Sensor Fault Detection and Isolation Using Phase Space Reconstruction**Resrach supported by Qatar National Research Fund (QNRF) National Priorities Research Program (NPRP) program. Conference Paper uri icon


  • © 2015 American Automatic Control Council. Fault diagnosis is the central component of abnormal event management (AEM) [1-3]. Because of the increasing need for higher system performance, product quality, human safety, and cost efficiency, fault diagnosis systems are applied in diverse industrial fields, such as petrochemical and petroleum industries, robotics, and automotive/aerospace systems [4, 5]. According to the International Federation of Automatic Control (IFAC), a fault is defined as an unpermitted deviation of at least one characteristic property or parameter of the system from the acceptable/usual/standard condition [6-8]. If the unpermitted deviation grows worse with time, a fault may result in abnormal events or accidents. This paper is focused in the direction of sensor faults to provide a novel method to detect and isolate multiple sensor faults. This paper is organized as follows. A comprehensive problem statement and literature review is given in the next two Sections. After that, an overview of phase space reconstruction is introduced, and the proposed method and its simulation results are presented. Conclusion is given in the last Section.

author list (cited authors)

  • Yang, C., Alemi, A., & Langari, R.

citation count

  • 2

publication date

  • July 2015