煤矿带式输送机健康诊断方法
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摘要
针对基于多传感器信息融合的煤矿带式输送机健康诊断方法运用D-S证据理论在处理冲突证据时失效的问题,提出了一种基于模糊证据理论的带式输送机健康诊断方法。该方法首先利用多种传感器采集带式输送机信息,并根据隶属度函数获取基本概率赋值,从而提取信息特征;然后通过对冲突证据进行修正并应用D-S证据理论的合成规则,实现基于模糊证据理论的信息融合;最后根据决策规则判断带式输送机运行状态。通过实例验证了该方法的有效性。
In view of problem of invalidation in dealing with conflicting evidence of D-S evidence theory used in health diagnosis method of coal mine belt conveyor based on multi-sensor information fusion,a health diagnosis method of coal mine belt conveyor based on fuzzy evidence theory was proposed.Firstly,information of belt conveyor are collected by use of multi-sensor,and basic probability assignments are obtained according to membership function,so as to extract information feature.Then information fusion based on fuzzy evidence theory is realized by modifying conflicting evidence and applying synthesis rule of D-S evidence theory.Finally,running state of belt conveyor is judged according to decision rule.Effectiveness of the method is verified by an example.
In view of problem of invalidation in dealing with conflicting evidence of D-S evidence theory used in health diagnosis method of coal mine belt conveyor based on multi-sensor information fusion,a health diagnosis method of coal mine belt conveyor based on fuzzy evidence theory was proposed.Firstly,information of belt conveyor are collected by use of multi-sensor,and basic probability assignments are obtained according to membership function,so as to extract information feature.Then information fusion based on fuzzy evidence theory is realized by modifying conflicting evidence and applying synthesis rule of D-S evidence theory.Finally,running state of belt conveyor is judged according to decision rule.Effectiveness of the method is verified by an example.
引文
[1]黄民,魏任之.矿用钢绳芯带式输送机实时工况监测与故障诊断技术[J].煤炭学报,2005,30(2):245-250.HUANG Min,WEI Renzhi.Real time monitoring techniques and fault diagnosis of mining steel cord belt conveyors[J].Journal of China Coal Society,2005,30(2):245-250.
[2]王金华.井下带式输送机煤流控制系统现状及发展趋势[J].工矿自动化,2015,41(3):32-34.WANG Jinhua.Current situation and development trend of coal flow control system of belt conveyor[J].Industry and Mine Automation,2015,41(3):32-34.
[3]徐琰珂,梁晓庚,贾晓洪.利用模糊证据理论的信息融合方法及其应用[J].哈尔滨工业大学学报,2012,44(3):107-111.XU Yanke,LIANG Xiaogeng,JIA Xiaohong.Information fusion based on fuzzy evidence theory and its application in target recognition[J].Journal of Harbin Institute of Technology,2012,44(3):107-111.
[4]任海东.基于D-S证据理论的带式输送机故障诊断[J].煤炭技术,2017,36(11):273-275.REN Haidong.Fault diagnosis of belt conveyor based on D-S evidence theory[J].Coal Technology,2017,36(11):273-275.
[5]吴定会,王莉,纪志成.信息融合在带式输送机故障诊断中的应用[J].控制工程,2014,21(4):483-486.WU Dinghui,WANG Li,JI Zhicheng.Application of information fusion technology in fault diagnosis of belt conveyor[J].Control Engineering of China,2014,21(4):483-486.
[6]胡伟,李欧.模糊信息融合在带式输送机故障诊断中的应用[J].工矿自动化,2013,39(5):48-51.HU Wei,LI Ou.Application of fuzzy information fusion in fault diagnosis of belt conveyor[J].Industry and Mine Automation,2013,39(5):48-51.
[7]杨棉绒,张鑫.多传感器模糊信息融合算法在煤矿瓦斯监测中的应用[J].煤炭技术,2013,32(7):132-133.YANG Mianrong,ZHANG Xin.Application of multisensor fuzzy information fusion algorithm in coal mine gas monitoring[J].Coal Technology,2013,32(7):132-133.
[8]韩峰,杨万海,袁晓光.基于模糊集合的证据理论信息融合方法[J].控制与决策,2010,25(3):449-452.HAN Feng,YANG Wanhai,YUAN Xiaoguang.Evidence theory information fusion method based on fuzzy set[J].Control and Decision,2010,25(3):449-452.
[9]王新,马庆林.一种新型的基本概率赋值分配函数获取方法及其应用[C]//第29届中国控制会议,北京,2010:4037-4040.
[10]胡海亮,钟求喜,刘浏.基于迭代合成的D-S证据理论改进方法[J].计算机应用研究,2016,33(10):2985-2987.HU Hailiang,ZHONG Qiuxi,LIU Liu.Improved method to D-S evidence theory based on iterative synthesis[J].Application Research of Computers,2016,33(10):2985-2987.
[11] JOUSSELME A L,MAUPIN P.Distances in evidence theory:comprehensive survey and generalizations[J].International Journal of Approximate Reasoning,2012,53(2):118-145.
[12]刘兵,李辉,邢刚.基于加权证据理论的模糊信息融合目标识别[J].计算机工程,2012,38(15):172-174.LIU Bing,LI Hui,XING Gang.Fuzzy information fusion target recognition based on weighted evidence theory[J].Computer Engineering,2012,38(15):172-174.
