Analytic Redundancy, Possible Conflicts, and TCG-based Fault Signature Diagnosis applied to Nonlinear Dynamic Systems

Biswas, Gautam; Bregón, Aníbal; Koutsoukos, Xenofon; Pulido, Belarmino

doi:10.3182/20090630-4-es-2003.00242

Cited by 7 publications

(2 citation statements)

References 15 publications

(28 reference statements)

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“…In the work [28,29], the Temporal Causal Graph (TCG) was built based on the bond graph. The TCG allows the generation of fault signatures containing signs of impact and allows us to take into account the dynamic effects of faults.…”

Section: The Sequence Of Symptomsmentioning

confidence: 99%

Diagnostic Column Reasoning Based on Multi-Valued Evaluation of Residuals and the Elementary Symptoms Sequence

2022

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The paper concerns a significant problem in the diagnostics of industrial processes, which is the need to achieve high fault distinguishability. High distinguishability results in the generation of precise diagnoses that enable making appropriate security decisions. In the known approaches, the efforts to obtain high distinguishability are focused on the selection of an appropriate set of generated residuals. The paper presents a new method of diagnostic reasoning using the notation of faults/diagnostic signals’ relations in the form of a Fault Isolation System (FIS), which enables the use of multivalent diagnostic signals. In addition, the proposed method uses knowledge (usually incomplete) about the sequence of symptoms. Reasoning was carried out on the basis of simple, physically possible signatures, resulting from the FIS. Assumptions and a diagnostic algorithm are given. The reasoning algorithm works in a step-by-step manner, after observing further symptoms. In each reasoning step, two diagnoses are generated in parallel. A more accurate, but less certain diagnosis is formulated on the basis of the value of all diagnostic signals, and the diagnosis is less accurate, but more reliable, solely on the basis of symptoms. An example of using the method for diagnosing a set of connected liquid tanks is given. The method was compared with other reasoning methods based on columns (signatures) and, also, with row-based reasoning methods. It is shown that the proposed method allows the increase of the distinguishability of faults compared to other methods. The distinguishability grows with the knowledge of elementary symptom sequences. It is also noted that the proposed approach makes possible diagnosing not only faults, but also cyber attacks.

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Section: The Sequence Of Symptomsmentioning

confidence: 99%

Diagnostic Column Reasoning Based on Multi-Valued Evaluation of Residuals and the Elementary Symptoms Sequence

2022

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“…Jiang and Chowdhury (2005) utilized an adaptive observer to handle a fault distribution function. Biswas et al (2009) developed complementary approaches in fault detection and isolation in dynamic systems. 1 An adaptive threshold was generated in the research of Meseguer, Puig, and Escobet (2006) to evaluate the fault detection residual.…”

Section: Introductionmentioning

confidence: 99%

Model-based fault detection, estimation, and prediction for a class of linear distributed parameter systems

2016

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This paper addresses a new model-based fault detection, estimation, and prediction scheme for linear distributed parameter systems (DPSs) described by a class of partial differential equations (PDEs). An observer is proposed by using the PDE representation and the detection residual is generated by taking the difference between the observer and the physical system outputs. A fault is detected by comparing the residual to a predefined threshold. Subsequently, the fault function is estimated, and its parameters are tuned via a novel update law. Though state measurements are utilized initially in the parameter update law for the fault function estimation, the output and input filters in the modified observer subsequently relax this requirement. The actuator and sensor fault functions are estimated and the time to failure (TTF) is calculated with output measurements alone. Finally, the performance of detection, estimation and a prediction scheme is evaluated on a heat transfer reactor with sensor and actuator faults.

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SBG for Health Monitoring of Fuel Cell System

Ould-Bouamama

Chatti

Gehin

2014

ICREGA’14 - Renewable Energy: Generation and Applications

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Analytic Redundancy, Possible Conflicts, and TCG-based Fault Signature Diagnosis applied to Nonlinear Dynamic Systems

Cited by 7 publications

References 15 publications

Diagnostic Column Reasoning Based on Multi-Valued Evaluation of Residuals and the Elementary Symptoms Sequence

Diagnostic Column Reasoning Based on Multi-Valued Evaluation of Residuals and the Elementary Symptoms Sequence

Model-based fault detection, estimation, and prediction for a class of linear distributed parameter systems

SBG for Health Monitoring of Fuel Cell System

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