Study on the Optimization of b-Value for Analyzing Weld Defects in the Primary System

This study presents a method to add a crack analysis algorithm to the Acoustic Leak Monitoring System (ALMS) to detect and evaluate the crack growth process in the primary system piping of nuclear power plants. To achieve this, a fracture test was conducted by applying stepwise loading to welded specimens that simulate the cold leg section, and acoustic emission (AE) signals were measured in relation to the increase in strain using an AE testing system. The experimental results indicated that the stability and instability of cracks could be assessed through the Kaiser effect and the Felicity effect when detecting crack growth using AE signals. Additionally, by utilizing both root mean square (RMS) and amplitude parameters simultaneously to calculate the b-value, it was confirmed that the RMS-based b-value minimizes the effects of AE signal attenuation and allows for a more stable assessment of crack progression. This demonstrates that the RMS, which reflects signal energy, is effective for real-time monitoring of the crack growth state. Finally, the results of this study suggest the potential for real-time crack monitoring using AE data in piping systems of critical structures, such as nuclear power plants; by adding a simple AE analysis method to the ALMS system, a practical approach has been derived that enhances the safety of the structure and allows for quantitative assessment of crack progression. Future research is expected to further refine the AE parameters and algorithms, leading to the advancement of safety monitoring systems in various industrial settings.