A method and device for diagnosing the metal wear state of a transformer power assembly

By constructing a transformer particle distribution function and conducting online monitoring, combined with the calculation of median particle size and weight growth rate, the problem of the inability to monitor small-sized particles in existing technologies has been solved, enabling real-time diagnosis of the wear condition of transformer power components and improving the convenience and timeliness of diagnosis.

CN116148113BActive Publication Date: 2026-06-19XISHUANGBANNA POWER SUPPLY BUREAU OF YUNNAN POWER GRID CO LTD +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
XISHUANGBANNA POWER SUPPLY BUREAU OF YUNNAN POWER GRID CO LTD
Filing Date
2023-02-24
Publication Date
2026-06-19

AI Technical Summary

Technical Problem

Existing metal abrasive sensors cannot effectively monitor small-sized ferromagnetic and non-ferromagnetic particles, resulting in the inability to diagnose the wear condition of transformer power components in a timely manner. Existing disassembly and inspection methods are labor-intensive and have poor timeliness.

Method used

A distribution function for ferromagnetic and non-ferromagnetic particles in a transformer is constructed. Data is collected by an abrasive sensor, and the median particle size and weight growth rate are calculated by combining a fitting formula to achieve online diagnosis of the metal wear condition of transformer power components.

Benefits of technology

It enables data prediction and real-time monitoring of small-diameter metal particles, avoiding the workload of disassembly and inspection, and improving the convenience and timeliness of diagnosis.

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Abstract

This application provides a method and apparatus for diagnosing the metal wear condition of transformer power components. The diagnostic method includes: constructing a distribution function of ferromagnetic and non-ferromagnetic particles in the transformer; acquiring data collected in a first period; inputting the collected data into the distribution function of ferromagnetic and non-ferromagnetic particles to calculate ferromagnetic and non-ferromagnetic particle data; adding the ferromagnetic and non-ferromagnetic particle data to obtain the metal particle data for the first period; acquiring the metal particle data for the second period; calculating the median particle size and weight growth rate of the metal particles based on the metal particle data from the two periods; and determining the metal wear condition of the transformer power components based on the median particle size and weight growth rate. By collecting and statistically analyzing metal particles in the oil of a faulty transformer, a statistical distribution function of the metal particles is obtained, and combined with actual monitoring data, prediction of small-diameter metal particle data that cannot be directly measured is achieved.
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Citation Information

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