Accurate Detection of Weld Defects Using Chirplet Transform


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.

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

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