Esteban, Andres

201

Detection and Diagnosis of Incipient Faults in Heavy-Duty Diesel Engines  

Microsoft Academic Search

This paper proposes a new methodology for detecting and diagnosing faults found in heavy-duty diesel engines based upon spectrometric analysis of lubrication samples and is compared against a conventional method, the redline limits, which is utilized in a number of major laboratories in the U.K. and across Europe. The proposed method applies computational power to a well-known maintenance technique and

Ian Morgan; Honghai Liu; Bernardo Tormos; Antonio Sala

2010-01-01

202

Customized wavelet denoising using intra- and inter-scale dependency for bearing fault detection  

Microsoft Academic Search

Bearing fault detection is a challenging task, especially at the incipient stage. Wavelet denoising is widely recognized as an effective tool for signal processing and feature extraction. The wavelet denoising method by incorporating neighboring coefficients (NeighCoeff), which is proposed by Cai and Silverman, gives the better results than the traditional term-by-term approaches. However, this method only exploits intra-scale dependency of

Li Zhen; He Zhengjia; Zi Yanyang; Wang Yanxue

2008-01-01

203

Fault detection and diagnosis of a gearbox in marine propulsion systems using bispectrum analysis and artificial neural networks  

NASA Astrophysics Data System (ADS)

A marine propulsion system is a very complicated system composed of many mechanical components. As a result, the vibration signal of a gearbox in the system is strongly coupled with the vibration signatures of other components including a diesel engine and main shaft. It is therefore imperative to assess the coupling effect on diagnostic reliability in the process of gear fault diagnosis. For this reason, a fault detection and diagnosis method based on bispectrum analysis and artificial neural networks (ANNs) was proposed for the gearbox with consideration given to the impact of the other components in marine propulsion systems. To monitor the gear conditions, the bispectrum analysis was first employed to detect gear faults. The amplitude-frequency plots containing gear characteristic signals were then attained based on the bispectrum technique, which could be regarded as an index actualizing forepart gear faults diagnosis. Both the back propagation neural network (BPNN) and the radial-basis function neural network (RBFNN) were applied to identify the states of the gearbox. The numeric and experimental test results show the bispectral patterns of varying gear fault severities are different so that distinct fault features of the vibrant signal of a marine gearbox can be extracted effectively using the bispectrum, and the ANN classification method has achieved high detection accuracy. Hence, the proposed diagnostic techniques have the capability of diagnosing marine gear faults in the earlier phases, and thus have application importance.

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

2011-03-01

204

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

205

Stator-Interturn-Fault Detection of Doubly Fed Induction Generators Using Rotor-Current and Search-Coil-Voltage Signature Analysis  

Microsoft Academic Search

A novel technique for detecting stator interturn faults in a doubly fed induction generator (DFIG) is proposed by analyzing its rotor current and search-coil voltage. So far, fault-diagnostic techniques proposed for stator-interturn-fault detection in DFIGs are based on analysis of stator current or vibration of generator. Results from these methods are ambiguous because they either fail to account for condition

Dhaval Shah; Subhasis Nandi; Prabhakar Neti

2009-01-01

206

Improved Condition Monitoring System for Induction Machines Using a Model-Based Fault Detection Approach  

Microsoft Academic Search

Due to their reliability, robustness and simple construction squirrel-cage induction motors are widely used in industry. However, faults like broken rotor bars, rotor eccentricity, bearing and winding faults can occur during normal operation of the motor. Techniques for the detection of these faults have been researched since more than ten years. Although hundreds of papers are published year by year

Loránd SZABÓ; Károly Ágoston BIRÓ; Dénes FODOR

207

An intelligent sensor and actuator fault detection and isolation scheme for nonlinear systems  

Microsoft Academic Search

This paper presents a robust fault detection and isolation (FDI) scheme for a general nonlinear system using a neural network-based observer. Both actuator and sensor faults are considered. The nonlinear system is subject to state and sensor uncertainties and disturbances. Two recurrent neural networks are employed to identify general unknown actuator and sensor faults. The neural network weights are updated

H. A. Talebi; K. Khorasani

2007-01-01

208

Fault detection, diagnosis, and data-driven modeling in HVAC chillers  

Microsoft Academic Search

Heating, Ventilation and Air Conditioning (HVAC) systems constitute the largest portion of energy consumption equipment in residential and commercial facilities. Real-time health monitoring and fault diagnosis is essential for reliable and uninterrupted operation of these systems. Existing fault detection and diagnosis (FDD) schemes for HVAC systems are only suitable for a single operating mode with small numbers of faults, and

Setu M. Namburu; Jianhui Luo; Mohammad Azam; Kihoon Choi; Krishna R. Pattipati

2005-01-01

209

Gyro -based maximum-likelihood thruster fault detection and identification1  

Microsoft Academic Search

When building smaller, less expensive spacecraft, there is a need for intelligent fault tolerance vs. increased hardware redundancy. If fault tolerance can be achieved using existing navigation sensors, cost and vehicle complexity can be reduced. A maximum -likelihood-based approach to thruster fault detection and identification (FDI) for spacecraft is developed here and applied in simulation to the X-38 space vehicle.

Edward Wilson; Chris Lages; Robert Mah

210

Gyro-based maximum-likelihood thruster fault detection and identification  

Microsoft Academic Search

When building smaller, less expensive spacecraft, there is a need for intelligent fault tolerance vs. increased hardware redundancy. If fault tolerance can be achieved using existing navigation sensors, cost and vehicle complexity can be reduced. A maximum-likelihood-based approach to thruster fault detection and identification (FDI) for spacecraft is developed here and applied in simulation to the X-38 space vehicle. The

Edward Wilson; Chris Lages; Robert Mah

2002-01-01

211

Fault detection and isolation of a two non-interacting tanks system using partial PCA  

Microsoft Academic Search

In this paper, the concept of principal component analysis (PCA) has been used to generate a residual space to detect an actuator and a sensor fault in a two non-interacting tank system. Since there is only one residual vector in the present case, isolation of faults using PCA is not feasible. For isolation of the fault, partial PCA based structured

N. Bhattacharjee; B. K. Roy

2010-01-01

212

Fault Detection And Identification With Application To Advanced Vehicle Control Systems  

Microsoft Academic Search

This report continues work on the design of a health monitoring system for automated vehicles. The approach is designed to fuse data from dissimilar instruments using modeled dynamic relationships and fault detection and identification filters. Issues relating to sensor models, output separability, steady-state fault persistence and the spectral content of sensor faults are considered.

Randal K. Douglas; Walter H. Chung; Durga P. Malladi; Robert H. Chen; D. Lewis Mingori

1997-01-01

213

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

PubMed

A proposed signal processing technique for incipient real time bearing fault detection based on kurtogram analysis is presented in this paper. The kurtogram is a fourth-order spectral analysis tool introduced for detecting and characterizing non-stationarities in a signal. This technique starts from investigating the resonance signatures over selected frequency bands to extract the representative features. The traditional spectral analysis is not appropriate for non-stationary vibration signal and for real time diagnosis. The performance of the proposed technique is examined by a series of experimental tests corresponding to different bearing conditions. Test results show that this signal processing technique is an effective bearing fault automatic detection method and gives a good basis for an integrated induction machine condition monitor. PMID:23145702

Tafinine, Farid; Mokrani, Karim

2012-11-01

214

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

215

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

216

IEEE issues high-impedance fault detection report  

SciTech Connect

High-impedance faults (HIF) on distribution circuits create unique challenges for the protection engineer. In response to this problem, Working Group D15 of the Institute of Electrical and Electronics Engineers (IEEE) Power System Relaying Committee had issued a report on HIF detection technology. A ground HIF occurs when a primary conductor makes unwanted electrical contact with a road surface, sidewalk, sod, tree limb, or with some other surface or object which restricts the flow of fault current to a level below that which can be reliably detected by conventional overcurrent devices. Often this situation leaves a conductor energized on the ground and poses a danger to the public. No all unsafe conditions involve an HIF. For example, a conductor may sag to a point near the ground or may break but still not touch a grounded element or another conductor. An HIF does not have to involve a path to ground. In fact, whether a ground is involved does not matter to an HIF detector. For example, a tree limb may bridge two-phase conductors.

Beaty, W. [ed.

1996-10-01

217

An adaptive SK technique and its application for fault detection of rolling element bearings  

NASA Astrophysics Data System (ADS)

In this paper, we propose an adaptive spectral kurtosis (SK) technique for the fault detection of rolling element bearings. The primary contribution is adaptive determination of the bandwidth and center frequency. This is implemented with successive attempts to right-expand a given window along the frequency axis by merging it with its subsequent neighboring windows. Influence of the parameters such as the initial window function, bandwidth and window overlap on the merged windows as well as how to choose those parameters in practical applications are explored. Based on simulated experiments, it can be found that the proposed technique can further enhance the SK-based method as compared to the kurtogram approach. The effectiveness of the proposed method in fault detection of the rolling element bearings is validated using experimental signals.

Wang, Yanxue; Liang, Ming

2011-07-01

218

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

PubMed Central

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

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

2013-01-01

219

Anomaly detection: A robust approach to detection of unanticipated faults  

Microsoft Academic Search

This paper introduces a methodology to detect as early as possible with specified degree of confidence and prescribed false alarm rate an anomaly or novelty (incipient failure) associated with critical components\\/subsystems of an engineered system that is configured to monitor continuously its health status. Innovative features of the enabling technologies include a Bayesian estimation framework, called particle filtering, that employs

Bin Zhang; Chris Sconyers; Carl Byington; Romano Patrick; Marcos Orchard; George Vachtsevanos

2008-01-01

220

GLRT Based Fault Detection in Sensor Drift Monitoring System  

NASA Astrophysics Data System (ADS)

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

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

221

Instrument fault detection and isolation: state of the art and new research trends  

Microsoft Academic Search

This paper presents the current state-of-the-art of residual generation techniques adopted in instrument fault detection and isolation. Both traditional and innovative methods are described with their advantages and their limits. The improvement of analytical redundancy technique performances for better dealing with high-dynamics systems and\\/or with online applications is pointed out as the most interesting need to focus the research efforts

Giovanni Betta; Antonio Pietrosanto

2000-01-01

222

A new PMU-based fault detection\\/location technique for transmission lines with consideration of arcing fault discrimination-part I: theory and algorithms  

Microsoft Academic Search

A new fault detection\\/location technique with consideration of arcing fault discrimination based on phasor measurement units for extremely high voltage\\/ultra-high voltage transmission lines is presented in this two-paper set. Part I of this two-paper set is mainly aimed at theory and algorithm derivation. The proposed fault detection technique for both arcing and permanent faults is achieved by a combination of

Ying-Hong Lin; Chih-Wen Liu; Ching-Shan Chen

2004-01-01

223

Fault detection and isolation in aircraft gas turbine engines. Part 2: validation on a simulation test bed  

Microsoft Academic Search

The first part of this two-part paper, which is a companion paper, has developed a novel concept of fault detection and isolation (FDI) in aircraft gas turbine engines. The FDI algorithms are built upon the statistical pattern recognition method of symbolic dynamic filtering (SDF) that is especially suited for real-time detection and isolation of slowly evolving anomalies in engine components,

S Sarkar; S Gupta; K Mukherjee; A Ray

2008-01-01

224

The integration of machine fault detection into an indirect field oriented induction machine drive control scheme-the Vienna Monitoring Method  

Microsoft Academic Search

This paper proposes a new approach for an on-line induction machine monitoring scheme tailored for variable speed drives. As the application of the commonly employed spectrum analysis techniques is complicated by the inverter drives inherent frequency variation, the Vienna Monitoring Method avoids any frequency analysis and observes instead the machine state with the help of on-line models. The key for

R. S. Wieser; M. Schagginger; C. Kral; F. Pirker

1998-01-01

225

Hazard detection and mitigation system and method  

US Patent & Trademark Office Database

Provided is a system and method for providing monitoring of hazardous materials, including collecting environmental data via one or more sensors directed at the hazardous materials source, the environmental data including one or more environmentally detectable reference points; comparing the environmental data to a set of current ambient conditions, the environmental data detectable in a reference frame by the one or more sensors directed at the hazardous materials source, the reference frame including at least one of the one or more environmentally detectable reference points; performing an alert determination according to the comparison of the environmental data to the set of ambient conditions; and transmitting the alert determination to an existing fault detection system for the hazardous material source to enable the existing fault detection system to override a status rating of the hazardous materials source. Also included is a sensing system including modules operating on a processor to perform the method.

2012-04-17

226

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

227

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

228

Feeder line fault detection in the Indian MST radar  

NASA Astrophysics Data System (ADS)

The MST Radar uses semi-rigid cables and directional couplers for feeding power from the transmitters to the antennas. Coaxial directional couplers used in the feeder network are made of aluminum. Since the feeder network is exposed to the sun, it heats up and expands its length. At night the feeder network cools down and the coaxial directional couplers contract in length. Due to the expansion and contraction, sometimes it is found that the contact between the center conductors of two consecutive directional couplers are separated and thereby make part of the antenna array ineffective. Contact between directional couplers may be broken also due to oxidation of aluminum. Although steps are taken to remove this problem using anti-corrosive grease, it is worthwhile to monitor the 'health' of the feeder line from time to time. A measurement scheme is suggested which helps to detect the faulty contact of the directional couplers and the location of the fault.

Sarkar, B. K.

1993-08-01

229

Transition Delay Fault Testing of Microprocessors by Spectral Method  

Microsoft Academic Search

We introduce a novel spectral method of delay test generation for microprocessors at the register-transfer level (RTL). Vectors are first generated by an available ATPG tool for transition faults on inputs and outputs of the RTL modules of the circuit. These vectors are analyzed using Hadamard matrices to obtain Walsh function components and random noise levels for each primary input.

Nitin YogiandVishwani; Vishwani D. Agrawal

2007-01-01

230

Pulsating parameter method for fault diagnosis for a hydraulic pump  

Microsoft Academic Search

The authors present the pulsating parameter method in the frequency domain using two parameters of the pulsating model of an axial piston pump as major monitoring parameters to diagnose the fault of the pump. In order to apply the theory of transmission in a hydraulic pipeline to identify the model, a whole set of algorithms is also developed. Compared with

S. Liu; J. C. Hung

1991-01-01

231

Hybrid time-frequency domain analysis for inverter-fed induction motor fault detection  

Microsoft Academic Search

The detection of faults in an induction motor is important as a part of preventive maintenance. Stator current is one of the most popular signals used for utility-supplied induction motor fault detection as a current sensor can be installed nonintrusively. In variable speeds operation, the use of an inverter to drive the induction motor introduces noise into the stator current

T. W. Chua; W. W. Tan; Z.-X. Wang; C. S. Chang

2010-01-01

232

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

Microsoft Academic Search

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

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

1996-01-01

233

A case-based reasoning approach for fault detection state in bridges assessment  

Microsoft Academic Search

Case-based reasoning (CBR) systems use previous knowledge stored in data bases to solve current issues. Nowadays, CBR approach is widely used in different areas with good results. Such an area is system diagnose and fault detection. In this paper, we suggest a new approach, based on CBR, for fault detection of reinforced concrete bridges on polluted area. Nowadays the bridge

Aurelian Ignat-Coman; Dorin Isoc; A. Joldis; I. Gaziuc

2008-01-01

234

Fault Detection in a Multistage Gearbox by Demodulation of Motor Current Waveform  

Microsoft Academic Search

Demodulation of vibration signal to detect faults in machinery has been a prominent prevalent technique that is discussed by a number of authors. This paper deals with the demodulation of the current signal of an induction motor driving a multistage gearbox for its fault detection. This multistage gearbox has three gear ratios, and thus, three rotating shafts and their corresponding

A. R. Mohanty

2006-01-01

235

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

236

Effects of machine speed on the development and detection of rolling element bearing faults  

Microsoft Academic Search

This research investigates the effects of a variable machine speed on machine vibration and the implications for bearing fault detection. These effects are important to understand because when ignored they can significantly hinder the ability to detect bearing faults. Experimental results verify that a variable machine speed can directly and nonlinearly alter the level of machine vibration. This is due

Jason R. Stack; Thomas G. Habetler; Ronald G. Harley

2003-01-01

237

Multiobjective fault detection observer design for a class of TS fuzzy nonlinear systems  

Microsoft Academic Search

This article presents the design of fault detection fuzzy observer with multiple performance constraints for a class of nonlinear system with Takagi-Sugeno fuzzy form. The multiobjective optimization and consistency analysis are applied to meeting the desirable transient behavior, steady output variance and H¡ index performance requirements. Thus, the rapidity of response to fault detection, robustness to noisy disturbances and sensitivity

Dengfeng Zhang; Xiaodong Han; Hong Wang; Zhiquan Wang

2011-01-01

238

A Fault Diagnostic Method for EFI Engine Based on MATLAB Software Package  

Microsoft Academic Search

At present, the diagnostic instruments used widely here and abroad is not entire, which can not diagnose the mechanical fault without fault code. In order to solve this problem, this paper presents a method for fault diagnosis of electronic fuel injection (EFI) engine using radial basis function (RBF) neural network. By connecting MATLAB software package and ACCESS database, a fault

Du Danfeng; Guo Xiurong; Guan Qiang

2008-01-01

239

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

240

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

PubMed

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

Wang, Huaqing; Chen, Peng

2009-04-01

241

Fault detection in variable speed machinery: Statistical parameterization  

NASA Astrophysics Data System (ADS)

Variable speed machinery presents a particular challenge to automated condition-monitoring systems; changes in speed have a strong relation to the vibration response collected by accelerometers—the effect of which may mask fault conditions in standard condition monitoring techniques. In order to account for the effects of this measurable variable, the vibration response will be segmented into speed bins with a small range of speed. The mean and covariance matrix for the feature vectors in each speed bin will be computed in order to derive a statistical novelty boundary for that bin. Each component of these statistical parameters can then be interpolated or regressed in order to derive boundaries for speed segments where no training data is available. A comparison of the use of a statistical decision boundary and support vector boundaries, whose inputs have been centralized and whitened with these statistical parameters, will reveal a stronger classification approach. These methods were validated on data gathered from an experimental gearbox and motor apparatus operating at variable speeds; the results indicate a high degree of separability between data from healthy and faulted states—providing exceptional classification error.

