Ndt & E International最新文献

Steel pipe structures are commonly used in the industrial field. Stress-induced structural failures can have a significant impact on equipment safety. Therefore, effective stress monitoring is a crucial area of research. Constrained by the multi-frequency and multi-modal characteristics of ultrasonic guided waves, the limitations of traditional stress measurement methods based on these waves lie in the lack of a systematic analysis of the impact of multi-modal fused signals on stress measurement. To explore the optimal guided wave stress measurement strategy, a mathematical model for the propagation of longitudinal guided waves in prestressed steel pipes, based on the principles of acoustoelasticity, is proposed. Using this model, the sensitivity of stress to each sub-mode of the longitudinal guided waves is analyzed, leading to the identification of the optimal guided wave mode (L(0,2) mode) and frequency range. In order to avoid the excitation of other low-sensitivity modes, further analysis of the optimal parameters for the piezoelectric array is conducted. Simulation results indicate that the designed transducer can effectively excite the target mode with high purity. The stress sensitivity of the target mode was experimentally determined to be $-2.5\times 10^{-5}{\text{MPa}}^{-1}$, which closely aligns with the theoretical results. Comparative analysis of the experiments emphasizes the influence of modal control on measurement outcomes. By selecting and controlling the appropriate mode, the maximum relative error in stress measurement is observed to be 5%.

To address the issue of geometric artifacts in equiangular fan-beam industrial computed tomography (CT) systems, this paper proposes a projection sinogram-based method for correcting these artifacts. Firstly, we discuss the formation mechanism of geometric artifacts in equiangular fan-beam industrial CT system when there is geometric deviation. Secondly, we establish a geometric model that incorporates these deviations and mathematically describe the projected position curve of a point within the plane. Subsequently, we use a needle gauge as a surrogate for the point, and fit the curve in the projection sinusoidal graph obtained from scanning the needle gauge to calibrate the geometric deviations. Finally, we introduce the calibrated geometric deviations into the filtered back projection (FBP) algorithm to achieve more accurate reconstructed images. The proposed method precisely calibrates geometrical deviations in the equiangular fan-beam industrial computed tomography (CT) system and effectively eliminates geometric artifacts in the reconstructed CT images, this is demonstrated by simulation and practical experiment. This method has also been successfully applied in engineering practice.

Thermal barrier coatings (TBC) are frequently employed in aircraft engines and turbine blades for protection against high temperatures. Constant exposure to in-service stresses, however, leads to a variety of anomalies in TBC that could prove to be potentially catastrophic for the assemblies they protect. This raises the need for inspection using non-destructive techniques (NDT) to ensure the reliability and structural integrity of the coated assemblies. Thickness evaluation of the topcoat of the TBC is paramount to determining structural integrity of the TBC. Microwaves are particularly suited for such applications since they readily penetrate low loss TBC. However, the performance of previous microwave-based TBC thickness evaluation techniques was limited in accuracy to 15 μm. In this paper, accurate thickness evaluation of thermal barrier coating (TBC) is performed using a microwave resonator sensor operating at a relatively low frequency (<1 GHz). TBC thicknesses as low as 100 μm are evaluated based on shift in resonant frequency of the probe. Overall, practically relevant thicknesses ranging from 100 μm to 600 μm are evaluated herein and multiple trials are performed to ascertain repeatability and assess uncertainty in measurements. For a 250 μm thick TBC sheet, a mean error of 0.9 μm was accomplished which translates to 0.36 % error with a standard deviation of 1.5 μm. Compared to other microwave sensors reported in the literature, a better estimation accuracy is demonstrated in this work, in particular for thicknesses less than <250 μm.

Pulse compression based excitation signals have been shown to improve signal quality in many active ranging applications without negatively impacting range resolution. Most prior work into using pulse compression presents the technique as if matched filtering is necessary to successfully achieve signal compression. Matched filtering against modulated excitation signals does result in useful information compression, however, it also suppresses information outside of the bandwidth of the transmission signal. This can distort or remove useful information in some applications, such as ultrasonic guided wave inspections, making the processing step unsuitable. In this paper, we show that when pulse compression with coded excitation is employed, a second filtering option is available for compressing the modulated information. The second option, which we have termed the sequence filter, utilises sequence elements as the template against which the filtering of coded excitation measurements is undertaken, thereby allowing compression to be achieved independent of received signal frequency content. We verify that sequence filtering successfully produces signal compression in two experimental ultrasound non-destructive testing applications where frequency modulated pulse compression was unsuitable. With both sequence filtering and matched filtering, we show signal-to-noise ratio gains in excess of 20 dB from using pulse compression.

The erosion behavior of trunk borers leads to the destruction of trunk structure and the formation of internal defects, which significantly impacts the ecological and economic value of trees. Traditional non-destructive testing (NDT) methods are costly and have low resolution, whereas electromagnetic NDT methods are more suitable for high-resolution detection and imaging. However, solving the highly nonlinear electromagnetic inverse scattering problems (ISPs) for small-sized defects with high contrast is challenging. Therefore, this paper proposes an improved subspace optimization algorithm based on a ResNet network called SOM-ResNet. SOM-ResNet incorporates physical principles into deep learning networks by simulating the iterative process of induced current and contrast, thereby enhancing its ability to accurately detect small objects with high contrast. Experimental results demonstrate that SOM-ResNet outperforms single inversion algorithms in detecting complex scatterers with small to medium-sized targets, validating its excellent performance.

