基于比例风险模型的转辙机状态-机会维修时机研究
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摘要
针对传统转辙机故障事后维修和定时维修模式存在的"维修过剩"和"维修不足"等对维修时机把握不清的问题,综合考虑设备的监测数据、历史故障数据等多类信息建立表征设备劣化特征,建立比例风险预测模型。设定比例风险模型的维修阈值和维修门限值,实施转辙机的状态-机会维修。从设备的最大可用性考虑优化调整系统被监测多部件的最小维修时间来确定最佳维修时机。以某电务段S700K型转辙机3个关键部件振动状态监测值进行维修时机的仿真验证,结果表明该方法具有可行性与有效性。
The problem of maintenance surplus and insufficient maintenance in the maintenance and repair of the traditional switch machine is not clear.A proportional hazards prediction model was established based on the comprehensive consideration of the monitoring data of the equipment,historical fault data and other information.By setting the maintenance threshold of the proportional hazards model and the maintenance threshold,the state of the switch machine was condition-opportunity maintenance.Once again,the optimum time of maintenance was determined by optimizing the minimum maintenance time of the multi-component by considering the maximum availability of the equipment.The simulation verification of the vibration state monitoring value of the three key components of the S700 K switch machine in an electrical section was carried out.The results show that the method is feasible and effective.
The problem of maintenance surplus and insufficient maintenance in the maintenance and repair of the traditional switch machine is not clear.A proportional hazards prediction model was established based on the comprehensive consideration of the monitoring data of the equipment,historical fault data and other information.By setting the maintenance threshold of the proportional hazards model and the maintenance threshold,the state of the switch machine was condition-opportunity maintenance.Once again,the optimum time of maintenance was determined by optimizing the minimum maintenance time of the multi-component by considering the maximum availability of the equipment.The simulation verification of the vibration state monitoring value of the three key components of the S700 K switch machine in an electrical section was carried out.The results show that the method is feasible and effective.
引文
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[16] RAO A N,BHADURY B.Opportunistic Maintenance of Multi-equipment System:A Case Study[J].Quality & Reliability Engineering International,2000,16(6):487-500.
[2] 李娜,董海鹰.基于D—S证据理论信息融合的轨道电路故障诊断方法研究[J].铁道科学与工程学报,2012,9(6):107-112.LI N,DONG H Y.Research on Track Circuit Fault Diagnosis Method Based on D-S Evidence Theory Information Fusion[J].Journal of Railway Science and Engineering,2012,9(6):107-112.
[3] 王瑞峰,陈旺斌.基于灰色神经网络的S700K转辙机故障诊断方法研究[J].铁道学报,2016,38(6):68-72.WANG R F,CHEN W B.Research on Fault Diagnosis Method of S700K Switch Machine Based on Grey Neural Network[J].Journal of the China Railway Society,2016,38(6):68-72.
[4] 伏玉明,刘伯鸿,宋爽.基于模糊综合评判的转辙机健康评估研究[J].铁道科学与工程学报,2017,14(5):1070-1076.FU Y M,LIU B H,SONG S.Research on Health Assessment Methods for Switch Machine Based on Fuzzy Comprehensive Evaluation[J].Journal of Railway Science and Engineering,2017,14(5):1070-1076.
[5] 米根锁,张凤霞,魏蕾.基于剩余寿命的铁路轨道电路调整型维修方法研究[J].铁道学报,2015(4):69-74.MI G S,ZHANG F X,WEI L.Research on Method of Modulation Maintenance in Railway Track Circuits Based on Residual Life[J].Journal of the China Railway Society,2015(4):69-74.
[6] 赵林海,冉义奎,穆建成.基于遗传算法的无绝缘轨道电路故障综合诊断方法[J].中国铁道科学,2010,31(3):107-114.ZHAO L H,RAN Y K,MU J C.A Comprehensive Fault Diagnosis Method for Jointless Track Circuit Based on Genetic Algorithm[J].China Railway Science,2010,31(3):107-114.
[7] 汪倩,周振威,陆裕东,等.转辙机的故障预测与健康管理技术[J].都市快轨交通,2015,28(1):58-61.WANG Q,ZHOU Z W,LU Y D,et al.Prognostics and Health Management Technology of Point Machine[J].Urban Rapid Rail Transit,2015,28(1):58-61
[8] NICOLAI R P,DEKKER R.Optimal Maintenance of Multi-component Systems:A Review[Z].Complex System Maintenance Handbook,2008:263-286.
[9] 王少华,张耀辉,韩小孩.基于比例风险模型的装备状态维修决策方法[J].火炮发射与控制学报,2014(4):67-72.WANG S H,ZHANG Y H,HAN X H.Equipment Condition-based Maintenance Decision-making Method Based on Proportional Hazard Model[J].Journal of Artillery Launch & Control,2014(4):67-72.
[10] 满强,陈丽,夏良华,等.基于比例风险模型的状态维修决策研究[J].装备指挥技术学院学报,2008,19(6):36-39.MAN Q,CHEN L,XIA L H,et al.Study on the Proportional Hazards Model Applied to CBM[J].Journal of the Academy of Equipment Command & Technology,2008,19(6):36-39.
[11] 曾庆虎.机械动力传动系统关键部件故障预测技术研究[D].长沙:国防科学技术大学,2010.
[12] 张凤霞,米根锁.基于健康指数的轨道电路设备寿命预测方法的研究[J].铁道学报,2015,37(12):61-66.ZHANG F X,MI G S.Research on Life Prediction Methods for Track Circuit Equipment Based on Health Index[J].Journal of the China Railway Society,2015,37(12):61-66.
[13] 赵洪山,张路朋.基于可靠度的风电机组预防性机会维修策略[J].中国电机工程学报,2014,34(22):3777-3783.ZHAO H S,ZHANG L P.Preventive Opportunity Maintenance Strategy for Wind Turbines Based on Reliability[J].Proceedings of the CSEE,2014,34(22):3777-3783.
[14] 周林,赵杰,冯广飞.装备故障预测与健康管理技术[M].北京:国防工业出版社,2015.
[15] 王英.设备状态维修系统结构与决策模型研究[D].哈尔滨:哈尔滨工业大学,2007.
[16] RAO A N,BHADURY B.Opportunistic Maintenance of Multi-equipment System:A Case Study[J].Quality & Reliability Engineering International,2000,16(6):487-500.