Complexity metrics for auto fault diagnosis based on information entropy

Ying Cheng, Zhiwei Guan, Honglin Zhao

Research output: Contribution to journalConference articlepeer-review

Abstract

Due to plenty of advanced and electronic technology used in the modern auto, the modern auto maintenance workload should consider the influence of the fault diagnosis complexity on maintenance man hour, so it is necessary and valuable to evaluate the complexity of the auto fault diagnosis. In this paper, the method of complexity assessment of auto fault diagnosis is discussed by using the information entropy. Firstly, the theory of complexity measurement based on information entropy is introduced, and then the complexity assessment index and the calculation process are shown. Finally, take the engine overheating fault for example, the hierarchy structure of this fault diagnosis is analyzed, and the complexity value of this fault diagnosis based on information entropy is obtained. The results show that this assessment method has a certain practicality and feasibility, which could be utilized to optimize the auto fault diagnosis strategy and maintenance work arrangement.

Original languageEnglish
Article number062147
JournalIOP Conference Series: Materials Science and Engineering
Volume392
Issue number6
DOIs
Publication statusPublished - 3 Aug 2018
Externally publishedYes
Event2018 International Conference on Manufacturing Technology, Materials and Chemical Engineering, MTMCE 2018 - Zhuhai, China
Duration: 22 Jun 201824 Jun 2018

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