Developing signal processing method for recognizing defects in metal samples based on heat diffusion properties in sonic infrared image sequences

Abstract

Abstract. In sonic infrared (SonicIR) imaging, heat is generated in defect areas during the sonic pulse; the heat appears bright in SonicIR images as the indication of a defect. However, in practical applications of SonicIR, there are lots of disturbing bright areas in infrared images, such as heat reflection and paint problem. When crack size is small, the generated heat appears not bright enough to be recognizable. Based on heat diffusion properties in the one-dimensional temporal and two-dimensional spatial domain, a method is developed to automatically recognize defect signals from SonicIR image sequences. The algorithm is verified with the SonicIR image sequences of 100 metal plates which may have different thickness, materials, or crack sizes. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.