An optimal selection method for morphological filter’s parameters and its application in bearing fault diagnosis

Abstract

The Mathematical morphological filter (MMF) is widely applied in vibration signal processing for fault diagnosis. The Structure element (SE) and the cutoff frequency of filter have important impacts on the filtering effect, but there is no selection principle of these parameters for vibration signal processing in fault diagnosis. In this paper, the working mechanism of the MMF is studied, and a novel technique with filter characteristics and selection criterion of the MMF is proposed. The filter characteristics of morphological filter are described through frequency response analysis. The relationship between the SE length and the cutoff frequency of MMF is put forward, and the quantitative selection method of SE in engineering is proposed to effectively remove the noise and detect the impulses. The method is evaluated using both simulated signal and experimental bearing vibration signal. The results show that quantized selection method can make MMF have the better filtering effect, and can reliably extract impulsive features for bearing defect diagnosis. The study provides a theoretical basis for the application of MMF in vibration signal processing.