Generally,a subsoiler is comprised of a shank and a point.The point shape has a significant effect on the draft force of a subsoiler.In this study,the draft force of subsoilers with four different points were compared...Generally,a subsoiler is comprised of a shank and a point.The point shape has a significant effect on the draft force of a subsoiler.In this study,the draft force of subsoilers with four different points were compared under the speed of 0.8 m/s and the depth of 350 mm in the soil bin.Discrete Element Method(DEM)was applied in simulating the working process of the subsoiler.The stiffness of soil particles used in DEM was calibrated by comparing the simulated draft force of a standard arc-shaped subsoiler with the experiment.The calibrated soil particle stiffness was 1.1×104 N/m.The validated model was then used to compare the draft force of subsoilers with four different points under the same condition in the test.Results showed that different points would cause different draft forces.The subsoiler with short chisel point caused the smallest draft force(2885 N)while the point with short face and wings had the largest force(4474 N).The relative errors of the simulated results were less than 4%,which proved that DEM was an effective way for predicting the draft force of subsilers.The velocity field and contact force filed could show the movement of soil around the subsoiler.展开更多
Tendency towards computer simulations linked to agricultural machinery has enormously increased in recent years.In this regard,the principal contribution of current research was to develop soft computing simulation wo...Tendency towards computer simulations linked to agricultural machinery has enormously increased in recent years.In this regard,the principal contribution of current research was to develop soft computing simulation workplaces for performance prognostication of tractor-implement system in plowing process.Two neurofuzzy strategies based on multiple adaptive neuro-fuzzy inference systems(MANFIS)scenario and the MANFIS coupled with multiple nonlinear equations(MNE)scenariowere executed in theworkplace.Additionally,neural strategy based on artificial neural network(ANN)scenario was also fulfilled in the workplace.Operational variables of plowing depth(10–30 cm),forward speed(2–6km/h),and tillage implement type(moldboard,disk,and chisel plow)were considered as theworkplace inputs and ten performance parameters were taken as the workplace outputs.According to the obtained prognostication accuracy,simulation time,and user-friendly configuration of three scenarios(ANN,MANFIS,andMANFIS+MNE),the MANFIS+MNE was recognized as the prominent simulation scenario.According to the MANFIS+MNE workplace results,for each tillage implement,the compound effect of plowing depth and forward speed on some performance parameters(required draft force of implement,tractor rear wheel slip,fuel consumption per working hour,specific volumetric fuel consumption,tractor drawbar power,energy requirement for tillage implement,overall energy efficiency,and tractor tractive efficiency)was nonlinearly synergetic.However,it was nonlinearly antagonism in case of specific draft force and fuel consumption per tilled area.The MANFIS+MNE workplace simulation results provide opportunity for technical farmer associations involved in the decision-making of agricultural machinerymanagement in order to gain exhaustive fundamental insights into the compound effect of plowing depth and forward speed on performance of tractor-implement systems in plowing process.展开更多
A computer program was developed in C++language to predict the effect of soil bulk density on draft force on bottoms,share thickness,stresses distribution and maximum deflection on standards,bending stresses distribut...A computer program was developed in C++language to predict the effect of soil bulk density on draft force on bottoms,share thickness,stresses distribution and maximum deflection on standards,bending stresses distribution on side plates,diameter of shear pins,and tensile stress on hitch bar.It was found that,as soil bulk density increased,stresses distribution and maximum deflection on standards,bending stresses distribution on side plates,diameter of shear pins,and tensile stress on hitch bar increased.The diameter of shear pin should be larger to meet wide range of soil density.展开更多
基金the National Science and Technology Supporting Plan of China(2011BAD29B08).
文摘Generally,a subsoiler is comprised of a shank and a point.The point shape has a significant effect on the draft force of a subsoiler.In this study,the draft force of subsoilers with four different points were compared under the speed of 0.8 m/s and the depth of 350 mm in the soil bin.Discrete Element Method(DEM)was applied in simulating the working process of the subsoiler.The stiffness of soil particles used in DEM was calibrated by comparing the simulated draft force of a standard arc-shaped subsoiler with the experiment.The calibrated soil particle stiffness was 1.1×104 N/m.The validated model was then used to compare the draft force of subsoilers with four different points under the same condition in the test.Results showed that different points would cause different draft forces.The subsoiler with short chisel point caused the smallest draft force(2885 N)while the point with short face and wings had the largest force(4474 N).The relative errors of the simulated results were less than 4%,which proved that DEM was an effective way for predicting the draft force of subsilers.The velocity field and contact force filed could show the movement of soil around the subsoiler.
文摘Tendency towards computer simulations linked to agricultural machinery has enormously increased in recent years.In this regard,the principal contribution of current research was to develop soft computing simulation workplaces for performance prognostication of tractor-implement system in plowing process.Two neurofuzzy strategies based on multiple adaptive neuro-fuzzy inference systems(MANFIS)scenario and the MANFIS coupled with multiple nonlinear equations(MNE)scenariowere executed in theworkplace.Additionally,neural strategy based on artificial neural network(ANN)scenario was also fulfilled in the workplace.Operational variables of plowing depth(10–30 cm),forward speed(2–6km/h),and tillage implement type(moldboard,disk,and chisel plow)were considered as theworkplace inputs and ten performance parameters were taken as the workplace outputs.According to the obtained prognostication accuracy,simulation time,and user-friendly configuration of three scenarios(ANN,MANFIS,andMANFIS+MNE),the MANFIS+MNE was recognized as the prominent simulation scenario.According to the MANFIS+MNE workplace results,for each tillage implement,the compound effect of plowing depth and forward speed on some performance parameters(required draft force of implement,tractor rear wheel slip,fuel consumption per working hour,specific volumetric fuel consumption,tractor drawbar power,energy requirement for tillage implement,overall energy efficiency,and tractor tractive efficiency)was nonlinearly synergetic.However,it was nonlinearly antagonism in case of specific draft force and fuel consumption per tilled area.The MANFIS+MNE workplace simulation results provide opportunity for technical farmer associations involved in the decision-making of agricultural machinerymanagement in order to gain exhaustive fundamental insights into the compound effect of plowing depth and forward speed on performance of tractor-implement systems in plowing process.
文摘A computer program was developed in C++language to predict the effect of soil bulk density on draft force on bottoms,share thickness,stresses distribution and maximum deflection on standards,bending stresses distribution on side plates,diameter of shear pins,and tensile stress on hitch bar.It was found that,as soil bulk density increased,stresses distribution and maximum deflection on standards,bending stresses distribution on side plates,diameter of shear pins,and tensile stress on hitch bar increased.The diameter of shear pin should be larger to meet wide range of soil density.
