Solar system fault detection

Science.gov (United States)

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

1984-05-14

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.

Voltage Based Detection Method for High Impedance Fault in a Distribution System

Science.gov (United States)

Thomas, Mini Shaji; Bhaskar, Namrata; Prakash, Anupama

2016-09-01

High-impedance faults (HIFs) on distribution feeders cannot be detected by conventional protection schemes, as HIFs are characterized by their low fault current level and waveform distortion due to the nonlinearity of the ground return path. This paper proposes a method to identify the HIFs in distribution system and isolate the faulty section, to reduce downtime. This method is based on voltage measurements along the distribution feeder and utilizes the sequence components of the voltages. Three models of high impedance faults have been considered and source side and load side breaking of the conductor have been studied in this work to capture a wide range of scenarios. The effect of neutral grounding of the source side transformer is also accounted in this study. The results show that the algorithm detects the HIFs accurately and rapidly. Thus, the faulty section can be isolated and service can be restored to the rest of the consumers.

Inelastic response evaluation of steel frame structure subjected to near-fault ground motions

Energy Technology Data Exchange (ETDEWEB)

Choi, In Kil; Kim, Hyung Kyu; Choun, Young Sun; Seo, Jeong Moon

2004-04-01

A survey on some of the Quaternary fault segments near the Korean nuclear power plants is ongoing. It is likely that these faults would be identified as active ones. If the faults are confirmed as active ones, it will be necessary to reevaluate the seismic safety of nuclear power plants located near the fault. This study was performed to acquire overall knowledge of near-fault ground motions and evaluate inealstic response characteristics of near-fault ground motions. Although Korean peninsular is not located in the strong earthquake region, it is necessary to evaluate seismic safety of NPP for the earthquakes occurred in near-fault area with characteristics different from that of general far-fault earthquakes in order to improve seismic safety of existing NPP structures and equipment. As a result, for the seismic safety evaluation of NPP structures and equipment considering near-fault effects, this report will give many valuable information. In order to improve seismic safety of NPP structures and equipment against near-fault ground motions, it is necessary to consider inelastic response characteristics of near-fault ground motions in current design code. Also in Korea where these studies are immature yet, in the future more works of near-fault earthquakes must be accomplished.

Wind turbine fault detection and fault tolerant control

DEFF Research Database (Denmark)

Odgaard, Peter Fogh; Johnson, Kathryn

2013-01-01

In this updated edition of a previous wind turbine fault detection and fault tolerant control challenge, we present a more sophisticated wind turbine model and updated fault scenarios to enhance the realism of the challenge and therefore the value of the solutions. This paper describes...

Fault geometry, rupture dynamics and ground motion from potential earthquakes on the North Anatolian Fault under the Sea of Marmara

KAUST Repository

Oglesby, David D.

2012-03-01

Using the 3-D finite-element method, we develop dynamic spontaneous rupture models of earthquakes on the North Anatolian Fault system in the Sea of Marmara, Turkey, considering the geometrical complexity of the fault system in this region. We find that the earthquake size, rupture propagation pattern and ground motion all strongly depend on the interplay between the initial (static) regional pre-stress field and the dynamic stress field radiated by the propagating rupture. By testing several nucleation locations, we observe that those far from an oblique normal fault stepover segment (near Istanbul) lead to large through-going rupture on the entire fault system, whereas nucleation locations closer to the stepover segment tend to produce ruptures that die out in the stepover. However, this pattern can change drastically with only a 10° rotation of the regional stress field. Our simulations also reveal that while dynamic unclamping near fault bends can produce a new mode of supershear rupture propagation, this unclamping has a much smaller effect on the speed of the peak in slip velocity along the fault. Finally, we find that the complex fault geometry leads to a very complex and asymmetric pattern of near-fault ground motion, including greatly amplified ground motion on the insides of fault bends. The ground-motion pattern can change significantly with different hypocentres, even beyond the typical effects of directivity. The results of this study may have implications for seismic hazard in this region, for the dynamics and ground motion of geometrically complex faults, and for the interpretation of kinematic inverse rupture models.

Fault geometry, rupture dynamics and ground motion from potential earthquakes on the North Anatolian Fault under the Sea of Marmara

KAUST Repository

Oglesby, David D.; Mai, Paul Martin

2012-01-01

Using the 3-D finite-element method, we develop dynamic spontaneous rupture models of earthquakes on the North Anatolian Fault system in the Sea of Marmara, Turkey, considering the geometrical complexity of the fault system in this region. We find that the earthquake size, rupture propagation pattern and ground motion all strongly depend on the interplay between the initial (static) regional pre-stress field and the dynamic stress field radiated by the propagating rupture. By testing several nucleation locations, we observe that those far from an oblique normal fault stepover segment (near Istanbul) lead to large through-going rupture on the entire fault system, whereas nucleation locations closer to the stepover segment tend to produce ruptures that die out in the stepover. However, this pattern can change drastically with only a 10° rotation of the regional stress field. Our simulations also reveal that while dynamic unclamping near fault bends can produce a new mode of supershear rupture propagation, this unclamping has a much smaller effect on the speed of the peak in slip velocity along the fault. Finally, we find that the complex fault geometry leads to a very complex and asymmetric pattern of near-fault ground motion, including greatly amplified ground motion on the insides of fault bends. The ground-motion pattern can change significantly with different hypocentres, even beyond the typical effects of directivity. The results of this study may have implications for seismic hazard in this region, for the dynamics and ground motion of geometrically complex faults, and for the interpretation of kinematic inverse rupture models.

Statistical Feature Extraction for Fault Locations in Nonintrusive Fault Detection of Low Voltage Distribution Systems

Directory of Open Access Journals (Sweden)

Hsueh-Hsien Chang

2017-04-01

Full Text Available This paper proposes statistical feature extraction methods combined with artificial intelligence (AI approaches for fault locations in non-intrusive single-line-to-ground fault (SLGF detection of low voltage distribution systems. The input features of the AI algorithms are extracted using statistical moment transformation for reducing the dimensions of the power signature inputs measured by using non-intrusive fault monitoring (NIFM techniques. The data required to develop the network are generated by simulating SLGF using the Electromagnetic Transient Program (EMTP in a test system. To enhance the identification accuracy, these features after normalization are given to AI algorithms for presenting and evaluating in this paper. Different AI techniques are then utilized to compare which identification algorithms are suitable to diagnose the SLGF for various power signatures in a NIFM system. The simulation results show that the proposed method is effective and can identify the fault locations by using non-intrusive monitoring techniques for low voltage distribution systems.

Final Technical Report: PV Fault Detection Tool.

Energy Technology Data Exchange (ETDEWEB)

King, Bruce Hardison [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Jones, Christian Birk [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-12-01

The PV Fault Detection Tool project plans to demonstrate that the FDT can (a) detect catastrophic and degradation faults and (b) identify the type of fault. This will be accomplished by collecting fault signatures using different instruments and integrating this information to establish a logical controller for detecting, diagnosing and classifying each fault.

Arc fault detection system

Science.gov (United States)

Jha, Kamal N.

1999-01-01

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

Arc fault detection system

Science.gov (United States)

Jha, K.N.

1999-05-18

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

A Game Theoretic Fault Detection Filter

Science.gov (United States)

Chung, Walter H.; Speyer, Jason L.

1995-01-01

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

A Novel Method for Detection and Classification of Covered Conductor Faults

Directory of Open Access Journals (Sweden)

Stanislav Misak

2016-01-01

Full Text Available Medium-Voltage (MV overhead lines with Covered Conductors (CCs are increasingly being used around the world primarily in forested or dissected terrain areas or in urban areas where it is not possible to utilize MV cable lines. The CC is specific in high operational reliability provided by the conductor core insulation compared to Aluminium-Conductor Steel-Reinforced (ACSR overhead lines. The only disadvantage of the CC is rather the problematic detection of faults compared to the ACSR. In this work, we consider the following faults: the contact of a tree branch with a CC and the fall of a conductor on the ground. The standard protection relays are unable to detect the faults and so the faults pose a risk for individuals in the vicinity of the conductor as well as it compromises the overall safety and reliability of the MV distribution system. In this article, we continue with our previous work aimed at the method enabling detection of the faults and we introduce a method enabling a classification of the fault type. Such a classification is especially important for an operator of an MV distribution system to plan the optimal maintenance or repair the faulty conductors since the fall of a tree branch can be solved later whereas the breakdown of a conductor means an immediate action of the operator.

Exact, almost and delayed fault detection

DEFF Research Database (Denmark)

Niemann, Hans Henrik; Saberi, Ali; Stoorvogel, Anton A.

1999-01-01

Considers the problem of fault detection and isolation while using zero or almost zero threshold. A number of different fault detection and isolation problems using exact or almost exact disturbance decoupling are formulated. Solvability conditions are given for the formulated design problems....... The l-step delayed fault detection problem is also considered for discrete-time systems....

Ground-fault protection of insulated high-voltage power networks in mines

Energy Technology Data Exchange (ETDEWEB)

Pudelko, H

1976-09-01

Safety of power networks is discussed in underground black coal mines in Poland. Safety in mines with a long service life was compared with safety in mines constructed since 1950. Power networks and systems protecting against electric ground-faults in the 2 mine groups are comparatively evaluated. Systems for protection against electric ground-faults in mine high-voltage networks with an insulated star point of the transformer are characterized. Fluctuations of resistance of electrical insulation under conditions of changing load are analyzed. The results of analyses are given in 14 diagrams. Recommendations for design of systems protecting against electric ground-faults in 6 kV mine power systems are made. 7 references.

77 FR 26579 - Certain Ground Fault Circuit Interrupters and Products Containing Same; Notice of Final...

Science.gov (United States)

2012-05-04

... INTERNATIONAL TRADE COMMISSION [Investigation No. 337-TA-739] Certain Ground Fault Circuit... importation of certain ground fault circuit interrupters and products containing the same by reason of... entry of ground fault circuit interrupters and products containing the same that infringe one or more of...

Active fault detection in MIMO systems

DEFF Research Database (Denmark)

Niemann, Hans Henrik; Poulsen, Niels Kjølstad

2014-01-01

The focus in this paper is on active fault detection (AFD) for MIMO systems with parametric faults. The problem of design of auxiliary inputs with respect to detection of parametric faults is investigated. An analysis of the design of auxiliary inputs is given based on analytic transfer functions...... from auxiliary input to residual outputs. The analysis is based on a singular value decomposition of these transfer functions Based on this analysis, it is possible to design auxiliary input as well as design of the associated residual vector with respect to every single parametric fault in the system...... such that it is possible to detect these faults....

Field Guide for Testing Existing Photovoltaic Systems for Ground Faults and Installing Equipment to Mitigate Fire Hazards

Energy Technology Data Exchange (ETDEWEB)

Brooks, William [Brooks Engineering, Vacaville, CA (United States); Basso, Thomas [National Renewable Energy Lab. (NREL), Golden, CO (United States); Coddington, Michael [National Renewable Energy Lab. (NREL), Golden, CO (United States)

2015-10-01

Ground faults and arc faults are the two most common reasons for fires in photovoltaic (PV) arrays and methods exist that can mitigate the hazards. This report provides field procedures for testing PV arrays for ground faults, and for implementing high resolution ground fault and arc fault detectors in existing and new PV system designs.

77 FR 11591 - Certain Ground Fault Circuit Interrupters and Products Containing Same, Investigations...

Science.gov (United States)

2012-02-27

... INTERNATIONAL TRADE COMMISSION [Investigation No. 337-TA-739] Certain Ground Fault Circuit Interrupters and Products Containing Same, Investigations: Terminations, Modifications and Rulings AGENCY: U.S... importation, and the sale within the United States after importation of certain ground fault circuit...

Seismic fragility analysis of a CANDU containment structure for near-fault ground motions

International Nuclear Information System (INIS)

Choi, In Kil; Choun, Young Sun; Seo, Jeong Moon; Ahn, Seong Moon

2005-01-01

The R. G. 1.60 spectrum used for the seismic design of Korean nuclear power plants provides a generally conservative design basis due to its broadband nature. A survey on some of the Quaternary fault segments near Korean nuclear power plants is ongoing. It is likely that these faults will be identified as active ones. If the faults are confirmed as active ones, it will be necessary to reevaluate the seismic safety of the nuclear power plants located near these faults. The probability based scenario earthquakes were identified as near-field earthquakes. In general, the near-fault ground motion records exhibit a distinctive long period pulse like time history with very high peak velocities. These features are induced by the slip of the earthquake fault. Near-fault ground motions, which have caused much of the damage in recent major earthquakes, can be characterized by a pulse-like motion that exposes the structure to a high input energy at the beginning of the motion. It is necessary to estimate the near-fault ground motion effects on the nuclear power plant structures and components located near the faults. In this study, the seismic fragility analysis of a CANDU containment structure was performed based on the results of nonlinear dynamic time-history analyses

Robust Mpc for Actuator–Fault Tolerance Using Set–Based Passive Fault Detection and Active Fault Isolation

Directory of Open Access Journals (Sweden)

Xu Feng

2017-03-01

Full Text Available In this paper, a fault-tolerant control (FTC scheme is proposed for actuator faults, which is built upon tube-based model predictive control (MPC as well as set-based fault detection and isolation (FDI. In the class of MPC techniques, tubebased MPC can effectively deal with system constraints and uncertainties with relatively low computational complexity compared with other robust MPC techniques such as min-max MPC. Set-based FDI, generally considering the worst case of uncertainties, can robustly detect and isolate actuator faults. In the proposed FTC scheme, fault detection (FD is passive by using invariant sets, while fault isolation (FI is active by means of MPC and tubes. The active FI method proposed in this paper is implemented by making use of the constraint-handling ability of MPC to manipulate the bounds of inputs.

Ground-Motion Simulations of Scenario Earthquakes on the Hayward Fault

Energy Technology Data Exchange (ETDEWEB)

Aagaard, B; Graves, R; Larsen, S; Ma, S; Rodgers, A; Ponce, D; Schwartz, D; Simpson, R; Graymer, R

2009-03-09

We compute ground motions in the San Francisco Bay area for 35 Mw 6.7-7.2 scenario earthquake ruptures involving the Hayward fault. The modeled scenarios vary in rupture length, hypocenter, slip distribution, rupture speed, and rise time. This collaborative effort involves five modeling groups, using different wave propagation codes and domains of various sizes and resolutions, computing long-period (T > 1-2 s) or broadband (T > 0.1 s) synthetic ground motions for overlapping subsets of the suite of scenarios. The simulations incorporate 3-D geologic structure and illustrate the dramatic increase in intensity of shaking for Mw 7.05 ruptures of the entire Hayward fault compared with Mw 6.76 ruptures of the southern two-thirds of the fault. The area subjected to shaking stronger than MMI VII increases from about 10% of the San Francisco Bay urban area in the Mw 6.76 events to more than 40% of the urban area for the Mw 7.05 events. Similarly, combined rupture of the Hayward and Rodgers Creek faults in a Mw 7.2 event extends shaking stronger than MMI VII to nearly 50% of the urban area. For a given rupture length, the synthetic ground motions exhibit the greatest sensitivity to the slip distribution and location inside or near the edge of sedimentary basins. The hypocenter also exerts a strong influence on the amplitude of the shaking due to rupture directivity. The synthetic waveforms exhibit a weaker sensitivity to the rupture speed and are relatively insensitive to the rise time. The ground motions from the simulations are generally consistent with Next Generation Attenuation ground-motion prediction models but contain long-period effects, such as rupture directivity and amplification in shallow sedimentary basins that are not fully captured by the ground-motion prediction models.

Statistical fault detection in photovoltaic systems

KAUST Repository

Garoudja, Elyes

2017-05-08

Faults in photovoltaic (PV) systems, which can result in energy loss, system shutdown or even serious safety breaches, are often difficult to avoid. Fault detection in such systems is imperative to improve their reliability, productivity, safety and efficiency. Here, an innovative model-based fault-detection approach for early detection of shading of PV modules and faults on the direct current (DC) side of PV systems is proposed. This approach combines the flexibility, and simplicity of a one-diode model with the extended capacity of an exponentially weighted moving average (EWMA) control chart to detect incipient changes in a PV system. The one-diode model, which is easily calibrated due to its limited calibration parameters, is used to predict the healthy PV array\\'s maximum power coordinates of current, voltage and power using measured temperatures and irradiances. Residuals, which capture the difference between the measurements and the predictions of the one-diode model, are generated and used as fault indicators. Then, the EWMA monitoring chart is applied on the uncorrelated residuals obtained from the one-diode model to detect and identify the type of fault. Actual data from the grid-connected PV system installed at the Renewable Energy Development Center, Algeria, are used to assess the performance of the proposed approach. Results show that the proposed approach successfully monitors the DC side of PV systems and detects temporary shading.

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

Science.gov (United States)

Oostdyk, Rebecca L.; Perotti, Jose M.

2011-01-01

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

Fault Detection for Industrial Processes

Directory of Open Access Journals (Sweden)

Yingwei Zhang

2012-01-01

Full Text Available A new fault-relevant KPCA algorithm is proposed. Then the fault detection approach is proposed based on the fault-relevant KPCA algorithm. The proposed method further decomposes both the KPCA principal space and residual space into two subspaces. Compared with traditional statistical techniques, the fault subspace is separated based on the fault-relevant influence. This method can find fault-relevant principal directions and principal components of systematic subspace and residual subspace for process monitoring. The proposed monitoring approach is applied to Tennessee Eastman process and penicillin fermentation process. The simulation results show the effectiveness of the proposed method.

Fault Detection and Isolation for Spacecraft

DEFF Research Database (Denmark)

Jensen, Hans-Christian Becker; Wisniewski, Rafal

2002-01-01

This article realizes nonlinear Fault Detection and Isolation for actuators, given there is no measurement of the states in the actuators. The Fault Detection and Isolation of the actuators is instead based on angular velocity measurement of the spacecraft and knowledge about the dynamics...... of the satellite. The algorithms presented in this paper are based on a geometric approach to achieve nonlinear Fault Detection and Isolation. The proposed algorithms are tested in a simulation study and the pros and cons of the algorithms are discussed....

Effect of faulting on ground-water movement in the Death Valley region, Nevada and California

International Nuclear Information System (INIS)

Faunt, C.C.

1997-01-01

This study characterizes the hydrogeologic system of the Death Valley region, an area covering approximately 100,000 square kilometers. The study also characterizes the effects of faults on ground-water movement in the Death Valley region by synthesizing crustal stress, fracture mechanics,a nd structural geologic data. The geologic conditions are typical of the Basin and Range Province; a variety of sedimentary and igneous intrusive and extrusive rocks have been subjected to both compressional and extensional deformation. Faulting and associated fracturing is pervasive and greatly affects ground-water flow patterns. Faults may become preferred conduits or barriers to flow depending on whether they are in relative tension, compression, or shear and other factors such as the degree of dislocations of geologic units caused by faulting, the rock types involved, the fault zone materials, and the depth below the surface. The current crustal stress field was combined with fault orientations to predict potential effects of faults on the regional ground-water flow regime. Numerous examples of fault-controlled ground-water flow exist within the study area. Hydrologic data provided an independent method for checking some of the assumptions concerning preferential flow paths. 97 refs., 20 figs., 5 tabs

Fault-weighted quantification method of fault detection coverage through fault mode and effect analysis in digital I&C systems

Energy Technology Data Exchange (ETDEWEB)

Cho, Jaehyun; Lee, Seung Jun, E-mail: sjlee420@unist.ac.kr; Jung, Wondea

2017-05-15

Highlights: • We developed the fault-weighted quantification method of fault detection coverage. • The method has been applied to specific digital reactor protection system. • The unavailability of the module had 20-times difference with the traditional method. • Several experimental tests will be effectively prioritized using this method. - Abstract: The one of the most outstanding features of a digital I&C system is the use of a fault-tolerant technique. With an awareness regarding the importance of thequantification of fault detection coverage of fault-tolerant techniques, several researches related to the fault injection method were developed and employed to quantify a fault detection coverage. In the fault injection method, each injected fault has a different importance because the frequency of realization of every injected fault is different. However, there have been no previous studies addressing the importance and weighting factor of each injected fault. In this work, a new method for allocating the weighting to each injected fault using the failure mode and effect analysis data was proposed. For application, the fault-weighted quantification method has also been applied to specific digital reactor protection system to quantify the fault detection coverage. One of the major findings in an application was that we may estimate the unavailability of the specific module in digital I&C systems about 20-times smaller than real value when we use a traditional method. The other finding was that we can also classify the importance of the experimental case. Therefore, this method is expected to not only suggest an accurate quantification procedure of fault-detection coverage by weighting the injected faults, but to also contribute to an effective fault injection experiment by sorting the importance of the failure categories.

Accounting for Fault Roughness in Pseudo-Dynamic Ground-Motion Simulations

KAUST Repository

Mai, Paul Martin

2017-04-03

Geological faults comprise large-scale segmentation and small-scale roughness. These multi-scale geometrical complexities determine the dynamics of the earthquake rupture process, and therefore affect the radiated seismic wavefield. In this study, we examine how different parameterizations of fault roughness lead to variability in the rupture evolution and the resulting near-fault ground motions. Rupture incoherence naturally induced by fault roughness generates high-frequency radiation that follows an ω−2 decay in displacement amplitude spectra. Because dynamic rupture simulations are computationally expensive, we test several kinematic source approximations designed to emulate the observed dynamic behavior. When simplifying the rough-fault geometry, we find that perturbations in local moment tensor orientation are important, while perturbations in local source location are not. Thus, a planar fault can be assumed if the local strike, dip, and rake are maintained. We observe that dynamic rake angle variations are anti-correlated with the local dip angles. Testing two parameterizations of dynamically consistent Yoffe-type source-time function, we show that the seismic wavefield of the approximated kinematic ruptures well reproduces the radiated seismic waves of the complete dynamic source process. This finding opens a new avenue for an improved pseudo-dynamic source characterization that captures the effects of fault roughness on earthquake rupture evolution. By including also the correlations between kinematic source parameters, we outline a new pseudo-dynamic rupture modeling approach for broadband ground-motion simulation.

Accounting for Fault Roughness in Pseudo-Dynamic Ground-Motion Simulations

Science.gov (United States)

Mai, P. Martin; Galis, Martin; Thingbaijam, Kiran K. S.; Vyas, Jagdish C.; Dunham, Eric M.

2017-09-01

Geological faults comprise large-scale segmentation and small-scale roughness. These multi-scale geometrical complexities determine the dynamics of the earthquake rupture process, and therefore affect the radiated seismic wavefield. In this study, we examine how different parameterizations of fault roughness lead to variability in the rupture evolution and the resulting near-fault ground motions. Rupture incoherence naturally induced by fault roughness generates high-frequency radiation that follows an ω-2 decay in displacement amplitude spectra. Because dynamic rupture simulations are computationally expensive, we test several kinematic source approximations designed to emulate the observed dynamic behavior. When simplifying the rough-fault geometry, we find that perturbations in local moment tensor orientation are important, while perturbations in local source location are not. Thus, a planar fault can be assumed if the local strike, dip, and rake are maintained. We observe that dynamic rake angle variations are anti-correlated with the local dip angles. Testing two parameterizations of dynamically consistent Yoffe-type source-time function, we show that the seismic wavefield of the approximated kinematic ruptures well reproduces the radiated seismic waves of the complete dynamic source process. This finding opens a new avenue for an improved pseudo-dynamic source characterization that captures the effects of fault roughness on earthquake rupture evolution. By including also the correlations between kinematic source parameters, we outline a new pseudo-dynamic rupture modeling approach for broadband ground-motion simulation.

Accounting for Fault Roughness in Pseudo-Dynamic Ground-Motion Simulations

KAUST Repository

Mai, Paul Martin; Galis, Martin; Thingbaijam, Kiran Kumar; Vyas, Jagdish Chandra; Dunham, Eric M.

2017-01-01

Geological faults comprise large-scale segmentation and small-scale roughness. These multi-scale geometrical complexities determine the dynamics of the earthquake rupture process, and therefore affect the radiated seismic wavefield. In this study, we examine how different parameterizations of fault roughness lead to variability in the rupture evolution and the resulting near-fault ground motions. Rupture incoherence naturally induced by fault roughness generates high-frequency radiation that follows an ω−2 decay in displacement amplitude spectra. Because dynamic rupture simulations are computationally expensive, we test several kinematic source approximations designed to emulate the observed dynamic behavior. When simplifying the rough-fault geometry, we find that perturbations in local moment tensor orientation are important, while perturbations in local source location are not. Thus, a planar fault can be assumed if the local strike, dip, and rake are maintained. We observe that dynamic rake angle variations are anti-correlated with the local dip angles. Testing two parameterizations of dynamically consistent Yoffe-type source-time function, we show that the seismic wavefield of the approximated kinematic ruptures well reproduces the radiated seismic waves of the complete dynamic source process. This finding opens a new avenue for an improved pseudo-dynamic source characterization that captures the effects of fault roughness on earthquake rupture evolution. By including also the correlations between kinematic source parameters, we outline a new pseudo-dynamic rupture modeling approach for broadband ground-motion simulation.

Stochastic Modeling and Simulation of Near-Fault Ground Motions for Performance-Based Earthquake Engineering

OpenAIRE

Dabaghi, Mayssa

2014-01-01

A comprehensive parameterized stochastic model of near-fault ground motions in two orthogonal horizontal directions is developed. The proposed model uniquely combines several existing and new sub-models to represent major characteristics of recorded near-fault ground motions. These characteristics include near-fault effects of directivity and fling step; temporal and spectral non-stationarity; intensity, duration and frequency content characteristics; directionality of components, as well as ...

Statistical fault detection in photovoltaic systems

KAUST Repository

Garoudja, Elyes; Harrou, Fouzi; Sun, Ying; Kara, Kamel; Chouder, Aissa; Silvestre, Santiago

2017-01-01

and efficiency. Here, an innovative model-based fault-detection approach for early detection of shading of PV modules and faults on the direct current (DC) side of PV systems is proposed. This approach combines the flexibility, and simplicity of a one-diode model

Fault Detection for Automotive Shock Absorber

Science.gov (United States)

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

2015-11-01

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

Planetary Gearbox Fault Detection Using Vibration Separation Techniques

Science.gov (United States)

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

2011-01-01

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

FUZZY FAULT DETECTION FOR PERMANENT MAGNET SYNCHRONOUS GENERATOR

Directory of Open Access Journals (Sweden)

N. Selvaganesan

2011-07-01

Full Text Available Faults in engineering systems are difficult to avoid and may result in serious consequences. Effective fault detection and diagnosis can improve system reliability and avoid expensive maintenance. In this paper fuzzy system based fault detection scheme for permanent magnet synchronous generator is proposed. The sequence current components like positive and negative sequence currents are used as fault indicators and given as inputs to fuzzy fault detector. Also, the fuzzy inference system is created and rule base is evaluated, relating the sequence current component to the type of faults. These rules are fired for specific changes in sequence current component and the faults are detected. The feasibility of the proposed scheme for permanent magnet synchronous generator is demonstrated for different types of fault under various operating conditions using MATLAB/Simulink.

Detecting Fan Faults in refrigerated Cabinets

DEFF Research Database (Denmark)

Thybo, C.; Rasmussen, B.D.; Izadi-Zamanabadi, Roozbeh

2002-01-01

Fault detection in supermarket refrigeration systems is an important topic due to both economic and food safety reasons. If faults can be detected and diagnosed before the system drifts outside the specified operational envelope, service costs can be reduced and in extreme cases the costly discar...

Static Decoupling in fault detection

DEFF Research Database (Denmark)

Niemann, Hans Henrik

1998-01-01

An algebraic approach is given for a design of a static residual weighting factor in connection with fault detection. A complete parameterization is given of the weighting factor which will minimize a given performance index......An algebraic approach is given for a design of a static residual weighting factor in connection with fault detection. A complete parameterization is given of the weighting factor which will minimize a given performance index...

Risk-based fault detection using Self-Organizing Map

International Nuclear Information System (INIS)

Yu, Hongyang; Khan, Faisal; Garaniya, Vikram

2015-01-01

The complexity of modern systems is increasing rapidly and the dominating relationships among system variables have become highly non-linear. This results in difficulty in the identification of a system's operating states. In turn, this difficulty affects the sensitivity of fault detection and imposes a challenge on ensuring the safety of operation. In recent years, Self-Organizing Maps has gained popularity in system monitoring as a robust non-linear dimensionality reduction tool. Self-Organizing Map is able to capture non-linear variations of the system. Therefore, it is sensitive to the change of a system's states leading to early detection of fault. In this paper, a new approach based on Self-Organizing Map is proposed to detect and assess the risk of fault. In addition, probabilistic analysis is applied to characterize the risk of fault into different levels according to the hazard potential to enable a refined monitoring of the system. The proposed approach is applied on two experimental systems. The results from both systems have shown high sensitivity of the proposed approach in detecting and identifying the root cause of faults. The refined monitoring facilitates the determination of the risk of fault and early deployment of remedial actions and safety measures to minimize the potential impact of fault. - Highlights: • A new approach based on Self-Organizing Map is proposed to detect faults. • Integration of fault detection with risk assessment methodology. • Fault risk characterization into different levels to enable focused system monitoring

A source of ground water 222Rn around Tachikawa fault

International Nuclear Information System (INIS)

Saito, Masaaki; Takata, Sigeru

1994-01-01

Radon ( 222 Rn) concentration in ground water was characteristically high on the south-western zone divided by the Tachikawa fault, Tokyo. (1) The concentration did not increase with depth, and alluvium is thick on the zone. The source of radon was not considered as the updraft from base rock through the fault. Comparing the south-western zone with its surrounding zone, the followings were found. (2) The distribution of tritium concentration was supported that water had easily permeated into ground on the zone. (3) As the zone is located beside the Tama River and its alluvial fan center, the river water had likely affected. The source of radon on the zone would be 226 Ra in the aquifer soil. It can be presumed that the water of the Tama River had permeated into ground on the zone and had accumulated 226 Ra. (author)

Fault detection for discrete-time switched systems with sensor stuck faults and servo inputs.

Science.gov (United States)

Zhong, Guang-Xin; Yang, Guang-Hong

2015-09-01

This paper addresses the fault detection problem of switched systems with servo inputs and sensor stuck faults. The attention is focused on designing a switching law and its associated fault detection filters (FDFs). The proposed switching law uses only the current states of FDFs, which guarantees the residuals are sensitive to the servo inputs with known frequency ranges in faulty cases and robust against them in fault-free case. Thus, the arbitrarily small sensor stuck faults, including outage faults can be detected in finite-frequency domain. The levels of sensitivity and robustness are measured in terms of the finite-frequency H- index and l2-gain. Finally, the switching law and FDFs are obtained by the solution of a convex optimization problem. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

A fault detection and diagnosis in a PWR steam generator

International Nuclear Information System (INIS)

Park, Seung Yub

1991-01-01

The purpose of this study is to develop a fault detection and diagnosis scheme that can monitor process fault and instrument fault of a steam generator. The suggested scheme consists of a Kalman filter and two bias estimators. Method of detecting process and instrument fault in a steam generator uses the mean test on the residual sequence of Kalman filter, designed for the unfailed system, to make a fault decision. Once a fault is detected, two bias estimators are driven to estimate the fault and to discriminate process fault and instrument fault. In case of process fault, the fault diagnosis of outlet temperature, feed-water heater and main steam control valve is considered. In instrument fault, the fault diagnosis of steam generator's three instruments is considered. Computer simulation tests show that on-line prompt fault detection and diagnosis can be performed very successfully.(Author)

Fault Structural Control on Earthquake Strong Ground Motions: The 2008 Wenchuan Earthquake as an Example

Science.gov (United States)

Zhang, Yan; Zhang, Dongli; Li, Xiaojun; Huang, Bei; Zheng, Wenjun; Wang, Yuejun

2018-02-01

Continental thrust faulting earthquakes pose severe threats to megacities across the world. Recent events show the possible control of fault structures on strong ground motions. The seismogenic structure of the 2008 Wenchuan earthquake is associated with high-angle listric reverse fault zones. Its peak ground accelerations (PGAs) show a prominent feature of fault zone amplification: the values within the 30- to 40-km-wide fault zone block are significantly larger than those on both the hanging wall and the footwall. The PGA values attenuate asymmetrically: they decay much more rapidly in the footwall than in the hanging wall. The hanging wall effects can be seen on both the vertical and horizontal components of the PGAs, with the former significantly more prominent than the latter. All these characteristics can be adequately interpreted by upward extrusion of the high-angle listric reverse fault zone block. Through comparison with a low-angle planar thrust fault associated with the 1999 Chi-Chi earthquake, we conclude that different fault structures might have controlled different patterns of strong ground motion, which should be taken into account in seismic design and construction.

Fault Detection for a Diesel Engine Actuator

DEFF Research Database (Denmark)

Blanke, M.; Bøgh, S.A.; Jørgensen, R.B.

1995-01-01

An electro-mechanical position servo is introduced as a benchmark for mode-based Fault Detection and Identification (FDI).......An electro-mechanical position servo is introduced as a benchmark for mode-based Fault Detection and Identification (FDI)....

Radial basis function neural network in fault detection of automotive ...

African Journals Online (AJOL)

Radial basis function neural network in fault detection of automotive engines. ... Five faults have been simulated on the MVEM, including three sensor faults, one component fault and one actuator fault. The three sensor faults ... Keywords: Automotive engine, independent RBFNN model, RBF neural network, fault detection

Distributed Fault Detection for a Class of Nonlinear Stochastic Systems

Directory of Open Access Journals (Sweden)

Bingyong Yan

2014-01-01

Full Text Available A novel distributed fault detection strategy for a class of nonlinear stochastic systems is presented. Different from the existing design procedures for fault detection, a novel fault detection observer, which consists of a nonlinear fault detection filter and a consensus filter, is proposed to detect the nonlinear stochastic systems faults. Firstly, the outputs of the nonlinear stochastic systems act as inputs of a consensus filter. Secondly, a nonlinear fault detection filter is constructed to provide estimation of unmeasurable system states and residual signals using outputs of the consensus filter. Stability analysis of the consensus filter is rigorously investigated. Meanwhile, the design procedures of the nonlinear fault detection filter are given in terms of linear matrix inequalities (LMIs. Taking the influence of the system stochastic noises into consideration, an outstanding feature of the proposed scheme is that false alarms can be reduced dramatically. Finally, simulation results are provided to show the feasibility and effectiveness of the proposed fault detection approach.

