SwePub
Sök i LIBRIS databas

  Extended search

onr:"swepub:oai:DiVA.org:hv-10071"
 

Search: onr:"swepub:oai:DiVA.org:hv-10071" > In-Process Tool Wea...

  • 1 of 1
  • Previous record
  • Next record
  •    To hitlist

In-Process Tool Wear Detection Using Internal Encoder Signals for Unmanned Robust Machining

Repo, Jari, 1976- (author)
Högskolan Väst,Avdelningen för avverkande och additativa tillverkningsprocesser (AAT),PTW
Wretland, Anders (author)
GKN Aerospace Engine Systems AB, Dept. 9634 – TL-3, SE-46181 Trollhättan, Sweden
Beno, Tomas (author)
Högskolan Väst,Avdelningen för avverkande och additativa tillverkningsprocesser (AAT),PTW
show more...
Tu, Juei-feng (author)
Högskolan Väst,Avdelningen för avverkande och additativa tillverkningsprocesser (AAT),North Carolina State University, Dept. of Mechanical and Aerospace Engineering, Raleigh, USA,PTW
show less...
 (creator_code:org_t)
De Gruyter Open, 2016
2016
English.
In: High Speed Machining. - : De Gruyter Open. - 2299-3975. ; 2:1, s. 37-50
  • Journal article (peer-reviewed)
Abstract Subject headings
Close  
  • 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 real-time detectability of the machining condition with distinguishable spectral modes. The embedded vibration signatures extracted from the encoder signals provided additional detectability of the machining condition with distinguishable spectral modes. In particular, tool chipping manifested itself as significant amplitude changes at a specific frequency band 20-30 Hz in the extracted vibration signatures. A new monitoring metric based on the XY-plane modulations combined with statistical process control charts was proposed and shown to be a robust tool wear and tool wear rate indicator. The results show that when tool chipping occurred, it could be detected in real-time when this this tool wear rate value jumped in combination with breach of the control limits. This confirms that internal encoder signals, together with the proposed metric, could be a robust in-process tool wear monitor.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Materialteknik -- Bearbetnings-, yt- och fogningsteknik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Materials Engineering -- Manufacturing, Surface and Joining Technology (hsv//eng)

Keyword

Face turning
TCM
tool wear
encoder signals
SPC
EWMA
Manufacturing and materials engineering
Produktions- och materialteknik
Production Technology
Produktionsteknik

Publication and Content Type

ref (subject category)
art (subject category)

Find in a library

To the university's database

  • 1 of 1
  • Previous record
  • Next record
  •    To hitlist

Find more in SwePub

By the author/editor
Repo, Jari, 1976 ...
Wretland, Anders
Beno, Tomas
Tu, Juei-feng
About the subject
ENGINEERING AND TECHNOLOGY
ENGINEERING AND ...
and Materials Engine ...
and Manufacturing Su ...
Articles in the publication
High Speed Machi ...
By the university
University West

Search outside SwePub

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

 
pil uppåt Close

Copy and save the link in order to return to this view