Search Results (54)

As the world increasingly gravitates towards green, environmentally friendly and low-carbon lifestyles, wind power has become one of the most technologically established renewable energy sources. However, with the continuous increase in their output power and height, wind turbine towers are subjected to higher-intensity alternating wind loads. This makes critical components more prone to fatigue failure, potentially leading to major accidents such as tower buckling or turbine collapse. High-strength bolts play a vital role in supporting towers but are susceptible to fatigue crack initiation under long-term cyclic loading, necessitating regular inspection. Types of wind turbine bolts mainly include high-strength bolts, stainless steel bolts, anchor bolts, titanium alloy bolts, and adjustable bolts. These bolts are distributed across different parts of the turbine and perform distinct functions. Among them, high-strength bolts in the tower are particularly critical for structural support, demanding prioritized periodic inspection. Compared to destructive offline inspection methods requiring bolt disassembly, non-destructive testing (NDT) has emerged as a trend in defect detection technologies. Therefore, this review comprehensively examines various types of NDT techniques for wind turbine towers’ high-strength bolts, including disassembly inspection techniques (magnetic particle inspection, penetration inspection, intelligent torque inspection, etc.) and non-disassembly inspection techniques (ultrasonic inspection, radiographic inspection, infrared thermographic inspection, etc.). For each technique, we analyze the fundamental principles, technical characteristics, and limitations, while emphasizing the interconnections between the methodologies. Finally, we discuss potential future research directions for bolt defect NDT technologies. Full article

Voids behind tunnel linings are common hidden defects in underground engineering, leading to reduced structural capacity and potential safety hazards. To address the deficiencies in the understanding of the mechanism and the optimization of design of the existing steel plate reinforcement methods, this study systematically investigates the reinforcement mechanisms and proposes refined design strategies through numerical simulations and experimental validation. First, a comparative analysis of the Concrete Damage Plasticity (CDP) model and the Extended Finite Element Method (XFEM) revealed that the CDP model exhibits superior accuracy and computational efficiency in simulating large-scale void linings. Second, the effectiveness of different reinforcement schemes (chemical anchor bolts alone, structural adhesive alone, and combined systems) was evaluated, demonstrating that structural adhesive dominates stress transfer, while chemical anchor bolts primarily prevent plate detachment. Through further optimization simulations of the steel plate spacing, it was found that a spacing of 0.25 m can balance the reinforcement effect and cost. This spacing restricts the maximum principal stress (1.83 MPa) below the tensile strength of concrete while essentially eliminating damage to the lower surface of the lining. An optimized steel plate reinforcement structure was ultimately proposed. By reducing the number of chemical anchor bolts and decreasing their size (with only M12 chemical anchor bolts arranged at the edges), local damage is minimized while maintaining reinforcement efficiency. The research results provide theoretical support and engineering guidance for the safe repair of tunnel void areas. Full article

This work aims to investigate the buckling and post-buckling behaviour of wood-based sandwich structures with and without a manufacturing defect, under compressive loading. The specimens were made by gluing birch veneers to a balsa wood core. The defect consisted of a central zone where glue was lacking between the skin and the core. A compression load was applied to the plate using the VERTEX test rig, with the plate placed on the upper surface of a rectangular box and bolted at its borders. The upper surface of the plate was monitored using optical and infrared cameras. The stereo digital image correlation method was used to capture the in-plane and out-of-plane deformations of the specimen, and to calculate the strains and stresses. The infrared camera enabled the failure scenario to be identified. The buckling behaviour of pristine specimens showed small local debonding in the post-buckling range, which was not detrimental to overall performance. In the presence of a manufacturing defect, the decrease in buckling load was only about 15%, but final failure occurred at lower compressive loads. Full article

