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个人信息Personal Information
教授
硕士生导师
性别:男
毕业院校:大连理工大学
学位:博士
所在单位:力学与航空航天学院
学科:工程力学. 计算力学
办公地点:力学楼404
电子邮箱:lishouju@dlut.edu.cn
Damage identification of mechanical system with artificial neural networks
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论文类型:会议论文
发表时间:2008-01-01
收录刊物:EI、CPCI-S
卷号:385-387
页面范围:877-+
关键字:natural frequency; damage identification; neural network; hybrid optimization; inverse problem
摘要:The inverse problem of structure damage detection is formulated as an optimization problem, which is then solved by using artificial neural networks. Based on the hybrid optimization strategy, the parameter identification algorithm was presented according to the measured data of vibrating frequency and mode shapes in the damaged structure. The proposed algorithm combines the local optimum method having fast convergence ability with the neural networks having global optimum ability. By doing this, the local minimization problem of the local optimum method can be solved, and the convergence speed of the global optimum method can be improved. The investigation shows that to identify the location and magnitude of the damaged structure by using an artificial neural network is feasible and a well trained artificial neural network by Levenberg-Marquardt algorithm reveals an extremely fast convergence and a high degree of accuracy.