Fuzzy logic and artificial neural network-based thermography approach for monitoring of high-voltage equipment

This paper presents two methods for condition monitoring of high-voltage equipment based on the thermography approach. The overheating temperature of the hot spot has been obtained using the performed thermography procedure. MATLAB((R)) technical computing software has been used to design the fuzzy controller and artificial neural network. The age of the element, the voltage level, the overheating temperature and the temperature of the previous overheating have been used as the reference inputs for the designed controller and artificial neural network. The developed software tool has been applied for the evaluation of the urgency of intervention in the function of the input data, designed rule base and the methods of defuzzification. Real measurements were used as input data in both methods so that the results were confirmed. The results might serve as a good orientation in the high-voltage equipment condition monitoring. The educational aspects of the application of this software tool are very important for both undergraduate and master's students studying Monitoring and Diagnostics of High Voltage Substations. During the past two academic years, the software application has received favorable comments from students.