期刊文献+

Sequential Fault Diagnosis Using an Inertial Velocity Differential Evolution Algorithm 被引量:4

Sequential Fault Diagnosis Using an Inertial Velocity Differential Evolution Algorithm
原文传递
导出
摘要 The optimal test sequence design for fault diagnosis is a challenging NP-complete problem.An improved differential evolution(DE)algorithm with additional inertial velocity term called inertial velocity differential evolution(IVDE)is proposed to solve the optimal test sequence problem(OTP)in complicated electronic system.The proposed IVDE algorithm is constructed based on adaptive differential evolution algorithm.And it is used to optimize the test sequence sets with a new individual fitness function including the index of fault isolation rate(FIR)satisfied and generate diagnostic decision tree to decrease the test sets and the test cost.The simulation results show that IVDE algorithm can cut down the test cost with the satisfied FIR.Compared with the other algorithms such as particle swarm optimization(PSO)and genetic algorithm(GA),IVDE can get better solution to OTP. The optimal test sequence design for fault diagnosis is a challenging NP-complete problem. An improved differential evolution(DE) algorithm with additional inertial velocity term called inertial velocity differential evolution(IVDE) is proposed to solve the optimal test sequence problem(OTP) in complicated electronic system. The proposed IVDE algorithm is constructed based on adaptive differential evolution algorithm. And it is used to optimize the test sequence sets with a new individual fitness function including the index of fault isolation rate(FIR) satisfied and generate diagnostic decision tree to decrease the test sets and the test cost. The simulation results show that IVDE algorithm can cut down the test cost with the satisfied FIR. Compared with the other algorithms such as particle swarm optimization(PSO) and genetic algorithm(GA), IVDE can get better solution to OTP.
出处 《International Journal of Automation and computing》 EI CSCD 2019年第3期389-397,共9页 国际自动化与计算杂志(英文版)
基金 supported by National Natural Science Foundation of Jiangxi Province, China (No. 20132BAB201044) Jiangxi Higher Technology Landing Project, China (No. KJLD12071)
关键词 Differential evolution(DE) EVOLUTIONARY computation FAULT isolation rate(FIR) TESTABILITY FAULT diagnosis Differential evolution(DE) evolutionary computation fault isolation rate(FIR) testability fault diagnosis
  • 相关文献

参考文献3

二级参考文献13

  • 1Pattipati K R, Alexandridis M. Application of heuristic search and information theory to sequential fault diagnosis. IEEE Transactions on SMC, 1990,20(4):872-887
  • 2Raghavan V, Shakeri M, Pattipati K R. Optimal and near optimal test sequencing algorithms with realistic test models. IEEE Transactions on SMC, 1999, 29(1): 11 27
  • 3Shakeri M, Raghavan V, Pattipati K R. Sequential testing algorithms for multiple fault diagnosis. IEEE Transactions on SMC, 2000, 30(1): 1-14
  • 4Tu Fang, Pattipati K R, Deb Set al. Computationally efficient algorithms for multiple fault diagnosis in large graphbased systems. IEEE Transactions on SMC, 2003, 33 (1) :73-85
  • 5Kundakcioglu O Erhun, Unltiyurt Tongue. Bottom-up construction of minimum-cost AND/OR trees for sequential fault diagnosis. IEEE Transactions on SMC, 2007, 37(5) : 621- 629
  • 6Kennedy J, Eberhart R C. Particle swarm optimization//Proceedings of the IEEE Conference on Neural Networks. IV, Piscataway, 1995: 1942-1948
  • 7Kennedy J, Eberhart R C. A discrete binary version of the particle swarm algorithm//Proceedings of the World Multiconference on Systemic, Cybernetics and Informatics. Piscataway, NJ, 1997:4104 -4109
  • 8Eberhart R C, Shi Y. Comparing inertia weights and constriction factors in particle swarm optimization//Proceedings of the 2000 Congress on Evolutionary Computation. San Diego, 2000:84-88
  • 9Sharon Goodall.Analog/Mixed Signal Fault Diagnosis Algorithm and Tool Review[].IEEE Autotestcon.1994
  • 10Mark Brodie,Irina Rish,Sheng Ma.Optimizing Probing Selection for Fault Localization[].Proceedings of DSOM.2001

共引文献26

同被引文献84

引证文献4

二级引证文献5

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