农业机械智能维护系统设计与实现

Design and Realization of Intelligent Maintenance System for Agricultural Machinery

随着农业机械设备的日益复杂化和集成化,农业机械设备维护和管理是保证农业机械稳定、安全和可靠运行的关键。传统的维护方式主要依赖于定期检查和经验判断,存在维护周期不合理、故障预测不准确、维修滞后等问题,容易导致设备突发故障,影响农业生产进程。该文提出了一种基于机器学习和大数据分析的智能维护系统,通过安装在农业机械上的传感器,实时采集设备运行数据,包括温度、振动、压力、电流等多种参数。数据通过无线通信网络传输至云端平台,进行数据存储和处理,并结合利用机器学习算法和大数据分析技术,对采集到的数据进行分析和处理,实现设备状态的实时监测、故障预测和健康评估。

With the increasing complexity and integration of agricultural machinery and equipment,agricultural machinery and equipment maintenance and management is the key to ensure the stable,safe and reliable operation of agricultural machinery.The traditional maintenance method mainly relies on regular inspection and empirical judgment,which has problems such as unreasonable maintenance cycle,inaccurate failure prediction,and lagging maintenance,which easily leads to sudden equipment failure and affects the agricultural production process.This study proposes an intelligent maintenance system based on machine learning and big data analysis,which collects real-time equipment operation data,including temperature,vibration,pressure,current and other parameters,through sensors installed on agricultural machinery.The data is transmitted to a cloud platform through a wireless communication network for data storage and processing,and combined with the use of machine learning algorithms and big data analysis technology,the collected data is analyzed and processed to achieve real-time monitoring,fault prediction,and health assessment of equipment status.