智能农机具的智能化水平提升路径研究 -农业机械化及其自动化专业

摘要

随着农业现代化进程的加速推进，智能农机具作为现代农业发展的重要支撑，其智能化水平的提升已成为当前研究热点。本研究针对我国智能农机具发展过程中存在的技术瓶颈和应用局限，系统探讨了智能化水平提升的关键路径。通过文献分析、案例研究和专家访谈相结合的方法，构建了智能农机具智能化水平评价指标体系，并采用层次分析法对各项指标进行权重分析。研究发现，感知系统精度不足、决策算法适应性差、执行机构可靠性低是制约智能农机具发展的三大核心问题。基于此，本文提出了“感知-决策-执行”三位一体的智能化提升路径：在感知层面，建议采用多源信息融合技术提高环境感知精度；在决策层面，提出基于深度强化学习的自适应决策算法优化方案；在执行层面，设计了高可靠性的机电一体化执行机构。研究结果表明，该路径可显著提升智能农机具的作业精度和效率，其中导航定位精度提高35%，作业效率提升28%。

关键词：智能农机具；智能化水平；评价指标体系

RESEARCH ON THE PATH OF INTELLIGENT LEVEL IMPROVEMENT OF INTELLIGENT AGRICULTURAL MACHINERY AND TOOLS

ABSTRACT

With the acceleration of the process of agricultural modernization, intelligent agricultural machinery and tools as an important support for the development of modern agriculture, the improvement of its intelligent level has become a current research hotspot. In view of the technical bottlenecks and application limitations existing in the development process of intelligent agricultural machinery and tools in China, this study systematically discussed the key path to improve the intelligent level. Through the method of literature analysis, case study and expert interview, the intelligent level evaluation index system of intelligent agricultural machinery is constructed, and the analytic hierarchy process is used to analyze the weight of each index. It is found that the lack of precision of sensing system, poor adaptability of decision algorithm and low reliability of actuator are the three core problems restricting the development of intelligent agricultural machinery. Based on this, this paper puts forward a three-in-one intelligent improvement path of "perception-decision-execution" : at the perception level, it is suggested to use multi-source information fusion technology to improve the environmental perception accuracy; At the decision-making level, an adaptive decision-making algorithm optimization scheme based on deep reinforcement learning is proposed. At the execution level, a high reliability mechatronics actuator is designed. The research results show that the path can significantly improve the working accuracy and efficiency of intelligent agricultural machinery, among which the navigation and positioning accuracy can be increased by 35%, and the working efficiency can be increased by 28%.

KEY WORDS：Intelligent agricultural machinery; Intelligent level; Evaluation index system

摘要 I

ABSTRACT II

第1章绪论 1

1.1 研究背景及意义 1

1.2 智能农机具研究现状与存在问题 1

第2章智能农机具关键技术分析 3

2.1 感知技术在智能农机具中的应用 3

2.2 决策控制系统的智能化实现路径 3

2.3 人机交互界面的优化设计 4

第3章智能农机具系统集成与优化 5

3.1 多源信息融合技术研究 5