Abstract: In order to collect date by sensors effectively and improve the accuracy of wind turbine blade's monitoring system, a new sensor placement method based on the multiple optimization strategies was presented. Firstly, to improve the convergence rate, QR-factorization method was used to screen the initial test point group. Secondly, the modal assurance criterion (MAC) matrix was taken as the target function, and a method of determining sensors number was proposed by the maximum off-diagonal element of MAC. Finally, in order to solve the problem that the traditional genetic algorithm is easy to fall into, local optimal solution and slow convergence SA was used as an operator of the genetic algorithm. The two kinds of mature intelligent algorithm was combined under the framework of Memetic by complementary advantage. The plan of optimal sensor placement for a 2-MW wind turbine blade was performed and compared with the traditional QR method and the standard genetic algorithm. The final results indicate that the arrangement through the new optimal method could solve the optimal sensor placement of blade and have better performance in convergence and optimization effect than the QR method and genetic algorithm.

Key words: wind turbine blade, health monitoring, optimal placement of sensor, modal assurance crite-rion, SA