吉林大学学报(工学版) ›› 2012, Vol. 42 ›› Issue (01): 51-56.

• 论文 • 上一篇    下一篇

不同适应度函数的遗传算法在桥梁结构传感器布设中的应用

刘寒冰, 吴春利, 程永春   

  1. 吉林大学 交通学院,长春 130022
  • 收稿日期:2010-11-10 出版日期:2012-01-01 发布日期:2012-01-01
  • 通讯作者: 程永春(1961-),男,教授,博士生导师.研究方向:道路工程材料试验与理论.E-mail:chengyc@jlu.edu.cn E-mail:chengyc@jlu.edu.cn
  • 作者简介:刘寒冰(1957-),男,教授,博士生导师.研究方向:道桥结构的动态优化设计.E-mail:lhb@jlu.edu.cn
  • 基金资助:

    吉林大学"985工程"项目;"863"国家高技术研究发展计划项目(2009AA11Z104) );吉林大学创新团队项目(2009008) .

Sensor placement on bridge structure based on genetic algorithms with different fitness functions

LIU Han-bing, WU Chun-li, CHENG Yong-chun   

  1. College of Transportation, Jilin University,Changchun 130022, China
  • Received:2010-11-10 Online:2012-01-01 Published:2012-01-01

摘要:

从模态振型正交性和模态能量两方面出发设计了3个适应度函数,将其分别应用于改进遗传算法和单亲遗传算法。采用两步法对大跨径桥梁结构传感器布设进行定量和定位分析。通过对两种遗传算法、3个适应度函数及有效独立算法在大跨径拱桥中的对比分析,证实了单亲遗传算法比改进遗传算法更适合于桥梁结构传感器的布设,基于组合评价准则适应度函数比单一评价准则适应度函数布设出的传感器位置更加合理,验证了两步法用于传感器定量及定位计算的有效性 。

关键词: 道路工程, 桥梁结构, 传感器优化布设, 改进遗传算法, 单亲遗传算法, 适应度函数

Abstract:

Three fitness functions were designed from the mode orthogonality and the modal energy, and they were used to the improved genetic algorithm and the single parent genetic algorithm. A 2-step method was proposed to determine the number and the location of the sensors on the large-span bridge structures. According to the comparative analyses of these 2 algorithms, 3 fitness functions and the effective independence algorithm applied to the large-span arch bridge, the single parent genetic algorithm appeared more suitable to the sensor placement problem than the improved genetic algorithm, and the fitness function designed by the combined evaluation criteria was more reasonable than the one designed by the single evaluation criterion. The effectireness of the 2-step method for the placement of the sensors on the bridge structure is proved.

Key words: road engineering, bridge structure, sensor optimal placement, improved genetic algorithm, single parent genetic algorithm, fitness function

中图分类号: 

  • U441


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