Nondestructive Evaluation Problems Research Articles

Image analysis and CNN-based crack depth estimation using eddy current data

This study presents a comprehensive approach for crack depth estimation utilizing advanced image analysis techniques and a Convolutional Neural Network (CNN) model. The aim is to enhance accuracy and reliability in predicting crack depths, particularly for sub-millimeter cracks. The research addresses challenges arising from noise in images by employing a pre-processing technique and augmentation methods. The proposed method's effectiveness is showcased through its application to experimental crack data from diverse specimens. The outcomes exhibit a Mean Relative Error (MRE) of around 6%, indicating a high level of precision. These results affirm the potential of the methodology for real-world industrial applications. Additionally, the study explores the integration of eddy current image processing with CNN for Non-Destructive Evaluation (NDE) problems, offering a new approach for tiny surface-crack detection and characterization.

Diagnostic complex «MicroLab-Z2» for non-destructive evaluation of structural and deformation parameters of metal conscructions

The behavior of the construction under the influence of external factors is determined by three key groups of parameters of the metal composition (chemical, structural and deformation). Obtaining information about these parameters directly on the construction will effectively solve the problem of assessing its actual technical condition. The problem of non-destructive evaluation of the chemical composition of a metal is solved using portable spectrometers. The MicroLab-Z2 diagnostic complex has been developed to evaluate the other two groups of parameters. It has two functional blocks. The surface preparation unit ensures that the surface of the construction site has a roughness, flatness and level of applied mechanical hardening corresponding to the laboratory preparation of metallographic grinds. The research unit is a platform on which a metallographic microscope and a portable microhardness tester are installed. It allows metallographic researches with magnification up to x1000, surface microindentation, measurement of microhardness values at load of 0—200 gs and optical study of the morphology of imprints in any spatial position. The reliability of the data obtained by the MicroLab-Z2 diagnostic complex has been confirmed during comparative tests with stationary equipment. With the help of the developed device, an assessment of the structure parameters, contamination of metal with non-metallic inclusions, assessment of the degree of hardening and embrittlement of metal, detection of aging processes can be performed. The use of the MicroLab-Z2 diagnostic complex for operational non-destructive evaluation of structural and deformation parameters of metal constructions will allow us to reach a qualitatively different level of efficiency in performing production and input control of manufactured products, assessing the maintainability of defects, planning repairs and other compensating measures, and industrial safety expertise.

Old but not obsolete: Dimensional analysis in nondestructive testing and evaluation

This paper proposes dimensional analysis for solving Non-Destructive Testing & Evaluation (NDT&E) problems. This is the first time that this approach has been adopted in the framework of NDT&E, and the paper ushers in the development of probes and methods for simultaneously estimating several parameters with a simple approach. The most important theorem of dimensional analysis is Buckingham’s π theorem, based on the concept that the laws of the physics do not depend on the particular set of units chosen. At the core of this theorem is a systematic reduction in the number of variables describing a physical problem. This reduction is equal to k, the number of fundamental dimensions required to describe the variables of the physical problem in its original setting. This makes the approach ideal when the number of variables in the physical problem is not much greater than k. In this paper, we demonstrate the approach’s effectiveness in the simple problem of simultaneously estimating the thickness and electrical conductivity of a conducting plate, via Eddy Current Testing. The approach is original, effective, efficient, and currently patent-pending. All the aspects, from theory to experimental validation, are provided, and it is proved that the proposed method achieves a very good degree of accuracy over a wide range of thicknesses and electrical conductivities. Moreover, the proposed method is compatible with the in-line and real-time estimation of thickness and electrical conductivity in an industrial environment.

Boundary geometry reconstruction for orthotropic heat conduction problems based on HT-FEM

It is usually inconvenient to directly measure the inner boundary geometry shape of thermal pipeline and furnace wall in engineering. A non-iterative algorithm is proposed to reconstruct the geometry shape of these structures for orthotropic heat conduction problems in nondestructive evaluation. First, the temperature of measurement points in the real domain is determined by utilizing the hybrid Trefftz finite element method (HT-FEM). Then, a virtual inner boundary is introduced into forming a virtual domain. The deviation between the measured temperature and the estimated temperature is defined as an objective function. The temperature on the virtual boundary is obtained by calculating the minimum of the objective function. Finally, the virtual boundary temperature is substituted into the direct problem to acquire the temperature distribution in the global domain. And the inner boundary geometry shape is identified by searching the isothermal curve. Several numerical examples are provided to verify the stability and effectiveness of the proposed method. The merit of this algorithm is that the unknown geometry shape can be directly and accurately reconstructed without the complex iterative process.

