Search Results (4,500)

To enable intelligent inspection of underground cable systems, this study presents a gecko-inspired quadruped robot that integrates multi-degree-of-freedom motion with a deep learning-based visual detection system. Inspired by the gecko’s flexible spine and leg structure, the robot exhibits strong adaptability to confined and uneven tunnel environments. The motion system is modeled using the standard Denavit–Hartenberg (D–H) method, with both forward and inverse kinematics derived analytically. A zero-impact foot trajectory is employed to achieve stable gait planning. For defect detection, the robot incorporates a binocular vision module and an enhanced YOLOv8 framework. The key improvements include a lightweight feature fusion structure (SlimNeck), a multidimensional coordinate attention (MCA) mechanism, and a refined MPDIoU loss function, which collectively improve the detection accuracy of subtle defects such as insulation aging, micro-cracks, and surface contamination. A variety of data augmentation techniques—such as brightness adjustment, Gaussian noise, and occlusion simulation—are applied to enhance robustness under complex lighting and environmental conditions. The experimental results validate the effectiveness of the proposed system in both kinematic control and vision-based defect recognition. This work demonstrates the potential of integrating bio-inspired mechanical design with intelligent visual perception to support practical, efficient cable inspection in confined underground environments. Full article

In the casting and rolling production process, surface longitudinal cracks are a typical casting defect. Tracing the causes of longitudinal cracks online and controlling the key parameters leading to their formation in a timely manner can enhance the stability of casting and rolling production. To this end, the influencing factors of longitudinal cracks were analyzed, a data integration storage platform was constructed, and a tracing model was established using empirical rule analysis, statistical analysis, and intelligent analysis methods. During the initial production phase of a casting machine, longitudinal cracks occurred frequently. The tracing results using the LightGBM-SHAP method showed that the relative influence of the narrow left wide inner heat flow ratio of the mold was significant, followed by the heat flow difference on the wide symmetrical face of the mold and the superheat of the molten steel, with weights of 0.135, 0.066, and 0.048, respectively. Based on the tracing results, we implemented online emergency measures. By controlling the cooling intensity of the mold, we effectively reduced the recurrence rate of longitudinal cracks. Root cause analysis revealed that the total hardness of the mold-cooling water exceeded the standard, reaching 24 mg/L, which caused scaling on the mold copper plates and uneven cooling, leading to the frequent occurrence of longitudinal cracks. After strictly controlling the water quality, the issue of longitudinal cracks was brought under control. The online application of the tracing method for the causes of longitudinal cracks has effectively improved efficiency in resolving longitudinal crack problems. Full article

Automated surface defect detection in steel manufacturing is pivotal for ensuring product quality, yet it remains an open challenge owing to the extreme heterogeneity of defect morphologies—ranging from hairline cracks and microscopic pores to elongated scratches and shallow dents. Existing approaches, whether classical vision pipelines or recent deep-learning paradigms, struggle to simultaneously satisfy the stringent demands of industrial scenarios: high accuracy on sub-millimeter flaws, insensitivity to texture-rich backgrounds, and real-time throughput on resource-constrained hardware. Although contemporary detectors have narrowed the gap, they still exhibit pronounced sensitivity–robustness trade-offs, particularly in the presence of scale-varying defects and cluttered surfaces. To address these limitations, we introduce MBY (MBDNet-Attention-YOLO), a lightweight yet powerful framework that synergistically couples the MBDNet backbone with the YOLO detection head. Specifically, the backbone embeds three novel components: (1) HGStem, a hierarchical stem block that enriches low-level representations while suppressing redundant activations; (2) Dynamic Align Fusion (DAF), an adaptive cross-scale fusion mechanism that dynamically re-weights feature contributions according to defect saliency; and (3) C2f-DWR, a depth-wise residual variant that progressively expands receptive fields without incurring prohibitive computational costs. Building upon this enriched feature hierarchy, the neck employs our proposed MultiSEAM module—a cascaded squeeze-and-excitation attention mechanism operating at multiple granularities—to harmonize fine-grained and semantic cues, thereby amplifying weak defect signals against complex textures. Finally, we integrate the Inner-SIoU loss, which refines the geometric alignment between predicted and ground-truth boxes by jointly optimizing center distance, aspect ratio consistency, and IoU overlap, leading to faster convergence and tighter localization. Extensive experiments on two publicly available steel-defect benchmarks—NEU-DET and PVEL-AD—demonstrate the superiority of MBY. Without bells and whistles, our model achieves 85.8% mAP@0.5 on NEU-DET and 75.9% mAP@0.5 on PVEL-AD, surpassing the best-reported results by significant margins while maintaining real-time inference on an NVIDIA Jetson Xavier. Ablation studies corroborate the complementary roles of each component, underscoring MBY’s robustness across defect scales and surface conditions. These results suggest that MBY strikes an appealing balance between accuracy, efficiency, and deployability, offering a pragmatic solution for next-generation industrial quality-control systems. Full article

