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为了将动态测试中的传感器配置在合理的自由度,以便充分反映结构的动力特性,需对传感器进行优化配置。分别以MAC矩阵、Fisher信息阵,及其组合为优化准则,采用微粒群算法,对传感器优化配置问题进行了研究,探讨了优化准则和优化算法对传感器优化配置结果的影响。通过与模态动能法、有效独立法及基于QR分解的逐步累积法比较,传感器优化配置的结果表明微粒群算法优于上述方法。
In order to configure the sensors in the dynamic test with a reasonable degree of freedom to fully reflect the dynamic characteristics of the structure, the sensors need to be optimally configured. Using the MAC matrix, Fisher information matrix, and their combination as optimization criteria respectively, the particle swarm optimization algorithm is used to study the optimal configuration of sensors. The influence of optimization rules and optimization algorithms on the optimal configuration of sensors is discussed. Compared with the modal kinetic energy method, the effective independent method and the step-by-step cumulant method based on QR decomposition, the results of the optimal sensor configuration show that the PSO is superior to the above method.