Aiming at problem of optimal placement of wireless sensor networks（ WSNs） nodes of wind turbine blade for health inspection

a weighted centroid fish swarm algorithm is introduced to initialize fish swarm. Enhance the diversity of population and improve optimizing precision. Adaptive changeable step strategy based on dynamic parameter is used to jump out local optimal solution and improve the convergence speed. Measurement point placement uses minimum value of the maximum non-diagonal elements of the modal confidence matrix as the objective function. Use five typical test functions to verify the algorithm

and carry out optimal placement of WSNs nodes on wind turbine blade. The results verify that weighted centroid fish swarm algorithm has better optimization effect than artificial fish swarm algorithm

which can solve the problem of optimal placement of blade WSNs nodes.