Ndt & E International最新文献

Electrical resistance is closely related to the damage of ceramic matrix composites (CMC) such as matrix crack, crack opening distance (COD), and interphase retention rate, giving it the potential to become a new non-destructive testing (NDT) technique. An electro-mechanical experiment method was designed for the tensile test of ceramic matrix mini-composites (CMMC). An optical in-situ tensile test was performed to obtain the pattern of matrix crack propagation. The result confirms that matrix crack saturation may not occur before the material fractures. An electromechanical model considering the COD was established to identify the damage situations. A new method for preparing ceramic matrix micro-composites composed of a single fiber and a single-layer pyrolytic carbon (PyC) interphase was realized. The accurate in-situ resistivity of the PyC was measured based on the micro-composites.

The application of the UHF RFID technique in non-destructive testing (NDT) and structural health monitoring (SHM) has gained increasing attention due to its wireless, battery-less, and cost-effective attributes. It offers a promising approach for SHM and the Internet of Things (IoTs). This paper reports commercial off-the-shelf (COTS) flexible UHF RFID tag-based sensors for corrosion characterization on coated mild steel. Two types of COTS flexible UHF RFID tags with different bends are fabricated as sensors. The received signal strength indicator (RSSI) measurement is implemented to characterize the corrosion. Three parts (T-match area, dipole arms, and dipole loadings) of the two tags are tested for sensing purposes, and comparison and discussion of sensitivity, read range, and results are provided. This study successfully validates the feasibility of the proposed tag-bent method for corrosion characterization undercoating. It can be concluded that the dipole arm part of the applied COTS tags is the most sensitive area.

Switch rails are weak but essential components in a high-speed rail track system, which have an urgent non-destructive testing requirement due to aging and associated fatigue damage accumulation. They are settled under sophisticated operation environments, which causes them to have unpredictable damages, such as abrasion, exfoliation, and cracks. Our goal is to propose a reliable system to detect structural damages of switch rails. Using ultrasonic guided waves to examine the health status of switch rails makes it possible to continuously evaluate the health status of switch rails when they are in use. Conventional damage detection methods with ultrasonic guided waves such as baseline signal subtraction, independent component analysis-based methods cannot always make reliable detection results. These methods are either lack of powerful abilities to capture the characteristics of damaged signals or time-consuming to be operated in real damage detection tasks. In this paper, a convolutional neural network-based system is proposed to solve both of the above challenges simultaneously. The proposed model employs multiple convolutional layers to extract deep features of ultrasonic guided wave signals. These features are then fed into a classifier to predict whether they are damaged signals or not. To evaluate the proposed model performance, we collected ultrasonic guided wave signals from two different switch rails. The proposed model achieved more than 91% testing accuracy and outperformed other relevant methods. It also demonstrated the proposed model had strong generalization abilities to make it capable in practical switch rail structural damage detection tasks.

Electrical impedance tomography (EIT) is a method of spatially mapping the conductivity distribution of a domain and has been studied as a potential embedded sensing or nondestructive evaluation (NDE) tool. An often touted advantage of EIT is that it can be used in-situ; that is, because the method only requires the application of unobtrusive electrodes, it can conceivably be used while the component or structure is in operation. This material-as-the-sensor philosophy strongly aligns with key components of the NDE 4.0 vision such as the realization of intelligent cyber–physical systems (CPS) and digital twins. To date, however, the claim of in-situ sensing via EIT has not been significantly substantiated. This is problematic because operational loads induce strains that often change the conductivity of the material. Establishing that EIT can detect damage-induced conductivity changes through the presence of unrelated strain-induced conductivity changes is therefore important. To that end, we herein study the application of EIT for detecting indentation damage in a carbon fiber/epoxy composite as the composite is loaded in a four-point bend. It was found that the bending load changes the contact impedance of the electrodes, which resulted in poor EIT images when solving the EIT inverse problem with the ${\ell }_2$-norm on the error term. Using the ${\ell }_1$-norm on the error term, solved via the primal–dual interior point method (PDIPM), significantly improved image quality. Image quality was even further improved through the use of a mixed prior for regularization, and EIT images were compared to thermography with good agreement. These results show that EIT can indeed detect damage through the presence of an applied load, but care must be taken to account for factors such as outlier data arising from electrode degradation and changing contact impedance. Use of the ${\ell }_1$-norm on the error term is therefore highly recommended for in-situ imaging via EIT.

In the context of nondestructive testing and evaluation, dispersion entropy (DisE) stands out as a promising dynamic nonlinear health monitoring measure for rotating machineries. However, in high-noise scenarios, transient impulses linked to rotating machinery faults often get submerged under the noise component present in the collected vibration signal. As a result, DisE not only fails to detect the presence of a fault at the earliest stage of inception but also performs poorly in tracking the progression of the incepted fault. Aiming at overcoming the limitations of DisE in dynamic health monitoring of rotating machineries, in this paper, impulses corresponding to a fault is extracted by suppressing the unnecessary noise component by weighting the squared envelope of the collected vibration signal. Due to the application of weighted squared envelope in calculating the DisE, the proposed measure is termed as weighted squared envelope dispersion entropy (WSEDisE). Effectiveness of WSEDisE in dynamic health monitoring of rotating machineries is verified by two different experimental run to failure data collected from rolling element bearings and spur gears. Experimental results show that WSEDisE not only overcomes the weaknesses of original DisE but also demonstrates better performance than conventional entropy-based methods such as permutation entropy (PE) and advanced DisE based method namely multiscale DisE (MDisE).

