A multiobjective sensor placement optimization for SHM systems considering Fisher information matrix and mode shape interpolation

2018 ◽  
Vol 35 (2) ◽  
pp. 519-535 ◽  
Author(s):  
Guilherme Ferreira Gomes ◽  
Fabricio Alves de Almeida ◽  
Patricia da Silva Lopes Alexandrino ◽  
Sebastiao Simões da Cunha ◽  
Bruno Silva de Sousa ◽  
...  
Keyword(s):  
Fisher Information ◽  
Mode Shape ◽  
Fisher Information Matrix ◽  
Information Matrix ◽  
Sensor Placement ◽  
Placement Optimization ◽  
Sensor Placement Optimization ◽  
Shape Interpolation

scholarly journals Optimal sensor placements using modified Fisher information matrix and effective information algorithm

2021 ◽  
Vol 17 (6) ◽  
pp. 155014772110230
Author(s):  
Eun-Taik Lee ◽  
Hee-Chang Eun
Keyword(s):  
Fisher Information ◽  
Mode Shape ◽  
Fisher Information Matrix ◽  
Information Matrix ◽  
Sensor Placement ◽  
Degree Of Freedom ◽  
Optimal Sensor Placement ◽  
Parameter Matrix ◽  
Placement Algorithm ◽  
Sensor Locations

This article presents an optimal sensor placement algorithm for modifying the Fisher information matrix and effective information. The modified Fisher information matrix and effective information are expressed using a dynamic equation constrained by the condensed relationship of the incomplete mode shape matrix. The mode shape matrix row corresponding to the master degree of freedom of the lowest-contribution Fisher information matrix and effective information indices is moved to the slave degree of freedom during each iteration to obtain an updated shape matrix, which is then used in subsequent calculations. The iteration is repeated until the target sensors attain the targeted number of modes. The numerical simulations are then applied to compare the optimal sensor placement results obtained using the number of installed sensors, and the contribution matrices using the Fisher information matrix and effective information approaches are compared based on the proposed parameter matrix. The mode-shape-based optimal sensor placement approach selects the optimal sensor layout at the positions to uniformly allocate the entire degree of freedom. The numerical results reveal that the proposed F-based and effective information–based approaches lead to slightly different results, depending on the number of parameter matrix modes; however, the resulting final optimal sensor placement is included in a group of common candidate sensor locations. However, the resulting final optimal sensor placement is included in a group of common candidate sensor locations.

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

2020 ◽  
pp. 136943322094719
Author(s):  
Xianrong Qin ◽  
Pengming Zhan ◽  
Chuanqiang Yu ◽  
Qing Zhang ◽  
Yuantao Sun
Keyword(s):  
Genetic Algorithm ◽  
Health Monitoring ◽  
Large Scale ◽  
Complex Structure ◽  
Sensor Placement ◽  
Placement Problem ◽  
Optimal Sensor Placement ◽  
Placement Optimization ◽  
Sensor Placement Optimization ◽  
Sensor Locations

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.

On the influence of problem definition in sensor placement optimization

2009 ◽  
Author(s):  
Chris L. Pettit ◽  
Sergey N. Vecherin ◽  
D. Keith Wilson
Keyword(s):  
Sensor Placement ◽  
Problem Definition ◽  
Placement Optimization ◽  
Sensor Placement Optimization
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