A Novelty Detector and Extreme Verification Latency Model for Nonstationary Environments
Document Type
Article
Publication Date
1-1-2019
Publication Title
IEEE Transactions on Industrial Electronics
Volume
66
Issue
1
First Page
561
Keywords
Diagnostic systems, extreme verification latency (EVL), nonstationary environments, novelty detection
Last Page
570
Abstract
Safe and reliable operation of systems relies on the use of online condition monitoring and diagnostic systems that aim to take immediate actions upon the occurrence of a fault. Model-based solutions are often not practical in nonstationary environments. Thus, the evolving data stream requires the data-driven model to be adaptive. In this paper, we propose a framework for the fault detection and classification that is accomplished on the data stream with both the gradual and abrupt drifts. The framework is only provided with prior information about the possible faults at the initial step; however, despite this, the framework can still detect the novel faults without receiving any update. Furthermore, an efficient fault classification algorithm is presented to maximize the efficiency of the proposed framework. Finally, the proposed framework is applied for diagnosing bearing defects in the induction motors to demonstrate its feasibility for industrial applications.
DOI
10.1109/TIE.2018.2826477
ISSN
02780046
Recommended Citation
Razavi-Far, Roozbeh; Hallaji, Ehsan; Saif, Mehrdad; and Ditzler, Gregory. (2019). A Novelty Detector and Extreme Verification Latency Model for Nonstationary Environments. IEEE Transactions on Industrial Electronics, 66 (1), 561-570.
https://scholar.uwindsor.ca/electricalengpub/136