双树复小波域隐Markov树模型降噪及在机械故障诊断中的应用

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振动与冲击 ›› 2011, Vol. 30 ›› Issue (6) : 47-52.

论文

双树复小波域隐Markov树模型降噪及在机械故障诊断中的应用

苏文胜;王奉涛;朱泓;张志新;李宏坤;郭正刚

作者信息 +

Denoising method based on hidden Markov tree model in dual tree complex wavelet domain and its application in mechanical fault diagnosis

Su Wen-sheng; Wang Feng-tao; Zhu Hong;Zhang Zhixin;Li Hongkun;Guo Zhenggang

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文章历史 +

摘要

提出一种基于双树复小波变换的隐Markov树模型的信号降噪方法，并将其成功应用于机械故障诊断中。机械设备的振动信号中不可避免的存在着噪声，使得微弱故障信息的提取一直是故障诊断的难点和热点。双树复小波变换具有近似平移不变性，而隐Markov树模型能有效刻画小波系数间的相关性和非高斯性，两种优势的结合可以获得比常规软、硬阈值小波降噪法和小波域隐Markov树模型降噪法更好的降噪效果。它不仅能有效抑制高斯白噪声，还能够去除异常冲击干扰，仿真信号验证了这一点。对于实际滚动轴承信号，使用该方法同样可以获得满意的结果

Abstract

A denoising method based on hidden Markov tree model in dual tree complex wavelet domain is proposed, and it is successfully applied in mechanical fault diagnosis. Noise is inevitably present in mechanical vibration signal, which makes the extraction of weak fault information be the difficulty and hotspot of fault diagnosis. Since dual tree complex wavelet transform has the approximate translation invariance while hidden Markov tree model can effectively describes the dependency between wavelet coefficients and the non-Gaussian nature of these coefficients, a method combining these advantages can achieve better denoising results than that of conventional soft or hard threshold denoising and hidden Markov tree model in wavelet domain. Applications of simulation signals verify that Gaussian white noise can be effectively inhibited, as well as abnormal impact can be removed by using this method. For actual rolling bearing signal, satisfied result also can be acquired

导出引用

苏文胜;王奉涛;朱泓;张志新;李宏坤;郭正刚. 双树复小波域隐Markov树模型降噪及在机械故障诊断中的应用[J]. 振动与冲击, 2011, 30(6): 47-52

Su Wen-sheng;Wang Feng-tao;Zhu Hong;Zhang Zhixin;Li Hongkun;Guo Zhenggang. Denoising method based on hidden Markov tree model in dual tree complex wavelet domain and its application in mechanical fault diagnosis[J]. Journal of Vibration and Shock, 2011, 30(6): 47-52