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Research and Application of Regularized Sparse Filtering Model for Intelligent Fault Diagnosis Under Large Speed Fluctuation
2020
IEEE Access
The speed of mechanical rotating parts often fluctuates during the working process. Vibration signals collected under constant speed have a strong correlation with the corresponding fault types. However, the mapping relationship becomes complex under large speed fluctuation, which is an urgent research subject in intelligent fault diagnosis. As an effective unsupervised learning method, sparse filtering (SF) has been successfully used in intelligent fault diagnosis. However, the generalization
doi:10.1109/access.2020.2975531
fatcat:wiglwfodvzhexdt63gfltkg7ty