| 连续小波变换在机械故障特征提取中的应用 |
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| 引用本文： | 张澎涛,刘晋浩. 连续小波变换在机械故障特征提取中的应用[J]. 吉林大学学报(信息科学版), 2014, 32(2): 172-176 |
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| 作者姓名： | 张澎涛 刘晋浩 |
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| 作者单位： | 1. 东北林业大学 机电工程学院, 哈尔滨 150040; 2. 北京林业大学 工学院,北京 100083 |
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| 基金项目： | 引进国际先进林业科学技术“948”基金资助项目（2013-4-20） |
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| 摘 要： | 为解决提取齿轮故障特征时去除外部噪声的问题, 以连续小波变换和自相关系数法为理论依据, 以缺齿齿轮故障为例, 提出了一种齿轮故障诊断方法。该方法能从所测量的含噪信号中确定出故障脉冲所对应的时间节点。利用多通带滤波器进行滤波处理, 可以从提取的故障特征中有效地剔除寄生脉冲。实验表明, 该方法能准确识别断齿振动信号的故障特征。
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| 关 键 词： | 连续小波变换 自相关系数 齿轮 故障诊断 特征提取 |
Application of CWT in Mechanical Fault Feature Extraction |
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| ZHANG Pengtao,LIU Jinhao. Application of CWT in Mechanical Fault Feature Extraction[J]. Journal of Jilin University:Information Sci Ed, 2014, 32(2): 172-176 |
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| Authors: | ZHANG Pengtao LIU Jinhao |
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| Affiliation: | 1. College of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, China;2. College of Engineering, Beijing Forestry University, Beijing 100083, China |
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| Abstract: | In order to solve the problem that can not denoising the external noise when extracting fault feature of gear,this paper introduces a method that can identify the time of periodic impulsive fault signatures from the measured noisy signal mixture on the basis of CWT （Continuous Wavelet Transfon） and auto-correlation coefficient method.A comb filter can be applied to extract fault features in time-scale domain,the spurious impulses can be removed effectively from the extracted fault feature.Experiments show that this method can accurately identifiy the fault feature of impulsive signals with missing tooth. |
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| Keywords: | continuous wavelet transfon （CWT） autocorrelation coefficient gear fault diagnosis feature extraction |
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