Journal of Nondestructive Evaluation最新文献

Pavement performance evaluation based on modulus is crucial for controlling the overall performance of pavements and decisions making throughout the pavement’s life cycle. Falling weight deflectometer (FWD) tests are commonly employed to collect deflection data, which is subsequently back-calculated to get each layer’s modulus. However, existing studies lack a complete framework for incorporating the bedrock condition in the back-calculation process. Here, an integrated process of pavement performance evaluation utilizing FWD tests is proposed, and the focus is on the classification of bedrock condition by modern classification algorithms (BPNN, MLP, SVM, and RF) to determine the presence or absence of bedrock and its depth range. The implementation of classification process allows for the inclusion of bedrock influence in the back-calculation process, thereby improving the accuracy of modulus results. Results from the four classification algorithms reveals that RF is the most suitable for classifying bedrock depth, exhibiting superior overall performance. The proposed integrated back-calculation process enables a comprehensive and objective evaluation of pavement structural performance, providing a valuable framework for informed decisions making.

This study assessed the viability of using hyperspectral imaging (HSI) technology for nondestructive detection of moisture content in oilseed rape leaves. Besides, a method (IVISSA-iPLS) coupling interval variable iterative space shrinkage approach (IVISSA) with interval partial least square (iPLS) was introduced to identify characteristic wavelengths. The IVISSA-iPLS algorithm changed the selection target from wavelength points to spectral intervals, reducing the computational burden while increasing the continuity between the selected wavelengths. Subsequently, the characteristic wavelengths selected by the IVISSA-iPLS were used as the input of the least square support vector regression (LSSVR) model to predict the moisture content of oilseed rape leaves. Additionally, the competitive adaptive reweighted sampling (CARS), the successive projections algorithm (SPA), the IVISSA, and the iPLS were investigated as wavelength selection algorithms for comparison. The results indicated that the LSSVR models based on the characteristic wavelengths acquired from the IVISSA-iPLS using divided wavelength intervals of 30, demonstrated the highest performance, with ({{text{R}}}_{{text{p}}}^{2}) of 0.9555, RMSEP of 0.0065, and ({text{RPD}}) of 4.715. Finally, the optimal prediction model was used to visualize the moisture content of oilseed rape leaves, which offered a more intuitive and effective method for the evaluation of moisture content. The results ascertained the significant possibility of combining HSI with combinatorial algorithms in detecting, quantifying, and visualizing the moisture content of oilseed rape leaves.

EIT was found recently that it can also be applied to dielectrics under a high-frequency AC voltage. However, the EIT evaluation method for dielectrics has not been established sufficiently; in particular, there are no example studies of the drawing of impedance plane diagrams, which is widely used as an evaluation method for eddy current testing (ECT). Therefore, we have attempted to draw an impedance plane diagram based on the Ampère-Maxwell equation and a simple electrical circuit, as performed in ECT. First, a theoretical solution for the impedance based on the Ampère-Maxwell equation that considers eddy and displacement currents was derived, and impedance plane diagrams were then drawn. From the impedance plane diagrams obtained, it was shown that the same trends can be drawn for the diagrams for both conductors and dielectrics. Next, an electrical circuit model for EIT was proposed that takes into account both the conductivity and the permittivity. Using this model, impedance plane diagrams for conductors and dielectrics were drawn, and for dielectrics in particular, it was shown that the diagrams can be drawn by considering the conductivity. In addition, similar to the impedance plane diagrams drawn from the electrical circuit model and derived from the Ampère-Maxwell equation, the change behavior in the diagrams clearly differs between the cases where the conductivity and permittivity change and the case where the lift-off changes. This demonstrates the effectiveness of the electrical circuit model in providing a qualitative understanding of the effects of the dielectric conditions and measurement conditions on EIT.

Nondestructive testing (NDT) plays a vital role in the production and quality control of the casting process. Due to the complexity of inspection procedures and the extensive scale of mass production, it becomes imperative to develop fast and precise automatic detection methods. This paper introduces a deep learning-based approach for detecting defects in X-ray images of aluminum castings. Firstly, we introduce the Gain-Adaptive Multi-Scale Retinex (GAMSR) algorithm, which is designed to enhance the low-contrast and noisy X-ray raw data. To address the problem of minor blowhole defects being overlooked during detections, we combine the Feature Pyramid Network (FPN) with the Convolutional Block Attention Module (CBAM) to extract high-level semantic information from the X-ray images. It can also promote the feature extraction network to focus more on the casting defect features. Furthermore, we employ Weighted Region of Interest pooling (W-RoI pooling) in place of RoIAlign. This strategy eliminates area misalignment and significantly enhances the precision of defect identification. Experiment results demonstrate that the proposed approaches can improve the performance of defect detection for aluminum casting DR images, with the accuracy increasing by 20.08%.

