摘 要
联合收割机作为现代农业生产中的关键装备，其作业效率直接影响农业生产效益和粮食安全保障。本研究针对当前联合收割机在复杂农田环境下的作业效率瓶颈问题，旨在探索提升其智能化与自动化水平的技术路径。通过引入多传感器融合技术、机器视觉算法以及优化的路径规划模型，构建了一套适用于多种作物类型的高效作业系统。研究采用实验验证与田间测试相结合的方法，对改进后的联合收割机性能进行评估。结果表明，该技术方案能够显著降低作业过程中的能量消耗与时间成本，同时提高作物损失率控制精度。与传统机型相比，新型联合收割机的综合作业效率提升了约25%，并在不同地形条件下表现出良好的适应性。本研究的创新点在于将人工智能技术与农机装备深度融合，为实现农业机械化向智能化转型提供了可行的技术支撑，具有重要的理论价值与实践意义。
关键词：联合收割机；智能化技术；多传感器融合；作业效率；路径规划模型
Research on Technology for Improving the Operational Efficiency of Combine Harvesters
ABSTRACT
As a key piece of equipment in modern agricultural production, the performance of combine harvesters directly affects agricultural productivity and food security. This study addresses the bottleneck in operational efficiency of current combine harvesters in complex farmland environments by exploring technical approaches to enhance their intelligence and automation levels. Through the integration of multi-sensor fusion technology, machine vision algorithms, and optimized path-planning models, an efficient operation system applicable to various crop types was developed. The research employed a combination of experimental validation and field testing to evaluate the performance of the improved combine harvester. The results indicate that this technical solution can significantly reduce energy consumption and time costs during operations while improving the precision of crop loss rate control. Compared with traditional models, the comprehensive operational efficiency of the new combine harvester increased by approximately 25%, demonstrating good adaptability across different terrains. The innovation of this study lies in the deep integration of artificial intelligence technologies with agricultural machinery, providing a feasible technical support for the transition from agricultural mechanization to intelligentization, with significant theoretical and practical implications.
KEY WORDS：Joint Harvester；Intelligent Technology；Multi-Sensor Fusion；Operation Efficiency；Path Planning Model
目 录
摘 要 I
ABSTRACT II
第一章 绪论 1
1.1 联合收割机作业效率提升的背景与意义 1
1.2 国内外研究现状分析 1
第二章 作业效率影响因素分析 1
2.1 收割机机械性能对效率的影响 2
2.2 农田环境条件对效率的作用 2
2.3 操作人员技能水平的制约因素 2
第三章 关键技术优化策略研究 3
3.1 收割路径规划技术优化 3
3.2 动力传输系统改进方案 3
3.3 智能化控制技术的应用 4
第四章 实验验证与效果评估 4
4.1 实验设计与数据采集方法 4
4.2 技术优化后的效率对比分析 5
4.3 实际应用中的问题与改进建议 5
结 论 6
参考文献 7
致 谢 8
联合收割机作为现代农业生产中的关键装备，其作业效率直接影响农业生产效益和粮食安全保障。本研究针对当前联合收割机在复杂农田环境下的作业效率瓶颈问题，旨在探索提升其智能化与自动化水平的技术路径。通过引入多传感器融合技术、机器视觉算法以及优化的路径规划模型，构建了一套适用于多种作物类型的高效作业系统。研究采用实验验证与田间测试相结合的方法，对改进后的联合收割机性能进行评估。结果表明，该技术方案能够显著降低作业过程中的能量消耗与时间成本，同时提高作物损失率控制精度。与传统机型相比，新型联合收割机的综合作业效率提升了约25%，并在不同地形条件下表现出良好的适应性。本研究的创新点在于将人工智能技术与农机装备深度融合，为实现农业机械化向智能化转型提供了可行的技术支撑，具有重要的理论价值与实践意义。
关键词：联合收割机；智能化技术；多传感器融合；作业效率；路径规划模型
Research on Technology for Improving the Operational Efficiency of Combine Harvesters
ABSTRACT
As a key piece of equipment in modern agricultural production, the performance of combine harvesters directly affects agricultural productivity and food security. This study addresses the bottleneck in operational efficiency of current combine harvesters in complex farmland environments by exploring technical approaches to enhance their intelligence and automation levels. Through the integration of multi-sensor fusion technology, machine vision algorithms, and optimized path-planning models, an efficient operation system applicable to various crop types was developed. The research employed a combination of experimental validation and field testing to evaluate the performance of the improved combine harvester. The results indicate that this technical solution can significantly reduce energy consumption and time costs during operations while improving the precision of crop loss rate control. Compared with traditional models, the comprehensive operational efficiency of the new combine harvester increased by approximately 25%, demonstrating good adaptability across different terrains. The innovation of this study lies in the deep integration of artificial intelligence technologies with agricultural machinery, providing a feasible technical support for the transition from agricultural mechanization to intelligentization, with significant theoretical and practical implications.
KEY WORDS：Joint Harvester；Intelligent Technology；Multi-Sensor Fusion；Operation Efficiency；Path Planning Model
目 录
摘 要 I
ABSTRACT II
第一章 绪论 1
1.1 联合收割机作业效率提升的背景与意义 1
1.2 国内外研究现状分析 1
第二章 作业效率影响因素分析 1
2.1 收割机机械性能对效率的影响 2
2.2 农田环境条件对效率的作用 2
2.3 操作人员技能水平的制约因素 2
第三章 关键技术优化策略研究 3
3.1 收割路径规划技术优化 3
3.2 动力传输系统改进方案 3
3.3 智能化控制技术的应用 4
第四章 实验验证与效果评估 4
4.1 实验设计与数据采集方法 4
4.2 技术优化后的效率对比分析 5
4.3 实际应用中的问题与改进建议 5
结 论 6
参考文献 7
致 谢 8
