| Paper Details: | Downloads: 810 |
| Serial Number: | P1121139827
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| Title: | Intelligent workpiece detection on CNC milling machine
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| Authors: | J. Balic and F. Cus and S. Klancnik
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| Abstract: | In this paper, system for optical determining the workpiece origin on the CNC machine is presented. Similar high sophisticated systems are commercially available but in most cases they are very expensive and so their purchase is economically unjustified. The purpose of our research is to develop an inexpensive system for non-contact determination of the workpiece origin, which is also sufficiently precise for practical use. The system is implemented on a three-axis CNC milling machine, which is primarily designed for good machinability materials. Calibration procedure using feed-forward neural networks was developed. With this method the calibration procedure is simplified and the mathematical derivation of camera model is avoided. Learned neural network represents the camera calibration model. After neural network learning is complete, we can begin using the system for determining the workpiece origin. This developed system was through a number of tests proved to be reliable and suitable for use in practice. In the paper, working of system is illustrated with a practical example, which confirms the effectiveness of the implemented system in actual use on machine.
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| Keywords: | Neural networks, Image Processing, Milling, Workpiece Detection
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| Journal/Conference: | ICGST Conference on Computer Science and Engineering, CSE-11
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| Volume: | 11
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| Issue: | 2
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| Submission Date: | 9/28/2011 12:00:00 AM
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| Review Date: | 12/5/2011 6:14:17 PM
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| Publishing Date: | 12/19/2011 12:00:00 AM
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| Article Downloads: | 810
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