Fault Detection for Shipboard Monitoring and Decision Support Systems

DEFF Research Database (Denmark)

Lajic, Zoran; Nielsen, Ulrik Dam

2009-01-01

In this paper a basic idea of a fault-tolerant monitoring and decision support system will be explained. Fault detection is an important part of the fault-tolerant design for in-service monitoring and decision support systems for ships. In the paper, a virtual example of fault detection...... will be presented for a containership with a real decision support system onboard. All possible faults can be simulated and detected using residuals and the generalized likelihood ratio (GLR) algorithm....

Data Fault Detection in Medical Sensor Networks

Directory of Open Access Journals (Sweden)

Yang Yang

2015-03-01

Full Text Available Medical body sensors can be implanted or attached to the human body to monitor the physiological parameters of patients all the time. Inaccurate data due to sensor faults or incorrect placement on the body will seriously influence clinicians’ diagnosis, therefore detecting sensor data faults has been widely researched in recent years. Most of the typical approaches to sensor fault detection in the medical area ignore the fact that the physiological indexes of patients aren’t changing synchronously at the same time, and fault values mixed with abnormal physiological data due to illness make it difficult to determine true faults. Based on these facts, we propose a Data Fault Detection mechanism in Medical sensor networks (DFD-M. Its mechanism includes: (1 use of a dynamic-local outlier factor (D-LOF algorithm to identify outlying sensed data vectors; (2 use of a linear regression model based on trapezoidal fuzzy numbers to predict which readings in the outlying data vector are suspected to be faulty; (3 the proposal of a novel judgment criterion of fault state according to the prediction values. The simulation results demonstrate the efficiency and superiority of DFD-M.

An effort allocation model considering different budgetary constraint on fault detection process and fault correction process

Directory of Open Access Journals (Sweden)

Vijay Kumar

2016-01-01

Full Text Available Fault detection process (FDP and Fault correction process (FCP are important phases of software development life cycle (SDLC. It is essential for software to undergo a testing phase, during which faults are detected and corrected. The main goal of this article is to allocate the testing resources in an optimal manner to minimize the cost during testing phase using FDP and FCP under dynamic environment. In this paper, we first assume there is a time lag between fault detection and fault correction. Thus, removal of a fault is performed after a fault is detected. In addition, detection process and correction process are taken to be independent simultaneous activities with different budgetary constraints. A structured optimal policy based on optimal control theory is proposed for software managers to optimize the allocation of the limited resources with the reliability criteria. Furthermore, release policy for the proposed model is also discussed. Numerical example is given in support of the theoretical results.

75 FR 62420 - In the Matter of: Certain Ground Fault Circuit Interrupters and Products Containing Same; Notice...

Science.gov (United States)

2010-10-08

... INTERNATIONAL TRADE COMMISSION [Inv. No. 337-TA-739] In the Matter of: Certain Ground Fault... fault circuit interrupters and products containing same by reason of infringement of certain claims of U... certain ground fault circuit interrupters and products containing same that infringe one or more of claims...

An Improved Wavelet‐Based Multivariable Fault Detection Scheme

KAUST Repository

Harrou, Fouzi

2017-07-06

Data observed from environmental and engineering processes are usually noisy and correlated in time, which makes the fault detection more difficult as the presence of noise degrades fault detection quality. Multiscale representation of data using wavelets is a powerful feature extraction tool that is well suited to denoising and decorrelating time series data. In this chapter, we combine the advantages of multiscale partial least squares (MSPLSs) modeling with those of the univariate EWMA (exponentially weighted moving average) monitoring chart, which results in an improved fault detection system, especially for detecting small faults in highly correlated, multivariate data. Toward this end, we applied EWMA chart to the output residuals obtained from MSPLS model. It is shown through simulated distillation column data the significant improvement in fault detection can be obtained by using the proposed methods as compared to the use of the conventional partial least square (PLS)‐based Q and EWMA methods and MSPLS‐based Q method.

Nonlinear Model-Based Fault Detection for a Hydraulic Actuator

NARCIS (Netherlands)

Van Eykeren, L.; Chu, Q.P.

2011-01-01

This paper presents a model-based fault detection algorithm for a specific fault scenario of the ADDSAFE project. The fault considered is the disconnection of a control surface from its hydraulic actuator. Detecting this type of fault as fast as possible helps to operate an aircraft more cost

Research on Integrated Geophysics Detect Potential Ground Fissure in City

Science.gov (United States)

Qian, R.

2017-12-01

North China confined aquifer lied 70 to 200 meters below the earth's surface has been exploited for several decades, which resulted in confined water table declining and has generated a mass of ground fissure. Some of them has reached the surface and the other is developing. As it is very difficult to stop the ground fissure coming into being, measures of avoiding are often taken. It brings great potential risk to urban architecture and municipal engineering. It is very important to find out specific distribution and characteristic of potential ground fissure in city with high resolution. The ground fissure is concealed, therefor, geophysical method is an important technology to detecting concealed ground fissure. However, it is very difficult to detect the characteristics of the superficial part of ground fissure directly, as it lies dozens of meters below and has only scores of centimeters fault displacement. This paper studies applied ground penetration radar, surface wave and shallow refleciton seismic to detect ground fissure. It sets up model of surface by taking advantage of high resolution of ground penetrating radar data, constrains Reilay wave inversion and improves its resolution. The high resolution reflection seismic is good at detecting the geology structure. The data processing and interpretation technique is developmented to avoid the pitfall and improve the aliability of the rusult. The experiment has been conducted in Shunyi District, Beijing in 2016. 5 lines were settled to collect data of integrated geophysical method. Development zone of concealed ground fissure was found and its ultra shallow layer location was detected by ground penetrating radar. A trial trench of 6 meters in depth was dug and obvious ground fissure development was found. Its upper end was 1.5 meters beneath the earth's surface with displacement of 0.3 meters. The favorable effect of this detection has provided a new way for detecting ground fissure in cities of China, such

A new fault detection method for computer networks

International Nuclear Information System (INIS)

Lu, Lu; Xu, Zhengguo; Wang, Wenhai; Sun, Youxian

2013-01-01

Over the past few years, fault detection for computer networks has attracted extensive attentions for its importance in network management. Most existing fault detection methods are based on active probing techniques which can detect the occurrence of faults fast and precisely. But these methods suffer from the limitation of traffic overhead, especially in large scale networks. To relieve traffic overhead induced by active probing based methods, a new fault detection method, whose key is to divide the detection process into multiple stages, is proposed in this paper. During each stage, only a small region of the network is detected by using a small set of probes. Meanwhile, it also ensures that the entire network can be covered after multiple detection stages. This method can guarantee that the traffic used by probes during each detection stage is small sufficiently so that the network can operate without severe disturbance from probes. Several simulation results verify the effectiveness of the proposed method

Optimal Robust Fault Detection for Linear Discrete Time Systems

Directory of Open Access Journals (Sweden)

Nike Liu

2008-01-01

Full Text Available 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−/ℋ∞, ℋ2/ℋ∞, and ℋ∞/ℋ∞ problems, are the same and can be obtained by solving a standard algebraic Riccati equation. Optimal filters are also derived for many other optimization criteria and it is shown that some well-studied and seeming-sensible optimization criteria for fault-detection filter design could lead to (optimal but useless fault-detection filters.

Event-Triggered Fault Detection of Nonlinear Networked Systems.

Science.gov (United States)

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

2017-04-01

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

Rapid detection of small oscillation faults via deterministic learning.

Science.gov (United States)

Wang, Cong; Chen, Tianrui

2011-08-01

Detection of small faults is one of the most important and challenging tasks in the area of fault diagnosis. In this paper, we present an approach for the rapid detection of small oscillation faults based on a recently proposed deterministic learning (DL) theory. The approach consists of two phases: the training phase and the test phase. In the training phase, the system dynamics underlying normal and fault oscillations are locally accurately approximated through DL. The obtained knowledge of system dynamics is stored in constant radial basis function (RBF) networks. In the diagnosis phase, rapid detection is implemented. Specially, a bank of estimators are constructed using the constant RBF neural networks to represent the training normal and fault modes. By comparing the set of estimators with the test monitored system, a set of residuals are generated, and the average L(1) norms of the residuals are taken as the measure of the differences between the dynamics of the monitored system and the dynamics of the training normal mode and oscillation faults. The occurrence of a test oscillation fault can be rapidly detected according to the smallest residual principle. A rigorous analysis of the performance of the detection scheme is also given. The novelty of the paper lies in that the modeling uncertainty and nonlinear fault functions are accurately approximated and then the knowledge is utilized to achieve rapid detection of small oscillation faults. Simulation studies are included to demonstrate the effectiveness of the approach.

Exact, almost and delayed fault detection: An observer based approach

DEFF Research Database (Denmark)

Niemann, Hans Henrik; Saberi, Ali; Stoorvogel, Anton A.

1999-01-01

This paper consider the problem of fault detection and isolation in continuous- and discrete-time systems while using zero or almost zero threshold. A number of different fault detections and isolation problems using exact or almost exact disturbance decoupling are formulated. Solvability...... conditions are given for the formulated design problems together with methods for appropriate design of observer based fault detectors. The l-step delayed fault detection problem is also considered for discrete-time systems . Moreover, certain indirect fault detection methods such as unknown input observers...

Fault-tolerant control for current sensors of doubly fed induction generators based on an improved fault detection method

DEFF Research Database (Denmark)

Li, Hui; Yang, Chao; Hu, Yaogang

2014-01-01

Fault-tolerant control of current sensors is studied in this paper to improve the reliability of a doubly fed induction generator (DFIG). A fault-tolerant control system of current sensors is presented for the DFIG, which consists of a new current observer and an improved current sensor fault...... detection algorithm, and fault-tolerant control system are investigated by simulation. The results indicate that the outputs of the observer and the sensor are highly coherent. The fault detection algorithm can efficiently detect both soft and hard faults in current sensors, and the fault-tolerant control...

Evaluation of fault-normal/fault-parallel directions rotated ground motions for response history analysis of an instrumented six-story building

Science.gov (United States)

Kalkan, Erol; Kwong, Neal S.

2012-01-01

According to regulatory building codes in United States (for example, 2010 California Building Code), at least two horizontal ground-motion components are required for three-dimensional (3D) response history analysis (RHA) of buildings. For sites within 5 km of an active fault, these records should be rotated to fault-normal/fault-parallel (FN/FP) directions, and two RHA analyses should be performed separately (when FN and then FP are aligned with the transverse direction of the structural axes). It is assumed that this approach will lead to two sets of responses that envelope the range of possible responses over all nonredundant rotation angles. This assumption is examined here using a 3D computer model of a six-story reinforced-concrete instrumented building subjected to an ensemble of bidirectional near-fault ground motions. Peak responses of engineering demand parameters (EDPs) were obtained for rotation angles ranging from 0° through 180° for evaluating the FN/FP directions. It is demonstrated that rotating ground motions to FN/FP directions (1) does not always lead to the maximum responses over all angles, (2) does not always envelope the range of possible responses, and (3) does not provide maximum responses for all EDPs simultaneously even if it provides a maximum response for a specific EDP.

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

Science.gov (United States)

Li, Xiao-Jian; Yang, Guang-Hong

2014-08-01

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

An Improved Wavelet‐Based Multivariable Fault Detection Scheme

KAUST Repository

Harrou, Fouzi; Sun, Ying; Madakyaru, Muddu

2017-01-01

Data observed from environmental and engineering processes are usually noisy and correlated in time, which makes the fault detection more difficult as the presence of noise degrades fault detection quality. Multiscale representation of data using

Modelling of Surface Fault Structures Based on Ground Magnetic Survey

Science.gov (United States)

Michels, A.; McEnroe, S. A.

2017-12-01

The island of Leka confines the exposure of the Leka Ophiolite Complex (LOC) which contains mantle and crustal rocks and provides a rare opportunity to study the magnetic properties and response of these formations. The LOC is comprised of five rock units: (1) harzburgite that is strongly deformed, shifting into an increasingly olivine-rich dunite (2) ultramafic cumulates with layers of olivine, chromite, clinopyroxene and orthopyroxene. These cumulates are overlain by (3) metagabbros, which are cut by (4) metabasaltic dykes and (5) pillow lavas (Furnes et al. 1988). Over the course of three field seasons a detailed ground-magnetic survey was made over the island covering all units of the LOC and collecting samples from 109 sites for magnetic measurements. NRM, susceptibility, density and hysteresis properties were measured. In total 66% of samples with a Q value > 1, suggests that the magnetic anomalies should include both induced and remanent components in the model.This Ophiolite originated from a suprasubduction zone near the coast of Laurentia (497±2 Ma), was obducted onto Laurentia (≈460 Ma) and then transferred to Baltica during the Caledonide Orogeny (≈430 Ma). The LOC was faulted, deformed and serpentinized during these events. The gabbro and ultramafic rocks are separated by a normal fault. The dominant magnetic anomaly that crosses the island correlates with this normal fault. There are a series of smaller scale faults that are parallel to this and some correspond to local highs that can be highlighted by a tilt derivative of the magnetic data. These fault boundaries which are well delineated by the distinct magnetic anomalies in both ground and aeromagnetic survey data are likely caused by increased amount of serpentinization of the ultramafic rocks in the fault areas.

Latest Progress of Fault Detection and Localization in Complex Electrical Engineering

Science.gov (United States)

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

2014-01-01

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

Ground motion modeling of Hayward fault scenario earthquakes II:Simulation of long-period and broadband ground motions

Energy Technology Data Exchange (ETDEWEB)

Aagaard, B T; Graves, R W; Rodgers, A; Brocher, T M; Simpson, R W; Dreger, D; Petersson, N A; Larsen, S C; Ma, S; Jachens, R C

2009-11-04

We simulate long-period (T > 1.0-2.0 s) and broadband (T > 0.1 s) ground motions for 39 scenarios earthquakes (Mw 6.7-7.2) involving the Hayward, Calaveras, and Rodgers Creek faults. For rupture on the Hayward fault we consider the effects of creep on coseismic slip using two different approaches, both of which reduce the ground motions compared with neglecting the influence of creep. Nevertheless, the scenario earthquakes generate strong shaking throughout the San Francisco Bay area with about 50% of the urban area experiencing MMI VII or greater for the magnitude 7.0 scenario events. Long-period simulations of the 2007 Mw 4.18 Oakland and 2007 Mw 4.5 Alum Rock earthquakes show that the USGS Bay Area Velocity Model version 08.3.0 permits simulation of the amplitude and duration of shaking throughout the San Francisco Bay area, with the greatest accuracy in the Santa Clara Valley (San Jose area). The ground motions exhibit a strong sensitivity to the rupture length (or magnitude), hypocenter (or rupture directivity), and slip distribution. The ground motions display a much weaker sensitivity to the rise time and rupture speed. Peak velocities, peak accelerations, and spectral accelerations from the synthetic broadband ground motions are, on average, slightly higher than the Next Generation Attenuation (NGA) ground-motion prediction equations. We attribute at least some of this difference to the relatively narrow width of the Hayward fault ruptures. The simulations suggest that the Spudich and Chiou (2008) directivity corrections to the NGA relations could be improved by including a dependence on the rupture speed and increasing the areal extent of rupture directivity with period. The simulations also indicate that the NGA relations may under-predict amplification in shallow sedimentary basins.

Reset Tree-Based Optical Fault Detection

Directory of Open Access Journals (Sweden)

Howon Kim

2013-05-01

Full Text Available 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.

Linear discriminant analysis for welding fault detection

International Nuclear Information System (INIS)

Li, X.; Simpson, S.W.

2010-01-01

This work presents a new method for real time welding fault detection in industry based on Linear Discriminant Analysis (LDA). A set of parameters was calculated from one second blocks of electrical data recorded during welding and based on control data from reference welds under good conditions, as well as faulty welds. Optimised linear combinations of the parameters were determined with LDA and tested with independent data. Short arc welds in overlap joints were studied with various power sources, shielding gases, wire diameters, and process geometries. Out-of-position faults were investigated. Application of LDA fault detection to a broad range of welding procedures was investigated using a similarity measure based on Principal Component Analysis. The measure determines which reference data are most similar to a given industrial procedure and the appropriate LDA weights are then employed. Overall, results show that Linear Discriminant Analysis gives an effective and consistent performance in real-time welding fault detection.

CRISP. Fault detection, analysis and diagnostics in high-DG distribution systems

International Nuclear Information System (INIS)

Fontela, M.; Bacha, S.; Hadsjaid, N.; Andrieu, C.; Raison, B.; Penkov, D.

2004-04-01

The fault in the electrotechnical meaning is defined in the document. The main part of faults in overhead lines are non permanent faults, what entails the network operator to maintain the existing techniques to clear as fast as possible these faults. When a permanent fault occurs the operator has to detect and to limit the risks as soon as possible. Different axes are followed: limitation of the fault current, clearing the faulted feeder, locating the fault by test and try under possible fault condition. So the fault detection, fault clearing and fault localization are important functions of an EPS (electric power systems) to allow secure and safe operation of the system. The function may be improved by means of a better use of ICT components in the future sharing conveniently the intelligence needed near the distributed devices and a defined centralized intelligence. This improvement becomes necessary in distribution EPS with a high introduction of DR (distributed resources). The transmission and sub-transmission protection systems are already installed in order to manage power flow in all directions, so the DR issue is less critical for this part of the power system in term of fault clearing and diagnosis. Nevertheless the massive introduction of RES involves another constraints to the transmission system which are the bottlenecks caused by important local and fast installed production as wind power plants. Dealing with the distribution power system, and facing a permanent fault, two main actions must be achieved: identify the faulted elementary EPS area quickly and allow the field crew to locate and to repair the fault as soon as possible. The introduction of DR in distribution EPS involves some changes in fault location methods or equipment. The different existing neutral grounding systems make it difficult the achievement of a general method relevant for any distribution EPS in Europe. Some solutions are studied in the CRISP project in order to improve the

Nonlinear Actuator Fault Detection and Isolation for a VTOL aircraft

NARCIS (Netherlands)

De Persis, Claudio; De Santis, Raffaella; Isidori, Alberto

2001-01-01

The recently introduced geometric approach to the nonlinear fault detection and isolation problem is used in this paper to detect actuator faults for the vertical takeoff and landing aircraft. The approach leads to a filter which, by processing the outputs of the plant, detects the faults and

Strong ground motion prediction applying dynamic rupture simulations for Beppu-Haneyama Active Fault Zone, southwestern Japan

Science.gov (United States)

Yoshimi, M.; Matsushima, S.; Ando, R.; Miyake, H.; Imanishi, K.; Hayashida, T.; Takenaka, H.; Suzuki, H.; Matsuyama, H.

2017-12-01

We conducted strong ground motion prediction for the active Beppu-Haneyama Fault zone (BHFZ), Kyushu island, southwestern Japan. Since the BHFZ runs through Oita and Beppy cities, strong ground motion as well as fault displacement may affect much to the cities.We constructed a 3-dimensional velocity structure of a sedimentary basin, Beppu bay basin, where the fault zone runs through and Oita and Beppu cities are located. Minimum shear wave velocity of the 3d model is 500 m/s. Additional 1-d structure is modeled for sites with softer sediment: holocene plain area. We observed, collected, and compiled data obtained from microtremor surveys, ground motion observations, boreholes etc. phase velocity and H/V ratio. Finer structure of the Oita Plain is modeled, as 250m-mesh model, with empirical relation among N-value, lithology, depth and Vs, using borehole data, then validated with the phase velocity data obtained by the dense microtremor array observation (Yoshimi et al., 2016).Synthetic ground motion has been calculated with a hybrid technique composed of a stochastic Green's function method (for HF wave), a 3D finite difference (LF wave) and 1D amplification calculation. Fault geometry has been determined based on reflection surveys and active fault map. The rake angles are calculated with a dynamic rupture simulation considering three fault segments under a stress filed estimated from source mechanism of earthquakes around the faults (Ando et al., JpGU-AGU2017). Fault parameters such as the average stress drop, a size of asperity etc. are determined based on an empirical relation proposed by Irikura and Miyake (2001). As a result, strong ground motion stronger than 100 cm/s is predicted in the hanging wall side of the Oita plain.This work is supported by the Comprehensive Research on the Beppu-Haneyama Fault Zone funded by the Ministry of Education, Culture, Sports, Science, and Technology (MEXT), Japan.

Unknown input observer based detection of sensor faults in a wind turbine

DEFF Research Database (Denmark)

Odgaard, Peter Fogh; Stoustrup, Jakob

2010-01-01

In this paper an unknown input observer is designed to detect three different sensor fault scenarios in a specified bench mark model for fault detection and accommodation of wind turbines. In this paper a subset of faults is dealt with, it are faults in the rotor and generator speed sensors as well...... as a converter sensor fault. The proposed scheme detects the speed sensor faults in question within the specified requirements given in the bench mark model, while the converter fault is detected but not within the required time to detect....

Observer Based Detection of Sensor Faults in Wind Turbines

DEFF Research Database (Denmark)

Odgaard, Peter Fogh; Stoustrup, Jakob; Nielsen, R.

2009-01-01

, if an unknown input observer the fault detection  scheme can be non dependent on the actual wind speed. The scheme  is validated on data from a more advanced and detailed simulation  model. The proposed scheme detects the sensor faults a few samples  after the beginning of the faults....

Variation in radon exhalation from the ground on the active fault in Kobe

Energy Technology Data Exchange (ETDEWEB)

Yasuoka, Y.; Shinogi, M. [Kobe Pharmaceutical Univ., Kobe, Hyogo (Japan)

1998-12-31

Since 27 January 1997, the measurements of radon (Rn-222) exhaled from the ground have been made continuously by the use of PICO-RAD detector (Packard instrument Co.) at monitoring stations on Ashiya active fault. The fault may have been slipped by the Kobe earthquake (magnitude 7.2, 17 January 1995). The variation of relative radon exhalation on the fault was large. We guessed the large variation of relative radon exhalation on the fault was caused by not only the influence of meteorology but also the influence of other factors. (author)

76 FR 2708 - In the Matter of Certain Ground Fault Circuit Interrupters and Products Containing Same; Notice...

Science.gov (United States)

2011-01-14

... INTERNATIONAL TRADE COMMISSION [Investigation No. 337-TA-739] In the Matter of Certain Ground Fault Circuit Interrupters and Products Containing Same; Notice of Commission Determination Not To... importation, and the sale within the United States after importation of certain ground fault circuit...

75 FR 70289 - In the Matter of Certain Ground Fault Circuit Interrupters and Products Containing Same; Notice...

Science.gov (United States)

2010-11-17

... INTERNATIONAL TRADE COMMISSION [Investigation No. 337-TA-739] In the Matter of Certain Ground Fault Circuit Interrupters and Products Containing Same; Notice of Commission Determination Not To... importation, and the sale within the United States after importation of certain ground fault circuit...

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

Science.gov (United States)

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

2013-12-01

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

Fault detection and reliability, knowledge based and other approaches

International Nuclear Information System (INIS)

Singh, M.G.; Hindi, K.S.; Tzafestas, S.G.

1987-01-01

These proceedings are split up into four major parts in order to reflect the most significant aspects of reliability and fault detection as viewed at present. The first part deals with knowledge-based systems and comprises eleven contributions from leading experts in the field. The emphasis here is primarily on the use of artificial intelligence, expert systems and other knowledge-based systems for fault detection and reliability. The second part is devoted to fault detection of technological systems and comprises thirteen contributions dealing with applications of fault detection techniques to various technological systems such as gas networks, electric power systems, nuclear reactors and assembly cells. The third part of the proceedings, which consists of seven contributions, treats robust, fault tolerant and intelligent controllers and covers methodological issues as well as several applications ranging from nuclear power plants to industrial robots to steel grinding. The fourth part treats fault tolerant digital techniques and comprises five contributions. Two papers, one on reactor noise analysis, the other on reactor control system design, are indexed separately. (author)

Early fault detection and diagnosis for nuclear power plants

International Nuclear Information System (INIS)

Berg, O.; Grini, R.; Masao Yokobayashi

1988-01-01

Fault detection based on a number of reference models is demonstrated. This approach is characterized by the possibility of detecting faults before a traditional alarm system is triggered, even in dynamic situations. Further, by a proper decomposition scheme and use of available process measurements, the problem area can be confined to the faulty process parts. A diagnosis system using knowledge engineering techniques is described. Typical faults are classified and described by rules involving alarm patterns and variations of important parameters. By structuring the fault hypotheses in a hierarchy the search space is limited which is important for real time diagnosis. Introduction of certainty factors improve the flexibility and robustness of diagnosis by exploring parallel problems even when some data are missing. A new display proposal should facilitate the operator interface and the integration of fault detection and diagnosis tasks in disturbance handling. The techniques of early fault detection and diagnosis are presently being implemented and tested in the experimental control room of a full-scope PWR simulator in Halden

Fault Detection and Isolation using Eigenstructure Assignment

DEFF Research Database (Denmark)

Jørgensen, R. B.; Patton, R.; Chen, J.

1994-01-01

The purpose of this article is to investigate the robustness to model uncertainties of observer based fault detection and isolation. The approach is designed with a straight forward dynamic nad the observer.......The purpose of this article is to investigate the robustness to model uncertainties of observer based fault detection and isolation. The approach is designed with a straight forward dynamic nad the observer....

Detection and Identification of Loss of Efficiency Faults of Flight Actuators

Directory of Open Access Journals (Sweden)

Ossmann Daniel

2015-03-01

Full Text Available We propose linear parameter-varying (LPV model-based approaches to the synthesis of robust fault detection and diagnosis (FDD systems for loss of efficiency (LOE faults of flight actuators. The proposed methods are applicable to several types of parametric (or multiplicative LOE faults such as actuator disconnection, surface damage, actuator power loss or stall loads. For the detection of these parametric faults, advanced LPV-model detection techniques are proposed, which implicitly provide fault identification information. Fast detection of intermittent stall loads (seen as nuisances, rather than faults is important in enhancing the performance of various fault detection schemes dealing with large input signals. For this case, a dedicated fast identification algorithm is devised. The developed FDD systems are tested on a nonlinear actuator model which is implemented in a full nonlinear aircraft simulation model. This enables the validation of the FDD system’s detection and identification characteristics under realistic conditions.

Controller modification applied for active fault detection

DEFF Research Database (Denmark)

Niemann, Hans Henrik; Stoustrup, Jakob; Poulsen, Niels Kjølstad

2014-01-01

This paper is focusing on active fault detection (AFD) for parametric faults in closed-loop systems. This auxiliary input applied for the fault detection will also disturb the external output and consequently reduce the performance of the controller. Therefore, only small auxiliary inputs are used...... with the result that the detection and isolation time can be long. In this paper it will be shown, that this problem can be handled by using a modification of the feedback controller. By applying the YJBK-parameterization (after Youla, Jabr, Bongiorno and Kucera) for the controller, it is possible to modify...... the frequency for the auxiliary input is selected. This gives that it is possible to apply an auxiliary input with a reduced amplitude. An example is included to show the results....

Closed-form critical earthquake response of elastic-plastic structures on compliant ground under near-fault ground motions

Directory of Open Access Journals (Sweden)

Kotaro eKojima

2016-01-01

Full Text Available The double impulse is introduced as a substitute of the fling-step near-fault ground motion. A closed-form solution of the elastic-plastic response of a structure on compliant (flexible ground by the ‘critical double impulse’ is derived for the first time based on the solution for the corresponding structure with fixed base. As in the case of fixed-base model, only the free-vibration appears under such double impulse and the energy approach plays an important role in the derivation of the closed-form solution of a complicated elastic-plastic response on compliant ground. It is remarkable that no iteration is needed in the derivation of the critical elastic-plastic response. It is shown via the closed-form expression that, in the case of a smaller input level of double impulse to the structural strength, as the ground stiffness becomes larger, the maximum plastic deformation becomes larger. On the other hand, in the case of a larger input level of double impulse to the structural strength, as the ground stiffness becomes smaller, the maximum plastic deformation becomes larger. The criticality and validity of the proposed theory are investigated through the comparison with the response analysis to the corresponding one-cycle sinusoidal input as a representative of the fling-step near-fault ground motion. The applicability of the proposed theory to actual recorded pulse-type ground motions is also discussed.

Active Fault Detection Based on a Statistical Test

DEFF Research Database (Denmark)

Sekunda, André Krabdrup; Niemann, Hans Henrik; Poulsen, Niels Kjølstad

2016-01-01

In this paper active fault detection of closed loop systems using dual Youla-Jabr-Bongiorno-Kucera(YJBK) parameters is presented. Until now all detector design for active fault detection using the dual YJBK parameters has been based on CUSUM detectors. Here a method for design of a matched filter...

A Novel Arc Fault Detector for Early Detection of Electrical Fires.

Science.gov (United States)

Yang, Kai; Zhang, Rencheng; Yang, Jianhong; Liu, Canhua; Chen, Shouhong; Zhang, Fujiang

2016-04-09

Arc faults can produce very high temperatures and can easily ignite combustible materials; thus, they represent one of the most important causes of electrical fires. The application of arc fault detection, as an emerging early fire detection technology, is required by the National Electrical Code to reduce the occurrence of electrical fires. However, the concealment, randomness and diversity of arc faults make them difficult to detect. To improve the accuracy of arc fault detection, a novel arc fault detector (AFD) is developed in this study. First, an experimental arc fault platform is built to study electrical fires. A high-frequency transducer and a current transducer are used to measure typical load signals of arc faults and normal states. After the common features of these signals are studied, high-frequency energy and current variations are extracted as an input eigenvector for use by an arc fault detection algorithm. Then, the detection algorithm based on a weighted least squares support vector machine is designed and successfully applied in a microprocessor. Finally, an AFD is developed. The test results show that the AFD can detect arc faults in a timely manner and interrupt the circuit power supply before electrical fires can occur. The AFD is not influenced by cross talk or transient processes, and the detection accuracy is very high. Hence, the AFD can be installed in low-voltage circuits to monitor circuit states in real-time to facilitate the early detection of electrical fires.

A Novel Arc Fault Detector for Early Detection of Electrical Fires

Science.gov (United States)

Yang, Kai; Zhang, Rencheng; Yang, Jianhong; Liu, Canhua; Chen, Shouhong; Zhang, Fujiang

2016-01-01

Arc faults can produce very high temperatures and can easily ignite combustible materials; thus, they represent one of the most important causes of electrical fires. The application of arc fault detection, as an emerging early fire detection technology, is required by the National Electrical Code to reduce the occurrence of electrical fires. However, the concealment, randomness and diversity of arc faults make them difficult to detect. To improve the accuracy of arc fault detection, a novel arc fault detector (AFD) is developed in this study. First, an experimental arc fault platform is built to study electrical fires. A high-frequency transducer and a current transducer are used to measure typical load signals of arc faults and normal states. After the common features of these signals are studied, high-frequency energy and current variations are extracted as an input eigenvector for use by an arc fault detection algorithm. Then, the detection algorithm based on a weighted least squares support vector machine is designed and successfully applied in a microprocessor. Finally, an AFD is developed. The test results show that the AFD can detect arc faults in a timely manner and interrupt the circuit power supply before electrical fires can occur. The AFD is not influenced by cross talk or transient processes, and the detection accuracy is very high. Hence, the AFD can be installed in low-voltage circuits to monitor circuit states in real-time to facilitate the early detection of electrical fires. PMID:27070618

Observer-based Fault Detection and Isolation for Nonlinear Systems

DEFF Research Database (Denmark)

Lootsma, T.F.

With the rise in automation the increase in fault detectionand isolation & reconfiguration is inevitable. Interest in fault detection and isolation (FDI) for nonlinear systems has grown significantly in recent years. The design of FDI is motivated by the need for knowledge about occurring faults...... in fault-tolerant control systems (FTC systems). The idea of FTC systems is to detect, isolate, and handle faults in such a way that the systems can still perform in a required manner. One prefers reduced performance after occurrence of a fault to the shut down of (sub-) systems. Hence, the idea of fault......-output decoupling is described. It is a new idea based on the solution of the input-output decoupling problem. The idea is to include FDI considerations already during the control design....

Nonlinear observer based fault detection and isolation for a momentum wheel

DEFF Research Database (Denmark)

Jensen, Hans-Christian Becker; Wisniewski, Rafal

2001-01-01

This article realizes nonlinear Fault Detection and Isolation for a momentum wheel. The Fault Detection and Isolation is based on a Failure Mode and Effect Analysis, which states which faults might occur and can be detected. The algorithms presented in this paper are based on a geometric approach...... toachieve nonlinear Fault Detection and Isolation. The proposed algorithms are tested in a simulation study and the pros and cons of the algorithm are discussed....

Sensor Fault Detection and Diagnosis for autonomous vehicles

Directory of Open Access Journals (Sweden)

Realpe Miguel

2015-01-01

Full Text Available In recent years testing autonomous vehicles on public roads has become a reality. However, before having autonomous vehicles completely accepted on the roads, they have to demonstrate safe operation and reliable interaction with other traffic participants. Furthermore, in real situations and long term operation, there is always the possibility that diverse components may fail. This paper deals with possible sensor faults by defining a federated sensor data fusion architecture. The proposed architecture is designed to detect obstacles in an autonomous vehicle’s environment while detecting a faulty sensor using SVM models for fault detection and diagnosis. Experimental results using sensor information from the KITTI dataset confirm the feasibility of the proposed architecture to detect soft and hard faults from a particular sensor.

