Araştırma Makalesi
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Vokselleştirme Tekniği ile Oluşturulan Kaynak Dolgusunu Kullanan 3B Bir Sanal Kaynak Simülatörü Geliştirilmesi

Yıl 2024, Cilt: 12 Sayı: 4, 1977 - 1992, 23.10.2024
https://doi.org/10.29130/dubited.1323945

Öz

Bu çalışmada, kaynakçı adaylarının eğitiminde kullanılmak üzere gerçek zamanlı ve maliyeti düşük bir sanal kaynak simülatörü tasarlanıp geliştirilmiştir. Gerçek zamanlı bir kaynak simülasyonu yapmak için öncelikle üç boyutlu bir kaynak dikiş formu tasarlanmıştır. Parabol ve kaynak dikişi arasındaki benzerlik göz önünde bulundurularak temel kaynak dikişi formu olarak parabol kullanılmıştır. Kaynak işlemi sırasında, yapay sinir ağı kullanılarak her zaman adımında kaynak dikişi şeklinin parametreleri hesaplanır. Bu ağ, torcun hareketini izleyen sensör cihazından alınan girdilere dayalı olarak kaynak dikişinin şeklini ve derinliğini belirler. Parabolün parametreleri belirlendikten sonra, gerçek zamanlı olarak voksel haritası ve karşılık gelen sekizli-ağaç veri yapısı oluşturulur. Vokselleştirilmiş veriler kullanılarak üçgenlerden oluşan kaynak dikişi eş-yüzeyi, daha gerçekçi kaynak dikişi şekilleri oluşturmamızı sağlayan yürüyen küp algoritması ile yeniden yapılandırılmıştır. Yüksek çözünürlüklü sanal sahnelerde hesaplama ve işlem maliyetini düşürmek amacıyla vokselizasyon ve eş-yüzey çıkarma işlemleri için çok iş parçacıklı programlama tekniği kullanılmıştır. Bu çalışmada, farklı iş parçacıkları için eş-yüzey çıkarma süreleri gösterilmiş olup geliştirilen simülatörün literatürdeki diğer simülatörlerle karşılaştırması da sunulmuştur.

Kaynakça

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Development of a 3D Virtual Welding Simulator Using Weld Bead Created by Voxelization Technique

Yıl 2024, Cilt: 12 Sayı: 4, 1977 - 1992, 23.10.2024
https://doi.org/10.29130/dubited.1323945

Öz

In this study, we developed and implemented a cost-reducing, real-time virtual welding simulator to train welder candidates. In order to make a real-time welding simulation, a three-dimensional weld bead form was designed. We used a parabola as the basic bead slice shape, considering the similarity between the parabola and the bead slice. During the welding process, the parameters of the weld bead shape are calculated at each time step using an artificial neural network. This network determines the shape of the weld bead and the depth of penetration, based on inputs received from the sensor device that tracks the motions of the torch. After the parabola’s parameters have been determined, the voxel map and corresponding hash-based octree data structure are generated in real-time. By using the voxelized data, a weld bead isosurface consisting of triangles is reconstructed with a marching cubes algorithm allowing us to generate more realistic weld seam shapes. We used multi-threaded programming for voxelization and isosurface extraction to reduce the computation cost on high-resolution virtual scenes. The isosurface extraction times for different thread counts and also a feature comparison with other simulators in the literature are shown in this paper.

