Experimental and Numerical Analysis of the Potential Drop Method for Defects Caused by Dynamic Loads

The potential drop method (PDM) is employed for defect detection in conductive specimens by measuring the change in impedance. Due to its ability to comprehensively monitor large structures entirely and its high sensitivity to material changes, PDM is a promising method for structural health monitoring (SHM) of specimens subjected to dynamic loads. However, PDM is rarely used in SHM because with increasing length and cross-section of the specimen, the defect sensitivity decreases. In this paper, we investigate how the electrodynamic proximity effect can be utilized by proper arrangement of the measurement setup to enhance the defect sensitivity of PDM in SHM applications. Our analysis shows that by proper arrangement of the measurement setup, the proximity effect enhances the defect sensitivity up to 300% compared to that of measurement setups in which the proximity effect is not utilized. Additionally, with proper arrangement of the setup, we found that the proximity effect linearizes the relationship between defect-induced resistance change and crack depth, facilitating the estimation of crack depth. We validated the results of the electrodynamic simulations for our PDM sensor experimentally by applying dynamic loads to a specimen via a resonance testing machine while measuring the defect-induced resistance change caused by a growing fatigue crack. Enhancing the defect sensitivity enables the SHM of larger specimens and thus improves the performance of PDM as an SHM technique.