基于RBF网络的三相桥式全控整流电路的故障诊断

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英文篇名：Fault Diagnosis of a Full Control Rectifier Circuit with Three-phase Bridge Based on RBF Network 作者：牛慧芳 ; 孟青 ; 庞丽英 英文作者：NIU Hui-fang;MENG Qing;PANG Li-ying;North University of China,Shuozhou; 关键词：RBF网络 ; 三相整流电路 ; 晶闸管 ; 故障诊断 英文关键词：RBF network;;three-phase rectifier circuit;;thyristor;;fault diagnosis 中文刊名：NMGX 英文刊名：Journal of Inner Mongolia University(Natural Science Edition) 机构：中北大学朔州校区; 出版日期：2019-03-15 出版单位：内蒙古大学学报(自然科学版) 年：2019 期：v.50;No.224 基金：山西省青年科技研究基金(2015021095) 语种：中文; 页：NMGX201902015 页数：6 CN：02 ISSN：15-1052/N 分类号：104-109

摘要

在分析三相桥式全控整流电路晶闸管各类故障的基础上,通过MATLAB/Simulink仿真发现对于同一类型故障,不同管子损坏时对应输出电压峰值在同一周期的时间不同.基于此,设计采用无局部极小值问题且分类特性好的径向基函数RBF网络来识别不同晶闸管的故障.MATLAB仿真结果显示,该算法在三相桥式全控整流电路故障诊断中取得了预期的效果,提高了三相整流电路故障诊断的可靠性和准确性,同时还可推广到其他变流电路的故障诊断中.
        Based on the analysis of various faults of the thyristor of the three-phase bridge fullcontrolled rectifier circuit,the MATLAB/Simulink simulation shows that the peak value of the corresponding output voltage is different in the same cycle when different tubes are damaged for the same type of fault.Based on the above,the design uses a radial basis function RBF network with no local minimum value problem and good classification characteristics to identify the faults of different thyristors.The simulation results of MATLAB show that the algorithm achieves the expected effect on the fault diagnosis of the three-phase bridge full-controlled rectifier circuit,and improves the reliability and accuracy of the fault diagnosis of the three-phase rectifier circuit.Meanwhile,the algorithm can also be extended to the fault diagnosis of other converter circuits.

引文

[1]龙杰,张彼德,张强,等.基于PCA和MPCA优化神经网络的整流器故障诊断[J].电测与仪表,2017,48(01):23-29.
    [2]姜艳姝,吴迪,王伟亮.基于BP神经网络的整流电路的故障诊断[J].哈尔滨理工大学学报,2018,23(02):35-39.
    [3]靳芳华,何玉珠,张庆荣.基于小波神经网络的三相整流电路的故障诊断[J].现代电子技术,2011,34(05):183-186.
    [4]岳琪,温新.基于GA和BP神经网络的教学质量评价模型研究[J].内蒙古大学学报:自然科学版,2018,49(2):204-211.
    [5]Soman R R,Davidson E M,Mcarthur S D J,et al.Model-based methodology using modified sneak circuit analysis for power electronic converter fault diagnosis[J].Power Electronics,2012,5(6):813-826.
    [6]Cui Jiang,Wang Youren.A novel approach of analog circuit fault diagnosis using support vector machines classifier[J].Measurement,2011,44(1):281-289.
    [7]鄢仁武,叶轻舟,周理.基于随机森林的电力电子电路故障诊断技术[J].武汉大学学报:工学版,2013,46(6):742-746.
    [8]Pancerz K,Schumann A.Rough set models of Physarum machines[J].International Journal of General Systems,2015,44(3):314-325.