Fault detection and isolation in the presence of process uncertainties

Han, Zhengang; Li, Weihua; Shah, Sirish L.

doi:10.1016/j.conengprac.2004.04.020

Cited by 47 publications

(24 citation statements)

References 30 publications

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“…When residuals are assumed normally distributed around a known average statistical methods to generate normal operating thresholds are well suited (Basseville et al, 1987). In the event that the uncertainty does not operate at the same frequency as defects, filtering methods are suitable property (Han et al, 2002). While the actuators and sensors faults are determined using parity space (Henry et al, 2001;Henry and Zolghari, 2006).…”

Section: Analysis Of Residuals Sensitivitymentioning

confidence: 99%

Robust Diagnosis of a DC Motor by Bond Graph Approach

Sallami¹,

Zanzouri²,

Ksouri³

2016

American Journal of Engineering and Applied Sciences

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In this article, a Bond Graph (BG) approach is used for modeling, simulation and robust diagnosis of a DC Motor. The design and calculation of an observer is achieved by using graphical methods taking advantage of the structural properties of bond graph model. Simulation results are used to show the dynamic behavior of the system variables and assessing the performance of the observer. A modeling Bond Graph form Linear Fractional Transformations (BG-LFT) to generate constituted Analytical Redundant Relationship (ARR) two parts perfectly separated: A nominal portion denotes the residual and an uncertain part, which serves both to the calculation of adaptive thresholds for normal operation and to sensitivity analysis.

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Section: Analysis Of Residuals Sensitivitymentioning

confidence: 99%

Robust Diagnosis of a DC Motor by Bond Graph Approach

Sallami¹,

Zanzouri²,

Ksouri³

2016

American Journal of Engineering and Applied Sciences

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“…Through splitting X, X1 U X2 = X, we can rewrite (8) Rf (X) C fR (Xi) U fR (X2) C fR (X), (9) To put an end to the splitting algorithm in (9), we introduce an internal estimate, Yrin (t) C Yr (t). If Ym(t) n Yri (t) 7t 0, then, logically we can expect that Ym(t)nYr(t) :t 0.…”

Section: Yr(t))mentioning

confidence: 99%

“…In fact, not only uncertainties exist in the analytical model A. Khosravi, J. Armengol and E. R. Gelso are with the Institut d'Informatica i Aplicacions, Universitat de Girona, E-17071 Girona, Catalonia, Spain {khosravi,armengol,ergelso}@eia.udg.es of the system owing some complicacy in modeling, but also they influentially mischievously impress measurements. A countless number of researchers have devoted a great deal of effort and time in last decades to deal with these uncertainties and confine their negative effects on fault detection and false alarm rates [5], [6], [7], [8], [9], [10].…”

Section: Introductionmentioning

confidence: 99%

An Interval Intelligent-based Approach for Fault Detection and Modelling

Khosravi

Llobet

Gelso

2007

2007 IEEE International Fuzzy Systems Conference

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Abstract-Not considered in the analytical model of the plant, uncertainties always dramatically decrease the performance of the fault detection task in the practice. To cope better with this prevalent problem, in this paper we develop a methodology using Modal Interval Analysis which takes into account those uncertainties in the plant model. A fault detection method is developed based on this model which is quite robust to uncertainty and results in no false alarm. As soon as a fault is detected, an ANFIS model is trained in online to capture the major behavior of the occurred fault which can be used for fault accommodation. The simulation results understandably demonstrate the capability of the proposed method for accomplishing both tasks appropriately.

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“…PROPOSED MAPPING SCHEME Our main objective is to take advantage of the hierarchical synchrophasor structure to monitor the network at lower PDC levels with the capability of identifying buses/lines that suffer from power disturbances such as faults or voltage instability. Numerous researches has been carried out in the field of fault detection and control [5,6,7]. However, most of the works are performed in centralized manner.…”

Section: Introductionmentioning

confidence: 99%

Distributed Control and Communications for Grid Systems

Gharavi

2016

2016 IEEE Global Communications Conference (GLOBECOM)

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Abstract-A major problem of the grid system is identifying the source of abnormal behaviors. It is particularly important to identify the areas in which the grid system suffers from power deficiencies due to fault or voltage instability. Phasor Measurement Units (PMUs) are capable of measuring current and voltage amplitudes and phase angles, which can then be effectively used to monitor the power quality. This would require the support of a communication network to detect regions in the grid that may suffer from voltage instability. In this paper we present a distributed mapping technique that is based on a hierarchical network structure to identify the proximity of the grid instability for any possible remedial control action at the local level. For voltage monitoring, we also develop an average standard deviation measurement technique to access the power quality. We use the IEEE 34 bus grid distribution model and the IEEE 39 bus transmission model to assess the performance of the proposed techniques.

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Fault detection and isolation in the presence of process uncertainties

Cited by 47 publications

References 30 publications

Robust Diagnosis of a DC Motor by Bond Graph Approach

Robust Diagnosis of a DC Motor by Bond Graph Approach

An Interval Intelligent-based Approach for Fault Detection and Modelling

Distributed Control and Communications for Grid Systems

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