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为了有效选择监控模态振型阶数,并使振型向量间夹角和测点振动能量同时尽可能大,提出了基于模态能量和自适应遗传算法的多目标传感器优化布置方法。首先,根据结构模态应变能的大小挑选出环境激励下结构的主要贡献模态,即优化时所取的监控模态。然后,根据单位刚度的模态运动能以及模态置信度矩阵构造新的适应度函数,利用自适应遗传算法对布点进行优化。以国家游泳中心钢结构为工程背景,对其模态测试时加速度传感器布点进行了优化。计算结果表明:所提方法适用于环境激励下大跨空间钢结构模态测试时传感器的优化布置。
In order to effectively select the mode shapes of the monitoring modes and maximize the angle between the mode shapes and the vibration energy at the measuring point, a multi-objective optimization method based on modal energy and adaptive genetic algorithm is proposed. First of all, according to the magnitude of the structural modal strain energy, the main contribution mode of the structure under environmental excitation is selected, that is, the monitoring modality taken during optimization. Then, a new fitness function is constructed according to the modal kinetic energy of unit stiffness and the modal confidence matrix, and the distribution point is optimized by using adaptive genetic algorithm. Taking the steel structure of National Swimming Center as the engineering background, the acceleration sensor placement during modal testing was optimized. The calculation results show that the proposed method is suitable for the optimal placement of sensors in the modal testing of long-span space steel structures under environmental excitation.