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基于模糊神经网络的MVB故障诊断算法
引用本文:吕洪武,赵航,王宏志,胡黄水.基于模糊神经网络的MVB故障诊断算法[J].吉林大学学报(理学版),2002,58(1):104-108.
作者姓名:吕洪武  赵航  王宏志  胡黄水
作者单位:1. 长春工业大学 计算机科学与工程学院, 长春 130012; 2. 吉林建筑科技学院 计算机科学与工程学院, 长春 130114
摘    要:针对多功能车辆总线具有随机性和不确定性导致故障诊断准确率较低的问题, 设计一种基于模糊神经网络的MVB故障诊断算法. 首先根据MVB故障类型给出诊断模型, 然后采用减法聚类生成数量较少的模糊规则, 最后采用T-S模糊神经网络对故障进行分类. 在MATLAB环境下对该算法的拟合能力及诊断准确率进行仿真分析的结果表明, 该算法简化了模糊神经网络结构, 有效提高了故障诊断准确率.

关 键 词:多功能车辆总线    故障诊断    模糊神经网络    减法聚类  
收稿时间:2019-06-13

Fault Diagnosis Algorithm for MVBBased on Fuzzy Neural Network
LV Hongwu,ZHAO Hang,WANG Hongzhi,HU Huangshui.Fault Diagnosis Algorithm for MVBBased on Fuzzy Neural Network[J].Journal of Jilin University: Sci Ed,2002,58(1):104-108.
Authors:LV Hongwu  ZHAO Hang  WANG Hongzhi  HU Huangshui
Affiliation:1. College of Computer Science and Engineering, Changchun University of Technology, Changchun 130012, China;[JP3]2. College of Computer Science and Engineering, Jilin University of Architecture and Technology, Changchun 130114, China
Abstract:Aiming at the problem of low fault diagnosis accuracy caused by the randomness and uncertainty of multifunction vehicle bus (MVB), we designed a fault diagnosis algorithm for MVB based on fuzzy neural network. Firstly, the diagnosis model was given according to thefault types of MVB. Secondly, the subtraction clustering was used to generate fewer fuzzy rules. Finally, the T-S fuzzy neural networkwas used to classify the faults. The simulation results of the fitting ability and diagnosis accuracy of the algorithm in MATLAB show that the proposedalgorithm simplifies the structure of the fuzzy neural network and effectively improves the accuracy of fault diagnosis.
Keywords:multifunction vehicle bus (MVB)  fault diagnosis  fuzzy neural network  subtraction clustering  
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