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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。
In this paper, genetic algorithm is used to search the optimal measuring points of the sensors in the suspension bridge structural health monitoring system. Taking Tsing Ma Suspension Bridge as an example, the optimal distribution of the sensors on stiffened girders and bridge towers is studied. After discussing the basic principles and advantages of classical genetic algorithm and the optimal placement of sensors for structural damage detection in structural health monitoring system, this paper discusses the generalized genetic algorithm and compares it with the generalized genetic algorithm The results show that the generalized genetic algorithm has obvious improvement over the classical genetic algorithm. Finally, taking Tsing Ma Bridge in Hong Kong as an example, the optimal measurement points of the long-span suspension bridge using the generalized genetic algorithm are discussed. Three fitness values are proposed for different sensors and different purposes. They are expressed by the displacement modal and the curvature modal respectively. According to these three fitness indexes, the optimal sensor points on Tsing Ma Bridge were searched by generalized genetic algorithm. The results show that using the generalized genetic algorithm to search the suspension bridge monitoring system, the optimal location of the sensor is stable and reliable, and converges rapidly.