基于经验小波变换的真空断路器关合预击穿燃弧时间分析

doi:10.19595/j.cnki.1000-6753.tces.L11013

Abstract
Figure/Table
References
Related Citation (15)

Download: PDF (2155 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract As an important equipment for switching capacitor banks for reactive power compensation in distribution network system, the reliability of vacuum circuit breaker directly affects the stable operation of power system. In the process of putting into the capacitor bank, when the circuit breaker is pre-strike, the closing inrush current appears synchronously until the contact is just closed, and the inrush current exists in the form of arcing, which is called pre-strike arcing. It will cause contact burning, fusion welding and material transfer, reduce the capacitive breaking capacity of the circuit breaker. Therefore, the accurate analysis of the pre-strike arcing time when the vacuum circuit breaker is closing can be used to evaluate the capacitive breaking capacity of the circuit breaker in real time.
When the capacitor bank is put into the system, the inrush current between the contacts of the circuit breaker can reach up to 20 kA, and the generated electric repulsion makes the final speed of the contact change at the moment of closing. In addition, when carrying out high-voltage and high-current conditioning, hundreds of closing operations are required. The mechanical dispersion of the circuit breaker mechanism itself will also affect the accurate positioning of the instant closing point and reduce the calculation accuracy of the pre-strike arcing time. The displacement signal contains the accurate information of the instant closing point. Based on this, this paper proposes an analysis method of closing pre-strike arcing time based on empirical wavelet transform (EWT).
Firstly, the least squares method is used to preprocess the collected closing displacement signal. On the premise of completely retaining the step change at the instant closing point, the environmental noise interference during signal acquisition is eliminated, which provides a guarantee for the accurate calculation of the subsequent closing pre-strike arcing time. After that, the pre-processed displacement signal is decomposed by EWT, and it is divided into six empirical wavelet function (EWF) components according to different frequency bands, and the high-frequency components of the contact closing moment are completely separated. Next, the kurtosis criterion is used to filter out the EWF component containing the effective information of the rigid point, and the effective positioning of the rigid point is realized. Finally, the starting time of the closing inrush current waveform is positioned, and the time difference between the starting time of the closing inrush current and the closing point is measured, and the pre-strike arcing time is obtained.
Through carrying out simulation analysis and comparing with different methods, the error range of the pre-strike arcing time analysis method based on EWT is within 0.18 ms, which is higher than the 0.35~0.5 ms of the comparison methods, showing higher accuracy. On this basis, considering the influence of different test voltages, different inrush current amplitudes, and different mechanism speeds, field tests were carried out. The experimental results show that the mean error represented by the mean absolute error (MAE) evaluation index is always less than 0.2 ms, and the error dispersion represented by mean-square error (MSE) is always less than 0.03 ms², which can meet the needs of accurate calculation of pre-strike arcing time without high-precision differential probes.
Subsequently, on this basis, the pre-strike arcing time analysis method can be further applied to high-voltage and high-current conditioning, and the quantitative improvement of capacitive breaking capacity can be realized by precise control of pre-strike arcing energy.

Key words： Vacuum circuit breaker pre-strike arcing time displacement signal least squares empirical wavelet transform kurtosis

Received: 06 July 2024

PACS:

TM561.2

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Zhang Dengkui
	Zhang Liyan
	Li Zhibing
	Zhang Ran
	Dong Enyuan

Cite this article:

Zhang Dengkui,Zhang Liyan,Li Zhibing等. Analysis of Pre-Strike Arcing Time for Vacuum Circuit Breaker Closure Based on Empirical Wavelet Transform[J]. Transactions of China Electrotechnical Society, 2024, 39(zk1): 106-116.

URL:

https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.L11013 OR https://dgjsxb.ces-transaction.com/EN/Y2024/V39/Izk1/106

