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The aim of this research is to propose a new efficient and reliable approach on the field of Non Destructive Testing (NDT), for the characterization of cracks in non-ferromagnetic material by Electromagnetic Acoustic Transducer (EMAT). EMAT is an ultrasonic technique that generates and detects ultrasonic waves in the conductive material without physical contact. The research goes through two principal phases. The first, which is a forward model, is based on Finite Element Method (FEM). The FEM is applied to simulate the EMAT response (output voltage) to the material under test in order to build a database for the inversion tool. The second is the inverse model and depends on the Partial Least Square Regression (PLSR) method, as it is a fast, simple, and accurate inversion tool, in order to estimate the depth and width of the cracks on the surface of non-ferromagnetic materials. PLSR is a dimensionality reduction method which aims to model the relationship between the matrix of independent variables (predictors) (X) and the matrix of dependent variables (response) (Y ). The purpose of PLSR is to find the Latent Variables (LV) that have a higher ability of prediction by projecting original predictors into a new space of reduced dimensions.

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─ Industrial structure are exposed to microstructural changes caused by fatigue cracking, corrosion and thermal aging. Generally, a hidden crack is very dangerous because it is difficult to detect by Non-Destructive Evaluation (NDE) techniques. This paper presents a new approach to estimate the hidden cracks dimensions inside a stainless steel plate based on the EMAT signal. The received signal by EMAT is simulated using the Finite Element Method (FEM). Then, the identification of the hidden crack sizes is performed via the combination of two techniques; the first one is the Time-of-Flight (ToF) technique which was applied to estimate the crack height by the evaluation of the difference between the ToF of the healthy form and the defective form. Then, the crack width is estimated by the solution of the inverse problem from the received signal based on a meta-heuristic algorithm called Teaching learning Based optimization (TLBO). The obtained results illustrate the sensitivity of the EMAT sensor to the variation of the crack sizes. Moreover, the quantitative evaluation of the cracks dimensions, show clearly the efficiency and reliability of the adopted approache.

Industrial equipment can be exposed to various types of damage during their long exploitation in harsh environments which might lead to corrosion cracking. Typically, a hidden crack is very dangerous since it is difficult to be detected by Non-Destructive Testing (NDT) techniques. Moreover, the integrity requirements of metallic structures cannot be satisfied by simply detecting the existence of cracks. However, the quantitative description of the cracks is still an issue that should be solved. This paper introduces a new approach to estimate the dimensions of hidden cracks inside a stainless steel plate based on Shear Vertical (SV) waves generated by an Electromagnetic Acoustic Transducer (EMAT). The Finite Elements Method (FEM) has been used to model the acquired signal by EMAT. Then, the characterization of hidden cracks is carried out by combining two methods; Time-of-Flight (ToF) technique that has been used to evaluate the crack height, and the Partial Least Square Regression (PLSR) method that has been used to estimate the crack width. The obtained results demonstrate the efficiency and the reliability of the adopted approach concerning the quantitative evaluation of the crack dimensions.