Authors

Abstract

Seedling replenishment during the operation of high-speed ride-on rice transplanters still relies heavily on manual labor, thereby limiting the level of operational automation. To address this limitation, an automatic seedling-loading system comprising a longitudinal conveying mechanism, a lateral drive mechanism, and a tracking compensation mechanism was developed. Based on an STM32 embedded platform, a control strategy for detecting seedling shortages and performing precise seedling-loading operations was developed, enabling automatic shortage detection, lateral positioning, and targeted seedling replenishment. The main operating parameters—conveyor belt speed, lateral offset distance, and fore-aft tilt angle—were first investigated individually to determine their appropriate ranges. Subsequently, a second-order, three-factor, five-level rotatable orthogonal experiment was conducted. Seedling-loading success rate was used as the evaluation index, and a multifactor regression model was established to analyze the interactions among the factors. Bench tests were conducted to optimize the system parameters and determine the optimal parameter combination. Subsequent field trials confirmed the operational reliability of the system, with an average seedling-loading success rate of 90.67% over five batches of tests. The proposed system shows considerable potential for replacing manual loading of mat-type rice seedlings and provides a practical solution for advancing the full-process automation of rice transplanting operations.

Abstract in English

在高速乘坐式插秧机作业过程中，补秧环节依赖人工、自动化程度不足。本文构建了由纵向输送装置、横向移动装置与随动装置组成的自动装秧系统，基于STM32嵌入式平台设计缺秧检测与执行机构控制逻辑，实现缺秧检测、横向定位与定点补秧。以输送带速度、横向偏移距离与前后倾斜角度为试验因素，开展单因素试验确定因素取值范围；采用三因素五水平二次旋转正交组合试验，以装秧成功率为评价指标建立多因素回归模型并分析各因素及其交互作用。通过台架试验优化关键参数。田间试验结果表明，系统完成5批次自动装秧任务，平均成功率为90.67%。所研制的自动装秧系统能够实现毯状苗机插从缺秧识别到定点补秧的自动补秧作业，降低了补秧过程的人工依赖，可为水稻种植全程自动化提供技术支持。