Pollution flashover accidents occur frequently in railway OCS in saline-alkali areas.To accurately predict the pollution flashover voltage of insulators,a pollution flashover warning should be made in advance.Accordin...Pollution flashover accidents occur frequently in railway OCS in saline-alkali areas.To accurately predict the pollution flashover voltage of insulators,a pollution flashover warning should be made in advance.According to the operating environment of insulators along the Qinghai-Tibet railway,the pollution flashover experiments were designed for the cantilever composite insulator FQBG-25/12.Through the experiments,the flashover voltage under the influence of soluble contaminant density(SCD)of different pollution components,non-soluble deposit density(NSDD),temperature(T),and atmospheric pressure(P)was obtained.On this basis,the GA-BP neural network prediction model was established.P,SCD,NSDD,CaSO_(4) mass fraction(w(CaSO_(4))),and T were taken as input parameters,50%flashover voltage(U_(50%))of the insulator was taken as output parameters.The results showed that the prediction deviation was less than 10%,which meets the basic engineering requirements.The results could not only provide early warning for the anti-pollution flashover work of the railway power supply department,but also be used as an auxiliary contrast to verify the accuracy of the results of the experiments,and provide a theoretical basis for the classification of pollution levels in different regions.展开更多
The prediction accuracy of existing models of the rolling force of a thick plate is always very low.To address this problem,a high-precision genetic algorithm-backpropagation network(GA-BP)model of deformation resista...The prediction accuracy of existing models of the rolling force of a thick plate is always very low.To address this problem,a high-precision genetic algorithm-backpropagation network(GA-BP)model of deformation resistance was built,and its integration with the traditional fitted model was further established.Then,a novel rolling force model was obtained by embedding the integration model of deformation resistance in the original model of rolling force.According to this research idea,the industrial data are normalized at first.On this basis,the interactions among the process parameters were disclosed through the variance analysis,and then described by various virtual factors.These factors are set as part of input parameters.Then,the optimal structure of the GA-BP model of deformation resistance was determined and an integration model of deformation resistance was built.Finally,a novel rolling force model is obtained by substituting the traditional fitted deformation resistance into the Sims model with the integration model of the deformation resistance.The results proves that the introduction of virtual factors can increase the hit rate of±5%from 75.8%to 78%and can reduce the root mean square error from 4.72%to 4.48%.Besides,it is found that the mean relative error of the traditional fitted deformation resistance is 0.142,while that of the modified deformation resistance is only 0.03.In addition,the mean relative error in the original rolling force model is 0.145,while that of the present model is only 0.03.展开更多
基金Supported by the National Natural Science Foundation of China(51767014)the Scientific and Technological Research and Development Program of the China Railway(2017J010-C/2017).
文摘Pollution flashover accidents occur frequently in railway OCS in saline-alkali areas.To accurately predict the pollution flashover voltage of insulators,a pollution flashover warning should be made in advance.According to the operating environment of insulators along the Qinghai-Tibet railway,the pollution flashover experiments were designed for the cantilever composite insulator FQBG-25/12.Through the experiments,the flashover voltage under the influence of soluble contaminant density(SCD)of different pollution components,non-soluble deposit density(NSDD),temperature(T),and atmospheric pressure(P)was obtained.On this basis,the GA-BP neural network prediction model was established.P,SCD,NSDD,CaSO_(4) mass fraction(w(CaSO_(4))),and T were taken as input parameters,50%flashover voltage(U_(50%))of the insulator was taken as output parameters.The results showed that the prediction deviation was less than 10%,which meets the basic engineering requirements.The results could not only provide early warning for the anti-pollution flashover work of the railway power supply department,but also be used as an auxiliary contrast to verify the accuracy of the results of the experiments,and provide a theoretical basis for the classification of pollution levels in different regions.
基金funded by the National Natural Science Foundation of China(Grant Nos.52274388,U1960105 and 52074187)the authors express gratitude to reviewers for precious suggestions.
文摘The prediction accuracy of existing models of the rolling force of a thick plate is always very low.To address this problem,a high-precision genetic algorithm-backpropagation network(GA-BP)model of deformation resistance was built,and its integration with the traditional fitted model was further established.Then,a novel rolling force model was obtained by embedding the integration model of deformation resistance in the original model of rolling force.According to this research idea,the industrial data are normalized at first.On this basis,the interactions among the process parameters were disclosed through the variance analysis,and then described by various virtual factors.These factors are set as part of input parameters.Then,the optimal structure of the GA-BP model of deformation resistance was determined and an integration model of deformation resistance was built.Finally,a novel rolling force model is obtained by substituting the traditional fitted deformation resistance into the Sims model with the integration model of the deformation resistance.The results proves that the introduction of virtual factors can increase the hit rate of±5%from 75.8%to 78%and can reduce the root mean square error from 4.72%to 4.48%.Besides,it is found that the mean relative error of the traditional fitted deformation resistance is 0.142,while that of the modified deformation resistance is only 0.03.In addition,the mean relative error in the original rolling force model is 0.145,while that of the present model is only 0.03.
