摘要
本文利用遗传算法搜索悬索桥结构健康监测系统中传感器的最优测点。以青马悬索桥为对象，研究其加劲梁和桥塔上传感器的最优布点。在讨论经典遗传算法的基本原理和优点，及在结构健康监测系统中，为探测累积损伤用的传感器最优布点之后，本文讨论了广义遗传算法，并用一个算例比较了广义遗传算法和经典遗传算法，结果表明广义遗传算法比经典遗传算法有明显改进。最后，以香港青马桥为例讨论了用广义遗传算法求大跨度悬索桥最优测点，文中针对不同传感器及不同目的提出了三个适应度，它们分别由位移模态和曲率模态表示。并根据这三个适应度用广义遗传算法搜索了青马桥上传感器最优布点。结果表明，用广义遗传算法搜索悬索桥监测系统中传感器的最优布点结果稳定可靠，且收敛迅速。
Damage detection is the most difficult part of Structural health monitoring systems. In order to acquire response information as much as possible, sensors should be carefully placed. Taking Tsing Ma bridge as an example and using the genetic algorithms (GAs), this paper discussed the optimal placement of sensors on suspension bridges for detection of accumulated damage for structural health monitoring systems. After a brief discussion on the classical GAs and background of the monitoring systems, the paper described the generalized GAs, and used an example to compare them with the clasaical GAs. The results show that the generallied GAs are clearly more effective than the classical GAs. On the baals of displacement and curvature modes, three expressions of the fitness were defined for different sensors and tasks. The generalized GAs were used to search the optimal placement of accelerometers and strain gages on the stiffening decks and the towers of Tsing Ma bridge. The results show that the generalized GAs give reliable and stable results with rapid convergence.
出处
《工程力学》
EI
CSCD
北大核心
2000年第1期25-34,共10页
Engineering Mechanics
基金
国家攀登计划B‘大型土木与水利工程安全性与耐久性的基础研究’资助
关键词
遗传算法
传感器
最优布点
监测系统
悬索桥
genetic algorithms
optimal placement of sensors
displacement modes, curvature modes
structural health monitoring systems
damage detection, suspension bridges
