Skip to Main Content
ASME Press Select Proceedings

International Conference on Computer and Automation Engineering, 4th (ICCAE 2012)

Jianhong Zhou
Jianhong Zhou
Search for other works by this author on:
No. of Pages:
ASME Press
Publication date:

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.

This content is only available via PDF.
Close Modal
This Feature Is Available To Subscribers Only

Sign In or Create an Account

Close Modal
Close Modal