Dry-type transformer temperature rise and partial discharge cooperative monitoring system

By collaboratively monitoring the temperature and electromagnetic pulse data of dry-type transformers, generating a health status benchmark and calculating residuals, the problem of misjudgment of dry-type transformers in complex environments is solved, and efficient identification of internal insulation defects and improvement of anti-interference capabilities are achieved.

CN122193840APending Publication Date: 2026-06-12一览众山(厦门)电力技术有限公司
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
一览众山(厦门)电力技术有限公司
Filing Date
2026-05-14
Publication Date
2026-06-12

AI Technical Summary

Technical Problem

Existing dry-type transformer monitoring technologies are prone to misjudging load temperature rise as internal insulation faults or external electromagnetic interference under heavy loads and complex electromagnetic environments, resulting in low identification accuracy and insufficient anti-interference capabilities.

Method used

The system employs a data acquisition module to acquire temperature and electromagnetic pulse data, combines a benchmark reconstruction module to generate an ideal temperature field and phase spectrum under healthy conditions, a parameter injection module to generate a theoretically damaged simulation state, a differential extraction module to calculate residuals, a coupled decision module to perform multidimensional similarity and correlation analysis, and a feedback module to update model parameters to improve accuracy.

Benefits of technology

It effectively distinguishes between load temperature rise, external electromagnetic interference and internal insulation defects, improves the anti-interference capability of the monitoring system and the interpretability and reliability of the evaluation results, and realizes early identification and continuous calibration of internal insulation defects.

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Abstract

The present application relates to the field of power equipment online monitoring and fault diagnosis, in particular to a dry-type transformer temperature rise and partial discharge cooperative monitoring system, comprising: a data acquisition module, which synchronously acquires temperature time series data, electromagnetic pulse time series data, power frequency phase reference data, load data, environmental data and spatial position identification; a reference reconstruction module, which generates ideal temperature field reference and ideal phase spectrum reference under healthy state; a parameter injection module, which injects parameterized defect model of predetermined insulation defect type, and generates theoretical damaged simulation state; a difference extraction module, which generates theoretical residual and actual residual; a coupling decision module, which constructs space-time joint tensor and outputs state evaluation result; a feedback module, which updates defect model parameters and / or decision threshold; the present application can realize stable identification of early internal insulation degradation under heavy load working condition.
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