McBain, Jordan; Timusk, Markus

2009-11-01

242

A modeling method of a high impedance fault in a distribution system using two series time-varying resistances in EMTP  

Microsoft Academic Search

More reliable algorithms for detecting a high impedance fault (HIF) require the voltage and current data at a relaying point instead of a faulted branch when HIF occurs. Thus, an accurate modeling method of HIF is essential for the development of a reliable detecting algorithm. The data should contain the complex characteristics of HIF such as buildup and shoulder as

S. R. Nam; J. K. Park; Y. C. Kang; T. H. Kim

2001-01-01

243

A multi-fault diagnosis method for sensor systems based on principle component analysis.  

PubMed

A model based on PCA (principal component analysis) and a neural network is proposed for the multi-fault diagnosis of sensor systems. Firstly, predicted values of sensors are computed by using historical data measured under fault-free conditions and a PCA model. Secondly, the squared prediction error (SPE) of the sensor system is calculated. A fault can then be detected when the SPE suddenly increases. If more than one sensor in the system is out of order, after combining different sensors and reconstructing the signals of combined sensors, the SPE is calculated to locate the faulty sensors. Finally, the feasibility and effectiveness of the proposed method is demonstrated by simulation and comparison studies, in which two sensors in the system are out of order at the same time. PMID:22315537

Zhu, Daqi; Bai, Jie; Yang, Simon X

2009-12-29

244

The combination method for dependent evidence and its application for simultaneous faults diagnosis  

Microsoft Academic Search

This paper provides a method based on Dezert-Smarandache theory (DSmT) for simultaneous faults diagnosis when evidence is dependent. Firstly, according to the characteristics of simultaneous faults, a frame of discernment is given for both single fault and simultaneous faults diagnosis, the DSmT combination rule applicable to simultaneous faults diagnosis is introduced. Secondly, the dependence of original evidence is classified according

Hai-Na Jiang; Xiao-Bin Xu; Cheng-Lin Wen

2009-01-01

245

An energy kurtosis demodulation technique for signal denoising and bearing fault detection  

NASA Astrophysics Data System (ADS)

Rolling element bearings are commonly used in rotary machinery. Reliable bearing fault detection techniques are very useful in industries for predictive maintenance operations. Bearing fault detection still remains a very challenging task especially when defects occur on rotating bearing components because the fault-related features are non-stationary in nature. In this work, an energy kurtosis demodulation (EKD) technique is proposed for bearing fault detection especially for non-stationary signature analysis. The proposed EKD technique firstly denoises the signal by using a maximum kurtosis deconvolution filter to counteract the effect of signal transmission path so as to highlight defect-associated impulses. Next, the denoised signal is modulated over several frequency bands; a novel signature integration strategy is proposed to enhance feature characteristics. The effectiveness of the proposed EKD fault detection technique is verified by a series of experimental tests corresponding to different bearing conditions.

Wang, Wilson; Lee, Hewen

2013-02-01

246

Detecting FET Stuck-Open Faults in CMOS Latches And Flip-Flops  

Microsoft Academic Search

The authors present evidence that conventional tests cannot detect FET stuck-open faults in several CMOS latches and flip-flops. Examples are given to show that stuck-open faults can change static latches and flip-flops into dynamic devices¿a danger to circuits whose operation requires static memory, since undetected FET stuck-open faults can cause malfunctions. Designs are given for several memory devices in which

Madhukar K. Reddy; Sudhakar M. Reddy

1986-01-01

247

Fault detection and identification based on combining logic and model in a wall-climbing robot  

Microsoft Academic Search

A combined logic- and model-based approach to fault detection and identification (FDI) in a suction foot control system of\\u000a a wall-climbing robot is presented in this paper. For the control system, some fault models are derived by kinematics analysis.\\u000a Moreover, the logic relations of the system states are known in advance. First, a fault tree is used to analyze the

Yong Jiang; Hongguang Wang; Lijin Fang; Mingyang Zhao

2009-01-01

248

Modified chain-code computer vision techniques for interrogation of vibration signatures for structural fault detection  

NASA Astrophysics Data System (ADS)

Vibration testing is a viable method for structural fault diagnosis. Different structural dynamic response variables and parameters that may be considered as candidate objects of interrogation are briefly reviewed. The fault diagnosis process is broken down into three parts, and only the detection process is addressed in this paper. The frequency response function obtained by exciting the structure at a selected reference point is utilized as the preferred form of vibration signature to be used for interrogation. The chain code computer vision technique is modified to evaluate the frequency response function signature as a waveform. Signatures are obtained from a laboratory structure in the form of a ribbed plate, similar to a highway bridge. Cracks are simulated in the structure by cutting through splice plates with a jigsaw. By applying the computer vision technique on the signatures and comparing inspection signatures with benchmark signatures, small cracks are detected consistently. Results of the interrogation are interpreted in a graphical manner. In addition, an automated evaluation technique is presented. The robustness of the technique is verified by contaminating signals with synthetic noise. Successful performance of the technique in the presence of noise indicates the potential for fault diagnosis of large outdoor structures.

Biswas, M.; Pandey, A. K.; Bluni, S. A.; Samman, M. M.

1994-08-01

249

Performance Comparison and Winding Fault Detection of Duplex 2Phase and 3Phase Fault-Tolerant Permanent Magnet Brushless Machines  

Microsoft Academic Search

This paper analyses feasible slot and pole number combinations for multiplex 2-phase and 3-phase fault-tolerant permanent-magnet machines and evaluates their relative merits via a design case study. An effective winding short-circuit detection technique based on search coils wound around the stator teeth is also presented, and its performance is assessed. It is shown that the proposed detection technique can reliably

Jie Chai; Jiabin Wang; Kais Atallah; David Howe

2007-01-01

250

APPLICATION OF WAVELETS TO GEARBOX VIBRATION SIGNALS FOR FAULT DETECTION  

Microsoft Academic Search

The wavelet transform is used to represent all possible types of transients in vibration signals generated by faults in a gearbox. It is shown that the transform provides a powerful tool for condition monitoring and fault diagnosis. The vibration signal from a helicopter gearbox is used to demonstrate the application of the suggested wavelet by a simple computer algorithm. The

W. J. Wang; P. D. McFadden

1996-01-01

251

A Literature Review of IGBT Fault Diagnostic and Protection Methods for Power Inverters  

Microsoft Academic Search

This paper presents a survey on existing methods for fault diagnosis and protection of insulated gate bipolar transistors with special focus on those used in three-phase power inverters. Twenty-one methods for open-circuit faults and ten methods for short-circuit faults are evaluated and summarized, based on their performance and implementation efforts. The gate-misfiring faults and their diagnostic methods are also briefly

Bin Lu; Santosh K. Sharma

2009-01-01

252

A Literature Review of IGBT Fault Diagnostic and Protection Methods for Power Inverters  

Microsoft Academic Search

This paper presents a survey on existing methods for fault diagnosis and protection of IGBT's, with special focus on those used in three-phase power inverters. Twenty one methods for open-circuit faults and ten methods for short-circuit faults are evaluated and summarized, based on their performance and implementation efforts. The gate-misfiring faults and their diagnostic methods are also briefly discussed. Finally,

Bin Lu; Santosh Sharma

2008-01-01

253

Recurrent neuro-fuzzy system for fault detection and isolation in nuclear reactors  

Microsoft Academic Search

This paper presents an application of recurrent neuro-fuzzy systems to fault detection and isolation in nuclear reactors. A general framework is adopted, in which a fuzzification module is linked to an inference module that is actually a neural network adapted to the recognition of the dynamic evolution of process variables and related faults. Process data is fuzzified in order to

Alexandre Evsukoff; Sylviane Gentil

2005-01-01

254

Induction motors' faults detection and localization using stator current advanced signal processing techniques  

Microsoft Academic Search

The knowledge about fault mode behavior of an induction motor drive system is extremely important from the standpoint of improved system design, protection, and fault-tolerant control. This paper addresses the application of motor current spectral analysis for the detection and localization of abnormal electrical and mechanical conditions that indicate, or may lead to, a failure of induction motors. Intensive research

Mohamed El Hachemi Benbouzid; Michelle Vieira; C. Theys

1999-01-01

255

A robust Fault Detection and Isolation scheme with application to magnetorquer type actuators for satellites  

Microsoft Academic Search

This paper presents a robust Fault Detection and Isolation (FDI) scheme for a general nonlinear system using a neural network based observer. The nonlinear system is subject to state and sensor uncertainties and disturbances. A recurrent nonlinear-in-parameters neural network (NLPNN) is employed to identify the general unknown fault. The neural network weights are updated based on a modified backpropagation scheme.

Heidar A. Talebi; Khashayar Khorasani

2007-01-01

256

Integrated scheme for high impedance fault detection in MV distribution system  

Microsoft Academic Search

High impedance fault (HIF) in MV distribution with restricted fault current cannot be detected and cleared by conventional overcurrent relays. HIF exposes great hazard for personal safety and property security. In this paper, an integrated scheme utilizing different features of HIF is presented. Various documented field data has been investigated and summarized to get the most distinctive features of HIF.

Tao Cui; Xinzhou Dong; Zhiqian Bo; S. Richards

2008-01-01

257

Intelligent detection and diagnosis of lightning arrester faults using digital thermovision image processing techniques  

Microsoft Academic Search

This paper describes a methodology that aims to detect and diagnosis faults in lightning arresters, using the thermovision technique. Thermovision is a non-destructive technique used in diverse services of maintenance, having the advantage not to demand the disconnection of the equipment under inspection. It uses a set of neuro-fuzzy networks to achieve the lightning arresters fault classification. The methodology also

Carlos A. Laurentys Almeida; Walmir M. Caminhas; Antonio P. Braga; Vinicius Paiva; Helvio Martins; Rodolfo Torres

2005-01-01

258

THE ENHANCEMENT OF IMPULSIVE NOISE AND VIBRATION SIGNALS FOR FAULT DETECTION IN ROTATING AND RECIPROCATING MACHINERY  

Microsoft Academic Search

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

S. K. Lee; P. R. White

1998-01-01

259

Virtual Sensor Based Fault Detection and Classification on a Plasma Etch Reactor  

Microsoft Academic Search

The SEMATECH sponsored J-88-E project teaming Texas Instruments with NeuroDyne (et al) focused on Fault Detection and Classification (FDC) on a Lam 9600 aluminum plasma etch reactor, used in the process of semiconductor fabrication. Fault classification was accomplished by implementing a series of virtual sensor models which used data from real sensors (Lam Station sensors, Optical Emission Spectroscopy, and RF

Donald Sofge

2007-01-01

260

Detection and isolation of sensor faults on nonlinear processes based on local linear models  

Microsoft Academic Search

The development of a reliable fault detection and isolation (FDI) scheme for nonlinear processes is often time consuming and difficult to achieve due to the complexity of the system. Neural networks and fuzzy models, able to approximate nonlinear dynamic functions offer a powerful tool to cope with this problem. In this paper, a new approach for FDI of sensor faults

P. Belle; Dominik Fussel; Oliver Hecker

1997-01-01

261

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

262

Concurrent Detection of Faults Affecting Energy Harvesting Circuits of Self-Powered Wearable Sensors  

Microsoft Academic Search

We address the problem of the concurrent detection of faults affecting an energy harvesting circuit that powers a wearable biomedical sensor. We analyze the effects of such faults, and we show that they may make it fail in producing the required power supply voltage level for the sensor. We propose a new low cost (in terms of power consumption and

Martin Omaña; Marcin Marzencki; Roberto Specchia; Cecilia Metra; Bozena Kaminska

2009-01-01

263

Fault Activity Investigations in the Lower Tagus Valley (Portugal) With Seismic and Geoelectric Methods  

NASA Astrophysics Data System (ADS)

The Lower Tagus River Valley is located in Central Portugal, and includes a large portion of the densely populated area of Lisbon. It is sited in the Lower Tagus Cenozoic Basin, a tectonic depression where up to 2,000 m of Cenozoic sediments are preserved, which was developed in the Neogene as a compressive foredeep basin related to tectonic inversion of former Mesozoic extensional structures. It is only a few hundred kilometers distant from the Eurasia-Africa plate boundary, and is characterized by a moderate seismicity presenting a diffuse pattern, with historical earthquakes having caused serious damage, loss of lives and economical problems. It has therefore been the target of several seismic hazard studies in which extensive geological and geophysical research was carried out on several geological structures. This work focuses on the application of seismic and geoelectric methods to investigate an important NW-SE trending normal fault detected on deep oil-industry seismic reflection profiles in the Tagus Cenozoic Basin. In these seismic sections this fault clearly offsets horizons that are ascribed to the Upper Miocene. However, due to the poor near surface resolution of the seismic data and the fact that the fault is hidden under the recent alluvial cover of the Tagus River, it was not clear whether it displaced the upper sediments of Holocene age. In order to constrain the fault geometry and kinematics and to evaluate its recent tectonic activity, a few high-resolution seismic reflection profiles were acquired and refraction interpretation of the reflection data was performed. Some vertical electrical soundings were also carried out. A complex fault system was detected, apparently with normal and reverse faulting. The collected data strongly supports the possibility that one of the detected faults affects the uppermost Neogene sediments and very probably the Holocene alluvial sediments of the Tagus River. The evidence of recent activity on this fault, its length (at least 10 km), location in an area with significant historical seismicity, and proximity to Lisbon and other small towns, all indicate that it represents a serious hazard to the study region and so should be considered in the regional seismic hazard evalution.

Carvalho, J. G.; Gonçalves, R.; Torres, L. M.; Cabral, J.; Mendes-Victor, L. A.

2004-05-01

264

Fault Tree and Formal Methods in System Safety Analysis  

Microsoft Academic Search

Fault tree analysis is a traditional deductive safety analysis technique that is applied during the system design stage. However, traditional fault trees often suffer from a lack of formal semantics to check the correctness or consistency of the descriptions. To overcome this limitation, we first propose a formal fault tree construction model in which the correctness of the fault tree

Jianwen Xiang; Kokichi Futatsugi; Yanxiang He

2004-01-01

265

On the Intelligent Fault Diagnosis Method for Marine Diesel Engine  

Microsoft Academic Search

The marine diesel engine is a complex system. Its mapping process of fault diagnosis has multi-fault attributes, which means input and output of fault pattern attribute are the multi-mapping relations. An approach of intelligent fault diagnosis using fuzzy neural networks and genetic algorithms to optimize and train is studied in this paper for this system. The structure and the model

Peng Li; Baoku Su

2008-01-01

266

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

267

Rule based decision support system for single-line fault detection in a delta-delta connected distribution system  

Microsoft Academic Search

Single-line fault detection, faulted feeder identification, fault type classification, fault location and fault impedance estimation, continue to pose a problem to delta-delta connected distribution systems such as the Los Angeles Department of Water and Power (LADWP) which has over 1500 feeder circuits at the 4.8 kV voltage level. This paper describes a rule based decision support (RBDS) system application to

J. A. Momoh; L. G. Dias; T. Thor; D. Laird

1994-01-01

268

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

NASA Astrophysics Data System (ADS)

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

Boutros, Tony; Liang, Ming

2011-08-01

269

A survey of IGBT fault diagnostic methods for three-phase power inverters  

Microsoft Academic Search

Fault diagnostics of power converters have drawn increasing attentions due to the widespread adoption of advanced power control devices, such as motor drives and uninterruptible power supplies. This paper presents a literature survey on existing methods for fault diagnosis and protection of IGBTpsilas, with special focus on those used in three-phase power inverters. Eleven methods for open-circuit faults and ten

Bin Lu; Santosh Sharma

2008-01-01

270

Geodetic detection of active faults in S. California  

Microsoft Academic Search

A new analysis of velocities of geodetic markers straddling the San Andreas Fault System in southern California reveals that interseismic deformation is localized along a dozen sub-parallel narrow belts of high shear strain rate that correlate well with active geologic fault segments and locally with concentrated zones of microseismicity. High shear strain rates (0.3-0.95 mustrain\\/year) are observed northward and southward

Shimon Wdowinski; Yonadav Sudman; Yehuda Bock

2001-01-01

271

Fault detection and analysis of electric generator based on wavelet transform and fuzzy logic technology  

NASA Astrophysics Data System (ADS)

A new method combining wavelet transform with fuzzy theory is proposed to improve the limitation of traditional fault diagnosis technology of electric generator. In order to determine the threshold of each order of wavelet space and the decomposition level adaptively, the statistic rule is brought forward to increase the signal-noise-ratio. The wavelet transform is used to acquire the effective feature components and the proposed fuzzy diagnosis equation is used to complete classify fault pattern. The fault diagnosis model of electric generator is established and the network parameters training are fulfilled by the improved least squares algorithm. The input nodes include the information representing the fault characters. On basis of experiments data to train the fault diagnosis mode, the accurate classification results can be achieved in accordance with expert experience. In view of actual applications, the proposed method can effectively diagnose the fault pattern of electric generator.