The accurate detection of surface bolt defects in railway steel truss bridges plays a vital role in maintaining structural integrity. Conventional manual inspection techniques require extensive labor and introduce subjective assessments, frequently yielding variable results across inspections. While UAV-based approaches have recently been developed, they still encounter significant technical obstacles, including small target recognition, background complexity, and computational limitations. To overcome these challenges, CSEANet is introduced—an improved YOLOv8-based framework tailored for bolt defect detection. Our approach introduces three innovations: (1) a sliding-window SAF preprocessing method that improves small target representation and reduces background noise, achieving a 0.404 mAP improvement compared with not using it; (2) a refined network architecture with BSBlock and MBConvBlock for efficient feature extraction with reduced redundancy; and (3) a novel BoltFusionFPN module to enhance multi-scale feature fusion. Experiments show that CSEANet achieves an mAP@50:95 of 0.952, confirming its suitability for UAV-based inspections in resource-constrained environments. This framework enables reliable, real-time bolt defect detection, supporting safer railway operations and infrastructure maintenance. Full article

Tower bolts play a crucial role as connecting components in wind turbines and are of great interest for health monitoring systems. Non-contact monitoring techniques offer superior efficiency, convenience, and intelligence compared to contact-based methods. However, the precision and robustness of the non-contact monitoring process are significantly impacted by suboptimal lighting conditions within the wind turbine tower. To address this problem, this article proposes an automated detection method for the bolt detachment of wind turbines in low-light scenarios. The approach leverages the deep convolutional generative adversarial network (DCGAN) to expand and augment the small-sample bolt dataset. Transfer learning is then applied to train the Zero-DCE++ low-light enhancement model and the bolt defect detection model, with the experimental verification of the proposed method’s effectiveness. The results reveal that the deep convolutional generative adversarial network can generate realistic bolt images, thereby improving the quantity and quality of the dataset. Additionally, the Zero-DCE++ light enhancement model significantly increases the mean brightness of low-light images, resulting in a decrease in the error rate of defect detection from 31.08% to 2.36%. In addition, the model’s detection performance is affected by shooting angles and distances. Maintaining a shooting distance within 1.6 m and a shooting angle within 20° improves the reliability of the detection results. Full article

The IDEA project, developed in the frame of MOST—National Centre for Sustainable Mobility—addressed the growing need for reliable bonded joints in fibre-reinforced polymer composite structures used in transportation. Purely bonded joints are preferred for their lightweight and cost-efficient properties, but contamination and defect detection issues often make them unreliable. To solve this, the project developed innovative surface treatments, a methodology for the safe, optimized design of bonded joints, and structural health monitoring solutions, viable for real-time assessment. These advancements aim to increase the reliability and safety of bonded connections, helping industries adopt lighter, purely bonded joints over heavier, hybrid bonded/bolted options. Full article

The high temperature performance of steel structures has long been a focus of research, but research on the damage and crack propagation mechanism of steel with initial defects at high temperature is relatively low. The high temperature performance of most steel structures in engineering has an important impact on the function and safety of the whole structure. At present, Peridynamics (PD) theory uses the integral method that has unique advantages compared with traditional methods to solve structural damage and fracture problems. Therefore, the effect of temperature change on steel properties is introduced into the PD, and the PD constitutive equation at high temperature is proposed. The damage and crack propagation mechanisms of 2D Q345 steel plates with bilateral cracks and different bolt holes at 20 °C, 300 °C, 400 °C and 600 °C were analyzed by applying temperature action and external load to double-cracked steel specimens by the direct thermostructural coupling method. At the same time, the damage values, displacement changes in X direction and Y direction under different temperatures were compared and analyzed, and the effects of temperature, bolt hole and external load on the damage, displacement and crack growth path of different parts of the structure were obtained. Full article