To address the issue of interfacial shrinkage deformation in optical resin–cement-based composites, this study examined the effects of casting methods and coupling agent treatments on the interfacial deformation behavior and underlying mechanisms at the resin–cement interface. A self-developed interfacial shrinkage testing apparatus, combined with ABAQUS numerical simulations, was employed to facilitate this analysis. The results revealed that the interfacial shrinkage strain followed a characteristic distribution—higher at both ends and lower in the middle region—as the temperature increased. The experimental data showed a strong agreement with the simulation outcomes. A comparative analysis indicated that the pre-cast cement method reduced the interfacial shrinkage strain by 16% compared to the pre-cast resin method. Furthermore, treatment with a coupling agent resulted in a 31% reduction in the strain, while combining a serrated surface modification with a coupling agent treatment achieved a maximum reduction of 43.5%. Microscopic characterization confirmed that the synergy between the coupling agent and surface roughening significantly enhanced interfacial bonding by filling microcracks, improving adhesion, and increasing mechanical interlocking. This synergistic effect effectively suppressed the relative slippage caused by asynchronous shrinkage between dissimilar materials, thereby mitigating the interfacial cracking issue in optical resin–cement-based composites. These findings provide theoretical insights for optimizing the interface design in organic–inorganic composite systems. Full article

During the process of oil and gas drilling, due to the existence of pores or micro-cracks, drilling fluid is prone to invade the formation. Under the action of hydration expansion of clay in the formation and liquid pressure, wellbore instability occurs. In order to reduce the wellbore instability caused by drilling fluid intrusion into the formation, this study proposed a method of forming a dynamic hydrogen bond cross-linked network weak gel structure with modified nano-silica and P(AM-AAC). The plugging performance of the drilling fluid and the performance of inhibiting the hydration of shale were evaluated through various experimental methods. The results show that the gel composite system (GCS) effectively optimizes the plugging performance of drilling fluid. The 1% GCS can reduce the linear expansion rate of cuttings to 14.8% and increase the recovery rate of cuttings to 96.7%, and its hydration inhibition effect is better than that of KCl and polyamines. The dynamic cross-linked network structure can significantly increase the viscosity of drilling fluid. Meanwhile, by taking advantage of the liquid-phase viscosity effect and the physical blocking effect, the loss of drilling fluid can be significantly reduced. Mechanism studies conducted using zeta potential measurement, SEM analysis, contact angle measurement and capillary force assessment have shown that modified nano-silica stabilizes the wellbore by physically blocking the nano-pores of shale and changing the wettability of the shale surface from hydrophilic to hydrophobic when the contact angle exceeds 60°, thereby reducing capillary force and surface free energy. Meanwhile, the dynamic cross-linked network can reduce the seepage of free water into the formation, thereby significantly lowering the fluid loss of the drilling fluid. This research provides new insights into improving the stability of the wellbore in drilling fluids. Full article

The resistivity imaging system is specifically designed for the precise measurement of resistivity distributions within drilled columnar core samples. Its coaxial symmetric configuration enables the non-destructive characterization of electrical properties, with broad applications in oil and gas exploration, reservoir evaluation, and geological research. By integrating a ring return electrode and full-circumference electrode arrays, the system can acquire core-scale resistivity data in conductive media environments. The self-developed imaging software employs advanced processing algorithms—including depth correction, amplitude normalization, and image enhancement—to transform raw resistivity measurements into high-resolution surface imaging maps. Experimental results demonstrate that the system can resolve features such as cracks with a minimum width of 0.5 mm and pores with a minimum inner diameter of 0.4 mm in granite core, providing a novel technical approach for the fine-scale characterization of core materials. Full article

