Search Results (3)

Non-destructive testing (NDT) methods are critical for evaluating the structural integrity of and detecting defects in composite materials across industries such as aerospace and renewable energy. This review examines the recent trends and successful implementations of NDT approaches for composite materials, focusing on articles published between 2015 and 2025. A systematic literature review identified 120 relevant articles, highlighting techniques such as ultrasonic testing (UT), acoustic emission testing (AET), thermography (TR), radiographic testing (RT), eddy current testing (ECT), infrared thermography (IRT), X-ray computed tomography (XCT), and digital radiography testing (DRT). These methods effectively detect defects such as debonding, delamination, and voids in fiber-reinforced polymer (FRP) composites. The selection of NDT approaches depends on the material properties, defect types, and testing conditions. Although each technique has advantages and limitations, combining multiple NDT methods enhances the quality assessment of composite materials. This review provides insights into the capabilities and limitations of various NDT techniques and suggests future research directions for combining NDT methods to improve quality control in composite material manufacturing. Future trends include adopting multimodal NDT systems, integrating digital twin and Industry 4.0 technologies, utilizing embedded and wireless structural health monitoring, and applying artificial intelligence for automated defect interpretation. These advancements are promising for transforming NDT into an intelligent, predictive, and integrated quality assurance system. Full article

The integrity of multi-bolted flanges is crucial for ensuring safety and operational efficiency in industrial systems across sectors such as oil and gas, chemical processing, and water treatment. Traditional non-destructive testing (NDT) methods often require operational downtime and may lack sensitivity for early-stage defect detection. This review examines acoustic emission testing (AET), a real-time monitoring technique for detecting acoustic waves generated by material defects. An analysis of 145 studies demonstrated AET’s effectiveness in detecting early-stage defects across various materials and industrial applications. Recent advances in sensor technology and signal processing have significantly enhanced AET’s capabilities. However, challenges remain regarding environmental noise interference and the need for specialized expertise. The review identifies knowledge gaps and proposes future research directions, including planned laboratory experiments to characterize defect signals in multi-bolted flange systems under different operational conditions. The findings position AET as a transformative solution for industrial inspection and maintenance, offering enhanced safety and reliability for critical infrastructures. Full article

In heterogeneous materials such as concrete, deterioration of the elastic wave—which acoustic emission technique (AET) is based on—is one of the research objects in the field. While many studies reveal that the wave is deteriorated due to the concrete content and deterioration of AE signals causes erroneous data interpretation, a limited number of them have suggested eliminating the effects of this problem. For this reason, contributing to the existing literature, this paper proposes to correct AE signals for fiber-reinforced concrete, which is a highly heterogeneous material, by 3D-PCT (Parameter Correction Technique) developed with new approaches in the authors’ previous study for concrete. First, the attenuation properties of concrete samples, including different types and amounts of fibers, were revealed within this scope. Contour maps showed that the type and amount of fiber are effective on elastic wave attenuation. Then, the samples were tested under flexure, and AE results were compared with mechanical findings after parameter correction. The effectiveness of the proposed correction method was verified by separating fiber activities from concrete cracking activities for the first time in the literature with weighted peak frequency and partial power. In this way, by successfully matching the fiber activities, which were revealed after the correction, with the crack development times obtained from frequency-based unsupervised pattern recognition, it was seen that a more accurate AE interpretation could be made with parameter correction. Moreover, corrected AE parameters also provided to propose a new inference for identifying a relationship between the amplitude and energy loss of the AE signals and the type of damage. Full article