Case studies are used to demonstrate the efficacy of the developed method. This work develops a new, simplified fuzzy logic–based method to predict the health of a transformer by taking into account the state of several individual components. These include transformer windings, insulations, transformer oil, core insulations, and ferromagnetic cores. There are several components whose condition can be studied to predict transformer failures and therefore the overall health of a transformer. The efficacy of such maintenance depends on a proper understanding of the transformer and its components and efficient prediction of faults in these components. To ensure such efficient operation, power distribution companies carry out routine maintenance of distribution transformers through preplanned schedules. The fault-free operation of step-up and step-down transformers is of prime importance to the continuous supply of electrical energy to the consumers. Power transformers are a fundamental component of the modern power distribution network. 9Department of Technology, Higher Institute of Computer Sciences and Mathematics, University of Monastir, Monastir, Tunisia.8Department of Computing, University of Turku, Turku, Finland.7Department of Computer Science, Hekma School of Engineering, Computing, and Informatics, Dar Al-Hekma University, Jedda, Saudi Arabia.6Department of Electrical Power and Machines, Faculty of Engineering, Alexandria University, Alexandria, Egypt.5Department of Electrical Power and Machines, Kafrelsheikh University, Cairo, Egypt.4National Engineering School of Gabès, Processes, Energy, Environment and Electrical Systems, University of Gabès, Gabès, Tunisia.3Department of Electrical Engineering, College of Engineering, Jouf University, Sakaka, Saudi Arabia.2School of Electronics Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China.1Department of Electrical Engineering, University of Engineering and Technology Lahore (UET Lahore), Lahore, Pakistan.
Muhammad Farhan Naeem 1, Khurram Hashmi 1*, Syed Abdul Rahman Kashif 1, Muhammad Mansoor Khan 2, Mamdouh L.
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