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Detectability of various machining conditions by using internal encoder signals
University West, Department of Engineering Science, Division of Mechanical Engineering and Natural Sciences. (PTW)ORCID iD: 0000-0002-3436-3163
GKN Aerospace Engine Systems AB, Trollhättan, Sweden.
University West, Department of Engineering Science, Division of Subtractive and Additive Manufacturing. (PTW)
University West, Department of Engineering Science, Division of Subtractive and Additive Manufacturing. North Carolina State University, Department of Mechanical and Aerospace Engineering, Raleigh, North Carolina, United States. (PTW)
2016 (English)In: The 7th International Swedish Production Symposium, SPS16, Conference Proceedings: 25th – 27th of October 2016, Lund: Swedish Production Academy , 2016, 1-7 p.Conference paper (Refereed)
Abstract [en]

Automated Tool Condition Monitoring (TCM) often relies on additional sensors sensitive to tool wear to achieve robust machining processes. The need of additional sensors could impede the implementation of tool monitoring systems in industry due to the cost and retrofitting difficulties. This paper has investigated the use of existing position encoder signals to monitor a special face turning process with constant feed per revolution and machining speed. A signal processing method by converting encoder signals into a complex-valued form and a new vibration signature extraction method based on phase function were developed to analyze the encoder signals in the frequency domain. The cumulative spectrum indicated that the spectral energy would shift from the lower to the higher frequency band with increasing cutting load. The embedded vibration signatures extracted from the encoder signals provided additional detectability of the machining condition with distinguishable spectral modes. This paper confirms the sensitivity of the encoder signals and more signatures could be extracted for tool wear detection in the future work.

Place, publisher, year, edition, pages
Lund: Swedish Production Academy , 2016. 1-7 p.
Keyword [en]
Face turning, machining process monitoring, encoder signals, detectability
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
ENGINEERING, Manufacturing and materials engineering
Identifiers
URN: urn:nbn:se:hv:diva-10238OAI: oai:DiVA.org:hv-10238DiVA: diva2:1052825
Conference
7th International Swedish Production Symposium, SPS16, Lund, Sweden, October 25–27, 2016
Available from: 2016-12-07 Created: 2016-12-07 Last updated: 2016-12-08Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • 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