Journal ArticleDOI
Internal fault detection techniques for power transformers
Narri Yadaiah,Nagireddy Ravi +1 more
- Vol. 11, Iss: 8, pp 5259-5269
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TLDR
An artificial neural network is used to detect faults off-line with dissolved gas analysis reports of transformers and whereas wavelet transforms are being used for on-line fault detection.Abstract:
This paper presents the methodologies for incipient fault detection in power transformers both off-line and on-line. An artificial neural network is used to detect faults off-line with dissolved gas analysis reports of transformers and whereas wavelet transforms are being used for on-line fault detection. The accuracy in fault detection through artificial neural networks is compared with Rogers ratio method using the analysis of experimental oil samples for power transformers of power companies in Andhra Pradesh, India. The Wavelet transform techniques have been developed with different mother wavelets to detect incipient faults and to distinguish between incipient fault and short circuit fault. Further their performances with different mother wavelets are compared.read more
Citations
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Journal ArticleDOI
An intelligent system based on optimized ANFIS and association rules for power transformer fault diagnosis.
TL;DR: Selecting the most educative attributes of DGAM, training ANFIS optimally, improving the robustness of ANfIS and increasing the classification accuracy are the main contribution of this paper in the field of power transformer fault detection and classification.
Journal ArticleDOI
Application of Gene Expression Programming (GEP) in Power Transformers Fault Diagnosis Using DGA
Hasmat Malik,Sukumar Mishra +1 more
TL;DR: Results and comparison against other soft computing approaches show relative superiority of GEP-based DGA interpretation in terms of classification accuracy.
Journal ArticleDOI
Adaptive threshold based on wavelet transform applied to the segmentation of single and combined power quality disturbances
TL;DR: A way of determining an adaptive threshold based on the decomposition of electrical signals through the Discrete Wavelet Transform (DWT) using Daubechies family filter banks, allowing for the segmentation of signals and, as a consequence, the analysis of disturbances related to Power Quality (PQ).
Journal ArticleDOI
Fuzzy reinforcement learning based intelligent classifier for power transformer faults.
TL;DR: Experimental results and comparison with other state-of-the-art approaches, highlights superiority and efficacy of the proposed fuzzy RL technique for transformer fault classification.
Journal ArticleDOI
Root cause analysis improved with machine learning for failure analysis in power transformers
TL;DR: The conventional action selection procedure of Reinforcement Learning is replaced by a machine learning based optimizer and the correlation is higher than 0.98 with tree learner classifier, with a validation of the over-fitting perspective.
References
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Journal ArticleDOI
An introduction to computing with neural nets
TL;DR: This paper provides an introduction to the field of artificial neural nets by reviewing six important neural net models that can be used for pattern classification and exploring how some existing classification and clustering algorithms can be performed using simple neuron-like components.
Journal ArticleDOI
An expert system for transformer fault diagnosis using dissolved gas analysis
TL;DR: A prototype expert system based on the dissolved gas analysis (DGA) technique for diagnosis of suspected transformer faults and their maintenance actions is developed and a synthetic method is proposed to assist the gas ratio method.
Journal ArticleDOI
Developing a new transformer fault diagnosis system through evolutionary fuzzy logic
TL;DR: In this paper, an evolutionary programming (EP) based fuzzy system development technique is proposed to identify the incipient faults of the power transformers using the IEC/IEEE DGA criteria as references, a preliminary framework of the fuzzy diagnosis system is first built.
Journal ArticleDOI
Modeling Transformers with Internal Incipient Faults
Hang Wang,K.L. Butler +1 more
TL;DR: In this paper, the authors presented a methodology to model internal incipient winding faults in distribution transformers by combining deteriorating insulation models with an internal short-circuit fault model using finite element analysis.
Proceedings ArticleDOI
Fault Identification Using Wavelet Transform
K. Rajesh,Narri Yadaiah +1 more
TL;DR: In this article, a wavelet analysis technique for identification of faults in high voltage direct current power transmission systems and A.C current systems is presented based on the representation of the travelling waves through wavelet modulus maxima.
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