| 神经网络方法在涡流无损检测定量分析中的应用 |
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| 引用本文： | 孙晓云,袁斌,盛剑霓.神经网络方法在涡流无损检测定量分析中的应用[J].西安交通大学学报,2000,34(6):6-10. |
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| 作者姓名： | 孙晓云 袁斌 盛剑霓 |
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| 作者单位： | 西安交通大学,710049,西安 |
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| 基金项目： | 教育部博士点基金资助项目 !(980 6 982 1 ) |
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| 摘 要： | 采用人工神经网络完成涡汉无损检测中的定量识别，首先，用数值方法分析了阴抗增量的幅值、相位与缺损尺度的关系，得出结论：用相位值来表征深度效果更好，精度更高，然后，应用小波边缘检测方法确定的信号特征值作为网络的输入，结果表明：计算量大为减小，网络结构得到了简化。
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| 关 键 词： | 神经网络 涡流无损检测 小波边缘检测 定理分析 |
Artificial Neural Network Applied to Eddy Current Nondestructive Testing |
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| Sun Xiaoyun,Yuan Bin,Sheng Jianni.Artificial Neural Network Applied to Eddy Current Nondestructive Testing[J].Journal of Xi'an Jiaotong University,2000,34(6):6-10. |
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| Authors: | Sun Xiaoyun Yuan Bin Sheng Jianni |
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| Abstract: | Artificial neural network(ANN) is applied to eddy current nondestructive testing( ECNT) for detecting defects. After establishing the correlation between the amplitude or phase with the defect size, phase value was found to correlate better with the depth of defect. Wavelet edge detecting method can be used finding free edges. The results were used as inputs to ANN for analysis. |
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| Keywords: | artificial neural netwrk ECNT wavelet edge detecting |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
