期刊文献+

基于改进粒子群算法的损伤检测数值仿真研究 被引量:1

Simulation Study of Damage Detection Based on Particle Swarm Optimization
下载PDF
导出
摘要 结构损伤检测在数学上常转化为约束优化问题.首先介绍了粒子群算法(PSO)的基本理论,并在分析传统粒子群算法容易陷入局部极小原理的基础上,提出了旨在增强粒子群算法后期粒子摆脱局部极小能力的改进粒子群算法(IPSO).5个常用测试函数的测试结果表明,改进粒子群算法的性能优于传统粒子群算法.最后通过两层钢框架多种损伤工况的数值研究,进一步验证了改进粒子群算法的优越性及其应用于损伤检测领域的可行性. Stru analysis of ctural damage detectio the theory of the parti increase the diversity of the particles benchmark functions; and the result steel frame structure with single and ble tool for structural damage detecti n often can be inverted into a constrained optimization problem. Based on cle swarm optimization (PSO), an improved PSO is proposed, aiming to in the later phase of the PSO. The improved PSO is first studied by five shows that it is superior to the basic PSO. Then it is simulated by the two damage detections; the results show that the improved PSO is a usaon.
出处 《三峡大学学报(自然科学版)》 CAS 2006年第5期409-414,共6页 Journal of China Three Gorges University:Natural Sciences
关键词 损伤检测 粒子群算法 框架结构 damage detection particle swarm optimization(PSO) frame structure
  • 相关文献

参考文献7

  • 1朱宏平,徐斌,黄玉盈.结构动力模型修正方法的比较研究及评估[J].力学进展,2002,32(4):513-525. 被引量:48
  • 2Kennedy J,Eberhart R C.Particle Swarm Optimization[A].Proc.IEEE Int.Conf.Neural Networks[C].Piscataway,NJ:IEEE Press,1995:216-219.
  • 3Kennedy J,Eberhart R C,Shi Y.Swarm Intelligence[M].San Francisco:Morgan Kaufmann Publishers,2001:226-232.
  • 4Van den Bergh F,Engelbrecht A P.Training Product Unit Networks Using Cooperative Particle Swarm Optimizers[C].In:Proc of the third Genetic and Evolutionary Computation Conference (GECCO),San Francisco,USA,2001:153-159.
  • 5孙木楠,史志俊.基于粒子群优化算法的结构模型修改[J].振动工程学报,2004,17(3):350-353. 被引量:18
  • 6Shi Y H,Eberhart R C.Parameter Selection in Particle Swarm Optimization[C].Annual,1998:54-62.
  • 7Shi Y H,Eberhart R C.A modified Particle Swarm Optimizer[C].In:IEEE World Congress on Computational Intelligence,1998:69-73.

二级参考文献72

  • 1Kennedy J,Eberhart R C. Particle swarm optimization.In: Proc. IEEE Int. Conf. Neural Networks, Perth, Australia,1995:1 942-1 948
  • 2Eberhart R C,Kennedy J. A new optimizer using particle swarm theory. In: Proc. Int. Symposium Micro Machine and Human Science ,Japan, 1995: 39-43
  • 3Srinivasan D,Wee H L,Ruey L C. Traffic incident detection using particle swarm optimization. In:Proc. Int.Swarm Intelligence Symposium, 2003: 144-151
  • 4Higashi N,Iba H. Particle swarm optimization with gaussian mutation. In:Proc. Int. Swarm Intelligence Symposium, 2003: 72-79
  • 5Venter G. Particle Swarm Optimization. AIAA-2002-1235,2002
  • 6Shi Y,Eberhart R C. Empirical study of particle swarm optimization. In :Proc. Congress on Evolutionary Computation,1999:1 945-1950
  • 7Hu X, Eberhart R. Solving constrained nonlinear optimization problems with particle swarm optimization. 6th World Multiconference on Systemics, Cybernetics and Informatics, Orlando, USA, 2002
  • 8向锦武,周传荣,张阿舟.基于建模误差位置识别的有限元模型修正方法[J].振动工程学报,1997,10(1):1-7. 被引量:16
  • 9徐宜桂,史铁林,杨叔子.基于神经网络的结构动力模型修改和破损诊断研究[J].振动工程学报,1997,10(1):8-12. 被引量:44
  • 10Bathe K J. Finite Element Procedures in Engineering Analysis. New Jersey: Prentice-Hall, Englewood Cliffes,1982. 1~5

共引文献59

同被引文献12

引证文献1

二级引证文献1

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