DBN (deep belief network)-GA neural network-based fault detection method of high-voltage circuit breaker

Abstract

The invention discloses a DBN (deep belief network)-GA neural network-based fault detection method of a high-voltage circuit breaker. The method specifically includes the following process: using current data, which are obtained by monitoring of an online monitoring system, as input variables; then using a deep belief network-based deep learning algorithm to construct a fault type prediction model, determining restricted Boltzmann machine models, marking the same as RBM, extracting partial current data samples to send the same to the constructed models, and carrying out training; carrying outtraining learning on the entire deep belief network model after training on the restricted Boltzmann machines; and finally, inputting all the data into the trained fault type prediction model, and processing the input coil tripping / closing current data by the fault type prediction model to complete fault detection of the high-voltage breaker. According to the method disclosed by the invention, a fault type of the circuit breaker can be judged more accurately and efficiently while compensating for the deficiencies of artificial neural network detection is realized, and then efficient inspectioncan be performed.

Description

technical field [0001] The invention belongs to the technical field of detection methods for high-voltage circuit breakers, and relates to a fault detection method for high-voltage circuit breakers based on a DBN-GA neural network. Background technique [0002] High-voltage circuit breakers are the most important control and protection devices in power systems, which are related to the reliability and safety of power transmission, power distribution and power consumption. High voltage circuit breakers are capable of multiple operations under system fault and non-fault conditions. The circuit breaker can also close, carry and break the normal current of the operating circuit, and can also close, carry and break the specified overload current within the specified time. High-voltage circuit breakers generally use electromagnets as the first control element to operate, and most of the operating mechanisms are DC electromagnets. When the current passes through the coil, magneti...

AI Technical Summary

Problems solved by technology

It can not only identify features, classify data, but also use it to generate data, but because its learning process is too simple, there may be incomplete training defects in the training process; therefore, using genetic algorithm (GA) to optimize deep belief neural network The network can solve this problem and update its weight until it is within the set error range to improve the accuracy of diagnosis. This method is well applied in circuit breaker fault diagnosis

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