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Inertial measurement unit for on-machine diagnostics of machine tool linear axes
KTH, School of Industrial Engineering and Management (ITM), Production Engineering.ORCID iD: 0000-0001-9185-4607
2016 (English)In: Proceedings of the Annual Conference of the Prognostics and Health Management Society, PHM, Prognostics and Health Management Society , 2016, 169-175 p.Conference paper (Refereed)
Abstract [en]

Machine tools degrade during operations, yet knowledge of degradation is elusive; accurately detecting degradation of machines' components such as linear axes is typically a manual and time-consuming process. Thus, manufacturers need automated, efficient, and robust methods to diagnose the condition of their machine tool linear axes with minimal disruptions to production. Towards this end, a method was developed to use data from an inertial measurement unit (IMU) for identification of changes in the translational and angular errors due to axis degradation. The IMU-based method uses data from accelerometers and rate gyroscopes to identify changes in linear and angular errors due to axis degradation. A linear axis testbed, established for the purpose of verification and validation, revealed that the IMU-based method was capable of measuring geometric errors with acceptable test uncertainty ratios. Specifically, comparison of the IMU-based and laser-based results demonstrate that the IMU-based method is capable of detecting micrometer-level and microradian-level degradation of linear axes. Consequently, an IMU was created for application of the IMU-based method on a machine tool as a proof of concept for detection of linear axis error motions. If the data collection and analysis are integrated within a machine controller, the process may be streamlined for the optimization of maintenance activities and scheduling, supporting more intelligent decision-making by manufacturing personnel and the development of self-diagnosing smart machine tools.

Place, publisher, year, edition, pages
Prognostics and Health Management Society , 2016. 169-175 p.
Keyword [en]
Decision making, Errors, Gyroscopes, Machine components, Manufacture, Systems engineering, Units of measurement, Inertial measurement unit, Intelligent decision making, Machine controllers, Maintenance activity, Micrometer levels, Proof of concept, Test uncertainty ratios, Verification-and-validation, Machine tools
National Category
Mechanical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-216864Scopus ID: 2-s2.0-85030248252ISBN: 9781936263059 OAI: oai:DiVA.org:kth-216864DiVA: diva2:1156398
Conference
2016 Annual Conference of the Prognostics and Health Management Society, PHM 2016, 3 October 2016 through 6 October 2016
Note

QC 20171113

Available from: 2017-11-13 Created: 2017-11-13 Last updated: 2017-11-13Bibliographically approved

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Archenti, Andreas

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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More styles
Language
  • de-DE
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  • en-US
  • fi-FI
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  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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  • asciidoc
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