Ultra-fast Resonant Hybrid DC Circuit Breaker

Weise, Nathan

doi:10.1007/978-3-031-26572-3_14

Power Systems

2023

DOI: 10.1007/978-3-031-26572-3_14

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Ultra-fast Resonant Hybrid DC Circuit Breaker

Nathan Weise

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2024

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“…E represents the input feature quantity at time t ; bf represents the bias.The input gate of the model determines the result of the update according to the sigmoid layer, creates a new candidate value vector t P [8], and introduces it into the cell state. The new information is stored in the cell state through the above two layers.…”

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Dynamic simulation analysis of high-voltage circuit breaker switch spring mechanism based on deep learning

Jiang,

Feng,

Lai

et al. 2024

International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023)

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As a key component of circuit breaker switch, the dynamic characteristics of spring mechanism are directly related to the response speed and stability of high voltage circuit breaker switch. Therefore, based on deep learning technology, this paper makes a dynamic simulation analysis of the switch spring mechanism of high voltage circuit breaker. Firstly, the operational data is decomposed into multiple IMF modal components using Empirical Mode Decomposition (IMF) method, and correlation coefficients are calculated to extract features. Secondly, using the Long Short Term Memory Network (LSTM) model, the feature inputs are learned and trained, and the dynamic mathematical model results of the spring mechanism are output. The forget gate and input gate in the model respectively handle information retention and update, achieving accurate simulation of dynamic simulation. The update of weights adopts the adaptive momentum estimation gradient optimization algorithm, which improves the accuracy of the model. By comparing the simulation results of traditional methods and deep learning methods, the superiority of deep learning algorithms in the dynamic simulation of high-voltage circuit breaker switch spring mechanisms was verified. By comparing the simulation results of traditional methods and deep learning methods, the superiority of deep learning algorithms in the dynamic simulation of high-voltage circuit breaker switch spring mechanisms was verified.

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confidence: 99%

Dynamic simulation analysis of high-voltage circuit breaker switch spring mechanism based on deep learning

Jiang,

Feng,

Lai

et al. 2024

International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023)

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Ultra-fast Resonant Hybrid DC Circuit Breaker

Cited by 1 publication

References 9 publications

Dynamic simulation analysis of high-voltage circuit breaker switch spring mechanism based on deep learning

Dynamic simulation analysis of high-voltage circuit breaker switch spring mechanism based on deep learning

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