Fault detection and fault tolerant control of a smart base isolation system with magneto-rheological damper

International Nuclear Information System (INIS)

Wang, Han; Song, Gangbing

2011-01-01

Fault detection and isolation (FDI) in real-time systems can provide early warnings for faulty sensors and actuator signals to prevent events that lead to catastrophic failures. The main objective of this paper is to develop FDI and fault tolerant control techniques for base isolation systems with magneto-rheological (MR) dampers. Thus, this paper presents a fixed-order FDI filter design procedure based on linear matrix inequalities (LMI). The necessary and sufficient conditions for the existence of a solution for detecting and isolating faults using the H ∞ formulation is provided in the proposed filter design. Furthermore, an FDI-filter-based fuzzy fault tolerant controller (FFTC) for a base isolation structure model was designed to preserve the pre-specified performance of the system in the presence of various unknown faults. Simulation and experimental results demonstrated that the designed filter can successfully detect and isolate faults from displacement sensors and accelerometers while maintaining excellent performance of the base isolation technology under faulty conditions

Fault Analysis and Detection in Microgrids with High PV Penetration

Energy Technology Data Exchange (ETDEWEB)

El Khatib, Mohamed [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hernandez Alvidrez, Javier [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Ellis, Abraham [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-05-01

In this report we focus on analyzing current-controlled PV inverters behaviour under faults in order to develop fault detection schemes for microgrids with high PV penetration. Inverter model suitable for steady state fault studies is presented and the impact of PV inverters on two protection elements is analyzed. The studied protection elements are superimposed quantities based directional element and negative sequence directional element. Additionally, several non-overcurrent fault detection schemes are discussed in this report for microgrids with high PV penetration. A detailed time-domain simulation study is presented to assess the performance of the presented fault detection schemes under different microgrid modes of operation.

Analytical Model-based Fault Detection and Isolation in Control Systems

DEFF Research Database (Denmark)

Vukic, Z.; Ozbolt, H.; Blanke, M.

1998-01-01

The paper gives an introduction and an overview of the field of fault detection and isolation for control systems. The summary of analytical (quantitative model-based) methodds and their implementation are presented. The focus is given to mthe analytical model-based fault-detection and fault...

Model-based fault detection algorithm for photovoltaic system monitoring

KAUST Repository

Harrou, Fouzi

2018-02-12

Reliable detection of faults in PV systems plays an important role in improving their reliability, productivity, and safety. This paper addresses the detection of faults in the direct current (DC) side of photovoltaic (PV) systems using a statistical approach. Specifically, a simulation model that mimics the theoretical performances of the inspected PV system is designed. Residuals, which are the difference between the measured and estimated output data, are used as a fault indicator. Indeed, residuals are used as the input for the Multivariate CUmulative SUM (MCUSUM) algorithm to detect potential faults. We evaluated the proposed method by using data from an actual 20 MWp grid-connected PV system located in the province of Adrar, Algeria.

Model-based fault detection algorithm for photovoltaic system monitoring

KAUST Repository

Harrou, Fouzi; Sun, Ying; Saidi, Ahmed

2018-01-01

Reliable detection of faults in PV systems plays an important role in improving their reliability, productivity, and safety. This paper addresses the detection of faults in the direct current (DC) side of photovoltaic (PV) systems using a

Fault detection of gearbox using time-frequency method

Science.gov (United States)

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

2017-04-01

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

Near-fault earthquake ground motion prediction by a high-performance spectral element numerical code

International Nuclear Information System (INIS)

Paolucci, Roberto; Stupazzini, Marco

2008-01-01

Near-fault effects have been widely recognised to produce specific features of earthquake ground motion, that cannot be reliably predicted by 1D seismic wave propagation modelling, used as a standard in engineering applications. These features may have a relevant impact on the structural response, especially in the nonlinear range, that is hard to predict and to be put in a design format, due to the scarcity of significant earthquake records and of reliable numerical simulations. In this contribution a pilot study is presented for the evaluation of seismic ground-motions in the near-fault region, based on a high-performance numerical code for 3D seismic wave propagation analyses, including the seismic fault, the wave propagation path and the near-surface geological or topographical irregularity. For this purpose, the software package GeoELSE is adopted, based on the spectral element method. The set-up of the numerical benchmark of 3D ground motion simulation in the valley of Grenoble (French Alps) is chosen to study the effect of the complex interaction between basin geometry and radiation mechanism on the variability of earthquake ground motion

Integration of control and fault detection

DEFF Research Database (Denmark)

Niemann, Hans Henrik; Stoustrup, J.

The integrated design of control and fault detection is studied. The result of the analysis is that it is possible to separate the design of the controller and the filter for fault detection in the case where the nominal model can be assumed to be fairly accurate. In the uncertain case, however......, the design of the filter and the controller can not be separated when an optiomal design is desired. For systems with significant uncertainties, there turn out to be a fundamental trade-off between the performance in the control loop and the performance in the filter....

Gear-box fault detection using time-frequency based methods

DEFF Research Database (Denmark)

Odgaard, Peter Fogh; Stoustrup, Jakob

2015-01-01

Gear-box fault monitoring and detection is important for optimization of power generation and availability of wind turbines. The current industrial approach is to use condition monitoring systems, which runs in parallel with the wind turbine control system, using expensive additional sensors...... in the gear-box resonance frequency can be detected. Two different time–frequency based approaches are presented in this paper. One is a filter based approach and the other is based on a Karhunen–Loeve basis. Both of them detect the gear-box fault with an acceptable detection delay of maximum 100s, which...... is neglectable compared with the fault developing time....

FaultBuster: data driven fault detection and diagnosis for industrial systems

DEFF Research Database (Denmark)

Bergantino, Nicola; Caponetti, Fabio; Longhi, Sauro

2009-01-01

. Multivariate statistical models based on principal components are used to detect abnormal situations. Tailored to alarms, a probabilistic inference engine process the fault evidences to output the most probable diagnosis. Results from the DX 09 Diagnostic Challenge shown strong detection properties, while...

Fault Detection, Isolation, and Accommodation for LTI Systems Based on GIMC Structure

Directory of Open Access Journals (Sweden)

D. U. Campos-Delgado

2008-01-01

Full Text Available In this contribution, an active fault-tolerant scheme that achieves fault detection, isolation, and accommodation is developed for LTI systems. Faults and perturbations are considered as additive signals that modify the state or output equations. The accommodation scheme is based on the generalized internal model control architecture recently proposed for fault-tolerant control. In order to improve the performance after a fault, the compensation is considered in two steps according with a fault detection and isolation algorithm. After a fault scenario is detected, a general fault compensator is activated. Finally, once the fault is isolated, a specific compensator is introduced. In this setup, multiple faults could be treated simultaneously since their effect is additive. Design strategies for a nominal condition and under model uncertainty are presented in the paper. In addition, performance indices are also introduced to evaluate the resulting fault-tolerant scheme for detection, isolation, and accommodation. Hard thresholds are suggested for detection and isolation purposes, meanwhile, adaptive ones are considered under model uncertainty to reduce the conservativeness. A complete simulation evaluation is carried out for a DC motor setup.

Detection of Partial Demagnetization Fault in PMSMs Operating under Nonstationary Conditions

DEFF Research Database (Denmark)

Wang, Chao; Delgado Prieto, Miguel; Romeral, Luis

2016-01-01

Demagnetization fault detection of in-service Permanent Magnet Synchronous Machines (PMSMs) is a challenging task because most PMSMs operate under nonstationary circumstances in industrial applications. A novel approach based on tracking characteristic orders of stator current using Vold-Kalman F......Demagnetization fault detection of in-service Permanent Magnet Synchronous Machines (PMSMs) is a challenging task because most PMSMs operate under nonstationary circumstances in industrial applications. A novel approach based on tracking characteristic orders of stator current using Vold......-Kalman Filter is proposed to detect the partial demagnetization fault in PMSMs running at nonstationary conditions. Amplitude of envelope of the fault characteristic orders is used as fault indictor. Experimental results verify the superiority of the proposed method on partial demagnetization online fault...... detection of PMSMs under various speed and load conditions....

Fault Detection and Load Distribution for the Wind Farm Challenge

DEFF Research Database (Denmark)

Borchersen, Anders Bech; Larsen, Jesper Abildgaard; Stoustrup, Jakob

2014-01-01

In this paper a fault detection system and a fault tolerant controller for a wind farm model is designed and tested. The wind farm model is taken from the wind farm challenge which is a public available challenge where a wind farm consisting of nine turbines is proposed. The goal of the challenge...... normal and faulty conditions. Thus a fault detection system and a fault tolerant controller has been designed and combined. The fault tolerant control system has then been tested and compared to the reference system and shows improvement on all measures....

Model Based Fault Detection in a Centrifugal Pump Application

DEFF Research Database (Denmark)

Kallesøe, Carsten; Cocquempot, Vincent; Izadi-Zamanabadi, Roozbeh

2006-01-01

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...

Internal Leakage Fault Detection and Tolerant Control of Single-Rod Hydraulic Actuators

Directory of Open Access Journals (Sweden)

Jianyong Yao

2014-01-01

Full Text Available The integration of internal leakage fault detection and tolerant control for single-rod hydraulic actuators is present in this paper. Fault detection is a potential technique to provide efficient condition monitoring and/or preventive maintenance, and fault tolerant control is a critical method to improve the safety and reliability of hydraulic servo systems. Based on quadratic Lyapunov functions, a performance-oriented fault detection method is proposed, which has a simple structure and is prone to implement in practice. The main feature is that, when a prescribed performance index is satisfied (even a slight fault has occurred, there is no fault alarmed; otherwise (i.e., a severe fault has occurred, the fault is detected and then a fault tolerant controller is activated. The proposed tolerant controller, which is based on the parameter adaptive methodology, is also prone to realize, and the learning mechanism is simple since only the internal leakage is considered in parameter adaptation and thus the persistent exciting (PE condition is easily satisfied. After the activation of the fault tolerant controller, the control performance is gradually recovered. Simulation results on a hydraulic servo system with both abrupt and incipient internal leakage fault demonstrate the effectiveness of the proposed fault detection and tolerant control method.

76 FR 35014 - Certain Ground Fault Circuit Interrupters and Products Containing Same; Notice of Commission...

Science.gov (United States)

2011-06-15

... INTERNATIONAL TRADE COMMISSION [Investigation No. 337-TA-739] Certain Ground Fault Circuit Interrupters and Products Containing Same; Notice of Commission Determination Not To Review an Initial... fault circuit interrupters and products containing the same by reason of infringement of various claims...

Development of a morphological convolution operator for bearing fault detection

Science.gov (United States)

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

2018-05-01

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

Optimization of Second Fault Detection Thresholds to Maximize Mission POS

Science.gov (United States)

Anzalone, Evan

2018-01-01

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

Fault detection in multiply-redundant measurement systems via sequential testing

International Nuclear Information System (INIS)

Ray, A.

1988-01-01

The theory and application of a sequential test procedure for fault detection and isolation. The test procedure is suited for development of intelligent instrumentation in strategic processes like aircraft and nuclear plants where redundant measurements are usually available for individual critical variables. The test procedure consists of: (1) a generic redundancy management procedure which is essentially independent of the fault detection strategy and measurement noise statistics, and (2) a modified version of sequential probability ratio test algorithm for fault detection and isolation, which functions within the framework of this redundancy management procedure. The sequential test procedure is suitable for real-time applications using commercially available microcomputers and its efficacy has been verified by online fault detection in an operating nuclear reactor. 15 references

Transient pattern analysis for fault detection and diagnosis of HVAC systems

International Nuclear Information System (INIS)

Cho, Sung-Hwan; Yang, Hoon-Cheol; Zaheer-uddin, M.; Ahn, Byung-Cheon

2005-01-01

Modern building HVAC systems are complex and consist of a large number of interconnected sub-systems and components. In the event of a fault, it becomes very difficult for the operator to locate and isolate the faulty component in such large systems using conventional fault detection methods. In this study, transient pattern analysis is explored as a tool for fault detection and diagnosis of an HVAC system. Several tests involving different fault replications were conducted in an environmental chamber test facility. The results show that the evolution of fault residuals forms clear and distinct patterns that can be used to isolate faults. It was found that the time needed to reach steady state for a typical building HVAC system is at least 50-60 min. This means incorrect diagnosis of faults can happen during online monitoring if the transient pattern responses are not considered in the fault detection and diagnosis analysis

A Survey on Distributed Filtering and Fault Detection for Sensor Networks

Directory of Open Access Journals (Sweden)

Hongli Dong

2014-01-01

Full Text Available In recent years, theoretical and practical research on large-scale networked systems has gained an increasing attention from multiple disciplines including engineering, computer science, and mathematics. Lying in the core part of the area are the distributed estimation and fault detection problems that have recently been attracting growing research interests. In particular, an urgent need has arisen to understand the effects of distributed information structures on filtering and fault detection in sensor networks. In this paper, a bibliographical review is provided on distributed filtering and fault detection problems over sensor networks. The algorithms employed to study the distributed filtering and detection problems are categorised and then discussed. In addition, some recent advances on distributed detection problems for faulty sensors and fault events are also summarized in great detail. Finally, we conclude the paper by outlining future research challenges for distributed filtering and fault detection for sensor networks.

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

Science.gov (United States)

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

2014-09-01

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

Wavelet Packet based Detection of Surface Faults on Compact Discs

DEFF Research Database (Denmark)

Odgaard, Peter Fogh; Stoustrup, Jakob; Wickerhauser, Mladen Victor

2006-01-01

based on these measurements. A precise detection of the surface fault is a prerequisite to a correct handling of the faults in order to protect the pick-up of the compact disc player from audible track losses. The actual fault handling which is addressed in other publications can be carried out......In this paper the detection of faults on the surface of a compact disc is addressed. Surface faults like scratches and fingerprints disturb the on-line measurement of the pick-up position relative to the track. This is critical since the pick-up is focused on and tracked at the information track...

All-to-all sequenced fault detection system

Science.gov (United States)

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

2010-11-02

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

Soft-Fault Detection Technologies Developed for Electrical Power Systems

Science.gov (United States)

Button, Robert M.

2004-01-01

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

The Way of Reducing Current Values in Optical Ground Wires at Asymmetrical Faults on Overhead Transmission Lines

Directory of Open Access Journals (Sweden)

Egamnazarov Georgiy

2016-12-01

Full Text Available Given the fact that the installing costs of an optical ground wire on overhead lines directly depend on its cross-section, which in turn depends on the level of fault current it should withstand, in order to reduce these current values in the optical ground wire, I suggested performing its isolated descents from the end towers of the line with its transition to an optical cable. The research was carried out on the example of a 500 kV overhead line in the National Electric Power Grid. The Method of Symmetrical Components for calculating asymmetrical fault currents was not used; therefore, calculations were carried out on the base of presenting the line as a multi-wire system for the considered case as a five-wire system (optical ground wire, steel ground wire, and three phase wires. Such approach allows taking into account the initial asymmetry of the line parameters and modeling any kind of asymmetrical faults. The analyses of calculated results were performed. The conclusive evidence that the optical ground wire isolated descents from the end towers of the line give the possibility of reducing the level of maximal fault current distribution values in it and therefore its cross section, is presented.

Fundamental problems in fault detection and identification

DEFF Research Database (Denmark)

Saberi, Ali; Stoorvogel, Anton A.; Sannuti, Peddapullaiah

1999-01-01

For certain fundamental problems in fault detection and identification, the necessary and sufficient conditions for their solvability are derived. These conditions are weaker than the ones found in the literature, since we do not assume any particular structure for the residual generator......For certain fundamental problems in fault detection and identification, the necessary and sufficient conditions for their solvability are derived. These conditions are weaker than the ones found in the literature, since we do not assume any particular structure for the residual generator...

The Fault Detection, Localization, and Tolerant Operation of Modular Multilevel Converters with an Insulated Gate Bipolar Transistor (IGBT Open Circuit Fault

Directory of Open Access Journals (Sweden)

Wei Li

2018-04-01

Full Text Available Reliability is one of the critical issues for a modular multilevel converter (MMC since it consists of a large number of series-connected power electronics submodules (SMs. In this paper, a complete control strategy including fault detection, localization, and tolerant operation is proposed for the MMC under an insulated gate bipolar transistor (IGBT open circuit fault. According to the output characteristics of the SM with the open-circuit fault of IGBT, a fault detection method based on the circulating current and output current observation is used. In order to further precisely locate the position of the faulty SM, a fault localization method based on the SM capacitor voltage observation is developed. After the faulty SM is isolated, the continuous operation of the converter is ensured by adopting the fault-tolerant strategy based on the use of redundant modules. To verify the proposed fault detection, fault localization, and fault-tolerant operation strategies, a 900 kVA MMC system under the conditions of an IGBT open circuit is developed in the Matlab/Simulink platform. The capabilities of rapid detection, precise positioning, and fault-tolerant operation of the investigated detection and control algorithms are also demonstrated.

Fault detection and isolation in processes involving induction machines

Energy Technology Data Exchange (ETDEWEB)

Zell, K; Medvedev, A [Control Engineering Group, Luleaa University of Technology, Luleaa (Sweden)

1998-12-31

A model-based technique for fault detection and isolation in electro-mechanical systems comprising induction machines is introduced. Two coupled state observers, one for the induction machine and another for the mechanical load, are used to detect and recognize fault-specific behaviors (fault signatures) from the real-time measurements of the rotor angular velocity and terminal voltages and currents. Practical applicability of the method is verified in full-scale experiments with a conveyor belt drive at SSAB, Luleaa Works. (orig.) 3 refs.

Fault detection and isolation in processes involving induction machines

Energy Technology Data Exchange (ETDEWEB)

Zell, K.; Medvedev, A. [Control Engineering Group, Luleaa University of Technology, Luleaa (Sweden)

1997-12-31

A model-based technique for fault detection and isolation in electro-mechanical systems comprising induction machines is introduced. Two coupled state observers, one for the induction machine and another for the mechanical load, are used to detect and recognize fault-specific behaviors (fault signatures) from the real-time measurements of the rotor angular velocity and terminal voltages and currents. Practical applicability of the method is verified in full-scale experiments with a conveyor belt drive at SSAB, Luleaa Works. (orig.) 3 refs.

Metric Learning Method Aided Data-Driven Design of Fault Detection Systems

Directory of Open Access Journals (Sweden)

Guoyang Yan

2014-01-01

Full Text Available Fault detection is fundamental to many industrial applications. With the development of system complexity, the number of sensors is increasing, which makes traditional fault detection methods lose efficiency. Metric learning is an efficient way to build the relationship between feature vectors with the categories of instances. In this paper, we firstly propose a metric learning-based fault detection framework in fault detection. Meanwhile, a novel feature extraction method based on wavelet transform is used to obtain the feature vector from detection signals. Experiments on Tennessee Eastman (TE chemical process datasets demonstrate that the proposed method has a better performance when comparing with existing methods, for example, principal component analysis (PCA and fisher discriminate analysis (FDA.

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

Science.gov (United States)

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

2007-01-01

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

EKF-based fault detection for guided missiles flight control system

Science.gov (United States)

Feng, Gang; Yang, Zhiyong; Liu, Yongjin

2017-03-01

The guided missiles flight control system is essential for guidance accuracy and kill probability. It is complicated and fragile. Since actuator faults and sensor faults could seriously affect the security and reliability of the system, fault detection for missiles flight control system is of great significance. This paper deals with the problem of fault detection for the closed-loop nonlinear model of the guided missiles flight control system in the presence of disturbance. First, set up the fault model of flight control system, and then design the residual generation based on the extended Kalman filter (EKF) for the Eulerian-discrete fault model. After that, the Chi-square test was selected for the residual evaluation and the fault detention task for guided missiles closed-loop system was accomplished. Finally, simulation results are provided to illustrate the effectiveness of the approach proposed in the case of elevator fault separately.

Ground-Fault Characteristic Analysis of Grid-Connected Photovoltaic Stations with Neutral Grounding Resistance

Directory of Open Access Journals (Sweden)

Zheng Li

2017-11-01

Full Text Available A centralized grid-connected photovoltaic (PV station is a widely adopted method of neutral grounding using resistance, which can potentially make pre-existing protection systems invalid and threaten the safety of power grids. Therefore, studying the fault characteristics of grid-connected PV systems and their impact on power-grid protection is of great importance. Based on an analysis of the grid structure of a grid-connected PV system and of the low-voltage ride-through control characteristics of a photovoltaic power supply, this paper proposes a short-circuit calculation model and a fault-calculation method for this kind of system. With respect to the change of system parameters, particularly the resistance connected to the neutral point, and the possible impact on protective actions, this paper achieves the general rule of short-circuit current characteristics through a simulation, which provides a reference for devising protection configurations.

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

Science.gov (United States)

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

2017-09-29

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

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

Directory of Open Access Journals (Sweden)

Rui Sun

2017-09-01

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

Study of a phase-to-ground fault on a 400 kV overhead transmission line

Science.gov (United States)

Iagăr, A.; Popa, G. N.; Diniş, C. M.

2018-01-01

Power utilities need to supply their consumers at high power quality level. Because the faults that occur on High-Voltage and Extra-High-Voltage transmission lines can cause serious damages in underlying transmission and distribution systems, it is important to examine each fault in detail. In this work we studied a phase-to-ground fault (on phase 1) of 400 kV overhead transmission line Mintia-Arad. Indactic® 650 fault analyzing system was used to record the history of the fault. Signals (analog and digital) recorded by Indactic® 650 were visualized and analyzed by Focus program. Summary of fault report allowed evaluation of behavior of control and protection equipment and determination of cause and location of the fault.

Integral Sensor Fault Detection and Isolation for Railway Traction Drive.

Science.gov (United States)

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

2018-05-13

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

Fault detection by surface seismic scanning tunneling macroscope: Field test

KAUST Repository

Hanafy, Sherif M.

2014-08-05

The seismic scanning tunneling macroscope (SSTM) is proposed for detecting the presence of near-surface impedance anomalies and faults. Results with synthetic data are consistent with theory in that scatterers closer to the surface provide brighter SSTM profiles than those that are deeper. The SSTM profiles show superresolution detection if the scatterers are in the near-field region of the recording line. The field data tests near Gulf of Aqaba, Haql, KSA clearly show the presence of the observable fault scarp, and identify the subsurface presence of the hidden faults indicated in the tomograms. Superresolution detection of the fault is achieved, even when the 35 Hz data are lowpass filtered to the 5-10 Hz band.

Fault detection by surface seismic scanning tunneling macroscope: Field test

KAUST Repository

Hanafy, Sherif M.; Schuster, Gerard T.

2014-01-01

The seismic scanning tunneling macroscope (SSTM) is proposed for detecting the presence of near-surface impedance anomalies and faults. Results with synthetic data are consistent with theory in that scatterers closer to the surface provide brighter SSTM profiles than those that are deeper. The SSTM profiles show superresolution detection if the scatterers are in the near-field region of the recording line. The field data tests near Gulf of Aqaba, Haql, KSA clearly show the presence of the observable fault scarp, and identify the subsurface presence of the hidden faults indicated in the tomograms. Superresolution detection of the fault is achieved, even when the 35 Hz data are lowpass filtered to the 5-10 Hz band.

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

Directory of Open Access Journals (Sweden)

Wonhee Lee

2014-02-01

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

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

Science.gov (United States)

Lee, Wonhee; Park, Chan Gook

2014-01-01

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

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

Science.gov (United States)

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

2017-06-20

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

Fault Detection and Isolation for Wind Turbine Electric Pitch System

DEFF Research Database (Denmark)

Zhu, Jiangsheng; Ma, Kuichao; Hajizadeh, Amin

2017-01-01

This paper presents a model-based fault detection and isolation scheme applied on electric pitch system of wind turbines. Pitch system is one of the most critical components due to its effect on the operational safety and the dynamics of wind turbines. Faults in this system should be precisely...... detected to prevent failures and decrease downtime. To detect faults of electric pitch actuators and sensors, an extended kalman filter (EKF) based multiple model adaptive estimation (MMAE) designed to estimate the states of the system. The proposed method is demonstrated in case studies. The simulation...

Fault Diagnosis for Actuators in a Class of Nonlinear Systems Based on an Adaptive Fault Detection Observer

Directory of Open Access Journals (Sweden)

Runxia Guo

2016-01-01

Full Text Available The problem of actuators’ fault diagnosis is pursued for a class of nonlinear control systems that are affected by bounded measurement noise and external disturbances. A novel fault diagnosis algorithm has been proposed by combining the idea of adaptive control theory and the approach of fault detection observer. The asymptotical stability of the fault detection observer is guaranteed by setting the adaptive adjusting law of the unknown fault vector. A theoretically rigorous proof of asymptotical stability has been given. Under the condition that random measurement noise generated by the sensors of control systems and external disturbances exist simultaneously, the designed fault diagnosis algorithm is able to successfully give specific estimated values of state variables and failures rather than just giving a simple fault warning. Moreover, the proposed algorithm is very simple and concise and is easy to be applied to practical engineering. Numerical experiments are carried out to evaluate the performance of the fault diagnosis algorithm. Experimental results show that the proposed diagnostic strategy has a satisfactory estimation effect.

Robust Fault Detection for Switched Fuzzy Systems With Unknown Input.

Science.gov (United States)

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

2017-10-03

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

New algorithm to detect modules in a fault tree for a PSA

International Nuclear Information System (INIS)

Jung, Woo Sik

2015-01-01

A module or independent subtree is a part of a fault tree whose child gates or basic events are not repeated in the remaining part of the fault tree. Modules are necessarily employed in order to reduce the computational costs of fault tree quantification. This paper presents a new linear time algorithm to detect modules of large fault trees. The size of cut sets can be substantially reduced by replacing independent subtrees in a fault tree with super-components. Chatterjee and Birnbaum developed properties of modules, and demonstrated their use in the fault tree analysis. Locks expanded the concept of modules to non-coherent fault trees. Independent subtrees were manually identified while coding a fault tree for computer analysis. However, nowadays, the independent subtrees are automatically identified by the fault tree solver. A Dutuit and Rauzy (DR) algorithm to detect modules of a fault tree for coherent or non-coherent fault tree was proposed in 1996. It has been well known that this algorithm quickly detects modules since it is a linear time algorithm. The new algorithm minimizes computational memory and quickly detects modules. Furthermore, it can be easily implemented into industry fault tree solvers that are based on traditional Boolean algebra, binary decision diagrams (BDDs), or Zero-suppressed BDDs. The new algorithm employs only two scalar variables in Eqs. to that are volatile information. After finishing the traversal and module detection of each node, the volatile information is destroyed. Thus, the new algorithm does not employ any other additional computational memory and operations. It is recommended that this method be implemented into fault tree solvers for efficient probabilistic safety assessment (PSA) of nuclear power plants

New algorithm to detect modules in a fault tree for a PSA

Energy Technology Data Exchange (ETDEWEB)

Jung, Woo Sik [Sejong University, Seoul (Korea, Republic of)

2015-05-15

A module or independent subtree is a part of a fault tree whose child gates or basic events are not repeated in the remaining part of the fault tree. Modules are necessarily employed in order to reduce the computational costs of fault tree quantification. This paper presents a new linear time algorithm to detect modules of large fault trees. The size of cut sets can be substantially reduced by replacing independent subtrees in a fault tree with super-components. Chatterjee and Birnbaum developed properties of modules, and demonstrated their use in the fault tree analysis. Locks expanded the concept of modules to non-coherent fault trees. Independent subtrees were manually identified while coding a fault tree for computer analysis. However, nowadays, the independent subtrees are automatically identified by the fault tree solver. A Dutuit and Rauzy (DR) algorithm to detect modules of a fault tree for coherent or non-coherent fault tree was proposed in 1996. It has been well known that this algorithm quickly detects modules since it is a linear time algorithm. The new algorithm minimizes computational memory and quickly detects modules. Furthermore, it can be easily implemented into industry fault tree solvers that are based on traditional Boolean algebra, binary decision diagrams (BDDs), or Zero-suppressed BDDs. The new algorithm employs only two scalar variables in Eqs. to that are volatile information. After finishing the traversal and module detection of each node, the volatile information is destroyed. Thus, the new algorithm does not employ any other additional computational memory and operations. It is recommended that this method be implemented into fault tree solvers for efficient probabilistic safety assessment (PSA) of nuclear power plants.

Methods for locating ground faults and insulation degradation condition in energy conversion systems

Science.gov (United States)

Agamy, Mohamed; Elasser, Ahmed; Galbraith, Anthony William; Harfman Todorovic, Maja

2015-08-11

Methods for determining a ground fault or insulation degradation condition within energy conversion systems are described. A method for determining a ground fault within an energy conversion system may include, in part, a comparison of baseline waveform of differential current to a waveform of differential current during operation for a plurality of DC current carrying conductors in an energy conversion system. A method for determining insulation degradation within an energy conversion system may include, in part, a comparison of baseline frequency spectra of differential current to a frequency spectra of differential current transient at start-up for a plurality of DC current carrying conductors in an energy conversion system. In one embodiment, the energy conversion system may be a photovoltaic system.

Application of a Fault Detection and Isolation System on a Rotary Machine

Directory of Open Access Journals (Sweden)

Silvia M. Zanoli

2013-01-01

Full Text Available The paper illustrates the design and the implementation of a Fault Detection and Isolation (FDI system to a rotary machine like a multishaft centrifugal compressor. A model-free approach, that is, the Principal Component Analysis (PCA, has been employed to solve the fault detection issue. For the fault isolation purpose structured residuals have been adopted while an adaptive threshold has been designed in order to detect and to isolate the faults. To prove the goodness of the proposed FDI system, historical data of a nitrogen centrifugal compressor employed in a refinery plant are considered. Tests results show that detection and isolation of single as well as multiple faults are successfully achieved.

Tectonic Setting of the Gravity Fault and Implications for Ground-Water Resources in the Death Valley Region, Nevada and California

Science.gov (United States)

Blakely, R. J.; Sweetkind, D. S.; Faunt, C. C.; Jansen, J. R.; McPhee, D. K.; Morin, R. L.

2007-12-01

The Amargosa trough, extending south from Crater Flat basin to the California-Nevada state line, is believed to be a transtensional basin accommodated in part by strike-slip displacement on the northwest-striking State Line fault and normal displacement on the north-striking Gravity fault. The Gravity fault, lying along the eastern margin of the Amargosa trough, was first recognized in the 1970s on the basis of correlations between gravity anomalies and a prominent spring line in Amargosa Valley. The Gravity fault causes an inflection in water-table levels, similar to other (but not all) normal faults in the area. Pools along the spring line, some of which lie within Death Valley National Park and Ash Meadows Wildlife Refuge, include endemic species potentially threatened by increasing agricultural activities in Amargosa Valley immediately to the west, where water tables are declining. Most of the springs and pools lie east of the Gravity fault, however, and it is important to understand the role that the Gravity fault plays in controlling ground-water flow. We have conducted a variety of geophysical investigations at various scales to better understand the tectonic framework of the Amargosa Desert and support new ground-water-flow models. Much of our focus has been on the tectonic interplay of the State Line, Gravity, and other faults in the area using gravity, ground-magnetic, audiomagnetotelluric (AMT), and time-domain electromagnetic (TEM) surveys. With 1250 new gravity measurements from Ash Meadows and Stewart Valley, we have developed a revised three-dimensional crustal model of the Amargosa trough constrained by well information and geologic mapping. The model predicts approximately 2 km of vertical offset on the Gravity fault but also suggests a complex structural framework. The fault is conventionally seen as a simple, down-to-the-west normal fault juxtaposing permeable pre-Tertiary carbonate rocks to the east against less permeable Tertiary sediments to

A Novel High-Frequency Voltage Standing-Wave Ratio-Based Grounding Electrode Line Fault Supervision in Ultra-High Voltage DC Transmission Systems

Directory of Open Access Journals (Sweden)

Yufei Teng

2017-03-01

Full Text Available In order to improve the fault monitoring performance of grounding electrode lines in ultra-high voltage DC (UHVDC transmission systems, a novel fault monitoring approach based on the high-frequency voltage standing-wave ratio (VSWR is proposed in this paper. The VSWR is defined considering a lossless transmission line, and the characteristics of the VSWR under different conditions are analyzed. It is shown that the VSWR equals 1 when the terminal resistance completely matches the characteristic impedance of the line, and when a short circuit fault occurs on the grounding electrode line, the VSWR will be greater than 1. The VSWR will approach positive infinity under metallic earth fault conditions, whereas the VSWR in non-metallic earth faults will be smaller. Based on these analytical results, a fault supervision criterion is formulated. The effectiveness of the proposed VSWR-based fault supervision technique is verified with a typical UHVDC project established in Power Systems Computer Aided Design/Electromagnetic Transients including DC(PSCAD/EMTDC. Simulation results indicate that the proposed strategy can reliably identify the grounding electrode line fault and has strong anti-fault resistance capability.

Fault detection using (PI) observers

DEFF Research Database (Denmark)

Niemann, Hans Henrik; Stoustrup, J.; Shafai, B.

1997-01-01

The fault detection and isolation (FDI) problem in connection with Proportional Integral (PI) Observers is considered in this paper. A compact formulation of the FDI design problem using PI observers is given. An analysis of the FDI design problem is derived with respectt to the time domain...

