摘要
利用压电材料(PZT-8)受力变形电压变化的机理,结合人工神经网络FBP方法对电梯钢丝绳安全工作状态进行智能监测。研究构建了基于压电理论的电梯钢丝绳安全状态智能监测方法,以压电理论和FBP人工神经网络为基础,进行了实验研究,实验获得了较好的数据,同时实验证明了该方法用于电梯钢丝绳安全状态监测,具有诊断速度快、精度高等特点。
The FBP neural network is used to intelligently monitor the safety operation state of the elevator wire rope by the mechanism of deformation force of the piezoelectric material( PZT- 8) in this paper. The intelligent monitoring model of the elevator wire rope safety state is constructed based on the piezoelectric theory,the experimental study is made,based on the theoretical theory and the FBP neural network and good data is obtained from the experimental study. The experimental results show that if this method is used for the safety state monitoring of the elevator wire rope,it has the characteristics of high speed,precision and so on.
出处
《机械制造与自动化》
2016年第6期239-241,共3页
Machine Building & Automation
基金
国家863专项资助(2012AA063506)
苏州市科技支撑项目(SS201344)
关键词
压电材料
钢丝绳安全状态
智能监测
piezoelectric material
elevator wire rope safety operation state
intelligent monitoring
