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步贤政, 单平, 罗震, 唐新新. 基于独立分量分析的点焊特征声音信号提取[J]. 焊接学报, 2009, (2): 41-44.
引用本文: 步贤政, 单平, 罗震, 唐新新. 基于独立分量分析的点焊特征声音信号提取[J]. 焊接学报, 2009, (2): 41-44.
BU Xianzheng, SHAN Ping, LUO Zhen, TANG Xinxin. Characteristic extraction of acoustic signals emitted from resistance spot welding process based on independent component analysis[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2009, (2): 41-44.
Citation: BU Xianzheng, SHAN Ping, LUO Zhen, TANG Xinxin. Characteristic extraction of acoustic signals emitted from resistance spot welding process based on independent component analysis[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2009, (2): 41-44.

基于独立分量分析的点焊特征声音信号提取

Characteristic extraction of acoustic signals emitted from resistance spot welding process based on independent component analysis

  • 摘要: 采用独立分量分析的方法和传感器阵列技术对点焊声音信号进行了研究,建立了点焊声音信号独立分量分析算法.采用8个传声器阵列,同时对点焊过程中的声音信号进行了测量,获得了比单传感器丰富的点焊信息.计算了这些声音信号的峰度系数,确认其为非高斯型,满足独立分量分析的要求,并对其进行独立分量分析.结果表明,基于FastICA算法的独立分量分析可以从叠加噪声中分离出点焊过程信号源,且效果明显,为深入分析点焊过程提供了一个新的技术手段,并且该算法可以应用于其它焊接方法中。

     

    Abstract: In this paper, independent component analysis(ICA)and multisensor array technology were used to research the acoustic emission signals from resistance spot welding.An independent component analysis algorithm for the acoustic signals from spot welding was established.A multisensor array system with 8 microphones was used to measure the acoustic emission signals from spot welding synchronously.According to the calculation of the kurtosis coefficient, the acoustic signals were found to be non-Gaussian distribution.So the acoustic signals were decomposed by the independent component analysis.The results showe that the independent component analysis based on Fast ICA algorithm can extract the characteristic signals of the spot welding from superimposed noises obviously, which provides a new technology for the profound analysis of spot welding.Further more, this algorithm can be used in other welding methords.

     

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