基于相对变化分析的多模态卷烟制叶丝段故障监测
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摘要
为解决卷烟制叶丝段中采用传统单变量统计过程控制方法故障监测效果欠佳等问题,通过对制叶丝段关键设备的运行特性分析,提出了一种基于相对变化分析的故障监测方法。该方法采用属性展开方式将具有批次、时间和属性特点的三维数据展开成二维数据,采用主元分析方法进行参考模态的统计建模和故障监测,根据备选模态的潜在过程波动以及与参考模态的相对变化,将参考模态监测模型的主元子空间和残差子空间分别进行分解,在分解后的4个子空间中进行备选模态的统计建模和故障监测。基于设备实际运行数据进行离线验证,结果表明:与彩虹图、过程能力指数等传统故障监测方法相比,该方法能更深入地揭示不同模态、不同批次间的过程变量动态性以及变量间关联关系的变化,能够及时、有效地检测出设备故障。
引文
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[23]Zhao C H.Concurrent phase partition between-mode statistical analysis for multimode and multiphase batch process monitoring[J].AICHE Journal,2014,60(2):559-573.
[2]张敏,童亿刚,戴志渊,等.SPC技术在制丝质量管理中的初步应用[J].烟草科技,2004,37(9):10-11.
[3]黄胜,李建辉,张永川.长沙卷烟厂SPC系统的应用实践[J].中国烟草学报,2008,14(S1):14-17.
[4]Mishra B,Dangayach G S.Performance improvement through statistical process control:a longitudinal study[J].International Journal of Globalization and Small Business,2009,3(1):55-72.
[5]李文泉,赵文田,李文斌.统计过程控制技术SPC在烟草制丝生产中的应用[J].机械工程与自动化,2009,(5):116-118.
[6]罗江,刘强斌.SPC系统在卷烟工业企业质量管理中的应用实践[J].产业经济,2011,(3):67-72.
[7]纪盛强,程晶晶,李郡.基于SPC和神经网络的卷烟制丝生产质量监控方法研究[J].工业控制计算机,2011,24(12):65-68.
[8]李铁军,杨得强,李强.SPC系统在卷烟制丝工艺质量控制的应用[J].中国质量,2013,(4):87-88.
[9]朱敏,王培琛,张学礼,等.基于统计过程控制的卷烟品控系统[J].PLC&FA,2014,(3):58-62.
[10]钱杰,徐进,季琦,等.制造执行系统在烟草企业中的应用[J].机械制造与自动化,2014,43(2):147-149.
[11]Wang H,Chai T Y,Ding J L,et al.Data driven fault diagnosis and fault tolerant control:some advances and possible new directions[J].ACTA AUTOMATICA SINICA,2009,35(6):739-747.
[12]刘强,柴天佑,秦泗钊,等.基于数据和知识的工业过程监视及故障诊断综述[J].控制与决策,2010,25(6):801-807.
[13]杨锦忠,宋希云.多元统计分析及其在烟草学中的应用[J].中国烟草学报,2014,20(5):134-138.
[14]邵惠芳,赵昕宇,许自成,等.基于Fisher判别分析的烤烟感官质量与工业应用价值的关系研究[J].中国烟草学报,2011,17(6):13-18.
[15]李伟,冯洪涛,周桂圆,等.Hotelling T2结合多组分NIR校正模型在卷烟生产过程质量监测中的应用[J].烟草科技,2014,47(7):5-9.
[16]Zhao S J,Zhang J,Xu Y M.Monitoring of processes with multiple operating modes through multiple principal component analysis models[J].Industrial&Engineering Chemistry Research,2004,43(22):7025-7035.
[17]Zhao S J,Zhang J,Xu Y M.Performance monitoring of processes with multiple operating modes through multiple PLS models[J].Journal of Process Control,2006,16(7):763-772.
[18]Lee Y H,Jin H D,Han C H.On-line process state classification for adaptive monitoring[J].Industrial&Engineering Chemistry Research,2006,45(9):3095-3107.
[19]Camacho J,Pico J.Online monitoring of batch processes using multi-phase principal component analysis[J].Journal of Process Control,2006,16(10):1021-1035.
[20]Xie X,Shi H B.Dynamic multimode process modeling and monitoring using adaptive Gaussian mixture models[J].Industrial and Engineering Chemistry Research,2012,51(15):5497-5505.
[21]Zhang Y W,Wang C,Lu R Q.Modeling and monitoring of multimode process based on subspace separation[J].Chemical Engineering Research and Design,2013,91(5):831-842.
[22]Zhao C H,Yao Y,Gao F R,Wang F L.Statistical Analysis and Online Monitoring for Multimode Processes with Between-mode Transitions[J].Chemical Engineering Science.2010,65(22):5961-5975.
[23]Zhao C H.Concurrent phase partition between-mode statistical analysis for multimode and multiphase batch process monitoring[J].AICHE Journal,2014,60(2):559-573.
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