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Multi-type, multi-sensor placement optimization for structural health monitoring of long span bridges

机译:用于大跨度桥梁结构健康监测的多类型,多传感器放置优化

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The paper presents a multi-objective optimization strategy for a multi-type sensor placement for Structural Health Monitoring (SHM) of long span bridges. The problem is formulated for simultaneous placement of strain sensors and accelerometers (heterogeneous network) based on application demands for SHM system. Modal Identification (MI) and Accurate Mode Shape Expansion (AMSE) were chosen as the application demands for SHM. The optimization problem is solved through the use of integer Genetic Algorithm (GA) to maximize a common metric to ensure adequate MI and AMSE. The performance of the joint optimization problem solved by GA is compared with other established methods for homogenous sensor placement. The results indicate that the use of a multi-type sensor system can improve the quality of SHM. It has also been demonstrated that use of GA improves the overall quality of the sensor placement compared to other methods for optimization of sensor placement.
机译:本文提出了一种用于大跨度桥梁结构健康监测(SHM)的多类型传感器放置的多目标优化策略。根据SHM系统的应用需求,提出了同时放置应变传感器和加速度计(异构网络)的问题。选择模式识别(MI)和精确模式形状扩展(AMSE)作为SHM的应用需求。通过使用整数遗传算法(GA)来最大化通用度量以确保足够的MI和AMSE来解决优化问题。将遗传算法解决的联合优化问题的性能与同质传感器放置的其他已建立方法进行比较。结果表明,使用多种类型的传感器系统可以提高SHM的质量。还已经证明,与其他用于优化传感器放置的方法相比,GA的使用提高了传感器放置的整体质量。

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