Usage
  • 14 views
  • 96 downloads

Model Based Fault Detection and Diagnosis of LTI Systems using Likelihood Ratio Tests

  • Author / Creator
    Kiasi, Fariborz
  • This study aims to develop a new framework to detect, isolate and estimate the magnitude of additive faults that occur in linear time invariant (LTI) systems. This study starts with introduction of a new framework to deal with additive step type faults to improve the shortcomings attributed to detection of time of occurrence of the fault (TOF) in existing methods. In the next step, a Bayesian approach is used to decouple detection and isolation phases from the estimation of fault magnitude. The final part of this study is dedicated to investigation of more realistic ramp and truncated ramp type faults.

  • Subjects / Keywords
  • Graduation date
    2014-06
  • Type of Item
    Thesis
  • Degree
    Doctor of Philosophy
  • DOI
    https://doi.org/10.7939/R3F47H28W
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
    English
  • Institution
    University of Alberta
  • Degree level
    Doctoral
  • Department
    • Department of Chemical and Materials Engineering
  • Specialization
    • Process Control
  • Supervisor / co-supervisor and their department(s)
    • Shah, Sirish (Chemical and Materials Engineering)
  • Examining committee members and their departments
    • Chen, Tongwen (Electrical and Computer Engineering)
    • Huang, Biao (Chemical and Materials Engineering)
    • Liu, Jinfeng (Chemical and Materials Engineering)
    • Narasimhan, Shankar (Chemical Engineering, IIT Madras, India)
    • Shah, Sirish (Chemical and Materials Engineering)