配电网隔离开关松动故障的振动非线性行为判别  

Nonlinear Behavior Discrimination of Vibration for Loose Fault of Isolation Switches in Distribution Networks

作　　者：鲍鹏飞 刘智昌 姚禧 吴江龙 BAO Pengfei;LIU Zhichang;YAO Xi;WU Jianglong(Shenzhen Power Supply Bureau Co.,Ltd.,Shenzhen Guangdong 518000,China)

机构地区：[1]深圳供电局有限公司,广东深圳518000

出　　处：《自动化与仪器仪表》2024年第11期288-292,297,共6页Automation & Instrumentation

基　　金：深圳供电局有限公司高品质供电引领区关键技术研究与示范应用项目(090000KK52220023)。

摘　　要：柔性高压直流配电网发生机械开关松动故障后,MMC的大量子模块电容迅速向故障点放电,故障电流迅速增大,系统电压急剧跌落,影响电网安全。但是相关信号特征会受到变频电流外部激励影响,导致松动行为检测失真。研究发现:隔离开关底座松动缺陷的时,频域振动图谱会出现非线性变化规律。结合这一特征,提出配电网隔离开关松动故障的振动非线性行为判别方法。以配电网常用的GW16型隔离开关为例,采用多重反馈自混合干涉测振技术,在松动状态下采集配电网隔离开关动静触头相对位置、动静触头接触压力、回路电阻、平衡弹簧力值等振动信号;通过EEMD方法分解开关信号,计算IMF分量的包络,在此基础上获得IMF分量的能量熵,将其作为开关松动信号的波形非线性特征;建立极限学习机,将开关松动信号的波形非线性特征输入极限学习机中,实现开关松动故障诊断与检测。实验结果表明,所提方法可采集高精度的开关松动行为振动特征信号,并提取非线性波形特征,具有松动故障诊断精度高、检测精度高的优点。After the mechanical switch looseness fault occurs in the flexible high-voltage DC distribution network,a large number of submodule capacitors of MMC quickly discharge towards the fault point,causing a rapid increase in fault current and a sharp drop in system voltage,affecting the safety of the power grid.However,the relevant signal characteristics will be affected by external excitation of variable frequency current,leading to distortion in loose behavior detection.Research has found that when the base of the isolation switch is loose and defective,the frequency domain vibration spectrum will exhibit nonlinear changes.Based on this feature,a vibration nonlinear behavior discrimination method for loose faults of isolation switches in distribution networks is proposed.Taking the GW16 type isolation switch commonly used in distribution networks as an example,multiple feedback self mixing interference vibration measurement technology is used to collect vibration signals such as the relative position of the dynamic and static contacts,contact pressure of the dynamic and static contacts,circuit resistance,and balance spring force value of the distribution network isolation switch in a loose state;Decompose the switch signal using the EEMD method,calculate the envelope of the IMF component,and based on this,obtain the energy entropy of the IMF component,which is used as the waveform nonlinear feature of the switch loosening signal;Establish an extreme learning machine to input the nonlinear characteristics of the waveform of the switch loosening signal into the machine,and achieve switch loosening fault diagnosis and detection.The experimental results show that the proposed method can collect high-precision vibration characteristic signals of switch looseness behavior and extract nonlinear waveform features,which has the advantages of high looseness fault diagnosis accuracy and detection accuracy.

关 键 词：配电网 机械开关 振动波形特征 非线性 松动故障 极限学习机 

分 类 号：TM732[电气工程—电力系统及自动化] TP206[自动化与计算机技术—检测技术与自动化装置]