Visible and infrared imaging based inspection of power installation

The inspection of power lines is the crucial task for the safe operation of power transmission: its components require regular checking to detect damages and faults that are caused by corrosion or any other environmental agents and mechanical stress. During recent years, the use of Unmanned Autonomous Vehicle (UAV) for environmental and industrial monitoring is constantly growing and the demand for fast and robust algorithms for the analysis of the data acquired by drones during the inspections has increased. In this work, we use UAV to acquire power transmission lines data and apply image processing to highlight expected faults. Our method is based on a fusion algorithm for the infrared and visible power lines images, which is invariant to large scale changes and illumination changes in the real operating environment. Hence, different algorithms from image processing are applied to visible and infrared thermal data, to track the power lines and to detect faults and anomalies. The method significantly identifies edges and hot spots from the set of frames with good accuracy. At the final stage we identify hot spots using thermal images. The paper concludes with the description of the current work, which has been carried out in a research project, namely SCIADRO.