A novel deep stacking least squares support vector machine for rolling bearing fault diagnosis

•A novel deep model, called DSLS-SVM, is proposed for rolling bearing fault diagnosis.•The measured vibration signals are used as the input of DSLS-SVM without manual domain-specific engineering.•The proposed method can extract intrinsic feature from measured vibration signal.•The experiment results show that the proposed method has a good effectiveness in rolling bearing fault diagnosis.