Studies from Shenyang University of Chemical Technology in the Area of Networks Reported (Rolling Bearing Compound Fault Diagnosis Based On Parameter Optimization Mckd and Convolutional Neural Network)

摘要

By a News Reporter-Staff News Editor at Network Daily News – Investigators discuss new findings in Networks. According to news originating from Shenyang, People’s Republic of China, by NewsRx correspondents, research stated, “For the sake of solving the problem of the difficulty of extracting fault features under the background of noise and accurately identify the state of the bearing, a compound fault diagnosis method of rolling bearing based on parameter optimization maximum correlated kurtosis deconvolution (MCKD) and convolutional neural network (CNN) is proposed. First, the adaptive multi-strategy cuckoo search algorithm (MSACS) is used to iteratively optimize the important parameters of MCKD.”