Sensor fault detection and recovery in satellite attitude control

Science.gov (United States)

Nasrolahi, Seiied Saeed; Abdollahi, Farzaneh

2018-04-01

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

Incipient Fault Detection for Rolling Element Bearings under Varying Speed Conditions

Directory of Open Access Journals (Sweden)

Lang Xue

2017-06-01

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

A New Acoustic Emission Sensor Based Gear Fault Detection Approach

Directory of Open Access Journals (Sweden)

Junda Zhu

2013-01-01

Full Text Available In order to reduce wind energy costs, prognostics and health management (PHM of wind turbine is needed to ensure the reliability and availability of wind turbines. A gearbox is an important component of a wind turbine. Therefore, developing effective gearbox fault detection tools is important to the PHM of wind turbine. In this paper, a new acoustic emission (AE sensor based gear fault detection approach is presented. This approach combines a heterodyne based frequency reduction technique with time synchronous average (TSA and spectrum kurtosis (SK to process AE sensor signals and extract features as condition indictors for gear fault detection. Heterodyne technique commonly used in communication is first employed to preprocess the AE signals before sampling. By heterodyning, the AE signal frequency is down shifted from several hundred kHz to below 50 kHz. This reduced AE signal sampling rate is comparable to that of vibration signals. The presented approach is validated using seeded gear tooth crack fault tests on a notational split torque gearbox. The approach presented in this paper is physics based and the validation results have showed that it could effectively detect the gear faults.

Land subsidence, Ground Fissures and Buried Faults: InSAR Monitoring of Ciudad Guzmán (Jalisco, Mexico

Directory of Open Access Journals (Sweden)

Carlo Alberto Brunori

2015-07-01

Full Text Available We study land subsidence processes and the associated ground fissuring, affecting an active graben filled by thick unconsolidated deposits by means of InSAR techniques and fieldwork. On 21 September 2012, Ciudad Guzmán (Jalisco, Mexico was struck by ground fissures of about 1.5 km of length, causing the deformation of the roads and the propagation of fissures in adjacent buildings. The field survey showed that fissures alignment is coincident with the escarpments produced on 19 September 1985, when a strong earthquake with magnitude 8.1 struck central Mexico. In order to detect and map the spatio-temporal features of the processes that led to the 2012 ground fissures, we applied InSAR multi-temporal techniques to process ENVISAT-ASAR and RADARSAT-2 satellite SAR images acquired between 2003 and 2012. We detect up to 20 mm/year of subsidence of the northwestern part of Ciudad Guzmán. These incremental movements are consistent with the ground fissures observed in 2012. Based on interferometric results, field data and 2D numerical model, we suggest that ground deformations and fissuring are due to the presence of areal subsidence correlated with variable sediment thickness and differential compaction, partly driven by the exploitation of the aquifers and controlled by the distribution and position of buried faults.

Fault and meal detection by redundant continuous glucose monitors and the unscented Kalman filter

DEFF Research Database (Denmark)

Mahmoudi, Zeinab; Nørgaard, Kirsten; Poulsen, Niels Kjølstad

2017-01-01

The purpose of this study is to develop a method for detecting and compensating the anomalies of continuous glucose monitoring (CGM) sensors as well as detecting unannounced meals. Both features, sensor fault detection/correction and meal detection, are necessary to have a reliable artificial pan...... is corrupted by PISA. The fault isolator can detect 199 out of 200 unannounced meals. The average change in the glucose concentrations between the meals and the detection time points is 46.3 mg/dL.......The purpose of this study is to develop a method for detecting and compensating the anomalies of continuous glucose monitoring (CGM) sensors as well as detecting unannounced meals. Both features, sensor fault detection/correction and meal detection, are necessary to have a reliable artificial...... from the two fault detectors differentiates between a sensor fault and an unannounced meal appearing as an anomaly in the CGM data. If the fault isolator indicates a sensor fault, a method based on the covariance matching technique tunes the covariance of the measurement noise associated...

Faults detection approach using PCA and SOM algorithm in PMSG-WT system

Directory of Open Access Journals (Sweden)

Mohamed Lamine FADDA

2016-07-01

Full Text Available In this paper, a new approach for faults detection in observable data system wind turbine - permanent magnet synchronous generator (WT-PMSG, the studying objective, illustrate the combination (SOM-PCA to build Multi-local-PCA models faults detection in system (WT-PMSG, the performance of the method suggested to faults detection in system data, finding good results in simulation experiment.

Fault detection and diagnosis using statistical control charts and artificial neural networks

International Nuclear Information System (INIS)

Leger, R.P.; Garland, W.J.; Poehlman, W.F.S.

1995-01-01

In order to operate a successful plant or process, continuous improvement must be made in the areas of safety, quality and reliability. Central to this continuous improvement is the early or proactive detection and correct diagnosis of process faults. This research examines the feasibility of using Cumulative Summation (CUSUM) Control Charts and artificial neural networks together for fault detection and diagnosis (FDD). The proposed FDD strategy was tested on a model of the heat transport system of a CANDU nuclear reactor. The results of the investigation indicate that a FDD system using CUSUM Control Charts and a Radial Basis Function (RBF) neural network is not only feasible but also of promising potential. The control charts and neural network are linked together by using a characteristic fault signature pattern for each fault which is to be detected and diagnosed. When tested, the system was able to eliminate all false alarms at steady state, promptly detect 6 fault conditions and correctly diagnose 5 out of the 6 faults. The diagnosis for the sixth fault was inconclusive. (author). 9 refs., 6 tabs., 7 figs

Experimental Fault Detection and Accomodation for an Agricultural Mobile Robot

DEFF Research Database (Denmark)

Østergaard, Kasper Zinck; Vinther, D.; Bisgaard, Morten

2005-01-01

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...

Fault Detection and Isolation for a Supermarket Refrigeration System - Part One

DEFF Research Database (Denmark)

Yang, Zhenyu; Rasmussen, Karsten B.; Kieu, Anh T.

2011-01-01

Fault Detection and Isolation (FDI) using the Kalman Filter (KF) technique for a supermarket refrigeration system is explored. Four types of sensor fault scenarios, namely drift, offset, freeze and hard-over, are considered for two temperature sensors, and one type of parametric fault scenario, n....... The test results show that the EKF-based FDI method generally performances better and faster than the KF-based method does. However, both methods can not handle the isolation between sensor faults and parametric fault.......Fault Detection and Isolation (FDI) using the Kalman Filter (KF) technique for a supermarket refrigeration system is explored. Four types of sensor fault scenarios, namely drift, offset, freeze and hard-over, are considered for two temperature sensors, and one type of parametric fault scenario...... isolation purpose, a bank of KFs arranged by splitting measurements is constructed for sensor fault isolation, while the Multi-Model Adaptive Estimation (MMAE) method is employed to handle parametric fault isolation. All these approaches are extended and checked by using Extended KF technique afterwards...

Fault detection in processes represented by PLS models using an EWMA control scheme

KAUST Repository

Harrou, Fouzi

2016-10-20

Fault detection is important for effective and safe process operation. Partial least squares (PLS) has been used successfully in fault detection for multivariate processes with highly correlated variables. However, the conventional PLS-based detection metrics, such as the Hotelling\\'s T and the Q statistics are not well suited to detect small faults because they only use information about the process in the most recent observation. Exponentially weighed moving average (EWMA), however, has been shown to be more sensitive to small shifts in the mean of process variables. In this paper, a PLS-based EWMA fault detection method is proposed for monitoring processes represented by PLS models. The performance of the proposed method is compared with that of the traditional PLS-based fault detection method through a simulated example involving various fault scenarios that could be encountered in real processes. The simulation results clearly show the effectiveness of the proposed method over the conventional PLS method.

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

Directory of Open Access Journals (Sweden)

Mehdi Shadaram

2010-10-01

Full Text Available 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.

Using Order Tracking Analysis Method to Detect the Angle Faults of Blades on Wind Turbine

DEFF Research Database (Denmark)

Li, Pengfei; Hu, Weihao; Liu, Juncheng

2016-01-01

The angle faults of blades on wind turbines are usually included in the set angle fault and the pitch angle fault. They are occupied with a high proportion in all wind turbine faults. Compare with the traditional fault detection methods, using order tracking analysis method to detect angle faults....... By analyzing and reconstructing the fault signals, it is easy to detect the fault characteristic frequency and see the characteristic frequencies of angle faults depend on the shaft rotating frequency, which is known as the 1P frequency and 3P frequency distinctly....

Fault Detection for Large-Scale Railway Maintenance Equipment Base on Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Junfu Yu

2014-04-01

Full Text Available Focusing on the fault detection application for large-scale railway maintenance equipment with the specialties of low-cost, energy efficiency, collecting data of the function units. This paper proposed energy efficiency, convenient installation fault detection application using Sigsbee wireless sensor networks, which Sigsbee is the most widely used protocol based on IEEE 802.15.4. This paper proposed a systematic application from hardware design using STM32F103 chips as processer, to software system. Fault detection application is the basic part of the fault diagnose system, wireless sensor nodes of the fault detection application with different kinds of sensors for verities function units communication by Sigsbee to collecting and sending basic working status data to the home gateway, then data will be sent to the fault diagnose system.

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

Science.gov (United States)

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

2018-03-01

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

Detecting Faults By Use Of Hidden Markov Models

Science.gov (United States)

Smyth, Padhraic J.

1995-01-01

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

Data driven fault detection and isolation: a wind turbine scenario

Directory of Open Access Journals (Sweden)

Rubén Francisco Manrique Piramanrique

2015-04-01

Full Text Available One of the greatest drawbacks in wind energy generation is the high maintenance cost associated to mechanical faults. This problem becomes more evident in utility scale wind turbines, where the increased size and nominal capacity comes with additional problems associated with structural vibrations and aeroelastic effects in the blades. Due to the increased operation capability, it is imperative to detect system degradation and faults in an efficient manner, maintaining system integrity, reliability and reducing operation costs. This paper presents a comprehensive comparison of four different Fault Detection and Isolation (FDI filters based on “Data Driven” (DD techniques. In order to enhance FDI performance, a multi-level strategy is used where:  the first level detects the occurrence of any given fault (detection, while  the second identifies the source of the fault (isolation. Four different DD classification techniques (namely Support Vector Machines, Artificial Neural Networks, K Nearest Neighbors and Gaussian Mixture Models were studied and compared for each of the proposed classification levels. The best strategy at each level could be selected to build the final data driven FDI system. The performance of the proposed scheme is evaluated on a benchmark model of a commercial wind turbine. 

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

Science.gov (United States)

Golafshan, Reza; Yuce Sanliturk, Kenan

2016-03-01

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

Integration of Fault Detection and Isolation with Control Using Neuro-fuzzy Scheme

Directory of Open Access Journals (Sweden)

A. Asokan

2009-10-01

Full Text Available In this paper an algorithms is developed for fault diagnosis and fault tolerant control strategy for nonlinear systems subjected to an unknown time-varying fault. At first, the design of fault diagnosis scheme is performed using model based fault detection technique. The neuro-fuzzy chi-square scheme is applied for fault detection and isolation. The fault magnitude and time of occurrence of fault is obtained through neuro-fuzzy chi-square scheme. The estimated magnitude of the fault magnitude is normalized and used by the feed-forward control algorithm to make appropriate changes in the manipulated variable to keep the controlled variable near its set value. The feed-forward controller acts along with feed-back controller to control the multivariable system. The performance of the proposed scheme is applied to a three- tank process for various types of fault inputs to show the effectiveness of the proposed approach.

Weak fault detection and health degradation monitoring using customized standard multiwavelets

Science.gov (United States)

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

2017-09-01

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

Evaluation of Wind Farm Controller based Fault Detection and Isolation

DEFF Research Database (Denmark)

Odgaard, Peter Fogh; Shafiei, Seyed Ehsan

2015-01-01

detection and isolation and fault tolerant control has previously been proposed. Based on this model, and international competition on wind farm FDI was organized. The contributions were presented at the IFAC World Congress 2014. In this paper the top three contributions to this competition are shortly......In the process of lowering cost of energy of power generated by wind turbines, some focus has been drawn towards fault detection and isolation and as well as fault tolerant control of wind turbines with the purpose of increasing reliability and availability of the wind turbines. Most modern wind...

Rupture Dynamics and Ground Motion from Earthquakes on Rough Faults in Heterogeneous Media

Science.gov (United States)

Bydlon, S. A.; Kozdon, J. E.; Duru, K.; Dunham, E. M.

2013-12-01

Heterogeneities in the material properties of Earth's crust scatter propagating seismic waves. The effects of scattered waves are reflected in the seismic coda and depend on the amplitude of the heterogeneities, spatial arrangement, and distance from source to receiver. In the vicinity of the fault, scattered waves influence the rupture process by introducing fluctuations in the stresses driving propagating ruptures. Further variability in the rupture process is introduced by naturally occurring geometric complexity of fault surfaces, and the stress changes that accompany slip on rough surfaces. Our goal is to better understand the origin of complexity in the earthquake source process, and to quantify the relative importance of source complexity and scattering along the propagation path in causing incoherence of high frequency ground motion. Using a 2D high order finite difference rupture dynamics code, we nucleate ruptures on either flat or rough faults that obey strongly rate-weakening friction laws. These faults are embedded in domains with spatially varying material properties characterized by Von Karman autocorrelation functions and their associated power spectral density functions, with variations in wave speed of approximately 5 to 10%. Flat fault simulations demonstrate that off-fault material heterogeneity, at least with this particular form and amplitude, has only a minor influence on the rupture process (i.e., fluctuations in slip and rupture velocity). In contrast, ruptures histories on rough faults in both homogeneous and heterogeneous media include much larger short-wavelength fluctuations in slip and rupture velocity. We therefore conclude that source complexity is dominantly influenced by fault geometric complexity. To examine contributions of scattering versus fault geometry on ground motions, we compute spatially averaged root-mean-square (RMS) acceleration values as a function of fault perpendicular distance for a homogeneous medium and several

A Novel Approach for Eccentricity Fault Detection in Squirrel Cage Induction Motors

Directory of Open Access Journals (Sweden)

Mehdi Ahmadi

2013-01-01

Full Text Available In this paper, static eccentricity fault detection in induction motors is studied. Two dimensional finite element method (2D-FEM is used for faultless and eccentric condition modeling in induction motors. Also current and speed signals are compared in two experimental and simulation cases for model validating. For fault detection, fast Fourier transform is used at first. In this method, high order harmonics with small amplitude can alarms the fault occurrence. For this reason, the fault detection process is difficult.To overcome these drawbacks, it is suggested that two test coils contrive around the air-gap. So, any changes in air-gap can be detected easily. Moreover this test coils are used in open circuit case. So, these test coils do not effect on motor dynamics. Also, the results show that modulated voltage can be alarm the fault occurrence, type and percent well.

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

International Nuclear Information System (INIS)

Wang, Wilson; Lee, Hewen

2013-01-01

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. (paper)

Active Fault Detection and Isolation for Hybrid Systems

DEFF Research Database (Denmark)

Gholami, Mehdi; Schiøler, Henrik; Bak, Thomas

2009-01-01

An algorithm for active fault detection and isolation is proposed. In order to observe the failure hidden due to the normal operation of the controllers or the systems, an optimization problem based on minimization of test signal is used. The optimization based method imposes the normal and faulty...... models predicted outputs such that their discrepancies are observable by passive fault diagnosis technique. Isolation of different faults is done by implementation a bank of Extended Kalman Filter (EKF) where the convergence criterion for EKF is confirmed by Genetic Algorithm (GA). The method is applied...

Reliable fault detection and diagnosis of photovoltaic systems based on statistical monitoring approaches

KAUST Repository

Harrou, Fouzi

2017-09-18

This study reports the development of an innovative fault detection and diagnosis scheme to monitor the direct current (DC) side of photovoltaic (PV) systems. Towards this end, we propose a statistical approach that exploits the advantages of one-diode model and those of the univariate and multivariate exponentially weighted moving average (EWMA) charts to better detect faults. Specifically, we generate array\\'s residuals of current, voltage and power using measured temperature and irradiance. These residuals capture the difference between the measurements and the predictions MPP for the current, voltage and power from the one-diode model, and use them as fault indicators. Then, we apply the multivariate EWMA (MEWMA) monitoring chart to the residuals to detect faults. However, a MEWMA scheme cannot identify the type of fault. Once a fault is detected in MEWMA chart, the univariate EWMA chart based on current and voltage indicators is used to identify the type of fault (e.g., short-circuit, open-circuit and shading faults). We applied this strategy to real data from the grid-connected PV system installed at the Renewable Energy Development Center, Algeria. Results show the capacity of the proposed strategy to monitors the DC side of PV systems and detects partial shading.

Observer Based Fault Detection and Moisture Estimating in Coal Mill

DEFF Research Database (Denmark)

Odgaard, Peter Fogh; Mataji, Babak

2008-01-01

In this paper an observer-based method for detecting faults and estimating moisture content in the coal in coal mills is presented. Handling of faults and operation under special conditions, such as high moisture content in the coal, are of growing importance due to the increasing...... requirements to the general performance of power plants. Detection  of faults and moisture content estimation are consequently of high interest in the handling of the problems caused by faults and moisture content. The coal flow out of the mill is the obvious variable to monitor, when detecting non-intended drops in the coal...... flow out of the coal mill. However, this variable is not measurable. Another estimated variable is the moisture content, which is only "measurable" during steady-state operations of the coal mill. Instead, this paper suggests a method where these unknown variables are estimated based on a simple energy...

Fault diagnosis and refrigerant leak detection in vapour compression refrigeration systems

Energy Technology Data Exchange (ETDEWEB)

Tassou, S.A.; Grace, I.N. [Brunel University, Uxbridge (United Kingdom). Department of Mechanical Engineering

2005-08-01

The environmental impact of refrigeration systems can be reduced by operation at higher efficiency and reduction of refrigerant leakage. Refrigerant loss contributes both directly and indirectly to global warming through inefficient system operation, increased power consumption and greenhouse gas emissions and higher maintenance costs. Existing sensor-based leak detection methods are limited by the inability to detect gradual leakage and the need for careful sensor location. There is a requirement for a real-time performance monitoring approach to leak detection and fault diagnosis which overcomes these disadvantages. This paper reports on the development of a fault diagnosis and refrigerant leak detection system based on artificial intelligence and real-time performance monitoring. The system has been used successfully to distinguish between faulty and fault free operation, steady-state and transient operation, leakage and over charge conditions. Work currently underway is aimed at testing additional fault conditions and establishing further rules to distinguish between these patterns. (author)

ASCS online fault detection and isolation based on an improved MPCA

Science.gov (United States)

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

2014-09-01

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

Automated Fault Detection for DIII-D Tokamak Experiments

International Nuclear Information System (INIS)

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

1999-01-01

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

Robust filtering and fault detection of switched delay systems

CERN Document Server

Wang, Dong; Wang, Wei

2013-01-01

Switched delay systems appear in a wide field of applications including networked control systems, power systems, memristive systems. Though the large amount of ideas with respect to such systems have generated, until now, it still lacks a framework to focus on filter design and fault detection issues which are relevant to life safety and property loss. Beginning with the comprehensive coverage of the new developments in the analysis and control synthesis for switched delay systems, the monograph not only provides a systematic approach to designing the filter and detecting the fault of switched delay systems, but it also covers the model reduction issues. Specific topics covered include: (1) Arbitrary switching signal where delay-independent and delay-dependent conditions are presented by proposing a linearization technique. (2) Average dwell time where a weighted Lyapunov function is come up with dealing with filter design and fault detection issues beside taking model reduction problems. The monograph is in...

Fault detection of a Five-Phase Permanent-Magnet Machine

DEFF Research Database (Denmark)

Bianchini, Claudio; Matzen, Torben N.; Bianchi, Nicola

2008-01-01

The paper focuses on the fault detection of a five-phase Permanent-Magnet (PM) machine. This machine has been de-signed for fault tolerant applications, and it is characterised by a mutual inductance equal to zero and a high self inductance, with the purpose to limit the short circuit current...

Ground Motion Synthetics For Spontaneous Versus Prescribed Rupture On A 45(o) Thrust Fault

Science.gov (United States)

Gottschämmer, E.; Olsen, K. B.

We have compared prescribed (kinematic) and spontaneous dynamic rupture propaga- tion on a 45(o) dipping thrust fault buried up to 5 km in a half-space model, as well as ground motions on the free surface for frequencies less than 1 Hz. The computa- tions are carried out using a 3D finite-difference method with rate-and-state friction on a planar, 20 km by 20 km fault. We use a slip-weakening distance of 15 cm and a slip- velocity weakening distance of 9.2 cm/s, similar to those for the dynamic study for the 1994 M6.7 Northridge earthquake by Nielsen and Olsen (2000) which generated satis- factory fits to selected strong motion data in the San Fernando Valley. The prescribed rupture propagation was designed to mimic that of the dynamic simulation at depth in order to isolate the dynamic free-surface effects. In this way, the results reflect the dy- namic (normal-stress) interaction with the free surface for various depths of burial of the fault. We find that the moment, peak slip and peak sliprate for the rupture breaking the surface are increased by up to 60%, 80%, and 10%, respectively, compared to the values for the scenario buried 5 km. The inclusion of these effects increases the peak displacements and velocities above the fault by factors up 3.4 and 2.9 including the increase in moment due to normal-stress effects at the free surface, and up to 2.1 and 2.0 when scaled to a Northridge-size event with surface rupture. Similar differences were found by Aagaard et al. (2001). Significant dynamic effects on the ground mo- tions include earlier arrival times caused by super-shear rupture velocities (break-out phases), in agreement with the dynamic finite-element simulations by Oglesby et al. (1998, 2000). The presence of shallow low-velocity layers tend to increase the rup- ture time and the sliprate. In particular, they promote earlier transitions to super-shear velocities and decrease the rupture velocity within the layers. Our results suggest that dynamic

Observer and data-driven model based fault detection in Power Plant Coal Mills

DEFF Research Database (Denmark)

Fogh Odgaard, Peter; Lin, Bao; Jørgensen, Sten Bay

2008-01-01

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......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...

Testing of ground fault relay response during the energisation of megawatt range electric boilers in thermal power plants

DEFF Research Database (Denmark)

Silva, Filipe Miguel Faria da; Bak, Claus Leth; Davidsen, Troels

2015-01-01

, with the advantage that the warmed water can be reused in a thermal power plant or at regional heating, thus, minimising the overall losses. However, one problem was raised by those purchasing the boilers, mainly the possibility of an unwanted triggering of the protections relays, especially ground fault protection...... for the testing of two ground fault protection relays, in order to assure that they are not triggered by the energisation of the boiler. The test is performed via an OMICRON CMC 256 with Advanced TransPlay SW, which generates the signals that would be present at the secondary of the instrumentation transformers......, during the energisation of a boiler. A special case for concern was the presence of an electric arc between the electrodes of the boiler and the water in the boiler during approximately 2s at the energisation, which can in theory be seen as a ground fault by the relay. The voltage and current transient...

Induced Voltages Ratio-Based Algorithm for Fault Detection, and Faulted Phase and Winding Identification of a Three-Winding Power Transformer

Directory of Open Access Journals (Sweden)

Byung Eun Lee

2014-09-01

Full Text Available This paper proposes an algorithm for fault detection, faulted phase and winding identification of a three-winding power transformer based on the induced voltages in the electrical power system. The ratio of the induced voltages of the primary-secondary, primary-tertiary and secondary-tertiary windings is the same as the corresponding turns ratio during normal operating conditions, magnetic inrush, and over-excitation. It differs from the turns ratio during an internal fault. For a single phase and a three-phase power transformer with wye-connected windings, the induced voltages of each pair of windings are estimated. For a three-phase power transformer with delta-connected windings, the induced voltage differences are estimated to use the line currents, because the delta winding currents are practically unavailable. Six detectors are suggested for fault detection. An additional three detectors and a rule for faulted phase and winding identification are presented as well. The proposed algorithm can not only detect an internal fault, but also identify the faulted phase and winding of a three-winding power transformer. The various test results with Electromagnetic Transients Program (EMTP-generated data show that the proposed algorithm successfully discriminates internal faults from normal operating conditions including magnetic inrush and over-excitation. This paper concludes by implementing the algorithm into a prototype relay based on a digital signal processor.

Gear Fault Detection Based on Teager-Huang Transform

Directory of Open Access Journals (Sweden)

Hui Li

2010-01-01

Full Text Available Gear fault detection based on Empirical Mode Decomposition (EMD and Teager Kaiser Energy Operator (TKEO technique is presented. This novel method is named as Teager-Huang transform (THT. EMD can adaptively decompose the vibration signal into a series of zero mean Intrinsic Mode Functions (IMFs. TKEO can track the instantaneous amplitude and instantaneous frequency of the Intrinsic Mode Functions at any instant. The experimental results provide effective evidence that Teager-Huang transform has better resolution than that of Hilbert-Huang transform. The Teager-Huang transform can effectively diagnose the fault of the gear, thus providing a viable processing tool for gearbox defect detection and diagnosis.

Application of Low Voltage High Resistance Grounding in Nuclear Power Plants

Directory of Open Access Journals (Sweden)

Choong-Koo Chang

2016-02-01

Full Text Available Most nuclear power plants now utilize solid grounded low voltage systems. For safety and reliability reasons, the low voltage (LV high resistance grounding (HRG system is also increasingly used in the pulp and paper, petroleum and chemical, and semiconductor industries. Fault detection is easiest and fastest with a solidly grounded system. However, a solidly grounded system has many limitations such as severe fault damage, poor reliability on essential circuits, and electrical noise caused by the high magnitude of ground fault currents. This paper will briefly address the strengths and weaknesses of LV grounding systems. An example of a low voltage HRG system in the LV system of a nuclear power plant will be presented. The HRG system is highly recommended for LV systems of nuclear power plants if sufficient considerations are provided to prevent nuisance tripping of ground fault relays and to avoid the deterioration of system reliability.

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

International Nuclear Information System (INIS)

Zhao Jinsong; Huang Jianchao; Sun Wei

2008-01-01

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

A Prognostic Method for Fault Detection in Wind Turbine Drivetrains

DEFF Research Database (Denmark)

Nejada, Amir R.; Odgaard, Peter Fogh; Gao, Zhen

2014-01-01

In this paper, a prognostic method is presented for fault detection in gears and bearings in wind turbine drivetrains. This method is based on angular velocity measurements from the gearbox input shaft and the output to the generator, using two additional angular velocity sensors on the intermedi......In this paper, a prognostic method is presented for fault detection in gears and bearings in wind turbine drivetrains. This method is based on angular velocity measurements from the gearbox input shaft and the output to the generator, using two additional angular velocity sensors...... bearing faults in three locations: the high-speed shaft stage, the planetary stage and the intermediate-speed shaft stage. Simulations of the faulty and fault-free cases are performed on a gearbox model implemented in multibody dynamic simulation software. The global loads on the gearbox are obtained from...

Fuzzy model-based observers for fault detection in CSTR.

Science.gov (United States)

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

2015-11-01

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

Fault Detection in Coal Mills used in Power Plants

DEFF Research Database (Denmark)

Odgaard, Peter Fogh; Mataji, Babak

2006-01-01

In order to achieve high performance and efficiency of coal-fired power plants, it is highly important to control the coal flow into the furnace in the power plant. This means suppression of disturbances and force the coal mill to deliver the required coal flow, as well as monitor the coal mill...... in order to detect faults in the coal mill when they emerge. This paper deals with the second objective. Based on a simple dynamic model of the energy balance a residual is formed for the coal mill. An optimal unknown input observer is designed to estimate this residual. The estimated residual is following...... tested on measured data of a fault in a coal mill, it can hereby be concluded that this residual is very useful for detecting faults in the coal mill....

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

Science.gov (United States)

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

2018-04-01

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

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

Science.gov (United States)

Li, Yunji; Wu, QingE; Peng, Li

2018-01-23

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

Ground Deformation Related to Caldera Collapse and Ring-Fault Activity

KAUST Repository

Liu, Yuan-Kai

2018-05-01

Volcanic subsidence, caused by partial emptying of magma in the subsurface reservoir has long been observed by spaceborne radar interferometry. Monitoring long-term crustal deformation at the most notable type of volcanic subsidence, caldera, gives us insights of the spatial and hazard-related information of subsurface reservoir. Several subsiding calderas, such as volcanoes on the Galapagos islands have shown a complex ground deformation pattern, which is often composed of a broad deflation signal affecting the entire edifice and a localized subsidence signal focused within the caldera floor. Although numerical or analytical models with multiple reservoirs are proposed as the interpretation, geologically and geophysically evidenced ring structures in the subsurface are often ignored. Therefore, it is still debatable how deep mechanisms relate to the observed deformation patterns near the surface. We aim to understand what kind of activities can lead to the complex deformation. Using two complementary approaches, we study the three-dimensional geometry and kinematics of deflation processes evolving from initial subsidence to later collapse of calderas. Firstly, the analog experiments analyzed by structure-from-motion photogrammetry (SfM) and particle image velocimetry (PIV) helps us to relate the surface deformation to the in-depth structures. Secondly, the numerical modeling using boundary element method (BEM) simulates the characteristic deformation patterns caused by a sill-like source and a ring-fault. Our results show that the volcano-wide broad deflation is primarily caused by the emptying of the deep magma reservoir, whereas the localized deformation on the caldera floor is related to ring-faulting at a shallower depth. The architecture of the ring-fault to a large extent determines the deformation localization on the surface. Since series evidence for ring-faulting at several volcanoes are provided, we highlight that it is vital to include ring-fault

Ground Deformation Related to Caldera Collapse and Ring-Fault Activity

KAUST Repository

Liu, Yuan-Kai

2018-01-01

Volcanic subsidence, caused by partial emptying of magma in the subsurface reservoir has long been observed by spaceborne radar interferometry. Monitoring long-term crustal deformation at the most notable type of volcanic subsidence, caldera, gives us insights of the spatial and hazard-related information of subsurface reservoir. Several subsiding calderas, such as volcanoes on the Galapagos islands have shown a complex ground deformation pattern, which is often composed of a broad deflation signal affecting the entire edifice and a localized subsidence signal focused within the caldera floor. Although numerical or analytical models with multiple reservoirs are proposed as the interpretation, geologically and geophysically evidenced ring structures in the subsurface are often ignored. Therefore, it is still debatable how deep mechanisms relate to the observed deformation patterns near the surface. We aim to understand what kind of activities can lead to the complex deformation. Using two complementary approaches, we study the three-dimensional geometry and kinematics of deflation processes evolving from initial subsidence to later collapse of calderas. Firstly, the analog experiments analyzed by structure-from-motion photogrammetry (SfM) and particle image velocimetry (PIV) helps us to relate the surface deformation to the in-depth structures. Secondly, the numerical modeling using boundary element method (BEM) simulates the characteristic deformation patterns caused by a sill-like source and a ring-fault. Our results show that the volcano-wide broad deflation is primarily caused by the emptying of the deep magma reservoir, whereas the localized deformation on the caldera floor is related to ring-faulting at a shallower depth. The architecture of the ring-fault to a large extent determines the deformation localization on the surface. Since series evidence for ring-faulting at several volcanoes are provided, we highlight that it is vital to include ring-fault

Nondestructive detection system of faults in fuses using radioisotope

International Nuclear Information System (INIS)

Goncalves, D.

1973-01-01

A system is developed to show the viability of non-destructive detection of the faults of explosive safety fuses which are manufactured by Fabrica da Estrela do Ministerio do Exercito. The faults are detected by an ion-chamber based on the variation of the intensity of the beta particles that penetrate the fuse which passes through a collimator. The beta particles are emitted by Strontium-90 + Yttrium-90 encapsulated in either stainless steel or aluminum. The concept of 'bucking Voltage' is applied to differentiate electronically the signal generated by the ion-chamber. (author)

Deconvolution effect of near-fault earthquake ground motions on stochastic dynamic response of tunnel-soil deposit interaction systems

Directory of Open Access Journals (Sweden)

K. Hacıefendioğlu

2012-04-01

Full Text Available The deconvolution effect of the near-fault earthquake ground motions on the stochastic dynamic response of tunnel-soil deposit interaction systems are investigated by using the finite element method. Two different earthquake input mechanisms are used to consider the deconvolution effects in the analyses: the standard rigid-base input and the deconvolved-base-rock input model. The Bolu tunnel in Turkey is chosen as a numerical example. As near-fault ground motions, 1999 Kocaeli earthquake ground motion is selected. The interface finite elements are used between tunnel and soil deposit. The mean of maximum values of quasi-static, dynamic and total responses obtained from the two input models are compared with each other.

Functional Fault Modeling Conventions and Practices for Real-Time Fault Isolation

Science.gov (United States)

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

2010-01-01

The purpose of this paper is to present the conventions, best practices, and processes that were established based on the prototype development of a Functional Fault Model (FFM) for a Cryogenic System that would be used for real-time Fault Isolation in a Fault Detection, Isolation, and Recovery (FDIR) system. The FDIR system is envisioned to perform health management functions for both a launch vehicle and the ground systems that support the vehicle during checkout and launch countdown by using a suite of complimentary software tools that alert operators to anomalies and failures in real-time. The FFMs were created offline but would eventually be used by a real-time reasoner to isolate faults in a Cryogenic System. Through their development and review, a set of modeling conventions and best practices were established. The prototype FFM development also provided a pathfinder for future FFM development processes. This paper documents the rationale and considerations for robust FFMs that can easily be transitioned to a real-time operating environment.

A Framework and Classification for Fault Detection Approaches in Wireless Sensor Networks with an Energy Efficiency Perspective

DEFF Research Database (Denmark)

Zhang, Yue; Dragoni, Nicola; Wang, Jiangtao

2015-01-01

efficiency to facilitate the design of fault detection methods and the evaluation of their energy efficiency. Following the same design principle of the fault detection framework, the paper proposes a classification for fault detection approaches. The classification is applied to a number of fault detection...

Signal processing for solar array monitoring, fault detection, and optimization

CERN Document Server

Braun, Henry; Spanias, Andreas

2012-01-01

Although the solar energy industry has experienced rapid growth recently, high-level management of photovoltaic (PV) arrays has remained an open problem. As sensing and monitoring technology continues to improve, there is an opportunity to deploy sensors in PV arrays in order to improve their management. In this book, we examine the potential role of sensing and monitoring technology in a PV context, focusing on the areas of fault detection, topology optimization, and performance evaluation/data visualization. First, several types of commonly occurring PV array faults are considered and detection algorithms are described. Next, the potential for dynamic optimization of an array's topology is discussed, with a focus on mitigation of fault conditions and optimization of power output under non-fault conditions. Finally, monitoring system design considerations such as type and accuracy of measurements, sampling rate, and communication protocols are considered. It is our hope that the benefits of monitoring presen...

