Title :
Dissolved gas analysis of mineral oil for power transformer fault diagnosis using fuzzy logic
Author :
Yann-Chang Huang ; Huo-Ching Sun
Author_Institution :
Dept. of Electr. Eng., Cheng Shiu Univ., Kaohsiung, Taiwan
Abstract :
This paper reviews the use of fuzzy logic (FL) for dissolved gas analysis (DGA) of mineral oil for power transformer fault diagnosis (PTFD). A brief overview of conventional PTFD techniques using DGA of mineral oil is firstly surveyed. Then, applications of FL techniques for PTFD reported in international journals for evaluating power transformer conditions are extensively reviewed. Various FL techniques for PTFD have been developed to reduce operating costs, enhance operational reliability, and improve power and services supplied to customers. These FL techniques enable researchers to analyze fault phenomena and diagnose transformer faults, and these approaches have evolved rapidly as highly effective approaches for PTFD. Potential improvements to FL-based systems are also discussed. Our conclusion is that no single DGA technique enables detection of the full range of faults, which is needed for reliable assessment of all power transformer conditions. Therefore, the most effective PTFD technique is to combine outputs from various DGA diagnostic methods and to aggregate them into an overall evaluation.
Keywords :
fault diagnosis; fuzzy logic; minerals; power transformer insulation; reliability; transformer oil; DGA diagnostic methods; FL techniques; FL-based systems; PTFD techniques; diagnose transformer faults; dissolved gas analysis; fault phenomena analysis; fuzzy logic; mineral oil; operating cost reduction; operational reliability; power transformer fault diagnosis; Fault diagnosis; Fuzzy logic; Gases; Oil insulation; Power transformer insulation; Uncertainty; Dissolved gas analysis; fuzzy logic; power transformer;
Journal_Title :
Dielectrics and Electrical Insulation, IEEE Transactions on
DOI :
10.1109/TDEI.2013.6518967