摘要
当油葵联合收获机出现脱粒滚筒堵塞等故障时会影响联合收割机作业效率,而缺少自动故障早期预警手段的问题日益突出。为此,以因素空间理论为基础,研究了油葵联合收获机的故障诊断问题。在因素空间中,油葵联合收获机故障通过将其征兆因素集综合起来进行描述,通过因素分析得到故障诊断类型;并构建了装备故障诊断知识库和推理机制,进行了油葵联合收获机故障诊断仿真。仿真结果表明:基于因素空间理论的故障诊断方法能够成功地诊断出其故障类型,对油葵作物联合收获机的科学维护及可靠运行提供重要的参考。
When breaking down,it will affect the efficiency in the use of combine harvesters,therefore,the problem of the lack of early automatic fault warning methods is becoming more and more serious.In this paper,fault diagnosis problem of oil sunflower combine harvester is studied based on the theory of factors space.In the factor space,the fault diagnosis of oil sunflower combine harvester is described through its symptom factors set together,and we got the fault type through factor analysis,at last,we built the equipment fault diagnosis knowledge base and reasoning mechanism,and the simulation analysis of fault diagnosis for the coal planer is carried out.The simulation results show that the fault diagnosis method based on the factor space theory can obtain the fault type of oil sunflower combine harvester correctly,this can provide important reference value for the scientific maintenance and reliable operation of oil sunflower combine harvester.
作者
李茜
张学军
朱兴亮
Li Xi;Zhang Xuejun;Zhu Xingliang(College of Mechanical and Electronical Engineering,Xinjiang Agricultural University,Urumqi 830052,China)
出处
《农机化研究》
北大核心
2019年第7期19-23,共5页
Journal of Agricultural Mechanization Research
基金
国家重点研发计划项目(2016YFD0702104-3)
国家自然科学基金项目(51665057)
关键词
联合收获机
故障诊断
因素空间
油葵
combine harvester
fault diagnosis
factors space
oil sunflower
作者简介
李茜(1985-),女,辽宁阜新人,硕士研究生,(E-mail)lixi629@163.com;通讯作者:张学军(1966-),男,乌鲁木齐人,教授,硕士生导师,博士,(E-mail)tuec@163.com。
