A Hybrid Methodology for Kinematic Calibration of Micro/Meso-Scale Machine Tools (mMTs)

[+] Author and Article Information
Andrew Honegger, Richard E. DeVor

Department of Mechanical and Industrial Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801

Shiv G. Kapoor

Department of Mechanical and Industrial Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801sgkapoor@uiuc.edu

J. Manuf. Sci. Eng 128(2), 513-522 (Nov 01, 2005) (10 pages) doi:10.1115/1.2162910 History: Received May 24, 2005; Revised November 01, 2005

A trigger probe measurement system and measurement methodology are developed for kinematic self-calibration of micro/meso-scale machine tools (mMTs). The trigger probe detects the contact between a spindle-mounted stylus and a table-mounted planar artifact. The trigger probe system is small enough to be easily mounted on an mMT. The measurement methodology is divided into off-machine and on-machine measurements. The off-machine measurements are only needed for the first calibration. Recalibration requires only the on-machine measurements to be repeated, thereby reducing recalibration time. The measurement system and methodology are implemented with existing kinematic modeling, error parameter estimation, and compensation techniques for the experimental calibration of a three-axis mMT. The measurement system error is evaluated and experimentally measured. Cutting tests are used to validate the performance of the calibration methodology.

Copyright © 2006 by American Society of Mechanical Engineers
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Figure 3

Workpiece mount kinematic coupling: (a) uncoupled, (b) coupled

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Figure 4

Hybrid measurement methodology

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Figure 5

Artifact orientations

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Figure 6

Trigger probe sensor and stylus mounted to UIUC three-axis mMT

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Figure 7

Three artifact orientations

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Figure 8

UIUC three-axis mMT test bed

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Figure 9

Diagram of error sources

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Figure 10

Repeatability results for a single point

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Figure 1

Trigger probe assembly

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Figure 11

Repeatability results for repositioning of sensor

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Figure 12

L2 estimation accuracy sensitivity to measurement noise

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Figure 13

Effect of number of measurement points on estimation accuracy

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Figure 14

Machined features for calibration validation

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Figure 15

Depth of slots before and after compensation



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