吉林大学学报(工学版) ›› 2015, Vol. 45 ›› Issue (2): 675-680.doi: 10.13229/j.cnki.jdxbgxb201502051

• Orignal Article • Previous Articles    

PSO based feature extraction method for analog circuit fault information

LIU Hong1,SUN Shuang-zi2,WANG Qing-yuan1,LI Yan-zhong1   

  1. 1.School of Photo-Electronic Engineering,Changchun University of Science and Technology,Changchun 130022,China;
    2.School of Computer Science and Technology,Changchun University of Science and Technology,Changchun 130022,China
  • Received:2013-12-13 Online:2015-04-01 Published:2015-04-01

RICH HTML

0   

PDF (PC)

401

Abstract: In order to improve the diagnosis efficiency of faulty circuits with tolerance and to ameliorate the characteristic description of faulty symptom, first, the faulty features of the circuit with tolerance are created by information entropy method. Then, a feature extraction method based on discrete Particle Swarm Optimization (PSO) algorithm is proposed to obtain the optimal feature subset of the faulty features. Finally, the optimal feature subset is used to train the classifier to diagnose the faults of circuit with tolerance. Experiment results validate this proposed method.

Key words: information process technique, information entropy, particle swarm optimization, feature extraction, analog circuits, fault location

CLC Number: 

  • TN707
[1] Liu Hong, Chen Guang-ju, Jiang Shu-yan, et al.A survey of feature extraction approaches in analog circuit fault diagnosis[C]∥Pacific-Asia Workshop on Computational Intelligence and Industrial Application. Wuhan: IEEE Computer Society, 2008: 676-680.
[2] 万九卿,李行善. 基于诊断信息量的测点选择方法[J].电子测量与仪器学报,2005, 19(5):1-5.
Wan Jiu-qing,Li Xing-shan. Test point selection based on diagnositc information[J]. Journal of Electronic Measurement and Instrument, 2005, 19(5):1-5.
[3] Li Bing, Zhang Pei-lin, Liang Shu-bao, et al.Feature extraction and selection for fault diagnosis of gear using wavelet entropy and mutual information[C]∥9th International Conference on Signal Processing, Beijing,2008:2846-2850.
[4] Cover T M, Thomas J A.信息论基础[M]. 阮吉祥,张华,译.北京:机械工业出版社,2005.
[5] 魏秀业,潘宏侠.粒子群优化及智能故障诊断[M].北京:国防工业出版社,2010.
[6] 周龙甫,师亦兵,赵光,等.模拟电路单软故障的改进粒子群算法诊断[J].计算机应用研究,2010,27(11):4171-4188.
Zhou Long-fu, Shi Yi-bing, Zhao Guang, et al. Improved PSO method for single soft fault diagnosis in analog circuit[J]. Application Research of Computers,2010, 27(11):4171-4188.
[7] 王刚,刘元宁,张晓旭,等.基于模糊自适应粒子群的垃圾邮件过滤新方法[J].吉林大学学报:工学版,2011,41(3):716-720.
Wang Gang,Liu Yuan-ning, Zhang Xiao-xu,et al. Novel spam filtering method based on fuzzy adaptive particle swarm optimization[J]. Journal of Universi-
ty(Engineering and Technology Edition),2011,41(3):716-720.
[8] 龚纯,王正林.精通MATLAB最优化计算[M].北京:电子工业出版社,2012.
[9] Liu Hong, Chen Guang-ju, Song Guo-ming, et al.Neural network ensemble approach in analog circuit fault diagnosis[C]∥ISNN2009 Proceedings,Wuhan: LNCS& AISC, 2009:749-757.
[10] 宦若红,张平,潘斌贝.PCA、ICA和Gabor小波决策融合的SAR目标识别[J].遥感学报,2012,16(2):268-274.
Huan Ruo-hong, Zhang Ping, Pan Yun. SAR target recognition using PCA, ICA and Gabor wavelet decision fusion[J]. Journal of Remote Sensing,2012,16(2): 268-274.
[1] ZHAO Dong,SUN Ming-yu,ZHU Jin-long,YU Fan-hua,LIU Guang-jie,CHEN Hui-ling. Improved moth-flame optimization method based on combination of particle swarm optimization and simplex method [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1867-1872.
[2] LIU Yuan-ning, LIU Shuai, ZHU Xiao-dong, CHEN Yi-hao, ZHENG Shao-ge, SHEN Chun-zhuang. LOG operator and adaptive optimization Gabor filtering for iris recognition [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1606-1613.
[3] ZANG Guo-shuai, SUN Li-jun. Method based on inertial point for setting depth to rigid layer [J]. 吉林大学学报(工学版), 2018, 48(4): 1037-1044.
[4] HUANG Hui, FENG Xi-an, WEI Yan, XU Chi, CHEN Hui-ling. An intelligent system based on enhanced kernel extreme learning machine for choosing the second major [J]. 吉林大学学报(工学版), 2018, 48(4): 1224-1230.
[5] GENG Qing-tian, YU Fan-hua, WANG Yu-ting, GAO Qi-kun. New algorithm for vehicle type detection based on feature fusion [J]. 吉林大学学报(工学版), 2018, 48(3): 929-935.
[6] DONG Qiang, LIU Jing-hong, ZHOU Qian-fei. Improved SURF algorithm used in image mosaic [J]. 吉林大学学报(工学版), 2017, 47(5): 1644-1652.
[7] LIU Ying, ZHANG Kai, YU Xiang-jun. Multi-objective optimization of hydrostatic bearing of hollow shaft based on surrogate model [J]. 吉林大学学报(工学版), 2017, 47(4): 1130-1137.
[8] HUANG Xuan, GUO Li-hong, LI Jiang, YU Yang. Target threat assessment based on BP neural network optimized by modified particle swarm optimization [J]. 吉林大学学报(工学版), 2017, 47(3): 996-1002.
[9] SUN Liang, XU Hai-lang, GE Hong-wei. Novel global convergence stochastic particle swarm optimizers [J]. 吉林大学学报(工学版), 2017, 47(2): 615-623.
[10] ZHANG Jia-xu, LI Jing. Parameter identification for UniTire model based on hybrid optimization method [J]. 吉林大学学报(工学版), 2017, 47(1): 15-20.
[11] YIN Ming, ZHAN Yin-wei, PEI Hai-long. Co-sparse analysis operator learning for image fusion [J]. 吉林大学学报(工学版), 2016, 46(6): 2052-2058.
[12] LU Ying, WANG Hui-qin, QIN Li-ke. Accurate fire location method in high and large-span space buildings [J]. 吉林大学学报(工学版), 2016, 46(6): 2067-2073.
[13] ZHANG Jing, LIU Xiang-dong. Prediction of concrete strength based on least square support vector machine optimized by chaotic particle swarm optimization [J]. 吉林大学学报(工学版), 2016, 46(4): 1097-1102.
[14] YU He, QIN Gui-he, SUN Ming-hui, YAN Xin, WANG Xuan-zhe. Cyber security and anomaly detection method for in-vehicle CAN [J]. 吉林大学学报(工学版), 2016, 46(4): 1246-1253.
[15] JI Yan-jie, CHEN Xiao-shi, WANG Wei, HU Bo. Short-term forecasting of parking space using particle swarm optimization-wavelet neural network model [J]. 吉林大学学报(工学版), 2016, 46(2): 399-405.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright © Journal of Jilin University(Engineering and Technology Edition), All Rights Reserved.
Tel: +86-431-85095297　Fax: +86-431-85094074　E-mail: xbgxb@jlu.edu.cn
Powered by Beijing Magtech Co. Ltd