收获开沟埋草一体机双圆盘开沟机构设计与参数优化

    Design and parameter optimization of double disk opener mechanism for harvest ditch and stalk-disposing machine

    • 摘要: 为提高已研制的稻麦联合收获开沟埋草多功能一体机免耕播种时的开沟播种质量,设计双圆盘开沟机构与一体机相结合。为获取影响双圆盘开沟机构作业质量因素的最优参数,以机器前进速度、开沟器入土深度、开沟器排种管固定装置固定孔中心点至排种管出口中心点横向距离为试验因素,以种子入沟率、各行播种量稳定性变异系数、播种均匀性变异系数为试验指标,进行三因素五水平二次正交旋转组合试验。试验结果表明:各试验因素对于种子入沟率与各行播种量稳定性变异系数影响程度从大到小皆依次是:固定孔横向距离、开沟器入土深度、机器前进速度;各试验因素对于播种均匀性变异系数的影响程度从大到小依次是:机器前进速度、开沟器入土深度、固定孔横向距离。优化所得双圆盘开沟机构开沟播种作业最佳参数组合为机器前进速度为0.46 m/s;开沟器入土深度为3.25 cm;固定孔横向距离为16.16 mm,验证试验表明各指标试验结果与理论优化结果相对误差均小于4%,验证了所建模型与优化参数的合理性。

       

      Abstract: Abstract: In order to advance the seeding quality of harvest ditch and stalk-disposing machine that our research group designed and fabricated, a double disk opener mechanism was designed combining with the harvest ditch and stalk-disposing machine. An electric lifting device was integrated into double disk opener mechanism installed underneath sowing box of the harvest ditch and stalk-disposing machine. To improve the working performance of double disk opener mechanism, the structure and installation parameters of the double disk opener mechanism were calculated. The diameter of double disk opener was 200 mm,the disc included angle of double disk opener was 15°, the accumulation point angle of double disk opener was 81.4°, the maximum entering soil depth of double disk opener was 60 mm, the joint lever length of central point of double disc opener to hinged installation point of bottom of header was 370 mm and the distance of upper connection point of electric lifting gear to ground was 661 mm. The three work factors, forward speed of machine, furrow depth of double disk opener, and horizontal distance of fixed hole central point of sowing pipe's fixed device on furrow opener to exit central point of sowing pipe (shortened horizontal distance of fixed hole), impacted quality of furrow and drill mainly. In order to optimize working quality parameters of double disk opener mechanism, a central composite design method of second order regression orthogonal rotation was carried out. In the experiment, the three work factors were used as the experiment factors and the rate of seeds into the ditch, each row seeding stability coefficient of variation, and seeding uniformity coefficient of variation were used as experiment indicators. In the experiment, forward speed of machine was 0.3-1.2 m/s, furrow depth of double disk opener was 1.5-4.5 cm, and horizontal distance of fixed hole was 14.5-18.5 mm. The variance analysis results of orthogonal experimental showed that among the three factors in the experiment, the horizontal distance of fixed hole had the greatest influence on the rate of seeds into the ditch and each row seeding stability coefficient, while the forward speed of machine had the least influence on the rate of seeds into the ditch and each row seeding stability coefficient, and forward speed of machine had the greatest influence on the seeding uniformity coefficient of variation, while the horizontal distance of fixed hole had the least influence on the seeding uniformity coefficient of variation. Through the MATLAB software, we optimized values of the three factors, and the optimized results showed that the optimal value of forward speed of machine was 0.46 m/s, furrow depth of double disk opener was 3.25 cm, and horizontal distance of fixed hole was 16.16 mm. When the three factors reached the optimal values, the value of the rate of seeds into the ditch was 90.3%, value of each row seeding stability coefficient of variation was 9.3% and value of seeding uniformity coefficient of variation was 10.2%. The validation experiment was carried out for making the rationality of optimal values. The validation experiment showed that when the values of three factors were the same as optimize values, the value of the rate of seeds into the ditch was 89.4%, value of each row seeding stability coefficient of variation was 9.4% and value of seeding uniformity coefficient of variation was 9.8%. The relative error was below 4% of experiment values with optimal values, which validated the optimal values of the three factors.

       

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