引用本文:齐咏生,王普,高学金.基于核主元分析–主元分析的多阶段间歇过程故障监测与诊断[J].控制理论与应用,2012,29(6):754~764.[点击复制]
QI Yong-sheng,WANG Pu,GAO Xue-jin.Fault detection and diagnosis of multiphase batch process based on kernel principal component analysis-principal component analysis[J].Control Theory and Technology,2012,29(6):754~764.[点击复制]
基于核主元分析–主元分析的多阶段间歇过程故障监测与诊断
Fault detection and diagnosis of multiphase batch process based on kernel principal component analysis-principal component analysis
摘要点击 2296  全文点击 1922  投稿时间:2011-04-05  修订日期:2011-10-08
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DOI编号  10.7641/j.issn.1000-8152.2012.6.CCTA110341
  2012,29(6):754-764
中文关键词  主元分析  核主元分析  故障诊断  间歇过程
英文关键词  principal component analysis  kernel principal component analysis  fault diagnosis  batch process
基金项目  国家自然科学基金资助项目(61174109, 60704036); 高等学校博士学科点专项科研基金资助项目(20101103110009); 内蒙古工业大学科学研究资助项目(ZS0201037).
作者单位E-mail
齐咏生* 内蒙古工业大学 电力学院 qyslyt@163.com 
王普 北京工业大学 电子信息与控制工程学院  
高学金 北京工业大学 电子信息与控制工程学院  
中文摘要
      具有过渡特性的多阶段间歇过程故障监测是一个复杂的问题, 既需要考虑稳定阶段下的故障监测, 也需要考虑不同阶段间的过渡故障监测. 为克服传统硬划分方法导致误警和漏报率高的缺陷, 同时也为实现更加精确、有效的故障监测与诊断, 提出一套完整的基于核主元分析–主元分析(KPCA–PCA)的多阶段间歇过程故障监测与诊断策略. 该方法依据数据相似度实现阶段划分, 定义模糊隶属度辨识相邻阶段间的过渡, 最后对稳定阶段和过渡过程分别建立具有时变协方差的PCA和KPCA故障监测与诊断模型. 通过对青霉素发酵过程的仿真平台及工业应用研究表明, 该方法具有更可靠的监控性能, 能及时、准确的检测出过程中存在的异常情况.
英文摘要
      Fault detection in multiple phase processes is a complicated problem, because it is needed in both the steady phase and the transition from phase to phase. To overcome the hard-partition and misclassification problems, and also to monitor batch processes more accurately and efficiently, we propose a novel strategy for fault monitoring and diagnosing in batch processes based on the kernel principal component analysis-principal component analysis (KPCA–PCA). In this work, a phase division algorithm is designed based on the similarity index between different time-slice data matrices of batch processes, following by a fuzzy membership grade transition identification step. The steady phase ranges and the transition ranges are then modeled by PCA with time-varying covariance structures and KPCA separately. Results of simulation study and industrial application to penicillin fermentation process clearly demonstrate the effectiveness and feasibility of the proposed method, which detects various faults more promptly with desirable reliability.