Kaynakça

  • [1] G. Karsai, K. Andersen, G.E. Cook, and R.J. Barnett, "Neural network methods for the modeling and control of welding processes," Journal of Intelligent Manufacturing, vol. 3, pp. 229-235, 1992.
  • [2] S. Teeravarunyou, and B. Poopatb, "Computer based welding training system," International Journal of Industrial Engineering: Theory Applications and Practice, vol. 6, no. 2, pp. 116-125, 2009.
  • [3] K.M. Kanti, and P.S. Rao, "Prediction of bead geometry in pulsed gma welding using back propagation neural network,". Journal of Materials Processing Technology, vol. 200(1-3), pp. 300-305, 2008.
  • [4] Q. Xue, S. Ma, Y. Liang, J. Wang, Y. Wang, F. He, and M. Liu, "Weld bead geometry prediction of additive manufacturing based on neural network," 11th International Symposium on Computational Intelligence and Design, China, 2018, pp. 47-51.
  • [5] P.K. Jayashree, S. Sharma, and N. Shetty, "TIG welding parameters optimization of Al–Si–Mg ternary alloy–SiC powder reinforced composites using Taguchi and RSM techniques," Cogent Engineering, vol. 9, no. 1, 2022.
  • [6] S.K. Katheria, D. Kumar, T.A. Khan, and M.K. Singh, "Reality based skills development approach in welding technology: An overview," Materials Today: Proceedings, vol. 47, no. 19, pp. 7184-7188, 2021.
  • [7] C. Papakostas, C. Troussas, A. Krouska, and C. Sgouropoulou, "User acceptance of augmented reality welding simulator in engineering training," Education and Information Technologies, vol. 27, no. 1, pp. 791-817, 2022.
  • [8] C. Wu, C. Wen, and L. Wu, "A microcomputer-controlled welder training system," Computers & Education, vol. 20, no. 3, pp. 271-274, 1993.
  • [9] Y. Top, "Using Simulator in Training of Arc Welder," Sakarya University Journal of Science, vol. 2, no. 1, pp. 93-98, 1998.
  • [10] C. Oz, F. Findik, O. Iyibilgin, U. Soy, Y. Kiyan, S. Serttas et al., K. Ayar, S. Uslu, and Y. Yasar, "Welding simulators: from past to present day," Metal Dunyasi, vol. 201, pp. 108-111, 2010.
  • [11] D. Mavrikios, V. Karabatsou, D. Fragos, and G. Chryssolouris, "A prototype virtual reality-based demonstrator for immersive and interactive simulation of welding process," International Journal of Computer Integrated Manufacturing, vol. 9, pp. 294-300, 2006. [12] K. Fast, T. Gifford, and R. Yancey, "Virtual training for welding," Proceedings of the Third IEEE and ACM International Symposium on Mixed and Augmented Reality, 2004, pp. 298-299.
  • [13] S.A. White, M. Prachyabrued, T.L. Chambers, C.W. Borst, and D. Reiners, "Low-cost simulated mig welding for advancement in technical training," Virtual Reality, vol. 15, no. 1, pp. 69-81, 2011.
  • [14] https://www.lincolnelectric.com/en-gb/equipment/training-equipment /vrtex360/ pages/ vrtex-360.aspx Accessed 21 May 2018
  • [15] Soldamatic’s HyperReal-Sim™: What is it all about?, December 2022. [Online]. Available: https://seaberyat.com/en/hyperreal-sim-of-soldamatic-what-is-it-about/
  • [16] V.G. Bharat and P. Rajashekar, "Virtual reality for metal arc welding: a review and design concept," International Journal of Mechanical Engineering and Technology, vol. 8, no. 1, pp. 132-138, 2017.
  • [17] P.K. Palani, and N. Murugan, "Modeling and simulation of wire feed rate for steady current and pulsed current gas metal arc welding using 317L flux cored wire," The International Journal of Advanced Manufactoring Technology, vol. 34, pp. 1111-1119, 2007.
  • [18] Ö.K. Kalkan, Ş, Karabulut, and G. Höke, "Effect of virtual reality‑based training on complex industrial assembly task performance," Arabian Journal for Science and Engineering, vol. 46, no. 12, pp. 12697-12708, 2021.
  • [19] C. Oz, and M.C. Leu, "Human-computer interaction system with artificial neural network using motion tracker and data glove," International Conference on Pattern Recognition and Machine Intelligence, vol. 3776, pp. 280-286, 2005.
  • [20] C. Oz, and M.C. Leu, "American sign language word recognition with a sensory glove using artificial neural networks," Engineering Applications of Artificial Intelligence, vol. 24, no. 7, pp.1204-1213, 2011.
  • [21] S. Serttas, K. Ayar, G. Cit, and C. Oz, "Multi-threaded application for marching cubes algorithm," International Symposium On Innovative Technologies In Engineering and Science, Turkiye, 2014, pp. 821-825.
  • [22] C. Oz, S. Serttas, K. Ayar, and F. Findik, "Effect of virtual welding simulator on tig welding training," Journal of Materials Education, vol. 37, pp.197-218, 2015
  • [23] G. Cit, K. Ayar, and C. Oz, "A real-time virtual sculpting application by using an optimized hash-based octree," Turkish Journal of Electrical Engineering and Computer Science, vol. 24, no. 4, pp. 2274-2289, 2016.
  • [24] G. Cook, R. Barnett, D. Hartman, and A. Strauss, "Neural network systems techniques in weld modeling and control," Computer Aided and Integrated Manufacturing Systems Techniques and Applications, 1997.
  • [25] P. Li, M.T.C. Fang, and J. Lucas, "Modelling of submerged arc weld beads using self-adaptive offset neutral networks," Journal of Materials Processing Technology, vol. 71, no. 2, pp. 288-298, 1997.
  • [26] B. Chan, J. Pacey, and M. Bibby, "Modelling gas metal arc weld geometry using artificial neural network technology," Canadian Metallurgical Quarterly, vol. 38, no. 1, pp. 43-51, 1999.
  • [27] M.I.S. Ismail, Y. Okamoto, and A. Okada, "Neural network modeling for prediction of weld bead geometry in laser microwelding," Advances in Optical Technologies, 2013.
  • [28] N. Murugan, and V. Gunaraj, "Prediction and control of weld bead geometry and shape relationships in submerged arc welding of pipes," Journal of Materials Processing Technology, vol. 168, no. 3, pp. 478-487, 2005.
  • [29] D. Jo, Y. Kim, U. Yang, G.A. Lee, and J.S. Choi, "Visualization of virtual weld beads," Proceedings of the ACM Symposium on Virtual Reality Software and Technology, 2009, pp. 269-270.
  • [30] J. Xiong, G. Zhang, H. Gao, and L. Wu, "Modeling of bead section profile and overlapping beads with experimental validation for robotic gmaw-based rapid manufacturing," Robotics and Computer-Integrated Manufacturing, vol. 29, no. 2, pp. 417-423, 2013.
  • [31] P.K. Palani, and N. Murugan, "Optimization of weld bead geometry for stainless steel claddings deposited by fcaw," Journal of Materials Processing Technology, vol. 190, pp. 291-299, 2007.
  • [32] K.N. Gowtham, M. Vasudevan, V. Maduraimuthu, and T. Jayakumar, "Intelligent modeling combining adaptive neuro fuzzy inference system and genetic algorithm for optimizing welding process parameters," Metallurgical and Materials Transactions B, vol. 42, no. 2, pp. 385-392, 2011.
  • [33] J.E. Pinto-Lopera, J.M.S.T. Motta, and S.C.A. Alfaro, "Real-time measurement of width and height of weld beads in gmaw processes," Sensors, vol. 16, no. 9, pp. 1-14, 2016.
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Toplam 70 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Kaynak Teknolojileri
Bölüm Makaleler
Yazarlar

