Change search
ReferencesLink to record
Permanent link

Direct link
A Data-Driven Method for Monitoring Systems that Operate Repetitively: Applications to Robust Wear Monitoring inan Industrial Robot Joint
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
ABB Corporate Research Västerås, Sweden.
ABB Corporate Research Västerås, Sweden.
2011 (English)Report (Other academic)
Abstract [en]

This paper presents a method for condition monitoring of systems that operate in a repetitive manner. A data driven method is proposed that considers changes in the distribution of data samples obtained from multiple executions of one or several tasks. This is made possible with the use of kernel density estimators and the Kullback-Leibler distance measure between distributions. To increase robustness to unknown disturbances and sensitivity to faults, the use of a weighting function is suggested which can considerably improve detection performance. The method is very simple to implement, it does not require knowledge about the monitored system and can be used without process interruption, in a batch manner. The method is illustrated with applications to robust wear monitoring in a robot joint. Interesting properties of the application are presented through a real case study and simulations. The achieved results show that robust wear monitoring in industrial robot joints is made possible with the proposed method.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2011. , 7 p.
LiTH-ISY-R, ISSN 1400-3902 ; 3040
Keyword [en]
FDI for robust nonlinear systems, Data-driven methods, Industrial robots, Wear monitoring, Condition based maintenance, Automation
National Category
Control Engineering
URN: urn:nbn:se:liu:diva-97982ISRN: LiTH-ISY-R-3040OAI: diva2:650879
Available from: 2013-09-23 Created: 2013-09-23 Last updated: 2014-06-16Bibliographically approved

Open Access in DiVA

fulltext(819 kB)192 downloads
File information
File name FULLTEXT01.pdfFile size 819 kBChecksum SHA-512
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Carvalho Bittencourt, André
By organisation
Automatic ControlThe Institute of Technology
Control Engineering

Search outside of DiVA

GoogleGoogle Scholar
Total: 192 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 136 hits
ReferencesLink to record
Permanent link

Direct link