Failure Probability Modeling of Miniature DC Motors and Its Application in Fault Diagnosis. (8th October 2021)

• Record Type: Journal Article
• Authors: Xie, Zhiping; Zhao, Rongchen; Zheng, Jiming; Lang, Yancheng
• Other Names: Lallart Mickael Academic Editor.
• Is Part Of: Shock and vibration. Volume 2021(2021)
• Publication Date: 2021-10-08
• Subjects: Shock (Mechanics) -- Periodicals; Vibration -- Periodicals; 534.5
• DOI: 10.1155/2021/9958412
• Languages: English
• ISSNs: 1070-9622

Abstract

Abstract : This paper proposes a fault diagnosis method for miniature DC motors (MDCMs) in the presence of the uncertainties caused by material and random factors of the production process. In this method, the probability models of fault multiple features are established based on the advantage criterion of the maximum overall average membership to determine the distribution of fault multiple features. The fault diagnosis algorithm is synthesized to obtain the threshold ranges of fault multiple features according to different confidence levels. Experimental test results are presented and analyzed to validate the efficiency and performance of the proposed fault diagnosis method.