关键词: 振动与波, 经验小波变换, 自适应性, 形态学滤波, 故障诊断

Abstract:

According to the non-linear and non-stationary characteristic of reciprocating compressor vibration signal, a fault feature extraction method based on adaptive empirical wavelet transform and mathematical morphology filtering is proposed. The method begin with using empirical wavelet transform, adaptively segments the Fourier spectrum by extracting the scale-space curve to separate the different modes, and then constructs adaptive band-pass filters in the frequency domain so as to construct orthogonal wavelet functions and extract AM-FM components that have compact support in Fourier spectrum. After segmenting the Fourier spectrum, the method filters the AM-FM components based on mathematical morphological. Different from other method, the structure elements in this paper are constructed according to the impact characteristics of reciprocating compressor. At last the method quantitatively analyzes AM-FM components by using the multiscale fuzzy entropy in order to identify and classify the fault of reciprocating compressor. Experiments and calculation results prove that this method can effectively diagnose the fault of reciprocating compressor.