State Monitoring System of Robot Welding Gun Based on ART2 Neural Networks

In Soo Lee; Won-Sub Tae; Yoon-Soo Kim; Myung-hwan Jeong; Jong-Pil Seo; Kyung-Jin Na; Dong-Jin Sung; Soo-Young Ha

doi:10.15377/2409-9694.2017.04.1

Articles

Vol. 4 (2017)

State Monitoring System of Robot Welding Gun Based on ART2 Neural Networks

In Soo Lee⁺⁻
Won-Sub Tae⁺⁻
Yoon-Soo Kim⁺⁻
Myung-hwan Jeong⁺⁻
Jong-Pil Seo⁺⁻
Kyung-Jin Na⁺⁻
Dong-Jin Sung⁺⁻
Soo-Young Ha ⁺⁻

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DOI: https://doi.org/10.15377/2409-9694.2017.04.1
Published: 10.08.2017

Abstract

In this paper, we propose an aging state monitoring system for robotic welding gun using ART2 NN (adaptive resonance theory 2 neural network) with uneven vigilance parameters and inspection equipment data. In this method, the inspection equipment data used for diagnosis of robotic welding gun via ART2 NN modules. The Graphical User Interface (GUI) program by Lab VIEW designed for convenient operation of the monitoring system. We also carried out the computer simulation to confirm the suitability of the proposed monitoring system.

References

Wagner J and Shoureshi R. A Failure Isolation Strategy for Thermofluid System Diagnostics. ASME J. Eng. for Industry 1993; 115: 459-465. https://doi.org/10.1115/1.2901790
Isermann R. Process Fault Detection Based on Modeling and Estimation Methods-a Survey. Automatica 1984; 20(4): 387-404. https://doi.org/10.1016/0005-1098(84)90098-0
Polycarpou MM and Vemuri AT. Learning Methodology for Failure Detection and Accommodation. IEEE Contr Shyest Mag 1995; 16-24.
Sorsa T, Koivo HN and Koivisto H. Neural Networks in Process Fault Diagnosis. IEEE Trans Syst Man and Cybern 1991; 21(4): 815-825. https://doi.org/10.1109/21.108299
Kramer MA and Leonard JA. Diagnosis Using Back Propagation Neural Networks-Analysis and Criticism. Computers Chem Engr 1990; 14(12): 1323-1338, 1990.
Lee IS, Kim JT, Lee JW, Lee YJ and Kim KY. Neural Networks-Based Fault Detection and Isolation of Nonlinear Systems. IASTED International Conference on Neural Networks and Computational Intelligence, Cancun 2003; 142-147.
Lee IS and Lee G. Fault Detection and Isolation Using Artificial Neural Networks. Proc of the ISCA Int’l Conference on Computer Applications in Industry and Engineering 2006; 335-340, Las Vegas, 2006.
Srinivasan A and Batur C. Hopfield /ART-1 neural networkbased fault detection and isolation. IEEE Trans. Neural Networks 1994; 5(6): 890-899. https://doi.org/10.1109/72.329685
Lee IS, Shin PJ and Jeon GJ. ART2 Multiple faults diagnosis of a linear system using ART2 neural networks. Journal of Institute of Control, Robotics and Systems 1997; 3(3): 244-251.
Kung SY. Digital Neural Networks. Prentice Hall, 1993.

Keywords

Robotic welding gun, inspection data, state monitoring system, ART2 neural network, GUI.

How to Cite

In Soo Lee, Won-Sub Tae, Yoon-Soo Kim, Myung-hwan Jeong, Jong-Pil Seo, Kyung-Jin Na, Dong-Jin Sung, & Soo-Young Ha . (2017). State Monitoring System of Robot Welding Gun Based on ART2 Neural Networks. International Journal of Robotics and Automation Technology, 4, 1–8. https://doi.org/10.15377/2409-9694.2017.04.1

[1] Wagner J and Shoureshi R. A Failure Isolation Strategy for Thermofluid System Diagnostics. ASME J. Eng. for Industry 1993; 115: 459-465. https://doi.org/10.1115/1.2901790

[2] Isermann R. Process Fault Detection Based on Modeling and Estimation Methods-a Survey. Automatica 1984; 20(4): 387-404. https://doi.org/10.1016/0005-1098(84)90098-0

[3] Polycarpou MM and Vemuri AT. Learning Methodology for Failure Detection and Accommodation. IEEE Contr Shyest Mag 1995; 16-24.

[4] Sorsa T, Koivo HN and Koivisto H. Neural Networks in Process Fault Diagnosis. IEEE Trans Syst Man and Cybern 1991; 21(4): 815-825. https://doi.org/10.1109/21.108299

[5] Kramer MA and Leonard JA. Diagnosis Using Back Propagation Neural Networks-Analysis and Criticism. Computers Chem Engr 1990; 14(12): 1323-1338, 1990.

[6] Lee IS, Kim JT, Lee JW, Lee YJ and Kim KY. Neural Networks-Based Fault Detection and Isolation of Nonlinear Systems. IASTED International Conference on Neural Networks and Computational Intelligence, Cancun 2003; 142-147.

[7] Lee IS and Lee G. Fault Detection and Isolation Using Artificial Neural Networks. Proc of the ISCA Int’l Conference on Computer Applications in Industry and Engineering 2006; 335-340, Las Vegas, 2006.

[8] Srinivasan A and Batur C. Hopfield /ART-1 neural networkbased fault detection and isolation. IEEE Trans. Neural Networks 1994; 5(6): 890-899. https://doi.org/10.1109/72.329685

[9] Lee IS, Shin PJ and Jeon GJ. ART2 Multiple faults diagnosis of a linear system using ART2 neural networks. Journal of Institute of Control, Robotics and Systems 1997; 3(3): 244-251.

[10] Kung SY. Digital Neural Networks. Prentice Hall, 1993.