面向无人机风机巡检的光照条件分析方法

Illumination Analysis Method for Wind Turbine Inspection of Drone

在无人机风机巡检作业中,光照异常会严重影响拍摄到的图像质量,导致风机叶片在图像中亮度异常,叶片上的裂纹等细微缺陷无法被有效判定,影响风机的安全稳定运行.本文针对此问题,开展风机巡检中的光照条件分析技术研究,在巡检前,根据规划的航迹及太阳的方位进行光照情况预判;在巡检中,根据风机叶片及塔筒的分割结果,针对性地分析关键部位的光照情况,辅助以基于加权均值的整幅图像光照分析算法,能够全方位地实现巡检中光照分析,提升作业效率和准确性.

In the inspection of a wind turbine in a drone,abnormal illumination may seriously affect the quality of the captured images.As a result,the blades of the wind turbine have abnormal brightness in the images,and small defects such as cracks on the blades cannot be found effectively,which affects the stable operation of the wind turbine.For this reason,this study proposes an illumination analysis method for the inspection of wind turbines.Before the inspection,the illumination situation is prejudged according to the planned trajectory and solar orientation.During the inspection,the illumination of the key parts is analyzed according to the segmentation results of the blades and tower barrel.In this process,we introduce a method of illumination analysis about the whole image based on weighted mean.In conclusion,the proposed method can predict the abnormal illumination in the whole inspection process and provide a basis for efficient and accurate inspections.