Weighted KNN algorithm-based moisture content evaluation method considering transformer aging effect

Abstract

The invention belongs to the technical field of electrical equipment fault diagnosis, and discloses a weighted KNN algorithm-based moisture content evaluation method considering a transformer aging effect. The method comprises the steps of: preparing and measuring FDS data of insulating paperboard samples in different aging states and moisture contents; extracting FDS curve characteristic parameters of the samples; fitting and constructing a database for representing water content information of the samples by using the characteristic parameters; constructing a moisture content evaluation model based on a KNN classification algorithm; testing the accuracy of the model by using laboratory samples; and applying the model to on-site transformer testing. According to the method, the FDS and KNN technologies are combined to construct the transformer oil paper insulation moisture content evaluation model considering the aging effect, the problem that the aging effect and the moisture content cannot be distinguished in a traditional FDS testing process is solved, and a basis is provided for deep mining of internal information of an FDS curve and accurate judgment of the moisture content of a field transformer.

Description

technical field [0001] The invention belongs to the technical field of fault diagnosis of electrical equipment, and in particular relates to a moisture content evaluation method based on a weighted KNN algorithm considering the aging effect of a transformer. Background technique [0002] Oil-immersed power transformers are key equipment for power system transmission. Its internal oil-paper insulation system plays an important role in the service life of the entire transformer. Therefore, an accurate evaluation of the insulation state of the transformer is an important issue related to the safe operation of the transformer and the stability of the entire power grid. [0003] As the operating time of oil-immersed power transformers increases, the performance of its internal insulation system gradually deteriorates, which is often accompanied by the generation of several aging by-products, such as acid, furan, alcohol, moisture, etc. Among them, moisture is not only a by-prod...

AI Technical Summary

Problems solved by technology

However, in addition to moisture effects, effects from aging by-products may also affect FDS data

In this case it is difficult to distinguish the contribution of moisture and aging on the measurement

Therefore, once the effect of aging on FDS is ignored, unreliable moisture content assessment results will be obtained

In addition, existing models are usually established with a small number of samples, and then only rely on qualitative / quantitative relationships to complete the state assessment. The above limitations limit the applicability of the model and it is difficult to generalize to different test conditions

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