APPLICATIONS OF FUZZY CONTROL IN GAS SHIELDED ARC WELDING SEAM TRACKING SYSTEM
Year 2016,
Volume: 57 Issue: 674, 57 - 64, 30.03.2016
Ahmet Öztürk
,
İlhan Asiltürk
Hayrettin Düzcükoğlu
,
Ömer Aydoğdu
Abstract
In this study welding seam tracking used seam tracking sensors in the welding systems by the horizontal and vertical welding defines the region. This defined the welding seam regions then is calculated using fuzzy control algorithm. Fuzzy rule tables prepared to be done with the welding process
described. The welding seam tracking changes in the X and Y coordinates of thanks to fuzzy logic
control algorithm is estimated. When the rate of change of the control elements or the welding region
of the angular changes are not sudden, X and Y movements directions providing speed of the control
elements is also fixed. If sudden changes occur in welding seam tracking, fuzzy logic algorithm calculates the amount of change of the error by sending a signal to adjust the speed and motion of the
elements has the ability to control the elements. Thanks to this, the welding torch movements of with
weld seams have been determined to be in the suitable location.
References
- 1. Yanling, X., Gu, F., Shanben, C., Jujia, Z. 2015. "Computer Vision Technology for Seam Tracking in Robotic GTAW and GMAW," Robotics and Computer-Integrated Manufacturing, vol. 32, p. 25-36.
- 2. He, Y., Xe, Y., Chen, Y., Chen, H., Chen, S. 2015. “Weld Seam Profile Detection and Feature Point Extraction for Multi-Pass Rout Eplanning Based on Visual Attention Model,” Robotics and Computer-Integrated Manufacturing, vol. 37, p. 251–261.
- 3. Wei, H., Radovan, K. 2012. “Development of a Real-Time Laser-Based Machine Vision System,” International Journal of Advanced Manufacturing Technology Journal, vol. 63, p. 235–248.
- 4. Moradi, N., Dezfulli, B., Mashalah, A., Alavi, C. 2013. “Development a Vision Based Seam Tracking System for None Destructive Testing Machines,” International Journal of Computer Science & Network Solutions, vol. 1, p. 45-56.
- 5. Du, J., Hua, L., Ge, S., Gu, P. 2012. “Weighted Multi-Sensor Data Fusion Based on Fuzzy Kalman Filter for Seam Tracking of the Welding Robots,” 2nd International Conference on Advanced Engineering Materials and Technology (AEMT 2012), July 6-8, 2012, China, p. 800-805.
- 6. Zou, Y., Du, D., Chang, B., Ji, L., Pan, J. 2015. "Automatic Weld Defect Detection Method Based on Kalman Filtering for Real-Time Radiographic Inspection of Spiral Pipe," NDT&E, vol. 72, p. 1-9.
- 7. Luo, Z., Dai, J. S., Wang, C., Wang, F., Tian, Y., Zhao, M. 2012. “Predictive Seam Tracking with Iteratively Learned Feedforward Compensation for High-Precision Robotic Laser Welding,” Journal of Manufacturing Systems, vol. 31, issue 1, p. 2–7.
- 8. Braunreuther, S., Hammerstingl, V., Schweier, M., Theodossiadis, G., Reinhart, G., Zaeh, M. 2015. “Welding Joint Detection by Calibrated Mosaicking with Laser Scanner
Systems,” CIRP Journal of Manufacturing Science and Technology, vol. 10, p. 16–23.
- 9. Huang, Y., Gao, X., You, D., Li, Z. 2012. “Investigation of Laser Welding Seam Tracking Based on Visual Sensing,” 2nd International Conference on Electronic & Mechanical Engineering and Information Technology, p. 1197- 1200.
- 10. Heber, M., Lenz, M., Rüthe, R., Bischof, H., Fronthaler, H., Croonen, G. 2013. “Weld Seam Tracking and Panorama Image Generation for on-Line Quality Assurance,” The International Journal of Advanced Manufacturing Technology, vol. 65, issue 9, p. 1371-1382.
- 11. Xiong, Z., Wan, W., Pan, J. 2011. “Application of Fuzzy Edge Detection in Weld Seam Tracking System. Robotic Welding,” Intelligence and Automation Lecture Notes in
Electrical Engineering, vol. 88, p. 323-330.
- 12. Bracun, D., Sluga, A. 2015. “Stereo Vision Based Measuring System for Online Welding Path Inspection,” Journal of Materials Processing Technology, vol. 223,
p. 28–336.
- 13. Xu, Y., Yu, H., Zhong, J., Lin, T., Shanben, C. 2012. “RealTime Seam Tracking Control Technology During Welding Robot Gtaw Process Based on Passive Vision Sensor,” Journal of Materials Processing Technology, vol. 212, issue 8, p. 1654–1662.
- 14. Davila-Rios, I., Lopez-Juarez, I., Navarro-Gonzalez, L. 2010. “Welding Seam Tracking Controller Simulation Using Fuzzy Logic,” 1st International Congress on Instrumentation and Applied Sciences, 26th-29th October 2010, Mexico.
- 15. Öztürk, A. 2011. “Bulanık Mantık Kontrollü Kaynak Ağzı İzleyen kaynak Robotunun Tasarımı ve İmalatı,” Yüksek Lisans Tezi, Selçuk Üniversitesi, Konya.
