Method of Analyzing Transformer DC Magnetic Bias Based on Big Data Cleaning and Dimensionality Reduction

Abstract

Transformer DC magnetic bias is difficult to accurately analyze and predict because it is caused by complex factors and has a wide influence. This paper combines big data with DC bias magnetic analysis method, making a breakthrough in the DC bias prediction model that only considers a single factor. From the perspective of multi-system coupling, this paper analyzes the modeling of DC magnetic bias based on multi-dimensional big data, and extracts the key influencing factors of transformer DC bias through multi-system big data cleaning and dimensionality reduction technology, thus providing an effective basis for "one-button sequence control" bias magnetic treatment.