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

Energy Technology Data Exchange (ETDEWEB)

Cheung, Howard [Purdue Univ., West Lafayette, IN (United States); Braun, James E. [Purdue Univ., West Lafayette, IN (United States)

2015-12-31

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

Model-Based Fault Detection and Isolation of a Liquid-Cooled Frequency Converter on a Wind Turbine

DEFF Research Database (Denmark)

Li, Peng; Odgaard, Peter Fogh; Stoustrup, Jakob

2012-01-01

advanced fault detection and isolation schemes. In this paper, an observer-based fault detection and isolation method for the cooling system in a liquid-cooled frequency converter on a wind turbine which is built up in a scalar version in the laboratory is presented. A dynamic model of the scale cooling...... system is derived based on energy balance equation. A fault analysis is conducted to determine the severity and occurrence rate of possible component faults and their end effects in the cooling system. A method using unknown input observer is developed in order to detect and isolate the faults based...... on the developed dynamical model. The designed fault detection and isolation algorithm is applied on a set of measured experiment data in which different faults are artificially introduced to the scaled cooling system. The experimental results conclude that the different faults are successfully detected...

Fault Detection of Aircraft Cable via Spread Spectrum Time Domain Reflectometry

Directory of Open Access Journals (Sweden)

Xudong SHI

2014-03-01

Full Text Available As the airplane cable fault detection based on TDR (time domain reflectometry is affected easily by various noise signals, which makes the reflected signal attenuate and distort heavily, failing to locate the fault. In order to solve these problems, a method of spread spectrum time domain reflectometry (SSTDR is introduced in this paper, taking the advantage of the sharp peak of correlation function. The test signal is generated from ML sequence (MLS modulated by sine wave in the same frequency. Theoretically, the test signal has the very high immunity of noise, which can be applied with excellent precision to fault location on the aircraft cable. In this paper, the method of SSTDR was normally simulated in MATLAB. Then, an experimental setup, based on LabVIEW, was organized to detect and locate the fault on the aircraft cable. It has been demonstrated that SSTDR has the high immunity of noise, reducing some detection errors effectively.

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

Science.gov (United States)

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

2010-08-17

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

Frequency Based Fault Detection in Wind Turbines

DEFF Research Database (Denmark)

Odgaard, Peter Fogh; Stoustrup, Jakob

2014-01-01

In order to obtain lower cost of energy for wind turbines fault detection and accommodation is important. Expensive condition monitoring systems are often used to monitor the condition of rotating and vibrating system parts. One example is the gearbox in a wind turbine. This system is operated...... in parallel to the control system, using different computers and additional often expensive sensors. In this paper a simple filter based algorithm is proposed to detect changes in a resonance frequency in a system, exemplified with faults resulting in changes in the resonance frequency in the wind turbine...... gearbox. Only the generator speed measurement which is available in even simple wind turbine control systems is used as input. Consequently this proposed scheme does not need additional sensors and computers for monitoring the condition of the wind gearbox. The scheme is evaluated on a wide-spread wind...

Improved Data-based Fault Detection Strategy and Application to Distillation Columns

KAUST Repository

Madakyaru, Muddu

2017-01-31

Chemical and petrochemical processes require continuous monitoring to detect abnormal events and to sustain normal operations. Furthermore, process monitoring enhances productivity, efficiency, and safety in process industries. Here, we propose an innovative statistical approach that exploits the advantages of multiscale partial least squares (MSPLS) models and generalized likelihood ratio (GLR) tests for fault detection in processes. Specifically, we combine an MSPLS algorithm with wavelet analysis to create our modeling framework. Then, we use GLR hypothesis testing based on the uncorrelated residuals obtained from the MSPLS model to improve fault detection. We use simulated distillation column data to evaluate the MSPLS-based GLR chart. Results show that our MSPLS-based GLR method is more powerful than the PLS-based Q and GLR method and MSPLS-based Q method, especially in early detection of small faults with abrupt or incipient behavior.

Improved Data-based Fault Detection Strategy and Application to Distillation Columns

KAUST Repository

Madakyaru, Muddu; Harrou, Fouzi; Sun, Ying

2017-01-01

Chemical and petrochemical processes require continuous monitoring to detect abnormal events and to sustain normal operations. Furthermore, process monitoring enhances productivity, efficiency, and safety in process industries. Here, we propose an innovative statistical approach that exploits the advantages of multiscale partial least squares (MSPLS) models and generalized likelihood ratio (GLR) tests for fault detection in processes. Specifically, we combine an MSPLS algorithm with wavelet analysis to create our modeling framework. Then, we use GLR hypothesis testing based on the uncorrelated residuals obtained from the MSPLS model to improve fault detection. We use simulated distillation column data to evaluate the MSPLS-based GLR chart. Results show that our MSPLS-based GLR method is more powerful than the PLS-based Q and GLR method and MSPLS-based Q method, especially in early detection of small faults with abrupt or incipient behavior.

Filtering, control and fault detection with randomly occurring incomplete information

CERN Document Server

Dong, Hongli; Gao, Huijun

2013-01-01

This book investigates the filtering, control and fault detection problems for several classes of nonlinear systems with randomly occurring incomplete information. It proposes new concepts, including RVNs, ROMDs, ROMTCDs, and ROQEs. The incomplete information under consideration primarily includes missing measurements, time-delays, sensor and actuator saturations, quantization effects and time-varying nonlinearities. The first part of this book focuses on the filtering, control and fault detection problems for several classes of nonlinear stochastic discrete-time systems and

Robust Fault Detection for a Class of Uncertain Nonlinear Systems Based on Multiobjective Optimization

Directory of Open Access Journals (Sweden)

Bingyong Yan

2015-01-01

Full Text Available A robust fault detection scheme for a class of nonlinear systems with uncertainty is proposed. The proposed approach utilizes robust control theory and parameter optimization algorithm to design the gain matrix of fault tracking approximator (FTA for fault detection. The gain matrix of FTA is designed to minimize the effects of system uncertainty on residual signals while maximizing the effects of system faults on residual signals. The design of the gain matrix of FTA takes into account the robustness of residual signals to system uncertainty and sensitivity of residual signals to system faults simultaneously, which leads to a multiobjective optimization problem. Then, the detectability of system faults is rigorously analyzed by investigating the threshold of residual signals. Finally, simulation results are provided to show the validity and applicability of the proposed approach.

Faults in clays their detection and properties

International Nuclear Information System (INIS)

Baldi, G.; Carabelli, E.; Chiantore, V.; Colombo, P.F.; Gruszka, A.; Pensieri, R.; Superbo, S.; Gera, F.

1991-01-01

The 'Faults in clays project', a cooperative research effort between Ismes and Enea of Italy and BGS and Exeter University of the UK, has been aimed at assessing and improving the resolution capability of some high resolution geophysical techniques for the detection of discontinuities in clay formations. All Ismes activities have been carried out in Italy: they consisted in the search of one or more sites - faulted clay formations - suitable for the execution of geophysical and geotechnical investigations, in the execution of such tests and in additional geological surveys and laboratory (geotechnical and geochemical) testing. The selected sites were two quarries in plio-pleistocenic clay formations in central Italy where faults had been observed. The greatest part of the research work has been carried out in the Orte site where also two 90 m boreholes have been drilled and cored. Geophysical work at Orte consisted of vertical electrical soundings (VESs) and horizontal electrical lines (HELs), four high resolution seismic reflection lines, and in-hole and cross-hole logs. Laboratory activities were geotechnical characterization and permeability tests, and measurements of disequilibrium in the uranium decay series. At Narni, where Exeter University sampled soil gases for geochemical analyses, the geophysical work consisted in a geo-electrical survey (five VESs and two HELs), and in two high resolution reflection seismic lines. Additional investigations included a structural geology survey. The main conclusion of the research is that current geophysical techniques do not have a resolution capacity sufficient to detect the existence and determine the characteristics of faults in deep homogeneous clay formations

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

Science.gov (United States)

Elbouchikhi, Elhoussin; Choqueuse, Vincent; Benbouzid, Mohamed

2016-07-01

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

Invariant protection of high-voltage electric motors of technological complexes at industrial enterprises at partial single-phase ground faults

Science.gov (United States)

Abramovich, B. N.; Sychev, Yu A.; Pelenev, D. N.

2018-03-01

Development results of invariant protection of high-voltage motors at incomplete single-phase ground faults are observed in the article. It is established that current protections have low action selectivity because of an inadmissible decrease in entrance signals during the shirt circuit occurrence in the place of transient resistance. The structural functional scheme and an algorithm of protective actions where correction of automatic zero sequence currents signals of the protected accessions implemented according to the level of incompleteness of ground faults are developed. It is revealed that automatic correction of zero sequence currents allows one to provide the invariance of sensitivity factor for protection under the variation conditions of a transient resistance in the place of damage. Application of invariant protection allows one to minimize damages in 6-10 kV electrical installations of industrial enterprises for a cause of infringement of consumers’ power supply and their system breakdown due to timely localization of emergency of ground faults modes.

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

Science.gov (United States)

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

2014-01-01

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

FAULT DETECTION AND LOCALIZATION IN MOTORCYCLES BASED ON THE CHAIN CODE OF PSEUDOSPECTRA AND ACOUSTIC SIGNALS

Directory of Open Access Journals (Sweden)

B. S. Anami

2013-06-01

Full Text Available Vehicles produce sound signals with varying temporal and spectral properties under different working conditions. These sounds are indicative of the condition of the engine. Fault diagnosis is a significantly difficult task in geographically remote places where expertise is scarce. Automated fault diagnosis can assist riders to assess the health condition of their vehicles. This paper presents a method for fault detection and location in motorcycles based on the chain code of the pseudospectra and Mel-frequency cepstral coefficient (MFCC features of acoustic signals. The work comprises two stages: fault detection and fault location. The fault detection stage uses the chain code of the pseudospectrum as a feature vector. If the motorcycle is identified as faulty, the MFCCs of the same sample are computed and used as features for fault location. Both stages employ dynamic time warping for the classification of faults. Five types of faults in motorcycles are considered in this work. Observed classification rates are over 90% for the fault detection stage and over 94% for the fault location stage. The work identifies other interesting applications in the development of acoustic fingerprints for fault diagnosis of machinery, tuning of musical instruments, medical diagnosis, etc.

Bayesian fault detection and isolation using Field Kalman Filter

Science.gov (United States)

Baranowski, Jerzy; Bania, Piotr; Prasad, Indrajeet; Cong, Tian

2017-12-01

Fault detection and isolation is crucial for the efficient operation and safety of any industrial process. There is a variety of methods from all areas of data analysis employed to solve this kind of task, such as Bayesian reasoning and Kalman filter. In this paper, the authors use a discrete Field Kalman Filter (FKF) to detect and recognize faulty conditions in a system. The proposed approach, devised for stochastic linear systems, allows for analysis of faults that can be expressed both as parameter and disturbance variations. This approach is formulated for the situations when the fault catalog is known, resulting in the algorithm allowing estimation of probability values. Additionally, a variant of algorithm with greater numerical robustness is presented, based on computation of logarithmic odds. Proposed algorithm operation is illustrated with numerical examples, and both its merits and limitations are critically discussed and compared with traditional EKF.

Ares I-X Ground Diagnostic Prototype

Science.gov (United States)

Schwabacher, Mark A.; Martin, Rodney Alexander; Waterman, Robert D.; Oostdyk, Rebecca Lynn; Ossenfort, John P.; Matthews, Bryan

2010-01-01

The automation of pre-launch diagnostics for launch vehicles offers three potential benefits: improving safety, reducing cost, and reducing launch delays. The Ares I-X Ground Diagnostic Prototype demonstrated anomaly detection, fault detection, fault isolation, and diagnostics for the Ares I-X first-stage Thrust Vector Control and for the associated ground hydraulics while the vehicle was in the Vehicle Assembly Building at Kennedy Space Center (KSC) and while it was on the launch pad. The prototype combines three existing tools. The first tool, TEAMS (Testability Engineering and Maintenance System), is a model-based tool from Qualtech Systems Inc. for fault isolation and diagnostics. The second tool, SHINE (Spacecraft Health Inference Engine), is a rule-based expert system that was developed at the NASA Jet Propulsion Laboratory. We developed SHINE rules for fault detection and mode identification, and used the outputs of SHINE as inputs to TEAMS. The third tool, IMS (Inductive Monitoring System), is an anomaly detection tool that was developed at NASA Ames Research Center. The three tools were integrated and deployed to KSC, where they were interfaced with live data. This paper describes how the prototype performed during the period of time before the launch, including accuracy and computer resource usage. The paper concludes with some of the lessons that we learned from the experience of developing and deploying the prototype.

Fault Detection of Wind Turbines with Uncertain Parameters: A Set-Membership Approach

Directory of Open Access Journals (Sweden)

Thomas Bak

2012-07-01

Full Text Available In this paper a set-membership approach for fault detection of a benchmark wind turbine is proposed. The benchmark represents relevant fault scenarios in the control system, including sensor, actuator and system faults. In addition we also consider parameter uncertainties and uncertainties on the torque coefficient. High noise on the wind speed measurement, nonlinearities in the aerodynamic torque and uncertainties on the parameters make fault detection a challenging problem. We use an effective wind speed estimator to reduce the noise on the wind speed measurements. A set-membership approach is used generate a set that contains all states consistent with the past measurements and the given model of the wind turbine including uncertainties and noise. This set represents all possible states the system can be in if not faulty. If the current measurement is not consistent with this set, a fault is detected. For representation of these sets we use zonotopes and for modeling of uncertainties we use matrix zonotopes, which yields a computationally efficient algorithm. The method is applied to the wind turbine benchmark problem without and with uncertainties. The result demonstrates the effectiveness of the proposed method compared to other proposed methods applied to the same problem. An advantage of the proposed method is that there is no need for threshold design, and it does not produce positive false alarms. In the case where uncertainty on the torque lookup table is introduced, some faults are not detectable. Previous research has not addressed this uncertainty. The method proposed here requires equal or less detection time than previous results.

Parameter-free bearing fault detection based on maximum likelihood estimation and differentiation

International Nuclear Information System (INIS)

Bozchalooi, I Soltani; Liang, Ming

2009-01-01

Bearing faults can lead to malfunction and ultimately complete stall of many machines. The conventional high-frequency resonance (HFR) method has been commonly used for bearing fault detection. However, it is often very difficult to obtain and calibrate bandpass filter parameters, i.e. the center frequency and bandwidth, the key to the success of the HFR method. This inevitably undermines the usefulness of the conventional HFR technique. To avoid such difficulties, we propose parameter-free, versatile yet straightforward techniques to detect bearing faults. We focus on two types of measured signals frequently encountered in practice: (1) a mixture of impulsive faulty bearing vibrations and intrinsic background noise and (2) impulsive faulty bearing vibrations blended with intrinsic background noise and vibration interferences. To design a proper signal processing technique for each case, we analyze the effects of intrinsic background noise and vibration interferences on amplitude demodulation. For the first case, a maximum likelihood-based fault detection method is proposed to accommodate the Rician distribution of the amplitude-demodulated signal mixture. For the second case, we first illustrate that the high-amplitude low-frequency vibration interferences can make the amplitude demodulation ineffective. Then we propose a differentiation method to enhance the fault detectability. It is shown that the iterative application of a differentiation step can boost the relative strength of the impulsive faulty bearing signal component with respect to the vibration interferences. This preserves the effectiveness of amplitude demodulation and hence leads to more accurate fault detection. The proposed approaches are evaluated on simulated signals and experimental data acquired from faulty bearings

Incipient fault detection and identification in process systems using accelerating neural network learning

International Nuclear Information System (INIS)

Parlos, A.G.; Muthusami, J.; Atiya, A.F.

1994-01-01

The objective of this paper is to present the development and numerical testing of a robust fault detection and identification (FDI) system using artificial neural networks (ANNs), for incipient (slowly developing) faults occurring in process systems. The challenge in using ANNs in FDI systems arises because of one's desire to detect faults of varying severity, faults from noisy sensors, and multiple simultaneous faults. To address these issues, it becomes essential to have a learning algorithm that ensures quick convergence to a high level of accuracy. A recently developed accelerated learning algorithm, namely a form of an adaptive back propagation (ABP) algorithm, is used for this purpose. The ABP algorithm is used for the development of an FDI system for a process composed of a direct current motor, a centrifugal pump, and the associated piping system. Simulation studies indicate that the FDI system has significantly high sensitivity to incipient fault severity, while exhibiting insensitivity to sensor noise. For multiple simultaneous faults, the FDI system detects the fault with the predominant signature. The major limitation of the developed FDI system is encountered when it is subjected to simultaneous faults with similar signatures. During such faults, the inherent limitation of pattern-recognition-based FDI methods becomes apparent. Thus, alternate, more sophisticated FDI methods become necessary to address such problems. Even though the effectiveness of pattern-recognition-based FDI methods using ANNs has been demonstrated, further testing using real-world data is necessary

Fault Detection Using the Clustering-kNN Rule for Gas Sensor Arrays

Directory of Open Access Journals (Sweden)

Jingli Yang

2016-12-01

Full Text Available The k-nearest neighbour (kNN rule, which naturally handles the possible non-linearity of data, is introduced to solve the fault detection problem of gas sensor arrays. In traditional fault detection methods based on the kNN rule, the detection process of each new test sample involves all samples in the entire training sample set. Therefore, these methods can be computation intensive in monitoring processes with a large volume of variables and training samples and may be impossible for real-time monitoring. To address this problem, a novel clustering-kNN rule is presented. The landmark-based spectral clustering (LSC algorithm, which has low computational complexity, is employed to divide the entire training sample set into several clusters. Further, the kNN rule is only conducted in the cluster that is nearest to the test sample; thus, the efficiency of the fault detection methods can be enhanced by reducing the number of training samples involved in the detection process of each test sample. The performance of the proposed clustering-kNN rule is fully verified in numerical simulations with both linear and non-linear models and a real gas sensor array experimental system with different kinds of faults. The results of simulations and experiments demonstrate that the clustering-kNN rule can greatly enhance both the accuracy and efficiency of fault detection methods and provide an excellent solution to reliable and real-time monitoring of gas sensor arrays.

Fault Detection Using the Clustering-kNN Rule for Gas Sensor Arrays

Science.gov (United States)

Yang, Jingli; Sun, Zhen; Chen, Yinsheng

2016-01-01

The k-nearest neighbour (kNN) rule, which naturally handles the possible non-linearity of data, is introduced to solve the fault detection problem of gas sensor arrays. In traditional fault detection methods based on the kNN rule, the detection process of each new test sample involves all samples in the entire training sample set. Therefore, these methods can be computation intensive in monitoring processes with a large volume of variables and training samples and may be impossible for real-time monitoring. To address this problem, a novel clustering-kNN rule is presented. The landmark-based spectral clustering (LSC) algorithm, which has low computational complexity, is employed to divide the entire training sample set into several clusters. Further, the kNN rule is only conducted in the cluster that is nearest to the test sample; thus, the efficiency of the fault detection methods can be enhanced by reducing the number of training samples involved in the detection process of each test sample. The performance of the proposed clustering-kNN rule is fully verified in numerical simulations with both linear and non-linear models and a real gas sensor array experimental system with different kinds of faults. The results of simulations and experiments demonstrate that the clustering-kNN rule can greatly enhance both the accuracy and efficiency of fault detection methods and provide an excellent solution to reliable and real-time monitoring of gas sensor arrays. PMID:27929412

Applying Parametric Fault Detection to a Mechanical System

DEFF Research Database (Denmark)

Felício, P.; Stoustrup, Jakob; Niemann, H.

2002-01-01

A way of doing parametric fault detection is described. It is based on the representation of parameter changes as linear fractional transformations (lfts). We describe a model with parametric uncertainty. Then a stabilizing controller is chosen and its robustness properties are studied via mu. Th....... The parameter changes (faults) are estimated based on estimates of the fictitious signals that enter the delta block in the lft. These signal estimators are designed by H-infinity techniques. The chosen example is an inverted pendulum....

Broken Bar Fault Detection in IM Operating Under No-Load Condition

Directory of Open Access Journals (Sweden)

RELJIC, D.

2016-11-01

Full Text Available This paper presents a novel method for broken rotor bar detection in a squirrel-cage induction motor (IM. The proposed method applies a single-phase AC voltage as a test signal on motor terminals, resulting in a stator backward-rotating magnetic field. The field ultimately causes additional current components in the stator windings whose magnitudes depend on the broken bar fault severity, even if the motor is unloaded. This allows robust broken bar fault detection based only on standard motor current signature analysis (MCSA technique. The proposed fault detection method is at first verified via simulations, using an IM model based on finite element analysis (FEA and multiple coupled circuit approach (MCCA. The subsequent experimental investigations have shown good agreement with both theoretical predictions and simulation results.

Early fault detection and on-line diagnosis in real-time environments

Directory of Open Access Journals (Sweden)

Andreas Bye

1993-01-01

Full Text Available This paper describes an approach to fault detection and diagnosis involving the simultaneous employment of quantitative and qualitative reasoning techniques. We show that early identification of process anomalies by means of a separate fault detection module paves the way for a fast and accuratc follow-up diagnosis. The diagnosis task is dramatically simplified because the diagnostic inferences can be performed at the soonest possible time: when the detection module first spots deviations between its calculated reference points and the corresponding measurements from the process.

In-Flight Fault Diagnosis for Autonomous Aircraft Via Low-Rate Telemetry Channel

DEFF Research Database (Denmark)

Blanke, Mogens; Hansen, Søren

2012-01-01

An in-flight diagnosis system that is able to detect faults on an unmanned aircraft using real-time telemetry data could provide operator assistance to warn about imminent risks due to faults. However, limited bandwidth of the air-ground radio-link makes diagnosis difficult. Loss of information a...

Fault detection and diagnosis in nonlinear systems a differential and algebraic viewpoint

CERN Document Server

Martinez-Guerra, Rafael

2014-01-01

The high reliability required in industrial processes has created the necessity of detecting abnormal conditions, called faults, while processes are operating. The term fault generically refers to any type of process degradation, or degradation in equipment performance because of changes in the process's physical characteristics, process inputs or environmental conditions. This book is about the fundamentals of fault detection and diagnosis in a variety of nonlinear systems which are represented by ordinary differential equations. The fault detection problem is approached from a differential algebraic viewpoint, using residual generators based upon high-gain nonlinear auxiliary systems (‘observers’). A prominent role is played by the type of mathematical tools that will be used, requiring knowledge of differential algebra and differential equations. Specific theorems tailored to the needs of the problem-solving procedures are developed and proved. Applications to real-world problems, both with constant an...

Characterization of the dynamic response of structures to damaging pulse-type near-fault ground motions

International Nuclear Information System (INIS)

Mollaioli, F.; Bruno, S.; Decanini, L.D.; Panza, G.F.

2006-12-01

The presence of long-period pulses in near-fault records can be considered as an important factor in causing damage due to the transmission of large amounts of energy to the structures in a very short time. Under such circumstances high-energy dissipation demands usually occur, which are likely to concentrate in the weakest parts of the structure. The maximum nonlinear response or collapse often happens at the onset of directivity pulse and fling, and this time is not predicted by the natural structural vibration periods. Nonlinear response leading to collapse may in most cases occur only during one large amplitude pulse of displacement. From the study of the response of both linear and nonlinear SDOF systems, the effects of these distinctive long-period pulses have been assessed by means of: (i) synthetic parameters directly derived from the strong ground motion records, and (ii) elastic and inelastic spectra of both conventional and energy-based seismic demand parameters. SDOF systems have first been subjected to records obtained during recent earthquakes in near-fault areas in forward directivity conditions. The results indicate that long duration pulses strongly affect the inelastic response, with very high energy and displacement demands which may be several times larger than the limit values specified by the majority of codes. In addition, from the recognition of the fundamental importance of velocity and energy-based parameters in the characterization of near-fault signals, idealized pulses equivalent to near-fault signals have been defined on account of such parameters. Equivalent pulses are capable of representing the salient observed features of the response to near-fault recorded ground motions. (author)

Transient Monitoring Function–Based Fault Detection for Inverter-Interfaced Microgrids

DEFF Research Database (Denmark)

Sadeghkhani, Iman; Esmail Hamedani Golshan, Mohamad; Mehrizi-Sani, Ali

2018-01-01

One of the major challenges in protection of the inverter-interfaced islanded microgrids is their limited fault current level. This degrades the performance of traditional overcurrent protection schemes. This paper proposes a fault detection strategy based on monitoring the transient response......-domain simulation case studies using the CIGRE benchmark low voltage microgrid network....

DYNAMIC SOFTWARE TESTING MODELS WITH PROBABILISTIC PARAMETERS FOR FAULT DETECTION AND ERLANG DISTRIBUTION FOR FAULT RESOLUTION DURATION

Directory of Open Access Journals (Sweden)

A. D. Khomonenko

2016-07-01

Full Text Available Subject of Research.Software reliability and test planning models are studied taking into account the probabilistic nature of error detection and discovering. Modeling of software testing enables to plan the resources and final quality at early stages of project execution. Methods. Two dynamic models of processes (strategies are suggested for software testing, using error detection probability for each software module. The Erlang distribution is used for arbitrary distribution approximation of fault resolution duration. The exponential distribution is used for approximation of fault resolution discovering. For each strategy, modified labeled graphs are built, along with differential equation systems and their numerical solutions. The latter makes it possible to compute probabilistic characteristics of the test processes and states: probability states, distribution functions for fault detection and elimination, mathematical expectations of random variables, amount of detected or fixed errors. Evaluation of Results. Probabilistic characteristics for software development projects were calculated using suggested models. The strategies have been compared by their quality indexes. Required debugging time to achieve the specified quality goals was calculated. The calculation results are used for time and resources planning for new projects. Practical Relevance. The proposed models give the possibility to use the reliability estimates for each individual module. The Erlang approximation removes restrictions on the use of arbitrary time distribution for fault resolution duration. It improves the accuracy of software test process modeling and helps to take into account the viability (power of the tests. With the use of these models we can search for ways to improve software reliability by generating tests which detect errors with the highest probability.

All row, planar fault detection system

Science.gov (United States)

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

2013-07-23

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

A statistical-based approach for fault detection and diagnosis in a photovoltaic system

KAUST Repository

Garoudja, Elyes; Harrou, Fouzi; Sun, Ying; Kara, Kamel; Chouder, Aissa; Silvestre, Santiago

2017-01-01

This paper reports a development of a statistical approach for fault detection and diagnosis in a PV system. Specifically, the overarching goal of this work is to early detect and identify faults on the DC side of a PV system (e.g., short

Fast Computation of Ground Motion Shaking Map base on the Modified Stochastic Finite Fault Modeling

Science.gov (United States)

Shen, W.; Zhong, Q.; Shi, B.

2012-12-01

Rapidly regional MMI mapping soon after a moderate-large earthquake is crucial to loss estimation, emergency services and planning of emergency action by the government. In fact, many countries show different degrees of attention on the technology of rapid estimation of MMI , and this technology has made significant progress in earthquake-prone countries. In recent years, numerical modeling of strong ground motion has been well developed with the advances of computation technology and earthquake science. The computational simulation of strong ground motion caused by earthquake faulting has become an efficient way to estimate the regional MMI distribution soon after earthquake. In China, due to the lack of strong motion observation in network sparse or even completely missing areas, the development of strong ground motion simulation method has become an important means of quantitative estimation of strong motion intensity. In many of the simulation models, stochastic finite fault model is preferred to rapid MMI estimating for its time-effectiveness and accuracy. In finite fault model, a large fault is divided into N subfaults, and each subfault is considered as a small point source. The ground motions contributed by each subfault are calculated by the stochastic point source method which is developed by Boore, and then summed at the observation point to obtain the ground motion from the entire fault with a proper time delay. Further, Motazedian and Atkinson proposed the concept of Dynamic Corner Frequency, with the new approach, the total radiated energy from the fault and the total seismic moment are conserved independent of subfault size over a wide range of subfault sizes. In current study, the program EXSIM developed by Motazedian and Atkinson has been modified for local or regional computations of strong motion parameters such as PGA, PGV and PGD, which are essential for MMI estimating. To make the results more reasonable, we consider the impact of V30 for the

Fault detection and diagnosis for compliance monitoring in international supply chains

NARCIS (Netherlands)

Wang, Yuxin; Tian, Yifu; Teixeira, André; Hulstijn, Joris; Tan, Yao-Hua

Currently international supply chains are facing risks concerning faults in compliance, such as altering shipping documentations, fictitious inventory, and inter-company manipulations. In this paper a method to detect and diagnose fault scenarios regarding customs compliance in supply chains is

Control Surface Fault Diagnosis with Specified Detection Probability - Real Event Experiences

DEFF Research Database (Denmark)

Hansen, Søren; Blanke, Mogens

2013-01-01

desired levels of false alarms and detection probabilities. Self-tuning residual generators are employed for diagnosis and are combined with statistical change detection to form a setup for robust fault diagnosis. On-line estimation of test statistics is used to obtain a detection threshold and a desired...... false alarm probability. A data based method is used to determine the validity of the methods proposed. Verification is achieved using real data and shows that the presented diagnosis method is efficient and could have avoided incidents where faults led to loss of aircraft....

A statistical-based approach for fault detection and diagnosis in a photovoltaic system

KAUST Repository

Garoudja, Elyes

2017-07-10

This paper reports a development of a statistical approach for fault detection and diagnosis in a PV system. Specifically, the overarching goal of this work is to early detect and identify faults on the DC side of a PV system (e.g., short-circuit faults; open-circuit faults; and partial shading faults). Towards this end, we apply exponentially-weighted moving average (EWMA) control chart on the residuals obtained from the one-diode model. Such a choice is motivated by the greater sensitivity of EWMA chart to incipient faults and its low-computational cost making it easy to implement in real time. Practical data from a 3.2 KWp photovoltaic plant located within an Algerian research center is used to validate the proposed approach. Results show clearly the efficiency of the developed method in monitoring PV system status.

A Research on the Electrical Test Fault Diagnostic and Data Mining of a Manned Spacecraft

Directory of Open Access Journals (Sweden)

Yang Feng

2017-01-01

Full Text Available The paper introduces the modeling method and modeling tool for the fault diagnosis of manned spacecraft, the multi-signal flow graph model of a manned space equipment was established using this method; the framework of the fault detection and diagnosis system of manned spacecraft is proposed, the function of ground system and function of the spacecraft are clearly defined. The structure of the functional module is given separately; finally, the tool builds the fault detection and diagnosis system, the application of fault diagnosis method for manned spacecraft is used for reference.

A Self-Learning Sensor Fault Detection Framework for Industry Monitoring IoT

Directory of Open Access Journals (Sweden)

Yu Liu

2013-01-01

Full Text Available Many applications based on Internet of Things (IoT technology have recently founded in industry monitoring area. Thousands of sensors with different types work together in an industry monitoring system. Sensors at different locations can generate streaming data, which can be analyzed in the data center. In this paper, we propose a framework for online sensor fault detection. We motivate our technique in the context of the problem of the data value fault detection and event detection. We use the Statistics Sliding Windows (SSW to contain the recent sensor data and regress each window by Gaussian distribution. The regression result can be used to detect the data value fault. Devices on a production line may work in different workloads and the associate sensors will have different status. We divide the sensors into several status groups according to different part of production flow chat. In this way, the status of a sensor is associated with others in the same group. We fit the values in the Status Transform Window (STW to get the slope and generate a group trend vector. By comparing the current trend vector with history ones, we can detect a rational or irrational event. In order to determine parameters for each status group we build a self-learning worker thread in our framework which can edit the corresponding parameter according to the user feedback. Group-based fault detection (GbFD algorithm is proposed in this paper. We test the framework with a simulation dataset extracted from real data of an oil field. Test result shows that GbFD detects 95% sensor fault successfully.

Earthquake cycle modeling of multi-segmented faults: dynamic rupture and ground motion simulation of the 1992 Mw 7.3 Landers earthquake.

Science.gov (United States)

Petukhin, A.; Galvez, P.; Somerville, P.; Ampuero, J. P.

2017-12-01

We perform earthquake cycle simulations to study the characteristics of source scaling relations and strong ground motions and in multi-segmented fault ruptures. For earthquake cycle modeling, a quasi-dynamic solver (QDYN, Luo et al, 2016) is used to nucleate events and the fully dynamic solver (SPECFEM3D, Galvez et al., 2014, 2016) is used to simulate earthquake ruptures. The Mw 7.3 Landers earthquake has been chosen as a target earthquake to validate our methodology. The SCEC fault geometry for the three-segmented Landers rupture is included and extended at both ends to a total length of 200 km. We followed the 2-D spatial correlated Dc distributions based on Hillers et. al. (2007) that associates Dc distribution with different degrees of fault maturity. The fault maturity is related to the variability of Dc on a microscopic scale. Large variations of Dc represents immature faults and lower variations of Dc represents mature faults. Moreover we impose a taper (a-b) at the fault edges and limit the fault depth to 15 km. Using these settings, earthquake cycle simulations are performed to nucleate seismic events on different sections of the fault, and dynamic rupture modeling is used to propagate the ruptures. The fault segmentation brings complexity into the rupture process. For instance, the change of strike between fault segments enhances strong variations of stress. In fact, Oglesby and Mai (2012) show the normal stress varies from positive (clamping) to negative (unclamping) between fault segments, which leads to favorable or unfavorable conditions for rupture growth. To replicate these complexities and the effect of fault segmentation in the rupture process, we perform earthquake cycles with dynamic rupture modeling and generate events similar to the Mw 7.3 Landers earthquake. We extract the asperities of these events and analyze the scaling relations between rupture area, average slip and combined area of asperities versus moment magnitude. Finally, the

Automated valve fault detection based on acoustic emission parameters and support vector machine

Directory of Open Access Journals (Sweden)

Salah M. Ali

2018-03-01

Full Text Available Reciprocating compressors are one of the most used types of compressors with wide applications in industry. The most common failure in reciprocating compressors is always related to the valves. Therefore, a reliable condition monitoring method is required to avoid the unplanned shutdown in this category of machines. Acoustic emission (AE technique is one of the effective recent methods in the field of valve condition monitoring. However, a major challenge is related to the analysis of AE signal which perhaps only depends on the experience and knowledge of technicians. This paper proposes automated fault detection method using support vector machine (SVM and AE parameters in an attempt to reduce human intervention in the process. Experiments were conducted on a single stage reciprocating air compressor by combining healthy and faulty valve conditions to acquire the AE signals. Valve functioning was identified through AE waveform analysis. SVM faults detection model was subsequently devised and validated based on training and testing samples respectively. The results demonstrated automatic valve fault detection model with accuracy exceeding 98%. It is believed that valve faults can be detected efficiently without human intervention by employing the proposed model for a single stage reciprocating compressor. Keywords: Condition monitoring, Faults detection, Signal analysis, Acoustic emission, Support vector machine

GOTRES: an expert system for fault detection and analysis

International Nuclear Information System (INIS)

Chung, D.T.; Modarres, M.

