Aging Analysis And Residual Life Study Of 10kV XLPE Cable For Mining

The aging of cable insulation layer is a multivariable and nonlinear process,which is difficult to be accurately described by traditional mathematical modeling methods.For cable insulation mechanism and residual life modeling study has important reference meaning for cable fault detection,therefore,aimed at the actual working environment of mine cable,cable insulation accelerated aging test,in reading,on the basis of a large number of related literature at home and abroad,put forward a kind of power cable based on fuzzy logic and neural network residual life prediction model,The specific research work is as follows:Firstly,the aging mechanism of dielectric insulation layer of power cable is analyzed,and various factors affecting the aging of insulation layer are studied.The aging model of mine XLPE cable insulation layer is constructed,and the simulation of mine XLPE cable is carried out by ANSYS software.The electric field intensity and temperature distribution in the cable under four conditions of normal operation,impurity in the insulation,cable defect and insulation aging are simulated.On this basis,the law of cable insulation failure caused by various influencing factors is summarized.Secondly,according to the characteristics of the underground environment and considering the aging time,applied temperature and humidity,a combination of humidity and heat accelerated aging test was carried out on MYJV22 XLPE cable,and the data characterizing the aging index of cable insulation,such as the tangent value of dielectric loss Angle and elongation at break,were obtained.According to the failure criterion that the retention rate of elongation at break is 50%,the remaining life of the cable is extrapolated based on the least square method and the Arrhenius equation.Finally,the framework of life prediction model for mine cables was constructed.Three factors,temperature,aging time and humidity,were taken as the input of the model.Combined with the experimental measured retention rate of elongation at break and tangent of dielectric loss Angle,the prediction model was solved by using the adaptive fuzzy neural network algorithm.The predicted results are compared with the results derived from the Arrhenius extrapolation equation,and the validity of the prediction model is verified.The method in this paper can not only consider the cable life prediction under the synergistic action of multiple factors,but also measure the cable historical data without damaging the cable to make the life prediction.It can be applied to the cable life prediction during the service period.The research results can provide an important reference for the same kind of cable life prediction.