基于因素空间的油葵联合收获机故障诊断推理机制
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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.
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.
引文
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[10]易立单.联合收割机堵塞故障监测系统研究[D].镇江:江苏大学,2010.
[11]郑世宇,陈进,李耀明.联合收获机多传感器信号采集与数据处理系统[J].农业机械学报,2011(S1):107-111.
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[13]徐凯.基于BPNN与DS理论的联合收割机堵塞故障诊断与报警系统[D].镇江:江苏大学,2016.
[14]柴杰,江青茵,曹志凯,等.基于因素空间变权理论的工业故障诊断[J].厦门大学学报:自然科学版,2002,41(4):448-452.
[15]王靳辉.因素空间与诊断型专家系统[J].测绘科学技术学报,1993(1):71-74.
[16]李莎莎,崔铁军,马云东,等. SFT中故障及其影响因素的背景关系分析[J].计算机应用研究,2017,34(11):3277-3280.
[17]汪培庄,郭嗣琮,包研科,等.因素空间中的因素分析法[J].辽宁工程技术大学学报:自然科学版,2014,33(7):865-870.
[18]汪培庄.因素空间与因素库[J].辽宁工程技术大学学报:自然科学版,2013(10):1297-1304.
[19]金小亮.联合收割机滚筒堵塞故障监测系统研究[D].合肥:安徽农业大学,2014.
[2]韩长杰,刘希光,袁盼盼,等.油葵收获机械研究现状及发展建议[J].农业工程,2017,7(2):1-4.
[3]龚洪浪.基于人机协同技术的农业收割机故障诊断系统设计[J].农机化研究,2018,40(3):203-207.
[4]于福生,罗承忠.基于因素空间理论的故障诊断数学模型及其应用[J].模糊系统与数学,1999(1):47-53.
[5]徐立章,李耀明,孙朋朋,等.履带式全喂入水稻联合收获机振动测试与分析[J].农业工程学报,2014,30(8):49-55.
[6]刘文亮,刘枫,胡浩,等.玉米联合收获机主要部件故障监测系统研究[J].农机使用与维修,2015(9):17-19.
[7]马世文,韩世文.玉米联合收获机常见故障与排除方法[J].农机使用与维修,2017(11):52-53.
[8]陈进,吕世杰,李耀明,等.基于PLC的联合收获机作业流程故障诊断方法研究[J].农业机械学报,2011(S1):112-116.
[9]汪凤珠,张俊宁,李瑞川,等.花生联合收获机作业在线监测与故障预警系统研究[J].农业机械学报,2015(S1):69-73.
[10]易立单.联合收割机堵塞故障监测系统研究[D].镇江:江苏大学,2010.
[11]郑世宇,陈进,李耀明.联合收获机多传感器信号采集与数据处理系统[J].农业机械学报,2011(S1):107-111.
[12]张忠侠.联合收割机常见故障原因的分析[J].农机使用与维修,2015(2):34.
[13]徐凯.基于BPNN与DS理论的联合收割机堵塞故障诊断与报警系统[D].镇江:江苏大学,2016.
[14]柴杰,江青茵,曹志凯,等.基于因素空间变权理论的工业故障诊断[J].厦门大学学报:自然科学版,2002,41(4):448-452.
[15]王靳辉.因素空间与诊断型专家系统[J].测绘科学技术学报,1993(1):71-74.
[16]李莎莎,崔铁军,马云东,等. SFT中故障及其影响因素的背景关系分析[J].计算机应用研究,2017,34(11):3277-3280.
[17]汪培庄,郭嗣琮,包研科,等.因素空间中的因素分析法[J].辽宁工程技术大学学报:自然科学版,2014,33(7):865-870.
[18]汪培庄.因素空间与因素库[J].辽宁工程技术大学学报:自然科学版,2013(10):1297-1304.
[19]金小亮.联合收割机滚筒堵塞故障监测系统研究[D].合肥:安徽农业大学,2014.