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

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

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

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

College of Engineering, Environment & Science

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

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 language	English
Title of host publication	Proceedings of the International Conference on Systems Science
Editors	Z. Bubnicki, A. Grzech
Pages	192-199
Number of pages	8
Publication status	Published - 2001
Event	International Conference on Systems Science - Wroclaw, Poland Duration: 11 Sept 2001 → 14 Sept 2001 Conference number: 14

Conference

Conference	International Conference on Systems Science
Country/Territory	Poland
City	Wroclaw
Period	11/09/01 → 14/09/01

Keywords

Differential equations
Neural networks
Nonlinear systems
Polynomials
Hydraulics
Hydraulic systems

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Shields, DN, 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, International Conference on Systems Science, Wroclaw, Poland, 11/09/01. <https://www.scopus.com/inward/record.uri?eid=2-s2.0-0035687529&partnerID=40&md5=a4ab93a52c2821126d2e34d0465808cb>

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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.",

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pages = "192--199",

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AU - Shields, D.N.

AU - Du, S.

AU - Gaura, E.

N1 - Conference code: 14

PY - 2001

Y1 - 2001

N2 - 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.

AB - 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.

KW - Differential equations

KW - Neural networks

KW - Nonlinear systems

KW - Polynomials

KW - Hydraulics

KW - Hydraulic systems

M3 - Conference proceeding

SP - 192

EP - 199

BT - Proceedings of the International Conference on Systems Science

A2 - Bubnicki, Z.

A2 - Grzech, A.

T2 - International Conference on Systems Science

Y2 - 11 September 2001 through 14 September 2001

ER -

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

Abstract

Conference

Keywords

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Cite this