引用本文:芮 勇,金丕彦.基于人工神经网络的FMS物料搬运机器人的故障诊断[J].控制理论与应用,1994,11(4):460~463.[点击复制]
RUI Yong,JIN Piyan.An Artificial Neural Network Based Fault-Diagnosis Method for FMS Element Transfer Robot[J].Control Theory & Applications,1994,11(4):460~463.[点击复制]
基于人工神经网络的FMS物料搬运机器人的故障诊断
An Artificial Neural Network Based Fault-Diagnosis Method for FMS Element Transfer Robot
摘要点击 1556  全文点击 623  投稿时间：1993-04-19  修订日期：1994-01-17
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DOI编号  
  1994,11(4):460-463
中文关键词  人工神经网络  自适应谐振理论ART  FMS物料搬运机器人  故障诊断
英文关键词  artificial neural network  adaptive resonance theory  FMS element transfer robot  fault-diagnosis
基金项目  
作者单位
芮 勇,金丕彦 清华大学自动化 
中文摘要
      本文讨论了一种无导师的神经网络模型—自适应谐振理论ART，详细分析了ART的工作原理及故障诊断过程。本文以FMS中的物料搬运机器人的故障诊断为例，详细说明了故障样本编码，ART的自学习，智能化诊断过程。并给出了仿真结果（在PC-486/33上实现），仿真结果表明ART是一种有效且实用的故障诊断方法。
英文摘要
      A successful non-teacher Artificial Neural Network model—Adaptive Resonance Theory (ART) model has been discussed in this paper. Also, we analyzed in details the operating principles of the ART model and the fault-diagnosis process. We used the FMS element transfer robot as an example to illustrate the whole fault-diagnosis process, which includes sample coding, training and diagnosing. Simulation results have been given (accomplished in PC-486/33), and the results show that ART is an effective and practical fault-diagnosis method.