Research on Transformer Health Status Assessment and Lifespan Prediction Based on Multidimensional Deterioration Fusion
Year: 2024
Type: article
Abstract: Power transformer is the core equipment in the power system, and its health status concerns the safe and stable operation of power system. Accurately evaluating and reliably predicting on the health status and lifespan of the transformer can provide important information for transformer operation and maintenance, consequently reduce the cost and fault risk. This work proposes a multidimensional degradation fusion method for evaluating the health status and predict the lifespan of transformers. Firstly, the multidimensional indicators that affect the health status of transformers are analyzed, and thus an indicator system is established. The degradation of each indicator is quantified by calculating the deviation between the measurement value and the initial value. Secondly, we analyzed impacts of various indicators on the health of transformers, hence we obtained the contribution weights of each dimension of deterioration on the health of transformers. Furthermore, we considered the nonlinear impact of indicator deterioration changes on transformer health. Consequently, we established the transformer health assessment model and the lifespan prediction model based on multidimensional deterioration nonlinear fusion mapping. Finally, we took an example to evaluate the health status of a transformer by utilizing the established mathematical model. The results demonstrated that the evaluation results of this method were consistent with reality, and the model was effective.
Authors: Jianmin Yang, Yalin Fang, Dezhi Li, Xing Li
Institution: Nanjing University of Aeronautics and Astronautics
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4402425183