上海交通大学学报 ›› 2020, Vol. 54 ›› Issue (11): 1142-1150.doi: 10.16183/j.cnki.jsjtu.2020.99.012
黄健,杨旭
收稿日期:
2019-12-13
出版日期:
2020-12-04
发布日期:
2020-12-04
通讯作者:
黄健(1990-),女,河北省廊坊市人,讲师,现主要从事工业过程监测与故障诊断研究.电话(Tel.):010-62332780;E-mail:jianhuang@ustb.edu.cn.
基金资助:
HUANG Jian,YANG Xu
Received:
2019-12-13
Online:
2020-12-04
Published:
2020-12-04
摘要: 在工业过程监测中,传统的过程监测方法无法提取过程的动态信息,且进行特征选择时没有突出在线故障特征.针对此问题,提出基于在线加权慢特征分析(OWSFA)的故障检测算法.采用慢特征分析(SFA)算法提取过程的本质动态特征;基于正常数据估计出特征阈值,根据松弛系数挑选出在线特征中超过阈值的嫌疑故障特征;引入权重系数,进一步构造基于在线加权的嫌疑故障特征统计量.将提出的OWSFA算法在数值系统和Tennessee Eastman过程进行仿真验证,证实了所提算法的故障检测效果优于主成分分析和SFA算法.OWSFA算法根据故障信息,在线构造加权统计量,加强了动态故障特征在监测模型中的表达.
中图分类号:
黄健, 杨旭. 基于在线加权慢特征分析的故障检测算法[J]. 上海交通大学学报, 2020, 54(11): 1142-1150.
HUANG Jian, YANG Xu. Online Weighted Slow Feature Analysis Based Fault Detection Algorithm[J]. Journal of Shanghai Jiao Tong University, 2020, 54(11): 1142-1150.
[1] | JIANG Q C, YAN X F, HUANG B. Performance-driven distributed PCA process monitoring based on fault-relevant variable selection and Bayesian inference[J]. IEEE Transactions on Industrial Electronics, 2016, 63(1): 377-386. |
[2] | JIANG Q C, YAN X F. Parallel PCA-KPCA for nonlinear process monitoring[J]. Control Engineering Practice, 2018, 80: 17-25. |
[3] | GE Z Q, CHEN J. Plant-wide industrial process monitoring: A distributed modeling framework[J]. IEEE Transactions on Industrial Informatics, 2015, 12(1): 310-321. |
[4] | DONG Y N, QIN S J. A novel dynamic PCA algorithm for dynamic data modeling and process monitoring[J]. Journal of Process Control, 2018, 67: 1-11. |
[5] | HE Y C, ZHOU L, GE Z Q, et al. Dynamic mutual information similarity based transient process identification and fault detection[J]. The Canadian Journal of Chemical Engineering, 2018, 96(7): 1541-1558. |
[6] | ZHENG H Y, JIANG Q C, YAN X F. Quality-relevant dynamic process monitoring based on mutual information multiblock slow feature analysis[J]. Journal of Chemometrics, 2019, 33(4): 1-16. |
[7] | CHEN Z W, CAO Y, DING S X, et al. A distributed canonical correlation analysis-based fault detection method for plant-wide process monitoring[J]. IEEE Transactions on Industrial Informatics, 2019, 15(5): 2710-2720. |
[8] | GE Z Q. Process data analytics via probabilistic latent variable models: A tutorial review[J]. Industrial & Engineering Chemistry Research, 2018, 57(38): 12646-12661. |
[9] | GE Z Q, LIU Y. Analytic hierarchy process based fuzzy decision fusion system for model prioritization and process monitoring application[J]. IEEE Transactions on Industrial Informatics, 2019, 15(1): 357-365. |
[10] | JIANG Q C, GAO F R, YI H, et al. Multivariate statistical monitoring of key operation units of batch processes based on time-slice CCA[J]. IEEE Transactions on Control Systems Technology, 2019, 27(3): 1368-1375. |
[11] | KU W F, STORER R H, GEORGAKIS C. Disturbance detection and isolation by dynamic principal component analysis[J]. Chemometrics and Intelligent Laboratory Systems, 1995, 30(1): 179-196. |
[12] | HUANG J, YAN X F. Dynamic process fault detection and diagnosis based on dynamic principal component analysis, dynamic independent component analysis and Bayesian inference[J]. Chemometrics and Intelligent Laboratory Systems, 2015, 148: 115-127. |
[13] | SHANG C, YANG F, GAO X Q, et al. Concurrent monitoring of operating condition deviations and process dynamics anomalies with slow feature analysis[J]. AIChE Journal, 2015, 61(11): 3666-3682. |
[14] | SHANG C, YANG F, HUANG B, et al. Recursive slow feature analysis for adaptive monitoring of industrial processes[J]. IEEE Transactions on Industrial Electronics, 2018, 65(11): 8895-8905. |
[15] | GUO F H, SHANG C, HUANG B, et al. Monitoring of operating point and process dynamics via probabilistic slow feature analysis[J]. Chemometrics and Intelligent Laboratory Systems, 2016, 151: 115-125. |
[16] | ZHANG H Y, TIAN X M, DENG X G. Batch process monitoring based on multiway global preserving kernel slow feature analysis[J]. IEEE Access, 2017, 5: 2696-2710. |
[17] | 汪嘉晨, 唐向红, 陆见光. 轴承故障诊断中特征选取技术[J]. 山东大学学报(工学版), 2019, 49(2): 80-87. |
WANG Jiachen, TANG Xianghong, LU Jianguang. Research onfeature selection technology in bearing fault diagnosis[J]. Journal of Shandong University (Engineering Science), 2019, 49(2): 80-87. | |
[18] | ZHOU P, HU X G, LI P P, et al. OFS-Density: A novel online streaming feature selection method[J]. Pattern Recognition, 2019, 86: 48-61. |
[19] | HUANG J, ERSOY O K, YAN X F. Slow feature analysis based on online feature reordering and feature selection for dynamic chemical process monitoring[J]. Chemometrics and Intelligent Laboratory Systems, 2017, 169: 1-11. |
[20] | LEE J M, YOO C, LEE I B. Statistical process monitoring with independent component analysis[J]. Journal of Process Control, 2004, 14(5): 467-485. |
[21] | DOWNS J J, VOGEL E F. A plant-wide industrial process control problem[J]. Computers & Chemical Engineering, 1993, 17(3): 245-255. |
[22] | LYMAN P R, GEORGAKIS C. Plant-wide control of the Tennessee Eastman problem[J]. Computers & Chemical Engineering, 1995, 19(3): 321-331. |
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