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Original Articles

An efficient ICA-DW-SVDD fault detection and diagnosis method for non-Gaussian processes

, , &
Pages 5208-5218 | Received 06 May 2015, Accepted 24 Feb 2016, Published online: 17 Mar 2016

References

  • Ammari, F., C. B. Y. Cordella, N. Boughanmi, and D. N. Rutledge. 2012. “Independent Components Analysis Applied to 3D-front-face Fluorescence Spectra of Edible Oils to Study the Antioxidant Effect of Nigella sativa L. Extract on the Thermal Stability of Heated Oils.” Chemometrics and Intelligent Laboratory Systems 113: 32–42.10.1016/j.chemolab.2011.06.005
  • Bakshi, B. R. 1998. “Multiscale PCA with Application to Multivariate Statistical Process Monitoring.” AIChE Journal 44 (7): 1596–1610.10.1002/(ISSN)1547-5905
  • Chen, G., and T. J. McAvoy. 1998. “Predictive on-line Monitoring of Continuous Processes.” Journal of Process Control 8 (5–6): 409–420.10.1016/S0959-1524(98)00023-7
  • Chiang, L. H., E. L. Russell, and R. D. Braatz. 2001. Fault Detection and Diagnosis in Industrial Systems. London: Springer.10.1007/978-1-4471-0347-9
  • Downs, J. J., and E. F. Vogel. 1993. “A Plant-wide Industrial Process Control Problem.” Computers & Chemical Engineering 17 (3): 245–255.
  • Durbin, J., and G. S. Watson. 1950. “Testing for Serial Correlation in Least Squares Regression: I.” Biometrika 37 (3–4): 409–428.
  • Ge, Z., and Z. Song. 2007. “Process Monitoring Based on Independent Component Analysis-Principal Component Analysis (ICA–PCA) and Similarity Factors.” Industrial & Engineering Chemistry Research 46 (7): 2054–2063.
  • Ge, Z., and Z. Song. 2008. “Online Monitoring of Nonlinear Multiple Mode Processes Based on Adaptive Local Model Approach.” Control Engineering Practice 16 (12): 1427–1437.10.1016/j.conengprac.2008.04.004
  • Ge, Z., and Z. Song. 2013a. “Bagging Support Vector Data Description Model for Batch Process Monitoring.” Journal of Process Control 23 (8): 1090–1096.10.1016/j.jprocont.2013.06.010
  • Ge, Z., and Z. Song. 2013b. “Performance-driven Ensemble Learning ICA Model for Improved Non-Gaussian Process Monitoring.” Chemometrics and Intelligent Laboratory Systems 123: 1–8.10.1016/j.chemolab.2013.02.001
  • Ge, Z., F. Gao, and Z. Song. 2011. “Batch Process Monitoring Based on Support Vector Data Description Method.” Journal of Process Control 21 (6): 949–959.10.1016/j.jprocont.2011.02.004
  • Ge, Z., Z. Song, and F. Gao. 2013. “Review of Recent Research on Data-based Process Monitoring.” Industrial & Engineering Chemistry Research 52: 3543–3562.
  • Gomez-Carracedo, M. P., J. M. Andrade, D. N. Rutledge, and N. M. Faber. 2007. “Selecting the Optimum Number of Partial Least Squares Components for the Calibration of Attenuated Total Reflectance-mid-infrared Spectra of Undesigned Kerosene Samples.” Analytica Chimica Acta 585 (2): 253–265.10.1016/j.aca.2006.12.036
  • Gourvénec, S., D. L. Massart, and D. N. Rutledge. 2002. “Determination of the Number of Components during Mixture Analysis Using the Durbin–Watson Criterion in the Orthogonal Projection Approach and in the SIMPLe-to-use Interactive Self-modelling Mixture Analysis Approach.” Chemometrics and Intelligent Laboratory Systems 61 (1–2): 51–61.10.1016/S0169-7439(01)00172-1
