Distribution transformer monitoring system and monitoring method

By preprocessing and field coupling analysis of multi-source data of distribution transformers and combining them with intelligent diagnosis models, the problem of low fault diagnosis accuracy of distribution transformers under complex working conditions is solved, and accurate identification of abnormal areas and fault risk assessment are achieved.

CN120632672AActive Publication Date: 2025-09-12GUANGZHOU POWER TRANSFORMATION & DISTRIBUTION INSTALLATION ENG CO LTD
7 Cites 6 Cited by

Patent Information

Application Number
CN202510692128.7
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-05-27
Publication Date
2025-09-12
Estimated Expiration
2045-05-27

AI Technical Summary

Technical Problem

Existing technologies are unable to accurately reflect the nonlinear interaction effects of multiple physical fields in distribution transformers under complex working conditions, resulting in low fault diagnosis accuracy. In particular, in scenarios of transient overload or local insulation degradation, it is easy to cause misjudgment and missed detection of abnormal areas.

Method used

By collecting multi-source data of distribution transformers in real time and preprocessing it, the three-dimensional temperature gradient field and mechanical stress distribution are calculated using finite element analysis and field coupling analysis. The OPTICS density clustering algorithm is combined to identify abnormal areas, and an intelligent diagnosis model is used to perform fault risk scoring and final diagnosis, ultimately generating a fault detection report.

Benefits of technology

It achieves accurate diagnosis of distribution transformer faults, improves the accuracy and reliability of fault diagnosis, and can automatically identify and quantify distributed fault areas.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

The invention discloses a distribution transformer monitoring system and method, and relates to the technical field of electric power intelligent monitoring, and the method comprises the steps: obtaining the three-dimensional temperature gradient field distribution and mechanical stress distribution of a distribution transformer based on a standardized multi-source data set, and outputting a comprehensive field matrix through a field coupling analysis method; performing spatial analysis on the comprehensive field matrix by adopting spatial hot spot analysis, identifying and marking temperature and mechanical stress abnormal areas, performing spatial aggregation and noise filtering through an OPTICS density clustering algorithm, and outputting abnormal feature vectors; inputting the abnormal feature vector into a pre-trained intelligent diagnosis model, outputting a comprehensive fault risk score and performing preliminary diagnosis; searching fault data in a historical case library based on the preliminary diagnosis result for comparison verification, and optimizing the preliminary diagnosis result through a machine learning algorithm to generate a final diagnosis result; according to the method, a field coupling analysis method is adopted to establish a heat-force bidirectional action model, and the spatial distribution characteristics of the temperature gradient and the stress tensor are accurately reflected.
Need to check novelty before this filing date? Find Prior Art