番茄钵苗移栽机自动取苗装置作业参数优化与试验

针对新疆地区番茄移栽机械自动化程度低、劳动强度大、作业效率低等问题,该文分析了一种番茄钵苗自动取苗装置的夹苗器凸轮运动过程,得到了凸轮运动过程参数,结合钵苗取苗作业要求搭建取苗试验台,对自动取苗装置主要工作参数进行优化。以适栽期番茄钵苗为试验对象,利用自动取苗试验台进行单因素试验。进一步结合理论分析及单因素试验,选取苗针长度、苗针开度、取苗频率为影响因素,以伤苗率、漏苗率和取苗成功率为评价指标进行三因素三水平二次旋转正交组合试验,通过Design-Expert.V8.0.6软件,得到理论最优参数组合:苗针长度198 mm,苗针开度19 mm,取苗频率57株/min,此参数组合下伤苗率为3.91%,漏苗率为1.56%,取苗成功率为94.69%。在自动取苗试验台上进行验证试验,取苗装置伤苗率为3.44%,漏苗率为1.72%,取苗成功率为94.38%,与优化结果基本吻合,验证了所建模型与优化参数的合理性。田间取苗试验伤苗率为3.65%,漏苗率为2.08%,取苗成功率为94.27%。田间试验取苗成功率与优化结果的误差为0.44%,表明取苗装置抗干扰能力较强。该研究结果可为番茄全自动移栽机取苗装置的结构改进和作业参数控制提供参考。

Optimization and experiment of working parameters of automatic seedling picking device for tomato seedlings transplanting

Xinjiang is the main producing area for processing tomatoes in China because of its unique light and heat resources. The tomato industry occupies a very important position in Xinjiang''s agricultural production and tomato planting mostly adopts seedling transplanting technology. In recent years, with the continuous expansion of planting scale, the demand for transplanting machinery increases sharply every spring. At present, most of the transplanting machines used are semi-automatic transplanters, and the seedling picking and throwing operations should be completed manually. The development of seedling transplanting technology is restricted by the low degree of automation, high labor intensity, low efficiency and high operation cost seriously. Therefore, the development of full-automatic transplanter has become eager and necessary to realize crop efficient large-scale transplanting in Xinjiang. The core of the research and development for the full-automatic transplanter is the automatic seedling picking technology. According to the full-automatic transplanter''s requirements of the automatic seedling picking and throwing operation, the automatic seedling picking device of tomato was designed in this study, and a performance test-bed for automatic seedling picking was built. The planet wheel train-link mechanism and the irregular sideways were used to control the movement process of the seedling clamper, and realize the required trajectory for automatic seedling picking. In addition, the cam lever mechanism is used to control the opening and closing of seedling needle to realize the action of seedling picking and throwing. In order to ensure the ideal working quality and success rate of the automatic seedling picking device, it is important to obtain the ideal working parameters and structural parameters of the automatic seedling picking device. With the help of the test-bed of the automatic seedling picking device, the main working parameters are optimized through experiments to improve the working quality. The single factor experiment was conducted with the length and opening size of seedling needle and the frequency of seedling picking as variables according to theoretical analysis and experimental research, combined with the requirements of transplanting on film in Xinjiang. The test results showed that each factor has influence on the injury rate, missing rate and success rate of seedling. Furthermore, quadratic rotation orthogonal combination experiments with three-factor three-level were conducted with the injury rate, the missing rate and the success rate of seedling picking as the evaluation indexes. The mathematical regression model between response indexes and influence factors was established by data optimization software Design-Expert 8.6.0. Response surface analysis was used to analyze the experimental results, and multi-objective optimization analysis was used to optimize each parameter. The regression model optimization results were the length of seedling needle 198 mm, the opening size of seedling needle 19 mm, and the frequency of seedling picking 57 (plants/min). Under these parameters combination, the injury rate of seedling was 3.44%, the missing rate of seedling was 1.72%, and the success rate of seedling picking was 94.38%. In the field experiment, the injury rate of the seedling was 3.65%, the missing rate of seedling was 2.08%, the success rate of seedling picking was 94.27%, and the error between the experimental value of the success rate of seedling picking and the optimization result was 0.44%, which indicated that the automatic seedling picking device for tomato seedlings could meet the requirements of picking and the anti-interference ability of the device was strong. The study can supply certain references for the design of key components of the automatic transplanting machine and the improvement of working performance parameters.