  • Guo, Y., J. Na, B. Li, and R. F. Fung. 2014. “Envelope Extraction Based Dimension Reduction for Independent Component Analysis in Fault Diagnosis of Rolling Element Bearing.” Journal of Sound and Vibration 333 (13): 2983–2994.10.1016/j.jsv.2014.02.038
  • Hsu, C.-C., L.-S. Chen, and C.-H. Liu. 2010a. “A Process Monitoring Scheme Based on Independent Component Analysis and Adjusted Outliers.” International Journal of Production Research 48 (6): 1727–1743.10.1080/00207540802552683
  • Hsu, C.-C., M.-C. Chen, and L.-S. Chen. 2010b. “Integrating Independent Component Analysis and Support Vector Machine for Multivariate Process Monitoring.” Computers & Industrial Engineering 59 (1): 145–156.
  • Hyvärinen, A. 1999a. “Fast and Robust Fixed-point Algorithms for Independent Component Analysis.” IEEE Transactions on Neural Networks 10 (3): 626–634.10.1109/72.761722
  • Hyvärinen, A. 1999b. “Survey on Independent Component Analysis.” Neural Computing Surveys 2: 94–128.
  • Hyvärinen, A., and E. Oja. 1997. “A Fast Fixed-point Algorithm for Independent Component Analysis.” Neural Computation 9 (7): 1483–1492.10.1162/neco.1997.9.7.1483
  • Jiang, Q., and X. Yan. 2013. “Non-Gaussian Chemical Process Monitoring with Adaptively Weighted Independent Component Analysis and Its Applications.” Journal of Process Control 23 (9): 1320–1331.10.1016/j.jprocont.2013.09.008
  • Jiang, Q., X. Yan, Z. Lv, and M. Guo. 2014. “Independent Component Analysis-based Non-Gaussian Process Monitoring with Preselecting Optimal Components and Support Vector Data Description.” International Journal of Production Research 52 (11): 3273–3286.10.1080/00207543.2013.870362
  • Kano, M., S. Tanaka, S. Hasebe, I. Hashimoto, and H. Ohno. 2003. “Monitoring Independent Components for Fault Detection.” AIChE Journal 49 (4): 969–976.10.1002/(ISSN)1547-5905
  • Khediri, I. B., M. Limam, and C. Weihs. 2011. “Variable Window Adaptive Kernel Principal Component Analysis for Nonlinear Nonstationary Process Monitoring.” Computer & Industrial Engineering 61 (3): 437–446.
  • Ku, W., R. H. Storer, and C. Georgakis. 1995. “Disturbance Detection and Isolation by Dynamic Principal Component Analysis.” Chemometrics and Intelligent Laboratory Systems 30 (1): 179–196.10.1016/0169-7439(95)00076-3
  • Kulkarni, A., V. K. Jayaraman, and B. D. Kulkarni. 2005. “Knowledge Incorporated Support Vector Machines to Detect Faults in Tennessee Eastman Process.” Computers & Chemical Engineering 29 (10): 2128–2133.
  • Lau, C. K., K. Ghosh, M. A. Hussain, and C. R. C. Hassan. 2013. “Fault Diagnosis of Tennessee Eastman Process with Multi-scale PCA and ANFIS.” Chemometrics and Intelligent Laboratory Systems 120: 1–14.10.1016/j.chemolab.2012.10.005
  • de Lázaro, J. M. B., A. P. Moreno, O. L. Santiago, and A. J. da Silva Neto. 2015. “Optimizing Kernel Methods to Reduce Dimensionality in Fault Diagnosis of Industrial Systems.” Computers & Industrial Engineering 87: 140–149.
  • Lee, J. M., C. K. Yoo, and I. B. Lee. 2004a. “Statistical Process Monitoring with Independent Component Analysis.” Journal of Process Control 14 (5): 467–485.10.1016/j.jprocont.2003.09.004
  • Lee, J. M., C. K. Yoo, and I. B. Lee. 2004b. “Statistical Monitoring of Dynamic Processes Based on Dynamic Independent Component Analysis.” Chemical Engineering Science 59 (14): 2995–3006.10.1016/j.ces.2004.04.031