A novel active thermal nondestructive testing (TNDT) technique using sequential heating and cooling is proposed. Properly chosen parameters of a heating/cooling technique may result in a sample excess temperature that is close to the sample’s initial temperature, which causes zero excess temperature when hidden defects still produce noticeable temperature signals. In this case, the running temperature contrast may increase, which improves detection reliability. This is due to the fact that the effect of emissivity variations on the surface of a test sample are minimized if the sample temperature is close to the ambient temperature.

The proposed technique was numerically modeled, and experiments were performed using a line-scanning TNDT procedure.

Locating and sizing delaminations is a common inspection task in the maintenance and quality control of construction and rehabilitation. Their detection is an important area of application of nondestructive testing in civil engineering (NDT-CE). To improve this application, NDT test systems and test solutions must be compared, for which specimens containing well-defined delaminations are needed to serve as a reference. Currently, there are no widely accepted procedures available for creating such flaws locally and reproducibly. This study presents procedures for creating artificial delaminations repeatably and as close as possible to natural delaminations. To produce the discontinuities only substances were used which can occur in concrete components and do not affect the application of NDT-CE methods. Ultrasonic pulse-echo (UPE) was used to test the flaws in the specimens. The delaminations were created by applying expansive mortar in prepared through holes. Three specimens with two delaminations each were built and tested using UPE.

Abstract

Cable tension is an important parameter for monitoring the health of cable-supported bridges. Live loads cause periodic changes in cable tension. Given the lack of test methods for cyclic cable tension, the resonance-enhanced magnetoelastic (REME) effect was adopted for cable tension monitoring. Combining the magnetoelastic effect and the electromagnetic induction theory, the relationship between cable tension and the REME sensor’s induced voltage was deduced. This relationship indicated the feasibility of using the REME effect to monitor cable tension. According to the variation law of cable tension, a cyclic cable tension monitoring experiment was carried out. Based on the experimental results, a cyclic cable tension monitoring method via the REME effect was proposed. When the tension variation amplitude was less than 100% of the design tension, the monitoring error was less than 5%. The proposed method could be used to accurately monitor the large-amplitude cyclic cable tension.

The FMC-TFM is currently a popular method for ultrasonic phased array imaging. In the FMC-TFM, ultrasonic echo energy is mainly used for imaging, but the directional nature of ultrasound phased array elements leads to differences in the energy of ultrasonic waves in different propagation directions, resulting in uneven imaging amplitudes of defects in different directions. When the beam pointing angle gradually approaches -90° and 90°, the beam directivity will slowly degenerate and the acoustic energy will progressively weaken, forming an angle blind spot for imaging. When the detection space is limited and the ultrasonic phased array transducer cannot be moved, defects within the angle blind spot will not be detected. Therefore, the paper analyzes the causes of and factors that influence the formation of ultrasonic phased array imaging angle blind spots, describes the distribution characteristics of the acoustic field radiation angle of the array element by using the solid directivity compensation factor, and constructs an ultrasonic phased array TFM algorithm based on the solid directivity compensation factor. The numerical simulation and experimental results show that when the array element width is 0.5 ((a = 0.5lambda), which is commonly used in industrial detection for phased array transducers), the solid directivity compensation TFM algorithm has a better ability to compensate for the imaging amplitudes of defects in blind spots than the conventional directivity compensation TFM algorithm. When the angle blind spot is small (i.e., (theta_{0} = 72.3^circ)), the clarity of the defect imaging of the solid directivity compensation TFM algorithm is better than that of both the TFM algorithm and the conventional directivity compensation TFM algorithm. When the angle blind spot is large (i.e., (theta_{0} = 76.5^circ)), defect imaging in the angle blind spot cannot be achieved by using the TFM algorithm and the conventional directivity compensation TFM algorithm, but the solid directivity compensation TFM algorithm can achieve accurate imaging, effectively suppressing the influence of angle blind spots and expanding the detection range of ultrasonic phased arrays.

The quality assessment of concrete material for new or existing buildings is critical to civil and structural engineers. In this scope, the development of nondestructive testing methods (NDT) has received significant attention and becomes essential for enhancing the on-site assessment of concrete performance. The Schmidt hammer (SH) test is one of the most widely used NDT for quantifying concrete strength. However, the reliability of this test and its accuracy are questioned by many researchers. In this study, the measurement quality of SH has been improved by attaching a developed cantilever-based jerk sensor to the SH mass. The theoretical model of the proposed measurement technique has been formulated and discussed. The experimental approach, jerk sensor design, SH body modification, electronic reading unit, testing, and construction of the calibration curves have been presented. Experimental results revealed that the accuracy of the developed SH has increased by 13% for concrete strength measurement, and the correlation coefficient of the strength calibration curve is 0.94. At the same time, the calibration curve of the concrete elasticity modulus showed a 0.93 correlation coefficient with 92% measurement accuracy. Analytical and experimental results have confirmed the applicability of the modified Schmidt hammer since it is reliable and more accurate compared to the traditional Schmidt Hammer.