Crack initiation, propagation, and slippage serve as the key mesoscopic mechanisms contributing to the deterioration of deep tunnel surrounding rocks. In this study, a secondary anisotropy of deep tunnels surrounding rocks was proposed: The axial-displacement constraint of deep tunnels forces cracks in the surrounding rock to initiate, propagate, and slip in planes parallel to the tunnel axial direction. These cracks have no significant effect on the axial strength of the surrounding rock but significantly reduce the tangential strength, resulting in the secondary anisotropy. First, the secondary anisotropy was verified by a hybrid stress–strain controlled true triaxial test of sandstone specimens, a CT 3D (computed tomography three-dimensional) reconstruction of a fractured sandstone specimen, a numerical simulation of heterogeneous rock specimens, and field borehole TV (television) images. Subsequently, a novel SSA (strain-softening and secondary anisotropy) constitutive model was developed to characterise the secondary anisotropy of the surrounding rock and developed using C++ into a numerical form that can be called by FLAC^3D (Fast Lagrangian Analysis of Continua in 3 Dimensions). Finally, effects of secondary anisotropy on a deep tunnel surrounding rock were analysed by comparing the results calculated by the SSA model and a uniform strain-softening model. The results show that considering the secondary anisotropy, the extent of strain-softening of the surrounding rock was mitigated, particularly the axial strain-softening. Moreover, it reduced the surface displacement, plastic zone, and dissipated plastic strain energy of the surrounding rock. The proposed SSA model can precisely characterise the objectively existent secondary anisotropy, enhancing the accuracy of numerical simulations for tunnels, particularly for deep tunnels. Full article

The incorporation of waste polyethylene terephthalate (PET) as a modifier for asphalt presents a promising approach to addressing the environmental pollution associated with waste plastics while simultaneously extending the service life of road surfaces. This study investigates the fundamental physical properties and rheological properties of asphalt modified with waste PET at both high and low temperatures. Utilizing the theory of fractional derivatives, performance evaluation indicators, such as the deformation factor and viscoelasticity factor, have been developed for the assessment of waste PET-modified asphalt. The underlying mechanism of this modification was examined through scanning electron microscopy and Fourier transform infrared spectroscopy. The results indicate that the addition of waste PET enhances the high-temperature stability of the base asphalt but reduces its resistance to cracking at low temperatures. The fractional derivative model effectively describes the dynamic shear rheological properties of waste PET-modified asphalt, achieving a maximum correlation coefficient of 0.99991. Considering the performance of modified asphalt at both high and low temperatures, the optimal concentration of waste PET was determined to be 6%. At this concentration, the minimum creep stiffness of the PET-modified asphalt was approximately 155 MPa at −6 °C. Additionally, the rutting factor of the waste PET-modified asphalt achieved a maximum value of 527.12 KPa at 52 °C. The interaction between waste PET and base asphalt was primarily physical, with mutual adsorption leading to the formation of a spatial network structure that enhanced the deformation resistance of the asphalt. This study provides a theoretical foundation and technical support for the engineering application of waste PET as a modifier in asphalt. Full article

Timely and accurate identification of surface damage in hydraulic structures is essential for maintaining structural integrity and ensuring operational safety. Traditional manual inspections are time-consuming, labor-intensive, and prone to subjectivity, especially for large-scale or inaccessible infrastructure. Leveraging advancements in aerial imaging, unmanned aerial vehicles (UAVs) enable efficient acquisition of high-resolution visual data across expansive hydraulic environments. However, existing deep learning (DL) models often lack architectural adaptations for the visual complexities of UAV imagery, including low-texture contrast, noise interference, and irregular crack patterns. To address these challenges, this study proposes a lightweight, robust, and high-precision segmentation framework, called LFPA-EAM-Fast-SCNN, specifically designed for pixel-level damage detection in UAV-captured images of hydraulic concrete surfaces. The developed DL-based model integrates an enhanced Fast-SCNN backbone for efficient feature extraction, a Lightweight Feature Pyramid Attention (LFPA) module for multi-scale context enhancement, and an Edge Attention Module (EAM) for refined boundary localization. The experimental results on a custom UAV-based dataset show that the proposed damage detection method achieves superior performance, with a precision of 0.949, a recall of 0.892, an F1 score of 0.906, and an IoU of 87.92%, outperforming U-Net, Attention U-Net, SegNet, DeepLab v3+, I-ST-UNet, and SegFormer. Additionally, it reaches a real-time inference speed of 56.31 FPS, significantly surpassing other models. The experimental results demonstrate the proposed framework’s strong generalization capability and robustness under varying noise levels and damage scenarios, underscoring its suitability for scalable, automated surface damage assessment in UAV-based remote sensing of civil infrastructure. Full article

