节点文献
荸荠振动筛分式自动分级机设计与试验
Design and performance test of water chestnut vibrating screening automatic classifier
【摘要】 针对荸荠人工分级效率低、成本高、缺少专用分级机等产业需求,设计一种荸荠振动筛分式自动分级机。首先,通过预试验和仿真试验,确定影响荸荠分级准确率的分级机工作参数。然后,基于ADAMS构建自动分级机关键部件振动筛的运动学仿真模型,分析确定曲柄长度及曲柄电机转速调节范围。运用Design—Expert软件设计三因素三水平Box—Behnken试验,并开展荸荠自动分级试验,分析得出影响总体分级准确率的较大因素依次为曲柄电机转速和筛板倾角。再以总体分级准确率最大为目标对分级机工作参数进行优化,得到最优工作参数为进料喂入量9.73 kg/min、筛板倾角2.11°、曲柄电机转速105.96 r/min。最后,基于优化后的工作参数进行荸荠分级验证试验。试验结果表明,自动分级机能高精度完成分级工作,总体分级准确率达到95.87%,试验值与模型预测值误差小于5%。为荸荠及类似不规则、易损伤的农业物料在产后自动分级的技术提升提供有效参考。
【Abstract】 Aiming at the industrial challenges such as low efficiency, high costs, and the lack of dedicated grading equipment for manual water chestnut grading, a vibrating screening-based automatic classifier specifically designed for water chestnuts was developed. Firstly, preliminary experiments and simulation tests were conducted to identify the operational parameters of the classifier that affect the grading accuracy of water chestnuts. A kinematic simulation model of the vibrating screen, the core component of the automatic classifier was then established by using ADAMS software to analyze and determine the crank length and the adjustable range of the crank motor speed. A three-factor and three-level Box—Behnken experiment was designed by using the Design—Expert software, and the automatic grading experiment of water chestnuts was carried out. The results revealed that the crank motor speed and sieve plate inclination angle were the most significant factors influencing overall grading accuracy. Subsequently, the operational parameters of classifier were optimized to maximize overall grading accuracy, the optimal working parameters were obtained by the feeding amount of 9.73 kg/min, sieve plate inclination of 2.11°, crank motor speed of 105.96 r/min. Finally, a water chestnut grading validation test was conducted based on the optimized operational parameters. The test results demonstrated that the automatic grading machine achieved high-precision grading, with an overall grading accuracy of 95.87% and the error between the test value and the model prediction value was less than 5%. This study provides an effective reference for the improvement of post-harvest automatic grading technologies for water chestnuts and similar irregular, damage-prone agricultural materials.
【Key words】 water chestnut; automatic classifer; size classification; vibrating screening; orthogonal test; parameter optimization;
- 【文献出处】 中国农机化学报 ,Journal of Chinese Agricultural Mechanization , 编辑部邮箱 ,2026年03期
- 【分类号】S226.5
- 【下载频次】22