Articles & Issues
- Language
- English
- Conflict of Interest
- In relation to this article, we declare that there is no conflict of interest.
- Publication history
-
Received January 15, 2016
Accepted July 8, 2016
-
This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits
unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright © KIChE. All rights reserved.
All issues
Fault detection based on polygon area statistics of transformation matrix identified from combined moving window data
Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, Shanghai 200237, P. R. China
Korean Journal of Chemical Engineering, February 2017, 34(2), 275-286(12), 10.1007/s11814-016-0201-8
Download PDF
Abstract
Principal component analysis (PCA) has been widely used in monitoring industrial processes, but it is still necessary to make improvements in having a timely and effective access to variation information. It is known that the transformation matrix generated from real-time PCA model indicates inner relations between original variables and new produced components, so this matrix would be different when modeling data deviate due to the change of the operating condition. Based on this theory, this paper proposes a novel real-time monitoring approach which utilizes polygon area method to measure the variation degree of the transformation matrices and then constructs a statistic for monitoring purpose. The on-line data are collected through a combined moving window (CMW), containing both normal and monitored data. To evaluate the performance of the proposed method, a simple numerical simulation, the CSTR process and the classic Tennessee Eastman process are employed for illustration, with some PCA-based methods used for comparison.
Keywords
References
Lee JM, Yoo CK, Lee IB, J. Process Control, 14(5), 467 (2004)
Nowicki A, Grochowski M, Duzinkiewicz K, Int. J. Appl. Mathematics Computer Sci., 22, 939 (2012)
Jiang Q, Yan X, Lv Z, Guo M, Korean J. Chem. Eng., 30(6), 1181 (2013)
Kolluri SS, Esfahani IJ, Garikiparthy PSN, Yoo CK, Korean J. Chem. Eng., 32(8), 1486 (2015)
Lu C, Xiao S, Gu X, Korean J. Chem. Eng., 31(11), 1943 (2014)
Jolliffe I, Principal component analysis, Wiley Online Library (2005).
Wehrens R, in Principal component analysis, pp. 43-66, Springer, (2011).
Chiang LH, Braatz RD, Russell EL, Fault detection and diagnosis in industrial systems, Springer Science & Business Media (2001).
Scholkopf B, Smola A, Muller KR, Neural Computation, 10, 1299 (1998)
Shao JD, Rong G, Lee JM, Chem. Eng. Res. Des., 87(11A), 1471 (2009)
Cheng CY, Hsu CC, Chen MC, Ind. Eng. Chem. Res., 49(5), 2254 (2010)
Jiang Q, Yan X, Korean J. Chem. Eng., 31(11), 1935 (2014)
Hyvarinen A, Oja E, Neural Networks, 13, 411 (2000)
Hyvarinen A, Karhunen J, Oja E, Independent component analysis, Wiley (2004).
Ge Z, Song Z, Korean J. Chem. Eng., 26(6), 1467 (2009)
Ge ZQ, Song ZH, Ind. Eng. Chem. Res., 46(7), 2054 (2007)
Tong CD, Song Y, Yan XF, Ind. Eng. Chem. Res., 52(29), 9897 (2013)
Ge ZQ, Zhang MG, Song ZH, J. Process Control, 20(5), 676 (2010)
Wang B, Yan X, Jiang Q, Lv Z, J. Chemometrics, 29(3), 165 (2014)
Nomikos P, Macgregor JF, AIChE J., 40(8), 1361 (1994)
Majid NAA, Taylor MP, Chen JJ, Stam MA, Mulder A, Young BR, Control Eng. Practice, 19, 367 (2011)
Li WH, Yue HH, Valle-Cervantes S, Qin SJ, J. Process Control, 10(5), 471 (2000)
Cheng C, Chiu MS, Chemometrics Intell. Lab. Syst., 76, 1 (2005)
Korenius T, Laurikkala J, Juhola M, Information Sciences, 177, 4893 (2007)
Lau C, Ghosh K, Hussain M, Che Hassan C, Chemometrics Intell. Lab. Syst., 120, 1 (2013)
Alwan LC, Roberts HV, J. Business Economic Statistics, 6, 87 (1988)
Montgomery D, Mastrangelo C, Faltin FW, Woodall WH, MacGregor JF, Ryan TP, J. Quality Technol., 23, 179 (1991)
Wiel SV, Technometrics, 38, 139 (1996)
Negiz A, Cinar A, AIChE J., 43(8), 2002 (1997)
Simoglou A, Martin EB, Morris AJ, Comput. Chem. Eng., 26(6), 909 (2002)
Ku W, Storer RH, Georgakis C, Chemometrics Intell. Lab. Syst., 30, 179 (1995)
Jingyuan W, Zhijiang S, Peng J, Ketian Y, Zhiqiang C, Comput. Appl. Chem., 1, 2 (2010)
Ryu SR, Noda I, Jung YM, Bull. Korean Chem. Soc., 32, 2232 (2011)
Wang X, Kruger U, Irwin GW, Ind. Eng. Chem. Res., 44(15), 5691 (2005)
Malinowski ER, Factor analysis in chemistry, Wiley (2002).
