基于自适应伪并行遗传算法的动力学参数识别  

Identification of dynamic parameters based on adaptive pseudo-parallel genetic algorithms

作　　者：赵凤遥[1] 马震岳[1] 王溢波[1] 

机构地区：[1]大连理工大学土木水利学院

出　　处：《大连理工大学学报》2007年第2期252-256,共5页Journal of Dalian University of Technology

基　　金：国家自然科学基金资助项目(50279003)

摘　　要：为研究结构动力学参数识别问题,引入一种新的度量种群多样性的指标,构造了新的自适应遗传算子,结合伪并行遗传算法,改进了遗传算法的全局收敛性和收敛速度;利用ANSYS程序的参数编程,将其成功应用于动力学模型中弹性模量和阻尼的识别.数值试验表明,该方法具有满意的识别效果,并具有较强的抗噪能力,可用于工程实际.For the parameters identification of dynamic problems, the convergence and convergence velocity could be improved through the creating of new self-adaptive genetic operators and the coupling with the idea of pseudo-parallel genetic algorithms by the introduction of a new index which can reflect the diversity of population in genetic algorithms. With the APDL （ANSYS parametic design language） parameter programme of ANSYS, the improving genetic algorithms were applied to the identification of dynamic parameters successfully. Practical example shows that the method has a great advantage and has a strong anti-noise ability, and it can be used in engineering practice.

关 键 词：参数识别 自适应 伪并行 遗传算法 ANSYS 

分 类 号：TM312[电气工程—电机]