Voids and cracks detection in bulk superconductors through magnetic field and displacement signals

Large-grain REBa₂Cu₃O_7−δ (REBCO, RE = rare earth) bulk superconductors offer promising magnetic field trapping capabilities due to their high critical current density, making them ideal for many important applications such as trapped field magnets. However, for such large-grain superconductor bulks, there are lots of voids and cracks forming during the process of melting preparation, and some of them can be up to hundreds of microns or even millimeters in size. Consequently, these larger size voids/cracks pose a great threat to the strength of the bulks due to the inherent brittleness of superconductor REBCO materials. In order to ensure the operational safety of related superconducting devices with bulk superconductors, it is firstly important to accurately detect these voids/cracks in them. In this paper, we proposed a method for quantitatively evaluating multiple voids/cracks in bulk superconductors through the magnetic field and displacement response signals at superconductor bulk surface. The proposed method utilizes a damage index constructed from the magnetic field signals and displacement responses to identify the number and preliminary location of multiple defects. By dividing the detection area into subdomains and combining the magnetic field signals with displacement responses within each subdomain, a particle swarm algorithm was employed to evaluate the location and size parameters of the defects. In contrast to other evaluation methods using only magnetic field or displacement response signals, the combined evaluation method using both signals can identify the number of cracks effectively. Numerical studies demonstrate that the morphology of voids and cracks reconstructed using the proposed algorithm ideally matches real defects and is applicable to cases where voids and cracks coexist. This study provides a theoretical basis for the quantitative detection of voids/cracks in bulk superconductors.