Health monitoring sensor placement optimization for Canton Tower using immune monkey algorithm

Abstract

SUMMARY Sensor placement is an integral component in the design of an effective and reliable structural health monitoring system for large-scale civil engineering structures. In this paper, a novel hybrid optimization algorithm, that is, immune monkey algorithm (IMA), by combining the monkey algorithm with the immune algorithm, is proposed to solve the optimal sensor placement problem. In the proposed algorithm, the dual-structure coding method is designed and adopted for the representation of design variables and a chaos-based approach is presented to initialize the monkey population. In addition, some improved strategies such as the advanced climb process, immune selection, clonal proliferation, and immune renewal are defined to maintain population diversity and inhibit degeneracy during evolution. The effectiveness and reliability of the proposed IMA is demonstrated by designing the sensor arrays of the Canton Tower, the second highest TV tower in the world. Numerical investigations presented clearly suggest that the proposed hybrid IMA outperforms the original monkey algorithm implementations both in terms of generating optimal solutions as well as faster convergence. The proposed algorithm can easily be extended to other multiple global optimization problems. Copyright © 2014 John Wiley & Sons, Ltd.