A power transformer fault prediction method through temporal convolutional network on dissolved gas chromatography data

HIGHLIGHTS

• who: Mengda Xing et al. from the School of Information Science and Technology, North China University of Technology, Beijing, China have published the research: A Power Transformer Fault Prediction Method through Temporal Convolutional Network on Dissolved Gas Chromatography Data, in the Journal: Security and Communication Networks of 11/04/2022
• what: The authors propose a method for fault prediction for power transformers based on dissolved gas chromatography data: after data preprocessing of defective raw data fault classification is performed based on the predictive regression results. (3) On real-world data, the work shows convincing benefits . . .
  

   

  

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