Abstract
Welding sound signal is mainly produced by the arc heat and the vibration of weld pool. In order to seek the relationship between characteristics in sound signal frequency and arc length variation, energy in every frequency band had been analysed, we found that arc sound signal distributed in every frequency band of 0–20 kHz, while arc length increasing, the energy of every frequency band increases, and the energy of 0–5000 Hz frequency band can generally reflect the increase and mutation of arc length, the differences when arc increase same value are similar. So linear fitting has been done to the original signal and the signal after 2 layer db3 wavelet denoising, conclusions can be made as that the average total energy of sound peak signal and the arc length have linear relationship, and 2 layer db3 wavelet denoising can make the error of linear relation smaller.
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References
Tarn TJ, Chen SB, Zhou CJ (2007) Robotic welding, intelligence and automation. Springer, Berlin
Cayo EH, Alfaro SCA (2009) A non-intrusive GMA welding process quality monitoring system using acoustic sensing. Sensors 9(9):7150–7166
Luksa K (2003) Correspondence between sound emissions generated in the GMA welding process and signals registered in the arc circuit. Weld Int 17(6):438–441
Pal K, Bhattacharya S, Pal SK (2010) Investigation on arc sound and metal transfer modes for on-line monitoring in pulsed gas metal arc welding. J Mater Process Technol 210(10):1397–1410
Chen CM, Kovaeevie R, Jandgrie D (2003) Wavelet transform analysis of acoustic emission in monitoring friction stir welding of 6061 aluminum. Int J Mach Tools Manuaf 43:1383–1390
Tam J, Huissoon J (2005) In Developing psycho-acoustic experiments in gas metal arc welding. In: Proceedings of the IEEE international conference on mechatronics and automation, Niagara, Falls, pp 1112–1117
Chen B, Wang JF, Chen SB (2010) A study on application of multi-sensor information fusion in pulsed GTAW. Ind Robot Int J 37(2):168–176
Ladislav G, Janez G, Ivan P, Janez MS (2004) Feasibility study of acoustic signal for on-line monitoring in short circuit gas metal arc welding. Int J Mach Tools Manuf 44(5):555–561
Schieebeck E, Mueller G (1991) Audible range acoustic diagnosis of the MAG welding arc. Weld Int 5(7):572–576
Sánchez Roca A, Carvajal Fals H, Blanco Fernández J et al (2009) Stability analysis of the gas metal arc welding process based on acoustic emission technique. Weld Int 23(3)
Kang MJ, Rhee S (1991) A study on the development of the arc stability index using multiple regression analysis in short-circuit transfer region of gas metal arc welding. Proc Inst Mech Eng 215(2):195–205
Wang JF, Chen B, Chen HB, Chen SB (2009) Analysis of arc sound characteristics for gas tungsten argon welding. Sens Rev 29(3):240–249
Lv N, Zhong J, Chen H et al (2014) Real-time control of welding penetration during robotic GTAW dynamical process by audio sensing of arc length. Int J Adv Manufact Technol 1–15
Lv N, Xu Y, Zhang Z et al (2013) Audio sensing and modeling of arc dynamic characteristic during pulsed Al alloy GTAW process. Sens Rev 33(2):7–7
Acknowledgment
This work is supported by the National Natural Science Foundation of China under the Grant No. 61374071 and No. 61401275.
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Zhang, HH., Lv, N., Chen, SB. (2015). Study on the Relationship Between the Energy in Most Effective Frequency Range of Arc Sound Signal and the Change of Arc Height in Pulsed Al Alloy GTAW Process. In: Tarn, TJ., Chen, SB., Chen, XQ. (eds) Robotic Welding, Intelligence and Automation. RWIA 2014. Advances in Intelligent Systems and Computing, vol 363. Springer, Cham. https://doi.org/10.1007/978-3-319-18997-0_33
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DOI: https://doi.org/10.1007/978-3-319-18997-0_33
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