Optimal Wireless Sensor Networks Nodes Placement For Wind Turbine Blade

Wind turbine blade is one of the key components of the wind turbine generator,it is responsible for convert wind energy into rotational mechanical energy of wind turbine rotors.The wind turbine blade is extremely easy to suffer varying degrees of damage under the influence of environment of wind,sand,ice,thunder and lightning,as well as a variety of stress concentrations,leading to the shutdown of the wind turbine,causing serious economic losses.The volume and mass of wind turbine blade is huge,so it is difficult to maintenance manually,with high maintenance costs.Therefore,in order to reduce the risk of operation,while reducing maintenance costs,it is of great significance to carry out health monitoring in the wind turbine blade structure,especially identify the damage state quickly and accurately.Carry out optimal wireless sensor network nodes placement for wind turbine blade,uses as few wireless sensor network nodes as possible to obtain as much structural modal information as possible,thereby reducing the detection costs and improving the reliability of the blade.The thesis focuses on the optimal placement of wireless sensor network nodes based on wind turbine blade.The main contents are as follows:(1)On the basis of the blade health monitoring system,analyzes the problem of optimal wireless sensor networks nodes placement for wind turbine blade,introduces the significance of optimal sensor placement,determines the mathematical model of optimal wireless sensor network nodes placement,and obtains decision variables,constraints and objective functions of the problem based on the mathematical model.(2)The random initialization distribution and fixed step in artificial fish swarm algorithm,which is limited in searching for optimal solution.A weighted centroid artificial fish swarm algorithm is proposed,which can solve the problem of optimal arrangement of blade wireless sensor network nodes.Enhance the diversity of fish and improve the search optimal precision by using weighted centroid algorithm to construct initial fish population.Adaptive changeable step based on dynamic parameter is used to jump out local optimal solution and improve the convergence speed,as well as searching performance.(3)Sensor placement is minimized by using the maximum non-diagonal elements of the modal assurance criterion as the objective function.The improved algorithm is tested and analyzed by using eight test functions as the standard to evaluate the algorithm,as well as analyze the advantages of adaptive changeable step and time complexity,the results indicate that the improved algorithm has more advantages.(4)By analyzing the structure and form,vibration mathematical model,basic parameters and material properties of the blades,a finite element model of the blade is established.Thefirst five natural vibration frequencies and the displacement vibration modes are acquired by modal analysis.(5)Corresponding the optimal solution calculated by the weighted centroid artificial fish swarm algorithm to the degree of freedom on a node basis blade,determines the placement of wireless sensor network nodes.Artificial fish swarm algorithm and weighted centroid artificial fish swarm algorithm are applied in optimal wireless sensor networks nodes placement for wind turbine blade,as well as contrast them,the results verify the feasibility and superiority of the optimal wireless sensor networks nodes placement for wind turbine blade by using weighted centroid artificial fish swarm algorithm.