Ding, Guangbin; Pang, Peilin

2008-11-01

272

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

273

Integrated intelligent fault detection and diagnosis system and its application in urea synthesis process  

Microsoft Academic Search

Based on the essential requirements of the CIPS, the paper presents an integrated intelligent fault detection and diagnosis system. A urea synthesis process is used as an illustration and the structure, functions and realization are discussed specifically

Cheng Cheng; Huang Dao

2000-01-01

274

Fault detection and isolation using a neofuzzy neuron-based system  

NASA Astrophysics Data System (ADS)

In this paper a fault detection and isolation scheme using a set of Neo fuzzy neurons will be presented. Such neurons use IF-THEN rules for characterizing the synaptic junctions in order to obtain complex nonlinear input/output maps in a simple structure, allowing an improvement of the learning and representation capabilities. As illustrative example, the fault detection scheme in a three interconnected tank system will be presented.

Novoa-Paredes, Darcy; Rivas-Echeverria, Francklin; Bravo-Bravo, Cesar

2001-03-01

275

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

Microsoft Academic Search

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

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

1997-01-01

276

Component-based multi-model approach for fault detection and diagnosis of a centrifugal pump  

Microsoft Academic Search

A model-based approach for fault detection and diagnosis of nonlinear processes is presented. However, the supervision of nonlinear systems is often very difficult in view of the lack of accurate models. Neuro-fuzzy models may help to cope with this problem since they can be trained from measured data. In this paper the application of a multi-model approach for fault detection

Armin Wolfram; Dominik Fussel; Torsten Brune; Rolf Isermann

2001-01-01

277

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

SciTech Connect

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

Wei Qiao

2012-05-29

278

Nucleic acid detection method  

US Patent & Trademark Office Database

A method of detecting a target nucleotide sequence in a nucleic acid molecule, which comprises: (a) binding of an oligonucleotide probe to said nucleic acid molecule; (b) selective labelling of the bound oligonucleotide probe in the presence of said target nucleotide sequence; (c) hybridization of the labelled oligonucleotide to a complementary sequence; and (d) subsequent detection of the label; such methods being suitable for qualitative and quantitative assays of microbiological populations.

Rudi; Knut (Oslo, NO); Jakobsen; Kjetill Sigurd (Olso, NO)

2003-09-09

279

Multigrid contact detection method.  

PubMed

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. PMID:17500829

He, Kejing; Dong, Shoubin; Zhou, Zhaoyao

2007-03-28

280

Study on estimate method of wave velocity and quality factor to fault seals  

Microsoft Academic Search

Based on ultrasonic test of fault rocks, the responses for wave velocity and quality factor (Q value) to lithology, porosity and permeability of fault rocks and mechanical property of faults are studied. In this paper,\\u000a a new quantitative estimate method of fault seals is originally offered. The conclusions are as follows: (1) Wave velocity\\u000a andQ value increase and porosity decreases

Zhensheng Li; Deliang Liu; Bo Liu; Qiang Yang; Jingming Li

2005-01-01

281

Teager energy operator for multi-modulation extraction and its application for gearbox fault detection  

NASA Astrophysics Data System (ADS)

This paper presents a parameter-free and broadband approach to detecting gear faults based on vibration signals. The technique is implemented using the Teager energy operator (TEO). It is shown that this operator can extract amplitude, phase and frequency modulations that are associated with various gear faults. Spectral analysis of the TEO-transformed signal provides the necessary information for fault detection. To improve the effectiveness of the proposed technique, we also devised a wavelet de-noising step based on online threshold estimation. In the de-noising step, the threshold estimation is performed through a frequency domain median absolute deviation (FMAD) scheme. The proposed fault detection technique is tested on simulated as well as experimental data acquired from a single-stage bevel gearbox and a two-stage parallel gearbox. US patent pending (serial number: 12/631,528).

Soltani Bozchalooi, I.; Liang, Ming

2010-07-01

282

Diagnosis of Stator-Winding-Turn Faults of Induction Motor by Direct Detection of Negative-Sequence Currents  

NASA Astrophysics Data System (ADS)

In an AC motor, the quick detection of an initially small fault is important for preventing any consequent large fault. Various detection approaches have been proposed in previous papers, for example, by the Park vector (PV), AI techniques, wavelet analysis, and negative-sequence analysis. This paper proposes a method for diagnosing the stator-winding faults of an induction motor by the direct detection of its negative-sequence current. Before starting the diagnosis, the asymmetry admittances for the considered fault cases are obtained by analysis or simulation. The amplitude and phase of the positive-sequence voltage, Vp, and of the positive-sequence current, Ip, are extracted from the voltage PV and current PV, respectively. The amplitude and phase of the negative-sequence, In, are extracted from the residue. The asymmetry admittance, Ya, is calculated from In and Vp. When the positive-sequence admittance is known, Ya can also be calculated from Yp, Ip, and In. These steps are repeated for each sample time and the motor condition is diagnosed according to the variations in the Ya values. The simulation and experimental results are also shown and the proposed method is investigated and validated.

Kato, Toshiji; Inoue, Kaoru; Yoshida, Keisuke

283

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

284

A Generalized Method of Differential Fault Attack Against AES Cryptosystem  

Microsoft Academic Search

In this paper we describe two difierential fault attack tech- niques against Advanced Encryption Standard (AES). We propose two models for fault occurrence; we could flnd all 128 bits of key using one of them and only 6 faulty ciphertexts. We need approximately 1500 faulty ciphertexts to discover the key with the other fault model. Union of these models covers

Amir Moradi; Mohammad T. Manzuri Shalmani; Mahmoud Salmasizadeh

2006-01-01

285

Current signature analysis to detect induction motor faults  

Microsoft Academic Search

Three-phase induction motors are the “workhorses” of industry and are the most widely used electrical machines. In an industrialized nation, they can typically consume between 40 to 50% of all the generated capacity of that country. This article focuses on the industrial application of motor current signature analysis (MCSA) to diagnose faults in three-phase induction motor drives. MCSA is a

W. T. Thomson; M. Fenger

2001-01-01

286

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

PubMed Central

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

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

2008-01-01

287

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

SciTech Connect

This paper addresses the problem of motor current spectral analysis for the detection of nonidealities in the air gap flux density when in the presence of an oscillating or position-varying load torque. Several schemes have been proposed for the detection of air gap eccentricities and broken rotor bars. The analysis of these effects, however, generally assumes that the load torque is constant. If the load torque varies with the rotational speed, then the motor current spectral harmonics produced by the load will overlap the harmonics caused by the fault conditions. The motor current spectral components in the presence of various fault and load conditions are reviewed. The interaction of the effects on the actual stator current spectrum caused by the fault condition and the torque oscillations are shown to be separable only if the angular position of the fault with respect to the load torque characteristic is known. This is an important result in the formulation of an on-line fault detection scheme that measures only a single phase of the stator current. Since the spatial location of the fault is not known, its influence on a specific current harmonic component cannot be separated from the load effects. Therefore, on-line detection schemes must rely on monitoring a multiple frequency signature and identifying those components not obscured by the load effect. Experimental results which show the current spectra of an induction machine under eccentric air gap and broken rotor bar conditions are given for both fixed and oscillating loads.

Schoen, R.R.; Habetler, T.G. [Georgia Inst. of Tech., Atlanta, GA (United States). School of Electrical Engineering

1995-07-01

288

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

SciTech Connect

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

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

1992-03-06

289

Performance of diagnosis methods for IGBT open circuit faults in three phase voltage source inverters for AC variable speed drives  

Microsoft Academic Search

Variable speed drives have become industrial standard in many applications. Therefore fault diagnosis of voltage source inverters is becoming more and more important. One possible fault within the inverter is an open circuit transistor fault. An overview of the different strategies to detect this fault is given, including the algorithms used to localize the open transistor. Previous work showed significant

K. Rothenhagen; F. W. Fuchs

2005-01-01

290

Method for detecting biomolecules  

Microsoft Academic Search

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

Qisheng Huo; Jun Liu

2008-01-01

291

Tacholess envelope order analysis and its application to fault detection of rolling element bearings with varying speeds.  

PubMed

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

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

2013-08-16

292

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

PubMed Central

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

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

2013-01-01

293

Interpreting muon radiographic data in a fault zone: possible application to geothermal reservoir detection and monitoring  

NASA Astrophysics Data System (ADS)

Rainfall-triggered fluid flow in a mechanical fracture zone associated with a seismic fault has been estimated (Tanaka et al., 2011) using muon radiography by measuring the water position over time in response to rainfall events. In this report, the data taken by Tanaka et al. (2011) are reanalyzed to estimate the porosity distribution as a function of a distance from the fault gouge. The result shows a similar pattern of the porosity distribution as measured by borehole sampling at Nojima fault. There is a low porosity shear zone axis surrounded by porous damaged areas with density increasing with the distance from the fault gouge. The dynamic muon radiography (Tanaka et al., 2011) provides a new method to delineate both the recharge and discharge zones along the fault segment, an entire hydrothermal circulation system. This might dramatically raise the success rate for drilling of geothermal exploration wells, and it might open a new horizon in the geothermal exploration and monitoring.

Tanaka, H. K. M.; Muraoka, H.

2013-03-01

294

Interpreting muon radiographic data in a fault zone: possible application to geothermal reservoir detection and monitoring  

NASA Astrophysics Data System (ADS)

Rainfall-triggered fluid flow in a mechanical fracture zone associated with a seismic fault has been estimated (Tanaka et al., 2011) using muon radiography by measuring the water position over time in response to rainfall events. In this report, the data taken by Tanaka et al. (2011) are reanalyzed to estimate the porosity distribution as a function of a distance from the fault gauge. The result shows a similar pattern of the porosity distribution as measured by borehole sampling at Nojima fault. There is a low porosity shear zone axis surrounded by porous damaged-areas with density increasing with the distance from the fault gauge. The dynamic muon radiography (Tanaka et al., 2011) provides a new method to delineate both the recharge and discharge zones along the fault segment, an entire hydrothermal circulation system. This might dramatically raise the success rate for drilling of geothermal exploration wells and it might open a new horizon in the geothermal exploration and monitoring.

Tanaka, H. K. M.; Muraoka, H.

2012-10-01

295

Takagi-Sugeno fuzzy-model-based fault detection for networked control systems with Markov delays.  

PubMed

A Takagi-Sugeno (T-S) model is employed to represent a networked control system (NCS) with different network-induced delays. Comparing with existing NCS modeling methods, this approach does not require the knowledge of exact values of network-induced delays. Instead, it addresses situations involving all possible network-induced delays. Moreover, this approach also handles data-packet loss. As an application of the T-S-based modeling method, a parity-equation approach and a fuzzy-observer-based approach for fault detection of an NCS were developed. An example of a two-link inverted pendulum is used to illustrate the utility and viability of the proposed approaches. PMID:16903375

Zheng, Ying; Fang, Huajing; Wang, Hua O

2006-08-01

296

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

2009-09-24

297

A fault detection scheme of an infusion system in a ventricular assist device  

Microsoft Academic Search

A fault detection algorithm was designed to monitor the infusion system of a ventricular assist device (AB-180 Circulatory Support System (AB-180 CSS), Cardiac Assist Technologies, Inc.). This algorithm measures the infusion pressure, calculates the pressure derivative, and then compares to the preset thresholds to detect leaks and kinks in the infusion line, abnormal infusion rate, and stopped infusion pump condition.

Yih-Choung Yu

2003-01-01

298

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

Microsoft Academic Search

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

Zhang Yu; Zhao Hangsheng; Liu Qiongli

2011-01-01

299

Fault detection combining interacting multiple model and multiple solution separation for aviation satellite navigation system  

Microsoft Academic Search

In civil aviation applications, satellite failures yield unacceptable positioning errors when using the Global Positioning System (GPS). To ensure the user security, the navigation system has to fulfill stringent performance requirements. Thus, detecting and excluding the faulty GPS measurements is necessary prior to estimating the mobile location. Classical fault detection algorithms based on Kalman filters (KF) are sensitive to the

Frederic Faurie; Audrey Giremus; Eric Grivel

2009-01-01

300

Fault Detection and Diagnosis in Deep-trough Hydroponics using Intelligent Computational Tools  

Microsoft Academic Search

The intelligent computational tools of feedforward neural networks and genetic algorithms are used to develop a real-time detection and diagnosis system of specific mechanical, sensor and plant (biological) failures in a deep-trough hydroponic system. The capabilities of the system are explored and validated. In the process of designing the fault detection neural network model, a new technique for neural network

K. P. Ferentinos; L. D. Albright

2003-01-01

301

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

302

Application of an improved kurtogram method for fault diagnosis of rolling element bearings  

Microsoft Academic Search

Kurtogram, due to the superiority of detecting and characterizing transients in a signal, has been proved to be a very powerful and practical tool in machinery fault diagnosis. Kurtogram, based on the short time Fourier transform (STFT) or FIR filters, however, limits the accuracy improvement of kurtogram in extracting transient characteristics from a noisy signal and identifying machinery fault. Therefore,

Yaguo Lei; Jing Lin; Zhengjia He; Yanyang Zi

2011-01-01

303

Bispectrum of stator phase current for fault detection of induction motor.  

PubMed

A number of research studies has shown that faults in a stator or rotor generally show sideband frequencies around the mains frequency (50 Hz) and at higher harmonics in the spectrum of the Motor Current Signature Analysis (MCSA). However in the present experimental studies such observations have not been seen, but any fault either in the stator or the rotor may distort the sinusoidal response of the motor RPM and the mains frequency so the MCSA response may contain a number of harmonics of the motor RPM and the mains frequency. Hence the use of a higher order spectrum (HOS), namely the bispectrum of the MCSA has been proposed here because it relates both amplitude and phase of number of the harmonics in a signal. It has been observed that it not only detects early faults but also indicates the severity of the fault to some extent. PMID:19394927

Treetrong, Juggrapong; Sinha, Jyoti K; Gu, Fengshu; Ball, Andrew

2009-04-23

304

Exoplanet Detection: Transit Method  

NSDL National Science Digital Library

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

Belloni, Mario

2010-06-29

305

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

306

An efficient boundary integral equation method applicable to the analysis of non-planar fault dynamics  

Microsoft Academic Search

We develop a novel and efficient boundary integral equation method based on the spatio-temporal formulation for the two-dimensional dynamic and quasistatic analyses of an earthquake fault in a single scheme. A major advantage of this method is its applicability to the analysis of non-planar faults with the same degree of accuracy as to that of planar faults. Calculation time and

Ryosuke Ando; Nobuki Kame; Teruo Yamashita

2007-01-01

307

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

308

Accuracy of Fault Detection in Real Rotating Machinery Using Model Based Diagnostic Techniques  

NASA Astrophysics Data System (ADS)

An experimental validation of a model based identification technique is presented in this paper. The validation is performed on both real machines, like large steam and gas turbogenerators, and test rigs. The aim is to show that the method is able to locate the actual fault, to evaluate its severity and to discriminate among faults that have similar symptoms. A quantitative index, called residual is introduced to evaluate the accuracy of the performed identification. The actual developing faults taken into account are some of the most common on rotating machines such as unbalances, thermal bows, fatigue cracks and radial and angular misalignments of couplings.

Bachschmid, Nicolò; Pennacchi, Paolo

309

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

310

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

NASA Astrophysics Data System (ADS)

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

Schlechtingen, Meik; Ferreira Santos, Ilmar

2011-07-01

311

A New Assessment Method for System Reliability Based on Dynamic Fault Tree  

Microsoft Academic Search

According to the deficiency of traditional Markov chain approach in dynamic fault tree analysis, a new modular method for system reliability analysis is proposed. This paper focuses on dividing the fault tree of system into independent subtrees using a linear-time algorithm, and the processing method for different subtrees: Binary decision diagram solution for static subtrees and Bayesian Network solution for

Duan Rongxing; Wan Guochun; Dong Decun

2010-01-01

312

Detecting dominant resonant modes of rolling bearing faults using the niching genetic algorithm  

NASA Astrophysics Data System (ADS)

In this paper we propose an improvement of methods for adaptive selection of frequency bands containing transients which indicate the presence of the dominant resonant modes of rolling bearing faults using niching genetic algorithm optimization. The main aim of this approach is to diagnose the condition of the bearings and to be able to recognize faults on various parts of bearings and possible combinations of faults. Because the vibration signals corresponding to faults on bearings are typically transients with a wide frequency range occurring around the excited mechanical resonant modes and drowned in the acquired vibration signals, it is necessary to emphasize these excited transients using a matched bank of filters. The dominant resonant modes of a bearing and the system modes produced from fault source are usually unknown, and so there is a need for robust global search methods able to deal with non-linear problems with multiple optima. Instead of applying an optimization method repeatedly for every optimum, non-dominated extensions of the genetic algorithm can be applied only one time to find and maintain multiple optimal solutions. The efficiency of the proposed approach - niching genetic algorithm with fitness sharing - was evaluated using vibration signals acquired on four tapered roller bearings with defined combinations of seeded faults.

