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

doi:10.12068/j.issn.1005-3026.2025.20240218

Abstract

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:

TM 41

Jian FENG, Bo-wen ZHANG, Ning ZHAO, Hui-jie JIANG. Digital Twin Fault Diagnosis Method of Power Transformer Based on Industrial Intelligence[J]. Journal of Northeastern University(Natural Science), 2025, 46(7): 22-29.

Figures/Tables 9

Fig.1 DT multifield coupling framework

Fig.2 Equivalent circuit diagram of inter-turn short circuit

Fig.3 Distribution of magnetic flux density inside transformerPYn=∑n=15Yn∑m=ACXm. (16)

Table 1 Basic parameters of transformer

名称	数值	名称	数值
额定容量/kVA	250	高压绕组直径/mm	240
额定电压/V	220/36	低压绕组直径/mm	180
高压绕组匝数/匝	220	高压绕组高度/mm	300
低压绕组匝数/匝	36	低压绕组高度/mm	300
铁芯宽度/mm	170	铁芯高度/mm	350

Fig.4 Experimental platform for magnetic leakage measurement

Fig.5 Comparison of magnetic flux density distribution in normal state

Fig.6 Comparison of magnetic flux density distribution in fault states

Fig.7 Fault location result and actual location

Fig.8 Fault location error

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