  • Li, Y., and X. Zhang. 2015. “Variable Moving Windows Based Non-Gaussian Dissimilarity Analysis Technique for Batch Processes Fault Detection and Diagnosis.” The Canadian Journal of Chemical Engineering 93: 689–707.10.1002/cjce.v93.4
  • Lowry, C. A., and D. C. Montgomery. 1995. “A Review of Multivariate Control Charts.” IIE Transactions 27 (6): 800–810.10.1080/07408179508936797
  • Luo, R., M. Misra, and D. M. Himmelblau. 1999. “Sensor Fault Detection via Multiscale Analysis and Dynamic PCA.” Industrial and Engineering Chemistry Research 38 (4): 1489–1495.10.1021/ie980557b
  • Montgomery, D. C. 2001. Introduction to Statistical Quality Control. 4th ed. New York: Wiley.
  • Nguyen, V. H., and J. C. Golinval. 2010. “Fault Detection Based on Kernel Principal Component Analysis.” Engineering Structures 32 (11): 3683–3691.10.1016/j.engstruct.2010.08.012
  • Raich, A. C., and A. Cinar. 1995. “Multivariate Statistical Methods for Monitoring Continuous Processes: Assessment of Discrimination Power of Disturbance Models and Diagnosis of Multiple Disturbances.” Chemometrics and Intelligent Laboratory Systems 30 (1): 37–48.10.1016/0169-7439(95)00035-6
  • Rato, T. J., and M. S. Reis. 2013. “Fault Detection in the Tennessee Eastman Benchmark Process Using Dynamic Principal Components Analysis Based on Decorrelated Residuals (DPCA-DR).” Chemometrics and Intelligent Laboratory Systems 125: 101–108.10.1016/j.chemolab.2013.04.002
  • Rutledge, D. N., and A. S. Barros. 2002. “Durbin–Watson Statistic as a Morphological Estimator of Information Content.” Analytica Chimica Acta 454 (2): 277–295.10.1016/S0003-2670(01)01555-0
  • Rutledge, D. N., and D. J. R. Bouveresse. 2013. “Independent Components Analysis with the JADE Algorithm.” TrAC Trends in Analytical Chemistry 50: 22–32.10.1016/j.trac.2013.03.013
  • Sun, R., and F. Tsung. 2003. “A Kernel-distance-based Multivariate Control Chart Using Support Vector Methods.” International Journal of Production Research 41 (13): 2975–2989.10.1080/1352816031000075224
  • Tax, D. M. J., and R. P. W. Duin. 2004. “Support Vector Data Description.” Machine Learning 54 (1): 45–66.10.1023/B:MACH.0000008084.60811.49
  • Verma, V. S., R. K. Jha, and A. Ojha. 2015. “Digital watermark extraction using support vector machine with principal component analysis based feature reduction.” Journal of Visual Communication and Image Representation 31: 75–85.
  • Wang, B., X. Yan, and Q. Jiang. 2015. “Loading-based Principal Component Selection for PCA Integrated with Support Vector Data Description.” Industrial & Engineering Chemistry Research 54 (5): 1615–1627.
  • Yoo, C. K., S. W. Choi, and I.-B. Lee. 2002. “Dynamic Monitoring Method for Multiscale Fault Detection and Diagnosis in MSPC.” Industrial & Engineering Chemistry Research 41 (17): 4303–4317.
  • Zhang, Y. 2008. “Fault Detection and Diagnosis of Nonlinear Processes Using Improved Kernel Independent Component Analysis (KICA) and Support Vector Machine (SVM).” Industrial & Engineering Chemistry Research 47 (18): 6961–6971.
  • Zhang, X., Y. Li, and M. Kano. 2015. “Quality Prediction in Complex Batch Processes with Just-in-time Learning Model Based on Non-Gaussian Dissimilarity Measure.” Industrial & Engineering Chemistry Research 54 (31): 7694–7705.

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