A Perspective of The Needs and Opportunities for Coupling Materials Science and Nondestructive Evaluation for Metals-Based Additive Manufacturing

This paper presents a perspective of the needs and opportunities associated with the multidisciplinary problem of nondestructive evaluation (NDE) of additive manufacturing (AM). Recognizing the multidisciplinary nature of the problem, as well as the need to bridge knowledge between the different communities, the paper is structured to provide brief backgrounds and details relevant to both communities, as well as present an assessment of the state of the art. This paper, in some respects, is meant to be a primer of the different landscapes, as well as a catalyst for making future connections. At the end, it will be clear that there is much more work to be done, but that the work that is ongoing is exciting, and the potential to exploit NDE techniques for metals-based AM is very high.

Nested kernel degeneration-based boundary element method solver for rapid computation of eddy current signals

In this article, the nested kernel degeneration (NKD) based integral equation fast solver is proposed to compress the dense system matrix generated by boundary element method (BEM) for calculating eddy current signals in 3D nondestructive evaluation (NDE) problems. The near and diagonal block interactions are computed and stored by full matrices. However, for the far block interactions, not like in the single level kernel degeneration-based method that all the interaction matrices are compressed by the interpolations, the nested approximation framework makes the expression of the higher-level matrices by the ones at leaf levels and the transfer matrices between neighboring levels. Different integral kernels are degenerated and nested to ensure the performance of NKD based method. The robustness and efficiency of the proposed solver are validated and verified by making numerical predictions and comparing them with the ones achieved by analytical method, numerical methods and experiments. Our numerical experiments show that the NKD solver is more efficient than the butterfly solver (multilevel adaptive cross approximation algorithm (MLACA)) for electrically small eddy current NDE problem. With the NKD based method, O(N) computational complexity is achieved for multiscale low frequency eddy current simulations without sacrificing accuracy, where N is the number of unknowns. So far, to our best knowledge, the proposed method with linear complexity is the most efficient integral equation-based BEM forward solver to predict the eddy current signals from cracks and flaws.

Automated immersion ultrasonic testing technology for debonding defects of the brazed joint of DOME in EAST divertor

Aiming at the problem of non-destructive evaluation of debonding defects on joint interface of DOME in EAST divertor, an automatic water immersion ultrasonic C-scan testing technology based on a six-axis robot is proposed in this research. First, the research and development ideas, principles and control logic of the testing system are explained. Second, testing technologies such as probe selection, reference sensitivity and gate setting, and scanning path planning based on robotic arm teaching technology are introduced in detail. Finally, the testing results of the test blocks and products are presented, and the distribution state and formation reasons of the debonding defects on the bonding surface are analyzed. The results show that the automatic water immersion ultrasonic C-scan inspection system based on the six-axis robot has good adaptability to the surface and high testing sensitivity, which can meet the requirements for product quality and technical specifications. In summary, the proposed technology can realize the non-destructive quantitative assessment of the debonding defects of the brazed joint of DOME.

Hybrid Method of ACA and Interpolation-based Algorithms for Analysis of Eddy Current Nondestructive Evaluations

ABSTRACT In this article, the hybridization of adaptive cross approximation (ACA) algorithm and interpolation-based separation of the kernel function is proposed to accelerate solving the matrix equations resulted in the boundary element method (BEM) for 3D arbitrary-shaped eddy current nondestructive evaluation problems. The hybrid method combines the advantages of both the ACA algorithm and the interpolation-based methods, and resolves the shortcoming of pure ACA method, when modeling the planar eddy current nondestructive evaluation problems, that it cannot compress the null entries the BEM generated when the testing and basis patches are co-planar. In the proposed method, the submatrices associated with the null entries are compressed by the interpolation-based method, while the others are compressed by the ACA algorithm. Several benchmarks are shown to demonstrate both the robustness and efficiency of the proposed fast and general solver.

