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Health monitoring sensor placement optimization based on initial sensor layout using improved partheno-genetic algorithm
Advances in Structural Engineering ( IF 2.1 ) Pub Date : 2020-08-18 , DOI: 10.1177/1369433220947198
Xianrong Qin 1 , Pengming Zhan 1 , Chuanqiang Yu 1 , Qing Zhang 1 , Yuantao Sun 1
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Optimal sensor placement is an important component of a reliability structural health monitoring system for a large-scale complex structure. However, the current research mainly focuses on optimizing sensor placement problem for structures without any initial sensor layout. In some cases, the experienced engineers will first determine the key position of whole structure must place sensors, that is, initial sensor layout. Moreover, current genetic algorithm or partheno-genetic algorithm will change the position of the initial sensor locations in the iterative process, so it is unadaptable for optimal sensor placement problem based on initial sensor layout. In this article, an optimal sensor placement method based on initial sensor layout using improved partheno-genetic algorithm is proposed. First, some improved genetic operations of partheno-genetic algorithm for sensor placement optimization with initial sensor layout are presented, such as segmented swap, reverse and insert operator to avoid the change of initial sensor locations. Then, the objective function for optimal sensor placement problem is presented based on modal assurance criterion, modal energy criterion, and sensor placement cost. At last, the effectiveness and reliability of the proposed method are validated by a numerical example of a quayside container crane. Furthermore, the sensor placement result with the proposed method is better than that with effective independence method without initial sensor layout and the traditional partheno-genetic algorithm.

中文翻译:

基于改进单性遗传算法的初始传感器布局的健康监测传感器布局优化

最佳传感器放置是大型复杂结构可靠性结构健康监测系统的重要组成部分。然而,目前的研究主要集中在优化没有任何初始传感器布局的结构的传感器放置问题。在某些情况下,有经验的工程师会首先确定整个结构必须放置传感器的关键位置,即初始传感器布局。而且,当前的遗传算法或孤雌遗传算法会在迭代过程中改变初始传感器位置的位置,因此无法适应基于初始传感器布局的最优传感器放置问题。在本文中,提出了一种基于初始传感器布局的优化传感器放置方法,使用改进的孤雌遗传算法。第一的,提出了一些改进的孤雌遗传算法的遗传操作,用于传感器初始布局优化的传感器布局,如分段交换、反向和插入算子,以避免初始传感器位置的变化。然后,基于模态保证准则、模态能量准则和传感器放置成本,提出了最优传感器放置问题的目标函数。最后,通过岸边集装箱起重机的数值算例验证了所提方法的有效性和可靠性。此外,该方法的传感器放置结果优于没有初始传感器布局的有效独立方法和传统的孤雌遗传算法。反转并插入操作符以避免初始传感器位置的变化。然后,基于模态保证准则、模态能量准则和传感器放置成本,提出了最优传感器放置问题的目标函数。最后,通过岸边集装箱起重机的数值算例验证了所提方法的有效性和可靠性。此外,该方法的传感器放置结果优于没有初始传感器布局的有效独立方法和传统的孤雌遗传算法。反转并插入操作符以避免初始传感器位置的变化。然后,基于模态保证准则、模态能量准则和传感器放置成本,提出了最优传感器放置问题的目标函数。最后,通过岸边集装箱起重机的数值算例验证了所提方法的有效性和可靠性。此外,该方法的传感器放置结果优于没有初始传感器布局的有效独立方法和传统的孤雌遗传算法。通过岸边集装箱起重机的数值算例验证了所提出方法的有效性和可靠性。此外,该方法的传感器放置结果优于没有初始传感器布局的有效独立方法和传统的孤雌遗传算法。通过岸边集装箱起重机的数值算例验证了所提出方法的有效性和可靠性。此外,该方法的传感器放置结果优于没有初始传感器布局的有效独立方法和传统的孤雌遗传算法。
更新日期:2020-08-18
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