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Fluid Power Applications Using Self-Organising Maps in Condition Monitoring
Linköping University, Department of Management and Engineering, Fluid and Mechanical Engineering Systems . Linköping University, The Institute of Technology.
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 [en]
Fluid power, pneumatic, self-organizing maps, condition monitoring
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:liu:diva-11127ISBN: 978-91-7393-971-3 (print)OAI: oai:DiVA.org:liu-11127DiVA: diva2:17576
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
List of papers
1. Self-Organising Maps for Illustration of Friction in a Pneumatic Cylinder
Open this publication in new window or tab >>Self-Organising Maps for Illustration of Friction in a Pneumatic Cylinder
2005 (English)In: 9th Scandinavian International Conference on Fluid Power, SICFP’05, 2005, 80-81 p.Conference paper, Published paper (Other academic)
Abstract [en]

Friction exists in virtually every mechanical system. A great many models for prediction and simulation of friction exist. However, due to the high non-linear nature of friction, especially stick-slip friction, there exists a trade-off between simplicity and accuracy in the predictions, also due to difficulties in building an accurate model.

Here an approach to estimation of friction based on accumulated knowledge, using previous measurements and estimations based on these measurements, is discussed. In this approach, a special kind of neural networks, is used. The type of neural network used here is a Kohonen self-organising map. Results from the trained map are used to illustrate how friction relates to states in the pneumatic cylinder. The structure in the map resulting from the different states is also discussed, interpreted and illustrated.

Keyword
Self-organizing maps, friction, pneumatic
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-12975 (URN)
Conference
9th Scandinavian International Conference on Fluid Power, SICFP’05, Linköping, Sweden, 1st-2nd June, 2005
Available from: 2008-02-26 Created: 2008-02-26 Last updated: 2013-11-21
2. Detection of System Changes for a Pneumatic Cylinder Using Self-Organizing Maps
Open this publication in new window or tab >>Detection of System Changes for a Pneumatic Cylinder Using Self-Organizing Maps
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.

Series
Keyword
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:nbn:se:liu:diva-12976 (URN)10.1109/CACSD.2006.285524 (DOI)0-7803-9798-3 (ISBN)
Available from: 2008-02-26 Created: 2008-02-26 Last updated: 2009-06-09
3. Self-Organising Maps for Monitoring Pneumatic Systems
Open this publication in new window or tab >>Self-Organising Maps for Monitoring Pneumatic Systems
2006 (English)In: The Bath Symposium on Power Transmission and Motion Control, PTMC’06, 2006, 181-194 p.Conference paper, Published paper (Refereed)
Keyword
Pneumatic, condition monitoring, neural networks, self-organizing maps
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-12977 (URN)
Available from: 2008-02-26 Created: 2008-02-26 Last updated: 2009-06-09
4. Condition Monitoring of Pneumatic Systems Using Self-Organising Maps
Open this publication in new window or tab >>Condition Monitoring of Pneumatic Systems Using Self-Organising Maps
2007 (English)In: 10th Scandinavian International Conference on Fluid Power, SICFP’07, Tampere, Finland, Tampere, Finland: Tampere University of Technology , 2007, 407-421 p.Conference paper, Published paper (Refereed)
Abstract [en]

Automated monitoring of systems is growing in importance as systems becomeincreasingly autonomous and intelligent control is being used to agrowing extent. At the same time, component manufacturers' desireto offer components with embedded condition monitoring systems isalso increasing.

This paper discusses one general, adaptive method -- theself-organising map, SOM -- suitable for such an application. Itconcerns how to improve interpretation of the fault classificationprocess by using a combination of outputs from the SOM. Thesimultaneous detection of both known and unknown faults isdiscussed.

Place, publisher, year, edition, pages
Tampere, Finland: Tampere University of Technology, 2007
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-12978 (URN)
Available from: 2008-02-26 Created: 2008-02-26 Last updated: 2009-05-19
5. Self-Organising Maps for Change Detection in Hydraulic Systems
Open this publication in new window or tab >>Self-Organising Maps for Change Detection in Hydraulic Systems
2007 (English)In: The Bath Symposium on Power Transmission & Motion Control, PTMC’07, Bath, UK, Basildon, Essex, UK: Hadleys Ltd , 2007, 41-52 p.Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Basildon, Essex, UK: Hadleys Ltd, 2007
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-12979 (URN)
Available from: 2008-02-26 Created: 2008-02-26 Last updated: 2009-05-19

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Zachrison, Anders

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