Analyzer for modeling and optimizing maintenance operations

Data processing: structural design – modeling – simulation – and em – Modeling by mathematical expression

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700 30, 700 31, G06F 1900

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061102148

ABSTRACT:
A first model or first analyzer having a series of filters is provided to represent time-varying effects of maintenance events. The first model or analyzer further enhances the selection of derived variables which are used as inputs to the first analyzer. Additionally, a combination of fuzzy logic and statistical regression analyzers are provided to better model the equipment and the maintenance process. An optimizer with a bi-modal optimization process which integrates discrete maintenance events with continuous process variables is also provided. The optimizer determines the time and the type of maintenance activities which are to be executed, as well as the extent to which the maintenance activities can be postponed by changing other process variables. Thus, potential modifications to process variables are determined to improve the current performance of the processing equipment as it drifts out of tolerance.

REFERENCES:
patent: 5027406 (1991-06-01), Roberts et al.
patent: 5079690 (1992-01-01), Li
patent: 5111531 (1992-05-01), Grayson et al.
patent: 5130936 (1992-07-01), Sheppard et al.
patent: 5142612 (1992-08-01), Skeirik
patent: 5159660 (1992-10-01), Lu et al.
patent: 5311562 (1994-05-01), Palusamy et al.
patent: 5386373 (1995-01-01), Keeler et al.
patent: 5446895 (1995-08-01), White et al.
patent: 5458732 (1995-10-01), Butler et al.
patent: 5477444 (1995-12-01), Bhat et al.
patent: 5680409 (1997-10-01), Qin et al.
patent: 5691895 (1997-11-01), Kurtzberg et al.
patent: 5710700 (1998-01-01), Kurtzberg et al.
patent: 5727128 (1998-03-01), Morrison
patent: 5771179 (1998-06-01), White et al.
patent: 5796606 (1998-08-01), Spring
patent: 5809490 (1998-09-01), Guiver et al.
patent: 5877954 (1999-03-01), Klimasauskas et al.
Geladi, Paul, et al., "Partial Least-Squares Regression: A Tutorial", Analytica Chimica Acta, 185 (1986) pp. 1-17.
Serth, R.W., et al., "Gross Error Detection and Data Reconciliation in Steam-Metering Systems", A.I.Ch.E. Journal, May 1986, vol. 32, No. 5, pp. 733-742.
Serth, R.W., et al., "Detection of Gross Errors in Nonlinearly Constrained Data: A Case Study", Chem. Eng. Comm. 1987, vol. 51, pp. 89-104.
Moody, J., et al., "Learning with Localized Receptive Fields", Yale University Dept. of Computer Science, Sep. 1988, pp. 1-11.
Wold, Svante, et al., "Nonlinear PLS Modeling", Chemometrics and Intelligent Laboratory Systems, 7 (1989), pp. 53-65.
Kramer, et al., "Diagnosis Using Backpropagation Neural Networks--Analysis and Criticism", Computers Chem. Engng., vol. 14, No. 2, 1990, pp. 1323-1338.
Helland, Kristian, et al., "Recursive algorithm for partial least squares regression", Chemometrics and Intelligent Laboratory Systems, 14 (1991), pp. 129-137.
Puskorius, G.V., et al., "Decoupled Extended Kalman Filter Training of Feedforward Layered Networks", IEEE, 1991, pp. I-771--I-777.
Kohonen, Teuvo, et al., LVQ.sub.-- PAK: A program package for the correct application of Learning Vector Quantization algorithms, IEEE, 1992, pp. I-725--I-730.
Plutowski, et al., "Selecting concise training sets from clean data", Feb. 1992, pp. 1-45.
Qin, S.J., et al., "Nonlinear PLS Modeling Using Neural Networks", Computers Chem. Engng., vol. 16, No. 4, 1992, pp. 379-391.
Su, Hong-Te, et al., "Integrating Neural Networks with First Principles Models of Dynamic Modeling", IFAC Symp. on DYCOR+, 1992, pp. 77-82.
Kramer, Mark A., et al., "Embedding Theoretical Models in Neural Networks", 1992 ACC/WA14, pp. 475-479.
Kramer, M.A., "Autoassociative Neural Networks", Computers Chem. Engng., vol. 16, No. 4, 1992, pp. 313-328.
Klimasauskas, C., "Developing a Multiple MACD Market Timing System," Advanced Technology for Developers, vol. 2, Special Issue, 4 Qtr. 1993, pp. 1-47.
Thompson, Michael L., et al., "Modeling Chemical Processes Using Prior Knowledge and Neural Networks", A.I.Ch.E. Journal, Aug. 1994, vol. 40, No. 8, pp. 1328-1340.
Haykin, Simon, "Neural Networks Expand SP's Horizons", IEEE Signal Processing Magazine, Mar. 1996, pp. 24-49.
Mulgrew, Bernard, "Applying Radial Basis Functions", IEEE Signal Processing Magazine, Mar. 1996, pp. 50-65.
Jain, Anik K., et al., Artificial Neural Networks: A Tutorial, Computer, Mar. 1996, vol. 29, No. 3, pp. 31-44.
Shang, Yi and Wah, Benjamin, "Global Optimization for Neural Network Training", Computer, Mar. 1996, vol. 29, No. 3, pp. 45-54.
Serbedzija, Nikola B., "Simulating Artificial Neural Networks on Parallel Architecture", Computer, Mar. 1996, vol. 29, No. 3, pp. 57-63.
Tan, Chew Lim, et al., "An Arificial Neural Network that Models Human Decision Making", Computer, Mar. 1996, vol. 29, No. 3, pp. 64-70.
Setiono, Rudy, et al., "Symbolic Representation of Neural Networks", Computer, Mar., 1996, vol. 29, No. 3, pp. 71-77.
Zhao, Hong, et al., "Modeling of Activated Sewage Wastewater Treatment Processes Using Integrated Neural Networks and a First Principle Model", IFAC, 13th World Congress, 1996, pp. 1-5.
Westinghouse Electric Corporation, Descriptive Bulletin 21-161, WDPFII System Overview, pp. 1-5.
Westinghouse Electric Corporation, Descriptive Bulletin 21-196, WDPFII WEStation Historian, pp. 1-4.
Westinghouse Electric Corporation, Descriptive Bulletin 21-188, WDPFII Distributed Processing Unit--Series 32, pp. 1-4.
Westinghouse Electric Corporation, Descriptive Bulletin 21-195, WEStation OpCon, pp. 1-4.
Westinghouse Electric Corporation, Descriptive Bulletin DB21-206, Standard Algorithms, pp. 1-8.
Westinghouse Electric Corporation, Descriptive Bulletin 21-189, WDPFII Westnet II Plus Data Highway, pp. 1-2.
Westinghouse Electric Corporation, Descriptive Bulletin 21-177, WDPFII Q-Line Process I/O, pp. 1-2.
White, David A., and Sofge, Donald A. (Ed.), Handbook of Intelligent Control, (pp. 283-356).
Farkow, Stanley J., Self-organizing methods in modeling "The GMDH Algorithm", (1984), pp. 1-24.
Collection of papers on Kernel Estimators and Adaptive Mixtures downloaded from http://irisd.nswc.navy.mil/AM/kernal.html.
Neuralware, Neural Computing--A Technology Handbook for Professional II/PLUS and Neuralworks Explorer (1993), pp. NC-171-181.
Berenji, Hamid R., et al., "Learning and Tuning Fuzzy Logic Controllers Through Reinforcements", IEEE Transactions on Neural Networks, vol. 3, No. 5, (Sep. 1992), pp. 724-740.

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