Fault Detection for Shipboard Monitoring – Volterra Kernel and Hammerstein Model Approaches

Zoran Lajic; Mogens Blanke; Ulrik Dam Nielsen

doi:10.3182/20090630-4-ES-2003.00004

Fault Detection for Shipboard Monitoring – Volterra Kernel and Hammerstein Model Approaches

Zoran Lajic, Mogens Blanke, Ulrik Dam Nielsen

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

Abstract

In this paper nonlinear fault detection for in-service monitoring and decision support systems for ships will be presented. The ship is described as a nonlinear system, and the stochastic wave elevation and the associated ship responses are conveniently modelled in frequency domain. The transformation from time domain to frequency domain has been conducted by use of Volterra theory. The paper takes as an example fault detection of a containership on which a decision support system has been installed.

Original language	English
Title of host publication	7. IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes
Publication date	2009
Pages	24-29
ISBN (Print)	978-3-902661-46-3
DOIs	https://doi.org/10.3182/20090630-4-ES-2003.00004
Publication status	Published - 2009
Event	7th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes - Barcelona, Spain Duration: 30 Jun 2009 → 3 Jul 2009 Conference number: 7 http://safeprocess09.upc.es/

Conference

Conference	7th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes
Number	7
Country/Territory	Spain
City	Barcelona
Period	30/06/2009 → 03/07/2009
Internet address	http://safeprocess09.upc.es/

Keywords

Sensor and actuator faults
Nonlinear methods
Marine applications

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.3182/20090630-4-ES-2003.00004

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@inproceedings{c4016a662f7c4ce5bfb4910a622f178c,

title = "Fault Detection for Shipboard Monitoring – Volterra Kernel and Hammerstein Model Approaches",

abstract = "In this paper nonlinear fault detection for in-service monitoring and decision support systems for ships will be presented. The ship is described as a nonlinear system, and the stochastic wave elevation and the associated ship responses are conveniently modelled in frequency domain. The transformation from time domain to frequency domain has been conducted by use of Volterra theory. The paper takes as an example fault detection of a containership on which a decision support system has been installed.",

keywords = "Sensor and actuator faults, Nonlinear methods, Marine applications",

author = "Zoran Lajic and Mogens Blanke and Nielsen, \{Ulrik Dam\}",

year = "2009",

doi = "10.3182/20090630-4-ES-2003.00004",

language = "English",

isbn = "978-3-902661-46-3",

pages = "24--29",

booktitle = "7. IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes",

note = "7th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, SAFEPROCESS 2009 ; Conference date: 30-06-2009 Through 03-07-2009",

url = "http://safeprocess09.upc.es/",

}

Lajic, Z, Blanke, M & Nielsen, UD 2009, Fault Detection for Shipboard Monitoring – Volterra Kernel and Hammerstein Model Approaches. in 7. IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes. pp. 24-29, 7th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, Barcelona, Spain, 30/06/2009. https://doi.org/10.3182/20090630-4-ES-2003.00004

TY - GEN

T1 - Fault Detection for Shipboard Monitoring – Volterra Kernel and Hammerstein Model Approaches

AU - Lajic, Zoran

AU - Blanke, Mogens

AU - Nielsen, Ulrik Dam

N1 - Conference code: 7

PY - 2009

Y1 - 2009

N2 - In this paper nonlinear fault detection for in-service monitoring and decision support systems for ships will be presented. The ship is described as a nonlinear system, and the stochastic wave elevation and the associated ship responses are conveniently modelled in frequency domain. The transformation from time domain to frequency domain has been conducted by use of Volterra theory. The paper takes as an example fault detection of a containership on which a decision support system has been installed.

AB - In this paper nonlinear fault detection for in-service monitoring and decision support systems for ships will be presented. The ship is described as a nonlinear system, and the stochastic wave elevation and the associated ship responses are conveniently modelled in frequency domain. The transformation from time domain to frequency domain has been conducted by use of Volterra theory. The paper takes as an example fault detection of a containership on which a decision support system has been installed.

KW - Sensor and actuator faults

KW - Nonlinear methods

KW - Marine applications

U2 - 10.3182/20090630-4-ES-2003.00004

DO - 10.3182/20090630-4-ES-2003.00004

M3 - Article in proceedings

SN - 978-3-902661-46-3

SP - 24

EP - 29

BT - 7. IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes

T2 - 7th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes

Y2 - 30 June 2009 through 3 July 2009

ER -

Fault Detection for Shipboard Monitoring – Volterra Kernel and Hammerstein Model Approaches

Abstract

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Keywords

UN SDGs

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