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Identification of machine tool geometric performance using on-machine inertial measurements

Vogl, Gregory (author)
National Institute of Standards and Technology (NIST), Gaithersburg, MD, USA
Pavel, R. (author)
TechSolve, Cincinnati, OH, USA
Archenti, Andreas, 1973- (author)
KTH,Industriell produktion,Manufacturing and Metrology Systems
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Winnard, T.J. (author)
Andrews University, Berrien Springs, MI, USA
M.M., Mennu (author)
University of South Florida, Tampa, FL, USA
B.A, Weiss (author)
National Institute of Standards and Technology (NIST), Gaithersburg, MD, USA
M.A., Donmez (author)
National Institute of Standards and Technology (NIST), Gaithersburg, MD, USA
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 (creator_code:org_t)
2017
2017
English.
In: 6th International Conference on Virtual Machining Process Technology (VMPT 2017).
  • Conference paper (peer-reviewed)
Abstract Subject headings
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  • Machine tools degrade during operations, yet accurately detecting degradation of machine components such as linear axes is typically a manual and time-consuming process. Thus, manufacturers need automated and efficient methods to diagnose the condition of their machine tool linear axes with minimal disruptions to production. Towards this goal, a method was developed to use accelerometer and rate gyroscope data from an inertial measurement unit (IMU) for identification of changes in the translational and angular errors due to axis degradation. An IMU was created for application of the method on a machine tool. As a proof of concept for detection of translational error motions, IMU data was collected on a machine tool with experimentally simulated degradation; as the worktable moved along its nominal path, a cross-axis moved along a swept sinusoidal pattern with micrometer-level amplitudes. In another experiment, data was collected at three different locations on a worktable for the same axis motion. These experiments showed that the IMU detected micrometer-level and microradian-level degradation of linear axes, revealing that the IMU-based method is plausible for use in smart machine tools. 

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Maskinteknik -- Produktionsteknik, arbetsvetenskap och ergonomi (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Mechanical Engineering -- Production Engineering, Human Work Science and Ergonomics (hsv//eng)

Keyword

Machine tool
Linear Axis
Error
Degradation
Diagnostics

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Vogl, Gregory
Pavel, R.
Archenti, Andrea ...
Winnard, T.J.
M.M., Mennu
B.A, Weiss
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M.A., Donmez
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ENGINEERING AND TECHNOLOGY
ENGINEERING AND ...
and Mechanical Engin ...
and Production Engin ...
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By the university
Royal Institute of Technology

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