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A triaxial accelerometer monkey algorithm for optimal sensor placement in structural health monitoring

机译:三轴加速度计猴子算法在结构健康监测中优化传感器放置

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摘要

Optimal sensor placement (OSP) technique is a vital part of the field of structural health monitoring (SHM). Triaxial accelerometers have been widely used in the SHM of large-scale structures in recent years. Triaxial accelerometers must be placed in such a way that all of the important dynamic information is obtained. At the same time, the sensor configuration must be optimal, so that the test resources are conserved. The recommended practice is to select proper degrees of freedom (DOF) based upon several criteria and the triaxial accelerometers are placed at the nodes corresponding to these DOFs. This results in non-optimal placement of many accelerometers. A 'triaxial accelerometer monkey algorithm' (TAMA) is presented in this paper to solve OSP problems of triaxial accelerometers. The EFI3 measurement theory is modified and involved in the objective function to make it more adaptable in the OSP technique of triaxial accelerometers. A method of calculating the threshold value based on probability theory is proposed to improve the healthy rate of monkeys in a troop generation process. Meanwhile, the processes of harmony ladder climb and scanning watch jump are proposed and given in detail. Finally, Xinghai NO. 1 Bridge in Dalian is implemented to demonstrate the effectiveness of TAMA. The final results obtained by TAMA are compared with those of the original monkey algorithm and EFI3 measurement, which show that TAMA can improve computational efficiency and get a better sensor configuration.
机译:最佳传感器放置(OSP)技术是结构健康监测(SHM)领域的重要组成部分。近年来,三轴加速度计已广泛用于大型结构的SHM中。三轴加速度计的放置方式必须能获得所有重要的动态信息。同时,传感器配置必须是最佳的,以便节省测试资源。推荐的做法是根据几个标准选择适当的自由度(DOF),并将三轴加速度计放置在与这些DOF相对应的节点上。这导致许多加速度计的非最佳放置。为了解决三轴加速度计的OSP问题,本文提出了一种“三轴加速度计猴子算法”(TAMA)。 EFI3测量理论经过修改并包含在目标函数中,以使其更适合于三轴加速度计的OSP技术。提出了一种基于概率论的阈值计算方法,以提高猴子在部队生成过程中的健康率。同时,提出并详细给出了和谐阶梯爬升和扫描表跳跃的过程。最后,星海号。大连的一座大桥被实施以证明TAMA的有效性。将TAMA的最终结果与原始猴子算法和EFI3测量的结果进行比较,表明TAMA可以提高计算效率并获得更好的传感器配置。

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