Data Acquisition in Cast Iron Foundries by Image Analysis

Bernd Dreier, Florian Blas, Alexander Kostgeld

Abstract

The project IDA - Intelligent Data Acquisition is an interdisciplinary project in the fields of applied informatics and mechanical engineering. Its purpose is to collect process relevant information in industrial foundry processes like iron casting with handmade and mechanically made molds. Currently a lot of data sets are collected by hand. But these contain inaccuracies and errors and are not available digitally for further analysis. As a result it is not possible to evaluate them automatically. In particular it is not possible to conclude from a defect cast part to the whole set of its production parameters. We develop several procedures to collect these data sets and prepare them for computation in data analysis algorithms. The acquisition of digitally available data in IDA is done mostly by optical sensors. In this paper we describe our approach especially regarding marking and recognition of relevant objects. Furthermore we show first results in environments close to reality.

References

  1. Baggio, D. (2012). Mastering OpenCV with Practical Computer Vision Projects. PACKT Publishing, Birmingham, 1st edition.
  2. Clemens, H. (2008). BuhlMark praegt die Produktdaten auf das Gussteil und macht damit jedes Teil eindeutig rueckverfolgbar.
  3. D. Hartmann, J. Gottschling, S. M. M. S. (2014). Intelligente Prozesssteuerung in Giessereien.
  4. Duda, R. O. and Hart, P. E. (1972). Use of the Hough Transformation To Detect Lines and Curves in Pictures.
  5. E.N.Gilbert (1957). Gray Codes and Paths on the n-Cube.
  6. Ethan, R. (2011). Orb: an efficient alternative to sift or surf. In Computer Vision (ICCV), 2011 IEEE International Conference on, pages 2564-2571. IEEE.
  7. Gagne, M. (2004). Sorelmetal Gusseisen mit Kugelgraphit. Rio Tinto Iron and Titanium, Montreal (Quebec), 1st edition.
  8. Gray, F. (1947). Gray Code.
  9. Hasse, S. (2003). Guss und Gefuegefehler. Schiele und Schoen, Berlin, second edition edition.
  10. Hovorka, F. (1996). Method for identifying cast parts. US Patent 5,584,113.
  11. Kimme, C., Ballard, D., and Sklasnky, J. (1975). Finding Circles by an Array of Accumulators.
  12. Laganiere, J. (2011). OpenCV 2 Computer Vision Application Programming Cookbook. PACKT Publishing, Birmingham, 1st edition.
  13. Leong, L. K. and Yue, W. (2009). Extraction of 2D Barcode Using Keypoint Selection and Line Detection. In Advances in multimedia information processing - PCM. Springer-Verlag.
  14. Lorsakul, A. (2007). Traffic Sign Recognition for Intelligent Vehicle/Driver Assistance System Using Neural Network on OpenCV.
  15. Meissner, K. (2011). Die neue Giessuhr vollflexibles Markiersystem fr Gussteile.
  16. Nicholson, M. and Monahan, B. (1999). Having the capability of operating over a broad range of temperatures; capable of operation in harsh, high temperature factory environments. US Patent 5,973,599.
  17. Parker, J. R. (2011). Algorithms for Image Processing and Computer Vision. Wiley Publishing, Inc., Indeanapolis, second edition edition.
  18. Wadhwa, R. S. (2013). Traceability and Data Support in SME Manufacturing.
Download


Paper Citation


in Harvard Style

Dreier B., Blas F. and Kostgeld A. (2015). Data Acquisition in Cast Iron Foundries by Image Analysis . In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015) ISBN 978-989-758-091-8, pages 63-70. DOI: 10.5220/0005281600630070


in Bibtex Style

@conference{visapp15,
author={Bernd Dreier and Florian Blas and Alexander Kostgeld},
title={Data Acquisition in Cast Iron Foundries by Image Analysis},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015)},
year={2015},
pages={63-70},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005281600630070},
isbn={978-989-758-091-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015)
TI - Data Acquisition in Cast Iron Foundries by Image Analysis
SN - 978-989-758-091-8
AU - Dreier B.
AU - Blas F.
AU - Kostgeld A.
PY - 2015
SP - 63
EP - 70
DO - 10.5220/0005281600630070