Transformer abnormal loss positioning method, device, storage medium and program product
By applying the load loss mechanism model and the root cause analysis method of the Adtributor algorithm in the transformer, the root cause of the abnormal load loss of the transformer is accurately positioned, and the problem of positioning difficulties in the existing technology is solved and the consistency of product quality is improved.
CN119375593BActive Publication Date: 2025-03-28TBEA TECH INVESTMENT CO LTD
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Patent Information
- Application Number
- CN202411909645.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-24
- Publication Date
- 2025-03-28
- Estimated Expiration
- 2044-12-24
AI Technical Summary
Technical Problem
The prior art is difficult to accurately locate the root cause of abnormal transformer load loss, which makes it difficult to control product quality consistency.
Method used
By obtaining the actual measured data and standard data of the transformer, the root cause analysis is performed based on the load loss mechanism model, including the resistance loss calculation model and the additional loss fitting model, and the main and potential root cause of load loss is used to locate the main and potential root cause of load loss.
Benefits of technology
Accurate positioning of abnormal load loss of transformer is achieved, subjective deviations in manual empirical judgments are reduced, and the accuracy of abnormal loss positioning and consistency of product quality are improved.
✦ Generated by Eureka AI based on patent content.
Abstract
The present application discloses a method, device, storage medium and program product for locating abnormal transformer loss, which relates to the technical field of transformers, including: obtaining transformer data of a transformer to be analyzed; transformer data includes measured data and corresponding standard data; performing root cause analysis on the transformer to be analyzed based on transformer data and a load loss mechanism model of the transformer, and obtaining root cause analysis results; the load loss mechanism model includes a resistance loss calculation model and an additional loss fitting model, and the additional loss fitting model is obtained by fitting multiple groups of measured values of additional loss influencing parameters and the additional loss measured values corresponding to each group of the measured values; based on the root cause analysis results, locating the load loss anomaly of the transformer to be analyzed. The present application can more accurately locate the root cause of the abnormal load loss of the transformer.
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