Intelligent Diagnosis Technology of Mechanical Defects of High Voltage Disconnector
Peng Shiyi1, Liu Yan1, Zhou Taotao2, Ruan Jiangjun2, Liu Yuan3
1. State Grid Jiangxi Electric Power Research Institute Nanchang 330096 China; 2. School of Electrical Engineering and Automation Wuhan University Wuhan 430072 China; 3. State Grid Jiangxi Construction Company Nanchang 330000 China
Abstract As high voltage equipment with the largest number and most failures, disconnector still judged by the backward traditional maintenance methods. This paper aims to propose a convenient and reliable fault diagnosis method for disconnector. Based on the consistent results of rigid-flexible coupling dynamic simulation and torque detection experiment, the driving torque is proved closely related to the states of disconnector, and three characteristics extracted from the driving torque wave was chosen as the input of the neural network model, which can identify four typical status of disconnector intelligently. And the neural network model was optimized to output more information about its degree, which can provide more useful reference for the fault diagnosis of disconnector.
Peng Shiyi,Liu Yan,Zhou Taotao等. Intelligent Diagnosis Technology of Mechanical Defects of High Voltage Disconnector[J]. Transactions of China Electrotechnical Society, 2021, 36(7): 1356-1367.
[1] 国家电网有限公司设备管理部. 构建基于“大云物移智”等现代信息通信技术的智能运检体系[J]. 电力设备管理, 2019(4): 26-27. Equipment management department of State Grid Corporation of China. Intelligent operation and inspection system based on modern information and communication technology such as "big-cloud-thing-moving-intelligence"[J]. Electric Power Equipment Management, 2019(4): 26-27. [2] 董洪达, 冯世涛, 黄涛, 等. 高压隔离开关典型机械故障与检测方法分析[J]. 电工技术, 2018(7): 36-38, 42. Dong Hongda, Feng Shitao, Huang Tao.Analysis of detection methods and typical mechanical faults of high voltage disconnectors[J]. Electric Engineering, 2018(7): 36-38, 42. [3] 马宏明, 周涛涛, 彭诗怡, 等. GW4隔离开关机械故障仿真与诊断技术[J]. 电工技术学报, 2019, 34(增刊2): 501-508. Ma Hongming, Zhou Taotao, Peng Shiyi, et al.Research on mechanical fault simulation and diagnosis technology of GW4 disconnector[J]. Transactions of China Electrotechnical Society, 2019, 34(S2): 501-508. [4] 姜才海. 高压隔离开关设备完善化设计与改进[D].北京: 华北电力大学, 2015. [5] 储燎原. 高压隔离开关若干关键部件腐蚀与防护试验研究[D]. 杭州: 浙江大学, 2017. [6] 国家能源局. 隔离开关及接地开关状态评价导则: DL/T1701-2017[S]. 北京: 中国电力出版社, 2018. [7] 王黎明, 何建明. 电动隔离开关机械故障状态监测的设想[J]. 浙江电力, 2006, 25(3): 56-59. Wang Liming, He Jianming.Mechanical fault monitoring of electrical driving disconnector[J]. Zhejiang Electric Power, 2006, 25(3): 56-59. [8] 马宏明, 周涛涛, 彭诗怡, 等. 基于操作杆转角信号的隔离开关机械故障诊断技术研究[J]. 高压电器, 2018, 54(8): 33-39, 47. Ma Hongming, Zhou Taotao, Peng Shiyi,et al.Research on mechanical fault diagnosis technology of disconnector based on operation corner angle signal[J]. High Voltage Apparatus, 2018, 54(8): 33-39, 47. [9] 李少华, 张文涛, 宋亚凯, 等. 基于高压隔离开关振动信号的故障诊断方法分析[J]. 内蒙古电力技术, 2018, 36(1): 89-92. Li Shaohua, Zhang Wentao, Song Yakai, et al.Analysis of fault diagnosis method based on vibration signal of high-voltage disconnector[J]. Inner Mongolia Electric Power, 2018, 36(1): 89-92. [10] 张一茗, 李少华, 陈士刚, 等. 基于ReliefF特征量优化及BP神经网络识别的高压隔离开关故障类型与位置诊断方法[J]. 高压电器, 2018, 54(2): 12-19. Zhang Yiming, Li Shaohua, Chen Shigang, et al.Fault type and position diagnosis method of high-voltage disconnectors based on ReliefF characteristic quantity optimization and BP neural network recognition[J]. High Voltage Apparatus, 2018, 54(2): 12-19. [11] Jia Yongyong, Wu Bang, Sun Shanyuan, et al.Research of the vibration characteristics in GIS disconnector under different contact state[C]//2018 IEEE International Conference on High Voltage Engineering and Application (ICHVE), ATHENS, Greece, 2018: 1-4. [12] Bian Chao, Zhou Yuqi, Guan Weimin, et al.Study on the closing state of high voltage disconnectors based on the modal analysis[C]//2017 20th International Conference on Electrical Machines and Systems (ICEMS), Sydney, NSW, Australia, 2017: 1-5. [13] 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. [14] 孙曙光, 李勤, 杜太行, 等. 