神经网络技术在结构损伤识别中的应用研究

【作者】 陈建林；

【导师】 郭杏林；

【作者基本信息】 大连理工大学 ， 工程力学， 2001， 硕士

【摘要】 对工程结构的损伤识别、定位以及估计是近年来十分流行的研究课题，结构损伤检测技术已被广泛应用于航天、土木、机械和核工业中，是一门建立在损伤机理、传感器技术、信号分析技术、计算机技术及人工智能技术之上的多学科综合性技术，相对于传统的结构损伤检测方法，本论文主要对基于神经网络的结构损伤检测技术理论与应用进行研究。 本文通过理论分析得出工程结构损伤前后的固有频率的变化包含了结构损伤位置和程度的信息，在此理论基础上，分别对一个桁梁桥模型和一个框架模型进行了损伤数值模拟，提取固有频率的变化的信息并采取合适的方法构造改进型BP神经网络的输入参数，应用训练后的神经网络对结构损伤进行检测，结果表明，该方法在工程损伤检测中具有一定的应用价值，最后通过一个简单结构简支梁的损伤判断的实验，进一步验证了上述论断。更多还原

【Abstract】 The detection, location, and estimation problem of structural damage has been the subject of much current research in recent years. The damage identification methods have been widely used in aeronautical, civil, mechanical and nuclear structures. It is polytechnic method constructed on the damage theory, sensor technology, signal analysis, computer science and artificial networks. Relative to the traditional technology of structural damage identification, this paper mainly studies the method based on the combination of the static modal analysis and artificial networks.In this paper, it is verified theoretically that the natural frequency changes of structure contain the information such as location and degree of the damage, based on this theory, use proper computer program to simulate different damage of a frame structure and a truss bridge separately, extract the natural frequency changes and form the input parameters of the improved BP algorithm network, detect the structural damage by the trained networks, the result shows the effectiveness of this method. In the end, through a simple structural damage identification experiment, the above conclusion is farther verified.更多还原