Monitoring And Fault Diagnosis Of Electrical Installation Using Thermal Imaging - Tiong, King Hock (Universiti Sains Malaysia, 2018)
Electrical fault is any abnormal electric current bypass the normal load. Thermal camera has been widely used for many years to monitor and inspect thermal defects of electrical equipment by detecting the hot-spot. However, manual analysis of infrared images for detecting defects and classifying the status of the equipment may consume a lot of time and efforts, and may also lead to incorrect diagnosis. In order to tackle this problem, image processing technique is introduced to analyze the possible electrical fault automatically from infrared images. In this project, Otsu’s method, Wiener filter and histogram equalization are implemented in analyzing the electrical fault. MATLAB is chosen as a platform to develop the algorithm to process the infrared image. In the first stage, the infrared images will be uploaded to the computer to analyze the high intensity parts of the image because these parts represent higher temperature hot-spot. Next, the hot-spot regions of the image will be cropped and the quality of these images will be enhanced by histogram equalization and Weiner filter. Then, comparison between the image of normal current condition and image of possible fault region will be carried out. After the comparison, it will alert the users if there is any possible fault. In this project, the ordinary Otsu’s method is modified so that it is suitable to be used to segment and analyse the electrical fault. If a fault is found on the system, a message will be generated by the system to alert the user. In conclusion, the automatic diagnosis technique can reduce a lot of manpower, time and prevent human error in electrical fault diagnosis.