A Time Series Analysis and Neural Network Based Scheme for Fault Diagnosis of Transformers

Abstract:

This research presents a time series analysis and artificial neural network (ANN)-based scheme for fault diagnosis of power transformers, which extracts the characteristic parameters of the faults of the transformer from the results of time series analysis and bases on this basis establishes the corresponding back propagation (BP) neural network to detect the transformer operating faults. The simulation experimental results show that as compared to the related works, the proposed approach effectively integrates the superiority of time series analysis and BP neural network and thus can greatly improve the diagnosis accuracy and reliability.

• Periodical: Applied Mechanics and Materials (Volume 742)
• Pages: 412-418
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.742.412
• Online since: March 2015
• Authors: Jian Jun Zhang*, Ye Xin Song, Yong Qu
• Keywords: Artificial Neural Network, Autoregressive Model, Fault Diagnosis, Time Series Analysis, Transformer

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