SEARCH

SEARCH BY CITATION

Literature Cited

  • Bakshi, B. R., and G. Stephanopoulos, “Representation of Process Trends—III. Multiscale Extraction of Trends from Process Data,Comput. & Chem. Eng., 18(4), 267 (1994a).
  • Bakshi, B. R., and G. Stephanopoulos, “Representation of Process Trends—IV. Induction of Real-Time Patterns from Operating Data for Diagnosis and Supervisory Control,Comput. & Chem. Eng., 18(4), 303 (1994b).
  • Bartle, R., Elements of Real Analysis, Wiley, New York (1976).
  • Cheung, J. T., and G. Stephanopoulos, “Representation of Process Trends—Part I. A Formal Representation Framework,Comput. & Chem. Eng., 14(4/5), 495 (1990).
  • Dash, S., “Data-Driven Qualitative and Model-Based Quantitative Approaches to Fault Diagnosis,” PhD Thesis, Purdue University (2001).
  • Dash, S., M. R. Maurya, R. Rengaswamy, and V. Venkatasubramanian, “A Novel Interval-Halving Framework for Automated Identification of Process Trends: Extended Version,” Technical Report CIPAC-03-3, Purdue University (2003a).
  • Dash, S., R. Rengaswamy, and V. Venkatasubramanian, “A Novel Interval Halving Algorithm for Process Trend Identification,” 4th IFAC Workshop on On-Line Fault Detection & Supervision in the Chemical Process Industries, Korea, 155 (2001).
  • Dash, S., R. Rengaswamy, and V. Venkatasubramanian, “Fuzzy-Logic based Trend Classification for Fault Diagnosis of Chemical Processes,Comput. & Chem. Eng., 27(3), 347 (2003b).
  • Davis, J. F., B. R. Bakshi, K. A. Kosanovich, and M. J. Piovoso, “Process Monitoring, Data Analysis and Data Interpretation,” Proc. of the First Int. Conf. on Intelligent Systems in Process Eng., Snowmass Village, CO, G. Stephanopoulos, J. F. Davis, and V. Venkatasubramanian, eds., CACHE Corp., University of Texas, Austin, TX, 1 (July 9–14, 1995).
  • Donoho, D. L., and I. M. Johnstone, “Ideal Spatial Adaptation via Wavelet Shrinkage,Biometrika, 81(3), 425 (1994).
  • Huang, Y. J., G. V. Reklaitis, and V. Venkatasubramanian, “A Heuristic Extended Kalman Filter Based Estimator for Fault Identification in a Fluid Catalytic Cracking Unit,Ind. Eng. Chem. Res., 42(14), 3361 (2003).
  • Janusz, M., and V. Venkatasubramanian, “Automatic Generation of Qualitative Description of Process Trends for Fault Detection and Diagnosis,Eng. Applic. Artif. Intell., 4(5), 329 (1991).
  • Jimenez, S., S. Bulgakov, and L. Vazquez, “Efficient Shooting Algorithms for Solving the Nonlinear One-Dimensional Scalar Helmholtz Equation,Applied Mathematics and Computation, 95(2–3), 101 (1998).
  • Kennedy, J. P., “Data Treatment and Applications—Future of Desktop,” Proc. of Foundations of Computer-Aided Process Operations, Mount Crested Butte, CO, D. W. T. Rippin, J. C. Hale, and J. F. Davis, eds., CACHE Corp., University of Texas, Austin, TX 1 (1993).
  • Keogh, E. J., S. Chu, D. Hart, and M. J. Pazzani, “An Online Algorithm for Segmenting Time Series,” IEEE Int. Conf. on Data Mining ICDM, San Jose, CA, IEEE Computer Society, Los Alamitos, CA. 289 (Nov. 29–Dec. 2, 2001).
  • Kiefer, J., “Optimum Sequential Search and Approximation Methods under Minimum Regularity Assumptions,J. Soc. Ind. Appl. Math., 5(3), 105 (1957).
  • Konstantinov, K. B., and T. Yoshida, “Real-Time Qualitative Analysis of the Temporal Shapes of (Bio)process Variables,AIChE J., 38(11), 1703 (1992).
  • Krongold, B. S., K. Ramchandran, and D. L. Jones, “Computationally Efficient Optimal-Power Allocation Algorithms for Multicarrier Communication Systems,IEEE Trans. Communications, 48(1), 23 (2000).
  • Mah, R. S. H., A. C. Tamhane, S. H. Tung, and A. N. Patel, “Process Trending with Piecewise Linear Smoothing,Comput. & Chem. Eng., 19(2), 129 (1995).
  • Maurya, M. R., “Integrating Causal Models and Trend Analysis for Process Fault Diagnosis,” PhD Thesis, Purdue University (2003).
  • Misra, M., S. Kumar, S. J. Qin, and D. Seemann, “Error Based Criterion for On-line Wavelet Data Compression,J. of Process Control, 11(6), 717 (2001).
  • Misra, M., H. H. Yue, S. J. Qin, and C. Ling, “Multivariate Process Monitoring and Fault Diagnosis by Multi-scale PCA,Comput. & Chem. Eng., 26(9), 1281 (2002).
  • Muske, K., J. Young, P. Grosdidier, and S. Tani, “Crude Unit Product Quality Control,Comput. & Chem. Eng., 15(9), 629 (1991).
  • Najim, K., and M. M. Saad, “Adaptive Control: Theory and Practical Aspects,J. of Process Control, 1(2), 84 (1991).
  • Paritosh, P. K., and R. Rengaswamy, “Interval-Halving Techniques for Process Trend Identification,” Technical Report PROCISS-99-01, I.I.T. Bombay, Mumbai, India (1999).
  • Peters, M. S., and K. D. Timmerhaus, Plant Design and Economics for Chemical Engineers, 4th ed., McGraw-Hill, New York (1990).
  • Rengaswamy, R., T. Hagglund, and V. Venkatasubramanian, “A Qualitative Shape Analysis Formalism for Monitoring Control Loop Performance,Eng. Applic. Artif. Intell., 14(1), 23 (2001).
  • Rengaswamy, R., and V. Venkatasubramanian, “A Syntactic Pattern-Recognition Approach for Process Monitoring and Fault Diagnosis,Eng. Applic. Artif. Intell., 8(1), 35 (1995).
  • Saxena, S. C., V. Kumar, and S. T. Hamde, “ECG Data Compression using Non-redundant Templates,IETE Tech. Rev., 17(5), 299 (2000).
  • Sebzalli, Y., R. Li, F. Chen, and X. Wang, “Knowledge Discovery from Process Operational Data for Assessment and Monitoring of Operator's Performance,Comput. & Chem. Eng., 24, 409 (2000).
  • Vedam, H., “OP-AIDE: An Intelligent Operator Decision Support System for Diagnosis and Assessment of Abnormal Situations in Process Plants,” PhD Thesis, Purdue University (1999).
  • Whiteley, J. R., and J. F. Davis, “Knowledge-Based Interpretation of Sensor Patterns,Comput. & Chem. Eng., 16(4), 329 (1992).
  • Witkin, A. P., “Scale-space Filtering,” Proc. Int. Joint Conf. Artificial Intell., Karlsruhe, Germany, A. Bundy, ed., Morgan Kaufmann Publishers, San Francisco, 1019 (Aug. 8–12, 1983).
  • Yabuki, Y., T. Nagasawa, and J. F. MacGregor, “Industrial Experiences with Product Quality Control in Semi-batch Processes,Comput. & Chem. Eng., 26(2), 205 (2002).