[1] 马喜平, 贾嵘, 梁琛, 等. 高比例新能源接入下电力系统降损研究综述[J]. 电网技术, 2022, 46(11): 4305-4315.
Ma Xiping, Jia Rong, Liang Chen, et al.Review of researches on loss reduction in context of high penetration of renewable power generation[J]. Power System Technology, 2022, 46(11): 4305-4315.
[2] Zhao Heng, Xiao Xianyong, Sun Qiuqin.Identifying electric shock in the human body via α dispersion[J]. IEEE Transactions on Power Delivery, 2018, 33(3): 1107-1114.
[3] 韩翔宇, 纽春萍, 何海龙, 等. 电磁式断路器状态监测与智能评估技术综述[J]. 电工技术学报, 2023, 38(8): 2191-2210.
Han Xiangyu, Niu Chunping, He Hailong, et al.Review of condition monitoring and intelligent assessment of electromagnetic circuit breaker[J]. Transactions of China Electrotechnical Society, 2023, 38(8): 2191-2210.
[4] 甘战, 冯田, 张鹏, 等. 基于录波数据的断路器关合时间整定计算方法研究[J]. 电力系统保护与控制, 2019, 47(18): 145-151.
Gan Zhan, Feng Tian, Zhang Peng, et al.Calculation method on circuit breaker closing time based on fault recording data[J]. Power System Protection and Control, 2019, 47(18): 145-151.
[5] Razi-Kazemi A A, Vakilian M, Niayesh K, et al. Priority assessment of online monitoring investment for power system circuit breakers: part I: qualitative-quantitative approach[J]. IEEE Transactions on Power Delivery, 2013, 28(2): 928-938.
[6] 高崇, 邵在康, 康忠健, 等. 基于扩展卡尔曼滤波的水中放电阶段辨识方法[J]. 电工技术学报, 2024, 39(11): 3475-3485.
Gao Chong, Shao Zaikang, Kang Zhongjian, et al.Method for identifying stages of discharge in water based on extended Kalman filter[J]. Transactions of China Electrotechnical Society, 2024, 39(11): 3475-3485.
[7] 刘士利, 吕东建, 张飞. 断路器并联动态合闸电阻对滤波器合闸涌流的抑制效能研究[J]. 电网技术, 2024, 48(9): 3931-3937.
Liu Shili, Lü Dongjian, Zhang Fei.Study on the suppression efficacy of filter closing inrush currents by shunt dynamic closing resistor of circuit breaker[J]. Power System Technology, 2024, 48(9): 3931-3937.
[8] 吴燕, 余勇祥, 韩筛根, 等. 真空开关容性电流开断技术[J]. 高压电器, 2017, 53(3): 26-34.
Wu Yan, Yu Yongxiang, Han Shaigen, et al.Technique of capacitive switching for vacuum switches[J]. High Voltage Apparatus, 2017, 53(3): 26-34.
[9] 雷雨, 李光辉, 王伟胜, 等. 跟网型和构网型新能源并网控制阻抗对比与振荡机理分析[J]. 中国电机工程学报, 2025, 45(1): 150-163.
Lei Yu, Li Guanghui, Wang Weisheng.et al.Comparison of impedance characteristics and oscillation mechanism for grid following and grid forming renewable energy[J]. Proceedings of the CSEE, 2025, 45(1): 150-163.
[10] 田阳, 李志兵, 田宇, 等. 高比例新能源接入下快速真空断路器容性开合能力提升研究[J]. 电网技术, 2024, 48(6): 2670-2679.
Tian Yang, Li Zhibing, Tian Yu, et al.Research on the improvement of capacitive opening and closing ability of fast circuit breaker under high proportion of new energy access[J]. Power System Technology, 2024, 48(6): 2670-2679.
[11] 李世民, 徐勋晨, 张潮海. 基于深度学习的冲击电压老炼过程中真空击穿机制甄别优化方法[J]. 电工技术学报, 2024, 39(13): 4153-4163.
Li Shimin, Xu Xunchen, Zhang Chaohai.Optimization method for classifying breakdown mechanism during impulse voltage conditioning process based on deep learning[J]. Transactions of China Electrotechnical Society, 2024, 39(13): 4153-4163.
[12] 常广, 王毅, 王玮. 采用振动信号零相位滤波时频熵的高压断路器机械故障诊断[J]. 中国电机工程学报, 2013, 33(3): 155-162, 3.
Chang Guang, Wang Yi, Wang Wei.Mechanical fault diagnosis of high voltage circuit breakers utilizing zero-phase filter time-frequency entropy of vibration signal[J]. Proceedings of the CSEE, 2013, 33(3): 155-162, 3.
[13] 周进飞, 罗勇, 韩耀东. 12kV真空断路器刚合点在线监测方法研究[J]. 高压电器, 2023, 59(9): 219-225.
Zhou Jinfei, Luo Yong, Han Yaodong.Research on online monitoring method of the instant closing point of 12kV vacuum circuit breaker[J]. High Voltage Apparatus, 2023, 59(9): 219-225.
[14] 岳宇鑫. 投切10kV电容器用真空断路器寿命评估方法研究[D]. 北京: 华北电力大学, 2022.
Yue Yuxin.Research on key technologies of partial porousexternally pressurized gas bearing[D]. Beijing: North China Electric Power University, 2022.
