| 基于小波神经网络复合材料损伤检测的研究 |
| |
| 引用本文： | 刘泉,江雪梅.基于小波神经网络复合材料损伤检测的研究[J].武汉理工大学学报,2002,24(12):72-74,81. |
| |
| 作者姓名： | 刘泉 江雪梅 |
| |
| 作者单位： | 武汉理工大学 |
| |
| 基金项目： | 湖北省自然科学基金项目资助 (2 0 0 0 J16 1) |
| |
| 摘 要： | 研究了一种采用埋入智能传感器对复合材料冲击损伤检测的系统，在对信号进行处理时，该系统结合了小波变换良好的时频局部特性和神经网络的自学习功能及良好的容错能力的优点，从而能准确地识别出复合材料冲击损伤的位置并提高了冲击损伤检测的速度与准确率。对复合材料的冲击损伤检测进行了仿真，结果表明了该方法是可行的。
|
| 关 键 词： | 智能传感器 复合 损伤检测 小波变换 神经网络 冲击损伤 |
| 文章编号： | 1671-4431(2002)12-0072-03 |
Simulation Research on a System of Impact Damage Detection for Composite Material Using Wavelet Neural Network |
| |
| Liu Quan Jiang Xuemei Prof.,School of Information Engineering,WUT,Wuhan ,China..Simulation Research on a System of Impact Damage Detection for Composite Material Using Wavelet Neural Network[J].Journal of Wuhan University of Technology,2002,24(12):72-74,81. |
| |
| Authors: | Liu Quan Jiang Xuemei Prof School of Information Engineering WUT Wuhan China |
| |
| Affiliation: | Liu Quan Jiang Xuemei Prof.,School of Information Engineering,WUT,Wuhan 430070,China. |
| |
| Abstract: | A system of impact damage detection for composite material structures by using an intelligent sensor embedded in composite material is described in this paper. In the course of signal processing, because Wavelet transform has the exceptional property of temporal frequency localization, whereas neural networks have excellent characteristics of self learning and fault tolerance. By combining their good merits in this system, it can properly recognize impact damage places of composite material and improve the speed and accuracy of impact damage detection. Simulation for impact damage detection for composite material shows that this approach is feasible. |
| |
| Keywords: | intelligent sensor composite material damage detection wavelet transform neural network |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
