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微细钻孔的模糊神经网络在线监测

On-line fuzzy neural network monitoring for micro hole drilling

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【作者】 杨兆军李雪韩愈崔亚新丁驰原

【Author】 Yang Zhao-jun1,Li Xue1,Han Yu1,Cui Ya-xin2,Ding Chi-yuan3(1.College of Mechanical Science and Engineering,Jilin University,Changchun 130022,China;2.College of Machinery and Electricity Engineering,Jilin Teacher Institute of Engineering and Technology,Changchun 130052,China;3.School of Aer Space Science and Engineering,Beijing Institute of Technology,Beijing 100081,China)

【机构】 吉林大学机械科学与工程学院吉林工程技术师范学院机电工程学院北京理工大学宇航科学技术学院 长春130022长春130022长春130052北京100081

【摘要】 建立了以压电钻削测力仪作为测量元件的微孔钻削力在线监测系统,构造了用于对微孔钻削力进行实时数据处理的4层模糊神经网络。网络经训练后用于实时获取隐含微细钻头磨损状态信息的钻削力值,对微孔钻削过程进行在线监测实验,结果表明,适当选择监测阈值,可以有效避免微细钻头的折断。

【Abstract】 An on-line micro hole drilling monitoring system with a piezoelectric element to measure the drilling thrust was built.A four-layor fuzzy neural network(FNN) was established for processing the real-time thrust data of the micro hole drilling.After drilling,the FNN was used to acquise the real-time thrust values which implicate the wear state information of the micro drill.The on-line tests to monitor the nicro hole drilling processes were performed with the established FNN,and the results showed that the drill break may be avoided if the monitoring threshold was selected properly.

【基金】 吉林省自然科学基金资助项目(20010574)
  • 【文献出处】 吉林大学学报(工学版) ,Journal of Jilin University(Engineering and Technology Edition) , 编辑部邮箱 ,2007年06期
  • 【分类号】TG52
  • 【被引频次】9
  • 【下载频次】164
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