Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Electrical signal parameter measurement system
Reexamination Certificate
2006-12-21
2008-09-02
Wachsman, Hal D (Department: 2857)
Data processing: measuring, calibrating, or testing
Measurement system in a specific environment
Electrical signal parameter measurement system
C702S185000, C702S196000
Reexamination Certificate
active
07421351
ABSTRACT:
A system and method for monitoring and fault detection in dynamic systems. A “cross-covariance” matrix is used to construct and implement a principle component analysis (PCA) model and/or partial least squares (PLS) model. This system is further utilized for monitoring and detecting faults in a dynamic system. Time series information is synchronized, with respect to a set of training data. Based on historical data, consistency of correlations between variables can be checked with respect to a given time stamp.
REFERENCES:
patent: 6157894 (2000-12-01), Hess et al.
patent: 6256586 (2001-07-01), Jacobs
patent: 6368975 (2002-04-01), Balasubramhanya et al.
patent: 6502042 (2002-12-01), Eid et al.
patent: 6521080 (2003-02-01), Balasubramhanya et al.
patent: 6804600 (2004-10-01), Uluyol et al.
patent: 6896763 (2005-05-01), Balasubramhanya et al.
patent: 6952657 (2005-10-01), Jahns et al.
patent: 2003/0117317 (2003-06-01), Vanderwerf et al.
patent: 2005/0141782 (2005-06-01), Guralnik et al.
patent: 2006/0058898 (2006-03-01), Emigholz et al.
patent: 2006/0259163 (2006-11-01), Hsiung et al.
Demeure et al., “The Euclid algorithm and the fast computation of cross-covariance and autocovariance sequences”, Apr. 1989. IEEE, IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. 37, issue 4, pp. 545-552.
Mossberg, “Identification of continuous-time ARX models using sample cross-covariances”, Jun. 8-10, 2005, IEEE, Proceedings of the 2005 American Control Conference, 2005, vol. 7, pp. 4766-4771.
Ramos et al., “A Vectorized Principal Component Approach for Solving the Data Registration Problem”, Dec. 13-15, 2006, pp. 1297-1302.
Combination of Multivariate Statistical Process Control and Classification Tool for Situation Assessment Applied to a Sequencing Batch Reactor Wastewater Treatment; M.L. Ruiz, J. Colomer, M. Rubio, J. Melendez; Control Engineering and Intelligent Systems; University of Girona, Spain.
Process Analytical Technology; M.L. Balboni; KMI Parexel; Pharmaceutical Technology, Oct. 2003.
Adaptive Multiscale Principal Component Analysis for On-line Monitoring of a Sequencing Batch Reactor; D.S. Lee, J.M. Park, P.A. Vanrolleghem; Journal of Biotechnology 116 (2005) 195-210.
Adaptive Consensus Principal Component Analysis for On-Line Batch Process Monitoring; D.S. Lee, P.A. Vanrolleghem; Biomath, Ghent University, Coupure Links 653, B-9000 Gent. Belgium.
A Tutorial on Principal Components Analysis; L.I. Smith, Feb. 26, 2002.
Fredrick Kris T.
Honeywell International , Inc.
Wachsman Hal D
LandOfFree
Monitoring and fault detection in dynamic systems does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Monitoring and fault detection in dynamic systems, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Monitoring and fault detection in dynamic systems will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-3989912