GAZALTI KAYNAĞINDA BULANIK MANTIK KONTROLLÜ İZ TAKİP SİSTEMİNİN UYGULANMASI
Year 2016,
Volume: 57 Issue: 674, 57 - 64, 30.03.2016
Ahmet Öztürk
,
İlhan Asiltürk
Hayrettin Düzcükoğlu
,
Ömer Aydoğdu
Abstract
Bu çalışmada, kaynak iz takibinde kullanılan iz takip sensörleri, kaynak yapılacak sistemlerde yatay
ve dikey hareket ederek kaynak iz bölgesini tanımlamaktadır. Tanımlanan bu kaynak iz bölgesi, daha
sonra fuzzy kontrol algoritması kullanılarak hesaplanmaktadır. Hazırlanan bulanık mantık kural tabloları ile yapılacak kaynak süreçleri tanımlanmıştır. Kaynak iz takibinde X ve Y koordinatlarındaki
değişimler bulanık mantık kontrol algoritması sayesinde tahmin edilmektedir. Kontrol elemanlarındaki hız değişimleri veya kaynak bölgesi açısal değişimler ani olmadığından, X ve Y yönlerindeki
hareketleri sağlayan kontrol elemanlarının hızları da sabit olmaktadır. Eğer kaynak izi takibinde ani
olarak değişmeler meydana gelirse, bulanık mantık algoritması hata değişim miktarını hesaplayıp
hareket elemanlarına sinyal göndererek kontrol elemanlarının hızlarını değiştirmektedir. Bu sayede,
kaynak torcunun pozisyon hareketleri kaynak izi takibiyle tespit edilmiştir.
References
- 1. Yanling, X., Gu, F., Shanben, C., Jujia, Z. 2015. "Computer Vision Technology for Seam Tracking in Robotic GTAW and GMAW," Robotics and Computer-Integrated Manufacturing, vol. 32, p. 25-36.
- 2. He, Y., Xe, Y., Chen, Y., Chen, H., Chen, S. 2015. “Weld Seam Profile Detection and Feature Point Extraction for Multi-Pass Rout Eplanning Based on Visual Attention Model,” Robotics and Computer-Integrated Manufacturing, vol. 37, p. 251–261.
- 3. Wei, H., Radovan, K. 2012. “Development of a Real-Time Laser-Based Machine Vision System,” International Journal of Advanced Manufacturing Technology Journal, vol. 63, p. 235–248.
- 4. Moradi, N., Dezfulli, B., Mashalah, A., Alavi, C. 2013. “Development a Vision Based Seam Tracking System for None Destructive Testing Machines,” International Journal of Computer Science & Network Solutions, vol. 1, p. 45-56.
- 5. Du, J., Hua, L., Ge, S., Gu, P. 2012. “Weighted Multi-Sensor Data Fusion Based on Fuzzy Kalman Filter for Seam Tracking of the Welding Robots,” 2nd International Conference on Advanced Engineering Materials and Technology (AEMT 2012), July 6-8, 2012, China, p. 800-805.
- 6. Zou, Y., Du, D., Chang, B., Ji, L., Pan, J. 2015. "Automatic Weld Defect Detection Method Based on Kalman Filtering for Real-Time Radiographic Inspection of Spiral Pipe," NDT&E, vol. 72, p. 1-9.
- 7. Luo, Z., Dai, J. S., Wang, C., Wang, F., Tian, Y., Zhao, M. 2012. “Predictive Seam Tracking with Iteratively Learned Feedforward Compensation for High-Precision Robotic Laser Welding,” Journal of Manufacturing Systems, vol. 31, issue 1, p. 2–7.
- 8. Braunreuther, S., Hammerstingl, V., Schweier, M., Theodossiadis, G., Reinhart, G., Zaeh, M. 2015. “Welding Joint Detection by Calibrated Mosaicking with Laser Scanner
Systems,” CIRP Journal of Manufacturing Science and Technology, vol. 10, p. 16–23.
- 9. Huang, Y., Gao, X., You, D., Li, Z. 2012. “Investigation of Laser Welding Seam Tracking Based on Visual Sensing,” 2nd International Conference on Electronic & Mechanical Engineering and Information Technology, p. 1197- 1200.
- 10. Heber, M., Lenz, M., Rüthe, R., Bischof, H., Fronthaler, H., Croonen, G. 2013. “Weld Seam Tracking and Panorama Image Generation for on-Line Quality Assurance,” The International Journal of Advanced Manufacturing Technology, vol. 65, issue 9, p. 1371-1382.
- 11. Xiong, Z., Wan, W., Pan, J. 2011. “Application of Fuzzy Edge Detection in Weld Seam Tracking System. Robotic Welding,” Intelligence and Automation Lecture Notes in
Electrical Engineering, vol. 88, p. 323-330.
- 12. Bracun, D., Sluga, A. 2015. “Stereo Vision Based Measuring System for Online Welding Path Inspection,” Journal of Materials Processing Technology, vol. 223,
p. 28–336.
- 13. Xu, Y., Yu, H., Zhong, J., Lin, T., Shanben, C. 2012. “RealTime Seam Tracking Control Technology During Welding Robot Gtaw Process Based on Passive Vision Sensor,” Journal of Materials Processing Technology, vol. 212, issue 8, p. 1654–1662.
- 14. Davila-Rios, I., Lopez-Juarez, I., Navarro-Gonzalez, L. 2010. “Welding Seam Tracking Controller Simulation Using Fuzzy Logic,” 1st International Congress on Instrumentation and Applied Sciences, 26th-29th October 2010, Mexico.
- 15. Öztürk, A. 2011. “Bulanık Mantık Kontrollü Kaynak Ağzı İzleyen kaynak Robotunun Tasarımı ve İmalatı,” Yüksek Lisans Tezi, Selçuk Üniversitesi, Konya.