Docekal, Adam; Smid, Radislav; Kreidl, Marcel; Krpata, Pavel

2011-10-01

313

The TR method: A new graphical method that uses the slip preference of the faults to separate heterogeneous fault-slip data in extensional and compressional stress regimes  

NASA Astrophysics Data System (ADS)

The new graphical TR method uses the slip preference (SP) of the faults to separate heterogeneous fault-slip data. This SP is described in detail and several examples of the application of the TR method are presented. For this purpose, synthetic fault-slip data driven by various extensional and compressional stress regimes whose greatest principal stress axis (?1) or least principal stress axis (?3) always remains in vertical or horizontal position respectively as in Andersonian stress states have been considered. Their SP is given through a simple graphical manner and the aid of the Win-Tensor stress inversion software. The extensional stress regimes that have been examined are the radial extension (RE), radial-pure extension (RE-PE), pure extension (PE), pure extension-transtension (PE-TRN) and transtension (TRN), whereas the compressional stress regimes are the radial compression (RC), radial-pure compression (RC-PC), pure compression (PC), pure compression-transpression (PC-TRP) and transpression (TRP). A necessary condition for the TR method that is the faults dipping towards the certain horizontal principal stress axis of the driving stress regime are dip-slip faults, either normal or reverse ones, is satisfied for all extensional and compressional stress regimes respectively. The trend of the horizontal least or greatest principal stress axis of the driving extensional or compressional stress regime respectively can be directly defined by the trend of the T-axes of the normal faults or the P-axes of the reverse faults respectively. Taking into account a coefficient of friction no smaller than 0.6, the reactivated extensional faults in the crust dip at angles higher than about 40°, and the increase of the stress ratio and/or the fault dip angle results in the increase of the slip deviation from the normal activation. In turn, in the compressional stress regimes, the dip angle and SP of the activated faults suggest the distinction of the compressional stress regimes into "real" and "hybrid" ones. The "real" compressional regimes are the RC, RC-PC and PC, where the activated faults dip at angles up to 50° and their slip deviation from the reverse activation is no more than 30°. The "hybrid" compressional stress regimes are PC-TRP and TRP, where the activated faults can dip with even higher angles than 50° and their slip deviation from the reverse activation increases with the dip angle and the decrease of the stress ratio. In these stress regimes, the steeply dipping faults behave as contractional oblique strike-slip and strike-slip faults when their dip direction shifts at high angles away from the ?1 trend. Examples of the application of the TR method indicate that the method not only succeeds in separating heterogeneous fault-slip data into homogeneous groups, but it can (a) distinguish stress regimes whose horizontal principal stress axes trend close to each other, (b) distinguish faults driven by either tectonic or magmatic stresses, e.g., along the South Aegean Volcanic Arc, and (c) partition the contemporary stress regime related with the plate convergence between the Philippines Sea and Eurasia due to the different orientation of the activated structures, e.g., the inherited N-S striking Chelungpu Thrust and NE-SW striking Shihkang-Shangchi fault zone that have been activated during the 1999 Chi Chi earthquake, Taiwan.

Tranos, Markos

2013-04-01

314

Transformer diagnosis using frequency response analysis: results from fault simulations  

Microsoft Academic Search

This paper presents an assessment of which faults can be detected using frequency response analysis (FRA) and how different faults may be distinguished. The test method and the method used by the author for presenting the results are described. The results of an extensive fault simulation programme on a 100 kVA distribution transformer are presented and discussed. The faults simulated

Simon A. Ryder

2002-01-01

315

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

316

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

317

Rupture Dynamics Simulation for Non-Planar fault by a Curved Grid Finite Difference Method  

NASA Astrophysics Data System (ADS)

We first implement the non-staggered finite difference method to solve the dynamic rupture problem, with split-node, for non-planar fault. Split-node method for dynamic simulation has been used widely, because of that it's more precise to represent the fault plane than other methods, for example, thick fault, stress glut and so on. The finite difference method is also a popular numeric method to solve kinematic and dynamic problem in seismology. However, previous works focus most of theirs eyes on the staggered-grid method, because of its simplicity and computational efficiency. However this method has its own disadvantage comparing to non-staggered finite difference method at some fact for example describing the boundary condition, especially the irregular boundary, or non-planar fault. Zhang and Chen (2006) proposed the MacCormack high order non-staggered finite difference method based on curved grids to precisely solve irregular boundary problem. Based upon on this non-staggered grid method, we make success of simulating the spontaneous rupture problem. The fault plane is a kind of boundary condition, which could be irregular of course. So it's convinced that we could simulate rupture process in the case of any kind of bending fault plane. We will prove this method is valid in the case of Cartesian coordinate first. In the case of bending fault, the curvilinear grids will be used.

Zhang, Z.; Zhu, G.; Chen, X.

2011-12-01

318

Integrated Fault Detection and Isolation: Application to a Winery's Wastewater Treatment Plant  

Microsoft Academic Search

In this paper, an integrated object-oriented fuzzy logic fault detection and isolation (FDI) module for a biological wastewater treatment process is presented. The defined FDI strategy and the software implementation are detailed. Using experimental results obtained with a one cubic meter fixed bed reactor for the anaerobic digestion of industrial wine distillery vinasses, examples of material and biological failures are

Antoine Genovesi; Jérôme Harmand; Jean-Philippe Steyer

2000-01-01

319

A New Fault Detection Scheme for Networked Control Systems Subject to Uncertain Time-Varying Delay  

Microsoft Academic Search

Fault detection of networked control systems subject to uncertain time varying delay is studied in this paper. For the convenience of residual generator design, influence caused by network-induced delay is first transformed into time varying polytopic uncertainty, which greatly facilitates further manipulation. Then design of the optimal residual generator is formulated as a model matching problem, i.e. to design a

Yongqiang Wang; Steven X. Ding; Hao Ye; Guizeng Wang

2008-01-01

320

Fault detection and isolation of the three-tank system using the modal interval analysis  

Microsoft Academic Search

Analytical redundancy is a widely used technique for fault detection. It consists of comparing the behaviour of a real system with a reference obtained by simulation of its model. The main problem is that there are always imprecisions and uncertainties which are not represented in the model so the behaviour of the real system and the behaviour of the model

Miguel Á. Sainz; Joaquim Armengol; Josep Veh??

2002-01-01

321

Fault detection and diagnosis system for air-conditioning units using recurrent type neural network  

Microsoft Academic Search

The air-conditioning systems of buildings have been diversified in recent years, and the complexity of the systems has increased. At the same time, stability in the system and low running cost are demanded. To solve these problems, various research projects have been done. The development of the energy load prediction systems and the fault detection and diagnosis systems have received

H. K. U. Samarasinghe; S. Hashimoto

2000-01-01

322

Fault detection and isolation using sliding mode observer for uncertain Takagi-Sugeno fuzzy model  

Microsoft Academic Search

This paper addresses fault detection and isolation (FDI) problem using a sliding mode fuzzy observer on the basis of a uncertain Takagi-Sugeno (T-S) fuzzy model. First, a robust fuzzy observer with respect to the uncertainties is designed. The convergence of the fuzzy observer is performed by the search of suitable Lyapunov matrices. It is shown how to synthesis observers using

Abdelkader Akhenak; Mohammed Chadli; Jos'e Ragot; Didier Maquin

2008-01-01

323

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

324

An adaptive SK technique and its application for fault detection of rolling element bearings  

Microsoft Academic Search

In this paper, we propose an adaptive spectral kurtosis (SK) technique for the fault detection of rolling element bearings. The primary contribution is adaptive determination of the bandwidth and center frequency. This is implemented with successive attempts to right-expand a given window along the frequency axis by merging it with its subsequent neighboring windows. Influence of the parameters such as

Yanxue Wang; Ming Liang

2011-01-01

325

Model-based fault detection and isolation for a diesel lean NO x trap aftertreatment system  

Microsoft Academic Search

The lean NOx trap (LNT) is an aftertreatment device used to reduce nitrogen oxides emissions on Diesel engines. To operate the LNT with high conversion efficiency, an optimized regeneration schedule is required, together with closed-loop control of the air\\/fuel ratio during regeneration. Furthermore, to comply with emissions regulations, diagnostic schemes are needed to detect and isolate faults, typically related to

Marcello Canova; Shawn Midlam-Mohler; Pierluigi Pisu; Ahmed Soliman

2009-01-01

326

Diagnostic significance of orbit shape analysis and its application to improve machine fault detection  

Microsoft Academic Search

The full spectrum analysis of rotating machine vibrations is a diagnostic tool that enables the symptoms of some special types of fault to be clearly detected. The Shape and Directivity Index (SDI) of journal filtered orbits is an additional diagnostic parameter whose evaluation can be combined with the full spectrum analysis. The ellipticity of the filtered orbit, as well as

N. Bachschmid; P. Pennacchi; A. Vania

2004-01-01

327

Word line pulsing technique for stability fault detection in SRAM cells  

Microsoft Academic Search

Stability testing of SRAMs has been time consuming. This paper presents a new programmable DFT technique for detection of stability and data retention faults in SRAM cells. The proposed technique offers extended flexibility in setting the weak overwrite test stress, which allows to track process changes without time-consuming post-silicon design iterations. Moreover, it does not introduce extra circuitry in the

Andrei Pavlov; Mohamed Azimane; J Pineda de Gyvez; Manoj Sachdev

2005-01-01

328

The use of Artificial Neural Networks for Sensor Fault Detection, Isolation, and Accommodation in Automotive Engines  

Microsoft Academic Search

The paper describes the hybrid solution, based on Artificial Neural Networks, ANNs, and production rule adopted in the realization of an Instrument Fault Detection, Isolation, and Accommodation scheme for automotive applications. Details on the ANN architectures and training are given together with diagnostic and dynamic performance of the scheme. In the last decade an increasing number of sensors and actuators

Domenico Capriglione; Consolatina Liguori; Cesare Pianese; Antonio Pietrosanto

329

On-line sensor fault detection, isolation, and accommodation in automotive engines  

Microsoft Academic Search

This paper describes the hybrid solution, based on artificial neural networks (ANNs), and the production rule adopted in the realization of an instrument fault detection, isolation, and accommodation scheme for automotive applications. Details on ANN architectures and training are given together with diagnostic and dynamic performance of the scheme.

Domenico Capriglione; Consolatina Liguori; Cesare Pianese; Antonio Pietrosanto

2003-01-01

330

Permanent magnet synchronous motor fault detection and isolation using second order sliding mode observer  

Microsoft Academic Search

This paper deals with the design of fault detection and isolation (FDI) scheme on the basis of high order sliding mode observer for permanent magnet synchronous motors(PMSM). More precisely, the main advantage of the use of high order sliding mode techniques is that it allows to avoid the chattering phenomenon which is inherent to the classical first order sliding mode

Yigeng Huangfu; Weiguo Liu; Ruiqing Ma

2008-01-01

331

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

Microsoft Academic Search

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

R. J. Patton; J. Chen

1991-01-01

332

The use of genetic algorithms for advanced instrument fault detection and isolation schemes  

Microsoft Academic Search

An advanced scheme for Instrument Fault Detection and Isolation is proposed. It is mainly based on Artificial Neural Networks (ANNs), organized in layers and handled by knowledge-based analytical redundancy relationships. ANN design and training is performed by genetic algorithms which allow ANN architecture and parameters to be easily optimized. The diagnostic performance of the proposed scheme is evaluated with reference

Giovanni Betta; C. Liguori; A. Pietrosanto

1996-01-01

333

A knowledge-based approach to instrument fault detection and isolation  

Microsoft Academic Search

A knowledge-based instrument fault detection and isolation (IFDI) technique is proposed and described. It is based on the “duplication” of measurement devices by means of suitable mathematical relationships and is implemented on an expert system. The latter allows a mathematical model to be substituted by integrating qualitative models with empirical knowledge, thereby reducing overall computer effort without any corresponding decrease

Giovanni Betta; M. D'Apuzzo; A. Pietrosanta

1995-01-01

334

An advanced neural-network-based instrument fault detection and isolation scheme  

Microsoft Academic Search

An advanced scheme for instrument fault detection and isolation is proposed. It is based on artificial neural networks (ANN's), organized in layers and handled by knowledge-based analytical redundancy relationships. ANN design and training is performed by genetic algorithms which allow ANN architecture and parameters to be easily optimized. The diagnostic performance of the proposed scheme is evaluated with reference to

Giovanni Betta; Consolatina Liguori; Antonio Pietrosanto

1998-01-01

335

On-line sensor fault detection, isolation, and accommodation in automotive engines  

Microsoft Academic Search

The paper describes the hybrid solution, based on Artificial Neural Networks, ANNs, and production rule adopted in the realization of an Instrument Fault Detection, Isolation, and Accommodation scheme for automotive applications. Details on the ANN architectures and training are given together with diagnostic and dynamic performance of the scheme.

Domenico Capriglione; Consolatina Liguori; Cesare Pianese; A. Pietrosanto

2002-01-01

336

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

337

Grid based fault detection and calibration of sensors on mobile robots  

Microsoft Academic Search

This paper presents a concept for fault detection and calibration of external sensors on mobile robots, based on a grid representation of the environment. For every grid cell consistency measures are derived by evaluating the information stored in them. The measures are then used to deliberate about the condition of the involved sensors. Thereby a mobile robot is equipped with

Martin Soika

1997-01-01

338

Fault detection and isolation for an experimental internal combustion engine via fuzzy identification  

Microsoft Academic Search

Certain engine faults can be detected and isolated by examining the pattern of deviations of engine signals from their nominal unfailed values. In this brief paper, we show how to construct a fuzzy identifier to estimate the engine signals necessary to calculate the deviation from nominal engine behavior, so that we may determine if the engine has certain actuator and

E. G. Laukonen; K. M. Passino; V. Krishnaswami; G.-C. Luh; G. Rizzoni

1995-01-01

339

Detection and Classification of Rolling-Element Bearing Faults using Support Vector Machines  

Microsoft Academic Search

This paper proposes development of support vector machines (SVMs) for detection and classification of rolling-element bearing faults. The training of the SVMs is carried out using the sequential minimal optimization (SMO) algorithm. In this paper, a mechanism for selecting adequate training parameters is proposed. This proposal makes the classification procedure fast and effective. Various scenarios are examined using two sets

Alfonso Rojas; Asoke K Nandi

2005-01-01

340

Sensorless Detection of Induction Motor Rotor Faults Using the Clarke Vector Approach  

NASA Astrophysics Data System (ADS)

Due to their rugged build, simplicity and cost effective performance, induction motors are used in a vast number of industries, where they play a significant role in responsible operations, where faults and downtimes are either not desirable or even unthinkable. As different faults can affect the performance of the induction motors, among them broken rotor bars, it is important to have a certain condition monitoring or diagnostic system that is guarding the state of the motor. This paper deals with induction motor broken rotor bars detection, using Clarke vector approach.

Vaimann, Toomas; Kallaste, Ants; Kilk, Aleksander

2011-01-01

341

Fault detection for hydraulic pump based on chaotic parallel RBF network  

NASA Astrophysics Data System (ADS)

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

Lu, Chen; Ma, Ning; Wang, Zhipeng

2011-12-01

342

An enhanced component connection method for conversion of fault trees to binary decision diagrams  

Microsoft Academic Search

Fault tree analysis (FTA) is widely applied to assess the failure probability of industrial systems. Many computer packages are available, which are based on conventional kinetic tree theory methods. When dealing with large (possibly non-coherent) fault trees, the limitations of the technique in terms of accuracy of the solutions and the efficiency of the processing time become apparent. Over recent

R. Remenyte-Prescott; J. D. Andrews

2008-01-01

343

A Method for Controlled Fault Interruption for Use with HV SF6 Circuit Breakers  

Microsoft Academic Search

A method has been developed for synchronizing the trip commands to a HV circuit breaker in order to achieve a preselected optimum arcing time, even under transient asymmetrical fault current conditions. The algorithm estimates parameters of the fault current by applying least means squares regression to a generic model and sampled values of the current in each phase. An analysis

Richard P. Thomas

2007-01-01

344

Fault diagnosis method of automobile engine based on least squares support vector machine  

Microsoft Academic Search

In order to improve diagnostic accuracy and quality of maintenance, it is very important to study fault diagnosis method for automobile engine. Least-squares support vector machine called LSSVM is a modified SVM, which use a set of linear equations instead of a quadratic programming problem. In the paper, least-squares support vector machine is proposed to fault diagnosis of automobile engine.

Qin Bo

2010-01-01

345

ANN-based techniques for estimating fault location on transmission lines using Prony method  

Microsoft Academic Search

A system is proposed to locate faults on transmission lines using the traveling wave phenomenon. Prony method is used to analyze the voltage or current signal at the local bus and extract its modal information. This information represents the traveling wave generated by the fault and can be used to estimate its location. Artificial neural networks (ANNs) are used to

M. M. Tawfik; M. M. Morcos

2001-01-01

346

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

347

Multi-model based fault detection for the power system of more electric aircraft  

Microsoft Academic Search

This paper presents a suitable scheme for the fault detection and isolation of a high voltage DC electrical network in more electric aircraft. Concerning a more electric aircraft architecture comprising one variable frequency generator, one 18-pulse autotransformer, power electronic converters, high voltage DC transmission lines, electromagnetic actuators and numerous constant electrical loads e.g. lighting and PCs, the multi-model detection approach

Y. Ji; J. Bals

2009-01-01

348

Fault Diagnosis Methods for District Heating Substations. Research Programme on Energy Use in Buildings.  

National Technical Information Service (NTIS)

The paper presents five different approaches to fault diagnosis. While developing the methods, various kinds of pragmatic aspects and robustness had to be considered in order to achieve practical solutions. The presented methods are: classification of fau...