In the past ten years, many coal mines have encountered the problem of a premature failure of anchor rod materials. Through field investigation and laboratory research, it was found that the premature failure of these bolt materials is mostly caused by mine water corrosion. In this paper, a Zn-Y₂O₃-Al₂O₃ composite coating was prepared by an electrodeposition method for the corrosion protection of underground anchors. Through the single-factor experiment method, the co-deposition process of Zn²⁺ nano-Y₂O₃ and nano-Al₂O₃ particles was studied. Microhardness was used as the index to determine the optimum preparation process for the composite coatings. Combined with FSEM and XRD tests, the results showed that the synergistic effect of nano-Y₂O₃ and nano-Al₂O₃ particles made the coating grain refined and reduced the coating defects. The hardness of the coating increased from 98.7 Hv to 347.9 Hv, and the hardness and wear resistance of the coating were improved. The hydrophobicity of the Zn-Y₂O₃-Al₂O₃ composite coating was improved, and its static contact angle was 93.28°. The corrosion resistance of the composite coating was studied through electrochemical impedance spectroscopy, the Tafel curve, corrosion morphology, and weight loss. Under the synergistic effect of nano-Y₂O₃ and nano-Al₂O₃ particles, the self-corrosion current density decreased from 4.21 × 10⁻⁴ A/cm² to 1.06 × 10⁻⁵ A/cm², which confirmed that the Zn-Y₂O₃-Al₂O₃ composite coating had better corrosion resistance and durability. After soaking in mine water for 63 days, the Zn-Y₂O₃-Al₂O₃ composite coating had no obvious shedding on the surface and was well preserved. The practical application results show that it has excellent corrosion resistance and durability. The Zn-Y₂O₃-Al₂O₃ nano-composite coating material has significant potential advantages in the field of corrosion resistance of underground anchor rods. 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

To enhance the automatic quality monitoring of bolt production, YOLOv10, Intel RealSense D435, and OpenCV were integrated to leverage GPU parallel computing capabilities for defect recognition and size measurement. To improve the model’s effectiveness across various industrial production environments, data augmentation techniques were employed, resulting in a trained model with notable precision, accuracy, and robustness. A high-precision camera calibration method was used, and image processing was accelerated through GPU parallel computing to ensure efficient and real-time target size measurement. In the real-time monitoring system, the average defect prediction time was 0.009241 s, achieving an accuracy of 99% and demonstrating high stability under varying lighting conditions. The average size measurement time was 0.021616 s, and increasing the light intensity could reduce the maximum error rate to 1%. These results demonstrated that the system excelled in real-time performance, accuracy, robustness, and efficiency, effectively addressing the demands of industrial production lines for rapid and precise defect detection and size measurement. In the dynamic and variable context of industrial applications, the system can be optimized and adjusted according to specific production environments and requirements, further enhancing the accuracy of defect detection and size measurement tasks. Full article

This research aimed to detect the defects of anchoring agents’ empty slurries in anchor support. The influence of anchoring defects on the propagation law of stress waves was comprehensively investigated using laboratory tests, theoretical calculations, and other methods. The characteristic modal components with symmetry and periodicity laws were extracted by adopting a variable modal decomposition (VMD) signal decomposition method. It was found that the bottom reflection time of stress waves had an inverse function relationship with the length of the anchorage flaw. The average propagation speed of the stress wave in the free rod was obtained as 5150 m/s, and the average consolidation wave speed was 4198 m/s. The calculation method of the bolt flaw length was finally proposed. After experimental verification, the average error rate was 2.65%, which meets the requirement of testing accuracy in the engineering field, which provides a guarantee for safe production. Full article

Near-net-shaped metal products manufactured by high-pressure diecasting (HPD) encountered more or less critical failure during operation, owing to the development of micro-defects and structural inhomogeneity attributed to the complexity of geometrical die design. Because the associated work primarily relies on technical experience, it is necessary to perform the structural analysis of the HPDed component in comparison with simulation-based findings that forecast flow behavior, hence reducing trial and error for optimization. This study validated the fluidity and solidification behaviors of a commercial-grade Al-Si-Cu-Mg alloy (ALDC12) that is widely used in electric vehicle housing parts using the ProCAST tool. Both experimental and simulation results exhibited that defects at the interface of a compact mold filling were barely detected. However, internal micro-pores were seen in the bolt region, resulting in a 17.27% drop in micro-hardness compared to other parts, for which the average values from distinguished observation areas were 111.24 HV, 92.03 HV, and 103.87 HV. The simulation aligns with structural observations on defect formation due to insufficient fluidity in local geometry. However, it may underestimate the cooling rate under isothermal conditions. Thus, the simulation used in this work provides reliable predictions for optimizing HPD processing of the present alloy. Full article

