Sensor fusion using self evaluating process sensors

Data processing: measuring – calibrating – or testing – Measurement system

Reexamination Certificate

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Reexamination Certificate

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07107176

ABSTRACT:
A measurement processing system is disclosed for fusing measurement data from a set of independent self-validating (SEVA™) process sensors monitoring the same real-time measurand in order to generate a combined best estimate for the value, uncertainty and measurement status of the measurand. The system also provides consistency checking between the measurements. The measurement processing system includes a first process sensor and a second process sensor. Each of the first and second process sensors receive a measurement signal from a transducer and generate independent process metrics. A measurement fusion block is connected to the first and second process sensors, the measurement fusion block is operable to receive the independent process metrics and execute a measurement analysis process to analyze the independent process metrics and generate the combined best estimate of the independent process metrics.

REFERENCES:
patent: 4926364 (1990-05-01), Brotherton
patent: 5570300 (1996-10-01), Henry et al.
patent: 5586066 (1996-12-01), White et al.
patent: 5680409 (1997-10-01), Qin et al.
patent: 5774378 (1998-06-01), Yang
patent: 5850625 (1998-12-01), Maren et al.
patent: 6047220 (2000-04-01), Eryurek
patent: 6580046 (2003-06-01), Koini et al.
patent: 6772082 (2004-08-01), van der Geest et al.
patent: 2002/0042694 (2002-04-01), Henry et al.
patent: 2003/0167139 (2003-09-01), Swartz et al.
patent: 0827096 (1998-03-01), None
patent: WO 93/21505 (1993-10-01), None
patent: WO 00/10059 (2000-02-01), None
M. Henry, Self-Validating Digital Coriolis Mass Flow Meter, (Oct. 2000), Computing & Control Engineering Journal.
G. Wood, UK Activities in Measurement Validation and Data Quality, (Oct. 2000), Computing & Control Engineering Journal.
M. Henry, Plant Asset Management Via Intelligent Sensors Digital, Distributed and For Free, Oct. 2000, Computing & Control Engineering Journal.
J.C.-Y. Yang & D.W. Clarke, Control Using Self-Validating Sensors, vol. 18, No. 1, (1996), Trans. Inst. MC.
M.P. Henry & D.W. Clarke, The Self-Validating Sensor: Rationale, Definitions and Examples, vol. 1, No. 4, pp. 585-610, (1993), Control Eng. Practice.
M. P. Henry, The Integration of Fault Detection Within Plant-Wide Data Quality Management. vol. 2, Jun. 13-16, (1994), IFAC-Safeprocess 94.
U. Enste & F. Uecker, The Use of Supervisory Information in Process Control, (Oct. 2000), IEE Computing & Control.
J. C. Yang & D.W. Clarke, The Self-Validating Actuator, vol. 7, pp. 249-260. (1999), Control Engineering Practice.
J. K. Hackett & M. Shah, Multi-Sensor Fusion: A Perspective, (1990), IEEE.
R.C. Luo & M. G. Kay, A Tutorial on Multisensor Integration and Fusion, (1990), IEEE.
M.P. Manus, Self-Validating, (Jun. 2001) Control Engineering Europe.
L. Mari & G. Zingales, Uncertainty in Measurement Science.
M. P. Henry, “A Seva Sensor—The Coriolis Mass Flow Meter,” IFAC Fault Detection, Supervision and Safety for Technical Processes, vol. 2, pp. 429-434, 1994.
Atia et al.; “A Self-Validating Temperature Sensor Implemented in FPGAs”; Proceedings of the 5thInternational Workshop on Field Programmable Logic and Applications; pp. 321-330; 1995.
Kresta et al.; “Multivariate Statistical Monitoring of Process Operating Performance”, Chemical Engineering Dept., McMaster Univ. Ontario, vol. Feb. 1991, pp. 35-47.
MacGregor et al., “Statistical Process Control of Multivariate Processes”, Chemical Engineering Dept., McMaster Advanced Control Consortium, McMaster Univ. vol. 3, No. 3, 1995, pp. 403-414.
MacGregor J. F. et al., 1991, “Multivariate Statistical Methods in Process Analysis and Control.” AtChE Symposium Proceedings of the Fourth International Conference on Chemical Process Control, AlChE Pub. No. P-67, New York, pp. 79-99.
McFarlane R.C. et al., “Dynamic Simulator for a Model IV Fluid Catalytic Cracking Unit,” American Institute of Chemical Engineering, Chicago, IL, Nov. 14, 1990, pp. 1-79.
Morud T.E., 1996, “Multivariate Statistical Process Control”; Example from the Chemical Process Industry,Journal of Chemometrics,vol. 10, Nos. 5 & 6, pp. 669-675.
Qin et al., “Self-Validating Inferential Sensor for Emission Monitoring”, Dept. of Chemical Engineering, Univ. of Texas, Jun. 1997, pp. 473-477.
Yang J.C.-Y; 1994, “Self-validating Sensors”, Dr. of Phil. Thesis, Department of Engineering Science, Univ. of Oxford.
Sheung Kai Yung, “Signal Processing in Local Sensor Validation,” Ph.D. Thesis—University of Oxford, Dept. of Engin. Science, 1993, pp. 1-244 with Table Of Contents and Abstract.
U.S. Appl. No. 09/815,275, filed Mar. 23, 2001.
S. J. Kline et al., “Describing Uncertainties in Single-Sample Experiments”, Mechanical Engineering, pp. 3-8, 1853.
Paul M. Frank, “Fault Diagnosis in Dynamic Systems Using Analytical and Knowledge-based Redundancy—A Survey and Some New Results,” Automatica, vol. 26, No. 3, pp. 459-474, 1990.
R. J. Moffat, “Contributions to the Theory of Single-Sample Uncertainty Analysis”, ASME Journal of Fluid Engineering, vol. 104, pp. 250-260, 1982.

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