基于图像增强识别的风电场巡检机器人设计

Design of wind farm inspection robot based on image enhancement recognition

为实现风电场巡检机器人全面代替人工巡检,对电站设备进行实时监测。研究利用迭代最近点法和红外与可见光的图像处理生成云匹配电子地图。然后利用遗传算法巡检任务路径进行规划。最后利用图像增强识别技术识别巡检设备。由此设计了基于图像增强识别的风电场巡检机器人。实验得到,平均识别准确率为95.54%,规划路径平均长度为345 m。由此可分析出,巡检机器人能够实现高效且准确的风电场巡检任务,为电站建设提供技术支持。

To realize the full replacement of manual inspection by wind farm inspection robot,real-time inspection of power plant equipment is carried out.The research uses iterative nearest point method and infrared and visible light image processing to generate cloud matching electronic map.Then use genetic algorithm to plan the patrol task path.Finally,the inspection equipment is identified by image enhancement recognition technology.Therefore,a wind farm inspection robot based on image enhancement recognition is designed.The experiment shows that the average recognition accuracy is 95.54%,and the average length of the planned path is 345 m.It can be analyzed that the inspection robot can achieve efficient and accurate inspection tasks of wind farms,and provide technical support for the construction of power stations.