Abstract
This work proposes a comprehensive combinational algorithm for sensor layout to solve the problem that unreasonable sensor layout affects the effectiveness of data selection and reduces the accuracy of monitoring system in healthy monitoring system of wind turbine blade structure. This algorithm integrates the advantages of kinetic energy method, effective independence method, modal assurance criterion (MAC), and many other optimal methods. In order to avoid information redundancy caused by partial concentration of test spots, Euclidean distance was introduced as the iteration condition of algorithm. Finite element simulation and experimental results show that the layout obtained by this method is beneficial to improving signal-to-noise ratio and can maximize the crossing angle between target vibration modes. Therefore, relatively complete characteristics of actual wind turbine blade structure can be obtained.
Highlights
As one of the key components and bases of the whole wind turbine generator, blade has value accounting for about 20% of the whole installation cost
The wind turbine generator always works under alternating load and in the wild environment of dust, rain, and snow, so the blade made of composite material always has abnormal deformation, acute vibration, and irregular distortion
This work proposed a combinational layout algorithm with good comprehensive performance to solve the problem that the sensor layout in monitoring system of fan blade structure is unreasonable
Summary
As one of the key components and bases of the whole wind turbine generator, blade has value accounting for about 20% of the whole installation cost. The wind turbine generator always works under alternating load and in the wild environment of dust, rain, and snow, so the blade made of composite material always has abnormal deformation, acute vibration, and irregular distortion. All of these phenomena may cause invisible internal damage in use [1,2,3,4,5]. It has been inevitable to choose an optimal sensor layout to obtain real, acute, and detailed high-resolution structural response data in healthy monitoring of blade structure
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