Fault Severity Estimation Method for Mechanical Parts in Circuit Breakers Based on Vibration Analysis
Yang Qiuyu1, Wang Dong2, Ruan Jiangjun3, Zhai Pengfei4
1. School of Electronic, Electrical Engineering and Physics Fujian University of Technology Fuzhou 350118 China; 2. Electric Power Research Institute of State Grid Henan Electric Power Company Zhengzhou 450052 China; 3. School of Electrical Engineering and Automation Wuhan University Wuhan 430072 China; 4. CEE Power Co. Ltd Fuzhou 350002 China
Abstract：How to effectively identify the fault severity for mechanical parts in high-voltage (HV) circuit breakers (CBs) is an unsolved issue so far. To address this issue, this paper proposes a fault severity identification method using morphological characteristics of chaotic attractor of CB vibration signal. First, in order to accurately extract the weak fault features for the early fault mechanical parts, the vibration signals are firstly divided into several sub-signals according to the CB's operation sequence. Then we propose an adaptive signal decomposition method for separating the mode components from the divided sub-signals. Finally, the chaotic attractor of the mode component is reconstructed and the fault severity of mechanical part is diagnosed by the morphological characteristics of the attractor. The experimental results of two different types of CBs show that the chaotic attractor is highly sensitive to the severity of fault, and that the shape of the attractors in normal and faulty states is significantly different. The shape of the attractor varies with the aggravation of the fault severity. This method could provide a new way to identify the fault severity for mechanical parts in HVCB.
杨秋玉, 王栋, 阮江军, 翟鹏飞. 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, Zhai Pengfei. Fault Severity Estimation Method for Mechanical Parts in Circuit Breakers Based on Vibration Analysis. Transactions of China Electrotechnical Society, 2021, 36(13): 2880-2892.
[1] CIGRE Working Group A3.06. Final report of the2004-2007 international enquiry on reliability of high voltage equipment, Part 2 - Reliability of high voltage SF6 circuit-breakers. CIGRE Technical Brochure 510, 2012. [2] 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. [3] Janssen A, Makareinis D, Solver C E.International surveys on circuit breaker reliability data for substation and system studies[J]. IEEE Transactions on Power Delivery, 2014, 29(2): 808-814. [4] Lai M L, Park S Y, Lin C C, et al.Mechanical failure detection of circuit breakers[J]. IEEE Transactions on Power Delivery, 1988, 3(4): 1724-1731. [5] Landry M, Leonard F, Landry C, et al.An improved vibration analysis algorithm as a diagnostic tool for detecting mechanical anomalies on power circuit breakers[J]. IEEE Transactions on Power Delivery, 2008, 23(4): 1986-1994. [6] 万书亭, 豆龙江, 李聪, 等. 基于振动信号的高压断路器合闸特性参数在线检测方法研究[J]. 振动工程学报, 2019, 32(2): 359-367. Wan Shuting, Dou Longjiang, Li Cong, et al.Study on on-line detection of high voltage circuit breaker closing characteristic parameters based on vibration signal[J]. Journal of Vibration Engineering, 2019, 32(2): 359-367. [7] 黄南天, 王斌, 蔡国伟, 等. 基于Tsallis熵与层次化混合分类器的含未知故障断路器机械故障诊断[J]. 高电压技术, 2019, 45(5): 1518-1525. Huang Nantian, Wang Bin, Cai Guowei, et al.Mechanical fault diagnosis containing unknown fault of high voltage circuit breaker based on Tsallis entropy and hybrid classifier[J]. High Voltage Engineering, 2019, 45(5): 1518-1525. [8] 杨秋玉, 阮江军, 黄道春, 等. 基于振动信号时频图像识别的高压断路器分闸缓冲器状态评估[J]. 