J. Pakanen J. Hyvaerinen J. Kuismin M. Ahonen

1996-01-01

349

Fault detection, diagnosis, and data-driven modeling in HVAC chillers  

NASA Astrophysics Data System (ADS)

Heating, Ventilation and Air Conditioning (HVAC) systems constitute the largest portion of energy consumption equipment in residential and commercial facilities. Real-time health monitoring and fault diagnosis is essential for reliable and uninterrupted operation of these systems. Existing fault detection and diagnosis (FDD) schemes for HVAC systems are only suitable for a single operating mode with small numbers of faults, and most of the schemes are systemspecific. A generic real-time FDD scheme, applicable to all possible operating conditions, can significantly reduce HVAC equipment downtime, thus improving the efficiency of building energy management systems. This paper presents a FDD methodology for faults in centrifugal chillers. The FDD scheme compares the diagnostic performance of three data-driven techniques, namely support vector machines (SVM), principal component analysis (PCA), and partial least squares (PLS). In addition, a nominal model of a chiller that can predict system response under new operating conditions is developed using PLS. We used the benchmark data on a 90-ton real centrifugal chiller test equipment, provided by the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE), to demonstrate and validate our proposed diagnostic procedure. The database consists of data from sixty four monitored variables under nominal and eight fault conditions of different severities at twenty seven operating modes.

Namburu, Setu M.; Luo, Jianhui; Azam, Mohammad; Choi, Kihoon; Pattipati, Krishna R.

2005-05-01

350

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

NASA Astrophysics Data System (ADS)

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

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

1996-03-01

351

Run-Time Fault Detection in Monitor Based Concurrent Programming  

Microsoft Academic Search

The monitor concept provides a structured and flexible high-level programming construct to control concurrent accesses to shared resources. It has been widely used in a concurrent programming environment for implicitly ensuring mutual exclusion and explicitly achieving process synchronization. This paper proposes an extension to the monitor construct for detecting run time errors in monitor operations. Monitors are studied and classified

Jiannong Cao; Nick K. C. Cheung; Alvin T. S. Chan

2001-01-01

352

Microcomputer-based fault detection using redundant sensors  

Microsoft Academic Search

The design of a prototype device that implements a redundancy management scheme for online detection and isolation of faulty sensors in strategic facilities such as nuclear reactors, hazardous chemical plants, and advanced aircraft is presented. Such a device can potentially reduce the number of display devices in the control room and relieve the plant operator(s) from the tasks of assimilation

HECTOR P. POLENTA; A. Ray; J. A. Bernard

1988-01-01

353

Model-based engine fault detection and isolation  

Microsoft Academic Search

To a large extent, tailpipe emissions are influenced by the accuracy and reliability of the intake manifold sensors and the predictive models used for cylinder charge estimation. In this paper, mathematical models of an internal combustion engine are employed to detect failures in the intake manifold. These can be associated with the upstream sensors such as the pressure and temperature

Arkadiusz Dutka; Hossein Javaherian; Michael J. Grimble

2009-01-01

354

A new method of detecting current transducer saturation based on wavelet transform  

Microsoft Academic Search

Bus bar differential protection using instantaneous current values is easily influenced by current transducer (CT) saturation, causing maloperation. A method of analyzing the voltage of busbars using the wavelet transform is presented in this paper to detect fault points accurately. One can distinguish whether the CT is saturated based on the time difference between the time of the fault and

Li Gtricun; Liu Wanshun; Jia Qingquan; Teng Lin; Cao Fengmei; Li Ying

2001-01-01

355

A New Method on Fault Diagnosis of Low-Speed Rolling Bearing Using Stress Waves  

Microsoft Academic Search

High-frequency stress wave analysis was used as characteristic parameter to detect the early stages of the loss of mechanical integrity in low-speed machinery in the paper. The background noise was eliminated using wavelet decomposition and the feature frequency of fault stress waves was extracted. Firstly, according to the characters of the fault stress waves obtained from a steel mill, db6

Zhou Bo; Zhang Yu

2010-01-01

356

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

NASA Astrophysics Data System (ADS)

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

Wang, Yanxue; He, Zhengjia; Zi, Yanyang

2010-01-01

357

Fault Detection in a Diesel Engine by Analysing the Instantaneous Angular Speed  

NASA Astrophysics Data System (ADS)

Instantaneous angular speed of a diesel engine contains a lot of information about gas pressure in cylinders, which can be used to diagnose combustion-related faults and other faults affecting the gas pressure, such as fuel leakage in fuel system, valve leakage, etc. In this paper, a dynamic model for simulating the instantaneous angular speed is presented, and the instantaneous angular speed waveforms on a small four-cylinder diesel engine are simulated. The tangential forces induced by the gas pressure and the vertical imbalance inertial force are calculated and analysed based on the proposed dynamic model, respectively. It is concluded that the gas pressure and the vertical imbalance inertial force have a great influence on the instantaneous angular speed. The simulated results of the instantaneous angular speed fluctuation ratio based on the dynamic model are confirmed by the experimental results. The instantaneous angular speed waveforms both in the fuel leakage condition and in the normal condition are measured under various engine speeds and loads in laboratory condition. The characteristic parameters for detecting the faults relating to the gas pressure in the cylinder are obtained successfully. It is promising, therefore, to develop and to apply the diagnosis technique further using the instantaneous angular speeds to detect the faults relating to the gas pressure in the cylinder.

Yang, Jianguo; Pu, Lijun; Wang, Zhihua; Zhou, Yichen; Yan, Xinping

2001-05-01

358

Spin-system dynamics and fault detection in threshold networks  

SciTech Connect

We consider an agent on a fixed but arbitrary node of a known threshold network, with the task of detecting an unknown missing link. We obtain analytic formulas for the probability of success when the agent's tool is the free evolution of a single excitation on an XX spin system paired with the network. We completely characterize the parameters, which allows us to obtain an advantageous solution. From the results emerges an optimal (deterministic) algorithm for quantum search, from which a quadratic speedup with respect to the optimal classical analog and in line with well-known results in quantum computation is gained. When attempting to detect a faulty node, the chosen setting appears to be very fragile and the probability of success too small to be of any direct use.

Kirkland, Steve; Severini, Simone [Hamilton Institute, National University of Ireland, Maynooth County Kildare (Ireland); Department of Physics and Astronomy, University College London, WC1E 6BT London (United Kingdom)

2011-01-15

359

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

360

Isolability of faults in sensor fault diagnosis  

NASA Astrophysics Data System (ADS)

A major concern with fault detection and isolation (FDI) methods is their robustness with respect to noise and modeling uncertainties. With this in mind, several approaches have been proposed to minimize the vulnerability of FDI methods to these uncertainties. But, apart from the algorithm used, there is a theoretical limit on the minimum effect of noise on detectability and isolability. This limit has been quantified in this paper for the problem of sensor fault diagnosis based on direct redundancies. In this study, first a geometric approach to sensor fault detection is proposed. The sensor fault is isolated based on the direction of residuals found from a residual generator. This residual generator can be constructed from an input-output or a Principal Component Analysis (PCA) based model. The simplicity of this technique, compared to the existing methods of sensor fault diagnosis, allows for more rational formulation of the isolability concepts in linear systems. Using this residual generator and the assumption of Gaussian noise, the effect of noise on isolability is studied, and the minimum magnitude of isolable fault in each sensor is found based on the distribution of noise in the measurement system. Finally, some numerical examples are presented to clarify this approach.

Sharifi, Reza; Langari, Reza

2011-10-01

361

Sensor fault detection and identification in dead-reckoning system of mobile robot: interacting multiple model approach  

Microsoft Academic Search

An interacting multiple-model (IMM) approach to sensor fault detection and identification (FDI) in the dead reckoning of mobile robots is proposed Changes of sensor normal\\/failure modes are explicitly modeled as switching from one mode to another in a probabilistic manner; mode probabilities and robot states are estimated via a bank of Kalman filters with mutual interaction. To provide better fault

Masafumi Hashimoto; Hiroyuki Kawashima; Takashi Nakagami; Fuminori Oba

2001-01-01

362

Fault detection, identification and estimation in the electro-hydraulic actuator system using EKF-based multiple-model estimation  

Microsoft Academic Search

In this paper, a fault detection, identification and estimation approach has been developed for the condition monitoring of the electro-hydraulic actuator (EHA) system using the multiple-model (MM) estimation algorithm. The MM estimation algorithm makes use of the extended Kalman filter (EKF) technique to generate estimates of states and key physical parameters, which are related to faults in the EHA system.

Xudong Wang; Vassilis L. Syrmos

2008-01-01

363

Robust fault detection and diagnosis in a class of nonlinear systems using a neural sliding mode observer  

Microsoft Academic Search

This article presents a robust fault detection and diagnosis scheme for any abrupt and incipient class of faults that can affect the state of a class of nonlinear systems. A nonlinear observer which synthesizes sliding mode techniques and neural state space models is proposed for the purpose of online health monitoring. The sliding mode term is utilized to eliminate the

Qing Wu; Mehrdad Saif

2007-01-01

364

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

Microsoft Academic Search

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

Fabio Immovilli; Marco Cocconcelli; Alberto Bellini; Riccardo Rubini

2009-01-01

365

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...

366

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

367

A seismic design method for subsea pipelines against earthquake fault movement  

NASA Astrophysics Data System (ADS)

As there are no specific guidelines on design of subsea pipelines crossing active seismic faults, methods for land buried pipelines have been applied to. Taking the large seismic fault movement into account, this paper proposes improved methods for seismic designs of subsea pipelines by comprehensively investigating the real constraining of soil on the pipelines, the interaction processes of soil with the pipeline, the plastic slippage of the soil, and the elastic-plastic properties of the pipeline materials. New formulas are given to calculate the length of transition section and its total elongation. These formulas are more reasonable in mechanism, and more practical for seismic design of subsea pipelines crossing active faults.

Duan, Meng-Lan; Mao, Dong-Feng; Yue, Zhi-Yong; Estefen, Segen; Li, Zhi-Gang

2011-06-01

368

Electrical properties and detection methods for CMOS IC defects  

Microsoft Academic Search

CMOS failure modes and mechanisms and the test vector and parametric test requirements for the detection are reviewed. The CMOS stuck-open fault is discussed from a physical viewpoint, with results given from failure analysis of ICs having this failure mode. The results show that among functional, stuck-at, stuck-open, and IDDQ test strategies, no single method guarantees detection of all types

Jerry M. Soden; Charles F. Hawkins

1989-01-01

369

Analytical Redundancy Techniques for Fault Detection in an Active Heavy Vehicle Suspension  

Microsoft Academic Search

This paper describes the design and implementation of an intelligent fault monitoring system for a prototype heavy vehicle active suspension system. A controller architecture has been designed, to facilitate safe start up and shutdown of the active control. This paper develops a method for monitoring the complete system, by dividing it into submodels which are more straightforward to analyse. The

B. P. Jeppesen; D. Cebon

2004-01-01

370

Detection of Gear Fault Based on Amplitude Demodulation of Rotary Speed  

Microsoft Academic Search

Aiming at the features of the engaging vibration's direct effects on the rotary speed of axis, this paper puts forward the faults diagnosis method of gearbox using amplitude demodulation technology to analyze the signals of rotary speed. First, the signals of rotary speed of gearbox are synchronously sampled in time domain; Next, the signals of torsional vibration are worked out

Zhang Qing-feng; Tang Li-wei; Cui Xiu-mei; Hou Cai-hong

2010-01-01

371

A non-parametric non-filtering approach to bearing fault detection in the presence of multiple interference  

NASA Astrophysics Data System (ADS)

Reliable fault detection of bearing faults is crucial to avoid costly machine failures. To this end, many methods have been proposed over the years. However, most of them are dependent on properly selected parameters, such as the center frequency and the bandwidth of the bandpass filter for the pass band in the high-frequency resonance method. Such parameters may also have to be updated in a variable operating environment which may not always be possible without the involvement of domain experts. As such, we propose a new non-parametric and non-filtering method which can perform reasonably well in the presence of vibration interference and noise. This method is based on the derivation of amplitude demodulation of a signal to suppress unwanted periodic interference components in the acquired signal. It has been shown that the proposed method can boost the signal-to-interference ratio by up to 2-12 times compared with the energy operator approach and can handle signals tinted by both noise and multiple interference. It compares favorably with other non-parameter methods, such as the plain envelope method and energy operator method. Its effectiveness has further been demonstrated using both simulated and experimental data.

Liang, M.; Faghidi, H.

2013-10-01

372

Detection of Nacelle Anemometers Faults in a Wind Farm  

Microsoft Academic Search

Control of wind farms requires the acquisition of accurate wind speed data. Nevertheless there is no system able to control the small, long-term degradation of data registered by anemometers installed in wind turbines. In this report we have developed a method to evaluate the quality of the wind speed measurements with the minimum uncertainty. This evaluation is made comparing the

J. Beltrán; A. Llombart; Juan Jose Guerrero Castillo

2009-01-01

373

Concurrent error detection schemes for fault-based side-channel cryptanalysis of symmetric block ciphers  

Microsoft Academic Search

Fault-based side-channel cryptanalysis is very effective against symmetric and asymmetric encryption algorithms. Although straightforward hardware and time redundancy-based concurrent error detection (CED) architectures can be used to thwart such attacks, they entail significant overheads (either area or performance). The authors investigate systematic approaches to low-cost low-latency CED techniques for symmetric encryption algorithms based on inverse relationships that exist between encryption

Ramesh Karri; Kaijie Wu; Piyush Mishra; Yongkook Kim

2002-01-01

374

A Survey of Fault Detection\\/Tolerance Strategies for AUVs and ROVs  

Microsoft Academic Search

The use of Remotely Operated Vehicles (ROVs) and Autonomous Underwater Vehicles (AUVs) increased significantly in the last\\u000a years. Such vehicles are complex systems engaged in missions in un-structured, unsafe environments for which the degree of\\u000a autonomy becomes a crucial issue. In this sense, the capability to detect and tolerate faults is a key to successfully terminate\\u000a the mission or recuperate

Gianluca Antonelli

375

Fault detection in CVS parity trees: application in SSC CVS parity and two-rail checkers  

Microsoft Academic Search

The problem of single stuck-at, stuck-open, and stuck-on fault detection in cascode voltage switch (CVS) parity trees is considered. The results are also applied to parity and two-rail checkers. CVS circuits are dynamic CMOS circuits which can implement both inverting and noninverting functions. If the CVS parity tree consists of only differential cascode voltage switch (DCVS) EX-OR gates, then it

Niraj K. Jha

1989-01-01

376

Fault detection of networked control systems with packet based periodic communication  

Microsoft Academic Search

SUMMARY Fault detection of networked control systems (NCS) with communication constraints is discussed in this paper. A so-called packet-based periodic communication strategy is proposed and two kinds of optimal observer-based residual generators are designed. One residual generator is designed based on the lifted model of NCS, which generates residual signals every communication period. The other works at a faster rate,

Yongqiang Wang; Steven X. Ding; Hao Ye; Li Wei; Ping Zhang; Guizeng Wang

2009-01-01

377

Online detection of multiple faults in crossbar nano-architectures using dual rail implementations  

Microsoft Academic Search

Crossbar nano-architectures based on self-assembled structures are promising alternatives for current CMOS technology, which is facing serious challenges for further down-scaling. However, high permanent and transient failure rates lead to multiple faults during lifetime operation of crossbar nano architectures. In this paper, we propose a concurrent multiple error detection scheme for multistage nano-crossbars based on dual-rail implementations of logic functions.

Navid Farazmand; Mehdi B. Tahoori

2009-01-01

378

An active ring fault detected at Tendürek volcano by using InSAR  

NASA Astrophysics Data System (ADS)

ring faults are present at many ancient, deeply eroded volcanoes, they have been detected at only very few modern volcanic centers. At the so far little studied Tendürek volcano in eastern Turkey, we generated an ascending and a descending InSAR time series of its surface displacement field for the period from 2003 to 2010. We detected a large (~105?km2) region that underwent subsidence at the rate of ~1?cm/yr during this period. Source modeling results show that the observed signal fits best to simulations of a near-horizontal contracting sill located at around 4.5?km below the volcano summit. Intriguingly, the residual displacement velocity field contains a steep gradient that systematically follows a system of arcuate fractures visible on the volcano's midflanks. RapidEye satellite optical images show that this fracture system has deflected Holocene lava flows, thus indicating its presence for at least several millennia. We interpret the arcuate fracture system as the surface expression of an inherited ring fault that has been slowly reactivated during the detected recent subsidence. These results show that volcano ring faults may not only slip rapidly during eruptive or intrusive phases, but also slowly during dormant phases.

Bathke, H.; Sudhaus, H.; Holohan, E. P.; Walter, T. R.; Shirzaei, M.

2013-08-01

379

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

380

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

381

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

NASA Astrophysics Data System (ADS)

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

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

2005-03-01

382

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

NASA Astrophysics Data System (ADS)

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.

Goto, Hayato; Uchikawa, Hironori

2013-06-01

383

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

PubMed Central

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.

