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- Carvalho Bittencourt, André, 1984-, et al.
(författare)
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A data-driven approach to diagnostics of repetitive processes in the distribution domain : Applications to gearbox diagnosticsin industrial robots and rotating machines
- 2014
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Ingår i: Mechatronics (Oxford). - : Elsevier. - 0957-4158 .- 1873-4006. ; 24:8, s. 1032-1041
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents a data-driven approach to diagnostics of systems that operate in a repetitive manner. Considering that data batches collected from a repetitive operation will be similar unless in the presence of an abnormality, a condition change is inferred by comparing the monitored data against an available nominal batch. The method proposed considers the comparison of data in the distribution domain, which reveals information of the data amplitude. This is achieved with the use of kernel density estimates and the Kullback–Leibler distance. To decrease sensitivity to disturbances while increasing sensitivity to faults, the use of a weighting vector is suggested which is chosen based on a labeled dataset. The framework is simple to implement and can be used without process interruption, in a batch manner. The approach is demonstrated with successful experimental and simulation applications to wear diagnostics in an industrial robot gearbox and for diagnostics of gear faults in a rotating machine.
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- Carvalho Bittencourt, André, 1984-, et al.
(författare)
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A Data-Driven Method for Monitoring of Repetitive Systems: Applications to Robust Wear Monitoring of a Robot Joint
- 2013
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This paper presents a method for monitoring of systems that operate in a repetitive manner. Considering that data batches collected from a repetitive operation will be similar unless in the presence of an abnormality, a condition change is inferred by comparing the monitored data against a nominal batch. The method proposed considers the comparison of data in the distribution domain, which reveals information of the data amplitude. This is achieved with the use of kernel density estimates and the Kullback-Leibler distance. To decrease sensitivity to unknown disturbances while increasing sensitivity to faults, the use of a weighting vector is suggested which is chosen based on a labeled dataset. The framework is simple to implement and can be used without process interruption, in a batch manner. The method was developed with interests in industrial robotics where a repetitive behavior is commonly found. The problem of wear monitoring in a robot joint is studied based on data collected from a test-cycle. Real data from accelerated wear tests and simulations are considered. Promising results are achieved where the method output shows a clear response to the wear increases.
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- Carvalho Bittencourt, André, et al.
(författare)
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A Data-Driven Method for Monitoring Systems that Operate Repetitively : Applications to Robust Wear Monitoring inan Industrial Robot Joint
- 2011
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- 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.
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- Carvalho Bittencourt, André, et al.
(författare)
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An Extended Friction Model to capture Load and Temperature effects in Robot Joints
- 2010
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Ingår i: Proceedings of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems. - Linköping : Linköping University Electronic Press. - 9781424466740 ; , s. 6161-6167
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Konferensbidrag (refereegranskat)abstract
- Friction is the result of complex interactions between contacting surfaces in a nanoscale perspective. Depending on the application, the different models available are more or less suitable. Available static friction models are typically considered to be dependent only on relative speed of interacting surfaces. However, it is known that friction can be affected by other factors than speed. In this paper, static friction in robot joints is studied with respect to changes in joint angle, load torque and temperature. The effects of these variables are analyzed by means of experiments on a standard industrial robot. Justified by their significance, load torque and temperature are included in an extended static friction model. The proposed model is validated in a wide operating range, reducing the average error a factor of 6 when compared to a standard static friction model.
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- Saarinen, Kari, et al.
(författare)
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Criticality Analysis Based Maintenance
- 2013
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Ingår i: Journal of Asset Management. - : Engineering Information Transfer. - 1470-8272 .- 1479-179X. ; 26:6, s. 16-19
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Tidskriftsartikel (refereegranskat)abstract
- Changing from a reactive to a preventive maintenance strategy can yield substantial cost savings in many sectors of industry. However, in the process industries, an installation may have many thousands of maintenance-worthy elements, rendering a solely preventive maintenance strategy impractical or even impossible. How then to determine the optimal maintenance strategy mix for such situations?
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