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小波分析算法研究及在齿轮与滚动轴承故障诊断中应用 被引量:7

Wavelet Transform Algorithm and Its Application in Fault Diagnose of Gear and Rolling Axletree
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摘要 分析了齿轮与滚动轴承故障振动信号的特征,利用小波变换的分解和重构算法,有效地提取出齿轮与滚动轴承故障特征信号,得到实验结果.通过比较频谱分析和小波分析的特点,有效地证明了小波分析在微弱故障信号提取中的优势. Vibration fault feature of gear and rolling axletree is analyzed. By using the decomposition and reconstruction algorithm of wavelet transform, the fault feature signal of gear and rolling axletree are extracted availably and the results of experimentation are obtained. The characteristic of spectrum analysis and wavelet analysis are compared, and the predominance of wavelet analysis in extraction of weak fault signal is proved.
出处 《传感技术学报》 CAS CSCD 北大核心 2007年第5期1196-1198,共3页 Chinese Journal of Sensors and Actuators
基金 国家自然科学基金资助项目(60102002) 霍英东基金资助项目(81057) 河北省博士基金资助项目(B2004522)
关键词 小波变换 故障特征提取 齿轮与滚动轴承故障诊断 wavelet transform extraction of fault characteristic fault diagnose of gear and rolling axletree
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参考文献8

  • 1姜万录,张淑清,王益群.基于混沌子波的故障信息诊断原理及应用[M].北京:国防工业出版社.2005.8.
  • 2杨福生.小波变换的工程分析与应用[M].北京:科学出版社,2001..
  • 3Chow T W S,Shi Hai.Induction Machine Fault Diagnostic Analysis with Wavelet Technique[J].IEEE Trans,June 2004,51(3):558-565.
  • 4Satish L,Nazneen B.Wavelet-Based Denoising of Partial Discharge Signals Buried in Excessive Noise and Interference[J].IEEE Trans,2000,April,10(2):354-367.
  • 5张淑清,陈艳,徐红,蔡文龙.基于小波分析的机械系统振动信号故障诊断[J].仪器仪表学报,2004,25(z1):756-757. 被引量:8
  • 6沈松,应怀樵,刘进明.用小波变换识别机械故障中的通过振动[C].第九届振动与噪声技术交流会论文集,北京,1997:248-252.
  • 7You Y L and Kaveh D.Fourth-Order Partial Differential Equations for Noise removal[J].IEEE Trans on Image Processing.2000.9:1723-30.
  • 8Sendur L and Selesnick I W.Bivariate Shrinkage Functions for Wavelet-Based Denoising Exploiting Interscale Dependency[J].IEEE Trans Signal Processing,2002,50:2744-56.

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