期刊文献+

基于遗传算法的模拟电路故障诊断激励优化 被引量:4

Optimizing the Stimulus of Analog Circuits Diagnosis Based on Genetic Algorithm
在线阅读 下载PDF
导出
摘要 介绍了用改进的遗传算法优化激励信号的参数。仿真实验表明,经过优化后的激励信号能大大提高模拟电路的故障诊断效率,对线性和非线性模拟电路都适用。 The improved genetic algorithm is used to search the optimum stimulus. Experiment results demonstrate that the optimum stimulus has high fault identification. The method can be applied to linear and nonlinear analog circuits.
出处 《测控技术》 CSCD 2007年第6期20-22,共3页 Measurement & Control Technology
基金 国家自然科学基金(60372001)
关键词 遗传算法 模拟电路 故障诊断 genetic algorithm analog circuits fault diagnosis
  • 相关文献

参考文献6

  • 1Li F,Woo P Y.Fault detection for linear analog IC--the method of short-circuit admittance parameters[ J ].IEEE Transactions on Circuits and Systems Ⅰ:Fundamental Theory and Applications,2002,49 (1):105-108.
  • 2Cesare Alippi,Marcantonio Catelani,Ada Fort,et al.SBT soft fault diagnosis in analog electronic circuits:a sensitivity-based approach by randomized algorithms[ J ].IEEE Transactions on Instrumentation and Measurement,2002,51 (5):1 116-1 125.
  • 3Burdiek B.The qualitative form of optimum transient test signals for analog circuits derived from control theory methods[ A ].IEEE International Symposium on Circuits and Systems[ C ].2002-05.
  • 4李春华,杨戍,刘少亭.基于遗传算法的截集FCM灰度图像分割方法研究[J].西安科技大学学报,2006,26(1):85-88. 被引量:3
  • 5邝航宇,金晶,苏勇.自适应遗传算法交叉变异算子的改进[J].计算机工程与应用,2006,42(12):93-96. 被引量:98
  • 6Somnath Sinha Maha Patra,Kousik Roy,Sarthak Banerjee,etc.Improved genetic algorithm for channel allocation with channel borrowing in mobile computing[ J ].IEEE Transactions on Mobile Computing,2006,5(7).

二级参考文献21

  • 1沙智明,郝育黔,郝玉山,杨以涵.基于改进自适应遗传算法的电力系统相量测量装置安装地点选择优化[J].电工技术学报,2004,19(8):107-112. 被引量:15
  • 2章毓晋.图像分割[M].北京:科学出版社,2001.34.
  • 3Bezdek J C,Hathaway R J.Optimization of fuzzy clustering criteria using genetic algorithm[C] FUZZ-IEEE'1994:589-594.
  • 4Liu J Z,Xie W X.A genetic-based approach to fuzzy clustering[J].FUZZY-IEEE'95,Japan,1995:2 233-2 240.
  • 5Bezdek J C.Pattern Recognition with Fuzzy Objective Function Algorithm[M].Plenum Press,New York,1981.
  • 6Shorkl Z.Selm.Soft clustering of multidimensional Data A SEMI-FUZZY approach[J].Pattern Recognition,1984,17(5):559-568.
  • 7Srinivas M,Parnaik L M.Adaptive Probabilities of Crossover and Mutations in Gas.[C]IEEE Trans.onSMC,1994,24(4):656-667.
  • 8Liedtke C E.Segmentation of Microscopic Cell Scenes[C].AQCH,1987:197-211.
  • 9Grnaf C N.Validation of the Interleved Pyramid for the Segmentation of 3D Vector Image[J].Pattern Recognition Letters,1994,15:467-475.
  • 10J H Holland.Adaptation in Natural Artificial Systems[M].MIT Press,1975

共引文献99

同被引文献23

引证文献4

二级引证文献8

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