Chuan LiJosé Valente de OliveiraMariela CerradaDiego CabreraRené–Vinicio SánchezGrover Zurita2026-03-222026-03-22201810.1109/tfuzz.2018.2878200https://doi.org/10.1109/tfuzz.2018.2878200https://andeanlibrary.org/handle/123456789/85555Citaciones: 138Bearings 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.enRotation formalisms in three dimensionsBearing (navigation)Fuzzy logicComputer scienceFault (geology)Data miningArtificial intelligenceMachine learningreview