1989-01-01

This paper describes a deep-knowledge expert system shell for diagnosing faults in process operations. The expert program shell is called GOTRES (GOal TRee Expert System) and uses a goal tree-success tree deep-knowledge structure to model its knowledge-base. To demonstrate GOTRES, we have built an on-line fault diagnosis expert system for an experimental nuclear reactor facility using this shell. The expert system is capable of diagnosing fault conditions using system goal tree as well as utilizing accumulated operating knowledge to predict plant causal and temporal behaviours. The GOTRES shell has also been used for root-cause detection and analysis in a nuclear plant. (author)

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

Science.gov (United States)

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

2010-12-07

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

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

Energy Technology Data Exchange (ETDEWEB)

Frank, Stephen; Heaney, Michael; Jin, Xin; Robertson, Joseph; Cheung, Howard; Elmore, Ryan; Henze, Gregor

2016-08-01

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

Model-based fault detection and isolation of a PWR nuclear power plant using neural networks

International Nuclear Information System (INIS)

Far, R.R.; Davilu, H.; Lucas, C.

2008-01-01

The proper and timely fault detection and isolation of industrial plant is of premier importance to guarantee the safe and reliable operation of industrial plants. The paper presents application of a neural networks-based scheme for fault detection and isolation, for the pressurizer of a PWR nuclear power plant. The scheme is constituted by 2 components: residual generation and fault isolation. The first component generates residuals via the discrepancy between measurements coming from the plant and a nominal model. The neutral network estimator is trained with healthy data collected from a full-scale simulator. For the second component detection thresholds are used to encode the residuals as bipolar vectors which represent fault patterns. These patterns are stored in an associative memory based on a recurrent neutral network. The proposed fault diagnosis tool is evaluated on-line via a full-scale simulator detected and isolate the main faults appearing in the pressurizer of a PWR. (orig.)

Detection of Inter-turn Faults in Five-Phase Permanent Magnet Synchronous Motors

Directory of Open Access Journals (Sweden)

SAAVEDRA, H.

2014-11-01

Full Text Available Five-phase permanent magnet synchronous motors (PMSMs have inherent fault-tolerant capabilities. This paper analyzes the detection of inter-turn short circuit faults in five-phase PMSMs in their early stage, i.e. with only one turn in short circuit by means of the analysis of the stator currents and the zero-sequence voltage component (ZSVC spectra. For this purpose, a parametric model of five-phase PMSMs which accounts for the effects of inter-turn short circuits is developed to determine the most suitable harmonic frequencies to be analyzed to detect such faults. The amplitudes of these fault harmonic are analyzed in detail by means of finite-elements method (FEM simulations, which corroborate the predictions of the parametric model. A low-speed five-phase PMSM for in-wheel applications is studied and modeled. This paper shows that the ZSVC-based method provides better sensitivity to diagnose inter-turn faults in the analyzed low-speed application. Results presented under a wide speed range and different load levels show that it is feasible to diagnose such faults in their early stage, thus allowing applying a post-fault strategy to minimize their effects while ensuring a safe operation.

Wind Turbine Fault Detection based on Artificial Neural Network Analysis of SCADA Data

DEFF Research Database (Denmark)

Herp, Jürgen; S. Nadimi, Esmaeil

2015-01-01

Slowly developing faults in wind turbine can, when not detected and fixed on time, cause severe damage and downtime. We are proposing a fault detection method based on Artificial Neural Networks (ANN) and the recordings from Supervisory Control and Data Acquisition (SCADA) systems installed in wind...

A Novel Protection Method for Single Line-to-Ground Faults in Ungrounded Low-Inertia Microgrids

Directory of Open Access Journals (Sweden)

Liuming Jing

2016-06-01

Full Text Available This paper proposes a novel protection method for single line-to-ground (SLG faults in ungrounded low-inertia microgrids. The proposed method includes microgrid interface protection and unit protection. The microgrid interface protection is based on the difference between the zero-sequence voltage angle and the zero-sequence current angle at the microgrid interconnection transformer for fast selection of the faulty feeder. The microgrid unit protection is based on a comparison of the three zero-sequence current phase directions at each junction point of load or distributed energy resources. Methods are also included to locate the minimum fault section. The fault section location technology operates according to the coordination of microgrid unit protection. The proposed method responds to SLG faults that may occur in both the grid and the microgrid. Simulations of an ungrounded low-inertia microgrid with a relay model were carried out using Power System Computer Aided Design (PSCAD/Electromagnetic Transients including DC (EMTDC.

A rule-based fault detection method for air handling units

Energy Technology Data Exchange (ETDEWEB)

Schein, J.; Bushby, S. T.; Castro, N. S. [National Institute of Standards and Technology, Gaithersburg, MD (United States); House, J. M. [Iowa Energy Center, Ankeny, IA (United States)

2006-07-01

Air handling unit performance assessment rules (APAR) is a fault detection tool that uses a set of expert rules derived from mass and energy balances to detect faults in air handling units (AHUs). Control signals are used to determine the mode of operation of the AHU. A subset of the expert rules which correspond to that mode of operation are then evaluated to determine whether a fault exists. APAR is computationally simple enough that it can be embedded in commercial building automation and control systems and relies only upon the sensor data and control signals that are commonly available in these systems. APAR was tested using data sets collected from a 'hardware-in-the-loop' emulator and from several field sites. APAR was also embedded in commercial AHU controllers and tested in the emulator. (author)

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

Science.gov (United States)

Yim, Keun Soo

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

Online model-based fault detection for grid connected PV systems monitoring

KAUST Repository

Harrou, Fouzi; Sun, Ying; Saidi, Ahmed

2017-01-01

This paper presents an efficient fault detection approach to monitor the direct current (DC) side of photovoltaic (PV) systems. The key contribution of this work is combining both single diode model (SDM) flexibility and the cumulative sum (CUSUM) chart efficiency to detect incipient faults. In fact, unknown electrical parameters of SDM are firstly identified using an efficient heuristic algorithm, named Artificial Bee Colony algorithm. Then, based on the identified parameters, a simulation model is built and validated using a co-simulation between Matlab/Simulink and PSIM. Next, the peak power (Pmpp) residuals of the entire PV array are generated based on both real measured and simulated Pmpp values. Residuals are used as the input for the CUSUM scheme to detect potential faults. We validate the effectiveness of this approach using practical data from an actual 20 MWp grid-connected PV system located in the province of Adrar, Algeria.

Online model-based fault detection for grid connected PV systems monitoring

KAUST Repository

Harrou, Fouzi

2017-12-14

This paper presents an efficient fault detection approach to monitor the direct current (DC) side of photovoltaic (PV) systems. The key contribution of this work is combining both single diode model (SDM) flexibility and the cumulative sum (CUSUM) chart efficiency to detect incipient faults. In fact, unknown electrical parameters of SDM are firstly identified using an efficient heuristic algorithm, named Artificial Bee Colony algorithm. Then, based on the identified parameters, a simulation model is built and validated using a co-simulation between Matlab/Simulink and PSIM. Next, the peak power (Pmpp) residuals of the entire PV array are generated based on both real measured and simulated Pmpp values. Residuals are used as the input for the CUSUM scheme to detect potential faults. We validate the effectiveness of this approach using practical data from an actual 20 MWp grid-connected PV system located in the province of Adrar, Algeria.

Robust fault detection in bond graph framework using interval analysis and Fourier-Motzkin elimination technique

Science.gov (United States)

Jha, Mayank Shekhar; Chatti, Nizar; Declerck, Philippe

2017-09-01

This paper addresses the fault diagnosis problem of uncertain systems in the context of Bond Graph modelling technique. The main objective is to enhance the fault detection step based on Interval valued Analytical Redundancy Relations (named I-ARR) in order to overcome the problems related to false alarms, missed alarms and robustness issues. These I-ARRs are a set of fault indicators that generate the interval bounds called thresholds. A fault is detected once the nominal residuals (point valued part of I-ARRs) exceed the thresholds. However, the existing fault detection method is limited to parametric faults and it presents various limitations with regards to estimation of measurement signal derivatives, to which I-ARRs are sensitive. The novelties and scientific interest of the proposed methodology are: (1) to improve the accuracy of the measurements derivatives estimation by using a dedicated sliding mode differentiator proposed in this work, (2) to suitably integrate the Fourier-Motzkin Elimination (FME) technique within the I-ARRs based diagnosis so that measurements faults can be detected successfully. The latter provides interval bounds over the derivatives which are included in the thresholds. The proposed methodology is studied under various scenarios (parametric and measurement faults) via simulations over a mechatronic torsion bar system.

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

Science.gov (United States)

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

2005-01-01

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

Near Fault Strong Ground Motion Records in the Kathmandu Valley during the 2015 Gorkha Nepal Earthquake

Science.gov (United States)

Takai, N.; Shigefuji, M.; Rajaure, S.; Bijukchhen, S.; Ichiyanagi, M.; Dhital, M. R.; Sasatani, T.

2015-12-01

Kathmandu is the capital of Nepal and is located in the Kathmandu Valley, which is formed by soft lake sediments of Plio-Pleistocene origin. Large earthquakes in the past have caused significant damage as the seismic waves were amplified in the soft sediments. To understand the site effect of the valley structure, we installed continuous recording accelerometers in four different parts of the valley. Four stations were installed along a west-to-east profile of the valley at KTP (Kirtipur; hill top), TVU (Kirtipur; hill side), PTN (Patan) and THM (Thimi). On 25 April 2015, a large interplate earthquake Mw 7.8 occurred in the Himalayan Range of Nepal. The focal area estimated was about 200 km long and 150 km wide, with a large slip area under the Kathmandu Valley where our strong motion observation stations were installed. The strong ground motions were observed during this large damaging earthquake. The maximum horizontal peak ground acceleration at the rock site was 271 cm s-2, and the maximum horizontal peak ground velocity at the sediment sites reached 112 cm s-1. We compared these values with the empirical attenuation formula for strong ground motions. We found the peak accelerations were smaller and the peak velocities were approximately the same as the predicted values. The rock site KTP motions are less affected by site amplification and were analysed further. The horizontal components were rotated to the fault normal (N205E) and fault parallel (N115E) directions using the USGS fault model. The velocity waveforms at KTP showed about 5 s triangular pulses on the N205E and the up-down components; however the N115E component was not a triangular pulse but one cycle sinusoidal wave. The velocity waveforms at KTP were integrated to derive the displacement waveforms. The derived displacements at KTP are characterized by a monotonic step on the N205E normal and up-down components. The displacement waveforms of KTP show permanent displacements of 130 cm in the fault

Detection of Eccentricity Faults in Five-Phase Ferrite-PM Assisted Synchronous Reluctance Machines

Directory of Open Access Journals (Sweden)

Carlos López-Torres

2017-05-01

Full Text Available Air gap eccentricity faults in five-phase ferrite-assisted synchronous reluctance motors (fPMa-SynRMs tend to distort the magnetic flux in the air gap, which in turn affects the spectral content of both the stator currents and the ZSVC (zero-sequence voltage component. However, there is a lack of research dealing with the topic of fault diagnosis in multi-phase PMa-SynRMs, and in particular, those focused on detecting eccentricity faults. An analysis of the spectral components of the line currents and the ZSVC allows the development of fault diagnosis algorithms to detect eccentricity faults. The effect of the operating conditions is also analyzed, since this paper shows that it has a non-negligible impact on the effectivity and sensitivity of the diagnosis based on an analysis of the stator currents and the ZSVC. To this end, different operating conditions are analyzed. The paper also evaluates the influence of the operating conditions on the harmonic content of the line currents and the ZSVC, and determines the most suitable operating conditions to enhance the sensitivity of the analyzed methods. Finally, fault indicators employed to detect eccentricity faults, which are based on the spectral content of the stator currents and the ZSVC, are derived and their performance is assessed. The approach presented in this work may be useful for developing fault diagnosis strategies based on the acquisition and subsequent analysis and interpretation of the spectral content of the line currents and the ZSVC.

Closed-loop fault detection for full-envelope flight vehicle with measurement delays

Directory of Open Access Journals (Sweden)

Wang Zhaolei

2015-06-01

Full Text Available A closed-loop fault detection problem is investigated for the full-envelope flight vehicle with measurement delays, where the flight dynamics are modeled as a switched system with delayed feedback signals. The mode-dependent observer-based fault detection filters and state estimation feedback controllers are derived by considering the delays’ impact on the control system and fault detection system simultaneously. Then, considering updating lags of the controllers/filters’ switching signals which are introduced by the delayed measurement of altitude and Mach number, an asynchronous H∞ analysis method is proposed and the system model is further augmented to be an asynchronously switched time-delay system. Also, the global stability and desired performance of the augmented system are guaranteed by combining the switched delay-dependent Lyapunov–Krasovskii functional method with the average dwell time method (ADT, and the delay-dependent existing conditions for the controllers and fault detection filters are obtained in the form of the linear matrix inequalities (LMIs. Finally, numerical example based on the hypersonic vehicles and highly maneuverable technology (HiMAT vehicle is given to demonstrate the merits of the proposed method.

Verification of a Novel Method of Detecting Faults in Medium-Voltage Systems with Covered Conductors

Directory of Open Access Journals (Sweden)

Mišák Stanislav

2017-06-01

Full Text Available This paper describes the use of new methods of detecting faults in medium-voltage overhead lines built of covered conductors. The methods mainly address such faults as falling of a conductor, contacting a conductor with a tree branch, or falling a tree branch across three phases of a medium-voltage conductor. These faults cannot be detected by current digital relay protection systems. Therefore, a new system that can detect the above mentioned faults was developed. After having tested its operation, the system has already been implemented to protect mediumvoltage overhead lines built of covered conductors.

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

Science.gov (United States)

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

2015-10-09

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

Process for detecting leak faults using a helium mass spectrometer

International Nuclear Information System (INIS)

Divet, Claude; Morin, Claude.

1977-01-01

The description is given of a process for detecting very small leak faults putting into communication the outer and inner sides of the wall of a containment, one of these wall sides being in contact with gaseous helium under a pressure of around one torr, the other side being one of the limits of a space pumped down to a residual gas pressure under 10 -3 torr. This space is in communication with the measuring cell of a helium mass spectrometer. This process may be applied to the detection of faults in metal claddings of the fuel rods used in nuclear reactors [fr

Application of D-S Evidence Fusion Method in the Fault Detection of Temperature Sensor

Directory of Open Access Journals (Sweden)

Zheng Dou

2014-01-01

Full Text Available Due to the complexity and dangerousness of drying process, the fault detection of temperature sensor is very difficult and dangerous in actual working practice and the detection effectiveness is not satisfying. For this problem, in this paper, based on the idea of information fusion and the requirements of D-S evidence method, a D-S evidence fusion structure with two layers was introduced to detect the temperature sensor fault in drying process. The first layer was data layer to establish the basic belief assignment function of evidence which could be realized by BP Neural Network. The second layer was decision layer to detect and locate the sensor fault which could be realized by D-S evidence fusion method. According to the numerical simulation results, the working conditions of sensors could be described effectively and accurately by this method, so that it could be used to detect and locate the sensor fault.

High Frequency Near-Field Ground Motion Excited by Strike-Slip Step Overs

Science.gov (United States)

Hu, Feng; Wen, Jian; Chen, Xiaofei

2018-03-01

We performed dynamic rupture simulations on step overs with 1-2 km step widths and present their corresponding horizontal peak ground velocity distributions in the near field within different frequency ranges. The rupture speeds on fault segments are determinant in controlling the near-field ground motion. A Mach wave impact area at the free surface, which can be inferred from the distribution of the ratio of the maximum fault-strike particle velocity to the maximum fault-normal particle velocity, is generated in the near field with sustained supershear ruptures on fault segments, and the Mach wave impact area cannot be detected with unsustained supershear ruptures alone. Sub-Rayleigh ruptures produce stronger ground motions beyond the end of fault segments. The existence of a low-velocity layer close to the free surface generates large amounts of high-frequency seismic radiation at step over discontinuities. For near-vertical step overs, normal stress perturbations on the primary fault caused by dipping structures affect the rupture speed transition, which further determines the distribution of the near-field ground motion. The presence of an extensional linking fault enhances the near-field ground motion in the extensional regime. This work helps us understand the characteristics of high-frequency seismic radiation in the vicinities of step overs and provides useful insights for interpreting the rupture speed distributions derived from the characteristics of near-field ground motion.

Hazard-to-Risk: High-Performance Computing Simulations of Large Earthquake Ground Motions and Building Damage in the Near-Fault Region

Science.gov (United States)

Miah, M.; Rodgers, A. J.; McCallen, D.; Petersson, N. A.; Pitarka, A.

2017-12-01

We are running high-performance computing (HPC) simulations of ground motions for large (magnitude, M=6.5-7.0) earthquakes in the near-fault region (steel moment frame buildings throughout the near-fault domain. For ground motions, we are using SW4, a fourth order summation-by-parts finite difference time-domain code running on 10,000-100,000's of cores. Earthquake ruptures are generated using the Graves and Pitarka (2017) method. We validated ground motion intensity measurements against Ground Motion Prediction Equations. We considered two events (M=6.5 and 7.0) for vertical strike-slip ruptures with three-dimensional (3D) basin structures, including stochastic heterogeneity. We have also considered M7.0 scenarios for a Hayward Fault rupture scenario which effects the San Francisco Bay Area and northern California using both 1D and 3D earth structure. Dynamic, inelastic response of canonical buildings is computed with the NEVADA, a nonlinear, finite-deformation finite element code. Canonical buildings include 3-, 9-, 20- and 40-story steel moment frame buildings. Damage potential is tracked by the peak inter-story drift (PID) ratio, which measures the maximum displacement between adjacent floors of the building and is strongly correlated with damage. PID ratios greater 1.0 generally indicate non-linear response and permanent deformation of the structure. We also track roof displacement to identify permanent deformation. PID (damage) for a given earthquake scenario (M, slip distribution, hypocenter) is spatially mapped throughout the SW4 domain with 1-2 km resolution. Results show that in the near fault region building damage is correlated with peak ground velocity (PGV), while farther away (> 20 km) it is better correlated with peak ground acceleration (PGA). We also show how simulated ground motions have peaks in the response spectra that shift to longer periods for larger magnitude events and for locations of forward directivity, as has been reported by

Back analysis of fault-slip in burst prone environment

Science.gov (United States)

Sainoki, Atsushi; Mitri, Hani S.

2016-11-01

In deep underground mines, stress re-distribution induced by mining activities could cause fault-slip. Seismic waves arising from fault-slip occasionally induce rock ejection when hitting the boundary of mine openings, and as a result, severe damage could be inflicted. In general, it is difficult to estimate fault-slip-induced ground motion in the vicinity of mine openings because of the complexity of the dynamic response of faults and the presence of geological structures. In this paper, a case study is conducted for a Canadian underground mine, herein called "Mine-A", which is known for its seismic activities. Using a microseismic database collected from the mine, a back analysis of fault-slip is carried out with mine-wide 3-dimensional numerical modeling. A back analysis is conducted to estimate the physical and mechanical properties of the causative fracture or shear zones. One large seismic event has been selected for the back analysis to detect a fault-slip related seismic event. In the back analysis, the shear zone properties are estimated with respect to moment magnitude of the seismic event and peak particle velocity (PPV) recorded by a strong ground motion sensor. The estimated properties are then validated through comparison with peak ground acceleration recorded by accelerometers. Lastly, ground motion in active mining areas is estimated by conducting dynamic analysis with the estimated values. The present study implies that it would be possible to estimate the magnitude of seismic events that might occur in the near future by applying the estimated properties to the numerical model. Although the case study is conducted for a specific mine, the developed methodology can be equally applied to other mines suffering from fault-slip related seismic events.

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

Science.gov (United States)

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

2017-11-01

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

Power plant surveillance and fault detection: applications to a commercial PWR

International Nuclear Information System (INIS)

Singer, R.M.; Gross, K.C.; Herzog, J.P.; Wegerich, S.; Van Alstine, R.; Bockhorst, F.K.

1998-01-01

The theoretical basis and validation studies of a real-time, model-based process monitoring and fault detection system (MSET, multivariate state estimation technique) 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 an experimental fast reactor and a commercial LWR are used to demonstrate functional capabilities of the monitoring system. In addition, operational data from the Crystal River-3 (CR-3) nuclear power plant are used to illustrate the high sensitivity, accuracy, and the rapid response time of MSET for annunciation of variety signal disturbances. The types of faults detected and identified included the gradual degradation of a venturi flowmeter, rapidly failing flow sensor and the loss-of-time-response of a pressure transmitter. (author)

An application of LTR design in fault detection

DEFF Research Database (Denmark)

Niemann, Hans Henrik

1998-01-01

The fault detection and isolation (FDI) problem is considered in this paper. The FDI problem is formulated as a filter design problem, where the faults in the system is estimated and the disturbance acting on the system is rejected. It turns out that the filter design problem can be considered...... as a standard Loop Transfer Recovery (LTR) design problem. As a consequence of the connection between LTR and FDI design, it is shown in an example how the LQG/LTR design method for full order and a proportional-integral observer can be applied with advantages in connection with FDI....

Fault detection of a spur gear using vibration signal with multivariable statistical parameters

Directory of Open Access Journals (Sweden)

Songpon Klinchaeam

2014-10-01

Full Text Available This paper presents a condition monitoring technique of a spur gear fault detection using vibration signal analysis based on time domain. Vibration signals were acquired from gearboxes and used to simulate various faults on spur gear tooth. In this study, vibration signals were applied to monitor a normal and various fault conditions of a spur gear such as normal, scuffing defect, crack defect and broken tooth. The statistical parameters of vibration signal were used to compare and evaluate the value of fault condition. This technique can be applied to set alarm limit of the signal condition based on statistical parameter such as variance, kurtosis, rms and crest factor. These parameters can be used to set as a boundary decision of signal condition. From the results, the vibration signal analysis with single statistical parameter is unclear to predict fault of the spur gears. The using at least two statistical parameters can be clearly used to separate in every case of fault detection. The boundary decision of statistical parameter with the 99.7% certainty ( 3   from 300 referenced dataset and detected the testing condition with 99.7% ( 3   accuracy and had an error of less than 0.3 % using 50 testing dataset.

Fault Detection and Location of IGBT Short-Circuit Failure in Modular Multilevel Converters

Directory of Open Access Journals (Sweden)

Bin Jiang

2018-06-01

Full Text Available A single fault detection and location for Modular Multilevel Converter (MMC is of great significance, as numbers of sub-modules (SMs in MMC are connected in series. In this paper, a novel fault detection and location method is proposed for MMC in terms of the Insulated Gate Bipolar Translator (IGBT short-circuit failure in SM. The characteristics of IGBT short-circuit failures are analyzed, based on which a Differential Comparison Low-Voltage Detection Method (DCLVDM is proposed to detect the short-circuit fault. Lastly, the faulty IGBT is located based on the capacitor voltage of the faulty SM by Continuous Wavelet Transform (CWT. Simulations have been done in the simulation software PSCAD/EMTDC and the results confirm the validity and reliability of the proposed method.

Robust fault detection for the dynamics of high-speed train with multi-source finite frequency interference.

Science.gov (United States)

Bai, Weiqi; Dong, Hairong; Yao, Xiuming; Ning, Bin

2018-04-01

This paper proposes a composite fault detection scheme for the dynamics of high-speed train (HST), using an unknown input observer-like (UIO-like) fault detection filter, in the presence of wind gust and operating noises which are modeled as disturbance generated by exogenous system and unknown multi-source disturbance within finite frequency domain. Using system input and system output measurements, the fault detection filter is designed to generate the needed residual signals. In order to decouple disturbance from residual signals without truncating the influence of faults, this paper proposes a method to partition the disturbance into two parts. One subset of the disturbance does not appear in residual dynamics, and the influence of the other subset is constrained by H ∞ performance index in a finite frequency domain. A set of detection subspaces are defined, and every different fault is assigned to its own detection subspace to guarantee the residual signals are diagonally affected promptly by the faults. Simulations are conducted to demonstrate the effectiveness and merits of the proposed method. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Impact of SSSC on Measured Impedance in Single Phase to Ground Fault Condition on 220 kV Transmission Line

Directory of Open Access Journals (Sweden)

Mohamed ZELLAGUI

2012-08-01

Full Text Available This paper presents and compares the impact of SSSC on measured impedance for single phase to ground fault condition. The presence of Static Synchronous SSSC on a transmission line has a great influence on the ZRelay in distance protection. The protection of the high voltage 220 kV single circuit transmission line in eastern Algerian electrical transmission networks is affected in the case with resistance fault RF. The paper investigate the effect of Static Synchronous Series Compensator (SSSC on the measured impedance (Relay taking into account the distance fault point (n and fault resistance (RF. The resultants simulation is performed in MATLAB software environment.

Adapting plant measurement data to improve hardware fault detection performance in pressurised water reactors

International Nuclear Information System (INIS)

Cilliers, A.C.; Mulder, E.J.

2012-01-01

Highlights: ► Attempt was to use available resources at a nuclear plant in a value added fashion. ► Includes plant measurement data and plant training and engineering simulator capabilities. ► Solving the fault masking effect by the distributed control systems in the plant. ► Modelling the effect of inaccuracies in plant models used in the simulators. ► Combination of above resulted in the development of a deterministic fault identifications system. -- Abstract: With the fairly recent adoption of digital control and instrumentation systems in the nuclear industry a lot of research now focus on the development expert fault identification systems. The fault identification systems enable detecting early onset faults of fault causes which allows maintenance planning on the equipment showing signs of deterioration or failure. This includes valve and leaks and small cracks in steam generator tubes usually detected by means of ultrasonic inspection. Detecting faults early during transient operation in NPPs is problematic due to the absence of a reliable reference to compare plant measurements with during transients. The distributed application of control systems operating independently to keep the plant operating within the safe operating boundaries complicates the problem since the control systems would not only operate to reduce the effect of transient disturbances but fault disturbances as well. This paper provides a method to adapt the plant measurements that isolates the control actions on the fault and re-introduces it into the measurement data, thereby improving plant diagnostic performance.

Reclosing operation characteristics of the flux-coupling type SFCL in a single-line-to ground fault

International Nuclear Information System (INIS)

Jung, B.I.; Cho, Y.S.; Choi, H.S.; Ha, K.H.; Choi, S.G.; Chul, D.C.; Sung, T.H.

2011-01-01

The recloser that is used in distribution systems is a relay system that behaves sequentially to protect power systems from transient and continuous faults. This reclosing operation of the recloser can improve the reliability and stability of the power supply. For cooperation with this recloser, the superconducting fault current limiter (SFCL) must properly perform the reclosing operation. This paper analyzed the reclosing operation characteristics of the three-phase flux-coupling type SFCL in the event of a ground fault. The fault current limiting characteristics according to the changing number of turns of the primary and secondary coils were examined. As the number of turns of the first coil increased, the first maximum fault current decreased. Furthermore, the voltage of the quenched superconducting element also decreased. This means that the power burden of the superconducting element decreases based on the increasing number of turns of the primary coil. The fault current limiting characteristic of the SFCL according to the reclosing time limited the fault current within a 0.5 cycles (8 ms), which is shorter than the closing time of the recloser. In other words, the superconducting element returned to the superconducting state before the second fault and normally performed the fault current limiting operation. If the SFCL did not recover before the recloser reclosing time, the normal current that was flowing in the transmission line after the recovery of the SFCL from the fault would have been limited and would have caused losses. Therefore, the fast recovery time of a SFCL is critical to its cooperation with the protection system.

Reclosing operation characteristics of the flux-coupling type SFCL in a single-line-to ground fault

Science.gov (United States)

Jung, B. I.; Cho, Y. S.; Choi, H. S.; Ha, K. H.; Choi, S. G.; Chul, D. C.; Sung, T. H.

2011-11-01

The recloser that is used in distribution systems is a relay system that behaves sequentially to protect power systems from transient and continuous faults. This reclosing operation of the recloser can improve the reliability and stability of the power supply. For cooperation with this recloser, the superconducting fault current limiter (SFCL) must properly perform the reclosing operation. This paper analyzed the reclosing operation characteristics of the three-phase flux-coupling type SFCL in the event of a ground fault. The fault current limiting characteristics according to the changing number of turns of the primary and secondary coils were examined. As the number of turns of the first coil increased, the first maximum fault current decreased. Furthermore, the voltage of the quenched superconducting element also decreased. This means that the power burden of the superconducting element decreases based on the increasing number of turns of the primary coil. The fault current limiting characteristic of the SFCL according to the reclosing time limited the fault current within a 0.5 cycles (8 ms), which is shorter than the closing time of the recloser. In other words, the superconducting element returned to the superconducting state before the second fault and normally performed the fault current limiting operation. If the SFCL did not recover before the recloser reclosing time, the normal current that was flowing in the transmission line after the recovery of the SFCL from the fault would have been limited and would have caused losses. Therefore, the fast recovery time of a SFCL is critical to its cooperation with the protection system.

STEM - software test and evaluation methods: fault detection using static analysis techniques

International Nuclear Information System (INIS)

Bishop, P.G.; Esp, D.G.

1988-08-01

STEM is a software reliability project with the objective of evaluating a number of fault detection and fault estimation methods which can be applied to high integrity software. This Report gives some interim results of applying both manual and computer-based static analysis techniques, in particular SPADE, to an early CERL version of the PODS software containing known faults. The main results of this study are that: The scope for thorough verification is determined by the quality of the design documentation; documentation defects become especially apparent when verification is attempted. For well-defined software, the thoroughness of SPADE-assisted verification for detecting a large class of faults was successfully demonstrated. For imprecisely-defined software (not recommended for high-integrity systems) the use of tools such as SPADE is difficult and inappropriate. Analysis and verification tools are helpful, through their reliability and thoroughness. However, they are designed to assist, not replace, a human in validating software. Manual inspection can still reveal errors (such as errors in specification and errors of transcription of systems constants) which current tools cannot detect. There is a need for tools to automatically detect typographical errors in system constants, for example by reporting outliers to patterns. To obtain the maximum benefit from advanced tools, they should be applied during software development (when verification problems can be detected and corrected) rather than retrospectively. (author)

Fault Detection of Reciprocating Compressors using a Model from Principles Component Analysis of Vibrations

International Nuclear Information System (INIS)

Ahmed, M; Gu, F; Ball, A D

2012-01-01

Traditional vibration monitoring techniques have found it difficult to determine a set of effective diagnostic features due to the high complexity of the vibration signals originating from the many different impact sources and wide ranges of practical operating conditions. In this paper Principal Component Analysis (PCA) is used for selecting vibration feature and detecting different faults in a reciprocating compressor. Vibration datasets were collected from the compressor under baseline condition and five common faults: valve leakage, inter-cooler leakage, suction valve leakage, loose drive belt combined with intercooler leakage and belt loose drive belt combined with suction valve leakage. A model using five PCs has been developed using the baseline data sets and the presence of faults can be detected by comparing the T 2 and Q values from the features of fault vibration signals with corresponding thresholds developed from baseline data. However, the Q -statistic procedure produces a better detection as it can separate the five faults completely.

A measurement-based fault detection approach applied to monitor robots swarm

KAUST Repository

Khaldi, Belkacem

2017-07-10

Swarm robotics requires continuous monitoring to detect abnormal events and to sustain normal operations. Indeed, swarm robotics with one or more faulty robots leads to degradation of performances complying with the target requirements. This paper present an innovative data-driven fault detection method for monitoring robots swarm. The method combines the flexibility of principal component analysis (PCA) models and the greater sensitivity of the exponentially-weighted moving average control chart to incipient changes. We illustrate through simulated data collected from the ARGoS simulator that a significant improvement in fault detection can be obtained by using the proposed methods as compared to the use of the conventional PCA-based methods.

Improved nonlinear fault detection strategy based on the Hellinger distance metric: Plug flow reactor monitoring

KAUST Repository

Harrou, Fouzi

2017-03-18

Fault detection has a vital role in the process industry to enhance productivity, efficiency, and safety, and to avoid expensive maintenance. This paper proposes an innovative multivariate fault detection method that can be used for monitoring nonlinear processes. The proposed method merges advantages of nonlinear projection to latent structures (NLPLS) modeling and those of Hellinger distance (HD) metric to identify abnormal changes in highly correlated multivariate data. Specifically, the HD is used to quantify the dissimilarity between current NLPLS-based residual and reference probability distributions obtained using fault-free data. Furthermore, to enhance further the robustness of these methods to measurement noise, and reduce the false alarms due to modeling errors, wavelet-based multiscale filtering of residuals is used before the application of the HD-based monitoring scheme. The performances of the developed NLPLS-HD fault detection technique is illustrated using simulated plug flow reactor data. The results show that the proposed method provides favorable performance for detection of faults compared to the conventional NLPLS method.

Detection of ''beading faults'' in welded tubes

International Nuclear Information System (INIS)

Mondot, J.

In the steel tube industry the word ''beading'' refers to a highly localised leak affecting the welded zone. During the pneumatic test its flow rate is generally very low no more than a few thousandths of a mm 3 /second. Detection of such a fault by this test is consequently slow, and those which are choked or at the limit of leakage may escape detection. For greater safety, the tube technician is now using non-destructive testing methods such as eddy-currents and ultrasonics [fr

Ground-Penetrating Radar Investigations along Hajipur Fault: Himalayan Frontal Thrust—Attempt to Identify Near Subsurface Displacement, NW Himalaya, India

Directory of Open Access Journals (Sweden)

Javed N. Malik

2012-01-01

Full Text Available The study area falls in the mesoseismal zone of 1905 Kangra earthquake (Mw 7.8. To identify appropriate trenching site for paleoseismic investigation and to understand the faulting geometry, ground-penetrating radar (GPR survey was conducted across a Hajipur Fault (HF2 scarp, a branching out fault of Himalayan Frontal Thrust (HFT in a foot hill zone of NW Himalaya. Several 2D and 3D profiles were collected using 200 MHz antenna with SIR 3000 unit. A 2D GPR profile collected across the HF2 scarp revealed prominent hyperbolas and discontinuous-warped reflections, suggesting a metal pipe and a zone of deformation along a low-angle thrust fault, respectively. The 3D profile revealed remarkable variation in dip of the fault plane and pattern of deformation along the strike of the fault.

Near-Fault Broadband Ground Motion Simulations Using Empirical Green's Functions: Application to the Upper Rhine Graben (France-Germany) Case Study

Science.gov (United States)

Del Gaudio, Sergio; Hok, Sebastien; Festa, Gaetano; Causse, Mathieu; Lancieri, Maria

2017-09-01

Seismic hazard estimation relies classically on data-based ground motion prediction equations (GMPEs) giving the expected motion level as a function of several parameters characterizing the source and the sites of interest. However, records of moderate to large earthquakes at short distances from the faults are still rare. For this reason, it is difficult to obtain a reliable ground motion prediction for such a class of events and distances where also the largest amount of damage is usually observed. A possible strategy to fill this lack of information is to generate synthetic accelerograms based on an accurate modeling of both extended fault rupture and wave propagation process. The development of such modeling strategies is essential for estimating seismic hazard close to faults in moderate seismic activity zones, where data are even scarcer. For that reason, we selected a target site in Upper Rhine Graben (URG), at the French-German border. URG is a region where faults producing micro-seismic activity are very close to the sites of interest (e.g., critical infrastructures like supply lines, nuclear power plants, etc.) needing a careful investigation of seismic hazard. In this work, we demonstrate the feasibility of performing near-fault broadband ground motion numerical simulations in a moderate seismic activity region such as URG and discuss some of the challenges related to such an application. The modeling strategy is to couple the multi-empirical Green's function technique (multi-EGFt) with a k -2 kinematic source model. One of the advantages of the multi-EGFt is that it does not require a detailed knowledge of the propagation medium since the records of small events are used as the medium transfer function, if, at the target site, records of small earthquakes located on the target fault are available. The selection of suitable events to be used as multi-EGF is detailed and discussed in our specific situation where less number of events are available. We

Faults in the Collection Grid of Offshore Wind Farms

DEFF Research Database (Denmark)

Lunow, Morten Erlandsson; Holbøll, Joachim; Henriksen, Mogens

2008-01-01

This paper deals with transient conditions in the collection grid of offshore wind farms under different faults. A model of a standard wind farm was established in two versions, with a floating and a grounded collection grid respectively. Line to ground faults and three-phase to ground faults were...... applied at critical points at worst-case phase angle and the results compared. The simulations show that it is better with a grounded collection grid, since lack of a ground reference will prevent the system from recovering after a line to ground fault....

Evaluation of influence of splay fault growth on groundwater flow around geological disposal system

International Nuclear Information System (INIS)

Takai, Shizuka; Takeda, Seiji; Sakai, Ryutaro; Shimada, Taro; Munakata, Masahiro; Tanaka, Tadao

2017-01-01

In geological disposal, the direct effect of active faults on geological repositories is avoided at the stage of site characterization, however, uncertainty remains for the avoidance of faults derived from active faults, which are concealed deep under the ground and are difficult to detect by site investigation. In this research, the influence of the growth of undetected splay faults on a natural barrier in a geological disposal system due to the future action of faults was evaluated. We investigated examples of splay faults in Japan and set conditions for the growth of splay faults. Furthermore, we assumed a disposal site composed of sedimentary rock and made a hydrogeological model of the growth of splay faults. We carried out groundwater flow analyses, changing parameters such as the location and depth of the repository and the growth velocity of splay faults. We carried out groundwater flow analyses, changing parameters such as the location and depth of the repository and the growth velocity of splay faults. The results indicate that the main flow path from the repository is changed into an upward flow along the splay fault due to its growth and that the average velocity to the ground surface becomes one or two orders of magnitude higher than that before its growth. The results also suggest that splay fault growth leads to the possibility of the downward flow of oxidizing groundwater from the ground surface area. (author)

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

Science.gov (United States)

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

2015-01-01

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

Pros and cons of rotating ground motion records to fault-normal/parallel directions for response history analysis of buildings

Science.gov (United States)

Kalkan, Erol; Kwong, Neal S.

2014-01-01

According to the regulatory building codes in the United States (e.g., 2010 California Building Code), at least two horizontal ground motion components are required for three-dimensional (3D) response history analysis (RHA) of building structures. For sites within 5 km of an active fault, these records should be rotated to fault-normal/fault-parallel (FN/FP) directions, and two RHAs should be performed separately (when FN and then FP are aligned with the transverse direction of the structural axes). It is assumed that this approach will lead to two sets of responses that envelope the range of possible responses over all nonredundant rotation angles. This assumption is examined here, for the first time, using a 3D computer model of a six-story reinforced-concrete instrumented building subjected to an ensemble of bidirectional near-fault ground motions. Peak values of engineering demand parameters (EDPs) were computed for rotation angles ranging from 0 through 180° to quantify the difference between peak values of EDPs over all rotation angles and those due to FN/FP direction rotated motions. It is demonstrated that rotating ground motions to FN/FP directions (1) does not always lead to the maximum responses over all angles, (2) does not always envelope the range of possible responses, and (3) does not provide maximum responses for all EDPs simultaneously even if it provides a maximum response for a specific EDP.

Detection of Naturally Occurring Gear and Bearing Faults in a Helicopter Drivetrain

Science.gov (United States)

2014-01-01

Detection of Naturally Occurring Gear and Bearing Faults in a Helicopter Drivetrain by Kelsen E. LaBerge, Eric C. Ames, and Brian D. Dykas...5066 ARL-TR-6795 January 2014 Detection of Naturally Occurring Gear and Bearing Faults in a Helicopter Drivetrain Kelsen E. LaBerge...ELEMENT NUMBER 6. AUTHOR(S) Kelsen E. LaBerge, Eric C. Ames, and Brian D. Dykas 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER

An Ensemble of HMMs for Cognitive Fault Detection in Distributed Sensor Networks

OpenAIRE

Roveri , Manuel; Trovò , Francesco

2014-01-01

Part 3: Social Media and Mobile Applications of AI; International audience; Distributed sensor networks working in harsh environmental conditions can suffer from permanent or transient faults affecting the embedded electronics or the sensors. Fault Diagnosis Systems (FDSs) have been widely studied in the literature to detect, isolate, identify, and possibly accommodate faults. Recently introduced cognitive FDSs, which represent a novel generation of FDSs, are characterized by the capability t...

Fault detection of sensors in nuclear reactors using self-organizing maps

Energy Technology Data Exchange (ETDEWEB)

Barbosa, Paulo Roberto; Tiago, Graziela Marchi [Instituto Federal de Educacao, Ciencia e Tecnologia de Sao Paulo (IFSP), Sao Paulo, SP (Brazil); Bueno, Elaine Inacio [Instituto Federal de Educacao, Ciencia e Tecnologia de Sao Paulo (IFSP), Guarulhos, SP (Brazil); Pereira, Iraci Martinez, E-mail: martinez@ipen.b [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

2011-07-01

In this work a Fault Detection System was developed based on the self-organizing maps methodology. This method was applied to the IEA-R1 research reactor at IPEN using a database generated by a theoretical model of the reactor. The IEA-R1 research reactor is a pool type reactor of 5 MW, cooled and moderated by light water, and uses graphite and beryllium as reflector. The theoretical model was developed using the Matlab Guide toolbox. The equations are based in the IEA-R1 mass and energy inventory balance and physical as well as operational aspects are taken into consideration. In order to test the model ability for fault detection, faults were artificially produced. As the value of the maximum calibration error for special thermocouples is +- 0.5 deg C, it had been inserted faults in the sensor signals with the purpose to produce the database considered in this work. The results show a high percentage of correct classification, encouraging the use of the technique for this type of industrial application. (author)

Fault detection of sensors in nuclear reactors using self-organizing maps

International Nuclear Information System (INIS)

Barbosa, Paulo Roberto; Tiago, Graziela Marchi; Bueno, Elaine Inacio; Pereira, Iraci Martinez

2011-01-01

In this work a Fault Detection System was developed based on the self-organizing maps methodology. This method was applied to the IEA-R1 research reactor at IPEN using a database generated by a theoretical model of the reactor. The IEA-R1 research reactor is a pool type reactor of 5 MW, cooled and moderated by light water, and uses graphite and beryllium as reflector. The theoretical model was developed using the Matlab Guide toolbox. The equations are based in the IEA-R1 mass and energy inventory balance and physical as well as operational aspects are taken into consideration. In order to test the model ability for fault detection, faults were artificially produced. As the value of the maximum calibration error for special thermocouples is +- 0.5 deg C, it had been inserted faults in the sensor signals with the purpose to produce the database considered in this work. The results show a high percentage of correct classification, encouraging the use of the technique for this type of industrial application. (author)

A method for detection and location of high resistance earth faults

Energy Technology Data Exchange (ETDEWEB)

Haenninen, S; Lehtonen, M [VTT Energy, Espoo (Finland); Antila, E [ABB Transmit Oy (Finland)

1998-08-01

In the first part of this presentation, the theory of earth faults in unearthed and compensated power systems is briefly presented. The main factors affecting the high resistance fault detection are outlined and common practices for earth fault protection in present systems are summarized. The algorithms of the new method for high resistance fault detection and location are then presented. These are based on the change of neutral voltage and zero sequence currents, measured at the high voltage / medium voltage substation and also at the distribution line locations. The performance of the method is analyzed, and the possible error sources discussed. Among these are, for instance, switching actions, thunder storms and heavy snow fall. The feasibility of the method is then verified by an analysis based both on simulated data, which was derived using an EMTP-ATP simulator, and by real system data recorded during field tests at three substations. For the error source analysis, some real case data recorded during natural power system events, is also used

Improved nonlinear fault detection strategy based on the Hellinger distance metric: Plug flow reactor monitoring

KAUST Repository

Harrou, Fouzi; Madakyaru, Muddu; Sun, Ying

2017-01-01

Fault detection has a vital role in the process industry to enhance productivity, efficiency, and safety, and to avoid expensive maintenance. This paper proposes an innovative multivariate fault detection method that can be used for monitoring

Similarity ratio analysis for early stage fault detection with optical emission spectrometer in plasma etching process.

Directory of Open Access Journals (Sweden)

Jie Yang

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

Fault Detection and Isolation and Fault Tolerant Control of Wind Turbines Using Set-Valued Observers

DEFF Research Database (Denmark)

Casau, Pedro; Rosa, Paulo Andre Nobre; Tabatabaeipour, Seyed Mojtaba

2012-01-01

Research on wind turbine Operations & Maintenance (O&M) procedures is critical to the expansion of Wind Energy Conversion systems (WEC). In order to reduce O&M costs and increase the lifespan of the turbine, we study the application of Set-Valued Observers (SVO) to the problem of Fault Detection...... and Isolation (FDI) and Fault Tolerant Control (FTC) of wind turbines, by taking advantage of the recent advances in SVO theory for model invalidation. A simple wind turbine model is presented along with possible faulty scenarios. The FDI algorithm is built on top of the described model, taking into account...

Experimental Investigation for RUAV's Actuator Fault Detections with AESMF

Directory of Open Access Journals (Sweden)

Dalei Song

2015-07-01

Full Text Available The adaptive extended set-membership filter (AESMF algorithm for robots' online modelling is today proposed for use in this field. Compared to the traditional ESMF, this novel filter method improves estimation accuracy under variable boundaries of unknown but bounded (UBB process noise, which is often caused by the uncertainties of robotic dynamics. However, the applicability and stability of the AESMF method have not been tested in detail or demonstrated for real robotic systems. In this research, AESMF is applied for the actuator fault detections of a rotor-craft unmanned air vehicle (RUAV. The stability of AESMF is firstly analysed using mathematics and actuator healthy coefficients (AHC are introduced for building the actuator failure model of RUAVs. AESMF is employed for the online boundary estimation of flight states and AHC parameters for fault tolerance control. Based on the proposed AESMF actuator fault estimation, flight experiments are conducted using a ServoHeli-40 RUAV platform and the flight results are compared with traditional ESMF and the adaptive extended Kalman filter (AEKF in order to demonstrate its effectiveness, as well as for suggesting improvements for the actuator failure detection of RUAVs.

Fault Detection for Non-Gaussian Stochastic Systems with Time-Varying Delay

Directory of Open Access Journals (Sweden)

Tao Li

2013-01-01

Full Text Available Fault detection (FD for non-Gaussian stochastic systems with time-varying delay is studied. The available information for the addressed problem is the input and the measured output probability density functions (PDFs of the system. In this framework, firstly, by constructing an augmented Lyapunov functional, which involves some slack variables and a tuning parameter, a delay-dependent condition for the existence of FD observer is derived in terms of linear matrix inequality (LMI and the fault can be detected through a threshold. Secondly, in order to improve the detection sensitivity performance, the optimal algorithm is applied to minimize the threshold value. Finally, paper-making process example is given to demonstrate the applicability of the proposed approach.

Hall Sensor Output Signal Fault-Detection & Safety Implementation Logic

Directory of Open Access Journals (Sweden)

Lee SangHun

2016-01-01

Full Text Available Recently BLDC motors have been popular in various industrial applications and electric mobility. Recently BLDC motors have been popular in various industrial applications and electric mobility. In most brushless direct current (BLDC motor drives, there are three hall sensors as a position reference. Low resolution hall effect sensor is popularly used to estimate the rotor position because of its good comprehensive performance such as low cost, high reliability and sufficient precision. Various possible faults may happen in a hall effect sensor. This paper presents a fault-tolerant operation method that allows the control of a BLDC motor with one faulty hall sensor and presents the hall sensor output fault-tolerant control strategy. The situations considered are when the output from a hall sensor stays continuously at low or high levels, or a short-time pulse appears on a hall sensor signal. For fault detection, identification of a faulty signal and generating a substitute signal, this method only needs the information from the hall sensors. There are a few research work on hall effect sensor failure of BLDC motor. The conventional fault diagnosis methods are signal analysis, model based analysis and knowledge based analysis. The proposed method is signal based analysis using a compensation signal for reconfiguration and therefore fault diagnosis can be fast. The proposed method is validated to execute the simulation using PSIM.

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

OpenAIRE

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

2017-01-01

The use of Unmanned Aerial Vehicles (UAVs) has increased significantly in recent years. On-board integrated navigation sensors are a key component of UAVs’ flight control systems and are essential for flight safety. In order to ensure flight safety, timely and effective navigation sensor fault detection capability is required. In this paper, a novel data-driven Adaptive Neuron Fuzzy Inference System (ANFIS)-based approach is presented for the detection of on-board navigation sensor faults in ...

Fault Detection and Diagnosis System in Process industry Based on Big Data and WeChat

Directory of Open Access Journals (Sweden)

Sun Zengqiang

2017-01-01

Full Text Available The fault detection and diagnosis information in process industry can be received, anytime and anywhere, based on bigdata and WeChat with mobile phone, which got rid of constraints that can only check Distributed Control System (DCS in the central control room or look over in office. Then, fault detection, diagnosis information sharing can be provided, and what’s more, fault detection alarm range, code and inform time can be personalized. The pressure of managers who worked on process industry can be release with the mobile information system.

Orion GN&C Fault Management System Verification: Scope And Methodology

Science.gov (United States)

Brown, Denise; Weiler, David; Flanary, Ronald

2016-01-01

In order to ensure long-term ability to meet mission goals and to provide for the safety of the public, ground personnel, and any crew members, nearly all spacecraft include a fault management (FM) system. For a manned vehicle such as Orion, the safety of the crew is of paramount importance. The goal of the Orion Guidance, Navigation and Control (GN&C) fault management system is to detect, isolate, and respond to faults before they can result in harm to the human crew or loss of the spacecraft. Verification of fault management/fault protection capability is challenging due to the large number of possible faults in a complex spacecraft, the inherent unpredictability of faults, the complexity of interactions among the various spacecraft components, and the inability to easily quantify human reactions to failure scenarios. The Orion GN&C Fault Detection, Isolation, and Recovery (FDIR) team has developed a methodology for bounding the scope of FM system verification while ensuring sufficient coverage of the failure space and providing high confidence that the fault management system meets all safety requirements. The methodology utilizes a swarm search algorithm to identify failure cases that can result in catastrophic loss of the crew or the vehicle and rare event sequential Monte Carlo to verify safety and FDIR performance requirements.

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

Directory of Open Access Journals (Sweden)

Kim Pyung Soo

2017-04-01

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

Fault Detection based on MCSA for a 400Hz Asynchronous Motor for Airborne Applications

Directory of Open Access Journals (Sweden)

Steffen Haus

2013-01-01

Full Text Available Future health monitoring concepts in different fields of engineering require reliable fault detection to avoid unscheduled machine downtime. Diagnosis of electrical induction machines for industrial applications is widely discussed in literature. In aviation industry, this topic is still only rarely discussed.A common approach to health monitoring for electrical induction machines is to use Motor Current Signature Analysis (MCSA based on a Fast Fourier Transform (FFT. Research results on this topic are available for comparatively large motors, where the power supply is typically based on 50Hz alternating current, which is the general power supply frequency for industrial applications.In this paper, transferability to airborne applications, where the power supply is 400Hz, is assessed. Three phase asynchronous motors are used to analyse detectability of different motor faults. The possibility to transfer fault detection results from 50Hz to 400Hz induction machines is the main question answered in this research work. 400Hz power supply frequency requires adjusted motor design, causing increased motor speed compared to 50Hz supply frequency. The motor used for experiments in this work is a 800W motor with 200V phase to phase power supply, powering an avionic fan. The fault cases to be examined are a bearing fault, a rotor unbalance, a stator winding fault, a broken rotor bar and a static air gap eccentricity. These are the most common faults in electrical induction machines which can cause machine downtime. The focus of the research work is the feasibility of the application of MCSA for small scale, high speed motor design, using the Fourier spectra of the current signal.Detectability is given for all but the bearing fault, although rotor unbalance can only be detected in case of severe damage level. Results obtained in the experiments are interpreted with respect to the motor design. Physical interpretation are given in case the results differ

Robust recurrent neural network modeling for software fault detection and correction prediction

International Nuclear Information System (INIS)

Hu, Q.P.; Xie, M.; Ng, S.H.; Levitin, G.

2007-01-01

Software fault detection and correction processes are related although different, and they should be studied together. A practical approach is to apply software reliability growth models to model fault detection, and fault correction process is assumed to be a delayed process. On the other hand, the artificial neural networks model, as a data-driven approach, tries to model these two processes together with no assumptions. Specifically, feedforward backpropagation networks have shown their advantages over analytical models in fault number predictions. In this paper, the following approach is explored. First, recurrent neural networks are applied to model these two processes together. Within this framework, a systematic networks configuration approach is developed with genetic algorithm according to the prediction performance. In order to provide robust predictions, an extra factor characterizing the dispersion of prediction repetitions is incorporated into the performance function. Comparisons with feedforward neural networks and analytical models are developed with respect to a real data set

Early detection of incipient faults in power plants using accelerated neural network learning

International Nuclear Information System (INIS)

Parlos, A.G.; Jayakumar, M.; Atiya, A.

1992-01-01

An important aspect of power plant automation is the development of computer systems able to detect and isolate incipient (slowly developing) faults at the earliest possible stages of their occurrence. In this paper, the development and testing of such a fault detection scheme is presented based on recognition of sensor signatures during various failure modes. An accelerated learning algorithm, namely adaptive backpropagation (ABP), has been developed that allows the training of a multilayer perceptron (MLP) network to a high degree of accuracy, with an order of magnitude improvement in convergence speed. An artificial neural network (ANN) has been successfully trained using the ABP algorithm, and it has been extensively tested with simulated data to detect and classify incipient faults of various types and severity and in the presence of varying sensor noise levels

Fault diagnostics in power transformer model winding for different alpha values

Directory of Open Access Journals (Sweden)

G.H. Kusumadevi

2015-09-01

Full Text Available Transient overvoltages appearing at line terminal of power transformer HV windings can cause failure of winding insulation. The failure can be from winding to ground or between turns or sections of winding. In most of the cases, failure from winding to ground can be detected by changes in the wave shape of surge voltage appearing at line terminal. However, detection of insulation failure between turns may be difficult due to intricacies involved in identifications of faults. In this paper, simulation investigations carried out on a power transformer model winding for identifying faults between turns of winding has been reported. The power transformer HV winding has been represented by 8 sections, 16 sections and 24 sections. Neutral current waveform has been analyzed for same model winding represented by different number of sections. The values of α (‘α’ value is the square root of total ground capacitance to total series capacitance of winding considered for windings are 5, 10 and 20. Standard lightning impulse voltage (1.2/50 μs wave shape have been considered for analysis. Computer simulations have been carried out using software PSPICE version 10.0. Neutral current and frequency response analysis methods have been used for identification of faults within sections of transformer model winding.

Fault Detection for Shipboard Monitoring – Volterra Kernel and Hammerstein Model Approaches

DEFF Research Database (Denmark)

Lajic, Zoran; Blanke, Mogens; Nielsen, Ulrik Dam

2009-01-01

In this paper nonlinear fault detection for in-service monitoring and decision support systems for ships will be presented. The ship is described as a nonlinear system, and the stochastic wave elevation and the associated ship responses are conveniently modelled in frequency domain. The transform....... The transformation from time domain to frequency domain has been conducted by use of Volterra theory. The paper takes as an example fault detection of a containership on which a decision support system has been installed....

Direct detection of near-surface faults by migration of back-scattered surface waves

KAUST Repository

Yu, Han; Guo, Bowen; Hanafy, Sherif; Lin, Fan-Chi; Schuster, Gerard T.

2014-01-01

We show that diffraction stack migration can be used to estimate the distribution of near-surface faults. The assumption is that near-surface faults generate detectable back-scattered surface waves from impinging surface waves. The processing steps

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

Science.gov (United States)

Boyle, Devin K.

2014-01-01

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

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

Science.gov (United States)

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

2017-06-01

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

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

Science.gov (United States)

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

2017-09-01

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

3D Dynamic Rupture Simulations along Dipping Faults, with a focus on the Wasatch Fault Zone, Utah

Science.gov (United States)

Withers, K.; Moschetti, M. P.

2017-12-01

We study dynamic rupture and ground motion from dip-slip faults in regions that have high-seismic hazard, such as the Wasatch fault zone, Utah. Previous numerical simulations have modeled deterministic ground motion along segments of this fault in the heavily populated regions near Salt Lake City but were restricted to low frequencies ( 1 Hz). We seek to better understand the rupture process and assess broadband ground motions and variability from the Wasatch Fault Zone by extending deterministic ground motion prediction to higher frequencies (up to 5 Hz). We perform simulations along a dipping normal fault (40 x 20 km along strike and width, respectively) with characteristics derived from geologic observations to generate a suite of ruptures > Mw 6.5. This approach utilizes dynamic simulations (fully physics-based models, where the initial stress drop and friction law are imposed) using a summation by parts (SBP) method. The simulations include rough-fault topography following a self-similar fractal distribution (over length scales from 100 m to the size of the fault) in addition to off-fault plasticity. Energy losses from heat and other mechanisms, modeled as anelastic attenuation, are also included, as well as free-surface topography, which can significantly affect ground motion patterns. We compare the effect of material structure and both rate and state and slip-weakening friction laws have on rupture propagation. The simulations show reduced slip and moment release in the near surface with the inclusion of plasticity, better agreeing with observations of shallow slip deficit. Long-wavelength fault geometry imparts a non-uniform stress distribution along both dip and strike, influencing the preferred rupture direction and hypocenter location, potentially important for seismic hazard estimation.

Detection of Early Faults in Rotating Machinery Based on Wavelet Analysis

Directory of Open Access Journals (Sweden)

Meng Hee Lim

2013-01-01

Full Text Available This paper explores the application of wavelet analysis for the detection of early changes in rotor dynamics caused by common machinery faults, namely, rotor unbalance and minor blade rubbing conditions. In this paper, the time synchronised wavelet analysis method was formulated and its effectiveness to detect machinery faults at the early stage was evaluated based on signal simulation and experimental study. The proposed method provides a more standardised approach to visualise the current state of rotor dynamics of a rotating machinery by taking into account the effects of time shift, wavelet edge distortion, and system noise suppression. The experimental results showed that this method is able to reveal subtle changes of the vibration signal characteristics in both the frequency content distribution and the amplitude distortion caused by minor rotor unbalance and blade rubbing conditions. Besides, this method also appeared to be an effective tool to diagnose and to discriminate the different types of machinery faults based on the unique pattern of the wavelet contours. This study shows that the proposed wavelet analysis method is promising to reveal machinery faults at early stage as compared to vibration spectrum analysis.

Fault Detection and Diagnosis of Railway Point Machines by Sound Analysis

Science.gov (United States)

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

2016-01-01

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

Stator fault detection for multi-phase machines with multiple reference frames transformation

DEFF Research Database (Denmark)

Bianchini, Claudio; Fornasiero, Emanuele; Matzen, T.N.

2009-01-01

The paper focuses on a new diagnostic index for fault detection of a five-phase permanent-magnet machine. This machine has been designed for fault tolerant applications, and it is characterized by a mutual inductance equal to zero and a high self inductance, in order to limit the short-circuit cu...

Stochastic Change Detection based on an Active Fault Diagnosis Approach

DEFF Research Database (Denmark)

Poulsen, Niels Kjølstad; Niemann, Hans Henrik

2007-01-01

The focus in this paper is on stochastic change detection applied in connection with active fault diagnosis (AFD). An auxiliary input signal is applied in AFD. This signal injection in the system will in general allow to obtain a fast change detection/isolation by considering the output or an err...

Distributed Fault Detection and Isolation for Flocking in a Multi-robot System with Imperfect Communication

Directory of Open Access Journals (Sweden)

Shao Shiliang

2014-06-01

Full Text Available In this paper, we focus on distributed fault detection and isolation (FDI for a multi-robot system where multiple robots execute a flocking task. Firstly, we propose a fault detection method based on the local-information-exchange and sensor-measurement technologies to cover cases of both perfect communication and imperfect communication. The two detection technologies can be adaptively selected according to the packet loss rate (PLR. Secondly, we design a fault isolation method, considering a situation in which faulty robots still influence the behaviours of other robots. Finally, a complete FDI scheme, based on the proposed detection and isolation methods, is simulated in various scenarios. The results demonstrate that our FDI scheme is effective.

Automatic Supervision And Fault Detection In PV System By Wireless Sensors With Interfacing By Labview Program

Directory of Open Access Journals (Sweden)

Yousra M Abbas

2015-08-01

Full Text Available In this work a wireless monitoring system are designed for automatic detection localization fault in photovoltaic system. In order to avoid the use of modeling and simulation of the PV system we detected the fault by monitoring the output of each individual photovoltaic panel connected in the system by Arduino and transmit this data wirelessly to laptop then interface it by LabVIEW program which made comparison between this data and the measured data taking from reference module at the same condition. The proposed method is very simple but effective detecting and diagnosing the main faults of a PV system and was experimentally validated and has demonstrated its effectiveness in the detection and diagnosing of main faults present in the DC side of PV system.

Bearing fault detection utilizing group delay and the Hilbert-Huang transform

International Nuclear Information System (INIS)

Jin, Shuai; Lee, Sang-Kwon

2017-01-01

Vibration signals measured from a mechanical system are useful to detect system faults. Signal processing has been used to extract fault information in bearing systems. However, a wide vibration signal frequency band often affects the ability to obtain the effective fault features. In addition, a few oscillation components are not useful at the entire frequency band in a vibration signal. By contrast, useful fatigue information can be embedded in the noise oscillation components. Thus, a method to estimate which frequency band contains fault information utilizing group delay was proposed in this paper. Group delay as a measure of phase distortion can indicate the phase structure relationship in the frequency domain between original (with noise) and denoising signals. We used the empirical mode decomposition of a Hilbert-Huang transform to sift the useful intrinsic mode functions based on the results of group delay after determining the valuable frequency band. Finally, envelope analysis and the energy distribution after the Hilbert transform were used to complete the fault diagnosis. The practical bearing fault data, which were divided into inner and outer race faults, were used to verify the efficiency and quality of the proposed method

Bearing fault detection utilizing group delay and the Hilbert-Huang transform

Energy Technology Data Exchange (ETDEWEB)

Jin, Shuai; Lee, Sang-Kwon [Inha University, Incheon (Korea, Republic of)

2017-03-15

Vibration signals measured from a mechanical system are useful to detect system faults. Signal processing has been used to extract fault information in bearing systems. However, a wide vibration signal frequency band often affects the ability to obtain the effective fault features. In addition, a few oscillation components are not useful at the entire frequency band in a vibration signal. By contrast, useful fatigue information can be embedded in the noise oscillation components. Thus, a method to estimate which frequency band contains fault information utilizing group delay was proposed in this paper. Group delay as a measure of phase distortion can indicate the phase structure relationship in the frequency domain between original (with noise) and denoising signals. We used the empirical mode decomposition of a Hilbert-Huang transform to sift the useful intrinsic mode functions based on the results of group delay after determining the valuable frequency band. Finally, envelope analysis and the energy distribution after the Hilbert transform were used to complete the fault diagnosis. The practical bearing fault data, which were divided into inner and outer race faults, were used to verify the efficiency and quality of the proposed method.

A first approach on fault detection and isolation for cardiovascular anomalies detection

KAUST Repository

Ledezma, Fernando

2015-07-01

In this paper, we use an extended version of the cardiovascular system\\'s state space model presented by [1] and propose a fault detection and isolation methodology to study the problem of detecting cardiovascular anomalies that can originate from variations in physiological parameters and deviations in the performance of the heart\\'s mitral and aortic valves. An observer-based approach is discussed as the basis of the method. The approach contemplates a bank of Extended Kalman Filters to achieve joint estimation of the model\\'s states and parameters and to detect malfunctions in the valves\\' performance. © 2015 American Automatic Control Council.

Fault detection in processes represented by PLS models using an EWMA control scheme

KAUST Repository

Harrou, Fouzi; Nounou, Mohamed N.; Nounou, Hazem N.

2016-01-01

with that of the traditional PLS-based fault detection method through a simulated example involving various fault scenarios that could be encountered in real processes. The simulation results clearly show the effectiveness of the proposed method over the conventional PLS

Fault Management: Degradation Signature Detection, Modeling, and Processing, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — Fault to Failure Progression (FFP) signature modeling and processing is a new method for applying condition-based signal data to detect degradation, to identify...

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

Science.gov (United States)

Osman, Shazali; Wang, Wilson

2018-03-01

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

Fault Detection for Diesel Engine Actuator

DEFF Research Database (Denmark)

Blanke, M.; Bøgh, S.A.; Jørgensen, R.B.

1994-01-01

Feedback control systems are vulnerable to faults in control loop sensors and actuators, because feedback actions may cause abrupt responses and process damage when faults occur.......Feedback control systems are vulnerable to faults in control loop sensors and actuators, because feedback actions may cause abrupt responses and process damage when faults occur....

Fault detection for nonlinear systems - A standard problem approach

DEFF Research Database (Denmark)

Stoustrup, Jakob; Niemann, Hans Henrik

1998-01-01

The paper describes a general method for designing (nonlinear) fault detection and isolation (FDI) systems for nonlinear processes. For a rich class of nonlinear systems, a nonlinear FDI system can be designed using convex optimization procedures. The proposed method is a natural extension...

Improved spectral kurtosis with adaptive redundant multiwavelet packet and its applications for rotating machinery fault detection

International Nuclear Information System (INIS)

Chen, Jinglong; Zi, Yanyang; He, Zhengjia; Yuan, Jing

2012-01-01

Rotating machinery fault detection is significant to avoid serious accidents and huge economic losses effectively. However, due to the vibration signal with the character of non-stationarity and nonlinearity, the detection and extraction of the fault feature turn into a challenging task. Therefore, a novel method called improved spectral kurtosis (ISK) with adaptive redundant multiwavelet packet (ARMP) is proposed for this task. Spectral kurtosis (SK) has been proved to be a powerful tool to detect and characterize the non-stationary signal. To improve the SK in filter limitation and enhance the resolution of spectral analysis as well as match fault feature optimally, the ARMP is introduced into the SK. Moreover, since kurtosis does not reflect the actual trend of periodic impulses, the SK is improved by incorporating an evaluation index called envelope spectrum entropy as supplement. The proposed method is applied to the rolling element bearing and gear fault detection to validate its reliability and effectiveness. Compared with the conventional frequency spectrum, envelope spectrum, original SK and some single wavelet methods, the results indicate that it could improve the accuracy of frequency-band selection and enhance the ability of rotating machinery fault detection. (paper)

A system for the non-destructive detection of faults in safety fuses using radioisotopes

International Nuclear Information System (INIS)

Goncalves, D.