Goto, Hayato; Uchikawa, Hironori

2013-01-01

384

Fault Detection and Reconfiguration Technique for Cascaded H-bridge 11-level Inverter Drives Operating under Faulty Condition  

Microsoft Academic Search

A fault detection and reconfiguration technique for a cascaded H-bridge 11-level inverter drives during faulty condition is proposed in this paper. The ability of cascaded H-bridge multilevel inverter drives (MLID) to operate under faulty condition is also discussed. Output phase voltages of a MLID can be used as a diagnostic signal to detect faults and their locations. Al-based techniques are

S. Khomfoi; L. M. Tolbert

2007-01-01

385

Multi-attribute ant-tracking and neural network for fault detection: a case study of an Iranian oilfield  

NASA Astrophysics Data System (ADS)

Fault detection is one of the most important steps in seismic interpretation in both exploration and development phases. A variety of seismic attributes enhancing fault visualization and detection have been used by many interpreters. Geometric seismic attributes such as coherency and curvature have been successfully applied in delineating faults in sedimentary basins. Seismic attributes are often sensitive to noise and it is necessary to reduce noise and enhance the seismic quality before computing the attributes. In this study, after enhancing the quality of the seismic data, several different seismic attributes sensitive to discontinuities such as similarity and curvature were computed and applied to a 3D seismic dataset and their effective parameters were explained. Ant-tracking as an algorithm that captures continuous features was used to improve fault visualization. Ant-tracking was applied to different fault-sensitive attributes and their results were compared. Also artificial neural networks were used for combining multiple attributes into a single image to allow us to visually cluster different fault-sensitive attributes. The area of this study was an oilfield in the South West of Iran lying in the Zagros thrust belt. Results showed that the similarity and the most-positive curvature could detect faults and fractures more properly than the other attributes and applying the ant-tracking algorithm provided better interpretable information for studying faults and subtle faults. Results proved that applying ant-tracking to the most-positive curvature attribute was more acceptable than the dip attribute or even the similarity in this field. Also by an unsupervised neural network, different ant-tracking volumes were integrated into one volume and faults with more probability were clustered in one group.

Mahdavi Basir, Hadi; Javaherian, Abdolrahim; Tavakoli Yaraki, Mehdi

2013-02-01

386

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

387

Using fault analysis methods to improve bioreactor safety.  

PubMed

A simplified fault analysis algorithm has been described and applied to the analysis of containment loss in a model bioreactor system. Using approximate data for component failure rates, the relative merits of three proposed operating regimes were evaluated by means of a computer program that implements the algorithm described. With the data given, operator error is shown to be the dominant cause of possible failure in the proposed system. In view of these results, the simplified algorithm appears useful for the comparative evaluation of various design proposals in simple systems. PMID:3460487

Jefferis, R P; Schlager, S T

1986-01-01

388

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

SciTech Connect

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

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

1995-07-01

389

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

390

Detection of Stator Faults in Induction Machines Using Residual Saturation Harmonics  

Microsoft Academic Search

Stator fault is one of the most commonly occurring faults in ac machines. Recent estimates suggest that 30%-40% of all reported induction machine faults are stator fault related. Going by the number of occurrences, the position of stator faults is only second to bearing-related faults. Third harmonic line currents, which are caused by the interaction of a reverse-rotating field and

Subhasis Nandi

2006-01-01

391

Intelligent detection and diagnosis of lightning arrester faults using digital thermovision image processing techniques  

NASA Astrophysics Data System (ADS)

This paper describes a methodology that aims to detect and diagnosis faults in lightning arresters, using the thermovision technique. Thermovision is a non-destructive technique used in diverse services of maintenance, having the advantage not to demand the disconnection of the equipment under inspection. It uses a set of neuro-fuzzy networks to achieve the lightning arresters fault classification. The methodology also uses a digital image processing algorithm based on the Watershed Transform in order to get the segmentation of the lightning arresters. This procedure enables the automatic search of the maximum and minimum temperature on the lightning arresters. These variables are necessary to generate the diagnosis. By appling the methodology is possible to classify lightning arresters operative condition in: faulty, normal, light, suspicious and faulty. The computacional system generated by the proposed methodology train its neuro-fuzzy network by using a historical thermovision data. During the train phase, a heuristic is proposed in order to set the number of networks in the diagnosis system. This system was validated using a database provided by the Eletric Energy Research Center, with a hundreds of different faulty scenarios. The validation error of the set of neuro-fuzzy and the automatic digital thermovision imagem processing was about 10 percent. The diagnosis system described has been sucessefully used by Eletric Energy Research Center as an auxiliar tool for lightning arresters fault diagnosis.

Laurentys Almeida, Carlos A.; Caminhas, Walmir M.; Braga, Antonio P.; Paiva, Vinicius; Martins, Helvio; Torres, Rodolfo

2005-03-01

392

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

393

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

394

The short-circuit characteristics of a DC reactor type superconducting fault current limiter with fault detection and signal control of the power converter  

Microsoft Academic Search

In general case of DC reactor type superconducting fault current limiter (SFCL), a fault current gradually increases during the fault. It takes above 5 cycles to cut off the fault in the existing power system installed the conventional circuit breakers (CBs). Therefore, the fault current increases during the fault even if the SFCL is installed. This paper proposes a technique

Min Cheol Ahn; Hyoungku Kang; Duck Kweon Bae; Dong Keun Park; Yong Soo Yoon; Sang Jin Lee; Tae Kuk Ko

2005-01-01

395

Hybrid stepping stone detection method  

Microsoft Academic Search

Stepping stone detection can be defined as a process to discover an intermediate host correlation that used by intruder. Most of the intruders cover their track by login into intermediate host first before execute the real attack. This intermediate hosts here known as stepping stone. This paper introduces a hybrid stepping stone detection method which combines the network-based and host-based

Mohd Nizam Omar; Lelyzar Siregar; Rahmat Budiarto

2008-01-01

396

Fast computation of the kurtogram for the detection of transient faults  

NASA Astrophysics Data System (ADS)

The kurtogram is a fourth-order spectral analysis tool recently introduced for detecting and characterising non-stationarities in a signal. The paradigm relies on the assertion that each type of transient is associated with an optimal (frequency/frequency resolution) dyad {f,?f} which maximises its kurtosis, and hence its detection. However, the complete exploration of the whole plane (f,?f) is a formidable task hardly amenable to on-line industrial applications. In this communication we describe a fast algorithm for computing the kurtogram over a grid that finely samples the (f,?f) plane. Its complexity is on the order of NlogN, similarly to the FFT. The efficiency of the algorithm is then illustrated on several industrial cases concerned with the detection of incipient transient faults.

Antoni, Jérôme

2007-01-01

397

Fault-detection sensors for gas-insulated equipment. Final report. [Operation and performance of chemical, optical and magnetic sensors  

Microsoft Academic Search

The EPRI-GE program develops new techniques for detecting and locating faults or internal insulation degradation in SFâ-insulated equipment, particularly coaxial conductors used extensively in EHV and UHV substations. The development is described of three types of sensors useful in determining the location of high current faults within the enclosed apparatus: resistive thin-film, optical, and magnetic. All are small in size,

J. K. Wittle; J. M. Houston; G. J. Carlson; W. D. Davis; A. M. Itani; J. G. Jewell; M. P. Perry; T. H. Rautenberg

1982-01-01

398

On-line fault detection and diagnosis obtained by implementing neural algorithms on a digital signal processor  

Microsoft Academic Search

A measurement instrument for on-line fault detection and diagnosis is proposed. It is based on the implementation of a neural network algorithm on a processor specialized in digital signal processing and provided with suitable data acquisition and generation units. Two specific implementations are detailed. The former uses the neural-network to simulate on-line the correct system behavior, thus allowing the fault

Andrea Bernieri; Giovanni Betta; Consolatina Liguori

1996-01-01

399

Comparing Detection Methods for Software Requirements Inspections: A Replicated Experiment  

Microsoft Academic Search

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

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

1995-01-01

400

Identifying fault segments from 3D fault drag analysis (Vienna Basin, Austria)  

NASA Astrophysics Data System (ADS)

The segmented growth of the Markgrafneusiedl normal fault in the late Miocene clastic sediments of the central Vienna Basin (Austria) was investigated by construction of a detailed three-dimensional (3D) structural model. Using high resolution 3D seismic data, the fault surface and marker horizons in the hanging wall and the footwall of the Markgrafneusiedl Fault were mapped and orientation, displacement and morphology of the fault surface were quantified. Individual, fault segments were identified by direct mapping of the deflection of the marker horizons close to the fault surface. Correlating the size of the identified segments with the magnitude of fault drag and displacement distribution showed that fault evolution progressed in several stages. The proposed method allows the detection of segments that are not recorded by the magnitude of displacement or fault morphology. Most importantly, detailed mapping of marker deflections in the hanging wall could help to constrain equivalent structures in the footwall, which may represent potential hydrocarbon traps.

Spahi?, Darko; Grasemann, Bernhard; Exner, Ulrike

2013-10-01

401

FAULT SCARP DETECTION BENEATH DENSE VEGETATION COVER: AIRBORNE LIDAR MAPPING OF THE SEATTLE FAULT ZONE, BAINBRIDGE ISLAND, WASHINGTON STATE  

Microsoft Academic Search

The emergence of a commercial airborne laser mapping industry, inspired by NASA technology research and development, is paying major dividends in an assessment of earthquake hazards in the Puget Lowland of Washington State. Geophysical observations and historical seismicity indicate the presence of active upper- crustal faults in the Puget Lowland, placing the major population centers of Seattle and Tacoma at

David J. Harding; Gregory S. Berghoff

2000-01-01

402

A Recurrent Neural-Network-Based Sensor and Actuator Fault Detection and Isolation for Nonlinear Systems With Application to the Satellite's Attitude Control Subsystem  

Microsoft Academic Search

This paper presents a robust fault detection and isolation (FDI) scheme for a general class of nonlinear systems using a neural-network-based observer strategy. Both actuator and sensor faults are considered. The nonlinear system considered is subject to both state and sensor uncertainties and disturbances. Two recurrent neural networks are employed to identify general unknown actuator and sensor faults, respectively. The

Heidar A. Talebi; Khashayar Khorasani; S. Tafazoli

2009-01-01

403

Thermodynamic method for generating random stress distributions on an earthquake fault  

USGS Publications Warehouse

This report presents a new method for generating random stress distributions on an earthquake fault, suitable for use as initial conditions in a dynamic rupture simulation. The method employs concepts from thermodynamics and statistical mechanics. A pattern of fault slip is considered to be analogous to a micro-state of a thermodynamic system. The energy of the micro-state is taken to be the elastic energy stored in the surrounding medium. Then, the Boltzmann distribution gives the probability of a given pattern of fault slip and stress. We show how to decompose the system into independent degrees of freedom, which makes it computationally feasible to select a random state. However, due to the equipartition theorem, straightforward application of the Boltzmann distribution leads to a divergence which predicts infinite stress. To avoid equipartition, we show that the finite strength of the fault acts to restrict the possible states of the system. By analyzing a set of earthquake scaling relations, we derive a new formula for the expected power spectral density of the stress distribution, which allows us to construct a computer algorithm free of infinities. We then present a new technique for controlling the extent of the rupture by generating a random stress distribution thousands of times larger than the fault surface, and selecting a portion which, by chance, has a positive stress perturbation of the desired size. Finally, we present a new two-stage nucleation method that combines a small zone of forced rupture with a larger zone of reduced fracture energy.

Barall, Michael; Harris, Ruth A.

2012-01-01

404

Numerical simulations of earthquakes and the dynamics of fault systems using the Finite Element method.  

NASA Astrophysics Data System (ADS)

Simulations using the Finite Element method are widely used in many engineering applications and for the solution of partial differential equations (PDEs). Computational models based on the solution of PDEs play a key role in earth systems simulations. We present numerical modelling of crustal fault systems where the dynamic elastic wave equation is solved using the Finite Element method. This is achieved using a high level computational modelling language, escript, available as open source software from ACcESS (Australian Computational Earth Systems Simulator), the University of Queensland. Escript is an advanced geophysical simulation software package developed at ACcESS which includes parallel equation solvers, data visualisation and data analysis software. The escript library was implemented to develop a flexible Finite Element model which reliably simulates the mechanism of faulting and the physics of earthquakes. Both 2D and 3D elastodynamic models are being developed to study the dynamics of crustal fault systems. Our final goal is to build a flexible model which can be applied to any fault system with user-defined geometry and input parameters. To study the physics of earthquake processes, two different time scales must be modelled, firstly the quasi-static loading phase which gradually increases stress in the system (~100years), and secondly the dynamic rupture process which rapidly redistributes stress in the system (~100secs). We will discuss the solution of the time-dependent elastic wave equation for an arbitrary fault system using escript. This involves prescribing the correct initial stress distribution in the system to simulate the quasi-static loading of faults to failure; determining a suitable frictional constitutive law which accurately reproduces the dynamics of the stick/slip instability at the faults; and using a robust time integration scheme. These dynamic models generate data and information that can be used for earthquake forecasting.

Kettle, L. M.; Mora, P.; Weatherley, D.; Gross, L.; Xing, H.

2006-12-01

405

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

Microsoft Academic Search

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

Yaguo Lei; Zhengjia He; Yanyang Zi

2009-01-01

406

Automatic Method for Correlating Horizons across Faults in 3D Seismic Data  

Microsoft Academic Search

Horizons are visible boundaries between certain sediment layers in seismic data, and a fault is a crack of horizons and it is recognized in seismic data by the discontinuities of horizons layers. Interpretation of seismic data is a time- consuming manual task, which is only partially supported by computer methods. In this paper, we present an auto- matic method for

Fitsum Admasu; Klaus D. Tönnies

2004-01-01

407

A fault diagnosis method for power system based on multilayer information fusion structure  

Microsoft Academic Search

This paper proposes an information fusion method for diagnosis. Multilayer structure of information fusion included data proposing, feature extraction and decision making, is constructed for dealing with the objects such as current, voltage and wave, etc. A Petri-network and a fault matching method of WAMS data are used in characteristic fusion. The application of this fame in the simulation resolves

Yi Liu; Yang Wang; Mingwei Peng; Chuangxin Guo

2010-01-01

408

Numerical simulations of earthquakes and the dynamics of fault systems using the Finite Element method  

Microsoft Academic Search

Simulations using the Finite Element method are widely used in many engineering applications and for the solution of partial differential equations (PDEs). Computational models based on the solution of PDEs play a key role in earth systems simulations. We present numerical modelling of crustal fault systems where the dynamic elastic wave equation is solved using the Finite Element method. This

L. M. Kettle; P. Mora; D. Weatherley; L. Gross; H. Xing

2006-01-01

409

A non-scan DFT method at register-transfer level to achieve complete fault efficiency  

Microsoft Academic Search

This paper presents a non-scan design-for- testability (DFT) method for VLSIs designed at register- transfer level (RTL) to achieve complete fault efficiency. In RTL design, a VLSI generally consists of a controller and a data path. The controller and the data path are con- nected with internal signals: control signals and status sig- nals. The proposed method consists of the

Satoshi Ohtake; Hiroki Wada; Toshimitsu Masuzawa; Hideo Fujiwara

2000-01-01

410

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

411

Comparison between Finite Element Method and Equilibrium Element Method to Predict Stress Field in Fault-bend Folds  

Microsoft Academic Search

The objective is to compare the merits of the Equilibrium Element Method (EEM), based on the internal approach of limit analysis, and the Finite-Element Method (FEM) for elastic perfectly plastic materials, in predicting the stress field in geological structures such as fault-bend folds. The two methods predict the same failure mode although the discontinuities in the stress fields constructed with

P. Souloumiac

412

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

NASA Astrophysics Data System (ADS)

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

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

2007-05-01

413

A Virtual Sensor for Online Fault Detection of Multitooth-Tools  

PubMed Central

The installation of suitable sensors close to the tool tip on milling centres is not possible in industrial environments. It is therefore necessary to design virtual sensors for these machines to perform online fault detection in many industrial tasks. This paper presents a virtual sensor for online fault detection of multitooth tools based on a Bayesian classifier. The device that performs this task applies mathematical models that function in conjunction with physical sensors. Only two experimental variables are collected from the milling centre that performs the machining operations: the electrical power consumption of the feed drive and the time required for machining each workpiece. The task of achieving reliable signals from a milling process is especially complex when multitooth tools are used, because each kind of cutting insert in the milling centre only works on each workpiece during a certain time window. Great effort has gone into designing a robust virtual sensor that can avoid re-calibration due to, e.g., maintenance operations. The virtual sensor developed as a result of this research is successfully validated under real conditions on a milling centre used for the mass production of automobile engine crankshafts. Recognition accuracy, calculated with a k-fold cross validation, had on average 0.957 of true positives and 0.986 of true negatives. Moreover, measured accuracy was 98%, which suggests that the virtual sensor correctly identifies new cases.

Bustillo, Andres; Correa, Maritza; Renones, Anibal

2011-01-01

414

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

Microsoft Academic Search

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

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

2006-01-01

415

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

416

Using functional fault simulation and the difference fault model to estimate implementation fault coverage  

Microsoft Academic Search

An approach to estimate the fault coverage of the implementation of a VLSI design obtained by fault simulation at the function level is presented. The proposed methodology begins by defining a fault model for the functional level, the difference fault model (DFM), which reflects all of the faults in the implementation level. Functional fault detection is recorded by performing a

Gabriel M. Silberman; Ilan Y. Spillinger

1990-01-01

417

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

418

An intelligent fault diagnosis method of rolling bearings based on regularized kernel Marginal Fisher analysis  

NASA Astrophysics Data System (ADS)

Generally, the vibration signals of fault bearings are non-stationary and highly nonlinear under complicated operating conditions. Thus, it's a big challenge to extract optimal features for improving classification and simultaneously decreasing feature dimension. Kernel Marginal Fisher analysis (KMFA) is a novel supervised manifold learning algorithm for feature extraction and dimensionality reduction. In order to avoid the small sample size problem in KMFA, we propose regularized KMFA (RKMFA). A simple and efficient intelligent fault diagnosis method based on RKMFA is put forward and applied to fault recognition of rolling bearings. So as to directly excavate nonlinear features from the original high-dimensional vibration signals, RKMFA constructs two graphs describing the intra-class compactness and the inter-class separability, by combining traditional manifold learning algorithm with fisher criteria. Therefore, the optimal low-dimensional features are obtained for better classification and finally fed into the simplest K-nearest neighbor (KNN) classifier to recognize different fault categories of bearings. The experimental results demonstrate that the proposed approach improves the fault classification performance and outperforms the other conventional approaches.

