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Search Results (5,357)

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22 pages, 6974 KB  
Article
An Experimental Evaluation of Steel Beam-HSST/CFSST Column Connection with Varying Joint Configurations
by Zongmin Zhang, Lanhua Chen, Ling Cai, Yanchun Li and Zaharah Mohd Yusoff
Buildings 2025, 15(20), 3774; https://doi.org/10.3390/buildings15203774 (registering DOI) - 19 Oct 2025
Abstract
Sixteen beam–column joints with different column types and connection configurations were designed and tested to identify suitable joints for low-rise prefabricated square steel tube (SST) columns and H-beams. The columns included hollow square steel tube (HSST) and concrete-filled square steel tube (CFSST) types, [...] Read more.
Sixteen beam–column joints with different column types and connection configurations were designed and tested to identify suitable joints for low-rise prefabricated square steel tube (SST) columns and H-beams. The columns included hollow square steel tube (HSST) and concrete-filled square steel tube (CFSST) types, while the joints consisted of welded, end plate, flange-connected, and angle connector plate configurations. Cyclic loading tests were conducted to examine failure modes, hysteresis and skeleton curves, stiffness degradation, and cumulative energy dissipation. The results showed that joints with angle connector plates outperformed welded, end-plate, and flange-connected joints. The height of the triangular stiffener was found to be a critical factor, with a 144 mm stiffener increasing the ultimate bending moment by 78.65% for CFSST and 79.3% for HSST columns, along with notable improvements in stiffness and energy dissipation. Based on Eurocode 3, angle connector plate joints with high stiffeners were classified as semi-rigid and full-strength. A combined assessment of mechanical behavior and economic efficiency indicated that this joint type provides the highest cost-effectiveness and significant application potential. Full article
(This article belongs to the Section Building Structures)
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26 pages, 3460 KB  
Article
Classification and Clustering of Fiber Break Events in Thermoset CFRP Using Acoustic Emission and Machine Learning
by Richard Dela Amevorku, David Amoateng-Mensah, Manoj Rijal and Mannur J. Sundaresan
Sensors 2025, 25(20), 6466; https://doi.org/10.3390/s25206466 (registering DOI) - 19 Oct 2025
Abstract
Carbon Fiber-Reinforced Polymer (CFRP) composites, widely used across industries, exhibit various damage mechanisms depending on the loading conditions applied. This study employs a structural health monitoring (SHM) approach to investigate the three primary failure modes, fiber breakage, matrix cracking, and delamination, in thermoset [...] Read more.
Carbon Fiber-Reinforced Polymer (CFRP) composites, widely used across industries, exhibit various damage mechanisms depending on the loading conditions applied. This study employs a structural health monitoring (SHM) approach to investigate the three primary failure modes, fiber breakage, matrix cracking, and delamination, in thermoset quasi-isotropic CFRPs subjected to quasi-static tensile loading until failure. Acoustic emission (AE) signals acquired from an experiment were leveraged to analyze and classify these real-time signals into the failure modes using machine learning (ML) techniques. Due to the extensive number of AE signals recorded during testing, manually classifying these failure mechanisms through waveform inspection was impractical. ML, alongside ensemble learning, algorithms were implemented to streamline the classification, making it more efficient, accurate, and reliable. Conventional AE parameters from the data acquisition system and feature extraction techniques applied to the recorded waveforms were implemented exclusively as classification features to investigate their reliability and accuracy in classifying failure modes in CFRPs. The classification models exhibited up to 99% accuracy, as depicted by evaluation metrics. Further studies, using cross-correlation techniques, ascertained the presence of fiber break events occurring in the bundles as the thermoset CFRP composite approached failure. These findings highlight the significance of integrating machine learning into SHM for the early detection of real-time damage and effective monitoring of residual life in composite materials. Full article
(This article belongs to the Special Issue Sensing and Machine Learning Control: Progress and Applications)
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14 pages, 870 KB  
Article
A Matrix-Based Analytical Approach for Reliability Assessment of Mesh Distribution Networks
by Shuitian Li, Lixiang Lin, Ya Chen, Chang Xu, Chenxi Zhang, Yuanliang Zhang, Fengzhang Luo and Jiacheng Fo
Energies 2025, 18(20), 5508; https://doi.org/10.3390/en18205508 (registering DOI) - 18 Oct 2025
Abstract
To address the limitations of conventional reliability assessment methods in handling mesh distribution networks with flexible operation characteristics and complex topologies, namely their poor adaptability and low computational efficiency, this paper proposes a matrix-based analytical approach for reliability assessment of mesh distribution networks. [...] Read more.