This article provides a comprehensive overview of recent studies concerning laser heat treatment (LHT) of structural and tool steels, with particular attention to the 21NiCrMo2 steel used for carburized gear wheels. Analysis includes the influence of critical laser processing conditions—including power output, motion speed, spot size, and focusing distance—on surface microhardness, hardening depth, and microstructure development. The findings indicate that the energy density is the dominant factor that affects the outcomes of LHT. Optimal results, in the form of a high surface microhardness and a sufficient depth of hardening, were achieved within the energy density range of 80–130 J/mm², allowing for martensitic transformation while avoiding defects such as melting or cracking. At densities below 50 J/mm², incomplete hardening occurred with minimal microhardness improvement. On the contrary, densities exceeding 150–180 J/mm² caused surface overheating and degradation. For carburized 21NiCrMo2 steel, the most effective parameters included 450–1050 W laser power, 1.7–2.5 mm/s scanning speed, and 2.0–2.3 mm beam diameter. The review confirms that process control through energy-based parameters allows for reliable prediction and optimization of LHT for industrial applications, particularly in components exposed to cyclic loads. Full article

Difficult, extreme operating conditions of parabolic antennas under precipitation and sub-zero temperatures require the creation of effective heating systems. The purpose of the research is to develop a multilayer coating containing two metal-ceramic layers, epoxy composite layers, carbon fabric, and an outer layer of basalt fabric, which allows for effective heating of the antenna, and to study the properties of this coating. The multilayer coating was formed on an aluminum base that was subjected to abrasive jet processing. The first and second metal-ceramic layers, Al₂O₃ + 5% Al, which were applied by high-speed multi-chamber cumulative detonation spraying (CDS), respectively, provide maximum adhesion strength to the aluminum base and high adhesion strength to the third layer of the epoxy composite containing Al₂O₃. On this not-yet-polymerized layer of epoxy composite containing Al₂O₃, a layer of carbon fabric (impregnated with epoxy resin) was formed, which serves as a resistive heating element. On top of this carbon fabric, a layer of epoxy composite containing Cr₂O₃ and SiO₂ was applied. Next, basalt fabric was applied to this still-not-yet-polymerized layer. Then, the resulting layered coating was compacted and dried. To study this multilayer coating, X-ray analysis, light and raster scanning microscopy, and transmission electron microscopy were used. The thickness of the coating layers and microhardness were measured on transverse microsections. The adhesion strength of the metal-ceramic coating layers to the aluminum base was determined by both bending testing and peeling using the adhesive method. It was established that CDS provides the formation of metal-ceramic layers with a maximum fraction of lamellae and a microhardness of 7900–10,520 MPa. In these metal-ceramic layers, a dispersed subgrain structure, a uniform distribution of nanoparticles, and a gradient-free level of dislocation density are observed. Such a structure prevents the formation of local concentrators of internal stresses, thereby increasing the level of dispersion and substructural strengthening of the metal-ceramic layers’ material. The formation of materials with a nanostructure increases their strength and crack resistance. The effectiveness of using aluminum, chromium, and silicon oxides as nanofillers in epoxy composite layers was demonstrated. The presence of structures near the surface of these nanofillers, which differ from the properties of the epoxy matrix in the coating, was established. Such zones, specifically the outer surface layers (OSL), significantly affect the properties of the epoxy composite. The results of industrial tests showed the high performance of the multilayer coating during antenna heating. Full article

