Adaptive thresholding - a robust fault detection approach

Ke Le, Zhaohui Huang, Chu Whan Moon, Anthony Tzes

Research output: Contribution to journalConference articlepeer-review

Abstract

A new non-statistical adaptive thresholding technique is proposed to address the problem of detection of `abrupt' fault in the presence of system uncertainties due to variabilities such as usage, life cycle, environment, installation, build-to-build, product configuration, and product line. Computationally efficient algorithms are presented using set-membership identification and multi-step ahead uncertainty prediction to find a 100% confident bound that specifies region of nominal system behavior. This bound produces the adaptive threshold for abrupt fault detection scheme. Examples of abrupt fault and outlier detections using the field data are given to demonstrate the proposed approach.

Original languageEnglish (US)
Pages (from-to)4490-4495
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
Volume5
StatePublished - 1997
EventProceedings of the 1997 36th IEEE Conference on Decision and Control. Part 1 (of 5) - San Diego, CA, USA
Duration: Dec 10 1997Dec 12 1997

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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