To improve the automation level and operation quality of China's beet harvester and reduce the loss due to damaged and missed excavation,this study used a self-developed sugar beet combine harvester and field simu...To improve the automation level and operation quality of China's beet harvester and reduce the loss due to damaged and missed excavation,this study used a self-developed sugar beet combine harvester and field simulation experiment platform,based on the single-factor bench test of the automatic row following system in the early stage,taking hydraulic flow A,spring preload B,and forward speed C which have significant influence on performance indices as test factors,and taking the missed excavation rate,breakage rate and reaction time as performance indices,the orthogonal experimental study on the parameter optimization of the three-factor and three-level automatic row following system with the first-order interaction of various factors was carried out.The results of the orthogonal experiments were analyzed using range analysis and variance analysis.The results showed that there were differences in the influence degree,factor priority order and first-order interaction,and the optimal parameter combination on each performance index.A weighted comprehensive scoring method was used to optimize and analyze each index.The optimal parameter combination of the overall operating performance of the automatic row following system was A 2B 2C 1,that is,the hydraulic flow was 25 L/min,the forward speed was 0.8 m/s,and the spring preload was 198 N.Under this combination,the response time was 0.496 s,the missed excavation rate was 2.35%,the breakage rate was 3.65%,and the operation quality was relatively good,which can meet the harvest requirements.The comprehensive optimization results were verified by field experiments with different ridge shapes and different planting patterns.The results showed that the mean values of the missed excavation rate of different planting patterns of conventional straight ridges and extremely large"S"ridges were 2.23%and 2.69%,respectively,and the maximum values were 2.39%and 2.98%,respectively;the average damage rates were 3.38%and 4.14%,and the maximum values were 3.58%and 4.48%,which meet the industry standards of sugar beet harvester operation quality.The overall adaptability of the automatic row following system is good.This study can provide a reference for research on automatic row following harvesting systems of sugar beets and other subsoil crop harvesters.展开更多
To improve the declining performance of a full-feed peanut picking device or solve the mechanical failures that occur due to fluctuations in the feeding rate during operation,the 4HLJI-3000 peanut intelligent picking ...To improve the declining performance of a full-feed peanut picking device or solve the mechanical failures that occur due to fluctuations in the feeding rate during operation,the 4HLJI-3000 peanut intelligent picking combine harvester,which is a picking device with a self-adaptive adjustment of the working clearance,was developed as the research object in this study.Moreover,the key components,such as the picking roller,concave plate sieve and clearance adjustment mechanism of the concave plate sieve,were designed and analysed.Through the force analysis of the concave plate sieve of the picking device,the mathematical model of the concave plate sieve displacement of the picking device and feeding rate was obtained.The software system for monitoring,storing and analysing the concave plate sieve displacement of the picking device based on EasyBuilder Pro was designed,and the road monitoring test of displacement variation of concave plate sieve of the picking device and feeding rate was carried out.The linear function,power function,exponential function,quadratic function,compound function,logarithmic function and cubic function fitting were used to perform regression analysis of the test results by using IBM SPSS software.The results showed that the cubic function model had a higher fitting precision,and its determination coefficient was 0.992.Model verification experiments were proposed,and the results showed that the established cubic function model had a good accuracy.The absolute deviation rate ranged from 0 to 4.83%,and the average deviation rate was 2.22%.The deviation rate increased with an increasing feeding rate.The field experiments also proved that there was a cubic function relationship between the feeding rate and concave plate sieve displacement,the measured concave plate sieve displacement deviation rate ranged from 0 to 6.19%,and the average deviation rate was 2.73%compared with the calculated results.This study can provide a reference for the optimization design of the structure of full-feeding picking devices for peanuts and other crops and the intelligent measurement and control of the feeding rates.展开更多
To obtain the optimal operation parameters of fixed-bed reversing ventilation drying of peanuts,a set of partial differential equations indicating the heat and mass transfer relationships between the peanut pods and a...To obtain the optimal operation parameters of fixed-bed reversing ventilation drying of peanuts,a set of partial differential equations indicating the heat and mass transfer relationships between the peanut pods and air during drying was proposed.Then,a series of discretized models were established for simulation,and the time consumed,unevenness,and energy consumption for batch drying were calculated.The results showed that reversing ventilation and segmented drying was helpful to these issues for high drying ability.The optimal operation parameters were determined by uniform design experimentation of mathematical simulation.The result showed that when the moisture content(wet basis)was above 22%,a ventilation velocity of 0.46 m/s was optimal;when the moisture content was between 8%and 22%,a ventilation velocity of 0.20 m/s was optimal.Using the optimal parameters,the computer simulating result was compared with the experimental results.The correlation coefficients between the simulating and the experimental values for the temperature and moisture content were all above 0.98 and the quality of dried peanuts was close to that of natural sun-dried ones,which indicates that the optimization results of the drying parameters are highly reliable.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.52105263)the Key Laboratory of Intelligent Equipment and Robotics for Agriculture of Zhejiang Province(Grant No.2022ZJZD2201).
文摘To improve the automation level and operation quality of China's beet harvester and reduce the loss due to damaged and missed excavation,this study used a self-developed sugar beet combine harvester and field simulation experiment platform,based on the single-factor bench test of the automatic row following system in the early stage,taking hydraulic flow A,spring preload B,and forward speed C which have significant influence on performance indices as test factors,and taking the missed excavation rate,breakage rate and reaction time as performance indices,the orthogonal experimental study on the parameter optimization of the three-factor and three-level automatic row following system with the first-order interaction of various factors was carried out.The results of the orthogonal experiments were analyzed using range analysis and variance analysis.The results showed that there were differences in the influence degree,factor priority order and first-order interaction,and the optimal parameter combination on each performance index.A weighted comprehensive scoring method was used to optimize and analyze each index.The optimal parameter combination of the overall operating performance of the automatic row following system was A 2B 2C 1,that is,the hydraulic flow was 25 L/min,the forward speed was 0.8 m/s,and the spring preload was 198 N.Under this combination,the response time was 0.496 s,the missed excavation rate was 2.35%,the breakage rate was 3.65%,and the operation quality was relatively good,which can meet the harvest requirements.The comprehensive optimization results were verified by field experiments with different ridge shapes and different planting patterns.The results showed that the mean values of the missed excavation rate of different planting patterns of conventional straight ridges and extremely large"S"ridges were 2.23%and 2.69%,respectively,and the maximum values were 2.39%and 2.98%,respectively;the average damage rates were 3.38%and 4.14%,and the maximum values were 3.58%and 4.48%,which meet the industry standards of sugar beet harvester operation quality.The overall adaptability of the automatic row following system is good.This study can provide a reference for research on automatic row following harvesting systems of sugar beets and other subsoil crop harvesters.
基金supported by the Jiangsu Agricultural Science and Technology Innovation Fund (Grant No.CX (23)3028)National Natural Science Foundation of China (Grant No.52105263)+2 种基金Key Laboratory of Modern Agricultural Intelligent Equipment in South China,Ministry of Agriculture and Rural Affairs,China (HNZJ202201)Key Laboratory of Intelligent Equipment and Robotics for Agriculture of Zhejiang Province (Grant No.2022ZJZD2201)Key Laboratory of Agricultural Equipment for Hilly and Mountainous Areas in Southeastern China (Co-construction by Ministry and Province),Ministry of Agriculture and Rural Affairs (Grant No.QSKF2023004).
文摘To improve the declining performance of a full-feed peanut picking device or solve the mechanical failures that occur due to fluctuations in the feeding rate during operation,the 4HLJI-3000 peanut intelligent picking combine harvester,which is a picking device with a self-adaptive adjustment of the working clearance,was developed as the research object in this study.Moreover,the key components,such as the picking roller,concave plate sieve and clearance adjustment mechanism of the concave plate sieve,were designed and analysed.Through the force analysis of the concave plate sieve of the picking device,the mathematical model of the concave plate sieve displacement of the picking device and feeding rate was obtained.The software system for monitoring,storing and analysing the concave plate sieve displacement of the picking device based on EasyBuilder Pro was designed,and the road monitoring test of displacement variation of concave plate sieve of the picking device and feeding rate was carried out.The linear function,power function,exponential function,quadratic function,compound function,logarithmic function and cubic function fitting were used to perform regression analysis of the test results by using IBM SPSS software.The results showed that the cubic function model had a higher fitting precision,and its determination coefficient was 0.992.Model verification experiments were proposed,and the results showed that the established cubic function model had a good accuracy.The absolute deviation rate ranged from 0 to 4.83%,and the average deviation rate was 2.22%.The deviation rate increased with an increasing feeding rate.The field experiments also proved that there was a cubic function relationship between the feeding rate and concave plate sieve displacement,the measured concave plate sieve displacement deviation rate ranged from 0 to 6.19%,and the average deviation rate was 2.73%compared with the calculated results.This study can provide a reference for the optimization design of the structure of full-feeding picking devices for peanuts and other crops and the intelligent measurement and control of the feeding rates.
基金supported by the Special Expenses for Basic Scientific Research of the Chinese Academy of Agricultural Sciences(Grant No.S201937)New Equipment and New Technology Research,Development and Promotion Project of Jiangsu Province Agricultural Machinery(Grant No.SZ120180032).
文摘To obtain the optimal operation parameters of fixed-bed reversing ventilation drying of peanuts,a set of partial differential equations indicating the heat and mass transfer relationships between the peanut pods and air during drying was proposed.Then,a series of discretized models were established for simulation,and the time consumed,unevenness,and energy consumption for batch drying were calculated.The results showed that reversing ventilation and segmented drying was helpful to these issues for high drying ability.The optimal operation parameters were determined by uniform design experimentation of mathematical simulation.The result showed that when the moisture content(wet basis)was above 22%,a ventilation velocity of 0.46 m/s was optimal;when the moisture content was between 8%and 22%,a ventilation velocity of 0.20 m/s was optimal.Using the optimal parameters,the computer simulating result was compared with the experimental results.The correlation coefficients between the simulating and the experimental values for the temperature and moisture content were all above 0.98 and the quality of dried peanuts was close to that of natural sun-dried ones,which indicates that the optimization results of the drying parameters are highly reliable.