Image processing to automate condition assessment of overhead line components

Condition monitoring of overhead electricity transmission line assets is essential to network operation. Traditionally, the condition of overhead lines are assessed visually. Visual inspection is difficult to apply to phase conductors due to their height above ground. As such, aerial imaging surveys seem to be an ideal solution to this problem. However, the large number of high resolution images generated by aerial surveys are costly to inspect in terms of time and labour. This paper presents an image processing system that automates conductor localization and spacer detection in order to reduce the work required in visual inspection. The implemented system was tested on over four thousand video images from actual aerial surveys of quad-conductor transmission line assets. Experimental results show highly accurate conductor localization and a robust hit rate for spacer detection. These results suggest that image processing can be used to help automate labour intensive tasks in the condition assessment of overhead line components.