Resilient Fault Diagnosis Under Imperfect Observations–A Need for Industry 4.0 Era
文献类型：期刊论文
| 作者 | Alejandro White; Ali Karimoddini; Mohammad Karimadini |
| 刊名 | IEEE/CAA Journal of Automatica Sinica
 |
| 出版日期 | 2020 |
| 卷号 | 7期号:5页码:1279-1288 |
| 关键词 | Cyber-physical systems discrete event systems fault diagnosis imperfect communication imperfect observation Industry 4.0 resilience |
| ISSN号 | 2329-9266 |
| DOI | 10.1109/JAS.2020.1003333 |
| 英文摘要 | 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. |
| 源URL | [http://ir.ia.ac.cn/handle/173211/43034]  |
| 专题 | 自动化研究所_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. |
入库方式： OAI收割
来源：自动化研究所
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