关键词: 牧场, 推料机器人, 参数优化, EDEM, 响应面分析

Abstract: To address the issue of low cleaning rate caused by the deposition of dry matter in feed during the feeding operation in dairy farms, this paper proposes a novel pusher structure featuring a “self-rotating drum, forward-leaning posture, and flexible cleaning”. A simulation model of the “roller brush, feed, and ground” system was established using the discrete element method(DEM). A multi-component- 引用格式:张文恺,杨术明,马永龙,等.基于EDEM的牧场推料机器人参数优化设计与试验［J］.河北大学学报(自然科学版),2026,46(3):225-236.引用格式:张文恺,杨术明,马永龙,等.基于EDEM的牧场推料机器人参数优化设计与试验［J］.河北大学学报(自然科学版),2026,46(3):225-236.DOI:10.3969/j.issn.1000-1565.2026.03.001基于EDEM的牧场推料机器人参数优化设计与试验张文恺¹,杨术明¹,马永龙²,李茂强²,马驰¹,颜铭宏¹,田世玉¹(1.宁夏大学 机械工程学院,宁夏 银川 750021;2.北方民族大学 机电工程学院,宁夏 银川 750021)摘 要:为解决牧场推料作业中饲料干物质沉积导致推净率低的问题,本文提出一种“自转滚筒、前倾姿态、柔性清扫”的推料机结构.采用离散元法(discrete element method,DEM)建立“滚筒毛刷、饲料、地面”的仿真模型;依据现场实测饲料截面尺寸与休止角构建多组分等效颗粒库,并在工程DEM(engineering DEM,EDEM)中完成几何与物性建模.以机器人前进速度、姿态倾角与滚筒转速为优化参数,以推送效率与推净率为评价指标.根据仿真结果采用三因素五水平中心复合设计(central composite design,CCD)开展响应面试验,并进行数据处理与回归分析,对优化结果进行试验验证.仿真结果显示,所建立模型对2项响应指标均极显著,失拟不显著;主效应分析中,前进速度的影响最显著;姿态倾角与滚筒转速对推送效率亦表现出显著影响.综合优化得到:当机器人前进速度、姿态倾角、滚筒转速分别为0.55 m/s、2.78°、29 r/min时,对应的推送效率与推净率仿真值分别为891 kg/min和98.0%,且与现场实测值的相对误差分别为2.36%与2.86%.本文验证了推料机结构的合理性,为精料残留清扫与推料作业标准化提供了工程化路径.关键词:牧场;推料机器人;参数优化;EDEM;响应面分析中图分类号:TP242.3 文献标志码:A 文章编号:1000-1565(2026)03-0225-12DOI:10.3969/j.issn.1000-1565.2026.03.001Parameter optimization design and experiment of the feed-pushing robot in dairy farms based on EDEMZHANG Wenkai¹, YANG Shuming¹, MA Yonglong², LI Maoqiang²,MA Chi¹, YAN Minghong¹, TIAN Shiyu¹(1. School of Mechanical Engineering, Ningxia University, Yinchuan 750021, China; 2. College of Mechanical and Electrical Engineering, North Minzu University, Yinchuan 750021, China)Abstract: To address the issue of low cleaning rate caused by the deposition of dry matter in feed during the feeding operation in dairy farms, this paper proposes a novel pusher structure featuring a “self-rotating drum, forward-leaning posture, and flexible cleaning”. A simulation model of the “roller brush, feed, and ground” system was established using the discrete element method(DEM). A multi-component- 收稿日期:2025-12-01;修回日期:2025-12-28 基金项目:国家自然科学基金项目(32260433);宁夏回族自治区重点研发项目(2024BBF02029) 第一作者:张文恺(1998—),男,宁夏大学在读硕士研究生,主要从事智能化农牧装备方向研究.E-mail:1562616569@qq.com 通信作者:杨术明(1974—),男,宁夏大学教授,主要从事智能化农牧装备方向研究.E-mail:shmyang@nxu.edu.cn 第3期张文恺等:基于EDEM的牧场推料机器人参数优化设计与试验河北大学学报(自然科学版) 第46卷equivalent particle library was constructed based on the measured cross-sectional dimensions and repose angles of the feed, and geometric and physical property modeling was completed in engineering DEM(EDEM). The forward speed, the attitude inclination angle, and the drum rotation speed of the robot were selected as optimization parameters, while the push efficiency and the clean push rate served as evaluation indicators. Based on the simulation results, a three-factor five-level response surface experiment based on central composite design(CCD)was designed, followed by data processing and regression analysis. The optimization results were experimentally validated. The simulation results indicate that the established model is highly significant for both responses, with no significant underfitting. Among the main effects, forward speed exhibits the most prominent influence, and both attitude inclination angle and drum rotation speed also show a significant impact on the push efficiency. The comprehensive optimization results show that when the robots forward speed, attitude inclination angle, and drum rotation speed are 0.55 m/s, 2.78°, and 29 r/min, respectively, the corresponding simulation values of push efficiency and clean push rate are 891 kg/min and 98.0%, respectively. The relative errors compared with the on-site measured values are 2.36% and 2.86%, respectively. This study verifies the rationality of the pusher mechanism and provides an engineering pathway for the cleaning of residual materials and the standardization of the pusher.

Key words: dairy farm, feed-pushing robot, parameter optimization, EDEM, response surface analysis