农业装备中传感器融合技术的应用研究
摘 要
随着现代农业的快速发展，农业装备的智能化和自动化需求日益增加。传感器融合技术作为一种多源信息集成与处理的有效手段，在农业装备中的应用逐渐受到广泛关注。本研究旨在探讨传感器融合技术在农业装备中的应用潜力，通过集成多种传感器数据，提升农业装备的感知能力和决策效率。研究采用了多传感器数据融合算法，结合实际农业场景中的土壤、气象、作物生长等多维度数据，构建了基于卡尔曼滤波和神经网络的融合模型。实验结果表明，该模型能够有效提高农业装备的环境感知精度，特别是在复杂农田环境中，相较于单一传感器系统，融合技术的应用显著提升了数据的可靠性和准确性。此外，本研究还针对中国典型农业区域进行了实地测试，验证了该技术在不同气候和土壤条件下的适应性。
关键词：传感器融合技术；农业装备智能化；多传感器
APPLICATION RESEARCH ON SENSOR FUSION TECHNOLOGY IN AGRICULTURAL EQUIPMENT
ABSTRACT
With the rapid development of modern agriculture, the demand for intelligence and automation of agricultural equipment is increasing. As an effective means of multi-source information integration and processing, the application of sensor fusion technology in agricultural equipment has gradually attracted wide attention. The purpose of this study is to explore the application potential of sensor fusion technology in agricultural equipment, and to improve the perception ability and decision-making efficiency of agricultural equipment by integrating various sensor data. Using the multi-sensor data fusion algorithm, combined with the multi-dimensional data of soil, meteorology and crop growth in the actual agricultural scenarios, we constructed a fusion model based on Kalman filter and neural network. The experimental results show that the model can effectively improve the environmental perception accuracy of agricultural equipment, especially in the complex farmland environment, compared with a single sensor system, the application of fusion technology significantly improves the reliability and accuracy of data. Moreover, this study conducted field tests on typical agricultural areas in China to verify the adaptability of this technique under different climate and soil conditions.
KEY WORDS：Sensor fusion technology; intelligent agricultural equipment; multi-sensors
目 录
摘 要 I
ABSTRACT II
第1章 绪论 1
1.1 研究背景及意义 1
1.2 研究目的和内容 1
1.3 国内外研究现状 1
第2章 传感器融合技术在农业装备中的理论基础 3
2.1 传感器融合技术的基本原理 3
2.2 农业装备中传感器融合的必要性分析 3
2.3 传感器融合技术在农业装备中的应用框架 4
第3章 农业装备中多传感器数据融合方法研究 5
3.1 多传感器数据采集与预处理技术 5
3.2 基于卡尔曼滤波的传感器数据融合算法 5
3.3 深度学习在农业传感器数据融合中的应用 6
第4章 传感器融合技术在农业装备中的实践应用 7
4.1 智能农机中传感器融合技术的应用案例 7
4.2 精准灌溉系统中的传感器融合优化策略 7
4.3 基于传感器融合的病虫害监测与预警系统 8
第5章 结论 9
参考文献 10
致 谢 11
摘 要
随着现代农业的快速发展，农业装备的智能化和自动化需求日益增加。传感器融合技术作为一种多源信息集成与处理的有效手段，在农业装备中的应用逐渐受到广泛关注。本研究旨在探讨传感器融合技术在农业装备中的应用潜力，通过集成多种传感器数据，提升农业装备的感知能力和决策效率。研究采用了多传感器数据融合算法，结合实际农业场景中的土壤、气象、作物生长等多维度数据，构建了基于卡尔曼滤波和神经网络的融合模型。实验结果表明，该模型能够有效提高农业装备的环境感知精度，特别是在复杂农田环境中，相较于单一传感器系统，融合技术的应用显著提升了数据的可靠性和准确性。此外，本研究还针对中国典型农业区域进行了实地测试，验证了该技术在不同气候和土壤条件下的适应性。
关键词：传感器融合技术；农业装备智能化；多传感器
APPLICATION RESEARCH ON SENSOR FUSION TECHNOLOGY IN AGRICULTURAL EQUIPMENT
ABSTRACT
With the rapid development of modern agriculture, the demand for intelligence and automation of agricultural equipment is increasing. As an effective means of multi-source information integration and processing, the application of sensor fusion technology in agricultural equipment has gradually attracted wide attention. The purpose of this study is to explore the application potential of sensor fusion technology in agricultural equipment, and to improve the perception ability and decision-making efficiency of agricultural equipment by integrating various sensor data. Using the multi-sensor data fusion algorithm, combined with the multi-dimensional data of soil, meteorology and crop growth in the actual agricultural scenarios, we constructed a fusion model based on Kalman filter and neural network. The experimental results show that the model can effectively improve the environmental perception accuracy of agricultural equipment, especially in the complex farmland environment, compared with a single sensor system, the application of fusion technology significantly improves the reliability and accuracy of data. Moreover, this study conducted field tests on typical agricultural areas in China to verify the adaptability of this technique under different climate and soil conditions.
KEY WORDS：Sensor fusion technology; intelligent agricultural equipment; multi-sensors
目 录
摘 要 I
ABSTRACT II
第1章 绪论 1
1.1 研究背景及意义 1
1.2 研究目的和内容 1
1.3 国内外研究现状 1
第2章 传感器融合技术在农业装备中的理论基础 3
2.1 传感器融合技术的基本原理 3
2.2 农业装备中传感器融合的必要性分析 3
2.3 传感器融合技术在农业装备中的应用框架 4
第3章 农业装备中多传感器数据融合方法研究 5
3.1 多传感器数据采集与预处理技术 5
3.2 基于卡尔曼滤波的传感器数据融合算法 5
3.3 深度学习在农业传感器数据融合中的应用 6
第4章 传感器融合技术在农业装备中的实践应用 7
4.1 智能农机中传感器融合技术的应用案例 7
4.2 精准灌溉系统中的传感器融合优化策略 7
4.3 基于传感器融合的病虫害监测与预警系统 8
第5章 结论 9
参考文献 10
致 谢 11