To address the limitations of conventional reliability assessment methods in handling mesh distribution networks with flexible operation characteristics and complex topologies, namely their poor adaptability and low computational efficiency, this paper proposes a matrix-based analytical approach for reliability assessment of mesh distribution networks. First, a network configuration centered on the soft open points (SOP) is established. Through multi-feeder interconnection and flexible power flow control, a topology capable of fast fault transfer and service restoration is formed. Second, based on the restoration modes of load nodes under fault scenarios, three types of fault incidence matrices (FIM) are proposed. By means of matrix algebra, explicit analytical expressions are derived for the relationships among equipment failure probability, duration, impact range, and reliability indices. This overcomes the drawbacks of iterative search in conventional reliability assessments, significantly improving efficiency while ensuring accuracy. Finally, a modified 44 bus Taiwan test system is used for reliability assessment to verify the effectiveness of the proposed method. The results demonstrate that the proposed matrix-based analytical reliability assessment method enables explicit analytical calculation of both system-level and load-level reliability indices in mesh distribution networks, providing effective support for planning and operational optimization to enhance reliability. Full article
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17 pages, 770 KB  
Article
Eccentric Quasi-Isometric Exercise Produces Greater Impulse with Less Pain than Isokinetic Heavy–Slow Resistance Exercise in Ankle Plantar Flexors: Quasi-Randomized Controlled Trial
by Luka Križaj, Žiga Kozinc and Nejc Šarabon
Appl. Sci. 2025, 15(20), 11177; https://doi.org/10.3390/app152011177 (registering DOI) - 18 Oct 2025
Abstract
Recently, there has been growing interest in optimizing exercise protocols in sports training and rehabilitation, with particular attention to eccentric quasi-isometric (EQI) contractions, which involve maintaining joint position until isometric failure and then resisting the subsequent eccentric phase. Evidence directly comparing EQI with [...] Read more.
Recently, there has been growing interest in optimizing exercise protocols in sports training and rehabilitation, with particular attention to eccentric quasi-isometric (EQI) contractions, which involve maintaining joint position until isometric failure and then resisting the subsequent eccentric phase. Evidence directly comparing EQI with other contraction modes remains scarce. This quasi-randomized controlled trial examined the short-term effects of EQI versus isokinetic heavy–slow resistance (IHSR) exercises on ankle plantar flexors, focusing on pain, range of motion (RoM), and strength performance. Thirty-two physically active participants were allocated to EQI (n = 16) or IHSR (n = 16) groups and assessed at baseline, immediately post-exercise, and 24 and 48 h later. Both groups performed three exercise sets with 3 min breaks. The protocols were designed to approximate matched loading, based on preliminary testing. Nevertheless, the EQI group achieved a significantly greater total impulse (p = 0.028), a shorter time under tension (p = 0.001), and lower effort scores (p < 0.001). Group × time analysis revealed less decline in maximal voluntary isometric contraction torque (p = 0.002; η2 = 0.16), as well as lower general (p < 0.001; η2 = 0.32) and activity-related pain (p < 0.001; η2 = 0.32) in the EQI group, with no significant differences in dorsiflexion RoM (p = 0.893). In conclusion, EQI produced a higher torque impulse while inducing less fatigue and post-exercise pain than IHSR, suggesting it may be a more efficient loading strategy for the ankle plantar flexors. The results contribute to the understanding of contraction-specific efficiency, and may inform the design of future training and rehabilitation protocols targeting the ankle plantar flexors. Full article
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30 pages, 1708 KB  
Article
BSEMD-Transformer: A New Framework for Rolling Element Bearing Diagnosis in Electrical Machines Based on Classification of Time–Frequency Features
by Lotfi Chaouech, Jaouher Ben Ali, Tarek Berghout, Eric Bechhoefer and Abdelkader Chaari
Machines 2025, 13(10), 961; https://doi.org/10.3390/machines13100961 - 17 Oct 2025
Abstract
Rolling Element Bearing (REB) failures represent a critical challenge in rotating machinery maintenance, accounting for approximately 45% of industrial breakdowns. Considering the variable operating conditions of speeds and loads, vibration fault signatures are generally masked by noises. Consequently, traditional diagnostic methods relying on [...] Read more.