1980-01-01

Design of an equipment for on line detection of faults in the safety fuses for conventional explosives employing transmission of #betta#-radiation is reported. The faults are detected by an ion-chamber based on the variation of the intensity of the beta particles transmitted through the fuse during its passage across the collimated beam. Strontium-90 encapsulated in stainless steel or aluminum is used as the #betta#-source. An electrical signal corresponding the fault is obtained by subtraction of an external current, that is equivalent to the output of the ion-chamber in the presence of faultless fuse. (Author) [pt

A geometric approach for fault detection and isolation of stator short circuit failure in a single asynchronous machine

KAUST Repository

Khelouat, Samir

2012-06-01

This paper deals with the problem of detection and isolation of stator short-circuit failure in a single asynchronous machine using a geometric approach. After recalling the basis of the geometric approach for fault detection and isolation in nonlinear systems, we will study some structural properties which are fault detectability and isolation fault filter existence. We will then design filters for residual generation. We will consider two approaches: a two-filters structure and a single filter structure, both aiming at generating residuals which are sensitive to one fault and insensitive to the other faults. Some numerical tests will be presented to illustrate the efficiency of the method.

A Novel Approach to Detect Faults Occurring During Power Swings by Abrupt Change of Impedance Trajectory

DEFF Research Database (Denmark)

Khodaparast, Jalal; Khederzadeh, M.; Silva, Filipe Miguel Faria da

2017-01-01

The main purpose of power swing blocking is to distinguish faults from power swings. However, faults occurred during a power swing should still be detected and cleared promptly. This paper proposes an index based on detecting abrupt jump of impedance trajectory by utilization of the predicting...... of Taylor expansion is used to decrease the corrugation effect of impedance estimation and increase the reliability of the proposed method. Furthermore, in order to increase the selectivity of the proposed method, the proposed index is armed with phase comparison logic to detect internal faults...

A Study on the Dependable and Secure Relaying Scheme under High Resistance Earth Faults on HV, EHV Line

Energy Technology Data Exchange (ETDEWEB)

Kim, I.D.; Han, K.N. [Korea Electric Power Research Institute, Taejeon (Korea, Republic of)

1997-12-31

This report contains following items for the purpose of investigating and analyzing characteristics of high impedance ground faults. - Reason and characteristics identification of HIF - Modeling of power system - Testing of protective relays using RTD(Real Time Digital Simulator) - Staged ground faults test - Development of new algorithm to detect HIF - Protective coordination schemes between different types of relays - HIF monitoring and relaying scheme and H/W prototyping. (author). 22 refs., 28 figs., 21 tabs.

Ground-rupturing earthquakes on the northern Big Bend of the San Andreas Fault, California, 800 A.D. to Present

Science.gov (United States)

Scharer, Katherine M.; Weldon, Ray; Biasi, Glenn; Streig, Ashley; Fumal, Thomas E.

2017-01-01

Paleoseismic data on the timing of ground-rupturing earthquakes constrain the recurrence behavior of active faults and can provide insight on the rupture history of a fault if earthquakes dated at neighboring sites overlap in age and are considered correlative. This study presents the evidence and ages for 11 earthquakes that occurred along the Big Bend section of the southern San Andreas Fault at the Frazier Mountain paleoseismic site. The most recent earthquake to rupture the site was the Mw7.7–7.9 Fort Tejon earthquake of 1857. We use over 30 trench excavations to document the structural and sedimentological evolution of a small pull-apart basin that has been repeatedly faulted and folded by ground-rupturing earthquakes. A sedimentation rate of 0.4 cm/yr and abundant organic material for radiocarbon dating contribute to a record that is considered complete since 800 A.D. and includes 10 paleoearthquakes. Earthquakes have ruptured this location on average every ~100 years over the last 1200 years, but individual intervals range from ~22 to 186 years. The coefficient of variation of the length of time between earthquakes (0.7) indicates quasiperiodic behavior, similar to other sites along the southern San Andreas Fault. Comparison with the earthquake chronology at neighboring sites along the fault indicates that only one other 1857-size earthquake could have occurred since 1350 A.D., and since 800 A.D., the Big Bend and Mojave sections have ruptured together at most 50% of the time in Mw ≥ 7.3 earthquakes.

Kinematics and strain analyses of the eastern segment of the Pernicana Fault (Mt. Etna, Italy derived from geodetic techniques (1997-2005

Directory of Open Access Journals (Sweden)

M. Mattia

2006-06-01

Full Text Available This paper analyses the ground deformations occurring on the eastern part of the Pernicana Fault from 1997 to 2005. This segment of the fault was monitored with three local networks based on GPS and EDM techniques. More than seventy GPS and EDM surveys were carried out during the considered period, in order to achieve a higher temporal detail of ground deformation affecting the structure. We report the comparisons among GPS and EDM surveys in terms of absolute horizontal displacements of each GPS benchmark and in terms of strain parameters for each GPS and EDM network. Ground deformation measurements detected a continuous left-lateral movement of the Pernicana Fault. We conclude that, on the easternmost part of the Pernicana Fault, where it branches out into two segments, the deformation is transferred entirely SE-wards by a splay fault.

Fault detection in IRIS reactor secondary loop using inferential models

International Nuclear Information System (INIS)

Perillo, Sergio R.P.; Upadhyaya, Belle R.; Hines, J. Wesley

2013-01-01

The development of fault detection algorithms is well-suited for remote deployment of small and medium reactors, such as the IRIS, and the development of new small modular reactors (SMR). However, an extensive number of tests are still to be performed for new engineering aspects and components that are not yet proven technology in the current PWRs, and present some technological challenges for its deployment since many of its features cannot be proven until a prototype plant is built. In this work, an IRIS plant simulation platform was developed using a Simulink® model. The dynamic simulation was utilized in obtaining inferential models that were used to detect faults artificially added to the secondary system simulations. The implementation of data-driven models and the results are discussed. (author)

Fault Detection of Wind Turbines with Uncertain Parameters

DEFF Research Database (Denmark)

Tabatabaeipour, Seyed Mojtaba; Odgaard, Peter Fogh; Bak, Thomas

2012-01-01

on the torque coefficient. High noise on the wind speed measurement, nonlinearities in the aerodynamic torque and uncertainties on the parameters make fault detection a challenging problem. We use an effective wind speed estimator to reduce the noise on the wind speed measurements. A set-membership approach...... is detected. For representation of these sets we use zonotopes and for modeling of uncertainties we use matrix zonotopes, which yields a computationally efficient algorithm. The method is applied to the wind turbine benchmark problem without and with uncertainties. The result demonstrates the effectiveness...

Detection of Stator Winding Fault in Induction Motor Using Fuzzy Logic with Optimal Rules

Directory of Open Access Journals (Sweden)

Hamid Fekri Azgomi

2013-04-01

Full Text Available Induction motors are critical components in many industrial processes. Therefore, swift, precise and reliable monitoring and fault detection systems are required to prevent any further damages. The online monitoring of induction motors has been becoming increasingly important. The main difficulty in this task is the lack of an accurate analytical model to describe a faulty motor. A fuzzy logic approach may help to diagnose traction motor faults. This paper presents a simple method for the detection of stator winding faults (which make up 38% of induction motor failures based on monitoring the line/terminal current amplitudes. In this method, fuzzy logic is used to make decisions about the stator motor condition. In fact, fuzzy logic is reminiscent of human thinking processes and natural language enabling decisions to be made based on vague information. The motor condition is described using linguistic variables. Fuzzy subsets and the corresponding membership functions describe stator current amplitudes. A knowledge base, comprising rule and data bases, is built to support the fuzzy inference. Simulation results are presented to verify the accuracy of motor’s fault detection and knowledge extraction feasibility. The preliminary results show that the proposed fuzzy approach can be used for accurate stator fault diagnosis.

Fault detection for hydraulic pump based on chaotic parallel RBF network

Directory of Open Access Journals (Sweden)

Ma Ning

2011-01-01

Full Text Available Abstract 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.

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

Directory of Open Access Journals (Sweden)

Detong Kong

2012-02-01

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

Development of methods for evaluating active faults

Energy Technology Data Exchange (ETDEWEB)

NONE

2012-08-15

The HERP report for long-term evaluation of active faults and the NSC safety review guide with regard to geology and ground of site were published on Nov. 2010 and on Dec. 2010, respectively. With respect to those reports, our investigation is as follows; (1) For assessment of seismic hazard, we estimated seismic sources around NPPs based on information of tectonic geomorphology, earthquake distribution and subsurface geology. (2) For evaluation on the activity of blind fault, we calculated the slip rate on the 2008 Iwate-Miyagi Nairiku Earthquake fault, using information on late Quaternary fluvial terraces. (3) To evaluate the magnitude of earthquakes whose sources are difficult to identify, we proposed a new method for calculation of the seismogenic layer thickness. (4) To clarify the activities of active faults without superstratum, we carried out the color analysis of fault gouge and divided the activities into thousand of years and tens of thousands. (5) For improving chronology of sediments, we detected new widespread cryptotephras using mineral chemistry and developed late Quaternary cryptotephrostratigraphy around NPPs. (author)

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

Science.gov (United States)

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

1996-03-01

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

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

Science.gov (United States)

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

2017-09-09

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

Implementation of fuzzy modeling system for faults detection and diagnosis in three phase induction motor drive system

Directory of Open Access Journals (Sweden)

Shorouk Ossama Ibrahim

2015-05-01

Full Text Available Induction motors have been intensively utilized in industrial applications, mainly due to their efficiency and reliability. It is necessary that these machines work all the time with its high performance and reliability. So it is necessary to monitor, detect and diagnose different faults that these motors are facing. In this paper an intelligent fault detection and diagnosis for different faults of induction motor drive system is introduced. The stator currents and the time are introduced as inputs to the proposed fuzzy detection and diagnosis system. The direct torque control technique (DTC is adopted as a suitable control technique in the drive system especially, in traction applications, such as Electric Vehicles and Sub-Way Metro that used such a machine. An intelligent modeling technique is adopted as an identifier for different faults; the proposed model introduces the time as an important factor or variable that plays an important role either in fault detection or in decision making for suitable corrective action according to the type of the fault. Experimental results have been obtained to verify the efficiency of the proposed intelligent detector and identifier; a matching between the simulated and experimental results has been noticed.

Incipient Fault Detection and Isolation of Field Devices in Nuclear Power Systems Using Principal Component Analysis

International Nuclear Information System (INIS)

Kaistha, Nitin; Upadhyaya, Belle R.

2001-01-01

An integrated method for the detection and isolation of incipient faults in common field devices, such as sensors and actuators, using plant operational data is presented. The approach is based on the premise that data for normal operation lie on a surface and abnormal situations lead to deviations from the surface in a particular way. Statistically significant deviations from the surface result in the detection of faults, and the characteristic directions of deviations are used for isolation of one or more faults from the set of typical faults. Principal component analysis (PCA), a multivariate data-driven technique, is used to capture the relationships in the data and fit a hyperplane to the data. The fault direction for each of the scenarios is obtained using the singular value decomposition on the state and control function prediction errors, and fault isolation is then accomplished from projections on the fault directions. This approach is demonstrated for a simulated pressurized water reactor steam generator system and for a laboratory process control system under single device fault conditions. Enhanced fault isolation capability is also illustrated by incorporating realistic nonlinear terms in the PCA data matrix

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

Science.gov (United States)

Xue, Song; Howard, Ian

2018-02-01

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

Robust fault detection of linear systems using a computationally efficient set-membership method

DEFF Research Database (Denmark)

Tabatabaeipour, Mojtaba; Bak, Thomas

2014-01-01

In this paper, a computationally efficient set-membership method for robust fault detection of linear systems is proposed. The method computes an interval outer-approximation of the output of the system that is consistent with the model, the bounds on noise and disturbance, and the past measureme...... is trivially parallelizable. The method is demonstrated for fault detection of a hydraulic pitch actuator of a wind turbine. We show the effectiveness of the proposed method by comparing our results with two zonotope-based set-membership methods....

Detection of Sensor Faults in Small Helicopter UAVs Using Observer/Kalman Filter Identification

Directory of Open Access Journals (Sweden)

Guillermo Heredia

2011-01-01

Full Text Available Reliability is a critical issue in navigation of unmanned aerial vehicles (UAVs since there is no human pilot that can react to any abnormal situation. Due to size and cost limitations, redundant sensor schemes and aeronautical-grade navigation sensors used in large aircrafts cannot be installed in small UAVs. Therefore, other approaches like analytical redundancy should be used to detect faults in navigation sensors and increase reliability. This paper presents a sensor fault detection and diagnosis system for small autonomous helicopters based on analytical redundancy. Fault detection is accomplished by evaluating any significant change in the behaviour of the vehicle with respect to the fault-free behaviour, which is estimated by using an observer. The observer is obtained from input-output experimental data with the Observer/Kalman Filter Identification (OKID method. The OKID method is able to identify the system and an observer with properties similar to a Kalman filter, directly from input-output experimental data. Results are similar to the Kalman filter, but, with the proposed method, there is no need to estimate neither system matrices nor sensor and process noise covariance matrices. The system has been tested with real helicopter flight data, and the results compared with other methods.

Colloid Detection in Natural Ground Water from Ruprechtov by Laser-Induced Breakdown Detection

Energy Technology Data Exchange (ETDEWEB)

Hauser, W.; Geckeis, H.; Goetz, R. [FZK - Inst. fuer Nukleare Entsorgung, Ka rlsruhe (Germany)]. e-mail: hauser@ine.fzk.de; Noseck, U. [Gesellschaft fuer Anlagen- und Reaktorsicherheit, D-38122 Braunschweig (Germany); Laciok, A. [Nuclear Research Inst. Rez plc, Waste and Environmental Management Dept., Husinec-Rez, PSC 250 68 (Czech Republic)

2007-06-15

A borehole ground water sampling system and a mobile laser-induced breakdown detection (LIBD) equipment for colloid detection combined with a geomonitoring unit have been applied to characterize the natural background colloid concentration in ground waters of the Ruprechtov natural analogue site (Czech Republic). Ground water has been sampled using steel cylinders. To minimize artifacts during ground water sampling the contact to atmospheric oxygen has been excluded. The ground water samples collected in this way are transported to the laboratory where they have been connected to a series of flow-through detection cells. Argon gas is used to press the ground water through these detection cells for colloid analysis (LIBD), pH, Eh, electrical conductivity and oxygen content. After the above mentioned analysis additional samples are taken for chemical analysis by ICP-AES, ICP-MS, IC- and DOC-detection. Our data obtained by in-situ- and laboratory- measurements point out that the natural colloid concentration found at the Ruprechtov site is a strong function of the ground water ionic strength. The LIBD determined natural background colloid concentrations found at Ruprechtov are compared with data of studies performed in Aespoe (Sweden) and Grimsel (Switzerland)

Fault Detection Coverage Quantification of Automatic Test Functions of Digital I and C System in NPPs

International Nuclear Information System (INIS)

Choi, Jong Gyun; Lee, Seung Jun; Hur, Seop; Lee, Young Jun; Jang, Seung Cheol

2011-01-01

Recently, analog instrument and control (I and C) systems in nuclear power plants (NPPs) have been replaced with digital systems for safer and more efficient operations. Digital I and C systems have adopted various fault-tolerant techniques that help the system correctly and safely perform the specific required functions in spite of the presence of faults. Each fault-tolerant technique has a different inspection period from real-time monitoring to monthly testing. The range covered by each fault-tolerant technique is also different. The digital I and C system, therefore, adopts multiple barriers consisting of various fault-tolerant techniques to increase total fault detection coverage. Even though these fault-tolerant techniques are adopted to ensure and improve the safety of a system, their effects have not been properly considered yet in most PSA models. Therefore, it is necessary to develop an evaluation method that can describe these features of a digital I and C system. Several issues must be considered in the fault coverage estimation of a digital I and C system, and two of them were handled in this work. The first is to quantify the fault coverage of each fault-tolerant technique implemented in the system, and the second is to exclude the duplicated effect of fault-tolerant techniques implemented simultaneously at each level of the system's hierarchy, as a fault occurring in a system might be detected by one or more fault-tolerant techniques. For this work, fault injection experiment was used to obtain the exact relations between faults and multiple barriers of fault-tolerant techniques. This experiment was applied to a bistable processor (BP) of a reactor protection system

New method of silicon photovoltaic panel fault detection using impedance spectroscopy

DEFF Research Database (Denmark)

Symonowicz, Joanna Karolina; Riedel, Nicholas; Thorsteinsson, Sune

2017-01-01

The aim of our project is to develop a new method for photovoltaic (PV) panel fault detection based on analysing its impedance spectra (IS). Although this technique was successful in assessing the state of degradation of fuel cells and batteries [1, 2], it has never been applied to PV cells...... on a wide scale. In this paper, we show that, unlike current-voltage (I-V) tests, the IS method is capable of early detection of changes in PV panel parameters due to microcracks and potential-induced degradation (PID). Although our measurements are only successful under dark conditions, the results...... are similar for both laboratory environment and for outdoor tests in various weather conditions. A fully developed IS technique, accounting for all kinds of most common PV panel degradation types, would surpass the existing PV fault detection methods then it comes to cost and accuracy [3,4]....

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

Science.gov (United States)

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

2010-01-01

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

Imaging of Subsurface Faults using Refraction Migration with Fault Flooding

KAUST Repository

Metwally, Ahmed Mohsen Hassan

2017-05-31

We propose a novel method for imaging shallow faults by migration of transmitted refraction arrivals. The assumption is that there is a significant velocity contrast across the fault boundary that is underlain by a refracting interface. This procedure, denoted as refraction migration with fault flooding, largely overcomes the difficulty in imaging shallow faults with seismic surveys. Numerical results successfully validate this method on three synthetic examples and two field-data sets. The first field-data set is next to the Gulf of Aqaba and the second example is from a seismic profile recorded in Arizona. The faults detected by refraction migration in the Gulf of Aqaba data were in agreement with those indicated in a P-velocity tomogram. However, a new fault is detected at the end of the migration image that is not clearly seen in the traveltime tomogram. This result is similar to that for the Arizona data where the refraction image showed faults consistent with those seen in the P-velocity tomogram, except it also detected an antithetic fault at the end of the line. This fault cannot be clearly seen in the traveltime tomogram due to the limited ray coverage.

Imaging of Subsurface Faults using Refraction Migration with Fault Flooding

KAUST Repository

Metwally, Ahmed Mohsen Hassan; Hanafy, Sherif; Guo, Bowen; Kosmicki, Maximillian Sunflower

2017-01-01

We propose a novel method for imaging shallow faults by migration of transmitted refraction arrivals. The assumption is that there is a significant velocity contrast across the fault boundary that is underlain by a refracting interface. This procedure, denoted as refraction migration with fault flooding, largely overcomes the difficulty in imaging shallow faults with seismic surveys. Numerical results successfully validate this method on three synthetic examples and two field-data sets. The first field-data set is next to the Gulf of Aqaba and the second example is from a seismic profile recorded in Arizona. The faults detected by refraction migration in the Gulf of Aqaba data were in agreement with those indicated in a P-velocity tomogram. However, a new fault is detected at the end of the migration image that is not clearly seen in the traveltime tomogram. This result is similar to that for the Arizona data where the refraction image showed faults consistent with those seen in the P-velocity tomogram, except it also detected an antithetic fault at the end of the line. This fault cannot be clearly seen in the traveltime tomogram due to the limited ray coverage.

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

Science.gov (United States)

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

2017-05-24

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

Fault Detection Based on Tracking Differentiator Applied on the Suspension System of Maglev Train

Directory of Open Access Journals (Sweden)

Hehong Zhang

2015-01-01

Full Text Available A fault detection method based on the optimized tracking differentiator is introduced. It is applied on the acceleration sensor of the suspension system of maglev train. It detects the fault of the acceleration sensor by comparing the acceleration integral signal with the speed signal obtained by the optimized tracking differentiator. This paper optimizes the control variable when the states locate within or beyond the two-step reachable region to improve the performance of the approximate linear discrete tracking differentiator. Fault-tolerant control has been conducted by feedback based on the speed signal acquired from the optimized tracking differentiator when the acceleration sensor fails. The simulation and experiment results show the practical usefulness of the presented method.

Fault Detection in High Speed Helical Gears Considering Signal Processing Method in Real Simulation

Directory of Open Access Journals (Sweden)

Amir Ali Tabatabai Adnani

Full Text Available Abstract In the present study, in order to detect the fault of the gearmeshs, two engaged gears based on research department of a major automotive company have been modeled. First off, by using the CATIA software the fault was induced to the output gear. Then, the faulty gearmesh and non-faulty gearmesh is modeled to find the fault pattern to predict and estimate the failure of the gearmesh. The induced defect is according to the frequently practical fault that takes place to the teeth of gears. In order to record the acceleration signals to calculate the decomposition algorithm, mount the accelerometer on accessible place of the output shaft to recognize the pattern. Then, for more realistic simulation, noise is added to the output signal. At the first step by means of Butterworth low pass digital, the noise has to be removed from signals after that by using the Empirical Mode Decomposition (EMD, signals have decomposed into the Instinct Mode Function (IMF and every IMF were tested by using the Instantaneous Frequency (IF in way of Hillbert Transform (HT. For this purpose a code was developed in MATLAB software. Then, in order to detect the presence of the fault the frequency spectrum of IMF's are created and defect is detected in gearmesh frequency of the spectrum.

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

Directory of Open Access Journals (Sweden)

Lue Chen

2013-01-01

Full Text Available 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.

Vibration-Based Adaptive Novelty Detection Method for Monitoring Faults in a Kinematic Chain

Directory of Open Access Journals (Sweden)

Jesus Adolfo Cariño-Corrales

2016-01-01

Full Text Available This paper presents an adaptive novelty detection methodology applied to a kinematic chain for the monitoring of faults. The proposed approach has the premise that only information of the healthy operation of the machine is initially available and fault scenarios will eventually develop. This approach aims to cover some of the challenges presented when condition monitoring is applied under a continuous learning framework. The structure of the method is divided into two recursive stages: first, an offline stage for initialization and retraining of the feature reduction and novelty detection modules and, second, an online monitoring stage to continuously assess the condition of the machine. Contrary to classical static feature reduction approaches, the proposed method reformulates the features by employing first a Laplacian Score ranking and then the Fisher Score ranking for retraining. The proposed methodology is validated experimentally by monitoring the vibration measurements of a kinematic chain driven by an induction motor. Two faults are induced in the motor to validate the method performance to detect anomalies and adapt the feature reduction and novelty detection modules to the new information. The obtained results show the advantages of employing an adaptive approach for novelty detection and feature reduction making the proposed method suitable for industrial machinery diagnosis applications.

Karhunen Loeve Basis Used for Detection of Gearbox Faults in a Wind Turbine

DEFF Research Database (Denmark)

Odgaard, Peter Fogh; Stoustrup, Jakob

2014-01-01

Reliability and sustainability of wind turbines increase in importance as wind turbines contribute with increasing power generation to the world's power grids. One possible way to achieve this is by using advanced fault detection and isolation methods in wind turbines based on the measurements...... provided to the control system. In this paper a Karhunen-Loeve basis approach is designed for detecting changes in frequency response from rotating parts like a gearbox. The potential of this method is shown by applying it to an established Wind Turbine FDI and FTC Benchmark model. These faults...

Fault Detection and Isolation Using Analytical Redundancy Relations for the Ship Propulsion Benchmark

DEFF Research Database (Denmark)

Izadi-Zamanabadi, Roozbeh

The prime objective of Fault-tolerant Control (FTC) systems is to handle faults and discrepancies using appropriate accommodation policies. The issue of obtaining information about various parameters and signals, which have to be monitored for fault detection purposes, becomes a rigorous task...... with the growing number of subsystems. The structural approach, presented in this report, constitutes a general framework for providing information when the system becomes complex. Furthermore, by using this approach, one can determine the calculation sequences of the residuals. The methodology of this approach...

Anomaly Detection for Next-Generation Space Launch Ground Operations

Science.gov (United States)

Spirkovska, Lilly; Iverson, David L.; Hall, David R.; Taylor, William M.; Patterson-Hine, Ann; Brown, Barbara; Ferrell, Bob A.; Waterman, Robert D.

2010-01-01

NASA is developing new capabilities that will enable future human exploration missions while reducing mission risk and cost. The Fault Detection, Isolation, and Recovery (FDIR) project aims to demonstrate the utility of integrated vehicle health management (IVHM) tools in the domain of ground support equipment (GSE) to be used for the next generation launch vehicles. In addition to demonstrating the utility of IVHM tools for GSE, FDIR aims to mature promising tools for use on future missions and document the level of effort - and hence cost - required to implement an application with each selected tool. One of the FDIR capabilities is anomaly detection, i.e., detecting off-nominal behavior. The tool we selected for this task uses a data-driven approach. Unlike rule-based and model-based systems that require manual extraction of system knowledge, data-driven systems take a radically different approach to reasoning. At the basic level, they start with data that represent nominal functioning of the system and automatically learn expected system behavior. The behavior is encoded in a knowledge base that represents "in-family" system operations. During real-time system monitoring or during post-flight analysis, incoming data is compared to that nominal system operating behavior knowledge base; a distance representing deviation from nominal is computed, providing a measure of how far "out of family" current behavior is. We describe the selected tool for FDIR anomaly detection - Inductive Monitoring System (IMS), how it fits into the FDIR architecture, the operations concept for the GSE anomaly monitoring, and some preliminary results of applying IMS to a Space Shuttle GSE anomaly.

Kinematic Earthquake Ground‐Motion Simulations on Listric Normal Faults

KAUST Repository

Passone, Luca

2017-11-28

Complex finite-faulting source processes have important consequences for near-source ground motions, but empirical ground-motion prediction equations still lack near-source data and hence cannot fully capture near-fault shaking effects. Using a simulation-based approach, we study the effects of specific source parameterizations on near-field ground motions where empirical data are limited. Here, we investigate the effects of fault listricity through near-field kinematic ground-motion simulations. Listric faults are defined as curved faults in which dip decreases with depth, resulting in a concave upward profile. The listric profiles used in this article are built by applying a specific shape function and varying the initial dip and the degree of listricity. Furthermore, we consider variable rupture speed and slip distribution to generate ensembles of kinematic source models. These ensembles are then used in a generalized 3D finite-difference method to compute synthetic seismograms; the corresponding shaking levels are then compared in terms of peak ground velocities (PGVs) to quantify the effects of breaking fault planarity. Our results show two general features: (1) as listricity increases, the PGVs decrease on the footwall and increase on the hanging wall, and (2) constructive interference of seismic waves emanated from the listric fault causes PGVs over two times higher than those observed for the planar fault. Our results are relevant for seismic hazard assessment for near-fault areas for which observations are scarce, such as in the listric Campotosto fault (Italy) located in an active seismic area under a dam.

Kinematic Earthquake Ground‐Motion Simulations on Listric Normal Faults

KAUST Repository

Passone, Luca; Mai, Paul Martin

2017-01-01

Complex finite-faulting source processes have important consequences for near-source ground motions, but empirical ground-motion prediction equations still lack near-source data and hence cannot fully capture near-fault shaking effects. Using a simulation-based approach, we study the effects of specific source parameterizations on near-field ground motions where empirical data are limited. Here, we investigate the effects of fault listricity through near-field kinematic ground-motion simulations. Listric faults are defined as curved faults in which dip decreases with depth, resulting in a concave upward profile. The listric profiles used in this article are built by applying a specific shape function and varying the initial dip and the degree of listricity. Furthermore, we consider variable rupture speed and slip distribution to generate ensembles of kinematic source models. These ensembles are then used in a generalized 3D finite-difference method to compute synthetic seismograms; the corresponding shaking levels are then compared in terms of peak ground velocities (PGVs) to quantify the effects of breaking fault planarity. Our results show two general features: (1) as listricity increases, the PGVs decrease on the footwall and increase on the hanging wall, and (2) constructive interference of seismic waves emanated from the listric fault causes PGVs over two times higher than those observed for the planar fault. Our results are relevant for seismic hazard assessment for near-fault areas for which observations are scarce, such as in the listric Campotosto fault (Italy) located in an active seismic area under a dam.

Use of Sparse Principal Component Analysis (SPCA) for Fault Detection

DEFF Research Database (Denmark)

Gajjar, Shriram; Kulahci, Murat; Palazoglu, Ahmet

2016-01-01

Principal component analysis (PCA) has been widely used for data dimension reduction and process fault detection. However, interpreting the principal components and the outcomes of PCA-based monitoring techniques is a challenging task since each principal component is a linear combination of the ...

Comparative Study of Parametric and Non-parametric Approaches in Fault Detection and Isolation

DEFF Research Database (Denmark)

Katebi, S.D.; Blanke, M.; Katebi, M.R.

This report describes a comparative study between two approaches to fault detection and isolation in dynamic systems. The first approach uses a parametric model of the system. The main components of such techniques are residual and signature generation for processing and analyzing. The second...... approach is non-parametric in the sense that the signature analysis is only dependent on the frequency or time domain information extracted directly from the input-output signals. Based on these approaches, two different fault monitoring schemes are developed where the feature extraction and fault decision...

Estimation of Seismic Ground Motions and Attendant Potential Human Fatalities from Scenario Earthquakes on the Chishan Fault in Southern Taiwan

Directory of Open Access Journals (Sweden)

Kun-Sung Liu

2017-01-01

Full Text Available The purpose of this study is to estimate maximum ground motions in southern Taiwan as well as to assess potential human fatalities from scenario earthquakes on the Chishan active faults in this area. The resultant Shake Map patterns of maximum ground motion in a case of Mw 7.2 show the areas of PGA above 400 gals are located in the northeastern, central and northern parts of southwestern Kaohsiung as well as the southern part of central Tainan, as shown in the regions inside the yellow lines in the corresponding figure. Comparing cities with similar distances located in Tainan, Kaohsiung, and Pingtung to the Chishan fault, the cities in Tainan area have relatively greater PGA and PGV, due to large site response factors in Tainan area. Furthermore, seismic hazards in terms of PGA and PGV in the vicinity of the Chishan fault are not completely dominated by the Chishan fault. The main reason is that some areas located in the vicinity of the Chishan fault are marked with low site response amplification values from 0.55 - 1.1 and 0.67 - 1.22 for PGA and PGV, respectively. Finally, from estimation of potential human fatalities from scenario earthquakes on the Chishan active fault, it is noted that potential fatalities increase rapidly in people above age 45. Total fatalities reach a high peak in age groups of 55 - 64. Another to pay special attention is Kaohsiung City has more than 540 thousand households whose residences over 50 years old. In light of the results of this study, I urge both the municipal and central governments to take effective seismic hazard mitigation measures in the highly urbanized areas with a large number of old buildings in southern Taiwan.

Monitoring a robot swarm using a data-driven fault detection approach

KAUST Repository

Khaldi, Belkacem

2017-06-30

Using swarm robotics system, with one or more faulty robots, to accomplish specific tasks may lead to degradation in performances complying with the target requirements. In such circumstances, robot swarms require continuous monitoring to detect abnormal events and to sustain normal operations. In this paper, an innovative exogenous fault detection method for monitoring robots swarm is presented. The method merges the flexibility of principal component analysis (PCA) models and the greater sensitivity of the exponentially-weighted moving average (EWMA) and cumulative sum (CUSUM) control charts to insidious changes. The method is tested and evaluated on a swarm of simulated foot-bot robots performing a circle formation task, via the viscoelastic control model. We illustrate through simulated data collected from the ARGoS simulator that a significant improvement in fault detection can be obtained by using the proposed method where compared to the conventional PCA-based methods (i.e., T2 and Q).

On-Line Fault Detection in Wind Turbine Transmission System using Adaptive Filter and Robust Statistical Features

Directory of Open Access Journals (Sweden)

Mark Frogley

2013-01-01

Full Text Available To reduce the maintenance cost, avoid catastrophic failure, and improve the wind transmission system reliability, online condition monitoring system is critical important. In the real applications, many rotating mechanical faults, such as bearing surface defect, gear tooth crack, chipped gear tooth and so on generate impulsive signals. When there are these types of faults developing inside rotating machinery, each time the rotating components pass over the damage point, an impact force could be generated. The impact force will cause a ringing of the support structure at the structural natural frequency. By effectively detecting those periodic impulse signals, one group of rotating machine faults could be detected and diagnosed. However, in real wind turbine operations, impulsive fault signals are usually relatively weak to the background noise and vibration signals generated from other healthy components, such as shaft, blades, gears and so on. Moreover, wind turbine transmission systems work under dynamic operating conditions. This will further increase the difficulties in fault detection and diagnostics. Therefore, developing advanced signal processing methods to enhance the impulsive signals is in great needs.In this paper, an adaptive filtering technique will be applied for enhancing the fault impulse signals-to-noise ratio in wind turbine gear transmission systems. Multiple statistical features designed to quantify the impulsive signals of the processed signal are extracted for bearing fault detection. The multiple dimensional features are then transformed into one dimensional feature. A minimum error rate classifier will be designed based on the compressed feature to identify the gear transmission system with defect. Real wind turbine vibration signals will be used to demonstrate the effectiveness of the presented methodology.

Fault tolerant control for uncertain systems with parametric faults

DEFF Research Database (Denmark)

Niemann, Hans Henrik; Poulsen, Niels Kjølstad

2006-01-01

A fault tolerant control (FTC) architecture based on active fault diagnosis (AFD) and the YJBK (Youla, Jarb, Bongiorno and Kucera)parameterization is applied in this paper. Based on the FTC architecture, fault tolerant control of uncertain systems with slowly varying parametric faults...... is investigated. Conditions are given for closed-loop stability in case of false alarms or missing fault detection/isolation....

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

Science.gov (United States)

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

2012-01-01

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

Aircraft applications of fault detection and isolation techniques

Science.gov (United States)

Marcos Esteban, Andres

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