Detecting faults in a hydraulic system using neural network and observer approaches

D.N. Shields, S. Du, E. Gaura

Research output: Chapter in Book/Report/Conference proceedingConference proceeding

Abstract

A detection observer and residual are designed for a general nonlinear system with polynomial-type nontinearities. A suboptomal approach is also described. The approach is applied to a three-tank hydraulic system for detecting two faults. Three different degree observers, with correponding residuals, are assessed. This observer approach is then compared to the performance of a neural network approach, where the same faults are assessed.
Original languageEnglish
Title of host publicationProceedings of the International Conference on Systems Science
EditorsZ. Bubnicki, A. Grzech
Pages192-199
Number of pages8
Publication statusPublished - 2001
EventInternational Conference on Systems Science - Wroclaw, Poland
Duration: 11 Sep 200114 Sep 2001
Conference number: 14

Conference

ConferenceInternational Conference on Systems Science
CountryPoland
CityWroclaw
Period11/09/0114/09/01

Keywords

  • Differential equations
  • Neural networks
  • Nonlinear systems
  • Polynomials
  • Hydraulics
  • Hydraulic systems

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  • Cite this

    Shields, D. N., Du, S., & Gaura, E. (2001). Detecting faults in a hydraulic system using neural network and observer approaches. In Z. Bubnicki, & A. Grzech (Eds.), Proceedings of the International Conference on Systems Science (pp. 192-199)