Rolling Element Bearing (REB) failures represent a critical challenge in rotating machinery maintenance, accounting for approximately 45% of industrial breakdowns. Considering the variable operating conditions of speeds and loads, vibration fault signatures are generally masked by noises. Consequently, traditional diagnostic methods relying on time and frequency analysis or conventional machine learning often fail to capture the nonlinear interactions and phase coupling characteristics essential for accurate fault detection, particularly in noisy industrial environments. In this study, we propose a framework that synergistically combines (1) Empirical Mode Decomposition (EMD) for adaptive handling of non-stationary vibration signals, (2) bispectrum analysis to extract phase-coupled features while inherently suppressing Gaussian noise, and (3) Time-Series Transformer with attention mechanisms to automatically weight discriminative feature interactions. Experimental results based on five different benchmarks show that the proposed BSEMD-Transformer framework is a powerful tool for REB diagnosis, reaching a classification accuracy of at least 98.2% for all tests regardless of the used dataset. The proposed approach is judged to be consistent, robust, and accurate even under variable conditions of speed and loads. Full article
(This article belongs to the Section Machines Testing and Maintenance)
28 pages, 8077 KB  
Article
Shear Behavior of Dowel–Stud Hybrid Connectors for HSS-HPC Composite Structures: Geometry Optimization and Material Synergistic Effects
by Bozhao Chen, Jun Chen, Yansong Gao, Miao Zhang and Zhang Li
Buildings 2025, 15(20), 3748; https://doi.org/10.3390/buildings15203748 - 17 Oct 2025
Abstract
The growing adoption of steel–concrete composite beams has spurred extensive use of high-strength steel (HSS) and high-performance concrete (HPC) in composite structures, capitalizing on their superior mechanical properties. To address the limited shear capacity of conventional stud connectors and unitary steel dowels, this [...] Read more.
The growing adoption of steel–concrete composite beams has spurred extensive use of high-strength steel (HSS) and high-performance concrete (HPC) in composite structures, capitalizing on their superior mechanical properties. To address the limited shear capacity of conventional stud connectors and unitary steel dowels, this study proposed a dowel–stud hybrid connector for advanced composite systems. Push-out tests were conducted on one conventional shear stud specimen, one monolithic steel dowel specimen, and four dowel–stud hybrid connector specimens. Experimental and finite element analyses were employed to evaluate the effects of the stud length, diameter, and layout on the failure modes and shear performance of composite connectors. The findings demonstrated that the hybrid connectors exhibited significantly enhanced shear capacity and ductility compared to those of both conventional stud connectors and monolithic steel dowels. Failure primarily occurred at the roots of the steel dowels and shear studs, with the underlying concrete exhibiting crushing failure. Increasing the diameter from 6 mm to 22 mm marginally influenced the ultimate shear capacity (the variation was <4%) but notably improved the initial stiffness. For composite connectors with 13 mm diameter studs, increasing the stud length from 40 mm to 80 mm and 120 mm raised the ultimate capacity by 4.7% and 8.8%, respectively. Conversely, for composite connectors with 16 mm diameter studs, length variations exerted negligible influence (<4%) on the ultimate capacity. In addition, the study layout critically influenced the performance. At a fixed 16 mm diameter, relocating studs from the dowel center to the sub-root region increased the shear capacity by 23%. Full article
(This article belongs to the Section Building Structures)
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17 pages, 5543 KB  
Article
TASNet-YOLO: An Identification and Classification Model for Surface Defects of Rough Planed Bamboo Strips
by Yitong Zhang, Rui Gao, Min Ji, Wei Zhang, Wenquan Yu and Xiangfeng Wang
Forests 2025, 16(10), 1595; https://doi.org/10.3390/f16101595 - 17 Oct 2025
Abstract
After rough planing, defects such as wormholes and small patches of green bark residue and decay are often overlooked and misclassified. Strip-like defects, including splinters and chipped edges, are easily confused with the natural bamboo grain, and a single elongated defect is frequently [...] Read more.
