溯源弹簧形变过程的断路器振动信号递归量化分析辨识方法

doi:10.19595/j.cnki.1000-6753.tces.230201

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Abstract High-voltage circuit breakers are key electrical equipment for power grid control and protection. As the structure complexity and automation of transmission and distribution networks continue to increase, the requirements for reliable operation are also increasing. Each movement has strict stage characteristics for high- voltage circuit breakers with the spring-operated mechanism, from energy storage spring release caused by the tripping of the locking mechanism to the moving contact driven by components and then to the rest. The mechanical vibration accompanying the action of the circuit breaker indicates the energy transmission and health status of the equipment. This paper proposes a method for the recursive quantitative analysis of vibration signals in high-voltage circuit breakers, focusing on traceability to the spring deformation process.
First, a high-speed camera captures the action image of the energy storage spring during circuit breaker operation. A specific target in the high-speed image sequence is dynamically extracted through a computer vision tracking algorithm (normalized cross-correlation graphic pyramid matching algorithm) to form a spring movement and displacement time curve. Four characteristic frames are defined for spring deformation: deformation start, maximum velocity, maximum deformation, and oscillation end. Secondly, according to the characteristic frame timing of the image sequence, the operation process is accurately divided into four stages: tripping, energy storage release, closing buffer, and oscillation braking. Each stage highlights the changing characteristics of signals, reflecting the correlation between the signal and the actual physical energy transfer state. Finally, vibration signals of different stages are mapped to a high-dimensional phase space. The recurrence plot (RP) reflecting the changing characteristics of the dynamic system is obtained through recursive analysis. In addition, the RQA feature sequence is obtained through recursive quantitative analysis (RQA), allowing for an accurate depiction of the relationship among spring discharge, vibration events, and component motion.
Taking a ZN65-12 high-voltage circuit breaker as the research object, a fault simulation experiment platform is built, and the support vector machine model is used to analyze and identify vibration characteristic samples under normal and fault conditions. The experimental results show that the timing of spring energy release refines vibration signals. Feature analysis effectively improves the accuracy of circuit breaker status identification. High-speed image and vibration signal capture are both non-invasive measurement methods. With accumulating experimental data and further algorithm improvement, it is expected to find applications in circuit breaker fault monitoring and live testing.

Key words： High voltage circuit breaker action period vibration signal recursive quantitative analysis status identification

Received: 21 February 2023

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TM561

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	Liu Huilan
	Chang Gengyao
	Zhao Shutao
	Fu Lei
	Liu Jiaomin

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Liu Huilan,Chang Gengyao,Zhao Shutao等. Circuit Breaker State Identification Method Based on Tracing Spring Deformation Process and Recurrence Quantitative Analysis of Vibration Signals[J]. Transactions of China Electrotechnical Society, 2024, 39(8): 2567-2577.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.230201 OR https://dgjsxb.ces-transaction.com/EN/Y2024/V39/I8/2567

