摘要
为了减少播种机故障频率,提升小麦播种机的播种效率和播种质量,基于预知维修对小麦播种机的运行监控系统进行了设计。系统的主要组成包括主控单片机、检测系统、显示监控系统、报警系统及电源。为了对播种机进行预知维修,将灰色模型和神经网络模型结合,建立了动态灰色神经网络模型,并进行了算法设计。为了验证小麦播种机监控系统性能和预知维修算法的有效性,对其进行了监测精度和趋势预测试验,结果表明:监测系统的监测精度较高,播种机可有效对数据趋势进行预测。
In order to reduce the failure frequency of seeder,improve the sowing efficiency and quality of wheat seeder,the operation monitoring system of wheat seeder based on predictive maintenance was designed.The system was constituted of main control microcontroller,detection system,display monitoring system,alarm system,power supply.To carry out predictive maintenance of seeder,a dynamic grey neural network model was established by combining grey model with neural network model.And the algorithm was designed.To verify the performance of the monitoring system and the effectiveness of the predictive maintenance algorithm,the monitoring accuracy and trend prediction tests were carried out.The test results show that the monitoring precision of the system is high,and the seeder could predict the data trend effectively.
作者
张惠峰
成静
Zhang Huifeng;Cheng Jing(Hebei Energy College of Vocation and Technology,Tangshan 063000,China)
出处
《农机化研究》
北大核心
2024年第7期121-124,130,共5页
Journal of Agricultural Mechanization Research
基金
河北省职业教育科学研究“十三五”规划课题(ZJY17056)。
关键词
小麦播种机
预知维修
运行监控系统
动态灰色神经网络模型
监测精度
wheat seeder
predictive maintenance
operation monitoring system
dynamic grey neural network model
monitoring accuracy
