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

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 diffu- sion properties in the one-dimensional temporal and two-dimensional spa- tial 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 differ- ent thickness, materials, or crack sizes.