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以网壳结构为对象,利用粒子群算法研究了其环向和径向杆件上传感器的最优布点。首先讨论了粒子群算法的基本原理和优点以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;接着,以凯威特型网壳为例讨论了用粒子群算法求大跨度空间网壳结构最优测点。针对应变传感器提出了相应的适应度由曲率模态表示,根据该适应度采用粒子群算法搜索了凯威特型网壳上的应变传感器最优布点。研究结果表明,采用粒子群算法搜索网壳结构监测系统中应变传感器最优布点方法,计算结果稳定可靠,收敛速度迅速。
With the reticulated shell structure as the object, the optimal distribution points of the sensors on the circumferential and radial rods were studied by using particle swarm optimization algorithm. Firstly, the basic principles and advantages of Particle Swarm Optimization (PSO) algorithm and the optimal placement of sensors in structural health monitoring system for detecting cumulative damage are discussed. Then, a case study of the Keyweave Reticulated Shell is discussed. Particle Swarm Optimization Reticular shell structure of the best measuring point. According to the strain sensor, the corresponding fitness is expressed by the curvature modal. According to the fitness, the particle swarm optimization algorithm is used to search the optimum distribution point of the strain sensor on the Kaiweite reticulated shell. The results show that the particle swarm optimization algorithm is used to search the optimal placement method of strain sensor in the monitoring system of reticulated shell structure. The results are stable and reliable and the convergence speed is fast.