scholarly journals A Neural Network Based Response Model for High Voltage Circuit-Breaker Testing

Author(s):  
Wesley Doorsamy ◽  
Pitshou Bokoro
2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Hongkui Yan ◽  
Xin Lin ◽  
Jianyuan Xu

In this article, we take a 126 kV single-break vacuum circuit breaker as the research object and study the application of high-energy-density PM motor in the high-voltage circuit breaker for the first time. The PM motor maintains maximum power density and torque density during the start-up phase. Note that most of the faults of high-voltage circuit breakers are mechanical faults. We designed a set of mechanical fault prediction systems for high-voltage circuit breakers. We present the prediction method of the opening and closing action curve of the high-voltage circuit breaker. It is inspired by Chaos Ant Colony Algorithm (CAS) and an optimized Long- and Short-Term Memory (LSTM) cycle neural network. We constructed the main structure of the neural network expert system and established the fault prediction model of the high-voltage circuit breaker, based on the LSTM cycle neural network, optimized by CAS. We used the improved least-square method to achieve the operation accuracy of the phase control switch. Finally, we completed the development and experiment of the prototype.


2013 ◽  
Vol 380-384 ◽  
pp. 3213-3216
Author(s):  
Hai Yan Wang ◽  
Duan Lei Yuan ◽  
Chen Xu Niu ◽  
Hua Jun Dong

In this paper, mainly for the problem that high voltage circuit breaker closing at the random phase can bring hard harmfulness to the power system. We design the 35kV SF6-Phase Control circuit breaker can control speed smartly, and opens or closes with phase selection, which is equipped with the magnetic actuator. In the article, the static and transient simulation analysis which includes the load force, and carried out prototype trial and test validation. At last, the results of simulation and test is given.


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