| 基于神经网络的金属基复合材料结构中深层界面脱粘缺陷识别 |
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| 引用本文： | 卢志才,敦怡,徐章遂,李伟芬,刘斌. 基于神经网络的金属基复合材料结构中深层界面脱粘缺陷识别[J]. 煤矿机械, 2007, 28(2): 47-48 |
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| 作者姓名： | 卢志才 敦怡 徐章遂 李伟芬 刘斌 |
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| 作者单位： | 军械工程学院,无损检测研究所,合肥,050000;合肥炮兵工程学院,合肥,050000;71320部队80分队,合肥,050000 |
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| 摘 要： | 在利用超声信号进行金属基复合材料结构的无损评价时,需要对不同界面脱粘进行识别。利用人工神经网络的方法可以对不同界面脱粘时的实验检测信号进行正确地识别。实验检测结果表明超声回波信号识别方法可用在金属基复合材料结构的无损检测中。
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| 关 键 词： | 金属基复合材料 超声 人工神经网络 |
| 文章编号： | 1003-0794（2007）02-0047-02 |
| 修稿时间： | 2006-10-15 |
Deep-layer Interface Debend Defect Recognition of MMC Based on Artificial Neural Network |
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| LU Zi-cai,DUN Yi,XU Zhang-shui,LI Wei-fen,LIU Bin. Deep-layer Interface Debend Defect Recognition of MMC Based on Artificial Neural Network[J]. Coal Mine Machinery, 2007, 28(2): 47-48 |
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| Authors: | LU Zi-cai DUN Yi XU Zhang-shui LI Wei-fen LIU Bin |
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| Affiliation: | 1. NDT Insifitute of Ordnance Engeering College, Hefei 050000, China; 2. Hefei Cannoneer Engeering College, Hefei 050000, China; 3. Unitof 71320 PLA Kaifeng, Hefel 050000, China |
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| Abstract: | In the ultrasonic non-destructive evaluation of metal matrix composite(MMC) multi-layer structure,it needs to clarify the disbands at different interface.Using artificial neural networks,can succeed in clarifying the experience disbands at different interfaces.This method of feature extraction is expected to be largely applicable to the non-destructive evaluation of MMC multi-layer bonded structure. |
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| Keywords: | metal matrix composite(MMC) ultrasonic artificial neural network |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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