Jiang, Li; Shi, Tielin; Xuan, Jianping

2012-05-01

419

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

420

EEMD method and WNN for fault diagnosis of locomotive roller bearings  

Microsoft Academic Search

The ensemble empirical mode decomposition (EEMD) can overcome the mode mixing problem of the empirical mode decomposition (EMD) and therefore provide more precise decomposition results. Wavelet neural network (WNN) possesses the advantages of both wavelet transform and artificial neural networks. This paper combines the merits of EEMD and WNN to propose an automated and effective fault diagnosis method of locomotive

Yaguo Lei; Zhengjia He; Yanyang Zi

2011-01-01

421

Life test method and fault mechanism analysis of pneumatic pressure regulator  

Microsoft Academic Search

Pneumatic pressure regulator is an important element in pneumatic fluid power systems; it decompresses and regulates the pressure of system, so its performance determines the system's performance and its reliability must be grasped. The paper firstly presents a method about the reliability test circuit of pneumatic regulators, which include test conditions, test circuit and threshold levels; then analyses the fault

Jungong Ma; Juan Chen; Xiaoye Qi; Zhanlin Wang; N. Oneyama

2009-01-01

422

Method for detecting biological toxins  

SciTech Connect

Biological toxins are indirectly detected by using polymerase chain reaction to amplify unique nucleic acid sequences coding for the toxins or enzymes unique to toxin synthesis. Buffer, primers coding for the unique nucleic acid sequences and an amplifying enzyme are added to a sample suspected of containing the toxin. The mixture is then cycled thermally to exponentially amplify any of these unique nucleic acid sequences present in the sample. The amplified sequences can be detected by various means, including fluorescence. Detection of the amplified sequences is indicative of the presence of toxin in the original sample. By using more than one set of labeled primers, the method can be used to simultaneously detect several toxins in a sample.

Ligler, F.S.; Campbell, J.R.

1992-01-01

423

Fault Modeling and Functional Test Methods for Digital Microfluidic Biochips  

Microsoft Academic Search

Dependability is an important attribute for microfluidic biochips that are used for safety-critical applications, such as point-of-care health assessment, air-quality monitoring, and food-safety testing. Therefore, these devices must be adequately tested after manufacture and during bioassay operations. Known techniques for biochip testing are all function oblivious (i.e., while they can detect and locate defect sites on a microfluidic array, they

Tao Xu; Krishnendu Chakrabarty

2009-01-01

424

Multi-Index Fusion-Based Fault Diagnosis Theories and Methods  

NASA Astrophysics Data System (ADS)

In this paper, using the information theory and the statistics analysis method, we have established the theory and method of faults diagnosis based on the multi-index fusion, including the information theory of multi-index diagnosis, diagnosis ability testing, indexes selecting, and Bayesian diagnosis modelling. And then, we applied the theories and methods to analyse the piston-liner wear condition of a diesel engine. In that, satisfactory results are achieved.

Wu, X.; Chen, J.; Wang, W.; Zhou, Y.

2001-09-01

425

Comparison of Fault Representation Methods in Finite Difference Simulations of Dynamic Rupture  

Microsoft Academic Search

Assessing accuracy of numerical methods for spontaneous rupture simu- lation is challenging because we lack analytical solutions for reference. Previous comparison of a boundary integral method (BI) and finite-difference method (called DFM) that explicitly incorporates the fault discontinuity at velocity nodes (traction- at-split-node scheme) shows that both converge to a common, grid-independent so- lution and exhibit nearly identical power-law convergence

Luis A. Dalguer; Steven M. Day

2006-01-01

426

Tunnel Detection Using Seismic Methods  

Microsoft Academic Search

Surface seismic methods have shown great promise for use in detecting clandestine tunnels in areas where unauthorized movement beneath secure boundaries have been or are a matter of concern for authorities. Unauthorized infiltration beneath national borders and into or out of secure facilities is possible at many sites by tunneling. Developments in acquisition, processing, and analysis techniques using multi-channel seismic

R. Miller; C. B. Park; J. Xia; J. Ivanov; D. W. Steeples; N. Ryden; R. F. Ballard; J. L. Llopis; T. S. Anderson; M. L. Moran; S. A. Ketcham

2006-01-01

427

Field test results of DC arc fault detection on residential and utility scale PV arrays  

Microsoft Academic Search

It has been recognized that DC arcing faults pose a hazard in present photovoltaic (PV) systems. The 2011 National Electric Code [1] added a requirement for arc fault circuit protection and Underwrites Laboratories (UL) recently published an outline of investigation (UL1699B) to define the requirements for such a device. To satisfy the need for a PV arc fault detector (AFD)

Charles Luebke; Tom Pier; Birger Pahl; Dan Breig; Joseph Zuercher

2011-01-01

428

Ground Motion Simulation for a Large Active Fault System using Empirical Green's Function Method and the Strong Motion Prediction Recipe - a Case Study of the Noubi Fault Zone -  

Microsoft Academic Search

The 1995 Hyogo-ken Nambu Earthquake (1995) near Kobe, Japan, spurred research on strong motion prediction. To mitigate damage caused by large earthquakes, a highly precise method of predicting future strong motion waveforms is required. In this study, we applied empirical Green's function method to forward modeling in order to simulate strong ground motion in the Noubi Fault zone and examine

M. Kuriyama; T. Kumamoto; M. Fujita

2005-01-01

429

Fault reconstruction from sensor and actuator failures  

Microsoft Academic Search

Many fault detection filters have been developed to detect and identify sensor and actuator faults by using analytical redundancy. In this paper, an approach for reconstructing sensor and actuator faults from the residual generated by the fault detection filter is proposed. The transfer matrix from the faults to the residual is derived in terms of the eigenvalues of the fault

Robert H. Chen; Jason L. Speyer

2001-01-01

430

Bridge fault simulation strategies for CMOS integrated circuits  

Microsoft Academic Search

Abstract Unfaulted Circuit Faulted Circuit X X After introducing the Primitive Bridge Function , a char - acteristic function describing the behavior of bridged com - ponents, we present a theorem for detecting feedback bridge faults We discuss two di erent methods of bridge fault simu - lation, one of which is new, and present experimental results relating the relative

Brian Chess; Tracy Larrabee

1993-01-01

431

The use of Petri nets to analyze coherent fault trees  

Microsoft Academic Search

The use of Petri nets to represent fault trees is discussed. Using reachability and other analytic properties of Petri nets, a more general and useful method to study the dynamic behavior of the model at various levels of abstraction is examined. The problems of fault-detection and propagation are discussed. For simplicity, only coherent fault trees are considered. However, the representation

G. S. Hura; J. W. Atwood

1988-01-01

432

An integrated electro-mechanical model of motor-gear units—Applications to tooth fault detection by electric measurements  

NASA Astrophysics Data System (ADS)

Fault diagnosis in geared transmissions is traditionally based on vibration monitoring but, in a number of cases, sensor implementation and signal transfer from rotary to stationary parts can cause problems. This paper presents an original integrated electro-mechanical model aimed at testing the possibility and the interest of tooth fault detection based on electric measurements on the motor stator. The motor is simulated using Kron's transformation while the mechanical transmission is accounted for by a lumped parameter model. Tooth defects are assimilated to distributions of initial separations between the mating flanks whose positions and shapes are controlled. A unique non-linear parametrically excited differential system is obtained, which provides direct access to both the electrical and mechanical variables. A number of results are presented, which illustrate the possibility of tooth fault detection by stator current measurements with regard to the position and dimensions of the defect.

Feki, N.; Clerc, G.; Velex, Ph.

2012-05-01

433

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

434

Identifying past earthquakes on carbonate faults: Advances and limitations of the 'Rare Earth Element' method based on analysis of the Spili Fault, Crete, Greece  

NASA Astrophysics Data System (ADS)

Recent work ( Carcaillet et al., 2008; Manighetti et al., 2010) has utilised a well-established earthquake record on a normal fault in Italy (the Magnola Fault) to successfully test a new method for identifying paleoearthquakes on carbonate rocks: that of chemical analysis of their exhumed fault planes. Here we take the next natural step, applying this novel method on a notionally active normal fault in Greece, the Spili Fault, for which no paleoearthquake record exists. Despite the 'blind' sampling, data reveal an outstanding record of systematic fluctuations in the concentrations of Rare Earth Elements (REE) and Yttrium (Y) upscarp, which closely resemble those recorded on the Magnola Fault. Chemical analysis of 35 core-samples extracted from a 10 m high section of the exhumed Spili Fault plane records upscarp depletion in the REE-Y concentrations at an average rate of ca. 9.3%/m. Depletion is overprinted by locally increased REE-Y concentrations upscarp. A minimum of four such concentration fluctuations, with wavelengths ranging from 0.5 to 3 m, are recorded. Each fluctuation is interpreted to be generated by at least one paleoearthquake that episodically exhumed a zone of the fault plane. Each zone consists of an upper domain that is enriched in REE-Y and a lower un-enriched domain. REE-Y enrichment is due to the prolonged (at least few 100's of years) contact of the limestone with the soil, whereas the un-enriched domain reflects instantaneous uplift from depths greater than the base of the soil, during the same earthquake. The REE-Y analytical method cannot resolve individual small-sized earthquakes (with slip less than the thickness of the soil-cover) and/or individual large- and small-sized earthquakes which are clustered in time (repeat time< 100's yr). It may therefore yield better results when applied on large (? 20 km) carbonate faults that rupture the earth's crust at most once every ca. 0.5 kyr; nevertheless the number of identified earthquakes should always be treated as a minimum.

Mouslopoulou, Vasiliki; Moraetis, Daniel; Fassoulas, Charalambos

2011-09-01

435

Leak detection method and apparatus  

SciTech Connect

A method and apparatus are described for using sulfur hexafluoride to detect leaks in fluid processing systems. Leak detection can be performed with the processing system continuing in operation. This apparatus detects leakage through a partition separating a portion of a first path from portion of a second path in a fluid processing system, while operation of the system is continued. The apparatus comprises a combination of 1) means for introducing a known quantity of sulfur hexafluoride into fluid flowing in the first path upstream of a partition; 2) means for continuously removing a sample of fluid flowing in the second path at a locus downstream of the partition; 3) means for removing normally liquid components from the sample; 4) means for testing the sample to determine the presence of sulfur hexafluoride; and 5) means for indicating the amount of sulfur hexafluoride in the sample. 2 claims.

Fries, B.A.

1982-05-11

436

Generic faults - The first word  

NASA Astrophysics Data System (ADS)

The achievement of highly reliable, full time critical control system designs, such as those of fly-by-wire and fly-by-light flight control systems, is through the institution of development methods which increase the likelihood of faults' detection and toleration by redundant system architectural practices and reconfiguration capabilities. Management methods must accordingly give attention to factors that can be computed to act as predictors of fault and error performance on the basis of physical data.

Cannon, D. G.

437

Importance Measure Method for Dynamic Fault Tree Based on Isomorphic Node  

Microsoft Academic Search

\\u000a In order to enhance the measure efficiency in the research field of importance measure for dynamic fault tree which contains\\u000a some structural information, a new method using this information is presented. By means of creating an object for every node,\\u000a identifying the isomorphic nodes and computing only once for the same kind of isomorphic nodes, this method reduces the number

Hong-Lin Zhang; Chun-Yuan Zhang; Dong Liu; Gui-Wu Xie

2010-01-01

438

The cause of false operating of the rotor ground fault protection based on the AC injection method  

Microsoft Academic Search

In this paper we tackle the issues of the protection of a synchronous generator field winding in the case of the first ground fault. We analyze the reasons of false operation of the rotor ground fault protection based on the AC injection method on the synchronous machine with a static excitation system. This paper presents the results of the measurements

A. Belan; Z. Eleschova; F. Janicek

2005-01-01

439

A new approach for fault detection of broken rotor bars in induction motor based on support vector machine  

Microsoft Academic Search

In this paper, a new approach is proposed to perform broken rotor bar fault detection in induction motors using of support vector machine (SVM) classifier. New features such as harmonic curve area, harmonic crest angle and harmonic amplitude have been extracted from power spectral density (PSD) of stator current in steady state condition using of Fast Fourier Transform (FFT). It

Mahdi Gordi Armaki; Reza Roshanfekr

2010-01-01

440

FAULT DETECTION IN A CAMS SYSTEM EXCITADED BY AN UNBALANCING FORCE USING THE METHODOLOGY OF STATE OBSERVERS  

Microsoft Academic Search

The main purpose of this paper is to present the methodology of State Observers applicability trough a specific application at a valve system of an internal combustion engine. Satisfactory results were found using global and robust observation to detect and localize the fault at this system.

Vinícius Fernandes; Gilberto Pechoto de Melo

441

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

Microsoft Academic Search

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

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

2011-01-01

442

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

NASA Astrophysics Data System (ADS)

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

Leclère, Henri; Fabbri, Olivier

2013-04-01

443

A dynamic fault tree  

Microsoft Academic Search

The fault tree analysis is a widely used method for evaluation of systems reliability and nuclear power plants safety. This paper presents a new method, which represents extension of the classic fault tree with the time requirements. The dynamic fault tree offers a range of risk informed applications. The results show that application of dynamic fault tree may reduce the

Marko ?epin; Borut Mavko

2002-01-01

444

Diagnosing process faults using neural network models  

SciTech Connect

In order to be of use for realistic problems, a fault diagnosis method should have the following three features. First, it should apply to nonlinear processes. Second, it should not rely on extensive amounts of data regarding previous faults. Lastly, it should detect faults promptly. The authors present such a scheme for static (i.e., non-dynamic) systems. It involves using a neural network to create an associative memory whose fixed points represent the normal behavior of the system.

Buescher, K.L.; Jones, R.D.; Messina, M.J.

1993-11-01

445

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

Microsoft Academic Search

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

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

2011-01-01

446

Quasi-induced exposure method: evaluation of not-at-fault assumption.  

PubMed

Crash rates are used to establish the relative safety of various variables of concern such as driver classes, vehicle types and roadway components. Appropriate exposure data for estimating crash rates is critical but crash databases do not contain information on driver or vehicle exposure. The quasi-induced exposure method, which uses not-at-fault driver/vehicle data as an exposure metric, is a technique used in order to overcome this problem. The basic assumption made here is that not-at-fault drivers represent the total population in question. This paper examines the validity of this assumption using the Kentucky crash database to define two samples of not-at-fault drivers. One sample included only not-at-fault drivers selected from the first two vehicles in a multi-vehicle crash (two or more vehicles involved) while the other included the not-at-fault drivers from multi-vehicle crashes with more than two vehicles involved and excluding the first two drivers. The assumption is that the randomness of the involvement of drivers in the second sample is more reasonable than the drivers in the first two vehicles involved in crashes. The results indicate that these two samples are similar; there is no statistical evidence demonstrating that both samples represent two different populations in the maneuvers and other variables/factors examined here; and they are representative simple random samples of the driver population with respect to the distribution of the driver age when there is no reasonable doubt about investigating officers' judgments. Thus, estimating relative crash propensities for any given driver type by using the quasi-induced exposure approach will yield reasonable estimates of exposure. PMID:19245890

Chandraratna, Susantha; Stamatiadis, Nikiforos

2009-01-20

447

Votierungsverfahren als Teil der Fehlertoleranz in Verteilten Pdv-Systemen (Vote Methods as a Part of the Fault Tolerance in Distribution Process Data Processing Systems).  

National Technical Information Service (NTIS)

Faults and fault tolerance, taking into account design faults, as well as existing vote methods are presented. The environment of the vote method, the concepts on which it is based and the computer programming are presented. The vote method was experiment...

G. Pauthner

1986-01-01

448

Method for detecting toxic gases  

DOEpatents

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

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

1991-01-01

449

A Novel Fault Diagnosis Method Based-on Modified Neural Networks for Photovoltaic Systems  

Microsoft Academic Search

\\u000a The main purpose of this paper is to propose an intelligent fault diagnostic method for photovoltaic (PV) systems. First,\\u000a Solar Pro software package was used to simulate a photovoltaic system for gathering power generation data of photovoltaic\\u000a modules during normal operations and malfunctions. Then, the collected power generation data was used to construct matter-element\\u000a models based on extension theory for

Kuei-Hsiang Chao; Chao-Ting Chen; Meng-Hui Wang; Chun-Fu Wu

2010-01-01

450

An optimized fault diagnosis method for reciprocating air compressors based on SVM  

Microsoft Academic Search

Fault diagnosis in reciprocating air compressors is essential for continuous monitoring of their performance and thereby ensuring quality output. Support Vector Machines (SVMs) are machine learning tools based on structural risk minimization principle and have the advantageous characteristic of good generalization. For this reason, four well-known and widely used SVM based methods, one-against-one (OAO), oneagainst-all (OAA), fuzzy decision function (FDF),

Nishchal K. Verma; Abhishek Roy; Al Salour

2011-01-01

451

Combining Methods for the Analysis of a Fault-Tolerant System  

Microsoft Academic Search

This paper presents experiences gained from the verification of a large-scale real-world embedded system by means of formal methods. This industrial verification project was performed for a fault-tolerant system designed and implemented by DaimlerChrysler Aerospace for the International Space Station ISS. The verification involved various aspects of system correctness, like deadlock and livelock analysis, correct protocol implementation, etc. The approach

Hui Shi; Jan Peleska; Michel Kouvaras

1999-01-01

452

Fault model development for fault tolerant VLSI design  

NASA Astrophysics Data System (ADS)

Fault models provide systematic and precise representations of physical defects in microcircuits in a form suitable for simulation and test generation. The current difficulty in testing VLSI circuits can be attributed to the tremendous increase in design complexity and the inappropriateness of traditional stuck-at fault models. This report develops fault models for three different types of common defects that are not accurately represented by the stuck-at fault model. The faults examined in this report are: bridging faults, transistor stuck-open faults, and transient faults caused by alpha particle radiation. A generalized fault model could not be developed for the three fault types. However, microcircuit behavior and fault detection strategies are described for the bridging, transistor stuck-open, and transient (alpha particle strike) faults. The results of this study can be applied to the simulation and analysis of faults in fault tolerant VLSI circuits.

