基于小波分析的焊接裂纹金属磁记忆信号特征提取

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材料工程 ›› 2008, Vol. 0 ›› Issue (1) : 34-37.

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测试与表征

基于小波分析的焊接裂纹金属磁记忆信号特征提取

严春妍¹, 李午申¹, 邸新杰¹, 薛振奎², 白世武², 刘方明²

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Feature Extraction of Metal Magnetic Memory Signals for Welding Cracks Based on Wavelet Analysis

YAN Chun-yan¹, LI Wu-shen¹, DI Xin-jie¹, XUE Zhen-kui², BAI Shi-wu², LIU Fang-ming²

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摘要

采用小波多分辨分析和快速傅里叶变换,对焊接裂纹金属磁记忆信号进行了处理,找出了焊接裂纹存在的磁记忆信号的判据特征,并建立了该特征的阈值.现场检测结果表明:采用小波多分辨分析和快速傅里叶变换得出的特征,可以准确判断出裂纹等缺陷是否存在.

Abstract

Based on multiscale wavelet analysis and fast Fourier transform,metal magnetic memory signals were processed for welding cracks.A criterion feature to identify the existence of welding cracks was found out.Corresponding threshold value of the feature was established.Field inspection indicated that welding cracks could be accurately identified with the criterion feature.

导出引用

严春妍, 李午申, 邸新杰, 薛振奎, 白世武, 刘方明. 基于小波分析的焊接裂纹金属磁记忆信号特征提取[J]. 材料工程, 2008, 0(1): 34-37

YAN Chun-yan, LI Wu-shen, DI Xin-jie, XUE Zhen-kui, BAI Shi-wu, LIU Fang-ming. Feature Extraction of Metal Magnetic Memory Signals for Welding Cracks Based on Wavelet Analysis[J]. Journal of Materials Engineering, 2008, 0(1): 34-37

中图分类号： TG115.28

参考文献

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