摘要
高压断路器的操动机构是保障断路器可靠动作的关键部件,准确判断操动机构状态至关重要。提出了基于图像、振动、声音的非侵入式多信息检测方法,对提取的图像特征向量(分闸时间、合闸时间、分闸速度、合闸速度、分闸行程、合闸行程)、振动特征向量(特征时间点、等能量5分段能量熵)、声音特征向量(特征时间点、等能量5分段能量熵)和操动机构状态(正常、基座松动、转轴卡涩、缓冲器性能下降、拐臂润滑不足)进行了多重对应分析,找到了机构状态和相应特征向量的关联关系。提出了基于机构状态和相应特征向量关联关系的分级诊断策略,经实验室故障模拟及诊断,基座松动故障、转轴卡涩故障、缓冲器性能下降故障的联合特征诊断较单一信号诊断正确率分别提升至90%、80%、90%,拐臂润滑不足故障的联合特征诊断准确率较单一信号诊断没有明显的提高。经现场实测及设备解体分析,证明了方法的通用有效性。
The operating mechanism of high voltage circuit breaker is the key part to ensure reliable operation of circuit breaker,and accurate judgement of the operating mechanism status is of great importance.A non-intrusive multi-information detection method based on image,vibration and sound is proposed,the multiple correspondence analysis of the extracted image feature vectors(opening time,closed time,opening speed,closed speed,opening stroke,closed stroke),vibration feature vectors(feature time points,equal energy 5-subsection energy entropy),sound feature vectors(feature time points,equal energy 5-subsection energy entropy)and status of the operating mechanism(normal,pedestal looseness,shaft jam,performance degradation of the buffer and insufficient lubrication of the lever)are analyzed,and the relationship between the state of the mechanism and the corresponding eigenvectors has been found.A hierarchical diagnosis strategy based on the relationship between the status of the mechanism and the corresponding eigenvectors is proposed.Throughout fault simulation and diagnosis of the experimental laboratory,the correct rate of the joint feature diagnosis of the fault of pedestal looseness,shaft jam and buffer performance degradation,compared to single signal diagnosis,is improved to 90%,80%and 90%respectively.The the accurate rate of the joint feature diagnosis of insufficient lubrication of lever,compared to the single signal diagnosis,is not improved obviously.The general effectiveness of the method is proved through the actual measurement at site and disassembly analysis of the equipment.
作者
李建鹏
赵冀宁
孟延辉
赵智龙
赵书涛
邹园
刘晓飞
LI Jianpeng;ZHAO Jining;MENG Yanhui;ZHAO Zhilong;ZHAO Shutao;ZOU Yuan;LIU Xiaofei(State Grid Hebei Extra High Voltage Company,Shijiazhuang 050070,China;North China Electric Power University,Hebei Baoding 071003,China;State Grid Hebei Training Center,Shijiazhuang 050031,China)
出处
《高压电器》
CAS
CSCD
北大核心
2024年第7期128-137,共10页
High Voltage Apparatus
关键词
操动机构
图像
振动
声音
多重对应分析
分级诊断
operating mechanism
image
vibration
sound
multiple correspondence analysis
grading diagnosis
作者简介
李建鹏(1985-),男,硕士,高级工程师,研究方向为电气设备在线监测与故障诊断(E-mail:lijianpeng0311@126.com)。