The often-assumed measurement reciprocity between scanning laser detection and scanning laser excitation is disproved by a simple experiment. Nevertheless, a deeper study based on the reciprocity relation reveals correct reciprocal measurement set-ups for both the probe-excitation/laser-detection and the laser-excitation/probe-detection case. Similarly, the all-laser measurement, that is thermoelastic laser excitation with laser vibrometer detection, is not in general reciprocal with respect to the exchange of excitation and detection positions. Again, a substitute for the laser doppler vibrometer out-of-plane displacement measurement was found which ensures measurement reciprocity together with laser excitation. The apparent confusion in literature about strict validity/non-validity of measurement reciprocity is mitigated by classifying the measurement situations systematically.

In this study, we present an extension of the virtual wave concept to enable photothermal reconstruction from temporal non-uniform pulsed thermography data. Therefore, we introduce a generalized discrete transformation kernel, which allows to account for arbitrary temporal sampling strategies. First, we show the evidence of the proposed strategy for analytical temperature signals. Moreover, we demonstrate the advantages of the strategy for simulated temperature signals, obtained from an orthotropic sample with defect interfaces at various depth positions. For experimental verification, we apply pulsed thermography in the pulse-echo configuration for a carbon fiber-reinforced polymer sample with different embedded defects. It can be shown that efficient time sampling in the virtual wave concept allows a significant reduction in the number of data points compared to uniform sampling, without compromising the quality of the reconstruction results.

In this study, we proposed an electromagnetic induction testing method for measuring the electrical properties of carbon fiber reinforced thermoplastics (CFRTPs) along the through-thickness direction. The effectiveness of the transmission method, wherein the coil is placed opposite to the object to be measured, was demonstrated through finite element analysis and experimental measurements. The simulation results indicated that the output voltage of an interlaminar non-electrically conductive specimen exceeded that of an interlaminar conductive specimen due to the electromagnetic shielding effect. In the experiments, the impedance along the through-thickness direction depended on the lamination configuration and the presence of the PA-6 layer. Our findings indicate that the proposed method can be used to measure the changes in the electrical properties of CFRTP along the through-thickness direction.

Currently, ultrasonic tomography is widely used for quantifying the status of damage/flaw in various materials including metal, concrete, and composite. It is capable of visualizing the internal damage or flaws by reconstructing the velocity of ultrasound. For most cases, the conventional ultrasonic tomography is adapted for slice-based investigations. Though 3D image can be generated by slice-based method, the involvement of multi-scan interpolation caused high computational cost and unexpected errors. Moreover, for 3D imaging, two essential factors are dominant: (i) reconstructing the velocity; and (ii) scheme of forming up the 3D image. To this end, this study proposed to develop a novel volumetric ultrasound imaging strategy with high accuracy. To obtain more accurate Time-of-Flight (TOF) for ultrasonic velocity, an improved method based on cumulative kurtosis is proposed. With the proposed method, the adverse influence of internal complexity within samples on ultrasound was reduced. The proposed novel volumetric ultrasound imaging strategy was verified numerically and experimentally. Finally, the performance of the proposed method has been evaluated by the comparison of three-dimensional imaging results with different inclusion. Additionally, the parametric study was conducted using path average velocity, voxel velocity, and image accuracy. The results show a positive correlation between the number of voxels and imaging accuracy. However, as the number of voxels increases, the errors introduced by the Simultaneous Algebraic Reconstruction Technique (SART) increase. The influential factors on the imaging accuracy were discussed, such as inclusion eccentricity, the relationship among the reduced volume imaging quantity, and accuracy in voxel inversion result. For further application, the recommendations were also provided.

Ultrasonic reflection coefficient is the key to contact state evaluation of mechanical devices. Edge blurring can lead to contact state (such as stress concentrations) measurement errors. This reduces the reliability of performance evaluations and introduces potential security risks. In this study, an edge blurring suppression method based on matching pursuit algorithm was proposed. Firstly, the interference signal prediction model is built based on the Nakagami model. Then, a blurred signal separation algorithm based on matching pursuit is proposed to obtain the effective signal. Finally, the reflection coefficient with and without edge blurring effect were obtained. The simulation results show that the maximum relative error of the reflection coefficient is reduced from 219 % to 15 %. The effectiveness of the proposed method is also verified by experiments. The experimental results show that the relative error of the reflection coefficient after edge blurring suppression is reduced from 64 % to 16 %. This indicates that the proposed method can effectively suppress edge blurring, which provides an effective method for edge blurring suppression in various application fields of ultrasonic measurement and improve the reliability of product quality evaluation.