Kayhan Ayar 0000-0002-8599-0896

Soydan Serttaş 0000-0001-8887-8675

Gülüzar Çit 0000-0002-1220-0558

Cemil Öz 0000-0001-9742-6021

Fehim Fındık 0000-0003-2537-1951

Yayımlanma Tarihi 23 Ekim 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 12 Sayı: 4

Kaynak Göster

APA Ayar, K., Serttaş, S., Çit, G., Öz, C., vd. (2024). Development of a 3D Virtual Welding Simulator Using Weld Bead Created by Voxelization Technique. Düzce Üniversitesi Bilim Ve Teknoloji Dergisi, 12(4), 1977-1992. https://doi.org/10.29130/dubited.1323945
AMA Ayar K, Serttaş S, Çit G, Öz C, Fındık F. Development of a 3D Virtual Welding Simulator Using Weld Bead Created by Voxelization Technique. DÜBİTED. Ekim 2024;12(4):1977-1992. doi:10.29130/dubited.1323945
Chicago Ayar, Kayhan, Soydan Serttaş, Gülüzar Çit, Cemil Öz, ve Fehim Fındık. “Development of a 3D Virtual Welding Simulator Using Weld Bead Created by Voxelization Technique”. Düzce Üniversitesi Bilim Ve Teknoloji Dergisi 12, sy. 4 (Ekim 2024): 1977-92. https://doi.org/10.29130/dubited.1323945.
EndNote Ayar K, Serttaş S, Çit G, Öz C, Fındık F (01 Ekim 2024) Development of a 3D Virtual Welding Simulator Using Weld Bead Created by Voxelization Technique. Düzce Üniversitesi Bilim ve Teknoloji Dergisi 12 4 1977–1992.
IEEE K. Ayar, S. Serttaş, G. Çit, C. Öz, ve F. Fındık, “Development of a 3D Virtual Welding Simulator Using Weld Bead Created by Voxelization Technique”, DÜBİTED, c. 12, sy. 4, ss. 1977–1992, 2024, doi: 10.29130/dubited.1323945.
ISNAD Ayar, Kayhan vd. “Development of a 3D Virtual Welding Simulator Using Weld Bead Created by Voxelization Technique”. Düzce Üniversitesi Bilim ve Teknoloji Dergisi 12/4 (Ekim 2024), 1977-1992. https://doi.org/10.29130/dubited.1323945.
JAMA Ayar K, Serttaş S, Çit G, Öz C, Fındık F. Development of a 3D Virtual Welding Simulator Using Weld Bead Created by Voxelization Technique. DÜBİTED. 2024;12:1977–1992.
MLA Ayar, Kayhan vd. “Development of a 3D Virtual Welding Simulator Using Weld Bead Created by Voxelization Technique”. Düzce Üniversitesi Bilim Ve Teknoloji Dergisi, c. 12, sy. 4, 2024, ss. 1977-92, doi:10.29130/dubited.1323945.
Vancouver Ayar K, Serttaş S, Çit G, Öz C, Fındık F. Development of a 3D Virtual Welding Simulator Using Weld Bead Created by Voxelization Technique. DÜBİTED. 2024;12(4):1977-92.