High-voltage circuit breaker mechanical performance evaluation method based on deep residual network

Abstract

The invention discloses a high-voltage circuit breaker mechanical performance evaluation method based on a deep residual network. The method comprises the following steps: S1, acquiring opening completion image data, opening and closing process image data, closing completion image data and opening and closing process current waveform data of different types of circuit breakers as sample data; S2, preprocessing sample data in the step S1, and dividing the preprocessed sample data into a training data set, a test data set and a verification data set; through the deep residual network algorithm, machine intelligent learning is carried out, the mechanical performance state of the high-voltage circuit breaker is intelligently judged, the accuracy and reliability of an evaluation result are improved, the performance state of the high-voltage circuit breaker can be accurately mastered by a power grid, the service life of the high-voltage circuit breaker is prolonged, and the input cost of the power grid for the high-voltage circuit breaker is reduced.

Description

technical field [0001] The invention relates to the technical field of high-voltage circuit breakers, in particular to a method for evaluating the mechanical performance of high-voltage circuit breakers based on a deep residual network. Background technique [0002] The circuit breaker is an important device in the high-voltage power grid, which mainly plays the role of control and protection equipment. With the increase of service time, some parts of the circuit breaker will continue to age or be damaged, such as the wear of the mechanical mechanism, the wear of the contacts, the failure of the opening and closing secondary mechanism, etc. These problems may lead to abnormal operation of the circuit breaker, and even affect the safe operation of the entire power grid. [0003] Therefore, it is very important to regularly check the performance of the circuit breaker and detect its operating status. However, there are many problems in the current detection methods of high-v...

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Problems solved by technology

[0005] The present invention mainly solves the problem of low accuracy of the mechanical performance state evaluation of the high-voltage circuit breaker in the existing technology; provides a method for evaluating the mechanical performance of the high-voltage circuit breaker based on the deep residual network, and combines the deep residual learning network for the high-voltage circuit breaker. Evaluate the mechanical performance of the high-voltage circuit breaker to improve the accuracy and reliability of the evaluation results, so that the power grid can accurately grasp the performance status of the high-voltage circuit breaker and prolong the service life of the high-voltage circuit breaker

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