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This paper presents a new method for nondestructive testing—a pulsed multifrequency excitation and spectrogram eddy current testing (PMFES-ECT), which is an extension of the multifrequency excitation and spectrogram eddy current testing. The new method uses excitation in the form of pulses repeated at a specified time, containing several periods of a waveform consisting of the sum of sinusoids with a selected frequency, amplitude and phase. This solution allows the maintenance of the advantages of multifrequency excitation and, at the same time, generates high energy pulses similar to those used in pulse eddy current testing (PECT). The effectiveness of the new method was confirmed by numerical simulations and the measurement of thin Inconel plates, consisting of notches manufactured by the electric-discharge method.

Wire rope inspection by nondestructive testing methods, sensors and signal processing techniques are mainly reviewed in this paper. Owing to the difference of physical mechanism and testing principles, magnetic flux leakage, eddy current, acoustic emission and ultrasonic guide wave testing as well as other inspection methods for steel wire rope are summarized. Then, the commonly and frequently used testing sensors of inductive coil, hall element, magnetoresistive sensors and others are compared in the perspective of their corresponding operating principles, development situation, advantages and disadvantages. Furthermore, signal processing techniques including the signal filtering techniques such as the time and frequency analysis methods, quantitative data processing methods such as the machine learning and defect classification are studied. Finally, the challenges and future developing trends of wire rope inspection in practical applications are discussed.

This paper presents the results of experiments using the eddy current system designated for nondestructive inspection of carbon fiber-reinforced composites. For this purpose, the eddy current testing system with a differential transducer with two pairs of excitation coils oriented perpendicularly and a central pick-up coil was utilized. The transducer measures the magnetic flux difference flowing through the pick-up coil. The transducer of this design has already been successfully utilized to inspect isotropic metal structures. However, the anisotropy of the composites and their lower conductivity compared to metal components made the transducer parameters adjustment essential. Thus, various excitation frequencies were considered and investigated. The system was evaluated using a sample made of orthogonally woven carbon fiber-reinforced composites with two artificial flaws (the notches with a maximum relative depth of 30% and 70%, respectively, thickness of 0.4 mm, and a length of 5 mm). The main goal was to find a configuration suitable for detecting hidden flaws in such materials.

The article discusses the utilization of Pulsed Multifrequency Excitation and Spectrogram Eddy Current Testing (PMFES-ECT) in conjunction with the supervised learning method for the purpose of estimating defect parameters in conductive materials. To obtain estimates for these parameters, a three-dimensional finite element method model was developed for the sensor and specimen containing defects. The outcomes obtained from the simulation were employed as training data for the k-Nearest Neighbors (k-NN) algorithm. Subsequently, the k-NN algorithm was employed to determine the defect parameters by leveraging the available measurement outcomes. The evaluation of classification accuracy for different combinations of predictors derived from measured data is also presented in this study.

The most crucial components in the system of eddy currents are the sensitivity of the probe to deliver a signal to detect a defect on the material efficiently. When the turns are closely spaced and the length is substantially more than the radius of the turns, the solenoid is perfect. This paper presents a development of a solenoid probe for the eddy current testing (ECT) technique probe to detect defects. The objectives of this research are to design and construct a high sensitivity rod-shaped solenoid probe, to find the optimal frequency for each metal testing (i.e., Copper (Cu), Aluminium (Al), and Stainless Steel) for this solenoid probe, and to obtain the output testing signals defects with vary of thickness (i.e., 1.5 mm, 3.0mm, and 5.0 mm). In addition, a hole of an artificial defect (i.e., 7.0 mm, 14.0 mm, 21.0 mm) has been drilled on each of the metal testings. This rod-shaped solenoid coil was designed with an iron core with 65 mm length, 5 mm area, and 200 turns. It demonstrates how the rod-shaped solenoid coil may be used to detect various flaws in copper (Cu), aluminium (Al), and stainless steel. The optimal frequencies for copper were 7.850 MHz, Aluminium was 7.383 MHz, and Stainless-Steel metal was 7.956 MHz.

Applying life estimation approaches to determine in-service life of structures and plan the inspection schedules accordingly are becoming acceptable safety design procedures in aerospace. However, these design systems shall be fed with reliable parameters related to material properties, loading conditions and defect characteristics. In this context, the role of non-destructive (NDT) testing reliability is of high importance in detecting and sizing defects. Eddy current test (ECT) is an electromagnetic NDT method frequently used to inspect tiny surface fatigue cracks in sensitive industries. Owing to the new advances in robotic technologies, there is a trend to integrate the ECT into automated systems to perform NDT inspections more efficiently. In fact, ECT can be effectively automated as to increase the coverage, repeatability and scanning speed. The reliability of ECT scanning, however, should be thoroughly investigated and compared to conventional modes of applications to obtain a better understanding of the advantages and shortcomings related to this technique. In this contribution, a series of manual and automated ECT tests are carried out on a set of samples using a split-D reflection differential surface probe. The study investigates the level of noise recorded in each technique and discuss its dependency on different parameters, such as surface roughness and frequency. Afterwards, a description of the effect of crack orientation on ECT signal amplitude is provided through experimental tests and finite element simulations. Finally, the reliability of each ECT technique is investigated by means of probability of detection (POD) curves. POD parameters are then extracted and compared to examine the effect of scanning index, frequency and automation on detection reliability.

