Prediction of the Closing Time of UHV Disc Spring Hydraulic Operating Mechanism Circuit Breakers Considering Low-Cycle Fatigue

To address the issues of cumulative plastic deformation and low-cycle fatigue cracking in ultra-high voltage (UHV) disc spring hydraulic circuit breakers under long-term cyclic high-pressure loads, which lead to internal structural changes and affect closing time stability and phase-controlled closing accuracy, this paper proposes a closing time prediction model considering the low-cycle fatigue of the operating mechanism. First, a Simulink-based simulation model of the 550 kV disc spring hydraulic operating mechanism transmission system was developed to analyze the influence of structural parameter variations on closing time under no-load conditions. Then, an objective function for judging action time stability was constructed, and the stability and influence weights of each structural parameter were calculated under different mechanical dispersion requirements using a combination of adaptive surrogate models and directional importance sampling. Results show that critical parameters such as working cylinder inner diameter, working cylinder stroke, main valve stroke, and working cylinder rod diameter significantly affect closing time, contributing approximately 25%, 20%, 15%, and 10%, respectively. Finally, a dynamic-weighted closing time prediction model was designed based on different phase-controlled accuracy requirements. Compared with no-load closing tests, under mechanical dispersion conditions of ±1 ms, ±1.5 ms, and ±2 ms, the optimized model reduced maximum deviations by 12.8%, 20.4%, and 23.3%, and narrowed fluctuation ranges by 37%, 38.3%, and 38.6%, respectively, significantly improving prediction accuracy. This work is supported by the Science and Technology Project of China Southern Power Grid (No.CGYKJXM20220346).

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Publication Details

Journal
Processes
Published
2025-04-15
DOI
https://doi.org/10.3390/pr13041196
Primary Topic
Smart Grid and Power Systems
Type
article
Field-Weighted Citation Impact
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article

Prediction of the Closing Time of UHV Disc Spring Hydraulic Operating Mechanism Circuit Breakers Considering Low-Cycle Fatigue

Qi Long, Dachao Huang, Xiongying Duan, Mingchun Hou et al.
Processes
Smart Grid and Power Systems
article

Prediction of the Closing Time of UHV Disc Spring Hydraulic Operating Mechanism Circuit Breakers Considering Low-Cycle Fatigue

Qi Long, Dachao Huang, Xiongying Duan, Mingchun Hou, Keru Jiang, Mingyang Li, Yang Xu, Weiguo Li, Peng Xiang, D.R Xiong
article en

Abstract

To address the issues of cumulative plastic deformation and low-cycle fatigue cracking in ultra-high voltage (UHV) disc spring hydraulic circuit breakers under long-term cyclic high-pressure loads, which lead to internal structural changes and affect closing time stability and phase-controlled closing accuracy, this paper proposes a closing time prediction model considering the low-cycle fatigue of the operating mechanism. First, a Simulink-based simulation model of the 550 kV disc spring hydraulic operating mechanism transmission system was developed to analyze the influence of structural parameter variations on closing time under no-load conditions. Then, an objective function for judging action time stability was constructed, and the stability and influence weights of each structural parameter were calculated under different mechanical dispersion requirements using a combination of adaptive surrogate models and directional importance sampling. Results show that critical parameters such as working cylinder inner diameter, working cylinder stroke, main valve stroke, and working cylinder rod diameter significantly affect closing time, contributing approximately 25%, 20%, 15%, and 10%, respectively. Finally, a dynamic-weighted closing time prediction model was designed based on different phase-controlled accuracy requirements. Compared with no-load closing tests, under mechanical dispersion conditions of ±1 ms, ±1.5 ms, and ±2 ms, the optimized model reduced maximum deviations by 12.8%, 20.4%, and 23.3%, and narrowed fluctuation ranges by 37%, 38.3%, and 38.6%, respectively, significantly improving prediction accuracy. This work is supported by the Science and Technology Project of China Southern Power Grid (No.CGYKJXM20220346).

ProcessesVol. 13(4)
Dalian University of Technology (CN), China Southern Power Grid (China) (CN)
China Southern Power Grid
Openalex Percentile: Top 94%
Smart Grid and Power Systems
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