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A Systematic Review of Fuzzy Formalisms for Bearing Fault Diagnosis.

, , , , , and . IEEE Trans. Fuzzy Syst., 27 (7): 1362-1382 (2019)

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Observer-biased bearing condition monitoring: From fault detection to multi-fault classification., , , , , , and . Eng. Appl. Artif. Intell., (2016)Multi-Stage Feature Selection by Using Genetic Algorithms for Fault Diagnosis in Gearboxes Based on Vibration Signal., , , , and . Sensors, 15 (9): 23903-23926 (2015)A Systematic Review of Fuzzy Formalisms for Bearing Fault Diagnosis., , , , , and . IEEE Trans. Fuzzy Syst., 27 (7): 1362-1382 (2019)Hierarchical feature selection based on relative dependency for gear fault diagnosis., , , , , and . Appl. Intell., 44 (3): 687-703 (2016)Fuzzy determination of informative frequency band for bearing fault detection., , , , , and . J. Intell. Fuzzy Syst., 30 (6): 3513-3525 (2016)Fault Diagnosis for Rotating Machinery Using Vibration Measurement Deep Statistical Feature Learning., , , , and . Sensors, 16 (6): 895 (2016)Multimodal deep support vector classification with homologous features and its application to gearbox fault diagnosis., , , , , and . Neurocomputing, (2015)A statistical comparison of neuroclassifiers and feature selection methods for gearbox fault diagnosis under realistic conditions., , , , , , , and . Neurocomputing, (2016)