Transformer fault diagnosis system and method based on digital twinning

Abstract

The invention belongs to the field of transformer fault diagnosis, and particularly relates to a transformer fault diagnosis system and method based on digital twinning, the transformer fault diagnosis system is composed of a physical system module, a digital twinning module and a fault diagnosis module, and the method specifically comprises the following steps: creating a three-dimensional model of the transformer by using the physical system module and acquiring transformer operation state data acquired by a sensor; using the digital twinning module to create a transformer digital twinning model, and generating analog data and calibration of the digital twinning model; and performing fault diagnosis of the transformer by using the fault diagnosis module. According to the invention, the physical entity of the transformer is combined with the virtual model, the digital twin model is corrected according to the state monitoring data obtained by the sensor and the simulation data of the twin model, the characteristic parameters are extracted, and the fault type is diagnosed by using the BP neural network algorithm. The possible reasons of the fault are analyzed, the maintenance cost and period of the transformer are reduced, the fault diagnosis efficiency is improved, and the transformer can operate safely and reliably.

Description

technical field [0001] The invention belongs to the field of transformer fault diagnosis, and in particular relates to a digital twin-based transformer fault diagnosis system and method thereof. Background technique [0002] Transformers are important equipment in power transmission, transformation, power supply and distribution systems. The safe, reliable and stable operation of transformers is the foundation of safe, reliable and stable operation of power supply networks. Once a failure occurs, it will affect the use of power and safe operation. Carry out real-time fault diagnosis according to the operation status of the transformer, so that the fault can be found and dealt with in time, so as to avoid huge economic losses. [0003] At present, the transformer fault diagnosis method is mostly through the combination of manual data sampling and online parameter sampling, and the maintenance personnel judge the operation status of the transformer according to these sampling ...

AI Technical Summary

Problems solved by technology

However, because manual judgment generally only combines the current sampling data, the efficiency of fault diagnosis is low, and it is impossible to find the source of the fault and determine the type of fault in time

Images