基于遗传算法的地下发电厂房动态识别  

Dynamic identification for underground power house based on genetic algorithm

作　　者：马震岳[1] 孙万泉[1] 陈维江[2] 

机构地区：[1]大连理工大学土木水利学院,辽宁大连116024 [2]中国水利水电科学研究院,北京100044

出　　处：《大连理工大学学报》2004年第2期292-296,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：结构的材料参数和边界条件是地下发电厂房动力特性分析研究中极为重要亦很难确定的控制参数.在借鉴以往反分析成果的基础上引入改进的遗传算法,实现了其与ANSYS软件的接口,并建立了结构最优化遗传动力识别通用模型.结合某抽水蓄能电站地下厂房结构的测试资料,反演识别了混凝土材料的动态弹性模量和围岩边界动态参数,可为工程应用提供参考.The parameters of the material and boundary condition are sensitive to the dynamic characteristics of the underground power house. Based on summarizing the development of inverse analysis methods, the improved genetic algorithm is jointed to the ANSYS Code and an optimal genetic dynamic identification model is obtained. Making use of the test data, the dynamic inverse analysis of an underground power house of a pumped storage power plant is carried out; and its average elastic modulus and the elastic resisting force of the surrounding rock are obtained.

关 键 词：遗传算法 地下发电厂房 动态识别 模态分析 水电站 结构最优化 

分 类 号：TV745[水利工程—水利水电工程]