基于本体的矿井提升机主轴系统故障诊断方法
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摘要
针对传统矿井提升机故障诊断方法效率低、准确性差及诊断知识难以重用和共享等问题,提出了一种基于本体的矿井提升机主轴系统故障诊断方法。针对矿井提升机主轴系统故障原因多样化的特点,提出用三维坐标法系统总结各种故障现象及其故障原因,解决了故障总结不全面、原因分析不合理等问题;通过Protégé4.3软件建立故障诊断本体库,将故障现象、故障原因及其对应的逻辑关系作为知识存入本体库,解决了故障诊断知识共享和重用困难等问题,提高了故障诊断效率;通过SQL Server 2008数据库存取主轴系统监测数据,利用Java持久层应用程序接口JPA和Java应用程序接口Jena建立本体库与数据库的映射,实现了数据库与本体库数据的动态交换;最后通过本体库对监测数据进行分析,确定故障原因并定位故障源,实现故障诊断。实例分析结果表明,基于本体的矿井提升机主轴系统故障诊断方法提高了故障诊断的效率和准确性,且可靠性较高。
In view of problems of low efficiency,poor accuracy and difficulty in reusing and sharing diagnostic knowledge of traditional fault diagnosis methods of mine hoist,a fault diagnosis method for mine hoist spindle system based on ontology was proposed.In view of diversification of fault causes of mine hoist spindle system,a three-dimensional coordinate method is proposed to summarize various fault phenomena and their causes,and the problems such as incomplete fault summary and unreasonable reason analysis are solved;fault diagnosis ontology library is established through Protégé4.3,and fault phenomenon,fault causes and their corresponding logical relationship are stored in ontology library as knowledge,which solves problems of knowledge sharing and reuse of fault diagnosis,and improvesefficiency of fault diagnosis;SQL Server 2008 database is used to access monitoring data of the spindle system,and Java persistence layer application program interface JPA and Java application program interface Jena are used to establish mapping between ontology library and database,so as to realize dynamic data exchange of database and ontology library;finally the monitoring data is analyzed through ontology library to determine fault causes and locate fault sources,and then fault diagnosis is realized.The example analysis results show that the fault diagnosis method for mine hoist spindle system based on ontology improves efficiency and accuracy of fault diagnosis,and has high reliability.
In view of problems of low efficiency,poor accuracy and difficulty in reusing and sharing diagnostic knowledge of traditional fault diagnosis methods of mine hoist,a fault diagnosis method for mine hoist spindle system based on ontology was proposed.In view of diversification of fault causes of mine hoist spindle system,a three-dimensional coordinate method is proposed to summarize various fault phenomena and their causes,and the problems such as incomplete fault summary and unreasonable reason analysis are solved;fault diagnosis ontology library is established through Protégé4.3,and fault phenomenon,fault causes and their corresponding logical relationship are stored in ontology library as knowledge,which solves problems of knowledge sharing and reuse of fault diagnosis,and improvesefficiency of fault diagnosis;SQL Server 2008 database is used to access monitoring data of the spindle system,and Java persistence layer application program interface JPA and Java application program interface Jena are used to establish mapping between ontology library and database,so as to realize dynamic data exchange of database and ontology library;finally the monitoring data is analyzed through ontology library to determine fault causes and locate fault sources,and then fault diagnosis is realized.The example analysis results show that the fault diagnosis method for mine hoist spindle system based on ontology improves efficiency and accuracy of fault diagnosis,and has high reliability.
引文
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[9] ZHANG Yueyang,ZHAO Jianjun,LIANG Wei.The fault diagnosis of electric power metering system based on momentum BP neural network[J].Applied Mechanics and Materials,2014,668-669:724-728.
[10]王毅,陈庆新,毛宁.基于本体的注塑模改模知识表达方法研究[J].机械设计与制造,2012(12):233-235.WANG Yi,CHEN Qingxin,MAO Ning.The research on the knowledge representation of the injection mould based on ontology[J].Machinery Design&Manufacture,2012(12):233-235.
[11]易钢,罗尧岳.基于本体的中医知识库系统的研究[J].医学信息(上旬刊),2010,23(10):3516-3518.
[12] ZHOU Anmei,YU Dejie,ZHANG Wenyi.A research on intelligent fault diagnosis of wind turbines based on ontology and FMECA[J].Advanced Engineering Informatics,2015,29(1):115-125.
[13]李娟莉,杨兆建.基于本体的矿井提升机故障诊断方法[J].振动.测试与诊断,2013,33(6):993-997.LI Juanli,YANG Zhaojian.Fault diagnosis method for mine hoist based on ontology[J].Journal of Vibration,Measurement&Diagnosis,2013,33(6):993-997.
