Infrared Emissivity Analysis Model for Rough-Textured Surfaces

The widespread use of infrared temperature measurement across various industries hinges on the accuracy of such measurements, which is directly affected by the surface infrared emissivity. Consequently, understanding and investigating surface infrared emissivity is paramount. This study proposes an infrared emissivity analysis model specifically for rough-textured surfaces, acknowledging the significant influence of surface roughness on material infrared emissivity. Initially, a power spectrum analysis of random roughness is performed, and the positive and negative power law components of the rough surface model are constructed using the Monte Carlo method and fractal theory, respectively. Subsequently, the infrared emissivity model for rough-textured surfaces is established leveraging the Kirchhoff approximation and perturbation method. To validate the effectiveness of the infrared emissivity model, the FDTD optical simulation software is employed to simulate the infrared emissivity of rough-textured surfaces with diverse fractal dimensions (D), characteristic length scales (G), and surface textures. Finally, the model is applied to the temperature measurement system of aluminum alloy friction stir welding, where a comparative analysis of the infrared measurement accuracy before and after correction is conducted to verify the model's accuracy.