Open AccessAn innovative method of fault detection in power transformers
Author(s) -
В. М. Левин,
Ammar Yahya
Publication year - 2022
Publication title -
international journal of power electronics and drive systems/international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
eISSN - 2722-2578
pISSN - 2722-256X
DOI - 10.11591/ijece.v12i2.pp1123-1130
Subject(s) - dissolved gas analysis , computer science , nonlinear system , classifier (uml) , transformer , bayesian probability , a priori and a posteriori , pattern recognition (psychology) , feature vector , artificial intelligence , data mining , algorithm , reliability engineering , machine learning , transformer oil , engineering , philosophy , physics , epistemology , quantum mechanics , voltage , electrical engineering
The Bayesian classifier is a priori the optimal solution for minimizing the total error in problems of statistical pattern recognition. The article suggests using the classifier as a regular tool to increase the reliability of defect recognition in power oil-filled transformers based on the results of the analysis of gases dissolved in oil. The wide application of the Bayesian method for solving tasks of technical diagnostics of electrical equipment is limited by the problem of the multidimensional distribution of random parameters (features) and the nonlinearity of classification. The application of a generalized feature of a defect in the form of a nonlinear function of the transformer state parameters is proposed. This simultaneously reduces the dimension of the initial space of the controlled parameters and significantly improves the stochastic properties of the random distribution of the generalized feature. A special algorithm has been developed to perform statistical calculations and the procedure for recognizing the current technical condition of the transformer using the generated decision rule. The presented research results illustrate the possibility of the practical application of the developed method in the conditions of real operation of power transformers.