[1] 豆龙江, 何玉灵, 万书亭, 等. 基于振动信号的高压断路器弹簧疲劳程度检测方法[J]. 电工技术学报, 2022, 37(24): 6420-6430.
Dou Longjiang, He Yuling, Wan Shuting, et al.Detecting method of high voltage circuit breaker spring fatigue based on vibration signal[J]. Transa- ctions of China Electrotechnical Society, 2022, 37(24): 6420-6430.
[2] 杨秋玉, 王栋, 阮江军, 等. 基于振动信号的断路器机械零部件故障程度识别[J]. 电工技术学报, 2021, 36(13): 2880-2892.
Yang Qiuyu, Wang Dong, Ruan Jiangjun, et al.Fault severity estimation method for mechanical parts in circuit breakers based on vibration analysis[J]. Transactions of China Electrotechnical Society, 2021, 36(13): 2880-2892.
[3] 赵书涛, 许文杰, 刘会兰, 等. 基于振动信号谱形状熵特征的高压断路器操动状态辨识方法[J]. 电工技术学报, 2022, 37(9): 2170-2178.
Zhao Shutao, Xu Wenjie, Liu Huilan, et al.Identification method for operation state of high voltage circuit breakers based on spectral shape entropy characteristics of vibration signals[J]. Transa- ctions of China Electrotechnical Society, 2022, 37(9): 2170-2178.
[4] 游颖敏, 王景芹, 舒亮, 等. 断路器保护特性测试电流的自适应控制策略[J]. 电工技术学报, 2020, 35(15): 3203-3213.
You Yingmin, Wang Jingqin, Shu Liang, et al.Research on adaptive current control method in circuit breaker protection characteristic test[J]. Transactions of China Electrotechnical Society, 2020, 35(15): 3203-3213.
[5] Sun Yihang, Wu Jianwen, Shi Yanhua, et al.Design of intelligent integrated controller of circuit breaker based on dual-core CPU[C]//2011 1st International Conference on Electric Power Equipment - Switching Technology, Xi'an, China, 2012: 315-318.
[6] 刘会兰, 许文杰, 赵书涛, 等. 面向高压断路器故障分类的电流-振动信号类聚几何敏感特征优选方法[J]. 电工技术学报, 2023, 38(1): 26-36.
Liu Huilan, Xu Wenjie, Zhao Shutao, et al.Opti- mization method of clustering geometric sensitive features of current vibration signals for fault classification of high voltage circuit breakers[J]. Transactions of China Electrotechnical Society, 2023, 38(1): 26-36.
[7] 刘晓明, 张煦松, 姜文涛, 等. 基于混沌吸引子的真空断路器永磁斥力机构机械故障识别方法[J]. 电工技术学报, 2022, 37(20): 5334-5346.
Liu Xiaoming, Zhang Xusong, Jiang Wentao, et al.A method of mechanical fault identification of per- manent magnet repulsion mechanism of vacuum circuit breaker based on chaos attractor[J]. Transa- ctions of China Electrotechnical Society, 2022, 37(20): 5334-5346.
[8] 孙曙光, 张强, 杜太行, 等. 基于振动信号的低压万能式断路器分合闸故障程度评估方法的研究[J]. 中国电机工程学报, 2017, 37(18): 5473-5482, 5547.
Sun Shuguang, Zhang Qiang, Du Taihang, et al.Study of evaluation method for low voltage conventional circuit breaker switching fault degree based on vibration signal[J]. Proceedings of the CSEE, 2017, 37(18): 5473-5482, 5547.
[9] 郭博文, 李楠, 李松原, 等. 断路器弹簧操动机构分/合闸弹簧的状态诊断[J]. 电气技术, 2021, 22(12): 57-62.
Guo Bowen, Li Nan, Li Songyuan, et al.State diagnosis for closing/opening spring in the spring operating mechanism of circuit breaker[J]. Electrical Engineering, 2021, 22(12): 57-62.
[10] 刘会兰, 许文杰, 赵书涛, 等. 基于振动信号时间历程和自适应谱融合的断路器操动机构状态辨识方法[J]. 高电压技术, 2023, 49(5): 1860-1869.
Liu Huilan, Xu Wenjie, Zhao Shutao, et al.State identification method of circuit breaker operating mechanism based on time course waveform and adaptive spectrum fusion analysis of vibration signal[J]. High Voltage Engineering, 2023, 49(5): 1860-1869.
[11] 朱洪伟, 康晓勇, 张家瑞, 等. 一种断路器缺陷零部件的诊断方法[J]. 高压电器, 2023, 59(3): 22-27.
Zhu Hongwei, Kang Xiaoyong, Zhang Jiarui, et al.Diagnostic method for defective parts of circuit breakers[J]. High Voltage Apparatus, 2023, 59(3): 22-27.
[12] 王展, 杜思远, 贺文治, 等. 基于全相位快速傅里叶变换的主轴不平衡特征提取及实验[J]. 仪器仪表学报, 2020, 41(4): 138-146.
Wang Zhan, Du Siyuan, He Wenzhi, et al.Unbalanced feature extraction and experiment of spindle based on the all phase fast Fourier transform method[J]. Chinese Journal of Scientific Instrument, 2020, 41(4): 138-146.
[13] 赵洋, 曾庆军, 严金城. 采用功率谱估计法的真空断路器振动分析[J]. 电气应用, 2009, 28(9): 62-65.
Zhao Yang, Zeng Qingjun, Yan Jincheng.Vibration analysis of vacuum circuit breaker using power spectrum estimation method[J]. Electrotechnical Application, 2009, 28(9): 62-65.
[14] 杨青乐, 梅检民, 肖静, 等. Teager能量算子增强倒阶次谱提取轴承微弱故障特征[J]. 振动与冲击, 2015, 34(6): 1-5.
Yang Qingle, Mei Jianmin, Xiao Jing, et al.Weak fault feature extraction for bearings based on an order cepstrum enhanced with Teager energy operator[J]. Journal of Vibration and Shock, 2015, 34(6): 1-5.
