Multivariate statistical process control (MSPC) has been successfully applied to performance monitoring and fault diagnosis for chemical processes However, traditional MSPC are based upon the assumption that the separ...Multivariate statistical process control (MSPC) has been successfully applied to performance monitoring and fault diagnosis for chemical processes However, traditional MSPC are based upon the assumption that the separated latent variables must be subject to normal probability distribution, which sometimes can not be satisfied In this paper, a novel method combining principal component analysis (PCA) and independent component analysis (ICA) is proposed to model non Gaussian data from industry and improve the monitoring performance of process In order to deal with the uncertainty of probability distribution within the independent component, a kind of classifier referred to as support vector classifier is used for classifying the abnormal modes Simulation result for a nonisothermal continuous stirred tank reactor (CSTR) by the presented method verifies the effectiveness of ICA based展开更多
精细化工产品的市场需求快速多变,产品更新换代快,使得精细化工生产过程一般采取小批量、多品种生产,生产过程多为间歇或半连续过程,时变性、非线性强,生产过程的工艺流程复杂,操作步骤繁杂,劳动强度大;精细化工生产过程的工艺介质多为...精细化工产品的市场需求快速多变,产品更新换代快,使得精细化工生产过程一般采取小批量、多品种生产,生产过程多为间歇或半连续过程,时变性、非线性强,生产过程的工艺流程复杂,操作步骤繁杂,劳动强度大;精细化工生产过程的工艺介质多为有一定毒性、腐蚀性和易燃易爆性的化学品,过程运行危险性大:这些特点使得精细化工生产过程更难以控制,综合自动化水平普遍较低。为了提高精细化工生产过程的综合自动化水平,需根据精细化工生产过程的特点及其控制需求,进行精细化工生产过程控制技术的研究和应用。目前,精细化工过程控制技术的主要发展动向为:从常规仪表控制向计算机控制、集散式控制系统(Distributed Control System,DCS)控制发展;从简单的顺序控制、程序控制向基于ISA SP88间歇过程控制标准的自动批量生产控制发展;从人工控制、常规PID控制向先进的批次-批次迭代学习优化控制发展:从简单工艺参数的控制向生产工况和生产质量的综合性统计过程控制发展:从简单的工艺参数越限连锁报警向综合性安全保护控制和在线实时非正常工况管理发展。展开更多
为了满足传统的统计过程控制理论中统计量彼此独立的基本假设,研究了多元自相关过程的残差T2控制图的控制方法及其控制性能。针对一般多元自相关过程,在参数已知的条件下,讨论了多元自相关过程的残差T2控制图,给出多元自相关过程偏移量...为了满足传统的统计过程控制理论中统计量彼此独立的基本假设,研究了多元自相关过程的残差T2控制图的控制方法及其控制性能。针对一般多元自相关过程,在参数已知的条件下,讨论了多元自相关过程的残差T2控制图,给出多元自相关过程偏移量的定义。通过M on te C arlo模拟,得出该控制图在不同偏移量时的平均链长,在残差T2控制图的适用范围内给出平均链长与偏移量之间的经验公式。结果表明,残差T2控制图可以有效控制出现大偏移的多元自相关过程。展开更多
文摘Multivariate statistical process control (MSPC) has been successfully applied to performance monitoring and fault diagnosis for chemical processes However, traditional MSPC are based upon the assumption that the separated latent variables must be subject to normal probability distribution, which sometimes can not be satisfied In this paper, a novel method combining principal component analysis (PCA) and independent component analysis (ICA) is proposed to model non Gaussian data from industry and improve the monitoring performance of process In order to deal with the uncertainty of probability distribution within the independent component, a kind of classifier referred to as support vector classifier is used for classifying the abnormal modes Simulation result for a nonisothermal continuous stirred tank reactor (CSTR) by the presented method verifies the effectiveness of ICA based
文摘精细化工产品的市场需求快速多变,产品更新换代快,使得精细化工生产过程一般采取小批量、多品种生产,生产过程多为间歇或半连续过程,时变性、非线性强,生产过程的工艺流程复杂,操作步骤繁杂,劳动强度大;精细化工生产过程的工艺介质多为有一定毒性、腐蚀性和易燃易爆性的化学品,过程运行危险性大:这些特点使得精细化工生产过程更难以控制,综合自动化水平普遍较低。为了提高精细化工生产过程的综合自动化水平,需根据精细化工生产过程的特点及其控制需求,进行精细化工生产过程控制技术的研究和应用。目前,精细化工过程控制技术的主要发展动向为:从常规仪表控制向计算机控制、集散式控制系统(Distributed Control System,DCS)控制发展;从简单的顺序控制、程序控制向基于ISA SP88间歇过程控制标准的自动批量生产控制发展;从人工控制、常规PID控制向先进的批次-批次迭代学习优化控制发展:从简单工艺参数的控制向生产工况和生产质量的综合性统计过程控制发展:从简单的工艺参数越限连锁报警向综合性安全保护控制和在线实时非正常工况管理发展。
文摘为了满足传统的统计过程控制理论中统计量彼此独立的基本假设,研究了多元自相关过程的残差T2控制图的控制方法及其控制性能。针对一般多元自相关过程,在参数已知的条件下,讨论了多元自相关过程的残差T2控制图,给出多元自相关过程偏移量的定义。通过M on te C arlo模拟,得出该控制图在不同偏移量时的平均链长,在残差T2控制图的适用范围内给出平均链长与偏移量之间的经验公式。结果表明,残差T2控制图可以有效控制出现大偏移的多元自相关过程。
