Ferromagnetic materials are widely used in engineering structures. Damages caused during manufacture and the use of ferromagnetic materials may seriously undermine the safety of the engineering structure, and even lead to serious industrial accidents. For the early damage testing problem of ferromagnetic materials, it is imperative to propose and adopt new nondestructive testing methods. The metal magnetic memory (MMM) method, which is also known as the micromagnetic testing method, can achieve the early detection of damages in ferromagnetic materials such as steels. However, due to the lack of the quantitative research, the MMM method is only applicable for damage localization. In this paper, the MMM method is utilized to quantitatively evaluate the stress and crack in ferromagnetic materials. The inverse model including the objective function and optimization parameters is proposed. The reconstruction approach is established based on the conjugate gradient inversion method and the exact line search algorithm. In the theoretical analysis, the effectiveness of the MMM method in quantitative determination regarding the position and size of defects is verified with the experimental signal of a hole defect. Following this, the theoretical analyses of localization and sizing of stress and crack are conducted by using the simulation results as the measured signals. It can be found from the results that the MMM method can be applicable for quantitative evaluation of surface rectangular cracks, surface stress concentration zone, convex-type defect, and so on. In addition, the influences of the signal selection, sampling rate, lift-off value, stress level, and noise amplitude on the quantitative analysis of early stress concentration are discussed in details.

Thermal barrier coating system plays key role in high temperature gas turbine blades. During the manufacture and in-service processes, defects are inevitable due to the inconsistent deformation and fatigue loading. The typical defects, e.g. interfacial debonding and crack in substrate, may significantly degrade the performance, safety and service life of gas turbine. However, it is challenging to non-destructively evaluate the small defects and/or coexistent multi-defects in thermal barrier coating system. Here, we propose a non-destructive method to detect the defects in thermal barrier coating system using the results of both infrared thermography and eddy current testing. Using this method, we detect interfacial debonding as small as 0.7 mm within 0.2 s and identify defect types which are essential for turbine blade fabrication and maintenance. By leveraging multi-physical fields, we achieve effective and quantitative evaluation of coexisting defects in thermal barrier coating system. This method integrates multiple non-destructive evaluation techniques and provides an approach to assess defects in multilayer structures without damaging them.

Inverse analysis is a promising tool for quantitative evaluation offering informative model-based prediction and providing accurate reconstruction results without pre-inspections for characterization criteria. For traditional defect inverse reconstruction, a large number of parameters are required to reconstruct a complex defect, and the corresponding forward modelling simulation is very time-consuming. Such issues result in ill-posed and complex inverse reconstruction results, which further reduces its practical applicability. In this paper, we propose and experimentally validate an inversion technique for the reconstruction of complexly-shaped delamination defects in a multilayered metallic structure using signals derived from infrared thermography (IRT) testing. First, we employ a novel defect parameterization strategy based on Fourier series fitting to represent the profile of a complicated delamination defect with relatively few coefficients. Secondly, the multi-medium element modelling method is applied to enhance a FEM fast forward simulator, in order to solve the mismatching mesh issue for mesh updating during inversion. Thirdly, a deterministic inverse algorithm based on a penalty conjugate gradient algorithm is employed to realize a robust and efficient inverse analysis. By reconstructing delamination profiles with both numerically-simulated IRT signals and those obtained through laser IRT experiments, the validity, efficiency and robustness of the proposed inversion method are demonstrated for delamination defects in a double-layered plate. Based on this strategy, not only is the feasibility of the proposed method in Infrared thermography NDT validated, but the practical applicability of inversion reconstruction analysis is significantly improved.