Optimal Selection of the Reference Potential Probe Point in DCPD Real-Time Monitoring of Crack Growth Rate

Abstract

Quantitatively monitor the crack growth rate of material stress corrosion cracking (SCC) in an autoclave that simulates a high-temperature and high-pressure water environment, and the direct current potential drop (DCPD) method is the main method. Since the DCPD method tests micro-nano-voltage drop signals, the monitoring signal is weak and easy to be interfered by the environment. To reduce and balance the error caused by the temperature drift and other factors to the monitoring accuracy, it is very important to reasonably select the position of the reference potential probe point. In this study, genetic algorithm (GA), finite element method (FEM), and experimental analysis are used to optimize the position of the reference potential probe point of the compact tensile (CT) sample. Finite element method is used to analyze the electric potential field of the compact tensile sample, a mathematical model of the measurability and crack independence of the reference potential difference are constructed, genetic algorithm is used to find the optimal reference potential difference (RPD) probe point position, and finally, the crack monitoring experiments are performed to evaluate the feasibility of algorithm optimization results. The results indicate that the RPD measured at the current input point and the upper right position of the CT sample can provide the maximum compensation for the potential on both sides of the crack and make the performance of the monitoring signal optimal.