[13]田鹤,韩刚.信息融合技术在带式输送机故障诊断中的应用[J].矿山机械,2011,39(3):47-50.TIAN He,HAN Gang.Application of information fusion technology to fault diagnosis of belt conveyors[J].Mining and Processing Equipment,2011,39(3):47-50.
[14]璩晶磊,李少波,张成龙.基于模糊证据理论的多传感器数据融合算法[J].仪表技术与传感器,2017(10):118-122.QU Jinglei,LI Shaobo,ZHANG Chenglong.Multisensor data fusion algorithm based on fuzzy evidence theory[J].Instrument Technique and Sensor,2017(10):118-122.
[15]张国栋,祁瑞敏.基于信息融合的煤矿绞车健康诊断系统设计[J].工矿自动化,2017,43(6):76-79.ZHANG Guodong,QI Ruimin.Design of health diagnosis system of coal mine winch based on informationfusion[J]. IndustryandMine Automation,2017,43(6):76-79.
[2]王金华.井下带式输送机煤流控制系统现状及发展趋势[J].工矿自动化,2015,41(3):32-34.WANG Jinhua.Current situation and development trend of coal flow control system of belt conveyor[J].Industry and Mine Automation,2015,41(3):32-34.
[3]徐琰珂,梁晓庚,贾晓洪.利用模糊证据理论的信息融合方法及其应用[J].哈尔滨工业大学学报,2012,44(3):107-111.XU Yanke,LIANG Xiaogeng,JIA Xiaohong.Information fusion based on fuzzy evidence theory and its application in target recognition[J].Journal of Harbin Institute of Technology,2012,44(3):107-111.
[4]任海东.基于D-S证据理论的带式输送机故障诊断[J].煤炭技术,2017,36(11):273-275.REN Haidong.Fault diagnosis of belt conveyor based on D-S evidence theory[J].Coal Technology,2017,36(11):273-275.
[5]吴定会,王莉,纪志成.信息融合在带式输送机故障诊断中的应用[J].控制工程,2014,21(4):483-486.WU Dinghui,WANG Li,JI Zhicheng.Application of information fusion technology in fault diagnosis of belt conveyor[J].Control Engineering of China,2014,21(4):483-486.
[6]胡伟,李欧.模糊信息融合在带式输送机故障诊断中的应用[J].工矿自动化,2013,39(5):48-51.HU Wei,LI Ou.Application of fuzzy information fusion in fault diagnosis of belt conveyor[J].Industry and Mine Automation,2013,39(5):48-51.
[7]杨棉绒,张鑫.多传感器模糊信息融合算法在煤矿瓦斯监测中的应用[J].煤炭技术,2013,32(7):132-133.YANG Mianrong,ZHANG Xin.Application of multisensor fuzzy information fusion algorithm in coal mine gas monitoring[J].Coal Technology,2013,32(7):132-133.
[8]韩峰,杨万海,袁晓光.基于模糊集合的证据理论信息融合方法[J].控制与决策,2010,25(3):449-452.HAN Feng,YANG Wanhai,YUAN Xiaoguang.Evidence theory information fusion method based on fuzzy set[J].Control and Decision,2010,25(3):449-452.
[9]王新,马庆林.一种新型的基本概率赋值分配函数获取方法及其应用[C]//第29届中国控制会议,北京,2010:4037-4040.
[10]胡海亮,钟求喜,刘浏.基于迭代合成的D-S证据理论改进方法[J].计算机应用研究,2016,33(10):2985-2987.HU Hailiang,ZHONG Qiuxi,LIU Liu.Improved method to D-S evidence theory based on iterative synthesis[J].Application Research of Computers,2016,33(10):2985-2987.
[11] JOUSSELME A L,MAUPIN P.Distances in evidence theory:comprehensive survey and generalizations[J].International Journal of Approximate Reasoning,2012,53(2):118-145.
[12]刘兵,李辉,邢刚.基于加权证据理论的模糊信息融合目标识别[J].计算机工程,2012,38(15):172-174.LIU Bing,LI Hui,XING Gang.Fuzzy information fusion target recognition based on weighted evidence theory[J].Computer Engineering,2012,38(15):172-174.
[13]田鹤,韩刚.信息融合技术在带式输送机故障诊断中的应用[J].矿山机械,2011,39(3):47-50.TIAN He,HAN Gang.Application of information fusion technology to fault diagnosis of belt conveyors[J].Mining and Processing Equipment,2011,39(3):47-50.
[14]璩晶磊,李少波,张成龙.基于模糊证据理论的多传感器数据融合算法[J].仪表技术与传感器,2017(10):118-122.QU Jinglei,LI Shaobo,ZHANG Chenglong.Multisensor data fusion algorithm based on fuzzy evidence theory[J].Instrument Technique and Sensor,2017(10):118-122.
[15]张国栋,祁瑞敏.基于信息融合的煤矿绞车健康诊断系统设计[J].工矿自动化,2017,43(6):76-79.ZHANG Guodong,QI Ruimin.Design of health diagnosis system of coal mine winch based on informationfusion[J]. IndustryandMine Automation,2017,43(6):76-79.