Abstract
This paper presents formulation and validation of an adaptive filter for real-time calibration of redundant signals consisting of sensor data and/or analytically derived measurements. The measurement noise covariance matrix is adjusted as a function of the a posteriori probabilities of failure of the individual signals. An estimate of the measured variable is obtained as a weighted average of the calibrated signals. The weighting matrix is recursively updated in real time instead of being fixed a priori. The calibration and estimation filter has been tested by injecting faults into the data set collected from an operating power plant. The filter software is presently hosted in a Pentium platform and is portable to other commercial platforms. The filter can be used to enhance the Instrumentation & Control System Software in tactical and transport aircraft, and nuclear and fossil power plants.
Original language | English (US) |
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Pages (from-to) | 1525-1534 |
Number of pages | 10 |
Journal | Automatica |
Volume | 36 |
Issue number | 10 |
DOIs | |
State | Published - Oct 2000 |
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Electrical and Electronic Engineering