Corrosion under insulation (CUI) is a major threat to the structural integrity of insulated pipes and vessels. Pulsed eddy-current testing (PECT) is well known in the industry for detecting CUI, but its readings can be easily influenced by nearby conductive objects, including the insulation supporting metal mesh. As a sequel to our previous study, this paper focuses on the surface distribution of eddy currents at the time of the turning off of the driving voltage instead of examining the overall process of eddy current diffusion. Based on the fact that CUI takes place on the outside of the insulated specimen, the probe footprint was calculated only on the specimen surface. The corrosion depth was regarded as an increment to the probe lift-off, whose information was carried in the early PECT signal. Finite element simulations were performed to facilitate the calculation of the probe footprint and predict the signal behavior. The peak value, which appeared in the early phase of the differential PECT signal, was found to be well correlated with the corrosion depth. Further studies revealed that the mild steel mesh could result in the enlargement of the probe footprint and a decrease in the change rate of the peak value in relation to the corrosion depth. Finally, experiments were conducted to verify the simulation results. The presented findings are consistent with the previously reported results and provide a potential alternative to evaluate CUI in specific scenarios where the insulation has a fixed and uniform thickness.

Hot rolling work rolls are essential components in the hot rolling process. However, they are subjected to high temperatures, alternating stress, and wear under prolonged and complex working conditions. Due to these factors, the surface of the work rolls gradually degrades, which significantly impacts the quality of the final product. This paper presents an improved degradation model based on the Wiener process for predicting the remaining useful life (RUL) of hot rolling work rolls, addressing the critical need for accurate and reliable RUL estimation to optimize maintenance strategies and ensure operational efficiency in industrial settings. The proposed model integrates pulsed eddy current testing with VMD-Hilbert feature extraction and incorporates a Gaussian kernel into the standard Wiener process to effectively capture complex degradation paths. A Bayesian framework is employed for parameter estimation, enhancing the model’s adaptability in real-time prediction scenarios. The experimental results validate the superiority of the proposed method, demonstrating reductions in RMSE by approximately 85.47% and 41.20% compared to the exponential Wiener process and the RVM model based on a Gaussian kernel, respectively, along with improvements in the coefficient of determination (CD) by 121% and 19.76%. Additionally, the model achieves reductions in MAE by 85.66% and 42.61%, confirming its enhanced predictive accuracy and robustness. Compared to other algorithms from the related literature, the proposed model consistently delivers higher prediction accuracy, with most RUL predictions falling within the 20% confidence interval. These findings highlight the model’s potential as a reliable tool for real-time RUL prediction in industrial applications.

In the detection of corrosion under insulation (CUI) using pulsed eddy current testing (PECT) method, it is of great significance to reduce the footprint of the probe for improving the spatial resolution to local corrosion. This paper presents a novel method to reduce the probe footprint by modifying the excitation coil into multiple sub-coils and driving them with sequential pulses of different delay time. Finite element simulations are conducted to reveal the underlying mechanism. It is found that by using the sequential excitation scheme, the diffusion and decay of eddy currents in the test piece are regulated, and both the footprint reduction and signal enhancement can be achieved. Afterwards, the effects of the sequence and the delay amount of the applying pulses on the probe footprint are analyzed. Results show that the optimal excitation sequence is to apply pulses with increasing delay time to the sub-coils from outside to inside; the probe footprint decreases with the increase of the delay amount. Experimental work is finally performed to verify the simulation results. A graphical method for measuring the probe footprint is proposed by moving the probe on a step wedge plate and plotting the evaluated thickness against the probe position. Footprint measurement results of a conventional probe and the presented 4-subcoil probe are compared. The effectiveness of the proposed method are validated and the differences between experimental and simulation results are analyzed.

The purpose of this paper is to conduct a thorough investigation of a stochastic eddy-current testing problem, when the geometric parameters of the system under study are characterized by uncertainty. Focusing on the case of subsurface defect detection, we devise reliable surrogates for the quantities of interest (QoI) based on the principles of the generalized polynomial chaos (PC) and using the orthogonal matching pursuit (OMP) solver to promote sparsity in the approximate models. In addition, a variance-based approach is implemented for the sequential construction of the necessary sample set, enabling more accurate estimation of the statistical metrics without imposing additional computational overhead. Apart from quantifying the inherent uncertainty, a sensitivity analysis is performed that assesses the impact of each geometric variable on the QoI, via the computation of Sobol indices. The efficiency of the OMP-PC algorithm is demonstrated in two variants of the subsurface-discontinuity problem, yielding at the same time useful conclusions regarding the properties of the stochastic outputs.