期刊
IEEE TRANSACTIONS ON FUZZY SYSTEMS
卷 27, 期 7, 页码 1362-1382出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TFUZZ.2018.2878200
关键词
Bearing; fault classification; fault detection; fault diagnosis; fuzzy entropy; fault prognosis; fuzzy clustering; fuzzy rules
资金
- Prometeo Project of SENESCYT, Ecuador
- National Key Research and Development Program, China [2016YFE0132200]
- FCT, Portugal [SFRH/BSAB/128153/2016]
- Fundação para a Ciência e a Tecnologia [SFRH/BSAB/128153/2016] Funding Source: FCT
Bearings are fundamental mechanical components in rotary machines (engines, gearboxes, generators, radars, turbines, etc.) that have been identified as one of the primary causes of failure in these machines. This makes bearing fault diagnosis (detection, classification, and prognosis) an economic very relevant topic, as well as a technically challenging one as evaluated by the extensive research literature on the subject. This paper employs a systematic methodology to identify, summarize, analyze, and interpret the primary literature on fuzzy formalisms for bearing fault diagnosis from 2000 to 2017 (March). The main contribution is an updated, unbiased, and (to a higher extend) repeatable search, review, and analysis (summary, classification, and critique) of the available approaches resorting to fuzzy formalisms in this trendy topic. A discussion on a new promising future research direction is provided. A comprehensive list of references is also included.
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