KMITL

Permanent URI for this communityhttps://dspace.kmitl.ac.th/handle/123456789/1

Browse

Settings

Author: search.filters.author.Kunakorn, A.Subject: search.filters.subject.Internal faults

Search Results

Now showing 1 - 3 of 3
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Item,
    Internal failure analysis of transformer windings
    (2012-12-31)
    Tuethong, P.
    ;
    Yutthagowith, P.
    ;
    Kunakorn, A.
    ;
    Potivejkul, S.
    This paper presents internal failure analysis of transformer windings based on the characteristic of winding impedance in the frequency domain. Two winding samples are selected to test. The simple equivalent circuit of the transformer winding is investigated and proposed. The two windings under test have 76 turns with different length. An iron core is either inserted or not inserted inside a winding in the test to investigate the effect of the iron core. Turn to turn short circuit on the windings is considered as internal failure in this paper. The simulated turn to turn short on the model is carried out in the experiment to observe impedance characteristic in the frequency domain. A number and position of short turns are varied to observe characteristics of impedances The impedance of the models of the transformer windings are measured by a spectrum analyzer in a wide frequency range upto 2 MHz. From the test results, it is investigated that a resonance frequency of the transformer model is depended on a number and position of short turns. From the investigation, it has high possibility that the characteristic can be used for analysis of internal failures occurring in a transformer. © 2012 IEEE.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Item,
    Detecting winding to ground fault locations in power transformers using back-propagation neural networks
    (2006-12-01)
    Ngaopitakkul, A.
    ;
    Kunakorn, A.
    This paper presents an algorithm based on a combination of discrete wavelet transforms and neural networks for detecting locations of winding to ground faults in a two-winding three-phase transformer. The fault conditions of the transformer are simulated using ATP/EMTP in order to obtain fault current signals used as an input for a training process of a back-propagation neural network. The training process and fault diagnosis decision algorithm are implemented using toolboxes on MATLAB/Simulink. Various cases studies based on Thailand electricity transmission and distribution systems are performed to verify the validity of the algorithm. It is found that the proposed method gives a satisfactory accuracy, and will be particularly useful in a fault diagnosis process for a transformer manufacturer.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Item,
    Discrimination between external short circuits and internal faults in transformer windings using discrete wavelet transforms
    (2005-12-01)
    Ngaopitakkul, A.
    ;
    Kunakorn, A.
    ;
    Ngamroo, I.
    In this paper, a technique for separation between internal faults in a two-winding three-phase transformer and external short circuits is presented. The fault detection algorithm is constructed on the basis of coefficient comparison from signals decomposed from Discrete Wavelet Transform. Computer simulations are performed using ATP/EMTP as well as MATLAB/Simulink. Various cases and fault types are studied to verify the validity of the algorithm. It is found that the proposed method gives a satisfactory accuracy, and will be particularly useful in a development of a modern differential relay for a transformer protection scheme. © 2005 IEEE.