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粗糙集神经网络系统在故障诊断中的应用
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.
作者姓名:郝丽娜  徐心和
作者单位:1. 东北大学机械工程与自动化学院,
2. 东北大学控制仿真中心,
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
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率,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。

关 键 词:粗糙集  人工神经网络  故障诊断  滚动轴承
文章编号:1000-8152(2001)05-0681-05
收稿时间:7/7/2000 12:00:00 AM
修稿时间:2000年7月7日

The Application of Rough Set Neural Network System in Fault Diagnosis
HAO Li-na and XU Xin-he.The Application of Rough Set Neural Network System in Fault Diagnosis[J].Control Theory & Applications,2001,18(5):681-685.
Authors:HAO Li-na and XU Xin-he
Affiliation:The College of Mechanical Engineering and Automation, Northeastern University, Shenyang,110004,P.R.China;Control and Simulation Research Center, Northeastern University, Shenyang, 110004,P.R.China
Abstract: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.
Keywords:rough sets  artificial neural networks  fault diagnosis
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