Measurement and Operation Based Condition Monitoring Methodology for High Voltage Circuit Breakers

Asefi, Sajjad; Andreesen, Guido; Leinakse, Madis; Kilter, Jako; Kalmet, Tauri; Manninen, Henri; Landsberg, Mart

doi:10.1109/isgt-europe54678.2022.9960521

Cited by 8 publications

(1 citation statement)

References 14 publications

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“…During the operation of the spring mechanism dynamics, the update of the weights is completed by the adaptive momentum estimation gradient optimization algorithm [10], and the formula is:…”

Section: Input Layermentioning

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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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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“…During the operation of the spring mechanism dynamics, the update of the weights is completed by the adaptive momentum estimation gradient optimization algorithm [10], and the formula is:…”

Section: Input Layermentioning

confidence: 99%