Intelligent Machine Tool – Vision Based 3D Scanning System for Positioning of the Workpiece

Author:

Pajor Mirosław1,Grudziński Marek1

Affiliation:

1. West Pomeranian University of Technology Szczecin

Abstract

The presented innovative vision system is a new solution for quick matching the workpiece reference point using non-contact 3D scanning method, based on structural light patterns [1, 2]. The vision system uses special reference markers [3] and flexible calibration procedure [4] in order to integrate with the CNC machine workspace. Based on 3D geometry of the workpiece, placed on CNC table, the new object coordinate system for tooling process is precisely aligned.At present, the system is in the final phase of laboratory tests confirmed its functionality. In this paper, the results of several tests for 3D scanning quality, scanning recurrence and for positioning recurrence using CNC table will be presented. All the most critical stages of integration with CNC machine will be showed and discussed. The obtained results revealed far improvement in terms of time and simplicity of use, as well as good stability of the system.

Publisher

Trans Tech Publications, Ltd.

Subject

Condensed Matter Physics,General Materials Science,Atomic and Molecular Physics, and Optics

Reference8 articles.

1. K. Okarma, M. Grudziński, Korekcja nieliniowości projektorów w wizyjnym systemie pozycjonowania przedmiotów obrabianych na obrabiarkach sterowanych numerycznie, Pomiary Automatyka Robotyka 1(2013) 147–152.

2. S. Zhang, High-resolution, real-time 3-D shape measurement: PhD thesis, Stony Brook University, (2005).

3. T. Luhmann, S. Robson, S. Kyle, I. Harley, Close Range Photogrammetry – Principles, Methods and Applications, Whittles Publishing, (2009).

4. S. Domek, P. Dworak, M. Grudziński, K. Okarma, Calibration of cameras and fringe pattern projectors in the vision system for positioning of workpieces on the CNC machines, Solid State Phenomena 199, 229–234.

5. M. Pajor, K. Marchelek, Aspekty tworzenia koncepcji obrabiarki inteligentnej, Inżynieria Maszyn, 16 (1–2) (2011).

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