Machine Learning Based Predictive Maintenance Solution for Transformers

Abstract

In order to improve the existing maintenance scheme for distribution transformers and better realise the application of big data in electricity, this paper proposes a machine learning-based predictive maintenance scheme for transformers, using data characterised by dissolved gas data in transformer oil, firstly processing the original transformer collection data, then using a hidden semi-Markov model (HSMM) to determine the operational status of the transformer, and further using an improved Convolutional neural networks are used to classify and predict abnormal data,