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Tytuł artykułu

Application of computer vision methods to estimate the coverage of peen formed plates

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Purpose: this paper aims to present a simple method that allows for a systematic estimation of coverage of peen aluminum workpiece submitted to a peen form process. Design/methodology/approach: This approach is based on the application of computer vision techniques for segmenting amplified images of the shot peening processed surface. The work has employed two combined methods of image segmentation – inductive algorithm generated rule segmentation and a multiagent segmentation system. Findings: The two combined methods of image segmentation has allowed for an estimation of low coverage plates as well as done by human expert. Furthermore a model of the spatial shot distribution was also achieved. Research limitations/implications: The surrogated method is suitable for plates with relative low coverages, circa 50 %. Originality/value: The model can be regarded as useful by acelerating the coverage evaluation in comparison with conventional industrial approach.
Rocznik
Strony
743--749
Opis fizyczny
Bibliogr. 17 poz., rys., tab.
Twórcy
autor
  • Instituto de Pesquisas Tecnológicas do Estado de São Paulo, Av. Prof. Almeida Prado, 532, São Paulo, 05508-901, Brazil
  • Instituto de Pesquisas Tecnológicas do Estado de São Paulo, Av. Prof. Almeida Prado, 532, São Paulo, 05508-901, Brazil
  • Escola Politécnica da Universidade de São Paulo, Av. Prof. Mello Moraes, 2232, São Paulo, 05508-970, Brazil
autor
  • Escola Politécnica da Universidade de São Paulo, Av. Prof. Mello Moraes, 2232, São Paulo, 05508-970, Brazil
  • Centro Universitário da FEI, Av. Humberto A. Castelo Branco, 3972, 09850-901, São Bernardo do Campo, Brazil
Bibliografia
  • [1] Z.A. Stotsko, T.O. Stefanovych, Ensuring uniformity of strengthening for machine parts surfaces by shot-peening, Journal of Achievements in Materials and Manufacturing Engineering 43/1 (2010) 440-447.
  • [2] T. Burakowski, A. Nakonieczny, General Aspects of Shot Peening Criteria of Parameters Selection, Proceedings of the 1th International Conference on Shot Peening, Washington DC, USA, 1981, 139-146.
  • [3] D. Clarke, S.S. Birley, The Control of Manual Shot Peening, Proceedings of the 1th International Conference on Shot Peening, Washington DC, USA, 1981, 167-174.
  • [4] T. Haubold, W. Hennig, F. Wüstefeld, S. Kittel, A. Friese, Implementing On-Line Process Control for Shot Peening, Proceedings of the 9th International Conference on Shot Peening, Paris, France, 2005, 360-365.
  • [5] SAE International, Shot Peening Coverage, Surface Vehicle Recommended Practice, SAE J2277, 2003.
  • [6] F.P. Leon, Model-Based Inspection of Shot Peened Surfaces Using Fusion Techniques, Proceedings of the SPIE 4189 (2001) 41-52.
  • [7] M. Handa, Y. Watanabe, K. Hattori, Suggestion of Image Processing System for Measurement of Coverage, The Shot Peener, 2005, 30-34.
  • [8] E.A. Bender, Mathematical Methods in Artificial Intelligence, IEEE Computer Society Press, Los Alamitos, California, 1996.
  • [9] G. Weiss, Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence, The MIT Press, New Edition, Boston, 2000.
  • [10] J.R. Quinlan, Induction of Decision Trees, Machine Learning 1 (1986) 81-106.
  • [11] R. Kohavi, D. Sommerfield, J. Dougherty, Data Mining using MLC++, a Machine Learning Library in C++, Proceedings of 8th IEEE International Conference on Tools With Artificial Intelligence, Toulouse, France, 1996, 234-245.
  • [12] M. Wooldridge, N.R. Jennings, D. Kinny, The Gaia Methodology for Agent-Oriented Analysis and Design, Autonomous Agents and Multi-Agent Systems 3/3 (2000) 285-312.
  • [13] F. Aurenhammer, R. Klein, Voronoi Diagrams. In: J. Sack, G. Urrutia (Editor), Handbook of Computational Geometry, Elsevier Science Publishing, 2000, 201-290.
  • [14] F. Bellifemine, A. Poggi, G. Rimassa, JADE – A FIPA-Complaint Agent Framework, Proceedings of the 4th International Conference on the Practical Application of Agents and Multi-Agent Technologies, London, 1999.
  • [15] A. Pokahr, L. Braubach, W. Lamersdorf, JADEX: Implementing a BDI Infrastructure for JADE Agents, In Search of Innovation (Special Issue on JADE), Turin, 2003.
  • [16] Foundation for Intelligent Physical Agents, FIPA ACL Message Structure Specification, 2002.
  • [17] M. Wooldridge, Intelligent Agents, in: G. Weiss (Editor). Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence, MIT Press, 1999, 27-77.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-afd62465-3973-46fe-8f77-f74564a61c53
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