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Crack Detection in Metallic Components with Varying Surface Characteristics Using Laser Spot Scanning Thermography

EasyChair Preprint no. 8955

6 pagesDate: October 3, 2022

Abstract

Cracks are the most common cause of failure in the manufacturing of metal parts, hence technologies for detecting them are essential for defect-free production. In this study, a local laser spot excitation combined with robotic scanning is used to identify vertical cracks in titanium. It is feasible to observe anisotropies in the lateral diffusivity by capturing temporal temperature data with an infrared camera utilizing local thermal stimulation. The crack parameter may then be quantified based on the regional transient behavior of temperature distribution. In doing so, we present an advanced technique for distinguishing between contrast created by the surface oxide layer and contrast caused by the vertical crack. In addition, we provide results from a numerical simulation that looked at the notion of local heat excitation for crack parameter quantification. Thermal conduction, radiation, and convection all play a role in the simulation. The experimental and theoretical findings were found to be quite consistent.

Keyphrases: FEM, laser thermography, NDT, Robotic scanning, Surface crack detection

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:8955,
  author = {Sreedhar Unnikrishnakurup and Jonathan Zheng and Vinod Kumar and Carlos Manzano and Andrew Ngo},
  title = {Crack Detection in Metallic Components with Varying Surface Characteristics Using Laser Spot Scanning Thermography},
  howpublished = {EasyChair Preprint no. 8955},

  year = {EasyChair, 2022}}
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