The fault diagnosis of the dissolved gas analysis (DGA) of the power transformer is to be enhanced than previous adopted techniques; this paper proposes a novel adaptive neuro Fuzzy inference system for the incipient fault recognition through enhanced approach. Complying with the practical DGA records and associated fault causes as much as possible, an ANFIS algorithm is presented to establish ...

This paper presents an analytical method to compute the leakage inductances of power transformers with a turn-to-turn winding fault. A leakage inductance model to represent the transformer with faulty turns is also proposed. The results obtained from the application of the analytical method are validated by using data obtained from finite-element analysis and experimental tests.

proper operations of transformer have several issues such as; preventing of unscheduled removal’s, increasing of reliability and continues supply of consumer demand. this result would be obtained that load and harmonic orders of sensitivity transformer at intervals appropriate for next hours and days is predicted to by selecting optimal utilization coefficient, reduction life of transformer is ...

Power transformers are one of the main equipment in power production, with high cost and long manufacturing time. If a fault occurs during supply process, it will prevent normal operation system result no electricity available to users. One factors affecting safe is short circuit fault, faults at outlet substations or close proximity can also pose serious threat transformers. This article simul...

An efficient transformer model is required to characterize the transformer internal faults for its condition assessment, which is experimentally very costly. This paper discusses the application of Neural Network (NN) techniques in the modeling of a distribution transformer with internal short-circuit winding faults. A transformer model can be viewed as a functional approximator constructing an...

The determination of transformer fault categories using soft-computing based techniques has been the subject of much research in the recent past. The development of an adaptive fuzzy classifier which can effectively determine various classes or categories of series and shunt impulse faults in a wide range of power transformers is described. The system employs a self-generating module to automat...

This paper presents an efficient wavelet and neural network (WNN) based algorithm for distinguishing magnetizing inrush currents from internal fault currents in three phase power transformers. The wavelet transform is applied first to decompose the current signals of the power transformer into a series of detailed wavelet components. The values of the detailed coefficients obtained can accurate...