| 摘要: |
| 研究了用小波分析方法从电极压力曲线上提取判定铝合金冲击波点焊过程发生喷溅的特征信息的方法。采用db5小波对发生喷溅焊点的电极压力曲线信号上的不规则信号突变进行了检测。结果表明,小波分解中高频部分重构信号可准确检测到电极压力曲线上信号发生突变时的位置及突变程度,也就是说能够将发生喷溅缺陷的时刻准确地表现出来。利用超过一定阈值的小波分解高频重构信号的全局最大值作为判定点焊过程发生喷溅缺陷的特征信息是准确可靠的,从而实现了将电极压力曲线上的信号特征转化为计算机容易识别的数值特征。 |
| 关键词: 铝合金点焊 喷溅 小波分析 特征信息 |
| DOI： |
| 分类号: |
| 基金项目:河北省自然科学基金资助项目(E2006000036) |
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| Extraction of diagnostic information of expulsion defect in resistance spot welding process by wavelet analysis method |
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XUE Haitao, LI Yongyan, CUI Chunxiang, DONG Tianshun
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School of Material Science and Engineering, Hebei University of Technology, Tianjin 300132, China
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| Abstract: |
| An effective approach was developed to extract diagnostic information used to identify expulsion from electrode force curve by using wavelets analysis method for aluminum alloy shock wave resistance spot welding.The irregular signal singularity of electrode force curve was detected by using db5 wavelet.The detection result shows that the location and intensity of the signal singularity can be detected accurately from high frequency reconstructed signal of wavelet decomposition structure.That is to say, the expulsion can be identified easily.The diagnostic information is the global maximum value of high frequency reconstructed signal.The recognition method is that if the global maximum value exceeds the threshold value built by analyzing a number of testing data, the expulsion will occur.The testing result proves that the method is correct, reliable and credible.Therefore, the signal characteristic of electrode fore curve can be transformed into numerical characteristic that can be identified by computer. |
| Key words: aluminum alloy resistance spot welding expulsion wavelet analysis diagnostic information |