Integral equation fast solver with truncated and degenerated kernel for computing flaw signals in eddy current non-destructive testing

In this article, the kernel independent H-matrix method is applied as the mathematical framework. The dense matrix generated by the selected integral equation, without low frequency breakdown problem for solving 3D arbitrary shaped eddy current nondestructive evaluation (NDE) forward problems, is compressed by the truncated and degenerated (TD) kernel function method. It results in a significant reduction in computational burden with nearly linear complexity. The kernel functions (Green's function) are degenerated by Lagrange polynomials which leads to two advantages: firstly, the double integrals are separated in two single integrals, and secondly, they are represented in a factorized form with good accuracy control. Meanwhile, due to the nature of the kernel function with exponential decay in the lossy medium, it is truncated to improve the overall performance. The TD kernel function-based boundary element method (BEM) fits well for solving eddy current NDE problems over the adaptive cross approximation based BEM, especially for detections of flaws or slots in planar objects. Several numerical predictions calculated by the proposed method are compared with those achieved by others such as the experiment, analytical and semi-analytical methods from benchmarks. The robustness and efficiency are demonstrated with excellent agreements and reduced complexity.

FEM of Magnetic Flux Leakage Signal for Uncertainty Estimation in Crack Depth Classification using Bayesian Convolutional Neural Network and Deep Ensemble

This paper investigates the impact of uncertainties during dynamic magnetization due to relative motion between magnetic flux leakage (MFL) sensors and material under test. A 3D finite element method (FEM) based model for the MFL inspection system is developed to better understand the relationships between inline inspection (ILI) data and damage parameters in nonlinear ferromagnetic materials. In real-life field testing or inspection scenario, there exist lots of uncertainties associated with nondestructive evaluation (NDE), which will further affect damage condition-based decision making. Therefore, it is vital to quantitatively analyze the uncertainties in NDE. This paper investigates uncertainty quantification via numerical simulation by developing Bayesian based Convolutional Neural Network and Deep Ensemble methods, which are demonstrated in MFL based defect depth classification for NDE applications. Prediction accuracy and uncertainties are compared, which is valuable in better assessing the performance and quantifying uncertainties for generalized NDE problems.

RECONSTRUCTION OF DEFECT SIZE AND SHAPE IN EDDY-CURRENT TESTING USING BENCHMARK PROBLEMS VALIDATION AND NEURAL NETWORK APPROACH

The benchmark problems in eddy-current nondestructive evaluation (EC-NDE) are based on careful measures of the change in coil impedance as a function of circular air cored coil position which is scanned along the axis of machined slot by electrodischarge in aluminum plate. Tow benchmark problems (TEAM workshop n° 15-1, and JSAEM n° 2-5) are presented to validate and verify ANSYS Maxwell 3D-resolution of defect size and shape using electromagnetic formulation. In order to provide a challenge for current theoretical models, slots of rectangular, elliptical, slope and triangular profiles are considered. The final impedance data can be directly used to verify theoretical inversion algorithms.

Analysis of electromagnetic non-destructive evaluation modelling using Stratton-Chu formulation-based fast algorithm.

The eddy current non-destructive evaluation (NDE) modelling using Stratton-Chu formulation-based fast algorithm is analysed. Stratton-Chu formulations, which have no low frequency breakdown issue, are selected for modelling electromagnetic NDE problems with low frequency and high conductivity approximations. As the main contribution of this article, the robustness and efficiency of the approximations, which result in big savings in both memory and CPU time, are validated and analysed using examples from practical EC testing. The boundary element method (BEM) is used to discretize the integral equations into a linear system of equations: the first order Rao-Wilton-Glisson (RWG) vector basis functions with the flat triangle meshes of the object and pulse basis functions are selected to expand the equivalent surface currents and the normal component of magnetic fields, respectively. Then the multilevel adaptive cross approximation (MLACA) algorithm is applied to accelerate the iterative solution process. The performance and efficiency of adaptively applying a multi-stage (level) algorithm based on the criteria concluded for the operators are shown. This article is part of the theme issue 'Advanced electromagnetic non-destructive evaluation and smart monitoring'.

