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| Intelligent monitor of cable suspension bridge's working states based on piezoelectric theory |
| YUAN Zeng-Yan, RUI Yan-Nian, ZHAO Kui, CHEN Huan |
| College of Mechanical and Electrical Engineering, Soochow University, Suzhou 215021, China |
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Abstract A new method using piezoelectric material (PZT) and artificial neural network control was put forward to repair in time by online monitoring the health state of cable suspension bridge. This method conducted online analysis and intelligent diagnosis on stress and stain of the mentioned bridge, which adopted the principle that when PZT had distortion, the voltage and intensity of electric field would change, to collect information and the improved ANN control. A great deal of data was obtained from experiments, and then the parameters of BP ANN were optimized, which demonstrated the feasibility and advancement of this method.
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Published: 28 December 2007
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基于压电理论的悬索桥工作状况智能监测与诊断方法
提出一种用压电材料（PZT）和人工神经网络控制理论相结合的方法，对悬索桥梁结构健康状态进行在线诊断，以便及时修复。该方法利用PZT受力变形时电压电场变化的机理采集信息，结合改进了的BP神经网络控制方法，对悬索桥梁的应力、应变进行在线分析和智能诊断。并通过实验研究获得大量的实验数据，对BP网络参数进行优化，证明了该方法的可行性和先进性。
关键词：
压电陶瓷,
BP人工神经网络,
悬索桥梁,
智能检测
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