Power equipment fault detection model based on attention mechanism in combination with GRU

Abstract

The invention discloses a power equipment fault detection model based on combination of an attention mechanism and a GRU, the power equipment fault detection model comprises a classification neural network model, and training data of the classification neural network model comes from a preprocessing model. The preprocessing model converts input unbalanced power equipment data into balanced data and performs embedded representation, and outputs intermediate data: a historical state sequence based on power equipment representation, label data embedded representation and embedded representation of power equipment portrait features; time and space features of the power equipment are extracted from the historical state sequence through a GRU module; state sequence features are extracted from the output of the GRU module through an attention mechanism module; environment information of the power equipment is extracted from the embedded representation of the portrait features of the power equipment through a graph attention mechanism module; and the state sequence features, the label data embedding representation and the environment information are aligned and fused to serve as training data input of the classification neural network.

Description

technical field [0001] The invention belongs to the technical field of power equipment fault detection, relates to a power grid fault detection method, and particularly relates to a power equipment fault detection model based on an attention mechanism combined with a GRU. Background technique [0002] In the era of the rapid development of science and technology and the continuous optimization of the economic structure, the power problem is facing major challenges. With the increase in the number of power users and enterprises, especially in areas with a large proportion of industrial development, the requirements for power supply will be higher. When the power supply equipment fails in these areas, the industrial equipment will be unable to operate for a long time, which will cause a A series of serious consequences, therefore, automatic fault detection of electrical equipment plays an important role in the power supply system. The existing fault detection methods based on...

AI Technical Summary

Problems solved by technology

Existing fault detection methods based on traditional power equipment are complicated and inefficient. At the same time, the existing models cannot make full use of unbalanced power fault data, which greatly reduces the actual value of the model.

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