The Information Fusion of the IR and UV Image for the Insulation Fault Diagnosis

The infrared (IR) and ultraviolet (UV) images can reflect the abnormal temperature rise and the partial discharge of insulation equipment respectively. The information fusion of them is helpful for the accurate diagnosis of the insulation faults. In this paper, the information fusion of the IR and UV image for the insulation fault diagnosis is studied in two terms: the image fusion and the feature fusion, to improve the visual effect and the accuracy of fault diagnosis. In the image fusion, we extracted the edge of insulation equipment in the IR and UV images, and used Speeded Up Robust Feature (SURF) to do the IR-UV image registration, and then we proposed the IR-UV image fusion algorithm and the feature extraction method after fusion. In the feature fusion, the IR and UV image features were studied in the experiments with different humidity and insulation fault levels. Based on the experimental results, a fuzzy inference model of insulation faults based on the IR-UV image features is constructed, and the information fusion of the IR and UV images on the feature level is realized. The accuracy test shows that the proposed IR-UV image fusion algorithm could fully retain external insulation fault feature and enhance the visual effect. After the feature fusion of the IR and UV image feature, the accuracy rate of the insulation fault diagnosis increased to 94%.