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Fault indicator

About: Fault indicator is a research topic. Over the lifetime, 10057 publications have been published within this topic receiving 143482 citations. The topic is also known as: FCI & power line fault indicator.


Papers
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Proceedings ArticleDOI
03 Oct 2000
TL;DR: The results suggest that untargetted test patterns perform almost as well as those targetted on a transition fault model, despite appearing to have a much lower fault coverage.
Abstract: This paper reflects on some recent results that show the value of delay-fault tests on a deep sub-micron process. However, the results also suggest that untargetted test patterns perform almost as well as those targetted on a transition fault model, despite appearing to have a much lower fault coverage. This leads to an examination of the defect mechanisms in deep sub-micron ICs, in particular the relationship of crosstalk and power-rail coupling to resistive opens and resistive bridges. A number of new fault mechanisms are described. The paper shows the importance of initialization conditions for resistive opens and the importance of noise margins with resistive bridges. These noise margin considerations throw doubts on the idea used by other authors of the "critical resistance" of a bridge.

54 citations

Proceedings ArticleDOI
01 Jan 1999
TL;DR: In this paper, the authors derived the optimal stochastic fault detection filter by keeping the ratio of the transmission from nuisance fault to target fault small, and showed that this filter approximates the properties of the classical fault detection filtering, such that in the limit where the ratio between the transmissions is zero, the optimal fault detector is equivalent to the unknown input observer if all invariant zero directions are included with the nuisance fault directions.
Abstract: Properties of the optimal stochastic fault detection filter for fault detection and identification are determined. The objective of the filter is to monitor certain faults called target faults and block other faults which are called nuisance faults. This filter is derived by keeping the ratio of the transmission from nuisance fault to the transmission from target fault small. It is shown that this filter approximates the properties of the classical fault detection filter such that in the limit where the ratio of the transmissions is zero, the optimal stochastic fault detection filter is equivalent to the unknown input observer if all invariant zero directions are included with the nuisance fault directions. Detection filter designs can be obtained for both linear time-invariant and time-varying systems.

54 citations

Journal ArticleDOI
TL;DR: The proposed fault diagnosis system study and analysis is proposed using a unified graphical tool such as Bond Graph tool, used for system modeling, structural analysis and fault diagnosis conclusions, and it is shown that the monitorability analysis using bond graph is automatically deduced using this unified tool, with respect to the detectability and isolability conditions.
Abstract: The present paper deals with bond graph model-based for structural component fault detection and isolation. The structural conditions of fault detectability and isolability are obtained directly from the bond graph using the properties of the bicausality and the causal path. It is shown that the monitorability analysis using bond graph is automatically deduced using this unified tool, with respect to the detectability and isolability conditions. A real mechatronic system application of intelligent autonomous vehicle is given to show the efficiency and the simplicity analysis of the proposed approach. This paper was motivated by the problem of integrated design of a fault diagnosis system by considering both, system instrumentation and the set of specifications regarding faults. Existing methods dealing with such problems are based mainly on the existing system instrumentation. In this paper, a fault diagnosis system study and analysis is proposed. This is done by using a unified graphical tool such as Bond Graph tool which is used for system modeling, structural analysis and fault diagnosis conclusions. Therefore, system modeling, fault monitorability analysis, and fault indicator generation are all performed by using the same graphical tool. In addition, the proposed method may be exploited for monitorability analysis before industrial design, i.e., ability to detect and isolate faults with given instrumentation architecture and how to make faulty components monitorable by adding new sensors. To show the effectiveness of the proposed method, an application on real mechatronic system is considered.

54 citations

Journal ArticleDOI
TL;DR: Experimental and simulation results show the effectiveness of the proposed fault-tolerant topology and its FPGA-based control.
Abstract: Fast fault detection and reconfiguration of power converters is necessary in electrical drives to prevent further damage and to make the continuity of service possible. On the other hand, component minimized converters may provide the benefits of higher reliability and less volume and cost. In this paper, a new fault-tolerant converter topology is studied. This converter has five legs before the fault occurrence, and after fault detection the converter continues to function with four legs. A very fast fault detection and reconfiguration scheme is presented and studied. Simulations and experimental tests are performed to evaluate the structure requirements, the digital reconfigurable controller, and fault detection scheme. For experimental tests, the control and the fault detection and reconfiguration schemes are implemented on a single field-programmable gate array (FPGA) chip. Experimental and simulation results show the effectiveness of the proposed fault-tolerant topology and its FPGA-based control.

54 citations

Journal ArticleDOI
TL;DR: An integrated method for the detection and isolation of incipient faults in common field devices, such as sensors and actuators, using plant operational data using principal component analysis (PCA), a multivariate data-driven technique, is presented.
Abstract: 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.

54 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202381
2022215
202127
202061
2019116
2018160