风电运行中叶片破损面积计算探究

Research on calculation of blade damage area in wind power operation

风电设备的维养和保护中,对叶片的破损区域进行精确监控与准确识别,实现对叶片破损面积的有效计算,是提升风电运行效率的基础条件。传统的叶片破损监控和计算方式存在一定程度的不足,为了提高风电运行效率和运行质量,提出以YOLO神经网络识别算法和视觉算法为基础的智能化叶片破损识别及破损面积计算。以期通过该计算方式的研究和应用,提高风电运行中叶片破损面积计算的有效性和精确性,为风电机组的高效安全运行保驾护航。

In the maintenance and protection of wind power equipment,accurate monitoring and identification of damaged areas of blades and effective calculation of damaged areas of blades are the basic conditions for improving the operational efficiency of wind power.The traditional monitoring and calculation methods of blade damage have some deficiencies.In order to improve the operational efficiency and quality of wind power,The intelligent blade damage identification and damage area calculation based on YOLO neural network identification algorithm and visual algorithm are proposed.Through the research and application of this calculation method,we hope to improve the effectiveness and accuracy of blade damage area calculation in wind power operation,and ensure the efficient and safe operation of wind turbines.