Optimal Sensor Placement and Evaluation Method of Stone Arch Bridge Based on Meta-Genetic Algorithm
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摘要:
为开发古代石拱桥传感器优化布置方法，本文以全国重点文物保护单位北京卢沟桥为例，建立考虑初始残损和材料参数随机的传感器优化计算模型；提出考虑复杂监测目标的适应度函数设计与求解方法、以元学习思想为基础的元遗传算法，对传感器优化布置问题进行搜优；并将提出方法与2种基于传统遗传算法的优化模式进行对比，实现了面向古代石拱桥的高效传感器优化布置. 研究结果表明：所提出方法具有更好的参数识别能力、损伤灵敏度与信息冗余水平；当噪声水平在5%以内时，元遗传算法给出的方案均可成功检测损伤，而另外2种方案的损伤检测成功率仅60.0%；当噪声水平达到10%时，元遗传算法给出方案可以检测出60.0%的损伤，而其他2种方案无法有效检测出损伤.
Abstract:To develop an optimal sensor placement method for ancient stone arch bridges, by taking the Beijing Lugou Bridge, a national key cultural relics protection unit, as an example, a sensor optimization model considering initial damage and random material parameters was established. A fitness function design and solution method considering complex monitoring targets was proposed, along with a meta-genetic algorithm based on the concept of meta-learning for solving the sensor placement optimization problem. The proposed method was compared with two optimization methods based on conventional genetic algorithms, achieving optimal sensor placement for ancient stone arch bridges. The results show that the proposed method offers better parameter identification capability, damage sensitivity, and information redundancy level. When the noise level is within 5%, the sensor placement scheme given by the meta-genetic algorithm can successfully detect the damage, while the other two methods achieve only a 60.0% success rate. When the noise level reaches 10%, the meta-genetic algorithm can detect 60.0% of the damage, while the other two methods fail to detect damage effectively.
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图 5 3种优化模式得出的最优传感器布设方案
Figure 5. Optimal sensor placement schemes obtained by three optimization modes
表 1 材料信息
Table 1. Information on materials
材料 弹性模量/ MPa 密度/（kg·m−3） 泊松比 石砌体 2450 2556 0.15 内填土 1000 1938 0.20 
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表 2 荷载信息
Table 2. Information on loads
噪声峰值/（×g） 权重 权重设置 0.002 1.000 实测服役峰值加速度，g为重力加速度，假定其发生概率为100% 0.050 0.815 扫频白噪声峰值，概率设定为0.001g与0.100g工况的均值 0.100 0.630 50年一遇多遇地震的加速度峰值，发生概率为63% 0.200 0.100 50年一遇设防地震的加速度峰值，发生概率为10% 0.300 0.030 50年一遇罕遇地震的加速度峰值，发生概率为3%
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