Enhancing osseointegration is a common goal for many titanium implant coatings, since the naturally forming oxides are often bioinert and exhibit less than ideal bone-to-implant contact. Oxide coating surface topographies, chemistries, and crystallinities are known to play key roles in enhancing bone–implant interactions. In the present study, two novel anodization processes were developed in electrolytes based on juiced navel oranges to create bioactive oxide coatings on commercially pure titanium (CPTi) surfaces. Both oxide groups revealed multi-scaled micro and nano surface topographies, significant Ca and P-dopant incorporation exhibiting Ca/P ratios similar to human bone (1.7 and 1.8), and physiologically relevant Mg uptake levels of <0.1% and 1.4 at%. XRD and FTIR analyses of each oxide revealed a combination of tricalcium phosphate and hydroxyapatite phases that showed carbonate substitutions indicative of bone-like apatite formation. Finally, VDI indentation testing revealed good adhesion strengths, minimal cracking, and no visible delamination for both oxides. In summary, the anodization processes in the present study were shown to produce carbonated tricalcium phosphate and apatite containing oxides with contrasting levels of Mg uptake that show much promise to improve future implant clinical outcomes. Full article

The article presents a new AM (Additive Manufacturing) process development, necessary to repair parts made from Aluminum 6061 material, with T6 treatment. The laser Directed Energy Deposition (DED) and Extreme High-Speed Directed Energy Deposition (EHLA) capabilities are evaluated for repairing Al large components. To optimize the process parameters, single-track depositions were analyzed for both laser-powder DED (feed rate of 2 m/min) and EHLA (feed rate 20 m/min) for AlSi10Mg and Al6061 powders. The cross-sections of single tracks revealed the bonding characteristics and provided laser-powder DED, a suitable parameter selection for the repair. Three damage types were identified on the Al component to define the specification of the repair process and to highlight the capabilities of laser-powder DED and EHLA in repairing intricate surface scratches and dents. Our research is based on variation of the powder mass flow and beam power, studying the influence of these parameters on the weld bead geometry and bonding quality. The evaluation criteria include bonding defects, crack formation, porosity, and dilution zone depth. The bidirectional path planning strategy was applied with a fly-in and fly-out path for the hatching adjustment and acceleration distance. Samples were etched for a qualitative microstructure analysis, and the HV hardness was tested. The novelty of the paper is the new process parameters for laser-powder DED and EHLA deposition strategies to repair large Al components (6061 T6), using AlSi10Mg and Al6061 powder. Our experimental research tested the defect-free deposition and the compatibility of AlSi10Mg on the Al6061 substrate. The readers could replicate the method presented in this article to repair by laser-powder DED/EHLA large Al parts and avoid the replacement of Al components with new ones. Full article

Wireless sensor networks (WSNs) are used for data acquisition and transmission in unmanned surface vessels (USVs). However, the openness of wireless networks makes USVs highly susceptible to false data injection (FDI) attacks during data transmission, which affects the sensors’ ability to receive real data and leads to decision-making errors in the control center. In this paper, a novel dynamic data encryption method is proposed whereby data are encrypted prior to transmission and the key is dynamically updated using historical system data, with a view to increasing the difficulty for attackers to crack the ciphertext. At the same time, a dynamic relationship is established among ciphertext, key, and auxiliary encrypted ciphertext, and an attack detection scheme based on dynamic encryption is designed to realize instant detection and localization of FDI attacks. Further, an $H_{\infty }$ fusion filter is designed to filter external interference noise, and the real information is estimated or restored by the weighted fusion algorithm. Ultimately, the validity of the proposed scheme is confirmed through simulation experiments. Full article

This study proposes a laser texturing method to optimize adhesion and minimize residual stresses in CVD diamond films deposited on tungsten carbide (WC-Co). WC-5.8 wt% Co substrates were textured with quadrangular pyramidal patterns (35 µm) using a 1064 nm nanosecond-pulsed laser, followed by chemical treatment (Murakami’s solution + aqua regia) to remove surface cobalt. Diamond films were grown via HFCVD and characterized by Raman spectroscopy, EDS, and Rockwell indentation. The results demonstrate that pyramidal texturing increased the surface area by a factor of 58, promoting effective mechanical interlocking and reducing compressive stresses to −1.4 GPa. Indentation tests revealed suppression of interfacial cracks, with propagation paths deflected toward textured regions. The pyramidal geometry exhibited superior cutting post-deposition cooling time for stress relief from 3 to 1 h. These findings highlight the potential of laser texturing for high-performance machining tool applications. Full article