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ASME Press Select Proceedings
International Conference on Computer and Automation Engineering, 4th (ICCAE 2012)
Jianhong Zhou
Jianhong Zhou
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ASME Press
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In the recent years there has been considerable interest in automatic monitoring of welding and ways to identify various conditions and faults in the system. This paper proposes a novel method for detection of voids in welding joints i.e. using adaptive chirplet analysis. It is shown that chirplet analysis can distinctively identify a fault in a welding joint. The arc weld sound signal sampled from the Pulsed-Gas Metal Arc Welding (P-GMAW) process was chosen for the analysis. Chirplet transform yielded distinctive feature extraction capabilities that provided the exact location of the fault occurrence in a work piece. Thus this paper establishes chirplet transform as an effective tool for better monitoring of a welding process.

Key Words
1 Introduction
2. Chirplet Transform
4. Experimental Procedure
5. Result and Discussion
6. Conclusion
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