摘要
利用压电陶瓷(PZT)智能材料作为驱动源产生的波动信号,结合人工神经网络控制方法对设备及结构健康状态进行智能诊断。通过研究首先构建了动力学模型,并通过对工程实际中常见结构缺陷问题的实验研究,对模型相关参数进行了优化,同时也证明了该方法的先进性、可行性和实用性。
It takes PZT intelligent material as the driving source to produce fluctuant signals, together with the artificial neural network control method, the health state of equipment and structure can be intelligently diagnosed. In the research, a kinetic model is constructed, and then the relative parameters are optimized on the basis of the experimental research of structural deject problem in engineering practice.Meanwhile, the advantages, feasibility and practicability of this method have been proved.
出处
《机械设计与制造》
北大核心
2007年第9期197-199,共3页
Machinery Design & Manufacture
基金
江苏省教育厅2005年高校自然科学研究指导性计划项目(项目编号:05KJD470200)
