The filter capacitor stack is one of the main acoustic noise sources in high-voltage DC(HVDC) converter stations.As HVDC systems are built more and more recently,it is significant to research the audible noise of filt...The filter capacitor stack is one of the main acoustic noise sources in high-voltage DC(HVDC) converter stations.As HVDC systems are built more and more recently,it is significant to research the audible noise of filter capacitors.In this paper,the current situation of research on vibration and audible noise of filter capacitors in HVDC converter stations,which is departed into three parts—generation mechanism,prediction methods,and reduction measures,is presented and the research achievements are discussed.Scholars have built the model that the alternating electric force caused by the voltage conduces to the vibration,which propagates to the enclosure and radiates audible noise.As a result,the parts contributing most to the generation of audible noise are the top and the bottom of capacitors. In the noise level prediction respect,several methods have been prospected including impact hammer,sweep frequency, impact current,monopole and Kirchhoff formula method,which are suitable for single capacitors or capacitors stacks individually.However,the sweep frequency method is restricted by experiment condition,and the impact current method needs further research and verified.On the other hand,CIGRE WG14.26 provides three sound reduction measures,but all of them are not so practicable,while MPP absorber and compressible space absorber prospected by Dr.Wu Peng are proved to be effective.The sound barriers are also considered by scholars,and the acoustic directivity performance of capacitors is also researched.Besides,the developing direction of each research field is prospected in corresponding part.展开更多
The resilient modulus(MR)of subgrade soils is usually used to characterize the stiffness of subgrade and is a crucial parameter in pavement design.In order to determine the resilient modulus of compacted subgrade soil...The resilient modulus(MR)of subgrade soils is usually used to characterize the stiffness of subgrade and is a crucial parameter in pavement design.In order to determine the resilient modulus of compacted subgrade soils quickly and accurately,an optimized artificial neural network(ANN)approach based on the multi-population genetic algorithm(MPGA)was proposed in this study.The MPGA overcomes the problems of the traditional ANN such as low efficiency,local optimum and over-fitting.The developed optimized ANN method consists of ten input variables,twenty-one hidden neurons,and one output variable.The physical properties(liquid limit,plastic limit,plasticity index,0.075 mm passing percentage,maximum dry density,optimum moisture content),state variables(degree of compaction,moisture content)and stress variables(confining pressure,deviatoric stress)of subgrade soils were selected as input variables.The MR was directly used as the output variable.Then,adopting a large amount of experimental data from existing literature,the developed optimized ANN method was compared with the existing representative estimation methods.The results show that the developed optimized ANN method has the advantages of fast speed,strong generalization ability and good accuracy in MR estimation.展开更多
This paper proposes a novel method to predict the spur gear pair’s static transmission error based on the accuracy grade,in which manufacturing errors(MEs),assembly errors(AEs),tooth deflections(TDs)and profile modif...This paper proposes a novel method to predict the spur gear pair’s static transmission error based on the accuracy grade,in which manufacturing errors(MEs),assembly errors(AEs),tooth deflections(TDs)and profile modifications(PMs)are considered.For the prediction,a discrete gear model for generating the error tooth profile based on the ISO accuracy grade is presented.Then,the gear model and a tooth deflection model for calculating the tooth compliance on gear meshing are coupled with the transmission error model to make the prediction by checking the interference status between gear and pinion.The prediction method is validated by comparison with the experimental results from the literature,and a set of cases are simulated to study the effects of MEs,AEs,TDs and PMs on the static transmission error.In addition,the time-varying backlash caused by both MEs and AEs,and the contact ratio under load conditions are also investigated.The results show that the novel method can effectively predict the range of the static transmission error under different accuracy grades.The prediction results can provide references for the selection of gear design parameters and the optimization of transmission performance in the design stage of gear systems.展开更多
Dimensional analysis and numerical simulations were carried out to research prediction method of breakthrough time of horizontal wells in bottom water reservoir. Four dimensionless independent variables and dimensionl...Dimensional analysis and numerical simulations were carried out to research prediction method of breakthrough time of horizontal wells in bottom water reservoir. Four dimensionless independent variables and dimensionless time were derived from 10 influencing factors of the problem by using dimensional analysis. Simulations of horizontal well in reservoir with bottom water were run to find the prediction correlation. A general and concise functional relationship for predicting breakthrough time was established based on simulation results and theoretical analysis. The breakthrough time of one conceptual model predicted by the correlation is very close to the result by Eclipse with less than 2% error. The practical breakthrough time of one well in Helder oilfield is 10 d, and the predicted results by the method is 11.2 d, which is more accurate than the analytical result. Case study indicates that the method could predict breakthrough time of horizontal well under different reservoir conditions accurately. For its university and ease of use, the method is suitable for quick prediction of breakthrough time.展开更多
基金Supported by National Natural Science Foundation of China(50907046)
文摘The filter capacitor stack is one of the main acoustic noise sources in high-voltage DC(HVDC) converter stations.As HVDC systems are built more and more recently,it is significant to research the audible noise of filter capacitors.In this paper,the current situation of research on vibration and audible noise of filter capacitors in HVDC converter stations,which is departed into three parts—generation mechanism,prediction methods,and reduction measures,is presented and the research achievements are discussed.Scholars have built the model that the alternating electric force caused by the voltage conduces to the vibration,which propagates to the enclosure and radiates audible noise.As a result,the parts contributing most to the generation of audible noise are the top and the bottom of capacitors. In the noise level prediction respect,several methods have been prospected including impact hammer,sweep frequency, impact current,monopole and Kirchhoff formula method,which are suitable for single capacitors or capacitors stacks individually.However,the sweep frequency method is restricted by experiment condition,and the impact current method needs further research and verified.On the other hand,CIGRE WG14.26 provides three sound reduction measures,but all of them are not so practicable,while MPP absorber and compressible space absorber prospected by Dr.Wu Peng are proved to be effective.The sound barriers are also considered by scholars,and the acoustic directivity performance of capacitors is also researched.Besides,the developing direction of each research field is prospected in corresponding part.
