Experimental and numerical analysis of the potential drop method for defects caused by dynamic loads

In our paper “Experimental and Numerical Analysis of the Potential Drop Method for Defects Caused by Dynamic Loads”, we investigate how the electrodynamic proximity effect can be utilized to enhance  the  defect   sensitivity  of  PDM  in   SHM  applications  by  proper  arrangement  of  the measurement setup. We showed how eddy current effects present in our PDM setup can be modeled analytically and numerically. Lock-in technique and the application of the skin effect allow high- resolution impedance measurements and a parallel temperature measurement helps to compensate cross influences due to temperature effects. 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.

In the experiment, we conducted measurements with our PDM sensor during the development of a fatigue  crack  generated  by  dynamic  loading  in  a  resonance-testing  machine.  The  experimental findings agree well with the simulations.

This work introduces models that support the design of measuring systems for crack detection based on the potential drop method. Enhancing the defect sensitivity by making use of lock-in technique, the skin effect and the proximity effect enables the SHM of larger specimens.