Model-based fault diagnosis and prognosis of dynamic systems: a review

被引：17

作者：

Ekanayake, Thushara ^{[1
]}

Dewasurendra, Devapriya ^{[3
]}

Abeyratne, Sunil ^{[3
]}

Ma, Lin ^{[2
]}

Yarlagadda, Prasad ^{[2
]}

机构：

[1] Uva Wellassa Univ, Fac Sci & Technol, Badulla 90000, Sri Lanka

[2] Queensland Univ Technol, Fac Sci & Engn, Brisbane, Qld 4000, Australia

[3] Univ Peradeniya, Fac Engn, Peradeniya 20400, Sri Lanka

来源：

DIGITAL MANUFACTURING TRANSFORMING INDUSTRY TOWARDS SUSTAINABLE GROWTH | 2019年 / 30卷

关键词：

model-based systems; fault diagnosis; fault prognosis; automata; Petri nets; bond graphs; Bayesian networks; DISCRETE-EVENT SYSTEMS; DIAGNOSABILITY;

D O I：

10.1016/j.promfg.2019.02.060

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

In maintenance of engineering systems, condition monitoring, fault diagnosis and fault prognosis constitute some of the principal tasks. With the increase of the number of machines within processing plants and their operational complexities, many engineers and researchers have started looking for automated solutions for these tasks. In most of the proposed solutions, these dynamic systems are modelled using tools like automata, Petri nets, bond graphs and Bayesian networks to diagnose and predict faults in those systems. This paper reviews these graphical model-based techniques related to fault diagnosis and prognosis and give suggestions for future research directions identifying research gaps in the field. (C) 2019 The Authors. Published by Elsevier Ltd.

引用

页码：435 / 442

页数：8

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