Sensitive and Reliable Eddy Current Array System for Microdefects in Turbine Blades

The defects including cavities, inclusions, and microcracks are prone to be formed during the directional solidification process of superalloy turbine blades. Eddy current testing is challenged by low sensitivity and lift-off noise due to the low conductivity and geometric changes of curved surfaces. An eddy current array system is designed in this work, integrated a self-adaptive elastic probe and signal processing algorithms. Firstly, an in-plane differential probe based on the can-shaped magnetic core is developed, where the eddy current density is directionally enhanced through magnetic field shielding to amplify defect response, while lift-off noise is compensated using a self-adaptive elastic structure. Secondly, an adaptive wavelet threshold denoising algorithm and multi-channel fusion algorithm based on array topology prior knowledge, enabled effective separation of defect signals from noise. Finally, a hardware system based on multi-channel demodulation is developed to improve detection speed and capability. Experimental results demonstrate that the system achieves reliable detection of 0.1 mm defects at scanning speed of 80 cm/s, achieved a detection probability of 98%. This performance significantly outperforms existing methodologies and provides an effective solution for identifying micro-defects in low-conductivity materials, particularly in critical components such as turbine blades.