Research On Intelligent Design Method Of Threshing Device Of Rice Combine Harvester

Breaking through the technical bottleneck of the research and development of high-end agricultural machinery equipment such as large-scale combine harvesters and realizing the effective supply of agricultural machinery products are major issues hindering the development of the agricultural machinery industry in China.Traditional design methods have long research and development cycles,have low efficiency,lack systematic and structured knowledge utilization systems,and cannot effectively integrate design and knowledge.Moreover,it is difficult to meet the needs of customized and diversified product design.In addition,the existing simulation software has difficulty describing the interaction between the combined disengagement device and the crop and determining the effective boundary conditions,which makes it difficult to match the simulation results with the actual results.In addition,the existing simulation software struggles to describe the interaction between the threshing device of a combine harvester and crops and to determine the effective boundary conditions,which also makes it difficult to match the simulation and actual results.In view of the problems above,the intelligent design of threshing devices and the dynamic modelling and simulation of rice threshing were studied in this paper.(1)The interval-valued intuitionistic fuzzy set(IVIFS)was used to calculate the comprehensive correlation strength between parts,and the comprehensive correlation strength matrix was transformed into a complex network model.An equivalent capacitance method was proposed to calculate the path weight.A similarity model of complex network nodes based on the equivalent capacitance method was established.Applying the similarity model to the hierarchical clustering algorithm,the NHC algorithm was proposed to realize the module division of agricultural machinery equipment.The feasibility of the method was verified by taking the module division of the threshing device as an example.(2)The matter-element representation method of the product case and module case was studied.Through the matter-element model,product cases and module cases were saved as reusable and modifiable knowledge in a unified form.A rule-based product module feature mapping model was established to map non-digital feature values.The case retrieval method of multi-attribute decision-making was studied,and the similarity calculation of feature values of different data types was realized.The matter-element transformation and multi-objective optimization methods were studied,and a variant design of the module was realized.A modular product configuration process was put forward by integrating various methods,and the feasibility of the method was verified by the configuration design of the combine harvester threshing device.(3)A bonded-particle straw model(BSM)with a flexible hollow cylindrical bond was established.The BSM was used to construct virtual crop straw,and the static and dynamic characteristics of the model were studied.Through the BSM static simulation of crop straw,the maximum relative errors between the transverse deflection and axial tensile displacement of the crop straw and the theoretical calculation results were 4.04%and 0.28%,respectively,and the maximum relative errors of the bending test and tensile test results were 12.87%and 4.78%,respectively.Dynamic simulation of the crop straw was carried out by the BSM.The results show that the lateral deflection and axial displacement of the free end of the straw change with time,which is consistent with the theoretical calculation results.The relative errors between the simulation results of the lateral vibration period and the axial vibration period and the theoretical calculation results were 0.22%and 0.56%,respectively.The BSM was used to simulate the separation of grain and straw under straw area densities of 2 kg/m~2 and 3 kg/m~2.The correlation coefficient between the cumulative mass curve of separated grains and the experimental results was more than0.995.At 2 kg/m~2 and 3 kg/m~2,the simulation results were in good agreement with the experimental results,and the maximum relative errors were 6.69%and 7.06%.The BSM could accurately describe the separation of grain from straw and quantify the interference between the straw and equipment.(4)A rice crop model was constructed using the BSM to study the simulation of flexible rice dynamic threshing.Under a large deformation,crushing and multiple collisions,the flexible rice body was subjected to a threshing simulation,and the cumulative distribution and separation rate of separated grains along the length of the threshing concave plate were consistent with the experimental results.Under different feeding amounts,the grain separation rate has a maximum relative error of 11.2%.The threshing simulation comprehensively described and quantified the dynamic threshing process and yielded grain movement information,position information and threshing state information,which is helpful for understanding the threshing process and the interaction mechanism between crops and machines.The modelling and simulation method proposed in this paper is a general algorithm that can be used to optimize the threshing process and design a new threshing device.(5)An intelligent design system for the threshing device of a combine harvester based on extension theory was designed and developed.On the basis of the key technologies studied in the chapters above,the main functions,i.e.,module division,feature mapping,case retrieval,extension transformation and multi-objective optimization,were realized.The feasibility of the system was verified by taking the longitudinal flow threshing device and the multi-flow threshing device as examples.