Study On The Application Of Mathematical Morphology In Vibration Signal Processing

The vibration signal containing a wealth of information such as fault features and the state of equipment is the important information sources of machinery condition monitoring and fault diagnosis. Analysis of vibration signals is an important fault diagnosis method. Mathematical morphology based on time-domain provides a nonlinear analysis method for the vibration signal processing. Compared with the traditional methods, morphological method has better signal processing result, faster calculating speed, so it is more suitable for fault diagnosis. A quantitative description of mathematical morphological filter’s characteristics is given, and the operation principle and unified application criterion are revealed. Based on the analysis of current application of mathematical morphology, the morphological methods used for fault feature extraction are analyzed. The innovations include:(1) This paper investigates the frequency response characteristics of the mathematical morphological filter and meanwhile presents the filters’ normalized cutoff frequency of different structural element widths and the functional relation between structural element width and cutoff frequency. Through analyzing the quantitative relationship between the structural element widthu sampling frequency、analyzing points and filtering feature, a quantitative description of mathematical morphological filter’s characteristics is given. The research indicates, when the sampling frequency is fixed, as the width of the structure element increases, the cutoff frequency decreases. And the shift of the cutoff frequency gets smaller as the arithmetic growth of the structure element’s width; when the width of the structure element is fixed, as the sampling frequency increases, the cutoff frequency increases, and the sampling frequency varies directly with the cutoff frequency. The comparative test with IIR filter shows that the morphological filter gets better noise suppressing result and keeps the phase of the original signal.(2) The morphological methods applied in the vibration signal fault feature extraction are summarized, and the characteristics of these methods are analyzed. Based on the analysis of these methods’implementation principle and frequency response characteristics, through the simulation analysis, the advantages and defects of the current methods are pointed out, and relevant suggestions are given.(3) The mathematical morphological method is applied in the actual vibration signal, through the faults example, the effectiveness of the mathematical morphological methods in vibration signal processing is verified.