|本期目录/Table of Contents|

[1]姜媛媛,王友仁,崔江,等.基于LS-SVM的电力电子电路故障预测方法[J].电机与控制学报,2011,(08):64-68.
 JIANG Yuan-yuan,WANG You-ren,CUI Jiang,et al.Research on fault prediction method of power electronic circuits based on least squares support vector machine[J].,2011,(08):64-68.
点击复制

基于LS-SVM的电力电子电路故障预测方法(PDF)
分享到:

《电机与控制学报》[ISSN:1007-449X/CN:23-1 408/TM]

卷:
期数:
2011年08
页码:
64-68
栏目:
出版日期:
2011-08-20

文章信息/Info

Title:
Research on fault prediction method of power electronic circuits based on least squares support vector machine
作者:
姜媛媛; 王友仁; 崔江; 孙凤艳;
南京航空航天大学自动化学院; 安徽理工大学电气与信息工程学院;
Author(s):
JIANG Yuan-yuan12WANG You-ren1CUI Jiang1SUN Feng-yan1
1.College of Automation Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China;2.College of Electric and Information Engineering,Anhui University of Science and Technology,Huainan 232001,China
关键词:
电力电子电路 故障预测 特征性能参数 数据驱动 最小二乘支持向量机
Keywords:
power electronic circuits fault prediction characteristic parameter data driving least squares support vector machine(LS-SVM)
分类号:
TN710
DOI:
-
文献标志码:
A
摘要:
针对现有电力电子电路故障预测技术的不足,提出将电路特征性能参数和最小二乘支持向量机(least squares support vector machine,LS-SVM)预测算法结合,对电力电子电路进行故障预测。以Buck电路为例,选择电路输出电压作为监测信号,提取输出电压平均值及纹波值作为电路特征性能参数,并利用LS-SVM回归算法实现故障预测。实验结果表明,利用LS-SVM对电路输出平均电压与输出纹波电压的预测相对误差均低于2%,能够跟踪故障特征性能参数的变化趋势,有效实现电力电子电路故障预测。
Abstract:
Aiming at the issue of fault prediction technique of power electronic circuits,a method based on characteristic parameter data and least squares support vector machine(LS-SVM) for the prediction of power electronic circuits was proposed.Taking the Buck converter circuit as an example,the fault prediction of power electronic circuits was achieved.Firstly,the output voltage was selected as monitoring signal,and then the average voltage and ripple voltage were extracted as characteristic parameters...

参考文献/References:

-

相似文献/References:

[1]罗慧,王友仁,崔江,等.电力电子电路多源特征层融合故障诊断方法[J].电机与控制学报,2010,(04):92.
 LUO Hui,WANG You-ren,CUI Jiang,et al.Intelligent fault diagnosis for power electronic circuits based on multi-source feature-level fusion[J].,2010,(08):92.
[2]曹正洪,沈继红.基于模糊集理论的传感器健康度评价方法[J].电机与控制学报,2010,(05):79.
 CAO Zheng-hong,SHEN Ji-hong.Sensor health degree evaluation method based on fuzzy set theory[J].,2010,(08):79.

备注/Memo

备注/Memo:
国家自然科学基金(60871009);航空科学基金(2009ZD52045);江苏省普通高校研究生科研创新计划项目(CXLX11-0183);南京航空航天大学基本科研业务费专项科研项目(NS2010063)
更新日期/Last Update: 2012-03-27