| The inverse power law presented by the applied electric field and the failure time is an important means to evaluate the electrical life of high-voltage DC cables and their insulating materials.Inverse power model(Inverse power model,IPM)parameters voltage tolerance index n and cumulative damage C are also important basis for guiding the thickness design of power cables and related testing.The traditional inverse power model is widely used in the engineering practice of cable insulation design due to its simple structure and fewer parameters.However,with the advancement of power cable manufacturing technology and maintenance level,the traditional life assessment method has encountered new challenges: it is difficult to obtain failure data in a short period of time for most long-life products,and there will be no failure data during the experiment time.Therefore,based on the introduction of the space charge accumulation effect,the performance degradation of characteristic quantities is considered as a variable factor to study the parameters of the existing improved electrical life model,which has certain reference value for engineering applications and theoretical research.The traditional inverse power model is difficult to accurately evaluate the life information of HVDC cables.In addition,the traditional life assessment requires the test to obtain the failure data of the sample,and it is difficult to obtain the failure data in the short-term test.The characteristic of the performance degradation model is that it is not necessary to obtain the failure data in the test.and taking into account the problem that the traditional life model is difficult to obtain the failure data,this article borrowed the change of the performance characteristic quantity that can characterize the failure mechanism of the product to push the failure data of the product,the statistical probability model was linked with the physical failure model trough the theoretical introduction of the performance degradation model,the research on the selection conditions of performance characteristic quantities and the analysis of how to use the performance degradation modeling analysis,and the failure mechanism of the product can be explained more accurately through the change of the performance characteristic quantity.There is no need to obtain failure data using the performance degradation model,which can greatly reduce the test time.In this paper,based on the influence of space charge accumulation effect on cable insulation failure in HVDC cables,the theory of its influence was studied.The effect of space charge accumulation which is an important factor inducing the insulation failure of the insulation material caused a complex failure principle to occur inside the insulation.In this experiment,the cross-linked polyethylene material sample model LS4258 DCE was used considering the influence of space charge effect.And through the research on the migration,accumulation and dissipation of the space charge inside the insulation,the pre-experimental treatment was carried out to clarify the performance degradation amount in this experiment-the selection of the average space charge density.With the aid of performance degradation model analysis,the characteristic quantity of average space charge density was selected to characterize the physical degradation characteristics of HVDC cables and use the method of performance degradation to derive the failure data of the cable material sample,then set up the traditional constant stress accelerated life test to solve the same kind of material electrical life model parameters of the control test.By comparing with the results of the traditional constant stress accelerated life test,the voltage withstand index n=13.015 and the cumulative damage value C=6.124 obtained by the performance degradation modeling analysis method in this paper,and the error of the parameters obtained with the traditional method is 6.724% and 8.813%,which meets the requirements of engineering application and verifies the effectiveness of the method. |
