Key characteristic quantity determination method and system for characterizing health state of transformer

Abstract

The invention relates to a key characteristic quantity determination method and system for characterizing the health state of a transformer. The method comprises: determining a characteristic component analysis matrix of the transformer to be tested according to a characteristic quantity normalization matrix of the transformer to be tested, determining a characteristic component correlation analysis matrix between the characteristic quantities of the to-be-detected transformer according to the characteristic component analysis matrix of the to-be-detected transformer, and determining a key characteristic quantity representing the health state of the to-be-tested transformer according to the characteristic component correlation analysis matrix between the characteristic quantities of the to-be-tested transformer. According to the technical scheme, the problems that a traditional feature extraction method is insufficient in fitting precision, and the training speed is too low based on artificial intelligence algorithms such as a neural network are solved, theoretical support is provided for estimation of the health state of the transformer, and meanwhile immeasurable engineering practical value is achieved for timely elimination of faults of the transformer in the future.

Description

technical field [0001] The invention relates to the field of feature engineering, in particular to a method and system for determining key feature quantities representing the health state of a transformer. Background technique [0002] As one of the important operating equipment of the distribution network, the safe and reliable operation of the transformer is directly related to the safety and stability of the distribution network; however, the internal structure of the transformer is complex, and the accident rate is on the rise. Therefore, certain technical means must be adopted to ensure the safety and stability of the transformer. Safe and stable operation. [0003] At present, the distribution network mainly conducts planned maintenance on the transformer to ensure the safe and stable operation of the transformer, but the planned maintenance actually sacrifices the economic effect of the distribution network on the premise of ensuring the safety and reliability of the ...

AI Technical Summary

Problems solved by technology

[0008] Aiming at the deficiencies in the prior art, the purpose of the present invention is to provide a method for determining the key feature quantities that characterize the health status of transformers, which solves the problem of insufficient fitting accuracy of traditional feature extraction methods and excessive training speed based on artificial intelligence algorithms such as neural networks. The slow problem provides theoretical support for the estimation of transformer health status, and at the same time has immeasurable engineering practical value for timely troubleshooting of transformer faults in the future

Images