Brief Calibration and estimation of redundant signals

  • Authors:

  • Asok Ray;Shashi Phoha

  • Affiliations:

  • Mechanical Engineering Department, The Pennsylvania State University, University Park, PA 16802, USA;Applied Research Laboratory, The Pennsylvania State University, University Park, PA 16802, USA

  • Venue:
  • Automatica (Journal of IFAC)
  • Year:
  • 2000

Quantified Score

Hi-index 22.14

Visualization

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.