After rough planing, defects such as wormholes and small patches of green bark residue and decay are often overlooked and misclassified. Strip-like defects, including splinters and chipped edges, are easily confused with the natural bamboo grain, and a single elongated defect is frequently fragmented into multiple detection boxes. This study proposes a modified TASNet-YOLO model, an improved detector built on YOLO11n. Unlike prior YOLO-based bamboo defect detectors, TASNet-YOLO is a mechanism-guided redesign that jointly targets two persistent failure modes—limited visibility of small, low-contrast defects and fragmentation of elongated defects—while remaining feasible for real-time production settings. In the backbone, a newly designed TriMAD_Conv module is introduced as the core unit, enhancing the detection of wormholes as well as small-area defects such as green bark residue and decay. The additive-gated C3k2_AddCGLU is further integrated at selected C3k2 stages. The combination of additive interaction and CGLU improves channel selection and detail retention, highlighting differences between splinters and chipped edges and bamboo grain strips, thereby reducing false positives and improving precision. In the neck, the neck replaces nearest-neighbor upsampling and CBS with SNI-GSNeck to improve cross-scale alignment and fusion. Under an acceptable real-time budget, predictions for splinters and chipped edges become more contiguous and better aligned to edges, while wormholes predictions are more circular and less noisy. Experiments on our in-house dataset (8445 bamboo-strip defect images) show that, compared with YOLO11n, the proposed model improves detection accuracy by 5.1%, achieves 106.4 FPS, and reduces computational costs by 0.4 GFLOPs per forward pass. These properties meet the throughput demand of 2 m/s conveyor lines, and the compact model size and compute footprint make edge deployment straightforward for fast online screening and preliminary quality grading in industrial production. Full article
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16 pages, 472 KB  
Article
Integrating the I–S Model and FMEA for Process Optimization in Packaging and Printing Industry
by Shun-Hsing Chen and Huay-In Yan
Processes 2025, 13(10), 3323; https://doi.org/10.3390/pr13103323 - 16 Oct 2025
Viewed by 302
Abstract
This study investigates the determinants of service demand in the packaging and printing industry, identifying 19 key factors through expert evaluation. These factors were analyzed using the Importance–Satisfaction (I–S) Model to pinpoint areas requiring enhancement, with four elements classified within the improvement zone. [...] Read more.
This study investigates the determinants of service demand in the packaging and printing industry, identifying 19 key factors through expert evaluation. These factors were analyzed using the Importance–Satisfaction (I–S) Model to pinpoint areas requiring enhancement, with four elements classified within the improvement zone. Considering resource constraints, improvement priorities were established through a modified Risk Priority Number (RPN) framework derived from Failure Modes and Effects Analysis (FMEA), expressed as RPN = I × F × E. The highest-priority areas for improvement included product pricing, flexibility in meeting customer requirements, suppliers’ emergency response capabilities, and proactive communication regarding raw material price fluctuations. The findings indicate that consumers balance price against sustainability value, highlighting the necessity of setting prices that align with perceived value to sustain trust and meet expectations. Strengthening firms’ emergency response mechanisms and developing an online standard operating procedure (SOP) notification system for raw material price changes can enhance communication efficiency, increase transparency in pricing, and ultimately improve organizational competitiveness. Full article
(This article belongs to the Section Manufacturing Processes and Systems)
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21 pages, 2249 KB  
Article
The Risk Assessment for Water Conveyance Channels in the Yangtze-to-Huaihe Water Diversion Project (Henan Reach)
by Huan Jing, Yanjun Wang, Yongqiang Wang, Jijun Xu and Mingzhi Yang
Water 2025, 17(20), 2992; https://doi.org/10.3390/w17202992 - 16 Oct 2025
Viewed by 94
Abstract
Water conveyance channels, as critical components of water diversion projects, feature numerous structures, complex configurations, and intensive operational management requirements, making them vulnerable to multiple risks, such as extreme flooding, channel blockage, structural failures, and management deficiencies. To ensure an accurate assessment of [...] Read more.
Water conveyance channels, as critical components of water diversion projects, feature numerous structures, complex configurations, and intensive operational management requirements, making them vulnerable to multiple risks, such as extreme flooding, channel blockage, structural failures, and management deficiencies. To ensure an accurate assessment of the operational safety risk, this study proposes a comprehensive risk assessment framework that integrates risk probability and risk loss. The former is quantified using the Consequence Reverse Diffusion Method (CRDM), which systematically identifies and categorizes key factors of primary dike failure modes into four domains: hydrological characteristics, channel morphology, engineering structures, and operational management. The latter is assessed by integrating socioeconomic impacts, including population exposure, infrastructure investment, and industrial and agricultural production. A structured assessment framework is established through systematic indicator selection, justified weight assignment, and standardized scoring criteria. Application of the framework to Yangtze-to-Huaihe Water Diversion Project (Henan Reach) reveals that the risk probability across four segments falls within the (1, 3) range, indicating a generally low to moderate risk profile, while channel morphology shows greater spatial variability than hydrological, structural, and management indicators, driven by local differences in crossing structure density, sinuosity, and regime coefficients. Meanwhile, the segments along the Qingshui River face higher risk losses owing to their upstream location and large-scale water supply capacity, resulting in a relatively higher comprehensive risk level. Full article
(This article belongs to the Section Water Resources Management, Policy and Governance)
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15 pages, 3602 KB  
Article
Fatigue Endurance of Continuous Fiber-Reinforced Polymer Matrix Composites Manufactured by 3D Printing
by Jorge Guillermo Díaz-Rodríguez, Alberto David Pertuz-Comas and Oscar Rodolfo Bohorquez-Becerra
Eng 2025, 6(10), 277; https://doi.org/10.3390/eng6100277 - 16 Oct 2025
Viewed by 149
Abstract
The article presents the results of uniaxial fatigue tests for the high-cycle regime on a polymer matrix composite material reinforced with Kevlar and carbon fibers, fabricated with material extrusion (MEX) technology. The samples were manufactured according to the ASTM D638 type-I standard, and [...] Read more.
The article presents the results of uniaxial fatigue tests for the high-cycle regime on a polymer matrix composite material reinforced with Kevlar and carbon fibers, fabricated with material extrusion (MEX) technology. The samples were manufactured according to the ASTM D638 type-I standard, and the tests were performed under a load inversion factor of 0.1 at room temperature, measuring the number of cycles to failure. Based on previous results, in which different configurations were tested, tests were carried out on specimens subjected to loads ranging from 40% to 91% of the rupture stress for Kevlar and 25.5% to 80.7% for carbon, obtaining a maximum life of 2.5 M cycles for Kevlar and 4.06 M cycles for carbon. The observed failure modes included fiber tearing, matrix cracking, and fiber–matrix pull-out. Full article
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14 pages, 3840 KB  
Article
Building Polyacryronitrile Fiber/Epoxy Resin (PANER) Interleaving Film to Strengthen Flexural and Compressive Performances of Laminated CFRP Composites
by Sidra Ashfaq, Jiaxin He, Yanan Lyu, Fei Cheng, Xiang Yuan, Xueling Liang, Shuying Shi, Evgeny Lomakin, Daria Bondarchuk, Rasuljon Tojiyev, Hao Liu, Xiaozhi Hu and Xi Chen
Nanomaterials 2025, 15(20), 1576; https://doi.org/10.3390/nano15201576 - 16 Oct 2025
Viewed by 177
Abstract
Carbon fiber-reinforced polymer (CFRP) composites have excellent mechanical properties, but their performance is hampered by delamination caused by weak interfacial bonding and resin-rich region (RRR). This research has proposed an interleaving film to improve interlaminar structure and mechanical properties by adding polyacrylonitrile (PAN) [...] Read more.
Carbon fiber-reinforced polymer (CFRP) composites have excellent mechanical properties, but their performance is hampered by delamination caused by weak interfacial bonding and resin-rich region (RRR). This research has proposed an interleaving film to improve interlaminar structure and mechanical properties by adding polyacrylonitrile (PAN) fiber into the epoxy interlayer of the CFRP laminates. The PAN fiber/epoxy resin (PANER) interleaving film could be prepared, which was beneficial to hinder crack initiation paths and improve the load transfer. Flexural and compression performance testing results showed optimum performance was obtained when 2 wt.% PAN fiber was added, and an increment of 28.6% was obtained in the flexural strength and 11.7% increment in compressive strength. The damaged energy absorption was improved up to 21.4% and 11.3% for the flexural and compressive properties, respectively. The overall thickness increments in the interlayer with PANER interleaving film were approximately 4–9 μm. X-Ray micro-computed tomography and scanning electron microscopy observations exhibited the potential of PAN fiber in the reduction of RRR, resulting in modes replacement from delamination-dominant failure to crossing-multi-layer failure. In all, PANER interleaving film at the interlayer has been confirmed to be an effective approach to produce a simple reinforcement technology for FRP laminates. Full article
(This article belongs to the Section Nanocomposite Materials)
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17 pages, 14176 KB  
Article
Mechanical Performance of Plywood TIE Joints Under Tension and Shear in the WikiHouse Skylark Modular System
by Moisés Sandoval, Juan Pablo Cárdenas-Ramírez, Paula Soto-Zúñiga, Michael Arnett, Angelo Oñate, Jorge Leiva, Rodrigo Cancino and Víctor Tuninetti
Materials 2025, 18(20), 4738; https://doi.org/10.3390/ma18204738 - 16 Oct 2025
Viewed by 168
Abstract
The construction sector’s environmental footprint is driving the adoption of sustainable modular timber systems. The WikiHouse Skylark is a promising open-source model whose structural reliability depends on the performance of its critical plywood TIE joints. This study presents an experimental investigation of full-scale [...] Read more.
The construction sector’s environmental footprint is driving the adoption of sustainable modular timber systems. The WikiHouse Skylark is a promising open-source model whose structural reliability depends on the performance of its critical plywood TIE joints. This study presents an experimental investigation of full-scale TIE joints fabricated from 18 mm Pinus radiata plywood in three variants: Standard (STD), Weather-Resistant (HR), and Fire-Resistant (FR). Monotonic tensile and shear tests were conducted to evaluate load–displacement behavior and failure modes. While the mean ultimate strengths varied between panel types, with HR highest in tension (7.7 kN) and FR highest in shear (8.2 kN), the most critical finding was the effect of the treatments on failure mode. The FR treatment induced a brittle fracture with significantly reduced ductility, in contrast to the more ductile tearing observed in STD and HR panels. This highlights a clear strength–ductility trade-off introduced by the fire-retardant treatment, a key consideration for structural design in modular timber construction. This dataset provides an essential empirical foundation for the numerical modeling and design guidelines of WikiHouse TIE joints, advancing the development of resilient and sustainable prefabricated housing. Full article
(This article belongs to the Section Mechanics of Materials)
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27 pages, 5651 KB  
Article
Integrating VMD and Adversarial MLP for Robust Acoustic Detection of Bolt Loosening in Transmission Towers
by Yong Qin, Yu Zhou, Cen Cao, Jun Hu and Liang Yuan
Electronics 2025, 14(20), 4062; https://doi.org/10.3390/electronics14204062 - 15 Oct 2025
Viewed by 131
Abstract
The structural integrity of transmission towers, as the backbone of power grids, is critical to overall grid safety, relying heavily on the reliability of bolted connections. Dynamic loads such as wind-induced vibrations can cause bolt loosening, potentially leading to structural deformation, cascading failures, [...] Read more.
The structural integrity of transmission towers, as the backbone of power grids, is critical to overall grid safety, relying heavily on the reliability of bolted connections. Dynamic loads such as wind-induced vibrations can cause bolt loosening, potentially leading to structural deformation, cascading failures, and large-scale blackouts. Traditional manual inspection methods are inefficient, subjective, and hazardous. Existing automated approaches are often limited by environmental noise sensitivity, high computational complexity, sensor placement dependency, or the need for extensive labeled data. To address these challenges, this paper proposes a portable acoustic detection system based on Variational Mode Decomposition (VMD) and an Adversarial Multilayer Perceptual Network (AT-MLP). The VMD method effectively processes non-stationary and nonlinear acoustic signals to suppress noise and extract robust time–frequency features. The AT-MLP model then performs state identification, incorporating adversarial training to mitigate distribution discrepancies between training and testing data, thereby significantly improving generalization and noise robustness. Comparison results and analysis demonstrate that the proposed VMD and AT-MLP framework effectively mitigates structural variability and environmental interference, providing a reliable solution for bolt loosening detection. The proposed method bridges structural mechanics, acoustic signal processing, and lightweight intelligence, offering a scalable solution for condition assessment and risk-aware maintenance of transmission towers. Full article
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30 pages, 8790 KB  
Article
An Adaptive Framework for Remaining Useful Life Prediction Integrating Attention Mechanism and Deep Reinforcement Learning
by Yanhui Bai, Jiajia Du, Honghui Li, Xintao Bao, Linjun Li, Chun Zhang, Jiahe Yan, Renliang Wang and Yi Xu
Sensors 2025, 25(20), 6354; https://doi.org/10.3390/s25206354 - 14 Oct 2025
Viewed by 540
Abstract
The prediction of Remaining Useful Life (RUL) constitutes a vital aspect of Prognostics and Health Management (PHM), providing capabilities for the assessment of mechanical component health status and prediction of failure instances. Recent studies on feature extraction, time-series modeling, and multi-task learning have [...] Read more.
The prediction of Remaining Useful Life (RUL) constitutes a vital aspect of Prognostics and Health Management (PHM), providing capabilities for the assessment of mechanical component health status and prediction of failure instances. Recent studies on feature extraction, time-series modeling, and multi-task learning have shown remarkable advancements. However, most deep learning (DL) techniques predominantly focus on unimodal data or static feature extraction techniques, resulting in a lack of RUL prediction methods that can effectively capture the individual differences among heterogeneous sensors and failure modes under complex operational conditions. To overcome these limitations, an adaptive RUL prediction framework named ADAPT-RULNet is proposed for mechanical components, integrating the feature extraction capabilities of attention-enhanced deep learning (DL) and the decision-making abilities of deep reinforcement learning (DRL) to achieve end-to-end optimization from raw data to accurate RUL prediction. Initially, Functional Alignment Resampling (FAR) is employed to generate high-quality functional signals; then, attention-enhanced Dynamic Time Warping (DTW) is leveraged to obtain individual degradation stages. Subsequently, an attention-enhanced of hybrid multi-scale RUL prediction network is constructed to extract both local and global features from multi-format data. Furthermore, the network achieves optimal feature representation by adaptively fusing multi-source features through Bayesian methods. Finally, we innovatively introduce a Deep Deterministic Policy Gradient (DDPG) strategy from DRL to adaptively optimize key parameters in the construction of individual degradation stages and achieve a global balance between model complexity and prediction accuracy. The proposed model was evaluated on aircraft engines and railway freight car wheels. The results indicate that it achieves a lower average Root Mean Square Error (RMSE) and higher accuracy in comparison with current approaches. Moreover, the method shows strong potential for improving prediction accuracy and robustness in varied industrial applications. Full article
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23 pages, 9717 KB  
Article
Effect of Laser Pulse Width on Cutting Quality and Efficiency in CFRP: Mechanism and Optimization
by Chunmeng Chen, Long Chen, Guojun Zhang, Yu Huang, Huijuan Ma and Youmin Rong
Materials 2025, 18(20), 4707; https://doi.org/10.3390/ma18204707 - 14 Oct 2025
Viewed by 239
Abstract
This study systematically investigates the influence of laser pulse duration on cutting efficiency, heat-affected-zone (HAZ) formation, and mechanical integrity during carbon fiber-reinforced polymer (CFRP) laser cutting. Three distinct pulse-width lasers—picosecond, nanosecond, and quasi-continuous-wave (QCW)—are compared. Results show that pulse duration governs material removal [...] Read more.
This study systematically investigates the influence of laser pulse duration on cutting efficiency, heat-affected-zone (HAZ) formation, and mechanical integrity during carbon fiber-reinforced polymer (CFRP) laser cutting. Three distinct pulse-width lasers—picosecond, nanosecond, and quasi-continuous-wave (QCW)—are compared. Results show that pulse duration governs material removal mechanisms and HAZ extent: the nanosecond laser achieves the smallest HAZ and minimal porosity; the picosecond laser exhibits limited thermal accumulation due to low average power; and the QCW laser induces the largest HAZ (11.6 times that of the nanosecond laser) and significant porosity. Cutting efficiency scales inversely with pulse width, with single-hole processing times of 480.4 s for picosecond-laser cutting, 76.8 s for nanosecond-laser cutting, and 4.028 s for QCW-laser cutting, reflecting a transition from thermal ablation to mechanical spallation. Mechanical testing reveals that while tensile and flexural strengths vary by less than 5% across laser types, damage morphology and failure modes differ significantly. In situ digital image correlation (DIC) and 3D CT imaging show that longitudinal plies fail via fiber pull-out, whereas transverse plies fail via interfacial debonding. QCW-laser-cut specimens exhibit more uniform strain distribution and higher damage tolerance. An optimized process parameter is proposed: nanosecond-laser cutting at 200 W and 20 kHz achieves a HAZ of less than 50 µm and a cutting time of less than 80 s, offering the best balance between efficiency and quality. Full article
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