[14]李娟莉.基于本体的矿井提升机故障诊断理论与方法[M].北京:国防工业出版社,2015.
[15]孟祥忠,王振起,林存海.基于模糊诊断理论的提升机振动监测诊断系统[J].电子测量技术,2016,39(9):172-175.MENG Xiangzhong,WANG Zhenqi,LIN Cunhai.Hoist vibration monitoring and diagnosis system based on the theory of fuzzy diagnosis[J].Electronic Measurement Technology,2016,39(9):172-175.
[16]李纪.矿山设备性能测定与状态诊断技术[M].北京:煤炭工业出版社,1995.
[2]乔国厚.基于振动信号分析的矿井提升机主轴装置在线监测与故障诊断系统设计应用[J].矿山机械,2013,41(12):51-55.QIAO Guohou.Design and application of online monitoring and fault diagnosis system for spindle assembly of mine hoist based on vibration signal analysis[J].Mining&Processing Equipment,2013,41(12):51-55.
[3]赵武.基于振动测试的矿井提升机故障诊断[J].制造业自动化,2011,33(5):49-52.ZHAO Wu.Fault diagnosis of mine hoist gear based on vibration test[J].Manufacturing Automation,2011,33(5):49-52.
[4]董磊,石瑞敏,曾志强.基于复杂网络聚类的提升机主轴系统故障诊断[J].振动.测试与诊断,2016,36(4):688-693.DONG Lei,SHI Ruimin,ZENG Zhiqiang.Fault diagnosis for spindle system of hoist based on complex network clustering[J].Journal of Vibration,Measurement&Diagnosis,2016,36(4):688-693.
[5]杜海峰,王娜,张进华,等.基于复杂网络的故障诊断策略[J].机械工程学报,2010,46(3):90-96.DU Haifeng,WANG Na,ZHANG Jinghua,et al.Fault diagnosis strategy based on complex network analysis[J].Journal of Mechanical Engineering,2010,46(3):90-96.
[6]季忠,黄捷,秦树人.提升小波在齿轮箱故障诊断中的应用[J].振动.测试与诊断,2010,30(3):291-294.JI Zhong,HUANG Jie,QIN Shuren.Gearbox fault diagnosis using lifting wavelet[J].Journal of Vibration,Measurement&Diagnosis,2010,30(3):291-294.
[7] RUBINI R,MENEGHETTI U.Application of the envelope and wavelet transform analyses for the diagnosis of incipient faults in ball bearings[J].MechanicalSystemsandSignalProcessing,2001,15(2):287-302.
[8]刘金辉,任小洪.LM算法BP神经网络的数控机床主轴系统故障诊断[J].机床与液压,2015,43(21):193-196.LIU Jinhui,REN Xiaohong.Fault diagnosis of CNC machine tool spindle system of LM algorithm of BP neural network[J].Machine Tool&Hydraulics,2015,43(21):193-196.
[9] ZHANG Yueyang,ZHAO Jianjun,LIANG Wei.The fault diagnosis of electric power metering system based on momentum BP neural network[J].Applied Mechanics and Materials,2014,668-669:724-728.
[10]王毅,陈庆新,毛宁.基于本体的注塑模改模知识表达方法研究[J].机械设计与制造,2012(12):233-235.WANG Yi,CHEN Qingxin,MAO Ning.The research on the knowledge representation of the injection mould based on ontology[J].Machinery Design&Manufacture,2012(12):233-235.
[11]易钢,罗尧岳.基于本体的中医知识库系统的研究[J].医学信息(上旬刊),2010,23(10):3516-3518.
[12] ZHOU Anmei,YU Dejie,ZHANG Wenyi.A research on intelligent fault diagnosis of wind turbines based on ontology and FMECA[J].Advanced Engineering Informatics,2015,29(1):115-125.
[13]李娟莉,杨兆建.基于本体的矿井提升机故障诊断方法[J].振动.测试与诊断,2013,33(6):993-997.LI Juanli,YANG Zhaojian.Fault diagnosis method for mine hoist based on ontology[J].Journal of Vibration,Measurement&Diagnosis,2013,33(6):993-997.
[14]李娟莉.基于本体的矿井提升机故障诊断理论与方法[M].北京:国防工业出版社,2015.
[15]孟祥忠,王振起,林存海.基于模糊诊断理论的提升机振动监测诊断系统[J].电子测量技术,2016,39(9):172-175.MENG Xiangzhong,WANG Zhenqi,LIN Cunhai.Hoist vibration monitoring and diagnosis system based on the theory of fuzzy diagnosis[J].Electronic Measurement Technology,2016,39(9):172-175.
[16]李纪.矿山设备性能测定与状态诊断技术[M].北京:煤炭工业出版社,1995.