This paper presents a filtering algorithm for calibration and estimation of redundant signals for real-time condition monitoring and control of continuous plants. The redundancy may consist of sensor signals and/or analytical measurements that are derived from other sensor signals and physical characteristics of the plant. The redundant measurements are simultaneously calibrated by additive corrections that are recursively estimated based on the principle of linear least-squares filtering. A weighted least-square estimate of the measured variable is generated in real time from the calibrated signals. The weighting matrix is adaptively adjusted as a function of the a posteriori probability of failure of the calibrated measurements. The effects of intra-sample failure and probability of false alarms are taken into account in the formulation of the recursive filter that has been tested for on-line calibration of four redundant sensors of the throttle steam temperature in a commercial-scale fossil power plant. The calibration and estimation filter is potentially applicable to the Instrumentation & Control System Software in tactical and transport aircraft, and nuclear and fossil power plants.
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Signal Processing
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering