一种输气管道燃气轮机的综合故障诊断方法
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摘要
基于单一参数的诊断方法无法准确高效地判断燃气轮机的故障状态,故提出了基于燃气轮机振动故障机理和性能故障机理的综合诊断方法。以中国石油西气东输一线某压气站燃驱离心压缩机组LM2500+SAC型燃气轮机运行过程出现异常振动为例,借助在线监测系统数据,基于振动和性能故障机理进行综合诊断,逐项排查异常振动的诱导因素,最终确定燃气轮机异常振动的激励源是轴承旋转封严损坏引起的不平衡量。由此避免了机组继续运行可能造成的严重后果,验证了该综合诊断方法的有效性,为类似故障的监测诊断提供了参考。(图9,参19)
Fault diagnosis method based on single parameter cannot judge the fault states of gas turbines accurately and efficiently,so the comprehensive diagnosis method based on vibration fault mechanism and performance fault mechanism was proposed.Abnormal vibration occured during the operation of LM2500+SAC gas turbine of the gas-driven centrifugal compressor set in one compressor station of the 1 st West-to-East Gas Pipeline of PetroChina. In this paper, the condition monitoring data were analyzed according to the mechanisms of vibration fault and performance fault of gas turbine. Then, the factors inducing the abnormal vibration were checked one by one. And it is ultimately determined that the excitation source to the abnormal vibration of gas turbine is the unbalance caused by the damage of bearing rotating sealing. The serious consequence may be caused by the continuous operation of the failed compressor set was avoided. It is verified that the comprehensive diagnosis method is effective and it can be used as the reference for the monitoring and diagnosis of similar faults.(9 Figures, 19 References)
Fault diagnosis method based on single parameter cannot judge the fault states of gas turbines accurately and efficiently,so the comprehensive diagnosis method based on vibration fault mechanism and performance fault mechanism was proposed.Abnormal vibration occured during the operation of LM2500+SAC gas turbine of the gas-driven centrifugal compressor set in one compressor station of the 1 st West-to-East Gas Pipeline of PetroChina. In this paper, the condition monitoring data were analyzed according to the mechanisms of vibration fault and performance fault of gas turbine. Then, the factors inducing the abnormal vibration were checked one by one. And it is ultimately determined that the excitation source to the abnormal vibration of gas turbine is the unbalance caused by the damage of bearing rotating sealing. The serious consequence may be caused by the continuous operation of the failed compressor set was avoided. It is verified that the comprehensive diagnosis method is effective and it can be used as the reference for the monitoring and diagnosis of similar faults.(9 Figures, 19 References)
引文
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[15]杨国安.信号处理基础[M].北京:中国石化出版社,2012:49-62.YANG G A.Signal processing basics[M].Beijing:China Petrochemical Press,2012:49-62.
[16]李刚,蔡德宇,王帅,等.EMD和SOM神经网络在燃气发动机故障诊断中的应用[J].压缩机技术,2011(2):31-34.LI G,CAI D Y,WANG S,et al.Application of EMD and SOMneural network in gas engine fault diagnosis[J].Compressor Technology,2011(2):31-34.
[17]李刚,刘培军,王帅,等.管道压缩机组视情维护及其发展策略[J].油气储运,2011,30(8):660-662.LI G,LIU P J,WANG S,et al.Maintenance and development strategy of pipeline compressor unit[J].Oil&Gas Storage and Transportation,2011,30(8):660-662.
[18]TAYARANI-BATHAIE S S,VANINI Z N S,KHORASANIK.Dynamic neural network-based fault diagnosis of gas turbine engines[J].Neurocomputing,2014,125:153-165.
[19]李刚,谷思宇,贾东卓,等.燃驱压缩机组性能监测系统的开发[J].油气储运,2018,37(1):52-56.LI G,GU S Y,JIA D Z,et al.Development of performance monitoring system used for turbine-driven compressor set[J].Oil&Gas Storage and Transportation,2018,37(1):52-56.
[2]赫德明,周景权,刘伟旭,等.长输管道燃气轮机输出功率影响因素定量分析[J].现代化工,2016(3):198-200.HE D M,ZHOU J Q,LIU W X,et al.Quantitative analysis of influencing factors on gas turbine output power for long-distance gas pipeline[J].Modern Chemical Industry,2016(3):198-200.
[3]张会生,周登极.燃气轮机可靠性维护理论及应用[M].上海:上海交通大学出版社,2016:50-58.ZHANG H S,ZHOU D J.Reliability maintenance theory and its applications for gas turbine[M].Shanghai:Shanghai Jiaotong University Press,2016:50-58.
