形态非抽样小波及其在冲击信号特征提取中的应用

针对形态小波分解过程的抽样引起信号长度逐层递减的问题,提出一种基于多尺度Top-Hat变换的形态非抽样小波构造方法。利用形态非抽样小波的一般框架,分别采用形态学开运算和多尺度Top-Hat变换作为形态非抽样小波分解的近似信号和细节信号的分析算子,使形态小波分解过程中信号长度保持不变,从而保证了形态分析时所需的信息量。结合转子振动冲击特征信号提取试验,验证所提方法在故障诊断中应用的可行性与有效性。

MORPHOLOGICAL UNDECIMATED WAVELET AND ITS APPLICATION TO FEATURE EXTRACTION OF IMPULSIVE SIGNAL

To avoid the decrease in signal length in morphological wavelet decomposition, a novel morphological undecimated wavelet (MUDW) based on multi-scale Top-Hat transformation is proposed. Morphological opening operator and multi-scale Top-Hat transformation are adopted as a signal analysis operator and a detail analysis operator under a MUDW framework to ensure an invariant signal length and sufficient signal information in morphological wavelet decomposition. The proposed MUDW is also examined by vibration signals of a rotor with impulsive feature. The results confirm that the proposed MUDW is feasible and effective in fault diagnosis.