An enhanced methodology of Fault Detection and Diagnosis based on Digital Twin

被引：5

作者：

Abdoune, Farah ^{[1
]}

Nouiri, Maroua ^{[1
]}

Cardin, Olivier ^{[1
]}

Castagna, Pierre ^{[1
]}

机构：

[1] Nantes Univ, Ecole Cent Nantes, CNRS, UMR 6004,LS2N, F-44000 Nantes, France

来源：

IFAC PAPERSONLINE | 2022年 / 55卷 / 19期

关键词：

Digital Twin; Fault detection; Fault diagnosis; monitoring; supervision; MANAGEMENT; KNOWLEDGE;

D O I：

10.1016/j.ifacol.2022.09.181

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Digital Twins (DT) have been used in a variety of industrial sectors and application areas in recent years. To avoid downtime and problems in manufacturing, DTs strive for real-time monitoring and optimization and anticipate the future status of the physical twin. Fault Detection and Diagnosis (FDD) is a maintenance field that has attracted the interest of the control and automation community as a viable means of ensuring the dependability and safety of industrial systems. An enhanced FDD methodology thought DT can provide significant benefits. The main contribution of this research focuses on the exploration of DT for FDD methodology and provides also a guideline of different alternatives in each step and highlights the importance of DT. Copyright (C) 2022 The Authors.

引用

页码：43 / 48

页数：6

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