[4]杨虞微.现代航空燃气涡轮发动机故障分析与智能诊断关键技术研究[D].南京:南京航空航天大学,2007:10-20.YANG Y W.Research on the key technology of fault analysis and intelligent diagnosis of modern aero-gas turbine engine[D].Nanjing:Nanjing University of Aeronautics and Astronautics,2007:10-20.
[5]赖伟,林国昌,陈聪慧.燃气轮机滚动轴承故障模式及延寿方法[J].航空发动机,2007,33(1):37-41.LAI W,LIN G C,CHEN C H.Failure mode and method of extending life for the rolling bearing in gas turbine[J].Aeroengine,2007,33(1):37-41.
[6]应光耀,童小忠,吴文健.9F燃气机组油膜涡动和油膜振荡的诊断及处理[J].浙江电力,2006,25(1):10-13.YING G Y,TONG X Z,WU W J.Diagnosis and treatment of oil whirling&oil whip on 9F combined-cycle power train[J].Zhejiang Electric Power,2006,25(1):10-13.
[7]姜广义,王娟,姜睿.航空发动机风扇机匣振动故障分析[J].航空发动机,2011,37(5):38-40.JIANG G Y,WANG J,JIANG R.Aeroengine fan casing vibration fault analysis[J].Aeroengine,2011,37(5):38-40.
[8]王玮,吴江桥,赵中刚,等.长输管道燃气轮机现场运行性能计算及评估[J].油气田地面工程,2015,34(10):68-70.WANG W,WU J Q,ZHAO Z G,et al.Calculation and evaluation of field operation performance of gas turbine in long distance pipeline[J].Oil-Gas Field Surface Engineering,2015,34(10):68-70.
[9]康维国,蒋东翔.基于扩展卡尔曼滤波的燃气轮机性能参数估计与故障诊断[J].热能动力工程,2015,30(5):702-707.KANG W G,JIANG D X.Performance parameter estimation and fault diagnosis of gas turbine based on extended Kalman filter[J].Journal of Engineering for Thermal Energy and Power,2015,30(5):702-707.
[10]ZHOU D J,WANG J Y,ZHANG H S,et al.A new gas path fault diagnostic method of gas turbine based on support vector machine[C].Montreal:ASME 2014 International Mechanical Engineering Congress and Exposition,2014:V06AT07A015.
[11]谷思宇,李刚.GE LM2500+SAC型燃气轮机压气机积垢判据的确定[J].油气储运,2016,35(7):763-767.GU S Y,LI G.Indicators for determining compressor fouling of GE LM2500+SAC gas turbines[J].Oil&Gas Storage and Transportation,2016,35(7):763-767.
[12]饶展,张晓茜.设备故障诊断在旋转机械上的应用分析[J].内燃机与配件,2018(16):153-154.RAO Z,ZHANG X Q.Application analysis of fault diagnosis of equipment in rotating machinery[J].Internal Combustion Engine&Parts,2018(16):153-154.
[13]黄现云.旋转机械振动信号处理及故障诊断方法研究[D].南京:南京信息工程大学,2018:20-28.HUANG X Y.Research on signal processing and fault diagnosis of rotating machinery vibration[D].Nanjing:Nanjing University of Information Science&Technology,2018:20-28.
[14]张津.旋转机械振动信号故障诊断研究[J].装备机械,2017(4):55-60.ZHANG J.Research on fault diagnosis of vibration signal of rotating machinery[J].The Magazine on Equipment Machinery,2017(4):55-60.
[15]杨国安.信号处理基础[M].北京:中国石化出版社,2012:49-62.YANG G A.Signal processing basics[M].Beijing:China Petrochemical Press,2012:49-62.
[16]李刚,蔡德宇,王帅,等.EMD和SOM神经网络在燃气发动机故障诊断中的应用[J].压缩机技术,2011(2):31-34.LI G,CAI D Y,WANG S,et al.Application of EMD and SOMneural network in gas engine fault diagnosis[J].Compressor Technology,2011(2):31-34.
[17]李刚,刘培军,王帅,等.管道压缩机组视情维护及其发展策略[J].油气储运,2011,30(8):660-662.LI G,LIU P J,WANG S,et al.Maintenance and development strategy of pipeline compressor unit[J].Oil&Gas Storage and Transportation,2011,30(8):660-662.
[18]TAYARANI-BATHAIE S S,VANINI Z N S,KHORASANIK.Dynamic neural network-based fault diagnosis of gas turbine engines[J].Neurocomputing,2014,125:153-165.
[19]李刚,谷思宇,贾东卓,等.燃驱压缩机组性能监测系统的开发[J].油气储运,2018,37(1):52-56.LI G,GU S Y,JIA D Z,et al.Development of performance monitoring system used for turbine-driven compressor set[J].Oil&Gas Storage and Transportation,2018,37(1):52-56.
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