A Systematic Review of Fuzzy Formalisms for Bearing Fault Diagnosis
| Autor: | Grover Zurita, Mariela Cerrada, José Valente de Oliveira, René-Vinicio Sánchez, Chuan Li, Diego Cabrera |
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| Rok vydání: | 2019 |
| Předmět: |
Bearing (mechanical)
Computer science business.industry Applied Mathematics Feature extraction 02 engineering and technology Fuzzy control system Machine learning computer.software_genre Mechanical components Rotation formalisms in three dimensions Fuzzy logic law.invention Computational Theory and Mathematics Artificial Intelligence Control and Systems Engineering law 0202 electrical engineering electronic engineering information engineering Entropy (information theory) Prognostics 020201 artificial intelligence & image processing Artificial intelligence business computer |
| Zdroj: | IEEE Transactions on Fuzzy Systems. 27:1362-1382 |
| ISSN: | 1941-0034 1063-6706 |
| DOI: | 10.1109/tfuzz.2018.2878200 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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