WSN nodes placement optimization based on a weighted centroid artificial fish swarm algorithm

Abstract

Aiming at optimal placement of wireless sensor network (WSN) nodes of wind turbine blade for health inspection, a weighted centroid artificial fish swarm algorithm (WC-AFSA) is proposed. A weighted centroid algorithm is applied to construct an initial fish population so to enhance the fish diversity and improve the search precision. Adaptive step based on dynamic parameter is used to jump out local optimal solution and improve the convergence speed. Optimal sensor placement is realized by minimizing the maximum off-diagonal elements of the modal assurance criterion as the objective function. Five typical test functions are applied to verify the effectiveness of the algorithm, and optimal placement of WSNs nodes on wind turbine blade is carried out. The results show that WC-AFSA has better optimization effect than AFSA, which can solve the problem of optimal arrangement of blade WSNs nodes.