| 引用本文: | 朱翔,吴贻鼎,魏炜.基于二阶BP神经网络的旋转机械故障的智能诊断[J].电力自动化设备,2004,(1):87-90 |
| .Intelligent fault diagnosis of rotating machinery based on two-order BP neural network[J].Electric Power Automation Equipment,2004,(1):87-90 |
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| 摘要: |
| 针对旋转机械故障的智能诊断问题，提出了结合二阶BP神经网络和模糊网络的集成诊断方法。系统由信号处理子系统和故障诊断子系统两大部分组成。信号子系统负责信号的提取和预处理，诊断子系统则是诊断的核心，不同信号送入不同子神经网络进行诊断，结果通过决策神经网络进行数据融合，做出最后的诊断。该系统具有知识自动获取、识别速度快、鲁棒性及容错能力强等特点。实例证明该系统是有效的。 |
| 关键词: 二阶BP神经网络 智能诊断 数据融合 集成神经网络 |
| DOI： |
| 分类号:TM307 TP183 |
| 基金项目: |
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| Intelligent fault diagnosis of rotating machinery based on two-order BP neural network |
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ZHU Xiang WU Yi-ding WEI Wei
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| Abstract: |
| An intelligent fault diagnosis method for rotating machinery is presented,which integrates two-order backpropagation neural network and fuzzy neural network.It consists of signal processing subsystem and diagnostic subsystem.The signals are extracted and preprocessed in the signal pro-cessing subsystem.The diagnostic subsystem is the core,in which different signals are loaded into different sub-neural networks and diagnosed,then the results are sent into decision-making neural network for data fusion and last diagnosis decision.The system obtains knowledge automatically and has the features of fast recognition,better robusticity and error-tolerance.Example test shows its effectiveness. |
| Key words: two-order backpropagation neural network,intelligent diagnosis,data fusion,inte-grated neural network |