电工技术学报, 2019, 34(19): 4048-4057. Yang Qiuyu, Ruan Jiangjun, Huang Daochun, et al.Opening damper condition evaluation based on vibration time-frequency images for high-voltage circuit breakers[J]. Transactions of China Electrotechnical Society, 2019, 34(19): 4048-4057. [9] 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. [10] Yang Qiuyu, Ruan Jiangjun, Zhuang Zhijian, et al.Fault diagnosis of circuit breakers based on time-frequency and chaotic vibration analysis[J]. IET Generation, Transmission & Distribution, 2020, 14(7): 1214-1221. [11] 赵书涛, 马莉, 朱继鹏, 等. 基于CEEMDAN样本熵与FWA-SVM的高压断路器机械故障诊断[J]. 电力自动化设备, 2020, 40(3): 181-186. Zhao Shutao, Ma Li, Zhu Jipeng, et al.Mechanical fault diagnosis of high voltage circuit breaker based on CEEMDAN sample entropy and FWA-SVM[J]. Electric Power Automation Equipment, 2020, 40(3): 181-186. [12] 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. [13] 程序, 关永刚, 张文鹏, 等. 基于因子分析和支持向量机算法的高压断路器机械故障诊断方法[J]. 电工技术学报, 2014, 29(7): 209-215. Cheng Xu, Guan Yonggang, Zhang Wenpeng, et al.Diagnosis method on the mechanical failure of high voltage circuit breakers based on factor analysis and SVM[J]. Transactions of China Electrotechnical Society, 2014, 29(7): 209-215. [14] 李德阁, 武建文, 马速良, 等. 基于行程信息的断路器弹簧故障程度诊断[J]. 高压电器, 2018, 54(4): 20-27. Li Dege, Wu Jianwen, Ma Suliang, et al.Fault degree diagnosis of circuit breaker spring based on travel signal[J]. High Voltage Apparatus, 2018, 54(4): 20-27. [15] 孙曙光, 张强, 杜太行, 等. 基于分合闸线圈电流的万能式断路器故障诊断[J]. 仪器仪表学报, 2018, 39(2): 130-140. Sun Shuguang, Zhang Qiang, Du Taihang, et al.Fault diagnosis for conventional circuit breaker based on switching coil current[J]. Chinese Journal of Scientific Instrument, 2018, 39(2): 130-140. [16] 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. [17] 阮江军, 杨秋玉, 黄道春, 等. 高压断路器机械振动信号混沌吸引子形态特性[J]. 电力自动化设备, 2020, 40(3): 187-193. Ruan Jiangjun, Yang Qiuyu, Huang Daochun, et al.Shape characteristic analysis of chaotic attractor for mechanical vibration signal of high-voltage circuit breaker[J]. Electric Power Automation Equipment, 2020, 40(3): 187-193. [18] Huang N E, Shen Z, Long S R, et al.The empirical mode decomposition and Hilbert spectrum for nonlinear and non-stationary time series analysis[J]. Proceedings A, 1998, 454(1971): 903-995. [19] 任宜春, 翁璞. 基于改进Hilbert-Huang变换的结构损伤识别方法研究[J]. 振动与冲击, 2015, 34(18): 195-199. Ren Yichun, Weng Pu.Structural damage detection based on improved Hilbert-Huang transform[J]. Journal of Vibration and Shock, 2015, 34(18): 195-199. [20] Dragomiretskiy K, Zosso D.Variational mode decomposition[J]. IEEE Transactions on Signal Processing, 2014, 62(3): 531-544. [21] 徐元博, 蔡宗琰, 胡永彪, 等. 强噪声背景下频率加权能量算子和变分模态分解在轴承故障提取中的应用[J]. 振动工程学报, 2018, 31(3): 513-522. Xu Yuanbo, Cai Zongyan, Hu Yongbiao, et al.A frequency-weighted energy operator and variational mode decomposition for bearing fault detection[J]. Journal of Vibration Engineering, 2018, 31(3): 513-522. [22] 赵岩, 朱均超, 张宝峰, 等. 基于VMD与Hilbert谱的旋转机械碰摩故障诊断方法[J]. 振动、测试与诊断, 2018, 38(2): 381-425. Zhao Yan, Zhu Yunchao, Zhang Baofeng, et al.Rub-impact fault diagnosis of rotating machinery based on VMD and Hilbert spectrum[J]. Journal of Vibration, Measurement & Diagnosis, 2018, 38(2): 381-425. [23] 孙曙光, 于晗, 杜太行, 等. 基于振动信号样本熵和相关向量机的万能式断路器分合闸故障诊断[J]. 电工技术学报, 2017, 32(7): 20-30. Sun Shuguang, Yu Han, Du Taihang, et al.Diagnosis on the switching fault of conventional circuit breaker based on vibration signal sample entropy and RVM[J]. Transactions of China Electrotechnical Society, 2017, 32(7): 20-30.
2021, Vol. 36 
