Support vector machine high-voltage circuit breaker fault diagnosis method based on fuzzy clustering

Abstract

The invention discloses a support vector machine high-voltage circuit breaker fault diagnosis method based on fuzzy clustering. The method comprises the steps of firstly, extracting a feature vector from a stroke-time curve of a circuit breaker moving contact, using the feature vector as a database of fault diagnosis, secondly, conducting fizzy clustering processing on a data sample, generating a new clustering center matrix, thirdly, using the clustering center matrix as a training sample, applying a support vector machine to conduct training, and fourthly applying the high-voltage circuit breaker fault diagnosis method to diagnose test data. According to the support vector machine high-voltage circuit breaker fault diagnosis method based on the fuzzy clustering, the efficiency of the high-voltage circuit breaker fault diagnosis can be effectively improved, the time of the fault diagnosis is reduced, the quality of the fault diagnosis is improved, and the support vector machine high-voltage circuit breaker fault diagnosis method has great significance for research on the safety and the reliability of the power grid.

Description

technical field [0001] The invention relates to the field of grid scheduling and fault diagnosis analysis, in particular to a support vector machine fault diagnosis method for high-voltage circuit breakers based on fuzzy clustering. Background technique [0002] With the development of society and economy, the power system plays an increasingly important role in the national economy. People's demand for electricity is increasing, prompting the continuous expansion of the grid. With the improvement of voltage level and the increase of installed capacity, users have higher and higher requirements for power supply quality and reliability, and the system has higher and higher requirements for the operation reliability of power equipment. Technology puts forward higher requirements. High-voltage circuit breakers play the dual role of control and protection in the power grid. They are very important switching devices in the power system, and there are many of them. Therefore, hi...

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Problems solved by technology

[0004] But now it is in the research stage, and the methods for fault identification of high-voltage circuit breakers are different. Some diagnostic algorithms are single, and some algorithms have their own limitations. The actual fault diagnosis and identification are not very good. As far as neural network identification is concerned, neural network The network is used in the fault diagnosis of high-voltage circuit breakers, which cannot adapt to the situation of small samples, is easy to fall into the situation of local minimum, and cannot meet the training speed of high-voltage circuit breaker diagnosis that needs real-time monitoring

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