liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Detection of System Changes for a Pneumatic Cylinder Using Self-Organizing Maps
Linköping University, Department of Management and Engineering, Fluid and Mechanical Engineering Systems . Linköping University, The Institute of Technology.
Linköping University, Department of Management and Engineering, Fluid and Mechanical Engineering Systems . Linköping University, The Institute of Technology.
2006 (English)In: IEEE International Symposium on Computer-Aided Control Systems Design, CACSD’06, 2006, 2647-2652 p.Conference paper, Published paper (Refereed)
Abstract [en]

Automated monitoring of system is growing in importance as systems become increasingly autonomous and intelligent control is being used. At the same time, component manufacturers' desire to offer components with embedded condition monitoring systems is also increasing. The problem with classical model based monitoring for the component manufacturer is the lack of information about the actual application in which the component is to be used. A general, adaptive method is therefore needed. One such algorithm is the self-organizing (feature) map, which has the desired property of reducing the dimensions of the information space. In this paper, two different measures of divergence from the normal state of operation are discussed: the quantization error and a measure of the neurons' individual training level. The combination of these measures is also briefly discussed.

Place, publisher, year, edition, pages
2006. 2647-2652 p.
Series
Keyword [en]
control engineering computing, intelligent control, monitoring, pneumatic control equipment, self-organising feature maps, automated system monitoring, autonomous control, condition monitoring systems, intelligent control, pneumatic cylinder, system change detection
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-12976DOI: 10.1109/CACSD.2006.285524ISBN: 0-7803-9798-3 (print)OAI: oai:DiVA.org:liu-12976DiVA: diva2:17572
Available from: 2008-02-26 Created: 2008-02-26 Last updated: 2009-06-09
In thesis
1. Fluid Power Applications Using Self-Organising Maps in Condition Monitoring
Open this publication in new window or tab >>Fluid Power Applications Using Self-Organising Maps in Condition Monitoring
2008 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Condition monitoring of systems and detection of changes in the systems are of significant importance for an automated system, whether it is for production, transport, amusement, or any other application. Although condition monitoring is already widely used in machinery, the need for it is growing, especially as systems become increasingly autonomous and self-contained. One of the toughest tasks concerning embedded condition monitoring is to extract the useful information and conclusions from the often large amount of measured data. The use of self-organising maps, SOMs, for embedded condition monitoring is of interest for the component manufacturer who lacks information about how the component is to be used by the system integrator, or in what applications and load cases.

At the same time, there is also a potential interest on the part of the system builders. Although they know how the system is designed and will be used, it is still hard to identify all possible failure modes. A component does not break at all locations or in all functions simultaneously, but rather in one, more stressed, location. Where is this location? Here, the collection of as much data as possible from the system and then processing it with the aid of SOMs allows the system integrators to create a map of the load on the system in its operating conditions. This gives the system integrators a better chance to decide where to improve the system.

Automating monitoring and analysis means not only being able to collect prodigious amounts of measured data, but also being able to interpret the data and transform it into useful information, e.g. conclusions about the state of the system. However, as will be argued in this thesis, drawing the conclusions is one thing, being able to interpret the conclusions is another, not least concerning the credibility of the conclusions drawn. This has proven to be particularly true for simple mechanical systems like pneumatics in the manufacturing industry.

Place, publisher, year, edition, pages
Institutionen för ekonomisk och industriell utveckling, 2008. 56 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1163
Keyword
Fluid power, pneumatic, self-organizing maps, condition monitoring
National Category
Signal Processing
Identifiers
urn:nbn:se:liu:diva-11127 (URN)978-91-7393-971-3 (ISBN)
Public defence
2008-03-28, A35, Hus A, Linköpings universitet, Linköping, 10:15 (English)
Opponent
Supervisors
Available from: 2008-02-26 Created: 2008-02-26 Last updated: 2009-05-19

Open Access in DiVA

No full text

Other links

Publisher's full textLink to Ph.D. thesis

Authority records BETA

Zachrison, AndersSethson, Magnus

Search in DiVA

By author/editor
Zachrison, AndersSethson, Magnus
By organisation
Fluid and Mechanical Engineering Systems The Institute of Technology
Engineering and Technology

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 76 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf