| 涡流检测信号小波除噪与缺陷特征提取 |
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| 引用本文： | 时振堂,陈德智. 涡流检测信号小波除噪与缺陷特征提取[J]. 无损检测, 2003, 25(9): 472-476,493 |
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| 作者姓名： | 时振堂 陈德智 |
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| 作者单位： | 1. 齐鲁石化公司热电厂,淄博,255411
2. 华中科技大学电气学院,武汉,430074 |
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| 摘 要： | 应用小波分析技术进行涡流检测的信号除噪和缺陷识别。根据信号在不同小波变换下表现形式不同的特点，提出一种综合应用多种小波除噪的方法，效果优于通常的单一小波方法。应用小波多尺度边缘检测功能进行缺陷的定位和尺寸判别。借助小波多尺度分析功能，可以对缺陷信号进行仔细分析，并对相近缺陷进行分类。
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| 关 键 词： | 涡流检测 信号处理 降噪 缺陷识别 小波分析 特征提取 |
| 文章编号： | 1000-6656(2003)09-0472-05 |
WAVELET DENOISING AND FEATURE EXTRACTION FOR EDDY CURRENT TESTING SIGNALS |
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| SHI Zhen-tang. WAVELET DENOISING AND FEATURE EXTRACTION FOR EDDY CURRENT TESTING SIGNALS[J]. Nondestructive Testing, 2003, 25(9): 472-476,493 |
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| Authors: | SHI Zhen-tang |
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| Abstract: | Wavelet analysis technique was applied to signal processing in eddy current testing. A denoising method combining different wavelets was presented. Its result was better than that of single wavelet method. Wavelet multiscale edge detection technique was used to locate and size defects. By using the method, the characters of similar defects could be distinguished. |
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| Keywords: | Eddy current testing Signal processing Denoising Defect identification Wavelet analysis |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
