引用本文:郝丽娜,徐心和.粗糙集神经网络系统在故障诊断中的应用[J].控制理论与应用,2001,18(5):681~685.[点击复制]
HAO Li-na,XU Xin-he.The Application of Rough Set Neural Network System in Fault Diagnosis[J].Control Theory and Technology,2001,18(5):681~685.[点击复制]
粗糙集神经网络系统在故障诊断中的应用
The Application of Rough Set Neural Network System in Fault Diagnosis
摘要点击 1576  全文点击 1649  投稿时间:2000-07-07  修订日期:2000-10-17
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DOI编号  10.7641/j.issn.1000-8152.2001.5.009
  2001,18(5):681-685
中文关键词  粗糙集  人工神经网络  故障诊断
英文关键词  rough sets  artificial neural networks  fault diagnosis
基金项目  西安交通大学 机械制造系统工程国家重点实验室开放基金资助项目.
作者单位
郝丽娜 东北大学 机械工程与自动化学院, 沈阳 110004 
徐心和 东北大学 控制仿真中心, 沈阳 110005 
中文摘要
      故障诊断中的误报和漏报现象直接影响诊断的准确率, 同时在线故障诊断又要求很强的实时性. 本文在给出粗糙集神经网络系统原理框图的基础上, 结合领域知识把该系统应用于滚动轴承的故障诊断中, 仿真实验结果表明该系统提高了故障诊断的准确率和诊断速度, 同时减少了检测项目, 降低了诊断成本, 在实际中有良好的应用前景.
英文摘要
      The phenomena of misinformation and failing to report in fault diagnosis affect directly the quality of diagnosis, meanwhile, fault diagnosis on line demands real time. On the basis of giving an architecture of rough set neural network system, this paper applies it to the fault diagnosis of rolling bearings combined with professional knowledge. Simulation results indicate that the system has increased the quality and rate of diagnosis, reduced measure items and costs of diagnosis. There will be well application prospect in practice.