| 基于小波包技术的复合材料损伤检测 |
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| 引用本文： | 吴辉军,陶宝祺.基于小波包技术的复合材料损伤检测[J].复合材料学报,1997,14(4):95-100. |
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| 作者姓名： | 吴辉军 陶宝祺 |
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| 作者单位： | 上海交通大学振动冲击噪声国家重点实验室，南京航空航天大学智能材料和结构研究所 |
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| 基金项目： | 国家自然科学基金,航空基金 |
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| 摘 要： | 小波包分解能够精细地把信号划分到不同的频带范围内,实现了不同频带范围内特征信息的分离和提取.据此并借助于小波神经网络实现了复合材料无损检测中的特征信号的模式识别.实验表明该方法稳定可靠.
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| 关 键 词： | 小波包 小波神经网络 特征提取 复合材料 损伤检测 |
| 收稿时间： | 1996-03-21 |
| 修稿时间： | 1996-11-21 |
DAMAGE DETECTION OF THE COMPOSITE MATERIALS BASED ON WAVELET PACKETS |
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| Wu YaoJun,Tao Baoqi,Shi Xizhi.DAMAGE DETECTION OF THE COMPOSITE MATERIALS BASED ON WAVELET PACKETS[J].Acta Materiae Compositae Sinica,1997,14(4):95-100. |
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| Authors: | Wu YaoJun Tao Baoqi Shi Xizhi |
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| Affiliation: | 1. National Key Laboratory for Vibration, Shock & Noise, Shanghai Jiao Tong University, Shanghai 200030;2. Nanjing University of Aeronautics & Astronautics, Nanjing 210016 |
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| Abstract: | An approach to feature extraction and recognition of the characteristic signal in the field of the damage detection of the composite materials is studied by thewavelet packets that disintegrate the signal into different frequency bands.These features are fed into the wavelet neural network as the input patterns for training and classifying.The experiments are conducted to demonstrate the feasibility of the proposed method. |
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| Keywords: | wavelet packets wavelet neural network feature extraction composite materials damage detection |
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