Applications of Non-destructive Testing Technologies in Materials or Engineering

Polymers find widespread applications in various industries, such as civil engineering, aerospace, and industrial machinery, contributing to vibration control, dampening, and insulation. To accurately design products that are able to predict their dynamic behavior in the virtual environment, it is essential to understand and reproduce their viscoelastic properties via material physical modeling. While Dynamic Mechanical Analysis (DMA) has traditionally been used, innovative non-destructive techniques are emerging for characterizing components and monitoring their performance without deconstructing them. In this context, the Time–Temperature Superposition Principle (TTSP) represents a powerful empirical procedure to extend a polymer’s viscoelastic behavior across a wider frequency range. This study focuses on replicating an indentation test on viscoelastic materials using the non-destructive Viscoelasticity Evaluation System evolved (VESevo) tool. The primary objective is to derive a unique temperature–frequency relationship, referred to as a “shift law”, using characteristic curves from this non-invasive approach. Encouragingly, modifying the device setup enabled us to replicate, virtually, three tests under identical initial conditions but with varying indentation frequencies. This highlights the tool’s ability to conduct material testing across a range of frequencies. These findings set the stage for our upcoming experiment campaign, aiming to create an innovative shift algorithm from at least three distinct master curves at specific frequencies, offering a significant breakthrough in non-destructive polymer characterization with broad industrial potential. Full article

In the current industrial revolution, advanced technologies and methods can be effectively utilized for the detection and verification of defects in high-speed steel filament production. This paper introduces an innovative methodology for the precise detection and verification of micro surface defects found in steel filaments through the application of the Eddy current principle. Permanent magnets are employed to generate a magnetic field with a high frequency surrounding a coil of sensors positioned at the filament’s output end. The sensor’s capacity to detect defects is validated through a meticulous rewinding process, followed by a thorough analysis involving scanning electron microscopy (SEM) and energy-dispersive spectroscopy (EDS). Artificial defects were intentionally introduced into a sample, and their amplitudes were monitored to establish a threshold value. The amplitude signal of these created defect was identified at approximately 10% FSH, which corresponds to a crack depth of about 20 µm. In the experimental production of 182 samples covering 38 km, the defect ratio was notably high, standing at 26.37%. These defects appeared randomly along the length of the samples. The verification results underscore the exceptional precision achieved in the detection of micro surface defects within steel filaments. These defects were primarily characterized by longitudinal scratches and inclusions containing physical tungsten carbide. Full article

The grinding grooves of material removal machining and the residues of a machining tool on the key component surface cause surface stress concentration. Thus, it is critical to carry out precise measurements on the key component surface to evaluate the stress concentration. Based on white-light interferometry (WLI), we studied the measurement distortion caused by the reflected light from the steep side of the grinding groove being unable to return to the optical system for imaging. A threshold value was set to eliminate the distorted measurement points, and the cubic spline algorithm was used to interpolate the eliminated points for compensation. The compensation result agrees well with the atomic force microscope (AFM) measurement result. However, for residues on the surface, a practical method was established to obtain a microscopic 3D micro-topography point cloud and a super-depth-of-field fusion image simultaneously. Afterward, the semantic segmentation network U-net was adopted to identify the residues in the super-depth-of-field fusion image and achieved a recognition accuracy of 91.06% for residual identification. Residual feature information, including height, position, and size, was obtained by integrating the information from point clouds and super-depth-of-field fusion images. This work can provide foundational data to study surface stress concentration. Full article

This study aims to propose and validate the state space mode decomposition technique for precise mode separation of non-classical damping systems and closely distributed modal systems. To assess the reliability and applicability of this technique, a 40-story building with a tuned mass damper is investigated, and acceleration responses measured by the building’s health monitoring system are used for the verification of the technique. The mode separation results reveal that the separated modal power spectrum becomes distorted at neighboring natural frequency ranges when the performance index only considers the concentration of power spectral energy at the target natural frequency. However, by introducing an augmented performance index that includes a constraint condition to account for distortion, more accurate mode decomposition can be achieved. Full article

Thermal barrier coatings (TBCs) play a crucial role in safeguarding aero-engine blades from high-temperature environments and enhancing their performance and durability. Accurate evaluation of TBCs’ porosity is of paramount importance for aerospace material research. However, existing evaluation methods often involve destructive testing or lack precision. In this study, we proposed a novel nondestructive evaluation method for TBCs’ porosity, utilizing terahertz time-domain spectroscopy (THz-TDS) and a machine learning approach. The primary objective was to achieve reliable and precise porosity evaluation without causing damage to the coatings. Multiple feature parameters were extracted from THz-TDS data to characterize porosity variations. Additionally, correlation analysis and p-value testing were employed to assess the significance and correlations among the feature parameters. Subsequently, the dung-beetle-optimizer-algorithm-optimized random forest (DBO-RF) regression model was applied to accurately predict the porosity. Model performance was evaluated using K-fold cross-validation. Experimental results demonstrated the effectiveness of our proposed method, with the DBO-RF model achieving high precision and robustness in porosity prediction. The model evaluation revealed a root-mean-square error of 1.802, mean absolute error of 1.549, mean absolute percentage error of 8.362, and average regression coefficient of 0.912. This study introduces a novel technique that presents a dependable nondestructive testing solution for the evaluation and prediction of TBCs’ porosity, effectively monitoring the service life of TBCs and determining their effectiveness. With its practical applicability in the aerospace industry, this method plays a vital role in the assessment and analysis of TBCs’ performance, driving progress in aerospace material research. Full article

An experimental study has been carried out to assess the effectiveness of infrared thermography in wrinkle detection in composite GFRP (Glass Fiber Reinforced Plastic) structures by infrared active thermography. Wrinkles in composite GFRP plates with different weave patterns (twill and satin) have been manufactured with the use of the vacuum bagging method. The different localization of defects in laminates has been taken into account. Transmission and reflection measurement techniques of active thermography have been verified and compared. The section of a turbine blade with a vertical axis of rotation containing post-manufacturing wrinkles has been prepared to verify active thermography measurement techniques in the real structure. In the turbine blade section, the influence of a gelcoat surface on the effectiveness of thermography damage detection has also been taken into account. Straightforward thermal parameters applied in structural health monitoring systems allow an effective damage detection method to be built. The transmission IRT setup allows not only for damage detection and localization in composite structures but also for accurate damage identification. The reflection IRT setup is convenient for damage detection systems coupled with nondestructive testing software. In considered cases, the type of fabric weave has negligible influence on the quality of damage detection results. Full article

The detection and quantification of fractures in rocks, as well as the detection of lithological changes, are of particular interest in scientific fields, such as construction materials, geotechnics, reservoirs and the diagnostics of dielectric composite materials and cultural heritage objects. Therefore, different methods and techniques have been developed and improved over the years to provide solutions, e.g., seismic, ground-penetrating radar and X-ray microtomography. However, there are always trade-offs, such as spatial resolution, investigated volume and rock penetration depth. At present, high-frequency radars (>60 GHz) are available on the market, which are compact in size and capable of imaging large areas in short periods of time. However, the few rock applications that have been carried out have not provided any information on whether these radars would be useful for detecting fractures and lithological changes in rocks. Therefore, in this work, we performed different experiments on construction and reservoir rocks using a frequency-modulated continuous wave radar working at 300 GHz to evaluate its viability in this type of application. The results showed that the radar quantified millimeter fractures at a 1 cm rock penetration depth with a sensitivity of 500 μm. Furthermore, lithological changes were identified, even when detecting interfaces generated by the artificial union of two samples from the same rock. Full article