Application of optimized multiscale mathematical morphology for bearing fault diagnosis

Abstract

In order to suppress noise effectively and extract the impulsive features in the vibration signals of faulty rolling element bearings, an optimized multiscale morphology (OMM) based on conventional multiscale morphology (CMM) and iterative morphology (IM) is presented in this paper. Firstly, the operator used in the IM method must be non-idempotent; therefore, an optimized difference (ODIF) operator has been designed. Furthermore, in the iterative process the current operation is performed on the basis of the previous one. This means that if a larger scale is employed, more fault features are inhibited. Thereby, a unit scale is proposed as the structuring element (SE) scale in IM. According to the above definitions, the IM method is implemented on the results over different scales obtained by CMM. The validity of the proposed method is first evaluated by a simulated signal. Subsequently, aimed at an outer race fault two vibration signals sampled by different accelerometers are analyzed by OMM and CMM, respectively. The same is done for an inner race fault. The results show that the optimized method is effective in diagnosing the two bearing faults. Compared with the CMM method, the OMM method can extract much more fault features under strong noise background.