Hartmann, C. R.; Lala, P. K.; Ali, A. M.; Visweswaran, G. S.; Ganguly, S.

1988-05-01

453

Fault detection system including a capacitor for generating a pulse and a processor for determining admittance versus frequency of a reflected pulse  

US Patent & Trademark Office Database

A system comprising a portable apparatus and employing a method of admittance versus frequency analysis to detect the existence of a fault in a de-energized electrical line regardless of whether the line contains branches. The portable apparatus comprises a capacitor unit detachably connected to a de-energized line, ground or a neutral conductor, a switch unit detachably connected to a de-energized line, the de-energized line being tested, and an insulated cable connecting the capacitor unit to the switch unit. The switch unit comprises a discharge switch that can be activated by pulling on the hot line tool. The capacitor unit comprises a capacitor which is discharged into the electrical line via the insulated cable and the switch unit when the discharge switch is activated to create a pulse. The capacitor unit comprises circuitry for generating voltage and current samples of pulse response signals and a microprocessor for determining the admittance of the electrical line using Fast Fourier transforms of the current and voltage samples. The admittance of the line is compared with stored data relating to lines having different load impedances and having faults located at various distances from the capacitor unit and detectable at various frequencies to determine the existence of a fault.

Rhein; David Adelbert (Columbia, MO); Beard; Lloyd Ronald (Centralia, MO); Roberts; Gerald Bernard (Paris, MO); Herrick; Thomas Jude (Rolla, MO)

1997-07-22

454

A model-based fault-detection and prediction scheme for nonlinear multivariable discrete-time systems with asymptotic stability guarantees.  

PubMed

In this paper, a novel, unified model-based fault-detection and prediction (FDP) scheme is developed for nonlinear multiple-input-multiple-output (MIMO) discrete-time systems. The proposed scheme addresses both state and output faults by considering separate time profiles. The faults, which could be incipient or abrupt, are modeled using input and output signals of the system. The fault-detection (FD) scheme comprises online approximator in discrete time (OLAD) with a robust adaptive term. An output residual is generated by comparing the FD estimator output with that of the measured system output. A fault is detected when this output residual exceeds a predefined threshold. Upon detecting the fault, the robust adaptive terms and the OLADs are initiated wherein the OLAD approximates the unknown fault dynamics online while the robust adaptive terms help in ensuring asymptotic stability of the FD design. Using the OLAD outputs, a fault diagnosis scheme is introduced. A stable parameter update law is developed not only to tune the OLAD parameters but also to estimate the time to failure (TTF), which is considered as a first step for prognostics. The asymptotic stability of the FDP scheme enhances the detection and TTF accuracy. The effectiveness of the proposed approach is demonstrated using a fourth-order MIMO satellite system. PMID:20106734

Thumati, Balaje T; Jagannathan, S

2010-01-26

455

Comparison between different methodologies for detecting radon in soil along an active fault: the case of the Pernicana fault system, Mt. Etna (Italy).  

PubMed

Three different methodologies were used to measure Radon ((222)Rn) in soil, based on both passive and active detection system. The first technique consisted of solid-state nuclear track detectors (SSNTD), CR-39 type, and allowed integrated measurements. The second one consisted of a portable device for short time measurements. The last consisted of a continuous measurement device for extended monitoring, placed in selected sites. Soil (222)Rn activity was measured together with soil Thoron ((220)Rn) and soil carbon dioxide (CO(2)) efflux, and it was compared with the content of radionuclides in the rocks. Two different soil-gas horizontal transects were investigated across the Pernicana fault system (NE flank of Mount Etna), from November 2006 to April 2007. The results obtained with the three methodologies are in a general agreement with each other and reflect the tectonic settings of the investigated study area. The lowest (222)Rn values were recorded just on the fault plane, and relatively higher values were recorded a few tens of meters from the fault axis on both of its sides. This pattern could be explained as a dilution effect resulting from high rates of soil CO(2) efflux. Time variations of (222)Rn activity were mostly linked to atmospheric influences, whereas no significant correlation with the volcanic activity was observed. In order to further investigate regional radon distributions, spot measurements were made to identify sites having high Rn emissions that could subsequently be monitored for temporal radon variations. SSNTD measurements allow for extended-duration monitoring of a relatively large number of sites, although with some loss of temporal resolution due to their long integration time. Continuous monitoring probes are optimal for detailed time monitoring, but because of their expense, they can best be used to complement the information acquired with SSNTD in a network of monitored sites. PMID:18986811

Giammanco, S; Immè, G; Mangano, G; Morelli, D; Neri, M

2008-09-26

456

Exoplanet Detection: Radial Velocity Method  

NSDL National Science Digital Library

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

Belloni, Mario

2010-06-29

457

Transition Fault Simulation  

Microsoft Academic Search

Delay fault testing is becoming more important as VLSI chips become more complex. Components that are fragments of functions, such as those in gate-array designs, need a general model of a delay fault and a feasible method of generating test patterns and simulating the fault. The authors present such a model, called a transition fault, which when used with parallel-pattern,

John Waicukauski; Eric Lindbloom; Barry Rosen; Vijay Iyengar

1987-01-01

458

FPGA-Based Online Induction Motor Multiple-Fault Detection with Fused FFT and Wavelet Analysis  

Microsoft Academic Search

Online monitoring of rotary machines, like induction motors, can effectively diagnosis electrical and mechanical faults. The origin of most recurrent faults in rotary machines is in the components: bearings, stator, rotor and others. Different methodologies based on current and vibration monitoring have been proposed using FFT and wavelet analysis for preventive monitoring of induction motors resulting in countless techniques for

E. Cabal-Yepez; Roque A. Osornio-Rios; René de Jesús Romero-Troncoso; J. R. Razo-Hernandez; R. Lopez-Garcia

2009-01-01

459

Gear Fault Detection Based on Ensemble Empirical Mode Decomposition and Hilbert-Huang Transform  

Microsoft Academic Search

A new approach to fault diagnosis of gear crack based on ensemble empirical mode decomposition (EEMD) and Hilbert-Huang transform (HHT) technique is presented. Firstly, the time-domain vibration signal of the gearbox with gear crack fault is measured. Then the original vibration signal is separated into intrinsic oscillation modes, using the ensemble empirical mode decomposition. Secondly, Hilbert transform tracks the modulation

Shufeng Ai; Hui Li

2008-01-01

460

Fuzzy fault diagnostic system based on fault tree analysis  

Microsoft Academic Search

A method is presented for process fault diagnosis using information from fault tree analysis and uncertainty\\/imprecision of data. Fault tree analysis, which has been used as a method of system reliability\\/safety analysis, provides a procedure for identifying failures within a process. A fuzzy fault diagnostic system is constructed which uses the fuzzy fault tree analysis to represent a knowledge of

Zong-Xiao Yang; Kazuhiko SUZUKI; Yukiyasu SHIMADA; Hayatoshi SAYAMA

1995-01-01

461

Detection, isolation, and identification of sensor faults in nuclear power plants  

Microsoft Academic Search

This paper presents methods to detect, locate, and identify sensor degradations. The first method is based on simple redundancy and consists in generating residuals by comparison of measurements provided by physically redundant sensors. The second uses analytical redundancy. Residuals are generated by comparing each measurement with an estimate computed from models of the process. The efficiency of each method is

Richard Dorr; F. Kratz; J. Ragot; F. Loisy; J.-L. Germain

1996-01-01

462

Failure detection and identification and fault tolerant control using the IMM-KF with applications to the Eagle-Eye UAV  

Microsoft Academic Search

We describe a novel approach to sensor\\/actuator failure detection and identification and fault tolerant control based on the interacting multiple model (IMM) Kalman filter approach. Failures are mapped into different (and unique) state-space model representations. The IMM algorithm computes (online) the posterior probability of each failure model, that can be interpreted as a failure indicator. The fault tolerant control approach

C. Rago; Ravi Prasanth; Raman K. Mehra; Robert Fortenbaugh

1998-01-01

463

Thermal Infrared Airborne Hyperspectral Detection of Fumarolic Ammonia Venting on the Calipatria Fault in the Salton Sea Geothermal Field, Imperial County, California  

Microsoft Academic Search

An airborne hyperspectral imaging survey was conducted along the Calipatria Fault in the vicinity of the Salton Sea in Southern California. In addition to strong thermal hotspots associated with active fumaroles along the fault, a number of discrete and distributed sources of ammonia were detected. Mullet Island, some recently exposed areas of sea floor, and a shallow-water fumarolic geothermal vent

D. K. Lynch; D. M. Tratt; K. N. Buckland; J. L. Hall; B. P. Kasper; M. G. Martino; L. J. Ortega; K. R. Westberg; S. J. Young; P. D. Johnson

2009-01-01

464

Comparison of methods for uncertainty analysis of nuclear-power-plant safety-system fault-tree models. [PWR; BWR  

Microsoft Academic Search

A comparative evaluation is made of several methods for propagating uncertainties in actual coupled nuclear power plant safety system faults tree models. The methods considered are Monte Carlo simulation, the method of moments, a discrete distribution method, and a bootstrap method. The Monte Carlo method is found to be superior. The sensitivity of the system unavailability distribution to the choice

H. F. Martz; R. J. Beckman; K. Campbell; D. E. Whiteman; J. M. Booker

1983-01-01

465

LMD Method and Multi-Class RWSVM of Fault Diagnosis for Rotating Machinery Using Condition Monitoring Information  

PubMed Central

Timely and accurate condition monitoring and fault diagnosis of rotating machinery are very important to maintain a high degree of availability, reliability and operational safety. This paper presents a novel intelligent method based on local mean decomposition (LMD) and multi-class reproducing wavelet support vector machines (RWSVM), which is applied to diagnose rotating machinery faults. First, the sensor-based vibration signals measured from the rotating machinery are preprocessed by the LMD method and product functions (PFs) are produced. Second, statistic features are extracted to acquire more fault characteristic information from the sensitive PF. Finally, these features are fed into a multi-class RWSVM to identify the rotating machinery health conditions. The experimental results validate the effectiveness of the proposed RWSVM method in identifying rotating machinery fault patterns accurately and effectively and its superiority over that based on the general SVM.

Liu, Zhiwen; Chen, Xuefeng; He, Zhengjia; Shen, Zhongjie

2013-01-01

466

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

NASA Astrophysics Data System (ADS)

Water plays an important role in the processes occurring at subduction zones since the release of water from the downgoing slab impacts seismicity and enhances arc volcanism. Geochemical indicators suggest that the Nicaraguan slab is anomalously wet, yet the mechanism of slab hydration remains poorly constrained. Extensional bending faults on the incoming oceanic plate of the Middle America Trench offshore Nicaragua have been observed to penetrate to mantle depths, suggesting a permeable pathway for hydration of the crust and serpentinization of the upper mantle. Low seismic velocities observed in the uppermost mantle of the incoming plate have been explained as serpentinization due to deep fluid penetration but could also be explained by intrinsic anisotropy and fractures in the absence of fluid circulation. Here we use controlled-source electromagnetic imaging to map the electrical resistivity of the crust and uppermost mantle along a 220 km profile crossing the trench offshore Nicaragua. Along the incoming plate our data reveal that crustal resistivity decreases by up to a factor of five directly with the onset of the bending faults. Furthermore, a strong azimuthal anisotropy compatible with conductive vertical fault planes is observed only on the faulted trench seafloor. The observed resistivity decrease and anisotropy can be explained by a porosity increase along vertical fault planes, which we interpret as evidence that the lithospheric bending faults provide the necessary permeable fluid pathways required for serpentinization of the uppermost mantle. This implies that most serpentinisation happens at the trench, with the width of the faulting region and the density of fractures controlling the extent of upper mantle alteration. This observation explains why the heavily faulted trench offshore Nicaragua is associated with an anomalously wet slab, whereas other sections of the Middle America Trench containing fewer bending faults have less fluid flux from the subducting slab.

Key, Kerry; Constable, Steven; Matsuno, Tetsuo; Evans, Rob L.; Myer, David

2012-10-01

467

A discussion on using Empirical Mode Decomposition for incipient fault detection and diagnosis of the wind turbine gearbox  

Microsoft Academic Search

Vibration signals from the gearbox of a wind turbine are essentially non-stationary and nonlinear in both time and frequency. Empirical Mode Decomposition (EMD) is an ideal method for dealing with this type of signal. Yet the signal containing the fault information was contaminated by the noise, which contains two different types of white noise and impact noise. This makes it

Yanyong Li

2010-01-01

468

Adaptive neuro-fuzzy inference system for bearing fault detection in induction motors using temperature, current, vibration data  

Microsoft Academic Search

In this study the features for bearing fault diagnosis is investigated based on the analysis of temperature, vibration and current measurements of a 3 phase, 4 poles, 5 HP induction motors which are chemically, thermally and electrically aged by artificial aging methods. Then three adaptive neuro-fuzzy inference systems which takes the temperature, current and vibration measurements as inputs and the

Malik S. Yilmaz; Emine Ayaz

2009-01-01

469

Concurrent error detection of fault-based side-channel cryptanalysis of 128-bit RC6 block cipher  

Microsoft Academic Search

Fault-based side channel cryptanalysis is very effective against symmetric and asymmetric encryption algorithms. Although straightforward hardware and time redundancy based concurrent error detection (CED) architectures can be used to thwart such attacks, they entail significant overhead (either area or performance). In this paper we investigate two systematic approaches to low-cost, low-latency CED for symmetric encryption algorithm RC6. The proposed techniques

Kaijie Wu; Piyush Mishra; Ramesh Karri

2003-01-01

470

Concurrent error detection of fault-based side-channel cryptanalysis of 128-bit symmetric block ciphers  

Microsoft Academic Search

Fault-based side channel cryptanalysis is very effective against symmetric and asymmetric encryption algorithms. Although straightforward hardware and time redundancy based concurrent error detection (CED) architectures can be used to thwart such attacks, they entail significant overhead (either area or performance). In this paper we investigate systematic approaches to low-cost, low-latency CED for symmetric encryption algorithms based on the inverse relationship

Ramesh Karri; Kaijie Wu; Piyush Mishra; Yongkook Kim

2001-01-01

471

Fine fault structure in intraplate earthquake region estimated by DD method with waveform correlation analysis, using nationwide seismic network Hi-net, Japan  

NASA Astrophysics Data System (ADS)

Determining highly resolved hypocenter distribution in intraplate earthquake region is very important for estimation of fine fault structure. The dense permanent nationwide seismic observation network (NIED Hi-net) with an average spacing of 20-30km has been developed all over the Japan region after the disasters of 1995 Kobe earthquake. The detection capability and accuracy of hypocentral location was quite improved by Hi-net. On the other hand, a double-difference (DD) earthquake location algorithm (Waldhauser and Ellsworth, 2000) was developed to improve the accuracy of relative hypocenter location. In this method, further improvement of location is expected by using waveform cross-correlation method. We applied DD algorithm using waveform cross- correlation method to the Hi-net data, to estimate the fine fault structure and confirm the availability of Hi-net routine seismic observation network. We relocated the hypocenters of aftershock sequences of two moderate crustal earthquakes, and of seismicity around the active fault system which displays one of the largest slip rates in the Japanese islands. We used the absolute travel time measurements and differential travel time measurements by waveform cross-correlation analysis. In this analysis, the velocity waveform of 0.75 sec containing the P or S wave onset was used, applying 3-20 Hz band-pass filter. Moderate crustal earthquakes occurred in the northern part of Mie Prefecture on 15 April, 2007 (Mw=5.0) and in the southwest part of Shizuoka Prefecture on 1 June, 2007 (Mw=4.4), each of which followed by aftershock sequences. In both regions, the hypocenter of aftershocks determined by routine process are scattered and we could not find any trend of main shock fault. However, the locations by DD method reveal the fine structure of seismicity. Most of events around the main shock hypocenter show a planer distribution, which is consistent with the focal mechanism of main shock. This planer distribution of hypocenters probably reflects the structure of main shock fault. In the northern part of Mie Prefecture, the locations by DD method also reveal another cluster 1 km off from the main shock hypocenter, which is parallel to the planer distribution of hypocenters around the main shock. This lineament might suggest a subsidiary fault system parallel to the fault of main shock. We relocated the hypocenter location around the Itoigawa-Shizuoka Tectonic Line active fault system (ISTL), which has large slip rate. In the northern part of ISTL, we found the planer distribution of hypocenters under the ISTL. In the central and south part of ISTL, on the other hand, the hypocenter distributions form a cloud surrounding the ISTL, which suggest that most of events did not occur on the ISTL in these areas. We concluded that the fine fault structure concerned with the moderate crustal earthquakes and the active fault system could be resolved from the hypocentral distribution by Hi-net, applying DD method. Aftershock sequences of moderate earthquakes define the planer distribution of hypocenters, which suggest that most of aftershocks concentrate on the fault of main shock.

Yukutake, Y.; Takeda, T.; Obara, K.

2007-12-01

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

National Technical Information Service (NTIS)

Runtime verification has primarily been developed and evaluated as a means of enriching the software