基于物理化学检测技术的开关柜潜伏性故障检测方法
2022,30(9):54-59
摘要：针对一些历史开关柜潜伏性故障诊断方法检测精度较低的问题,该研究设计了一种新型开关柜故障诊断系统,采用一种物理化学监测技术,通过分析六氟化硫(SF6)分解产物来检测开关柜故障原因,利用离子迁移法分析环境中的SF6离子,进而掌握变电站开关柜中气体情况,通过差分能量检测算法对检测数据进行分析,计算出气体泄漏对变电站关柜的影响,制定出最优SF6填充范围,为开关柜安全运行提供帮助。仿真结果表明,该研究检测数据平均精度高,最高精度为92.5%,体现出该研究基于SF6气体分解物理化学检测方法的优越性。
关键词：物理化学检测技术;开关柜;故障诊断;六氟化硫;差分能量检测算法
Latent Fault Diagnosis Method of Switchgear based on Physicochemical Detection Technology
Abstract：In view of the low detection accuracy of some historical switchgear latent fault diagnosis methods, a new switchgear fault diagnosis system is designed in this study. A physicochemical monitoring technology is used to detect the cause of switchgear fault by analyzing the decomposition products of sulfur hexafluoride (SF6), and the ion migration method is used to analyze the SF6 ion in the environment, Then master the gas situation in the switchgear of the substation, analyze the detection data through the differential energy detection algorithm, calculate the impact of gas leakage on the switchgear of the substation, and formulate the optimal SF6 filling range, so as to provide help for the safe operation of the switchgear. The simulation results show that the average accuracy of the detection data is high, and the maximum accuracy is 92.5%, which reflects the superiority of the physical and chemical detection method based on SF6 gas decomposition.
Key words：Physicochemical detection technology; Switch cabinet; Fault diagnosis; Sulfur hexafluoride; Differential energy detection algorithm
收稿日期：2022-03-01
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