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文章摘要
模糊神经网络专家系统在动力锂电池组故障诊断中的应用
Fuzzy Neural Network Expert System for Fault Diagnosis in Power Lithium Battery Application
Received:July 23, 2014  Revised:July 23, 2014
DOI:
中文关键词: 模糊  神经网络  动力锂电池  故障诊断  专家系统
英文关键词: fuzzy,neural  network,power  lithium,fault  diagnosis,expert  system
基金项目:
Author NameAffiliationE-mail
WANG Yi-hui* School of Electrical Electronic Engineering,Changchun University of Technology 351744218@qq.com 
JIANG Chang-hong School of Electrical Electronic Engineering,Changchun University of Technology  
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中文摘要:
      动力锂电池故障的产生原因具有一定的复杂性和不确定性。为此,本文提出了一种基于模糊神经网络的故障诊断专家系统,该方法结合了模糊数学,神经网络以及专家系统的优点。用模糊数学可以将症状模糊化以表征故障的隶属度;神经网络具有良好的自学习能力;专家系统具有推理能力强;三者的相互结合,即提高了系统的准确性和可操作性,又满足了对故障诊断智能化,自动化的要求。试验结果表明该方法可以准确的判断出系统的故障,不仅将故障检测的精度提高到0.001,预测误差在1%-8%之间,而且检测时间大大缩短。提高了动力锂电池的自适应能力,自主学习能力,为动力锂电池故障诊断提出了一种科学高效的新方法。
英文摘要:
      Power lithium battery failure causes has a certain complexity and uncertainty.To this end,this paper proposes a fault diagnosis expert system based on fuzzy neural network,This method combines the fuzzy mathematics,the advantages of neural network and expert system.Using fuzzy mathematics can be blurred to characterize the membership degree of the fault symptoms;neural network has good self-learning ability;the expert system have strong reasoning ability;All three together,that is,to improve the accuracy of the system and operability,meet again for intelligent fault diagnosis,the requirement of automation.The test results show that the method can accurately judge the fault in the system,not only to increase the accuracy of fault detection to 0.001,the prediction error between 1%and 8%,and shorten the testing time.Improve the adaptive ability of the power lithium batteries,the independent learning ability,power lithium battery fault diagnosis is put forward a new method for scientific and efficient.
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