Plasma evolution investigation and aging grade evaluation of heat resistant steel based on laser induced plasma images

Abstract

The accurate evaluation of heat-resistant steel deterioration using laser-induced breakdown spectroscopy (LIBS) is of great importance for the safe operation of high-temperature pressure equipment. Understanding how plasma expresses matrix properties and utilizing plasma information effectively can lead to achieving more effective detection methods. In this study, the plasma evolution and pulse fluctuations of typical heat-resistant steel T91 are studied based on plasma images to understand the different evolution stages and characteristics of plasma. T91 specimens with different aging grades are employed to investigate the expression form, evolution and identification of matrix information on plasma. Subsequently, the plasma images and the RSD images based on pulse–pulse relative standard deviation (RSD) were employed to build an aging grade evaluation model, the best model accuracies were 96.6% and 96.0%, respectively. A model combining these two image features achieved the highest accuracy at 99.8%. Finally, the effects of the delay time, region selection, and data coupling strategy on model performance were explored. The results indicate that the temporal–spatial characteristics, identification, and stability of plasma information have a significant effect on the performance of the model. This study deepens the understanding of the plasma evolution and matrix effect of heat-resistant steel and expands the application of plasma image information for property detection.