Enhanced Ultrasonic Imaging and Non-Destructive Evaluation Using Angle-of-Arrival Estimation in Dimension-Reduced Beam Space

Abstract Robust defect detection in the presence of grain noise originating from material microstructures is a challenging yet essential problem in ultrasonic non-destructive evaluation (NDE). In this paper, a novel method is proposed to suppress the gain noise and enhance the defect detection and imaging. The defect echo and grain noise are distinguished through analyzing the spatial location where the echo is originating from. This is achieved by estimation of the angle of arrival (AOA) of the returned echo and evaluation of the likelihood that the echo is reflected from the point where the array is focused or otherwise from the random reflectors like the grain boundaries. The method explicitly addresses the statistical models of the defect echoes and the spatial noise across the array aperture, as well as the correlation between the flaw signal and the interfering echoes; estimates the AOA and the likelihood in a dimension-reduced beam space via a linear transformation; and determines a weighting factor based on the mean likelihood. The factors are then normalized and utilized to correct and weigh the NDE images. Experiments on industrial samples of austenitic stainless steel and INCONEL Alloy 617 are conducted with a 5 MHz transducer array, and the results demonstrate that the grain noise is reduced by about 20 dB while the defect reflection is well retained, thus the great benefits of the method on enhanced defect detection and imaging in ultrasonic NDE are validated.

Deep learning based crack damage detection technique for thin plate structures using guided lamb wave signals

In this paper, convolutional neural network (CNN) is employed for crack damage detection in thin aluminum plates. Identifying a successful damage feature is a critical step in computationally efficient damage detection and characterization process; however, such feature identification process is generally time-consuming and often difficult to execute. The CNN model is a deep learning model that can be trained to represent high dimensional data for which traditional mathematical model is ill to describe. This study first formalizes the nondestructive evaluation (NDE) problem of notch-type crack damage detection in thin metal plates into an image classification problem in the machine learning domain, which is then solved with a deep CNN model trained using Lamb wave data converted images. Analytical formulas have been derived for generating Lamb wave signals subsequently used for training and validation test of the proposed crack damage detection technique for thin metal plates. Experimental test data from aluminum plate with simulated notch damage has also been used to independently validate the CNN model. The study results show its potential as a promising NDE tool for crack damage detection in thin plate structures.

Multilevel adaptive cross approximation for efficient modeling of 3D arbitrary shaped eddy current NDE problems

In this article, the multilevel adaptive cross approximation (MLACA) algorithm is presented to accelerate the boundary element method (BEM) for eddy current nondestructive evaluation (NDE) 3D problems involving arbitrary shapes. The Stratton-Chu formula, which does not have the low frequency breakdown issue, has been selected for modeling. The equivalent electric and magnetic surface currents are expanded with Rao-Wilton-Glisson (RWG) vector basis functions while the normal component of the magnetic field is expanded with pulse basis functions. The MLACA compresses the rank deficient matrices with the ACA and the butterfly algorithm. We improve the efficiency of MLACA by truncating the integral kernels after a certain distance and applying the multi-stage (level) algorithm adaptively based on the criteria for different operators to further decrease the memory and CPU time requirements while keeping almost the same accuracy comparing with the traditional MLACA. The proposed method is especially helpful to deal with the large solution domain issue of the BEM for eddy current problems. Numerical predictions are compared with the analytical, the semi-analytical predictions and the experimental results for 3D eddy current NDE problems of practical interest to demonstrate the robustness and efficiency of the proposed method.

Composite Material Characterization using Eddy Current by 3D FEM Associated with Iterative Technique

In this paper, an iterative technique, employing the T formulation associated with the finite element method, based on Maxwell's equations and the Biot-savart law, is used for analyzing the density of eddy currents in composite carbon fiber reinforced polymer (CFRP) materials. For this purpose, a code has been developed for solving an electromagnetic 3D non-destructive evaluation problem. This latter permits the characterization of this CFRP and determinate of fibers orientation using the impedance variation which is implanted in polar diagram. Firstly, the obtained results are compared with those of the analytical model. This comparison reveals a high concordance which proves the validity of the proposed method. Secondly, three different applications are shown for illustrating the characterization of unidirectional, bidirectional and multidirectional piece using a rectangular coil plotted in normalized impedance diagram.