基于一维卷积神经网络的低压万能式断路器附件故障诊断[J]. 电工技术学报, 2020, 35(12): 2562-2573. Sun Shuguang, Li Qin, Du Taihang, et al.Fault diagnosis of accessories for the low voltage conventional circuit breaker based on one-dimensional convolutional neural network[J]. Transactions of China Electrotechnical Society, 2020, 35(12): 2562-2573. [15] 杨秋玉, 阮江军, 黄道春, 等. 基于VMD-Hilbert边际谱能量熵和SVM的高压断路器机械故障诊断[J]. 电机与控制学报, 2020, 24(3): 11-19. Yang Qiuyu, Ruan Jiangjun, Huang Daochun, et al.Mechanical fault diagnosis for high voltage circuit breakers based on VMD-Hilbert marginal spectrum energy entropy and SVM[J]. Electric Machines and Control, 2020, 24(3): 11-19. [16] 张丽萍, 石敦义, 缪希仁. 低压断路器振动特性分析及其故障诊断研究[J]. 电机与控制学报, 2016, 20(10): 82. Zhang Liping, Shi Dunyi, Miao Xiren.Research on vibration signal feature analysis and its fault diagnosis[J]. Electric Machines and Control, 2016, 20(10): 82. [17] 陈士刚, 关永刚, 张小青, 等. 不完备故障类别下基于Multi-SVDD的高压隔离开关故障诊断方法[J]. 电工技术学报, 2018, 33(11): 2439-2447. Chen Shigang, Guan Yonggang, Zhang Xiaoqing, et al.Diagnosis method of high voltage isolating switch fault based on Multi-SVDD under incomplete fault type[J]. Transactions of China Electrotechnical Society, 2018, 33(11): 2439-2447. [18] 刘贤杰, 高世伟, 胡曙明. 防止高压电动隔离开关支柱绝缘子断裂措施新探[J]. 山西电力, 2013(3): 59-61. Liu Xianjie, Gao Shiwei, Hu Shuming.New measures to avoid the fracture of high voltage post insulator of electric isolating switch[J]. Shanxi Electric Power, 2013(3): 59-61. [19] 邱志斌, 阮江军, 黄道春, 等. 高压隔离开关机械故障分析及诊断技术综述[J]. 高压电器, 2015, 51(8): 171-179. Qiu Zhibin, Ruan Jiangjun, Huang Daochun, et al.Mechanical faults analysis of high voltage disconnectors and review of diagnosis technology[J]. High Voltage Apparatus, 2015, 51(8): 171-179. [20] Qiu Zhibin, Ruan Jiangjun, Huang Daochun, et al.Mechanical fault diagnosis of high voltage outdoor disconnector based on motor current signal analysis[C]//2014 International Conference on Power System Technology, Chengdu, 2014: 1193-1198. [21] 黄聿琛, 阮江军, 邱志斌, 等. 隔离开关操动机构电机输出轴扭矩和电流关系的研究[J]. 高压电器, 2015, 51(6): 139-144. Huang Yuchen, Ruan Jiangjun, Qiu Zhibin, et al.Study on the relationship between motor output shaft torque and motor current of disconnector operation mechanism[J]. High Voltage Apparatus, 2015, 51(6): 139-144. [22] Peng Tao, Lü Chaohui, Du Yi, et al.Mechanical fault diagnosis of high voltage disconnector based on motor current detection[C]//2019 IEEE 3rd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC), Chengdu, China: 1726-1729. [23] 杨文英, 刘兰香, 刘洋, 等. 考虑碰撞弹跳的接触器动力学模型建立及其弹跳特性影响因素分析[J]. 电工技术学报, 2019, 34(9): 1900-1911. Yang Wenying, Liu Lanxiang, Liu Yang, et al.Establishing of contactor dynamic model considering collision bounce and analysis of influencing factors of bounce characteristics[J]. Transactions of China Electrotechnical Society, 2019, 34(9): 1900-1911. [24] 王栋. 隔离开关智能测试装置的设计[D]. 上海: 上海交通大学, 2014. [25] 刘春来, 周涛涛, 马宏明, 等. 基于力矩与转角检测的GW4-126型隔离开关典型机械故障诊断[J]. 高压电器, 2020, 56(2): 232-239. Liu Chunlai, Zhou Taotao, Ma Hongming, et al.Typical mechanical fault diagnosis of GW4-126 disconnector based on torque and angle detection[J]. High Voltage Apparatus, 2020, 56(2): 232-239. [26] 赵科, 杨景刚, 马速良, 等. 基于神经网络集成模型在高压断路器机械故障诊断中的应用[J]. 高压电器, 2018, 54(7): 217-223. Zhao Ke, Yang Jinggang, Ma Suliang, et al.Application of neural network ensemble model in mechanical fault identification of high voltage circuit breaker[J]. High Voltage Apparatus, 2018, 54(7): 217-223. [27] 程学珍, 朱晓林, 杜彦镔, 等. 基于神经模糊Petri网的高压断路器故障诊断研究[J]. 电工技术学报, 2018, 33(11): 2535-2544. Cheng Xuezhen, Zhu Xiaolin, Du Yanbin, et al.High voltage circuit breaker fault diagnosis based on neural fuzzy Petri nets[J]. Transactions of China Electrotechnical Society, 2018, 33(11): 2535-2544. [28] 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.
2021, Vol. 36 
