single-au.php

IJAT Vol.14 No.3 pp. 512-520
doi: 10.20965/ijat.2020.p0512
(2020)

Paper:

Development of Tool Shape Estimation Method Integrating Multidirectional Optical Measurement

Mayumi Kaneko*,†, Takahiro Kaminaga*, Jun’ichi Kaneko*, Kiyohiko Katano**, Takeyuki Abe*, and Kenichiro Horio*

*Saitama University
255 Shimo-okubo, Sakura-ku, Saitama City, Saitama 338-8570, Japan

Corresponding author

**Kuraki Co., Ltd., Nagaoka, Japan

Received:
November 7, 2019
Accepted:
January 8, 2020
Published:
May 5, 2020
Keywords:
machining simulation, human error, optically measure, dexel model
Abstract

Advance avoidance of machine collision by means of computer simulation is now common in NC machining. However, human errors from the tool shape mounted in the machine tool main shaft not matching the simulation data and the actual tool have become a problem. Therefore, in this research, we have developed a high-speed method of comparing the shape of a tool mounted on a machine tool main shaft and an estimated shape in a simulation. This is done by capturing an image of the tool with a camera and estimating the tool shape from multiple images.

Cite this article as:
M. Kaneko, T. Kaminaga, J. Kaneko, K. Katano, T. Abe, and K. Horio, “Development of Tool Shape Estimation Method Integrating Multidirectional Optical Measurement,” Int. J. Automation Technol., Vol.14 No.3, pp. 512-520, 2020.
Data files:
References
  1. [1] N. Umezu, K. Asai, and M. Inui, “Wavelet Transform Data Compression with an Error Level Guarantee for Z-Map Models,” Int. J. Automation Technol., Vol.10, No.2, pp. 201-208, 2016.
  2. [2] T. Nakamura, J. Kaneko, T. Abe, and K. Horio, “Developing a Support System for Loading Planning,” Int. J. Automation Technol., Vol.13, No.4, pp. 475-481, 2019.
  3. [3] N. Kochi, T. Tanabata, A. Hayashi, and S. Isobe, “A 3D Shape-Measuring System for Assessing Strawberry Fruits,” Int. J. Automation Technol., Vol.12, No.3, pp. 395-404, 2018.
  4. [4] Y. Midorikawa and H. Masuda, “Extraction of Rotational Surfaces and Generalized Cylinders from Point-Clouds Using Section Curves,” Int. J. Automation Technol., Vol.12, No.6, pp. 901-910, 2018.
  5. [5] K. Ichikawa, H. Saito, J. Kaneko, Y. Okuma, and K. Horio, “Estimation Method of Machining Error on Low Rigidity Workpiece for Tool Posture Planning,” Int. J. Automation Technol., Vol.11, No.6, pp. 964-970, 2017.
  6. [6] F. Uchiyama, A. Tsuboi, and T. Matsumura, “Surface Profile Analysis in Milling with Structured Tool,” Int. J. Automation Technol., Vol.13, No.1, pp. 101-108, 2019.
  7. [7] J. Kaneko, Y. Yamauchi, and K. Horio, “Fast Estimation Method of Machinable Area of Workpiece Surface for 3+2-Axis Control Machining Using Graphics Device – Visualization Algorithm of Machinable Area and Minimum Shank Length with Texture Projection Technique –,” Int. J. Automation Technol., Vol.8, No.3, pp. 420-427, 2014.
  8. [8] I. Nishida and K. Shirase, “Machine Tool Assignment Realized by Automated NC Program Generation and Machining Time Prediction,” Int. J. Automation Technol., Vol.13, No.5, pp. 700-707, 2019.
  9. [9] K. Miura, A. Nose, H. Suzuki, and M. Okada, “Cutting Tool Edge and Textured Surface Measurements with a Point Autofocus Probe,” Int. J. Automation Technol., Vol.11, No.5, pp. 761-765, 2017.
  10. [10] S. Ibaraki and Y. Ota, “Error Calibration for Five-Axis Machine Tools by On-the-Machine Measurement Using a Touch-Trigger Probe,” Int. J. Automation Technol., Vol.8, No.1, pp. 20-27, 2014.
  11. [11] P. Khajornrungruang, K. Kimura, K. Suzuki, and T. Inoue, “Micro Tool Diameter Monitoring by Means of Laser Diffraction for On-Machine Measurement,” Int. J. Automation Technol., Vol.11, No.5, pp. 736-741, 2017.
  12. [12] H. Nguyen and B. Lee, “3D Model Reconstruction System Development Based on Laser-Vision Technology,” Int. J. Automation Technol., Vol.10, No.5, pp. 813-820, 2016.
  13. [13] T. Kaminaga, J. Kaneko, and K. Horio, “Development of tool shape estimation method by integrating multi-directional optical measurement,” Proc. of the 2017 Annual Meeting of the Japan Society of Mechanical Engineers, S1320104, 2017.
  14. [14] S. Usuki, M. Uno, and K. Miura, “Digital Shape Reconstruction of a Micro-Sized Machining Tool Using Light-Field Microscopy,” Int. J. Automation Technol., Vol.10, No.2, pp. 172-178, 2016.
  15. [15] K. Endo, T. Ishiwata, and T. Yamazaki, “Development of Ultralow-Cost Machine Vision System,” Int. J. Automation Technol., Vol.11, No.4, pp. 629-637, 2017.
  16. [16] Nara Institute of Science and Technology OpenCV Programming Book Production Team, “OpenCV programming book,” Mainichi Communications, 2007.
  17. [17] OpenCV2 Programming Book Production Team, “OpenCV2 programming book,” Mynavi Publishing Corporation, 2011.
  18. [18] M. Inui, T. Sakurai, and N. Umezu, “Data Conversion Technology between Triple Dexel Model and Polygonal Model,” J. of the Japan Society for Precision Engineering, Vol.76, No.2, pp. 226-231, 2010.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Apr. 19, 2024