摘要
为了研究受潮状态下油纸绝缘样品的电导与极化特性,并提取能够准确量化油纸绝缘样品受潮程度的特征参量。采用一种新型弛豫响应模型——混合极化电路模型来探究频域介电谱技术在油纸绝缘受潮状态评估中的应用。首先,推导了该模型的频域介电响应函数,并基于FDS实测数据进行模型参数辨识;其次,研究温度和水分含量对模型参数的影响规律,进而提取出3个油纸绝缘受潮状态特征参量——绝缘电阻R_(g)、平均串联极化支路时间常数τ_(p)与平均界面极化支路时间常数τ_(h);最后,实验结果表明,混合极化电路模型能够准确拟合复合绝缘介质的弛豫响应过程,所提取的特征参量与油纸绝缘水分含量存在明显的指数关系,有助于实现电力设备受潮状态的定量评估。
In order to study conductivity and polarization characteristics of oil-paper insulating samples under damp condition,the characteristic parameters which can accurately quantify the degree of damp of oil-paper insulating samples were extracted.A new relaxation response model,the mixed polarization circuit model,was used to explore application of frequency domain dielectric spectroscopy(FDS)in the evaluation of damp status of oil-paper insulation.Firstly,the frequency domain dielectric response function of the model was derived,and the model parameters were identified based on the measured data of FDS.Then,the influences of temperature and moisture content on the model parameters were studied.Then,three characteristic parameters of oil-paper insulation were extracted:insulation resistance R_(g),average series polarization branch time constant τ_(p) and average interface polarization branch time constant τ_(h).Finally,the experimental results show that the mixed polarization circuit model can accurately fit the relaxation response process of the composite insulating medium,and there is an obvious exponential relationship between the extracted characteristic parameters and the moisture content of oil paper insulation,which is helpful for the quantitative evaluation of the moisture status of power equipmen.
作者
邹阳
翁祖辰
金涛
ZOU Yang;WENG Zu-chen;JIN Tao(College of Electrical Engineering and Automation,Fuzhou University,Fuzhou 350108,China)
出处
《电机与控制学报》
EI
CSCD
北大核心
2022年第7期88-97,共10页
Electric Machines and Control
基金
国家自然科学基金(51977039)
福建省自然科学基金(2019J01248)。
关键词
油纸绝缘
混合极化电路模型
频域介电谱
受潮状态
特征参量
定量评估
oil paper insulation
hybrid polarization circuit model
frequency domain dielectric spectrum
damp condition
characteristic parameter
quantitative evaluation