基于统计模式分析的多变量连续过程故障检测
针对一些批处理过程中,如同步批轨迹处理和多峰分布等问题,提出了一种基于统计模量（statistics pattern analysis,SPA）分析连续过程的故障诊断方法。FD-SPA和MPCA的显著差别是前者的监测对象是批次变量的统计特征,而后者监控过程变量。MPCA通过分析过程变量的方差—协方差进行故障检测,在SPA中,既要统计过程变量的均值与方差,又要统计过程变量间的协方差结构、偏度、峭度、自相关和互相关性。提出了一种基于滑动窗口的统计模量方法监测非线性的连续过程,使故障检测的准确性与可靠性得到提高。通过在TE过程中与传统的MPCA和KNN方法对比,验证了此方法的有效性。...
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| Published in | 计算机应用研究 Vol. 32; no. 7; pp. 2060 - 2064 |
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| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
沈阳化工大学信息工程学院,沈阳,110142
2015
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1001-3695 |
| DOI | 10.3969/j.issn.1001-3695.2015.07.035 |
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| Abstract | 针对一些批处理过程中,如同步批轨迹处理和多峰分布等问题,提出了一种基于统计模量（statistics pattern analysis,SPA）分析连续过程的故障诊断方法。FD-SPA和MPCA的显著差别是前者的监测对象是批次变量的统计特征,而后者监控过程变量。MPCA通过分析过程变量的方差—协方差进行故障检测,在SPA中,既要统计过程变量的均值与方差,又要统计过程变量间的协方差结构、偏度、峭度、自相关和互相关性。提出了一种基于滑动窗口的统计模量方法监测非线性的连续过程,使故障检测的准确性与可靠性得到提高。通过在TE过程中与传统的MPCA和KNN方法对比,验证了此方法的有效性。 |
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| AbstractList | TP277; 针对一些批处理过程中,如同步批轨迹处理和多峰分布等问题,提出了一种基于统计模量(statistics pattern analysis,SPA)分析连续过程的故障诊断方法.FD-SPA和MPCA的显著差别是前者的监测对象是批次变量的统计特征,而后者监控过程变量.MPCA通过分析过程变量的方差—协方差进行故障检测,在SPA中,既要统计过程变量的均值与方差,又要统计过程变量间的协方差结构、偏度、峭度、自相关和互相关性.提出了一种基于滑动窗口的统计模量方法监测非线性的连续过程,使故障检测的准确性与可靠性得到提高.通过在TE过程中与传统的MPCA和KNN方法对比,验证了此方法的有效性. 针对一些批处理过程中,如同步批轨迹处理和多峰分布等问题,提出了一种基于统计模量（statistics pattern analysis,SPA）分析连续过程的故障诊断方法。FD-SPA和MPCA的显著差别是前者的监测对象是批次变量的统计特征,而后者监控过程变量。MPCA通过分析过程变量的方差—协方差进行故障检测,在SPA中,既要统计过程变量的均值与方差,又要统计过程变量间的协方差结构、偏度、峭度、自相关和互相关性。提出了一种基于滑动窗口的统计模量方法监测非线性的连续过程,使故障检测的准确性与可靠性得到提高。通过在TE过程中与传统的MPCA和KNN方法对比,验证了此方法的有效性。 |
| Author | 逄玉俊 李娜 李元 张成 |
| AuthorAffiliation | 沈阳化工大学信息工程学院,沈阳110142 |
| AuthorAffiliation_xml | – name: 沈阳化工大学信息工程学院,沈阳,110142 |
| Author_FL | Li Na Pang Yujun Li Yuan Zhang Cheng |
| Author_FL_xml | – sequence: 1 fullname: Pang Yujun – sequence: 2 fullname: Li Na – sequence: 3 fullname: Li Yuan – sequence: 4 fullname: Zhang Cheng |
| Author_xml | – sequence: 1 fullname: 逄玉俊 李娜 李元 张成 |
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| Copyright | Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
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| DocumentTitleAlternate | Study of fault-detection method in continuous process based on statistical features analysis |
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| EndPage | 2064 |
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| Keywords | statistical pattern 统计模量 continuous process 连续过程 多向主元分析 fault detection 故障检测 multiway principal component analysis |
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| Notes | 51-1196/TP continuous process; statistical pattern; multiway principal component analysis; fault detection Pang Yujun, Li Na, Li Yuan, Zhang Cheng （ College of Information Engineering, Shenyang University of Chemical Technology, Shenyang 110142, China） This paper proposed a new method to monitor continuous processes based on the statistics pattern analysis （SPA） framework. It developed the SPA framework to address some challenges associated with batch process monitoring, such as unsynchronized batch trajectories and muhimodal distribution. The major difference between the multiway principal component analysis （MPCA） and SPA was that MPCA monitored process variables while SPA monitored the statistics of process variables. In other words, MPCA examined the variance-covariance of the process variables to perform fault detection while SPA examined the variance- covariance of the process variable statistics （e. g. , mean, variance, autoeorrelation, cross-correlation, etc. ）. It proposed a window-based SPA method to a |
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| Publisher | 沈阳化工大学信息工程学院,沈阳,110142 |
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| SubjectTerms | 多向主元分析 故障检测 统计模量 连续过程 |
| Title | 基于统计模式分析的多变量连续过程故障检测 |
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