Camacho J, Ferrer A, J. Chemometrics, 26, 361 (2012)
Valle S, Li W, Qin SJ, Ind. Eng. Chem. Res., 38, 4389 (1999)
Jiang QC, Yan XF, Zhao WX, Ind. Eng. Chem. Res., 52(4), 1635 (2013)
Jiang QC, Yan XF, AIChE J., 60(3), 949 (2014)
Bishop CM, Nasrabadi NM, Pattern recognition and machine learning, Springer New York (2006).
Kano M, Hasebe S, Hashimoto L, Ohno H, AIChE J., 48(6), 1231 (2002)
Robbins DP, Discrete Computational Geometry, 12, 223 (1994)
Pak I, Adv. Appl. Mathematics, 34, 690 (2005)
Yoon SY, MacGregor JF, J. Process Control, 11(4), 387 (2001)
Cho JH, Lee JM, Choi SW, Lee D, Lee IB, Chem. Eng. Sci., 60(1), 279 (2005)
Mansouri M, Nounou M, Nounou H, Karim N, J. Loss Prev. Process Ind., 40, 334 (2016)
Alcala CF, Qin SJ, Ind. Eng. Chem. Res., 49(17), 7849 (2010)
Downs JJ, Vogel EF, Comput. Chem. Eng., 17, 245 (1993)
Jiang Q, Yan X, Huang B, IEEE Trans. Ind. Electron., 63, 377 (2015)
Du KL, Swamy M, Neural Networks and Statistical Learning, 355, Springer (2014).
Wang B, Jiang Q, Yan X, Korean J. Chem. Eng., 31(6), 930 (2014)
Nowicki A, Grochowski M, Duzinkiewicz K, Int. J. Appl. Mathematics Computer Sci., 22, 939 (2012)
Jiang Q, Yan X, Lv Z, Guo M, Korean J. Chem. Eng., 30(6), 1181 (2013)
Kolluri SS, Esfahani IJ, Garikiparthy PSN, Yoo CK, Korean J. Chem. Eng., 32(8), 1486 (2015)
Lu C, Xiao S, Gu X, Korean J. Chem. Eng., 31(11), 1943 (2014)
Jolliffe I, Principal component analysis, Wiley Online Library (2005).
Wehrens R, in Principal component analysis, pp. 43-66, Springer, (2011).
Chiang LH, Braatz RD, Russell EL, Fault detection and diagnosis in industrial systems, Springer Science & Business Media (2001).
Scholkopf B, Smola A, Muller KR, Neural Computation, 10, 1299 (1998)
Shao JD, Rong G, Lee JM, Chem. Eng. Res. Des., 87(11A), 1471 (2009)
Cheng CY, Hsu CC, Chen MC, Ind. Eng. Chem. Res., 49(5), 2254 (2010)
Jiang Q, Yan X, Korean J. Chem. Eng., 31(11), 1935 (2014)
Hyvarinen A, Oja E, Neural Networks, 13, 411 (2000)
Hyvarinen A, Karhunen J, Oja E, Independent component analysis, Wiley (2004).
