Resilient Fault Diagnosis Under Imperfect Observations–A Need for Industry 4.0 Era

doi:10.1109/JAS.2020.1003333

CASIA OpenIR > 学术期刊 > IEEE/CAA Journal of Automatica Sinica

	Resilient Fault Diagnosis Under Imperfect Observations–A Need for Industry 4.0 Era
	Alejandro White; Ali Karimoddini; Mohammad Karimadini
发表期刊	IEEE/CAA Journal of Automatica Sinica
ISSN	2329-9266
	2020
卷号	7 期号:5 页码:1279-1288
摘要	In smart industrial systems, in many cases, a fault can be captured as an event to represent the distinct nature of subsequent changes. Event-based fault diagnosis techniques are capable model-based methods for diagnosing faults from a sequence of observable events executed by the system under diagnosis. Most event-based diagnosis techniques rely on perfect observations of observable events. However, in practice, it is common to miss an observable event due to a problem in sensor-readings or communication/transmission channels. This paper develops a fault diagnosis tool, referred to as diagnoser, which can robustly detect, locate, and isolate occurred faults. The developed diagnoser is resilient against missed observations. A missed observation is detected from its successive sequence of events. Upon detecting a missed observation, the developed diagnoser automatically resets and then, asynchronously resumes the diagnosis process. This is achieved solely based on post-reset/activation observations and without interrupting the performance of the system under diagnosis. New concepts of asynchronous detectability and asynchronous diagnosability are introduced. It is shown that if asynchronous detectability and asynchronous diagnosability hold, the proposed diagnoser is capable of diagnosing occurred faults under imperfect observations. The proposed technique is applied to diagnose faults in a manufacturing process. Illustrative examples are provided to explain the details of the proposed algorithm. The result paves the way towards fostering resilient cyber-physical systems in Industry 4.0 context.
关键词	Cyber-physical systems discrete event systems fault diagnosis imperfect communication imperfect observation Industry 4.0 resilience
DOI	10.1109/JAS.2020.1003333
引用统计	被引频次：27[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/43034
专题	学术期刊_IEEE/CAA Journal of Automatica Sinica
推荐引用方式 GB/T 7714	Alejandro White,Ali Karimoddini,Mohammad Karimadini. Resilient Fault Diagnosis Under Imperfect Observations–A Need for Industry 4.0 Era[J]. IEEE/CAA Journal of Automatica Sinica,2020,7(5):1279-1288.
APA	Alejandro White,Ali Karimoddini,&Mohammad Karimadini.(2020).Resilient Fault Diagnosis Under Imperfect Observations–A Need for Industry 4.0 Era.IEEE/CAA Journal of Automatica Sinica,7(5),1279-1288.
MLA	Alejandro White,et al."Resilient Fault Diagnosis Under Imperfect Observations–A Need for Industry 4.0 Era".IEEE/CAA Journal of Automatica Sinica 7.5(2020):1279-1288.

条目包含的文件		下载所有文件
文件名称/大小	文献类型	版本类型	开放类型	使用许可
JAS-2020-0510.pdf（6170KB）	期刊论文	出版稿	开放获取	CC BY-NC-SA	浏览下载