基于多目标差分进化算法的结构物理参数辨识
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摘要
优化算法在用于结构的物理参数辨识时,测量数据的不完备和噪声严重影响了参数的辨识精度。针对这一问题,为得到理想的辨识精度,将时程响应数据和频率数据定义为多目标函数,并利用多目标差分进化算法(DEMO)进行优化求解。在数值模拟中,利用10层剪切型框架结构和31个单元的桁架桥结构作为算例。计算结果表明,该多目标函数和DEMO算法,利用不完备的且含有噪声的测量数据,可以得到具有较高精度的辨识结果。
Using optimization algorithms to identify structural physical parameters,the identification precision is seriously influenced by incomplete measurement and noise.In order to solve this problem,a new multi-objective function defined by dynamic responses and frequencies was proposed,and the Multi-objective Differential Evolution Optimization(DEMO) was used to obtain optimal solutions.In numerical simulation,a 10-floor shear structure and 31 elements truss structure were identified,and the results proved that the multi-objective function and DEMO using incomplete noise measurements can get highly precise identification results.
Using optimization algorithms to identify structural physical parameters,the identification precision is seriously influenced by incomplete measurement and noise.In order to solve this problem,a new multi-objective function defined by dynamic responses and frequencies was proposed,and the Multi-objective Differential Evolution Optimization(DEMO) was used to obtain optimal solutions.In numerical simulation,a 10-floor shear structure and 31 elements truss structure were identified,and the results proved that the multi-objective function and DEMO using incomplete noise measurements can get highly precise identification results.
引文
[1]李宏男,李东升.土木工程结构安全性评估、健康监测及诊断综述[J].地震工程与工程振动,2002,22(3):82-90.
[2]裴强,郭迅,张敏政.桥梁健康监测及诊断研究综述[J].地震工程与工程振动,20032,3(2):61-67.
[3]Hesheng Tang,Songtao Xue,Cunxin Fan.Differential evolution strategy for structural system identification[J].Computers and Structures,2008,86(21-22):2004-2012.
[4]Perera R,Ruiz A,Manzano C.An evolutionary multiobjective framework for structural damage localization and quantification[J].EngineeringStructures,2007,29(10):2540-2550.
[5]Nadia Nedjah,Leandro dos Santos Coelho,Luiza Macedo Mourelle.Multi-objective Swarm Intelligent systems:theory&Experiences[M].Germa-ny:Springer,2009.
[6]Zhang Z,Koh C G,Duan W H.Uniformly sampled genetic algorithm with gradient search for structural identification-Part II:Local search[J].Computers and Structures,2010,88:1149-1161.
[7]Price K,Storn R,Lampinen J.Differential evolution a practical approach to global optimization[M].Germany:Springer,2009.
[8]Kalyanmoy Deb,Amrit Pratap,Sameer Agarwal,Meyarivan T.A fast and elitist multiobjective genetic algorithm:NSGA-II[J].IEEE Transac-tions on Evolutionary Computation,2002,6(2):182-197.
[9]Tea Robic,Bogdan Filipi.DEMO:Differential evolution for multi-objective optimization[C]//Proceedings of the 3rd International Conferenceon Evolutionary Multi-Criterion Optimization.Germany:Springer,2005:520-533.
[10]Vesterstr M J,Thomsen R.A comparative study of differential evolution,particle swarm optimization,and evolutionary algorithms on numericalbenchmark problems[C]//Congress on Evolutionary Computation,USA:IEEE,2004:1980-1987.
[2]裴强,郭迅,张敏政.桥梁健康监测及诊断研究综述[J].地震工程与工程振动,20032,3(2):61-67.
[3]Hesheng Tang,Songtao Xue,Cunxin Fan.Differential evolution strategy for structural system identification[J].Computers and Structures,2008,86(21-22):2004-2012.
[4]Perera R,Ruiz A,Manzano C.An evolutionary multiobjective framework for structural damage localization and quantification[J].EngineeringStructures,2007,29(10):2540-2550.
[5]Nadia Nedjah,Leandro dos Santos Coelho,Luiza Macedo Mourelle.Multi-objective Swarm Intelligent systems:theory&Experiences[M].Germa-ny:Springer,2009.
[6]Zhang Z,Koh C G,Duan W H.Uniformly sampled genetic algorithm with gradient search for structural identification-Part II:Local search[J].Computers and Structures,2010,88:1149-1161.
[7]Price K,Storn R,Lampinen J.Differential evolution a practical approach to global optimization[M].Germany:Springer,2009.
[8]Kalyanmoy Deb,Amrit Pratap,Sameer Agarwal,Meyarivan T.A fast and elitist multiobjective genetic algorithm:NSGA-II[J].IEEE Transac-tions on Evolutionary Computation,2002,6(2):182-197.
[9]Tea Robic,Bogdan Filipi.DEMO:Differential evolution for multi-objective optimization[C]//Proceedings of the 3rd International Conferenceon Evolutionary Multi-Criterion Optimization.Germany:Springer,2005:520-533.
[10]Vesterstr M J,Thomsen R.A comparative study of differential evolution,particle swarm optimization,and evolutionary algorithms on numericalbenchmark problems[C]//Congress on Evolutionary Computation,USA:IEEE,2004:1980-1987.
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