Wavelet Package for the In-Process Monitoring of Gas Metal Arc Welding Mild Steel

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Abstract:

The acoustic signals were strongly related to the behavior of the arc column, the molten pool and droplet transfer in gas metal arc welding(GMAW).In this study, all the work pieces (JIS SS400) were welded at the same speed with different currents using a gas metal arc; the purpose was to observe the relationship between these factors. Using a sound capture card and microphone we collected the audio signals generated by the welding. In this paper, wavelet package transformation (WPT) decomposes the sounds signals into 128 channels within the frequency domain. The properties of the audio signals were analyzed by the wavelet-based channel energy. The ROC (Receiver Operating Characteristic) parameters, (Ac, Se, Sp, ppv, and npv), were used for classification performance evaluation. Experimental results also show that acoustic emissions are useful in the quality control of plasma arc welding.

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3652-3656

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October 2011

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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[1] Kamal Pal, Sandip Bhatta Charya, and Surjya K. : Pal, Investigation on Arc Sound and Metal Transfer modes for On-line Monitoring in Pulsed Gas Metal Arc Welding, Journal of Processing Technology, vol. 210(2010), pp.1397-1410.

DOI: 10.1016/j.jmatprotec.2010.03.029

Google Scholar

[2] Yaowen Wang and Pensheng Zhao: Noncontact acoustic analysis monitoring of plasma arc welding, International Journal of Pressure Vessels and Piping, vol. 78(2001), pp.43-47.

DOI: 10.1016/s0308-0161(00)00085-5

Google Scholar

[3] H.K. Tonsho, M. Jung , S. Mannel and W. Rietz : Using acoustic emission signals for monitoring of production processes, Ultrasonics, vol. 37(2000), p.681–686.

DOI: 10.1016/s0041-624x(00)00026-3

Google Scholar

[4] H. Shinno and H. Hashizume: In-process Monitoring Method Environment Based on Simultaneous Multiphenomena sensing , annals of the CIRP Vol. 46(1997).

DOI: 10.1016/s0007-8506(07)60774-4

Google Scholar

[5] J Shao and Y Yan : Review of techniques for On-line Monitoring and Inspection of Laser Welding, Institute of Physics Publishing, Journal of Physics (2005), p.101–107.

Google Scholar

[6] E. Saad, H. Wang and R. Kovacevic : Classification of molten pool modes in variable polarity plasma arc welding based on acoustic signature, Journal of Materials Processing Technology, vol. 174(2006) , p.127–136.

DOI: 10.1016/j.jmatprotec.2005.03.020

Google Scholar

[7] Y. Wang and P. Zhao : Plasma-arc Welding Sound Signature for On-line Quality Control, ISIJ International, vol. 41, No. 2(2001), p.164–167.

DOI: 10.2355/isijinternational.41.164

Google Scholar

[8] Y. Wang and Q. Chen : On-line quality monitoring in plasma-arc welding, Journal of Materials Processing Technology, vol. 120(2002) , p.270–274.

DOI: 10.1016/s0924-0136(01)01190-6

Google Scholar

[9] Q. Liu, X. Chen and N. Gindy : Investigation of acoustic emission signals under a simulative environment of grinding burn, International Journal of Machine Tools & Manufacture, vol. 46(2006), p.284–292.

DOI: 10.1016/j.ijmachtools.2005.05.017

Google Scholar

[10] C.M. Chen, R. Kovacevic and D. Jandgric : Wavelet transform analysis of acoustic emission in monitoring friction stir welding of 6061 aluminum, International Journal of Machine Tools & Manufacture, vol. 43(2003), p.1383–1390.

DOI: 10.1016/s0890-6955(03)00130-5

Google Scholar

[11] Ladislav Grad, Janez Grum, Ivan Polajnar and Janez Marko Slabe : Feasibility study of acoustic signals for on-line monitoring in short circuit gas metal arc welding, International Journal of Machine Tools & Manufacture, vol. 44(2004), pp.555-561.

DOI: 10.1016/j.ijmachtools.2003.10.016

Google Scholar

[12] M. Nadler and E. P. Smith, Pattern Recognition Engineering. New York: Wiley-Interscience.

Google Scholar

[13] S. Gefen, O. J. Tretiak, C. W. Piccoli, K. D. Donohue, A. P. Petropulu, P. M. Shankar, V. A. Dumane, L. Huang, M. A. Kutay, V. Genis, F. Forsberg. J. M. Reid, and B. B. Goldberg, ROC analysis of ultrasound tissue characterization classifiers for breast cancer diagnosis, IEEE Trans. Med. Imag., vol. 22, pp.170-177, Feb. (2003).

DOI: 10.1109/tmi.2002.808361

Google Scholar