Bearing quantitative diagnosis method based on morphological filtering and complexity measure

The invention relates to a bearing quantitative diagnosis method based on morphological filtering and complexity measure, comprising the following steps: firstly selecting Morlet wavelet and Laplace wavelet as the structural elements of a morphological filter; utilizing morphological filtering method based on immue optimization to carry out time domain filtering processing on vibration signal of a rolling bearing obtained through collection; and then adopting an algorithm based on improved complexity measure to carry out quantitative evaluation on the vibration signal of the rolling bearing after filtering. According to the method, the fault grade of the rolling bearing is evaluated from a qualitative angle, and the bearing data processed through complexity measure has the characteristic of monotonicity and can be used for indicating the real-time running state of the bearing to monitor; and therefore, the accuracy of the fault diagnosis of the rolling bearing is improved, and the on-site maintenance is facilitated.