复解析最优小波解调法  

Optimization of Complex Analytical Wavelet Demodulation

作　　者：刘小峰[1] 张开飞[1] 赵玲[2] 

机构地区：[1]重庆大学机械传动国家重点实验室,重庆400044 [2]重庆交通大学信息科学与工程学院,重庆400044

出　　处：《振动．测试与诊断》2012年第5期741-745,860-861,共5页Journal of Vibration,Measurement & Diagnosis

基　　金：国家自然科学基金资助项目(编号:51005261);重庆大学211工程资助项目(编号:S-09106)

摘　　要：针对齿轮箱故障信号的多分量多频调制特点,结合基于复解析小波变换的信号分量的包络幅值提取原理,提出了一种基于峭度和平滑指数的最优小波解调技术。首先,采用连续小波变换谱的能量熵作为时间尺度分辨率的度量指标,将其应用到Morlet分析小波的参数优化选择中;其次,对常规小波峭度计算法进行改进,结合平滑指数对最优小波变化尺度进行迭代搜索;最后,针对解调谱线繁杂密集无法分辨的问题,采用频谱细化的方法提高了复解析小波解调谱的频谱精度。应用试验结果表明,该复解析最优小波解调方法较传统的解调方法,可以更加准确有效地提出齿轮箱复杂信号中的微弱故障特征。In order to analyze the multi-component and multi-modulation characteristics of gearbox fault signal, an optimal wavelet demodulation method based on kurtosis and smoothness index is proposed. In this method, Morlet wavelet transform is used as an adaptive band-pass filter to extract the envelope amplitude of impact component in gearbox vibration signal. The energy entropy is used as wavelet time-scale resolution index to optimize the Morlet wavelet parameters. The improved kurtosis and smoothness index of wavelet coefficient is utilized to determine the optimal wavelet coefficient. In allusion to the complexity and denseness problem of demodulated frequencies, The Zoom-FFT technology is exploited to improve the preciseness of demodulation spectrum. The experimental results show that the method proposed can more accurately and more effectively extract the fault characteristic hidden in gearbox vibration signal, comparing with the traditional wavelet demodulation method.

关 键 词：连续小波变换 能量熵 谱峭度 平滑指数 故障诊断 

分 类 号：TH115[机械工程—机械设计及理论] TP395.02[自动化与计算机技术—计算机应用技术]