Journal of Northeastern University(Natural Science) ›› 2025, Vol. 46 ›› Issue (7): 22-29.DOI: 10.12068/j.issn.1005-3026.2025.20240218

• Industrial Intelligent Theory and Methods • Previous Articles     Next Articles

Digital Twin Fault Diagnosis Method of Power Transformer Based on Industrial Intelligence

Jian FENG1(), Bo-wen ZHANG1,2, Ning ZHAO1, Hui-jie JIANG1   

  1. 1.School of Information Science & Engineering,Northeastern University,Shenyang 110819,China
    2.Northeast Branch,State Grid Corporation of China,Shenyang 110000,China.
  • Received:2024-11-25 Online:2025-07-15 Published:2025-09-24
  • Contact: Jian FENG

Abstract:

As a key development direction integrating new-generation information technology with advanced manufacturing techniques, industrial intelligence leverages intelligent, digital, and automated methods to significantly enhance industrial production efficiency and optimize the prediction and maintenance management of industrial equipment. This paper focuses on the intelligentization of industrial equipment, with the goal of ensuring the efficient and stable operation of power transformers within power systems. A digital twin model for transformer inter-turn short circuit faults is constructed based on electromagnetic field equations and equivalent circuit models. The model analyzes the symmetry of the transformer in both normal and fault conditions from an electromagnetic field perspective, thereby integrating digital twin technology with fault diagnosis. Furthermore, through in-depth analysis of the virtual model of the transformer, the location of faults is accurately identified, ensuring the safe operation of the transformer, improving its reliability and efficiency, and advancing the intelligentization and modernization of the entire power system.

Key words: digital twin (DT), industrial intelligence, power transformer, electromagnetic field, fault location

CLC Number: