On-site Detection of Pollution Level of Insulators Based on Infrared-thermal-image Processing

In view of the close relationship between thermal distribution and conditions about contamination and wetness on insulators’ surface, a detection method for on-site pollution level of insulators is proposed based on infrared- thermal-image processing. The procedures of detection were as follows: Firstly, infrared thermal images were denoised with the stationary wavelet-domain local-adaptive method to suppress white-noise interference in infrared imaging. Secondly, Otsu’s method was adopted for image segmentation on the basis of logarithmic transformation to the denoised images. Thirdly, edge points of disc surface of insulators were sampled through scattering lines at different angles from the barycentric coordinates, which were computed from binarized images. Fourthly, the elliptic equation for disc surface edge was fitted by the least square method. Fifthly, the ellipse image region above its long axis was abstracted and normalized. Finally, the gray histograms of the normalized images were calculated. According to above procedures, a feature library was established, including massive infrared-thermal-image gray histograms of various pollution-level insulators under different humidity. On-site pollution level was evaluated by maximum comparability criteria of gray synthetically relational degrees with samples under the nearest humidity condition. Experimental results proved the method’s feasibility and effectiveness in detection of on-site pollution level for insulators.