期刊文献+

基于累积和等距映射的缓变故障检测方法 预览 被引量:1

RAMP FAULT DETECTION METHOD BASED ON CUSUM-ISOMAP
在线阅读 下载PDF
收藏 分享 导出
摘要 针对化工过程存在的缓变微小故障,提出一种基于累积和等距离映射(CUSUM-ISOMAP)的多变量过程故障检测方法。该方法首先运用累积和控制图的思想,分别对每一个变量计算均值偏差累积和及方差偏差累积和,之后建立扩展增广矩阵,对增广数据运用基于IS0MAP的降维特征提取算法建立统计量进行故障检测。传统的IS0MAP算法无法获取输入输出数据之间的映射关系,不能处理新的采样数据。引入核岭回归算法获得新采样点的降维输出。CSTR过程的仿真结果表明了算法对过程微小故障实施故障检测的有效性。 In order to detect the ramp minor fault in chemical processes,we proposed a new multivariable process fault detection method which is based on CUSUM-ISOMAP.It first calculates the mean deviation cumulative sum and variance deviation cumulative sum for each variable using the idea of CUSUM control chart,and then creates extended augmented matrix and employs the ISOMAP-based dimensionality reduction feature extraction algorithm on the augmented data to set up statistics and carry out fault detection.Traditional ISOMAP algorithm is unable to get the mapping relationship between inputs and outputs,so it cannot handle the new sampling data.In the paper we introduce Kernel ridge regression algorithm to obtain the dimensionality-reduced outputs of the new sampling data.Simulation result of CSTR process shows the effectiveness of the method proposed in the paper on exerting fault detection for minor process fault.
作者 谷善茂 张妮 刘云龙 Gu Shanmao;Zhang Ni;Liu Yunlong;College of Information and Control Engineering,Weifang University;
出处 《计算机应用与软件》 CSCD 2016年第6期251-254,305共5页 Computer Applications and Software
基金 国家自然科学基金项目(61403283) .
关键词 累积和控制图 ISOMAP算法 核岭回归 缓变故障 故障检测 CUSUM control chart ISOMAP algorithm Kernel ridge regress Ramp fault Fault detection
  • 相关文献

参考文献14

  • 1Venkatasubramanian V,Rengaswamy R,Kavuri S N,et al.A review of process fault detection and diagnosis Part III: process history basedmethods [J].Computers and Chemical Engineering,2003 ,27(3):327-346. 被引量:1
  • 2Qin S.Survey on data-driven industrial process monitoring and diagnosis[J].Annual Reviews in Control,2012 ,36(2):220-234. 被引量:1
  • 3韩利强,陈泽华,曹长青,张志远.TEP故障诊断方法研究[J].计算机应用与软件,2014,31(7):82-85. 被引量:1
  • 4Russell L H.Fault detection and diagnosis in industrial system [M].London:Springer Verlag Press,2003. 被引量:1
  • 5Jiang Q C.Fault detection and diagnosis in chemical processes using sensitive principal component analysis [J].Industrial & Engineering Chemistry Research,2013,52(4):1635-1644. 被引量:1
  • 6Shao J D,Rong G.Nonlinear process monitoring based on maximum varianceunfolding projections [J].Expert Systems with Applications,2009,36(8):11332-11340. 被引量:1
  • 7Zhang Muguang,Ge Zhiqiang, Song Zhihuan,et al.Global-Local Structure Analysis Model and Its Application for Fault Detection and Identification[J].Industrial & Engineering Chemistry Research,2011,50(11):6837-6848. 被引量:1
  • 8Wong W K,Zhao H T.Supervised optimal locality preserving projection[J].Pattern Recognition,2012,45(7): 186-197. 被引量:1
  • 9张妮,田学民.基于等距离映射的非线性动态故障检测方法[J].上海交通大学学报,2011,45(8):1202-1206. 被引量:9
  • 10葛志强,宋执环,杨春节.基于MCUSUM-ICA-PCA的微小故障检测[J].浙江大学学报:工学版,2008,42(3):373-377. 被引量:8

二级参考文献39

共引文献17

同被引文献9

引证文献1

二级引证文献3

投稿分析
职称考试

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部 意见反馈