Novel prediction-reliability based graphical DGA technique using multi-layer perceptron network & gas ratio combination algorithm

Kingshuk Chatterjee, Subham Dawn, Vinay K. Jadoun, R. K. Jarial

Research output: Contribution to journalArticle


Dissolved gas analysis (DGA) is among the most essential techniques for diagnosis of incipient faults in power transformers. Here, a novel graphical DGA technique is proposed in which fault zones are distinguished based on certainty of prediction. The Duval Pentagon 1 and gas ratio combination methods are two most recent techniques with high prediction accuracy. In the Duval Pentagon 1, the rigidly separated distinct fault zones reduce the flexibility of analysis because the fault distributions themselves are not that strictly separated. This also prevents the full utilisation of the information available from the distribution patterns of the graphical representation. This problem has been addressed by overlapping individual fault zones and overlapping them using a multi-layer perceptron (MLP) network with fuzzy class boundaries. Then, in the regions, where multiple fault zones overlap, a modified gas ratio combination method is applied. Finally, a fuzzy decision-making system is developed for predicting the fault using information from both graphical distribution and gas ratios. The combined accuracy of the regions of certainty has been found exceptionally high (98.36%) compared to the regions of uncertainty (58.97%), whereas the overall prediction accuracy of the proposed technique is found comparatively higher (83%) than both the existing methods.

Original languageEnglish
Pages (from-to)836-842
Number of pages7
JournalIET Science, Measurement and Technology
Issue number6
Publication statusPublished - 01-08-2019


All Science Journal Classification (ASJC) codes

  • Atomic and Molecular Physics, and Optics
  • Electrical and Electronic Engineering

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