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

D.N. Shields, S. Du, E. Gaura, Grzech A. Bubnicki Z. (Editor)

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
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

    Fingerprint

Keywords

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

Cite this

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