Directional expansion‐based fault diagnosis algorithm using orthotopic and ellipsoidal filtering

Liu, Zixing; Wang, Ziyun; Yan, Wang; Park, Ju H.; Ji, Zhicheng

doi:10.1049/iet-cta.2020.0029

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2021

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“…[1] and the references therein). Generally, the fault diagnosis approaches can be classified to time-driven [1][2][3][4][5] and event-driven [6] approaches. Timedriven approaches can diagnose a fault occurrence by analyzing the states of the system based on the information received from the observation of the system's degraded performance over time [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

An inferencing structure for MPO‐based decentralized dynamic fault diagnosis

Khaleghi

Yazdi

Karimoddini

et al. 2021

IET Control Theory & Appl

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This paper addresses the problem of fault diagnosis in discrete event systems through a decentralized structure. Within the proposed decentralized diagnosis structure, local most permissive bbservers (MPOs) are employed as diagnosis tools, and an effective protocol is proposed to coordinate local MPOs to infer diagnosis information. It is shown that the proposed technique can diagnose fault occurrences subjected to proper sensing decisions.A sufficient condition on sensing decision policies is derived for diagnosis of faults in a decentralized setting. Further, it is proven that the proposed decentralized structure has less complexity than a centralized structure. The details of the proposed technique are illustrated by applying the developed method to a manufacturing system.

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