Sensor fusion using self evaluating process sensors

Details Sensor fusion using self evaluating process sensors Sensor fusion using self evaluating process sensors

2006-08-07

2008-09-16

Lau, Tung S (Department: 2863)

Data processing: measuring, calibrating, or testing

Measurement system

Reexamination Certificate

active

07426449

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.

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R.J. Moffat, “Contributions to the Theory of Single-Sample Uncertainty Analysis”, ASME Journal of Fluid Engineering, vol. 104, pp. 250-260, 1982.
R.C. Luo & M. G. Kay, A Tutorial on Multisensor Integration and Fusion, (1990), IEEE.
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