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Journal of Sensors
Volume 2016, Article ID 2567305, 10 pages
Research Article

Determining the Optimal Placement of Sensors on a Concrete Arch Dam Using a Quantum Genetic Algorithm

Kai Zhu,1,2,3 Chongshi Gu,1,2,3 Jianchun Qiu,1,2,3 Wanxin Liu,1,2,3 Chunhui Fang,4 and Bo Li5

1State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China
2National Engineering Research Center of Water Resources Efficient Utilization and Engineering Safety, Hohai University, Nanjing 210098, China
3College of Water-Conservancy and Hydropower, Hohai University, Nanjing 210098, China
4Zhejiang Institute of Hydraulics and Estuary, Hangzhou 310020, China
5Engineering Safety and Disaster Prevention Department, Changjiang River Scientific Research Institute, Wuhan 430010, China

Received 18 September 2015; Accepted 1 December 2015

Academic Editor: Kourosh Kalantar-Zadeh

Copyright © 2016 Kai Zhu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Structural modal identification has become increasingly important in health monitoring, fault diagnosis, vibration control, and dynamic analysis of engineering structures in recent years. Based on an analysis of traditional optimization algorithms, this paper proposes a novel sensor optimization criterion that combines the effective independence (EFI) method with the modal strain energy (MSE) method. Considering the complex structure and enormous degrees of freedom (DOFs) of modern concrete arch dam, a quantum genetic algorithm (QGA) is used to optimize the corresponding sensor network on the upstream surface of a dam. Finally, this study uses a specific concrete arch dam as an example and determines the optimal sensor placement using the proposed method. By comparing the results with the traditional optimization methods, the proposed method is shown to maximize the spatial intersection angle among the modal vectors of sensor network and can effectively resist ambient perturbations, which will make the identified modal parameters more precise.