| 形态小波降噪方法在齿轮故障特征提取中的应 |
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| 引用本文： | 沈路,周晓军,刘莉,杨富春. 形态小波降噪方法在齿轮故障特征提取中的应[J]. 农业机械学报, 2010, 41(4): 217-221. DOI: 10.3969/j.issn.1000-1298.2010.04.044 |
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| 作者姓名： | 沈路 周晓军 刘莉 杨富春 |
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| 作者单位： | 1. 浙江大学流体传动及控制国家重点实验室,杭州,310027
2. 内蒙古一机集团大地工程机械有限公司,包头,014032 |
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| 摘 要： | 针对齿轮故障特征往往被强背景噪声淹没的问题,采用形态小波降噪方法来提取故障特征.形态小波降噪方法适合于对具有一定形态特征的齿轮故障信号进行特征提取.首先采用形态小波对信号进行分解,然后对各层的细节系数进行软阈值降噪处理,最后根据处理得到的小波系数重构信号以提取故障特征.仿真与实例证明,该方法可有效地提取隐含在噪声中的齿轮故障特征.形态小波降噪算法只涉及加减和极大、极小运算,运算简单且执行高效,适合于齿轮故障的在线监测与诊断.
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| 关 键 词： | 故障诊断 齿轮 特征提取 形态小波 软阈值降噪 |
of Morphological Wavelet De-noising in Extracting Gear Fault Feature |
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| Shen Lu Zhou Xiaojun Liu Li Yang Fuchun. of Morphological Wavelet De-noising in Extracting Gear Fault Feature[J]. Transactions of the Chinese Society for Agricultural Machinery, 2010, 41(4): 217-221. DOI: 10.3969/j.issn.1000-1298.2010.04.044 |
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| Authors: | Shen Lu Zhou Xiaojun Liu Li Yang Fuchun |
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| Affiliation: | 1.The State Key Lab of Fluid Power Transmission and Control/a>;Zhejiang University/a>;Hangzhou 310027/a>;China 2.DADI Engineering Machinery Co./a>;Ltd./a>;Inner Mongolia First Machinery Group Corporation/a>;Baotou 014032/a>;China |
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| Abstract: | Fault feature is always hidden by strong noise background in gear fault signal.Based on morphological wavelet de-noising,a novel method was proposed to extract gear fault feature. Morphological wavelet de-noising has a good performance in extracting morphological feature in signal. Firstly,the signal was decomposed by morphological wavelet.Secondly,detail coefficient in each level was processed using soft threshold de-noising.Finally,fault feature was extracted by reconstructing original signal.Simulation a... |
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| Keywords: | Fault diagnosis Gear Feature extraction Morphological wavelet Soft threshold de-noising |
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