基于宏微观参数结合的XLPE电缆水树诊断研究

Water tree diagnosis of XLPE cable based on combination of macro and micro parameters

为解决交联聚乙烯电缆(XLPE)水树密度的预测问题,提出了将老化电缆的宏观检测数据与微观水树形貌相结合的分析方法,同时提出了两种新的参数(碳氧指数、含水指数)来定量描述水树区域的能谱分析(EDS)结果和红外光谱(FTIR)结果的变化。首先通过对不同实验条件下的水树老化电缆进行极化/去极化电流法(PDC)检测,得到电缆的老化因子、直流电导率以及0.1 Hz介质损耗因数等一系列宏观参数,再将电缆切片进行微观观测,得到水树的微观参数,建立水树生长的模型计算电缆的水树密度,对PDC测试得到的电缆的宏观参数与微观水树密度进行相关性分析。结果表明:老化时间越长,碳氧指数和含水指数越大,且增大的速率越快。根据相关系数建立了一种新的预测XLPE电缆内部水树生长密度的数学模型,实现了电缆内部水树的微观结构与宏观测试参数的结合。

In order to solve the prediction problem of water tree density of XLPE cable,an analysis method combining the macro detection data with the micro water tree profile of aged cable was proposed.Two new parameters(carbon and oxygen index and water content index)were proposed to quantitatively describe the changes of EDS and FTIR results in the water tree region.Firstly,the polarization and depolarization current method(PDC)was used to detect the water-tree ageing cables under different experimental conditions.A series of macroscopic parameters such as cable ageing factor,DC conductivity,and 0.1 Hz dielectric loss factor were obtained.Then,the micro parameters of water tree were obtained by microscopic observation of cable slice.The water tree growth model was established to calculate the water tree density of cable,and the correlation between the macroscopic parameters of cable and the microscopic water tree density was analyzed.The results show that the longer the ageing time,the greater the carbon oxygen index and water content index,and the faster the rate of increase.Based on the correlation coefficient,a new mathematical model for predicting the growth density of water tree inside XLPE cable is established,which realize the combination of microstructure of water tree inside cable and macro test parameters.