[15] Ren Weixin, Sun Zengshou.Structural damage identi- fication by using wavelet entropy[J]. Engineering Structures, 2008, 30(10): 2840-2849.
[16] 孙一航, 武建文, 廉世军, 等. 结合经验模态分解能量总量法的断路器振动信号特征向量提取[J]. 电工技术学报, 2014, 29(3): 228-236.
Sun Yihang, Wu Jianwen, Lian Shijun, et al.Extraction of vibration signal feature vector of circuit breaker based on empirical mode decomposition amount of energy[J]. Transactions of China Electro- technical Society, 2014, 29(3): 228-236.
[17] 黄南天, 陈怀金, 林琳, 等. 基于S变换和极限学习机的高压断路器机械故障诊断[J]. 高压电器, 2018, 54(6): 74-80.
Huang Nantian, Chen Huaijin, Lin Lin, et al.Mecha- nical fault diagnosis of high voltage circuit breakers based on S-transform and extreme learning machine[J]. High Voltage Apparatus, 2018, 54(6): 74-80.
[18] 陈欣昌, 冯玎, 林圣. 基于深度自编码网络的高压断路器操作机构机械故障诊断方法[J]. 高电压技术, 2020, 46(9): 3080-3088.
Chen Xinchang, Feng Ding, Lin Sheng.Mechanical fault diagnosis method of high voltage circuit breaker operating mechanism based on deep auto-encoder network[J]. High Voltage Engineering, 2020, 46(9): 3080-3088.
[19] 王静君, 王飞, 杨元威, 等. 短时能量法在断路器机械振动信号分析中的应用[J]. 高压电器, 2017, 53(12): 14-19.
Wang Jingjun, Wang Fei, Yang Yuanwei, et al.Appli- cation of short-time energy method in the analysis of mechanical vibration signal of circuit breaker[J]. High Voltage Apparatus, 2017, 53(12): 14-19.
[20] 孟永鹏, 贾申利, 荣命哲. 短时能量分析法在断路器机械状态监测中的应用[J]. 西安交通大学学报, 2004, 38(12): 1301-1305.
Meng Yongpeng, Jia Shenli, Rong Mingzhe.Appli- cation of short-time energy analysis in condition monitoring of circuit breakers[J]. Journal of Xi'an Jiaotong University, 2004, 38(12): 1301-1305.
[21] 万书亭, 马晓棣, 陈磊, 等. 基于振动信号短时能熵比与DTW的高压断路器状态评估及故障诊断[J]. 高电压技术, 2020, 46(12): 4249-4257.
Wan Shuting, Ma Xiaodi, Chen Lei, et al.State evaluation and fault diagnosis of high-voltage circuit breaker based on short-time energy entropy ratio of vibration signal and DTW[J]. High Voltage Engin- eering, 2020, 46(12): 4249-4257.
[22] Eckmann J P, Kamphorst S O, Ruelle D.Recurrence plots of dynamical systems[J]. Europhysics Letters, 1987, 4(9): 973-977.
[23] 孟庆芳, 陈珊珊, 陈月辉, 等. 基于递归量化分析与支持向量机的癫痫脑电自动检测方法[J]. 物理学报, 2014, 63(5): 88-95.
Meng Qingfang, Chen Shanshan, Chen Yuehui, et al.Automatic detection of epileptic EEG based on recurrence quantification analysis and SVM[J]. Acta Physica Sinica, 2014, 63(5): 88-95.
[24] Webber C L Jr, Zbilut J P. Dynamical assessment of physiological systems and states using recurrence plot strategies[J]. Journal of Applied Physiology, 1994, 76(2): 965-973.
[25] 赵书涛, 王科登, 闫筱, 等. 基于识别区域估计优化NCC-P算法的断路器储能弹簧形变特性研究[J]. 中国电机工程学报, 2019, 39(24): 7413-7420, 7514.
Zhao Shutao, Wang Kedeng, Yan Xiao, et al.Circuit breaker energy storage spring deformation characte- ristics test method based on identification region estimation and optimization of NCC-P algorithm[J]. Proceedings of the CSEE, 2019, 39(24): 7413-7420, 7514.
[26] Sen U, Gangopadhyay T, Bhattacharya C, et al.Dynamic characterization of a ducted inverse diffusion flame using recurrence analysis[J]. Com- bustion Science and Technology, 2018, 190(1): 32-56.
[27] Cao Liangyue.Practical method for determining the minimum embedding dimension of a scalar time series[J]. Physica D: Nonlinear Phenomena, 1997, 110(1/2): 43-50.
[28] Marwan N, Carmen Romano M, Thiel M, et al.Recurrence plots for the analysis of complex systems[J]. Physics Reports, 2007, 438(5/6): 237-329.
[29] 杨秋玉, 阮江军, 张灿, 等. 基于定量递归分析的高压断路器机械缺陷辨识及应用[J]. 电工技术学报, 2020, 35(18): 3848-3859.
Yang Qiuyu, Ruan Jiangjun, Zhang Can, et al.Study and application of mechanical defect identification for high-voltage circuit breakers using recurrence quantification analysis[J]. Transactions of China Electrotechnical Society, 2020, 35(18): 3848-3859.
[30] 刘春玲, 王旭. 基于定量递归分析(RQA)方法的肌电信号处理[J]. 计算机工程与应用, 2007, 43(1): 204-205.
Liu Chunling, Wang Xu.Surface electromyography processing based on recurrence quantification analysis[J]. Computer Engineering and Applications, 2007, 43(1): 204-205.
[31] 豆龙江. 断路器弹簧操作机构故障机理分析及诊断方法研究[D]. 北京: 华北电力大学, 2019.