基于机器视觉和激光测距的输电线故障定位

结合定位技术和激光测距技术,提出了一种基于机器视觉的电力巡线故障定位新方法.通过无人机搭载可见光相机进行巡线拍摄,将航拍图像实时传回地面站进行处理.采用数学形态学的图像处理方法和模式识别方法进行故障检测与识别.通过惯性测量系统进行初步定位,得到无人机的经纬度坐标.利用无人机机载激光测距模块,测量故障点到无人机的距离来修正坐标.最后,经过空间大地坐标系和空间直角坐标系的变换,以及两个空间直角坐标系的基准转换,计算出了故障点的准确位置,并且很大程度地提高了定位的准确性,其空间直角坐标测量精度可达0.11m.

Transmission Line Fault Location Based on Machine Vision and Laser Ranging

Combined with positioning technology and laser ranging technology, a novel method for transmission lines fault location is proposed by machine vision. The unmanned aerial vehicle carries a visible light camera for shooting work of transmission line. The aerial images are transmitted back to the ground station in real time for further processing. The image processing and pattern recognition methods are adopted to detect and recognize faults on transmission lines, where the mathematical morphology algorithms are applied in image processing. The initial positioning is used to obtain the longitude and latitude coordinates of unmanned aerial vehicle by using the inertial measurement system. An airborne laser ranging module is used to correct the coordinates by measuring the distance from the fault point to the unmanned aerial vehicle. Finally, accurate position coordinates of fault points are calculated after coordinate transformation between the space geodetic and space rectangular coordinate system as well as datum transformation between two rectangular coordinate systems. The positioning accuracy has been greatly improved and the space rectangular coordinate measurement accuracy can be as high as 0.11 m.