摘要
为了实时掌握收割机工作状态,提高堵塞故障预警和预处理的能力,设计了一种联合收割机智能监控系统。该系统以单片机为主控制器,触摸屏为人机交互系统,运用基于BPNN(BP神经网络)与DS理论的堵塞故障诊断算法分析收割机工作状态,依据诊断结果自动控制收割机前进速度,实现优化联合收割机工作状态,降低堵塞故障发生率的目的。试验表明,系统操作方便、运行稳定,改善收割机操控环境,使得堵塞故障预警时间达到3 s以上,降低了堵塞故障发生率。
To grasp the harvester working state timely and improve the early warning and pretreatment ability of jam fault, this paper designed a set of combine harvester intelligent monitoring system. This system takes the MCU as the main controller, touch screen as man -machine interactive system, using based on BPNN （BP neural network） and DS theory of jam fault diagnosis algorithm to analyze harvester working state, according to the diagnosis to control harvester forward speed automaticlly and realize the optimization of the combined harvester working condition and reduce blockage fault occurrence rate. The test shows that the system has the advantages of easy operation, stable operation, improving the harvester control environment, making jam fault warning time reach more than 3 seconds and reducing the blockage failure rate.
出处
《电子科技》
2016年第12期152-155,共4页
Electronic Science and Technology
基金
国家高技术研究发展计划(863计划)基金资助项目(2012AA10A502)
江苏省科技支撑计划基金资助项目(BE2012312)
江苏省科技成果转化基金资助项目(BA2014.62)
关键词
联合收割机
BP神经网络
DS理论
故障诊断
自动控制
故障预警
combine harvester
BP neural network
DS theory
fault diagnosis
automaticl control
fault early warning