Alternating Current Field Measurement (ACFM) technique has been widely used in various fields such as oil & gas, aerospace areas. However, during the detection process, the probability of detection (POD) is influenced by multi-factors such as lift-off height, scanning angle and detection speed. In this paper, a bicharacteristic probability of detection (BPOD) model is developed for quantifying the crack detection reliability using integrated Bx and Bz signals in the ACFM technique. A multidimensional BPOD model is established to study the influence of multiple factors on the detection probability of cracks using ACFM technique. A Bayesian network-based method is proposed to reverse the hierarchical impact weights of influence factors on the BPOD of the ACFM technique. The results show that the BPOD model considering both Bx and Bz response signals can evaluate smaller defects than the conventional POD model. The multiple influencing factors can substantially decrease the BPOD of cracks. The hierarchical impact weights on BPOD for cracks are ranked as follows: lift-off height, detection speed, personnel involved in the detection process and scanning angle. This approach can retrospectively find the potential contributors to the missed detections based on the BPOD.

This work addresses the crucial challenges of simulating ultrasonic inspections in welded parts. We focus on the simulation of radiated ultrasonic fields in welded materials, incorporating spatially varying anisotropy and damping properties. Using macroscale descriptions to capture variations in weld properties as a function of grain orientation, two simulation methods are evaluated: a ray method and a hybrid finite element solution within the CIVA software. Simple simulations validate both models, but complexities emerge in real-world scenarios, notably caustic phenomena and beam splitting due to specific grain orientations. The proposed hybrid FE model can therefore provide reliable reference solutions, even for 3D configurations, allowing the biases arising from radius approximations to be quantified.

Achieving high horizontal resolution is crucial for general non-destructive testing (NDT) applications, and in the domain of ground penetrating radar (GPR), it can be more challenging due to inefficient transmissions of electromagnetic waves into and through complex material under test (MUT). In this study, we showcase the validation results of our recently designed ultra-wideband metasurface (UWM) in improving the horizontal resolution for GPR B-Scan images. This UWM has an ultra-wide working frequency band (100%) from 1 to 3 GHz, in which high-frequency GPR signals can be enhanced and transmitted into MUT. Our fourteen-day consecutive GPR experiments demonstrate that two buried pipes with an edge-to-edge spacing of 8 cm that are hard to distinguish by traditional GPR surveys can be visually identified by depositing the UWM atop the MUT. The underlying mechanism is the sustained and improved transmission of high-frequency signals into the MUT, enabled by the removal of transmission coupling loss by the UWM at the air–MUT interface and the resulting enhanced transmission of more high-frequency components. Our simulations also provide quantitative analysis of such enhanced behavior with a nominal transmittance increase of 30% $\sim$50%. We believe the horizontal resolution improvement enabled by UWM will open a new corridor for high-resolution GPR system design.

Ultrasonic technology is widely used in the field of rail defects detection. 3D reconstruction of rail defects can intuitively restore the 3D size and spatial position of the defects inside the rail. Currently, ultrasound-based 3D reconstruction requires a multi-probe or mechanical scanning platform in a laboratory setting, which is not suitable for the railway environment. In addition, 3D reconstruction requires a large amount of data, making it difficult to collect sufficient ultrasonic 3D defect data for long-distance rail inspections. This paper proposes an ultrasonic field-guided 3D reconstruction method combined with machine learning hybrid physics for rail defects. It combines both sound field GAN model to reconstruct the defect 3D model from the 2D B-scan data. The proposed method can generate a defect cross-sectional image using a deep learning algorithm guided by the acoustic field in the B-scan space, and extract the 3D size information of the defect from the 2D B-scan information by establish a defect echo model. By stablishing a spatial mapping relationship between the B-scan and the rail coordinate system, the position of the defect in the rail coordinate system is obtained. The defect data of standard damage rails are tested. Experiment results indicate that the defects in different parts of the rail can be reconstructed by the proposed method. The average size error rate is 9.56%–21.14 %, and the average height error is 3.458mm–6.353 mm.

In this paper, we extend a piezoelectric and laser ultrasonic system (PLUS) to a high-frequency version for high-sensitivity three-dimensional (3D) ultrasonic imaging by utilizing a unique characteristic of PLUS. PLUS combines a piezoelectric transmitter and a two-dimensional (2D) scan of a laser Doppler vibrometer (LDV). A high frequency can be used simply by adopting a high-frequency piezoelectric transmitter with a center frequency, such as 15 MHz, since the LDV has a broad bandwidth reception of 0–25 MHz. Furthermore, a 2D array receiver with a small interelement pitch can be achieved by precisely scanning a small laser irradiation spot. We experimentally demonstrate its 3D imaging capability for flat-bottom-hole and fatigue-crack specimens.