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基于独立分量分析的消噪方法在旋转机械特征提取中的应用
引用本文:季忠,金涛,杨炯明,秦树人. 基于独立分量分析的消噪方法在旋转机械特征提取中的应用[J]. 中国机械工程, 2005, 16(1): 50-53
作者姓名:季忠  金涛  杨炯明  秦树人
作者单位:重庆大学,重庆,400030
基金项目:国家自然科学基金资助项目(59875090)
摘    要:为了有效提取信号特征,为后续的故障诊断分析提供足够的信息,针对旋转机械故障诊断的特点,探讨了在旋转机械振动信号采集过程中基于独立分量分析方法的降噪措施的可行性,并在此基础上,研究了基于独立分量分析的消噪方法在旋转机械升降速过程中信号特征提取中的应用。实验结果表明,利用该方法可有效消除振动信号采集过程中混入的噪声。

关 键 词:旋转机械 独立分量分析 故障诊断 消噪
文章编号:1004-132X(2005)01-0050-04

Applications of Noise-Reduction with ICA in Feature Extraction of Rotating Machinery
Ji Zhong Jin Tao Yang Jiongming Qin Shuren Chongqing University,Chongqing. Applications of Noise-Reduction with ICA in Feature Extraction of Rotating Machinery[J]. China Mechanical Engineering, 2005, 16(1): 50-53
Authors:Ji Zhong Jin Tao Yang Jiongming Qin Shuren Chongqing University  Chongqing
Affiliation:Ji Zhong Jin Tao Yang Jiongming Qin Shuren Chongqing University,Chongqing,400030
Abstract:For the characteristics of fault diagnosis of rotating machinery, the paper discussed the feasibility of noise-reduced measures with ICA during the process of data acquisition of vibration signals of rotating machinery, and the noise-reduced method based on ICA has been studied to extract features during the process of run-up and run-down of the rotating machinery. Experimental results show that this method can simply and effectively remove the noise contained in the sampled vibration signals.
Keywords:rotating machinery  Independent Component Analysis(ICA)  fault diagnosis  noise-reduction
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