期刊文献+
任意字段
题名或关键词
题名
关键词
文摘
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息

Soft Fault Diagnosis of Analog Circuit Based on Particle Swarm Optimization

Soft Fault Diagnosis of Analog Circuit Based on Particle Swarm Optimization
下载PDF
导出
摘要 A single soft fault diagnosis method for analog circuit with tolerance based on particle swarm optimization （PSO） is proposed. The parameter deviation of circuit elements is defined as the element of particle. Node-voltage incremental equations based on the sensitivity analysis are built as constraints of a linear programming （LP） equation. Through inducing the penalty coefficient, the LP equation is set as the fitness function for the PSO program. After evaluating the best position of particles, the position of the optimal particle states whether the actual parameter is within tolerance range or not. Simulation result shows the effectiveness of the method. A single soft fault diagnosis method for analog circuit with tolerance based on particle swarm optimization （PSO） is proposed. The parameter deviation of circuit elements is defined as the element of particle. Node-voltage incremental equations based on the sensitivity analysis are built as constraints of a linear programming （LP） equation. Through inducing the penalty coefficient, the LP equation is set as the fitness function for the PSO program. After evaluating the best position of particles, the position of the optimal particle states whether the actual parameter is within tolerance range or not. Simulation result shows the effectiveness of the method.
作者 Long-Fu Zhou Yi-Bing Shi Wei Zhang
机构地区 School of Automation Engineering
出处 《Journal of Electronic Science and Technology of China》 2009年第4期358-361,共4页 中国电子科技（英文版）
基金 supported by the Program for New Century Excellent Talents in University under Grant No.NCET-05-0804 partly supported by Chinese National Programs for High Technology Research and Development under Grant No.2006AA06Z222
关键词 Analog circuit DIAGNOSIS linear program particle swarm optimization soft fault. Analog circuit, diagnosis, linear program, particle swarm optimization, soft fault.
分类号 TN949.7 [电子电信—信号与信息处理] TP18 [自动化与计算机技术—控制理论与控制工程]
  • 相关文献

参考文献9

  • 1J. W. Bandler and A. E. Salama, "Fault diagnosis of analog circuits," Proceeding of IEEE, vol. 73, no. 8, pp. 1279-1325, 1985.
  • 2F. Li and P.-Y. Woo, "The invariance of node-voltage sensitivity sequence and its application in a unified fault detection dictionary method," IEEE Trans. on Circuits and System 1, vol. 46, no. 10, pp. 1222-1227, 1999.
  • 3L. Zhou and Y. Shi, "Soft fault diagnosis in analog circuit based on fuzzy and direction vector," Metrology and Measurement Systems, vol. ⅩⅥ, no. 1, pp. 61-75, 2009.
  • 4M. Tadeusiewicz, S. Halgas, and M. Korzybski, "An algorithm for soft-fault diagnosis of linear and nonlinear circuits," IEEE Trans. on Circuits and System Ⅰ, vol. 49, no. 11, pp. 648-1653, 2002.
  • 5R. Eberhart and J. Kennedy, "A new optimizer using particle swarm theory," in Proc. of the Sixth International Symposium on Micro Machine and Human Science, Nagoya, 1995, pp. 39-43.
  • 6Z.-H. Wu and L. Wang, "Overview of particle swarm optimization," Computer Knowledge and Technology, vol. 1, no. 7, pp. 1270-1274, Jul. 2008 (in Chinese).
  • 7Y.-L. Gao, C.-X. Xu, and J.-M. Li. "Linear programming relax-PSO hybrid bound algorithm for a class of nonlinear integer programming problems," in Proc. of 2006 International Conference on Computational Intelligence and Security, Guangzhou, 2006, pp. 380-383.
  • 8B. Yang, Y.-P Chen, Z.-L. Zhao, and Q.-Y. Han. "A master-slave particle swarm optimization algorithm for solving constrained optimization problems," in Proe. of the 6th Worm Congress on Intelligent Control and Automation, Dalian, 2006, pp. 3208-3212.
  • 9D.-Q. Guo, Y.-J. Zhao, H. Xiong, and X. Li, "A new class of hybrid particle swarm optimization algorithm," Journal of Electronic Science and Technology of China, vol. 5, no. 2, pp. 149-152, 2007.
Journal of Electronic Science and Technology of China
2009年 第4期

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部