摘 要
随着农业现代化的快速发展，智能农业机械的应用日益广泛，但其远程监控与故障诊断技术仍面临诸多挑战。为提高农业机械运行效率并降低维护成本，本文设计了一种基于物联网和人工智能技术的远程监控与故障诊断系统。该系统通过集成传感器网络、数据通信模块及云端计算平台，实现了对农业机械运行状态的实时监测与数据分析，并结合深度学习算法构建了精准的故障预测模型。研究中采用边缘计算优化数据传输效率，同时引入异常检测机制以提升系统的鲁棒性。实验结果表明，该系统能够有效识别机械故障类型，预测准确率超过95%，显著缩短了故障响应时间。此外，系统还支持移动端可视化管理，便于用户实时掌握设备状态。本研究的主要创新点在于融合多源异构数据进行智能化分析，并提出了一种轻量级故障诊断算法，为智能农业机械的高效运维提供了新思路。研究成果可为现代农业装备的智能化升级提供重要参考。
关键词：智能农业机械；远程监控与故障诊断；物联网；深度学习；边缘计算
DESIGN OF REMOTE MONITORING AND FAULT DIAGNOSIS SYSTEM FOR INTELLIGENT AGRICULTURAL MACHINERY
ABSTRACT
With the rapid development of agricultural modernization, the application of intelligent agricultural machinery is becoming increasingly widespread; however, remote monitoring and fault diagnosis technologies still face numerous challenges. To enhance the operational efficiency of agricultural machinery and reduce maintenance costs, this study designs a remote monitoring and fault diagnosis system based on Internet of Things (IoT) and artificial intelligence technologies. By integrating sensor networks, data communication modules, and cloud computing platforms, the system achieves real-time monitoring and analysis of the operational status of agricultural machinery, while employing deep learning algorithms to construct an accurate fault prediction model. Edge computing is adopted to optimize data transmission efficiency, and an anomaly detection mechanism is introduced to improve the robustness of the system. Experimental results demonstrate that the system can effectively identify types of mechanical faults with a prediction accuracy exceeding 95%, significantly reducing fault response time. Moreover, the system supports mobile-end visualized management, enabling users to conveniently monitor equipment status in real time. The primary innovation of this research lies in the integration of multi-source heterogeneous data for intelligent analysis and the proposal of a lightweight fault diagnosis algorithm, providing new insights into the efficient operation and maintenance of intelligent agricultural machinery. This study offers critical references for the intelligent upgrading of modern agricultural equipment.
KEY WORDS：Intelligent Agricultural Machinery；Remote Monitoring And Fault Diagnosis；Internet Of Things；Deep Learning；Edge Computing
目 录
摘 要 I
ABSTRACT II
第一章 绪论 1
1.1 智能农业机械远程监控的意义 1
1.2 国内外研究现状分析 1
1.3 本文研究方法与结构安排 1
第二章 系统需求分析与设计框架 2
2.1 农业机械远程监控的功能需求 2
2.2 故障诊断系统的性能要求 2
2.3 系统整体架构设计 3
第三章 关键技术实现与算法研究 3
3.1 数据采集与传输技术应用 3
3.2 故障诊断算法的设计与优化 4
3.3 远程监控平台的开发与实现 4
第四章 系统测试与案例分析 5
4.1 测试环境与评估标准 5
4.2 实验结果与数据分析 5
4.3 典型应用场景探讨 6
结 论 6
参考文献 7
致 谢 8