[15] Razi-Kazemi A A, Niayesh K, Nilchi R. A probabilistic model-aided failure prediction approach for spring-type operating mechanism of high-voltage circuit breakers[J]. IEEE Transactions on Power Delivery, 2019, 34(4): 1280-1290.
[16] 胡博凯, 李奎, 牛峰, 等. 低压断路器机械特性状态监测方法研究[J]. 电工技术学报, 2022, 37(13): 3317-3330.
Hu Bokai, Li Kui, Niu Feng, et al.Research on condition monitoring method of mechanical characteristics of low-voltage circuit breaker[J]. Transactions of China Electrotechnical Society, 2022, 37(13): 3317-3330.
[17] Yang Qiuyu, Ruan Jiangjun, Zhuang Zhijian, et al.Chaotic analysis and feature extraction of vibration signals from power circuit breakers[J]. IEEE Transactions on Power Delivery, 2020, 35(3): 1124-1135.
[18] Albernaz Lacerda V, Monaro R M, Campos-Gaona D, et al.Distance protection algorithm for multiterminal HVDC systems using the Hilbert-Huang transform[J]. IET Generation, Transmission & Distribution, 2020, 14(15): 3022-3032.
[19] 林湘宁, 刘畅, 汪致洵, 等. 基于动态权重修正D-S证据理论的最后断路器多判据保护跳闸策略[J]. 中国电机工程学报, 2018, 38(9): 2609-2621, 2829.
Lin Xiangning, Liu Chang, Wang Zhixun, et al.Tripping strategy of multi criteria of last breaker protections based on dynamic weight correction D-S evidence theory[J]. Proceedings of the CSEE, 2018, 38(9): 2609-2621, 2829.
[20] 张志丰, 张凯, 董轩, 等. 基于电流有效值实时算法的限流器快速故障辨识方法[J]. 电气技术, 2022, 23(7): 81-88.
Zhang Zhifeng, Zhang Kai, Dong Xuan, et al.Fast fault identification method based on real-time algorithm of current root mean square value for fault current limiter[J]. Electrical Engineering, 2022, 23(7): 81-88.
[21] 何俊佳, 邹积岩, 张汉明, 等. 火花老炼对真空灭弧室绝缘强度的影响[J]. 电工技术学报, 1997, 12(3): 33-36.
He Junjia, Zou Jiyan, Zhang Hanming, et al.Effect of spark conditioning treatment on electrical strength of vacuum interrupters[J]. Transactions of China Electro-technical Society, 1997, 12(3): 33-36.
[22] Gilles J.Empirical wavelet transform[J]. IEEE Transactions on Signal Processing, 2013, 61(16): 3999-4010.
[23] Elouaham S, Dliou A, Nassiri B, et al.Combination method for denoising EMG signals using EWT and EMD techniques[C]//2023 IEEE International Con-ference on Advances in Data-Driven Analytics and Intelligent Systems (ADACIS), Marrakesh, Morocco, 2023: 1-6.
[24] Wei D, Ramamurthy K N, Katz-Rogozhnikov D A, et al. Multiplicative regression via constrained least squares[C]//2014 IEEE Workshop on Statistical Signal Processing (SSP), Gold Coast, Australia, 2014: 304-307.
[25] Zhao Hui, Wang Ruyan, Song Daiping, et al.Minimum norm least squares extrapolation estimate for discrete (a, b, c, d)-bandlimited signals[J]. IEEE Signal Processing Letters, 2012, 19(12): 853-856.
[26] 王晓卫, 王雪, 王毅钊, 等. 基于图像信息熵与多元变分模态分解的电缆局放信号去噪方法[J]. 电工技术学报, 2024, 39(13): 4100-4115, 4152.
Wang Xiaowei, Wang Xue, Wang Yizhao, et al.A denoising algorithm for cable partial discharge signals based on image information entropy and multivariate variational mode decomposition[J]. Transactions of China Electrotechnical Society, 2024, 39(13): 4100-4115, 4152.
[27] Khazaal A, Cabot F, Anterrieu E, et al.A kurtosis-based approach to detect RFI in SMOS image reconstruction data processor[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(11): 7038-7047.
[28] Hussein R, Shaban K B, El-Hag A H. Denoising different types of acoustic partial discharge signals using power spectral subtraction[J]. High Voltage, 2018, 3(1): 44-50.
[29] 刘萍, 李泽文, 蔡雨思, 等. 基于等效电路模型和数据驱动模型融合的SOC和SOH联合估计方法[J]. 电工技术学报, 2024, 39(10): 3232-3243.
Liu Ping, Li Zewen, Cai Yusi, et al.Joint estimation method of SOC and SOH based on fusion of equivalent circuit model and data-driven model[J]. Transactions of China Electrotechnical Society, 2024, 39(10): 3232-3243.