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In view of the lack of effective model and the large prediction error in the traditional prediction methods, a collaborative prediction method for remaining useful life of bearing based on DNN and GBDT is proposed. Firstly, the degradation characteristics are constructed through normalization processing of parameters in time domain and frequency domain that can clearly represent the healthy running state of bearings, in order to improve the correlation of degradation characteristics, the priordoi:10.17762/converter.96 fatcat:pkygskbd4bdh5euf73hqb746j4