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联合收割机脱粒状态监测及故障诊断系统设计OA

Design of State Monitoring and Fault Diagnosis System for Combine Harvester

中文摘要英文摘要

针对联合收割机在环境恶劣多变工作条件下关键部件状态不易监测,且系统发生故障无法及时排除的问题,设计了联合收割机状态监测及故障诊断系统.利用数据采集系统获取联合收割机工作参数(包括温度、转速和振动参数),通过云端通信模块实现数据与手机客户端的对接,用户采用 Android 客户端获取联合收割机实时运行状况,可通过设置相关阈值实现故障预警及报警.试验结果表明:利用 WIFI 无线通信技术和 RS485 串口通信技术相结合,通过 Socket 方式可以实现 Android 客户端与服务器的数据通信;所监测的温度、转速、振动速度及振动幅度的曲线图及数据能够实时动态更新,数据延迟为 100ms,满足监测要求.所提出的联合收割机脱粒系统故障诊断方法,能够准确做出故障预警及报警,具有较高的可靠性.

Aiming at the problem that the working status of the key device of combine harvester is difficult to monitor un-der the harsh and variable working conditions.At the same time,the system failure can not be eliminated in time.Com-bine harvester status monitoring and fault diagnosis system was designed.In this paper,we used the data acquisition sys-tem to obtain the working parameters of combine harvester(including temperature,speed and vibration parameters)and realized the docking of data and mobile phone client through the cloud communication module.The operator can use the Android client to obtain the real-time operating status of combine harvester.The early warning and alarm of the fault can be realized by setting the relevant threshold.The test results showed that the combination of WIFI wireless communication technology,the RS485 wireless communication technology and the socket method can realize the data communication be-tween the Android client and the server.The monitored graphs and data of temperature,rotation speed,vibration speed and vibration amplitude can be dynamically updated in real time.The monitored data delay is 100ms,which meets the monitoring requirements.When the combine harvester is operating in the field,the fault diagnosis method based on the in-stantaneous change trend of the target signal can accurately discover the fault early warning and alarm functions.

陈经纬;郝帅华;王成;唐忠;顾新阳

江苏大学 农业工程学院, 江苏 镇江 212013

农业工程

联合收割机脱粒状态无线监测故障诊断

combine harvesterthreshing statewireless monitoringfault diagnosis

《农机化研究》 2024 (007)

115-120 / 6

国家重点研发计划项目(2017YFD0700203);国家级大学生创新训练项目(202110299074Z)

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