基金Project(51878078)supported by the National Natural Science Foundation of ChinaProject(2018-025)supported by the Training Program for High-level Technical Personnel in Transportation Industry,ChinaProject(CTKY-PTRC-2018-003)supported by the Design Theory,Method and Demonstration of Durability Asphalt Pavement Based on Heavy-duty Traffic Conditions in Shanghai Area,China。
文摘The resilient modulus(MR)of subgrade soils is usually used to characterize the stiffness of subgrade and is a crucial parameter in pavement design.In order to determine the resilient modulus of compacted subgrade soils quickly and accurately,an optimized artificial neural network(ANN)approach based on the multi-population genetic algorithm(MPGA)was proposed in this study.The MPGA overcomes the problems of the traditional ANN such as low efficiency,local optimum and over-fitting.The developed optimized ANN method consists of ten input variables,twenty-one hidden neurons,and one output variable.The physical properties(liquid limit,plastic limit,plasticity index,0.075 mm passing percentage,maximum dry density,optimum moisture content),state variables(degree of compaction,moisture content)and stress variables(confining pressure,deviatoric stress)of subgrade soils were selected as input variables.The MR was directly used as the output variable.Then,adopting a large amount of experimental data from existing literature,the developed optimized ANN method was compared with the existing representative estimation methods.The results show that the developed optimized ANN method has the advantages of fast speed,strong generalization ability and good accuracy in MR estimation.
基金Project(51675061)supported by the National Natural Science Foundation of China。
文摘This paper proposes a novel method to predict the spur gear pair’s static transmission error based on the accuracy grade,in which manufacturing errors(MEs),assembly errors(AEs),tooth deflections(TDs)and profile modifications(PMs)are considered.For the prediction,a discrete gear model for generating the error tooth profile based on the ISO accuracy grade is presented.Then,the gear model and a tooth deflection model for calculating the tooth compliance on gear meshing are coupled with the transmission error model to make the prediction by checking the interference status between gear and pinion.The prediction method is validated by comparison with the experimental results from the literature,and a set of cases are simulated to study the effects of MEs,AEs,TDs and PMs on the static transmission error.In addition,the time-varying backlash caused by both MEs and AEs,and the contact ratio under load conditions are also investigated.The results show that the novel method can effectively predict the range of the static transmission error under different accuracy grades.The prediction results can provide references for the selection of gear design parameters and the optimization of transmission performance in the design stage of gear systems.
基金Project(2011ZX05009-004)supported by the National Science and Technology Major Projects of China
文摘Dimensional analysis and numerical simulations were carried out to research prediction method of breakthrough time of horizontal wells in bottom water reservoir. Four dimensionless independent variables and dimensionless time were derived from 10 influencing factors of the problem by using dimensional analysis. Simulations of horizontal well in reservoir with bottom water were run to find the prediction correlation. A general and concise functional relationship for predicting breakthrough time was established based on simulation results and theoretical analysis. The breakthrough time of one conceptual model predicted by the correlation is very close to the result by Eclipse with less than 2% error. The practical breakthrough time of one well in Helder oilfield is 10 d, and the predicted results by the method is 11.2 d, which is more accurate than the analytical result. Case study indicates that the method could predict breakthrough time of horizontal well under different reservoir conditions accurately. For its university and ease of use, the method is suitable for quick prediction of breakthrough time.