Ge Z, Song Z, Korean J. Chem. Eng., 26(6), 1467 (2009)
Ge ZQ, Song ZH, Ind. Eng. Chem. Res., 46(7), 2054 (2007)
Tong CD, Song Y, Yan XF, Ind. Eng. Chem. Res., 52(29), 9897 (2013)
Ge ZQ, Zhang MG, Song ZH, J. Process Control, 20(5), 676 (2010)
Wang B, Yan X, Jiang Q, Lv Z, J. Chemometrics, 29(3), 165 (2014)
Nomikos P, Macgregor JF, AIChE J., 40(8), 1361 (1994)
Majid NAA, Taylor MP, Chen JJ, Stam MA, Mulder A, Young BR, Control Eng. Practice, 19, 367 (2011)
Li WH, Yue HH, Valle-Cervantes S, Qin SJ, J. Process Control, 10(5), 471 (2000)
Cheng C, Chiu MS, Chemometrics Intell. Lab. Syst., 76, 1 (2005)
Korenius T, Laurikkala J, Juhola M, Information Sciences, 177, 4893 (2007)
Lau C, Ghosh K, Hussain M, Che Hassan C, Chemometrics Intell. Lab. Syst., 120, 1 (2013)
Alwan LC, Roberts HV, J. Business Economic Statistics, 6, 87 (1988)
Montgomery D, Mastrangelo C, Faltin FW, Woodall WH, MacGregor JF, Ryan TP, J. Quality Technol., 23, 179 (1991)
Wiel SV, Technometrics, 38, 139 (1996)
Negiz A, Cinar A, AIChE J., 43(8), 2002 (1997)
Simoglou A, Martin EB, Morris AJ, Comput. Chem. Eng., 26(6), 909 (2002)
Ku W, Storer RH, Georgakis C, Chemometrics Intell. Lab. Syst., 30, 179 (1995)
Jingyuan W, Zhijiang S, Peng J, Ketian Y, Zhiqiang C, Comput. Appl. Chem., 1, 2 (2010)
Ryu SR, Noda I, Jung YM, Bull. Korean Chem. Soc., 32, 2232 (2011)
Wang X, Kruger U, Irwin GW, Ind. Eng. Chem. Res., 44(15), 5691 (2005)
Malinowski ER, Factor analysis in chemistry, Wiley (2002).
Camacho J, Ferrer A, J. Chemometrics, 26, 361 (2012)
Valle S, Li W, Qin SJ, Ind. Eng. Chem. Res., 38, 4389 (1999)
Jiang QC, Yan XF, Zhao WX, Ind. Eng. Chem. Res., 52(4), 1635 (2013)
Jiang QC, Yan XF, AIChE J., 60(3), 949 (2014)
Bishop CM, Nasrabadi NM, Pattern recognition and machine learning, Springer New York (2006).
Kano M, Hasebe S, Hashimoto L, Ohno H, AIChE J., 48(6), 1231 (2002)
Robbins DP, Discrete Computational Geometry, 12, 223 (1994)
Pak I, Adv. Appl. Mathematics, 34, 690 (2005)
Yoon SY, MacGregor JF, J. Process Control, 11(4), 387 (2001)
Cho JH, Lee JM, Choi SW, Lee D, Lee IB, Chem. Eng. Sci., 60(1), 279 (2005)
Mansouri M, Nounou M, Nounou H, Karim N, J. Loss Prev. Process Ind., 40, 334 (2016)
Alcala CF, Qin SJ, Ind. Eng. Chem. Res., 49(17), 7849 (2010)
Downs JJ, Vogel EF, Comput. Chem. Eng., 17, 245 (1993)
Jiang Q, Yan X, Huang B, IEEE Trans. Ind. Electron., 63, 377 (2015)
Du KL, Swamy M, Neural Networks and Statistical Learning, 355, Springer (2014).
Wang B, Jiang Q, Yan X, Korean J. Chem. Eng., 31(6), 930 (2014)