Multi-layer conductive structures, especially those with features like bolt holes, are vulnerable to hidden corrosion and cracking, posing a serious threat to equipment integrity. Early defect detection is vital for implementing effective maintenance strategies. However, the subtle signals produced by these defects necessitate highly sensitive non-destructive testing (NDT) techniques. Analytical modeling plays a critical role in both enhancing defect-detection capabilities and guiding the design of highly sensitive sensors for these complex structures. Compared to the finite element method (FEM), analytical approaches offer advantages, such as faster computation and high accuracy, enabling a comprehensive analysis of how sensor and material parameters influence defect detection outcomes. This paper introduces a novel T-core eddy current sensor featuring a central air gap. Utilizing the vector magnetic potential method and a truncated region eigenfunction expansion (TREE) method, an analytical model was developed to investigate the sensor’s interaction with multi-layer conductive materials containing a hidden hole. The model yielded closed-form expressions for the induced eddy current density and coil impedance. A comparative study, implemented in Matlab, analyzed the eddy current distribution generated by T-core, E-core, I-core, and air core sensors under identical conditions. Furthermore, the study examined how the impedance of the T-core sensor changed at different excitation frequencies between 100 Hz and 10 kHz when positioned over a multi-layer conductor with a hidden air hole. These findings were then compared to those obtained from E-core, I-core, and air-core sensors. The analytical results were validated through finite element simulations and experimental measurements, exhibiting excellent agreement. The study further explored the influence of T-core design parameters, including the air gap radius, dome radius, core column height, and relative permeability of the T-core material, on the inspection sensitivity. Finally, the proposed T-core sensor was used to evaluate crack and hole defects in conductors, demonstrating its superior sensitivity compared to I-core and air core sensors. Although slightly less sensitive than the E-core sensor, the T-core sensor offers advantages, including a more compact design and reduced material requirements, making it well-suited for inspecting intricate and confined surfaces of the target object. This analytical model provides a valuable tool for designing advanced eddy current sensors, particularly for applications like detecting bolt hole defects or measuring the thickness of non-conductive coatings in multi-layer conductor structures. Full article

In the literature on rotating machinery, many articles discuss the analysis of various rotor and bearing defects, including both sliding and rolling bearings. Defects in the rotor supporting system are investigated much less frequently. In rotor-bearing-supporting structure systems, where there are couplings between the individual sub-systems, damage to the supporting structure can significantly impact the dynamic properties of the entire machine. The authors of this article have, therefore, focused on analysing the defects that can occur in the supporting system of the rotor and bearings. This article presents the results of a numerical analysis of two common defects in the supporting structure: cracks in the bolted joints attaching the machine body to the foundation and a decrease in foundation stiffness. The research object was a test rig that accurately reproduced the dynamic phenomena occurring in rotating machinery, such as vapour and gas turbines. In the numerical model of the rotating machine, a three-dimensional linear model of the supporting structure was combined with a beam model of the rotor line via a nonlinear fluid film-bearing model. The developed model allowed for the analysis of two different failures in the supporting system over a wide range of rotational speeds. The calculations showed that damage to the supporting structure can significantly impact the dynamic characteristics of the entire rotating machine. Full article

With the increasing demand for the performance and design refinement of steel structures (including houses, bridges, and infrastructure), many structures have adopted ultimate bearing capacity in service. The design service lives of steel building structures are generally more than 50 years, and most of them contain bolted connections, which suffer from extreme conditions such as fire (high temperature) during service. When the structure contains defects or cracks and bolt holes, it is easy to produce stress concentration at the defect location, which leads to crack nucleation and crack propagation, reduces the bearing capacity of the structure, and causes the collapse of the structure and causes disasters. In the process of structural damage and crack propagation, the traditional method has some disadvantages, such as stress singularity, the mesh needing to be redivided, and the crack being restricted to mesh; however, the integral method of peridynamics (PD) can completely avoid these problems. Therefore, in this paper, the constitutive equation of PD in high temperature is derived according to the variation law of steel material properties when changed by temperature increase and peridynamics parameters; the damage and crack expansion characteristics of Q345 steel specimens with bolt holes and a central double-crack at 20 °C, 200 °C, 400 °C, and 600 °C were analyzed to clarify the structural damage and failure mechanism. This study is helpful for providing theoretical support for the design of high-temperature steel structures, improving the stability of the structure, and ensuring the bearing capacity of the structure and the safety of people’s lives and property. Full article