Health monitoring sensor placement optimization based on initial sensor layout using improved partheno-genetic algorithm

被引:19
|
作者
Qin, Xianrong [1 ]
Zhan, Pengming [1 ]
Yu, Chuanqiang [1 ]
Zhang, Qing [1 ]
Sun, Yuantao [1 ]
机构
[1] Tongji Univ, Sch Mech Engn, 1239 Siping Rd, Shanghai 200092, Peoples R China
关键词
effective independence method; initial sensor layout; optimal sensor placement; partheno-genetic algorithm; structural health monitoring; ORBIT MODAL IDENTIFICATION; PARAMETER-IDENTIFICATION; METHODOLOGY;
D O I
10.1177/1369433220947198
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
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.
引用
收藏
页码:252 / 265
页数:14
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