المؤلفون: Sheng Liu, Yue Sun, Lanyong Zhang

المصدر: The Journal of Engineering (2018)

مصطلحات موضوعية: genetic algorithms, acoustic signal processing, cerebellar model arithmetic computers, rolling bearings, neurocontrollers, mechanical engineering computing, white noise, vibrations, machine bearings, fault diagnosis, fault diagnosis approach, noise-assisted multivariate empirical mode decomposition, fuzzy recurrent cerebellar model articulation controller neural networks, artificial experience, genetic algorithm, auxiliary white noise parameters, FRCMAC structure, fuzzy processing, input space, association degree, Gaussian function, association unit, autoregressive unit, dynamic mapping, traditional CMAC structure, GA-NA-MEMD method, intrinsic mode functions, IMFs, fault feature vectors, FRCMAC neural network, neural network structure suitable, bearing fault diagnosis, Bearing Data Center, fault diagnosis method, diagnosis time, precision, fault diagnosis results, Engineering (General). Civil engineering (General), TA1-2040

وصف الملف: electronic resource

Relation: https://digital-library.theiet.org/content/journals/10.1049/joe.2018.8991; https://doaj.org/toc/2051-3305

URL الوصول: https://doaj.org/article/b4bc21ecf50c46a6a826f5ef6d40944a