Adaptive Cross Approximation Algorithm for Accelerating BEM in Eddy Current Nondestructive Evaluation

This paper presents the adaptive cross approximation (ACA) algorithm to accelerate boundary element method (BEM) for eddy current nondestructive evaluation (NDE) problem. The eddy current problem is formulated by boundary integral equation and discretized into matrix equations by BEM. Stratton–Chu formulation is selected and implemented for the conductive medium which does not has low frequency breakdown issue. The ACA algorithm has the advantage of purely algebraic and kernel independent. It starts with hierarchically partitioning the object to get diagonal blocks, near blocks and far blocks. The far-block interactions which are rank deficient can be compressed by ACA algorithm meanwhile the elements for diagonal-block interactions and near-block interactions are stored and computed by BEM. We apply modified ACA (MACA) for more memory saving while keeping almost same accuracy compared with original ACA. For numerical testing, several practical NDE examples such as coil above a half space conductor, tube in a fast reactor and Testing Electromagnetic Analysis Methods (TEAM) workshop benchmark problem are presented to show the robust and efficiency of our method. With the aid of ACA, for electrically small problems, the complexity of both the memory requirement and CPU time for BEM are reduced to $$ O\left( {N\log N} \right). $$

A computational investigation and smooth-shaped defect synthesis for eddy current testing problems using the subregion finite element method

ABSTRACTEddy Current Testing (ECT) plays a key role in detecting cracks and defects in conductors. The present study examines for the first time how the subregion method as an effective mathematical and computational technique can be admixed with Finite Element Method (FEM) to study multiple defects parameters for ECT issues. Separating a defect region from the entire domain in any computational technique will save both time and storage space. Examples of different types of defects are presented in this article . A tangible result of processing time reduction by 90% has been achieved which has led us to consider the subregion FEM method as an effective method in solving different Nondestructive Evaluation (NDE) problems. An agreement between our results and others using classical FEM has been achieved which could lead to using this technique in online and field testing problems. The presented subregion FEM algorithm was verified experimentally with good agreement by testing Aluminum (T6061-T6) samples with defects. A Tunneling Magnetoresistive (TMR) sensor was used to measure the component of the magnetic field from normal to the sample top surface. A major component of minimizing processing time was achieved, which could lead to using this technique in online and field testing problems.

Robustness of ultrasonic detection of flaws by using synthetic aperture focusing technique

One of the challenging problems in non-destructive evaluation is related to identification and sizing of flaws. A high resolution image of the scanned part is required. This allows, through using adequate post-processing of data, to perform localisation and sizing of a flaw. Several techniques have been introduced recently for this purpose. These include among others the synthetic aperture focusing technique, inverse wave-field extrapolation and the total focusing method. However, large uncertainties are affecting the inverse problem solution as provided by these methods when dealing with small defects. It was recognized that reconstruction based on the ultrasonic synthetic aperture focusing technique elaborated in frequency domain provides high resolution imaging even at large distances. This work focused on this promising procedure for the special case of ultrasonic imaging of flaws in 2D elastic medium under plane strain conditions, where the image is provided by a B-scan. Robustness of detection was investigated through perturbing the radargram by white noise and assessed as function of noise energy. It was found that synthetic aperture focusing technique is insensitive to noise.

Monotonicity based imaging method for time-domain eddy current problems**This paper is dedicated to Professor Guglielmo Rubinacci on the occasion of his 65th Birthday.

Eddy current imaging is an example of inverse problem in nondestructive evaluation for detecting anomalies in conducting materials. This paper introduces the concept of time constants and associated natural modes in eddy current imaging. The monotonicity of time constants is then described and applied to develop a non-iterative imaging method. The proposed imaging method has a low computational cost which makes it suitable for real-time operations. Full 3D numerical examples prove the effectiveness of the method in realistic scenarios.