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A New Sensor Fault Diagnosis Technique Based Upon Subspace Identification and Residual Filtering

  • Srinivasan Rajaraman
  • Uwe Kruger
  • M. Sam Mannan
  • Juergen Hahn
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4114)

Abstract

This paper presents a new methodology for designing a detection, isolation, and identification scheme for sensor faults in linear time-varying systems. Practically important is that the proposed methodology is constructed on the basis of historical data and does not require a priori information to isolate and identify sensor faults. This is achieved by identifying a state space model and designing a fault isolation and identification filter. To address time-varying process behavior, the state space model and fault reconstruction filter are updated using a two-time-scale approach. Fault identification takes place at a higher frequency than the adaptation of the monitoring scheme. To demonstrate the utility of the new scheme, the paper evaluates its performance using simulations of a LTI system and a chemical process with time-varying parameters and industrial data from a debutanizer and a melter process.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Srinivasan Rajaraman
    • 1
    • 2
  • Uwe Kruger
    • 3
  • M. Sam Mannan
    • 1
  • Juergen Hahn
    • 2
  1. 1.Department of Chemical Engineering, Texas A&M University, College Station, TX 77843-3122USA
  2. 2.Mary Kay O’ Connor Process Safety Center,Texas A&M University, College Station, TX 77843-3122USA
  3. 3.Intelligent Systems and Control Group, Queen’s University Belfast, BT9 5AHUK

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