Dissertation > Agricultural Sciences > Agricultural Engineering > Agricultural machinery and implements > Planting machinery > Planting machine

Digital Design and Experiment Study on Soft Disc Seedling Transplanter

Author WangShi
Tutor LiChengHua
School Shenyang Agricultural University
Course System Theory and Design of Agricultural Machinery
Keywords Soft Disc transplanter digital design QGA ADAMS simulationanalysis experiment study
CLC S223.9
Type PhD thesis
Year 2013
Downloads 40
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Digital design is the core of modern design theory and method, it contains all the latest technologies applied in modern design. Digital design technologies wasintroduced into agricultural machinery industry to change the traditional design method and to improve the integral design and manufacturing level of Chinese agricultural machinery.Based on the structure and working principle of Kombinette soft disc transplanter, the influence of coefficient λ on upright degree of seedling during transplantation conditions was analyzed. The transplanting process was analyzed and deduced and the kinematic model of seedling was established. In addition, the relationship between transplanter structure parameters and seedling landing angles and between transplanter working parameters and seedling landing angles were determined. Therefore, the technical and theoretical bases for transplanter design was provided.The basic concept, principle and calculation process of quantum computing, genetic algorithm and the quantum genetic algorithm was analyze, and the factors of QGA, such as convergence time, population diversity and adjust tactics of rotational angle were analyzed. Based on the fact that the structure parameter of soft disc transplanter is nonlinear and multidimensional, a universal QGA optimizing plan was composed. By comparing QGA, GA and IGA, that QGA was more suitable for the study.Taking Kombinette soft disc transplanter as subject, the geometric modeling, feature modeling, parametric modeling and digital assembly technology of3D entity model were studied. The3D entity model of the key parts of the soft disc transplanter was built by using feature modeling and constraint modeling. Thus, the parameterization of product characteristics was realized. According to the inner structure of the transplanter, customer demands and production requirements for transplanting, the relationship between design parameters was found out. The digital model for key parts of transplanter and for complete transplanter was built. These digital models probided basis for stimulation, analysis and testing optimization.Through specialized interface module MECHANISM/Pro, the Kombinette transplanter and seedling entity models were built in ADAMS and parameters were set to make the stimulation identical to the reality. With the optimized seedling dropping parameters and transplanter working parameters, based on the script simulation technology, the simulation of seedling transplanting was realized. The stimulation results were used to verify the optimized parameters calculated by QGA and theory.Kombinette soft disc transplanter was tested transplanting pepper seedlings. Through single factor experiment, the impact of speed, ditch depth and the position of ditcher on the upright degree, buried soil depth and seedling buried percentage were analyzed. By means of quadratic orthogonal rotational combination design and double-factor tests, the mathematical models descoribing relationship between experiment criteria and experiment factor were developed and the importance of the factors was analyzed. By optimizing calculating method, a combination of optimal solution and suitable factors were determined. The correctness of optimized parameters calculated by QGA, simulation results and experimental results were verified by the theoretical optimal criteria.A digital design system was developed for the Kombinette soft disc transplanter and three dimensional entity modeling, parameterization design, performance parameter calculation and data management were realized. The design system could reduce the workloads of designers, improve design efficiency, shorten product design cycle, reduce development costs and improve the competitiveness of the product and the enterprise.

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