Performance of UV and IR Sensors for Inspections of Power Equipment

Electric power infrastructure, such as transmission lines or substations, is usually routinely inspected to assess its condition. The vast majority of typical defects in power transmission equipment manifests itself either through corona phenomena or through thermal effects. Therefore, an IR camera and a solar blind UV camera are sufficient for the detection of most defects in power transmission equipment. In the past, many network operators have relied mostly on manual inspections. In recent years, however, manned as well as unmanned aerial inspection methods, which are significantly more time effective, have become increasingly affordable and are therefore gaining in popularity rapidly.
To obtain meaningful measurement results, many factors must be taken into account, which can even be difficult with conventional, static measurements. In the case of highly dynamic measurement practices (airborne or vehicle based), the combination of velocity and distance presents further challenges.
This contribution is focused on the detection performance of UV and IR sensors under dynamic conditions. For this purpose, experiments were carried out with a typical IR and UV/corona camera at various distances to artificial defects. Additionally, a method for the automatic evaluation of UV und IR data based on machine learning is presented.