Search Results (3,505)

A dam deformation prediction method based on interpretable component decomposition and integration is proposed to address the problems of weak interpretability, difficult identification of key factors, and insufficient accuracy in the prediction model of deformation monitoring values of concrete dams due to multiple factors such as environmental loads and time factors. This method first strips the temporal component from the original sequence to obtain the castration sequence. Furthermore, complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is used to decompose and reconstruct it into environmental load components and residual terms. In the process of deformation prediction, based on the characteristics of each deformation component, logarithmic functions, bidirectional long short-term memory (BiLSTM) networks optimized by The Black-Winged Kite Algorithm (BKA), and cloud models are used to fit and predict the temporal components, environmental load components, and residual terms, and the final prediction results are obtained through integration. At the same time, the SHAP (SHapley Additive exPlanations) method is introduced to quantify the contribution of input factors to enhance the interpretability of the model. Case study shows that the model outperforms the comparison model in both prediction accuracy and trend tracking ability, effectively improving the reliability of prediction results and significantly increasing the interpretability of deformation prediction, providing a more reliable analysis technique for dam deformation safety monitoring. Full article

Long-term stability of dam infrastructure is crucial for flood protection, water resource management, and drinking water supply. In many regions, the increasing impact of climate change and structural aging necessitates advanced monitoring approaches for embankment and gravity dams. PSI has emerged as a valuable technique for detecting surface deformation rates with millimeter precision. This study presents a comprehensive monitoring concept that combines satellite-based PSI analyses with the first operational use of ECRs at dam sites in North Rhine-Westphalia (NRW), Germany. Over a period of more than two years, ECRs were observed under real-world conditions using Sentinel-1 data. Compared to traditional passive reflectors, ECRs offer improved signal stability and a compact design, making them particularly suitable for confined or sensitive dam environments. The analysis of displacement time series confirms the suitability of ECRs for long-term deformation monitoring in complex dam settings. Intercomparison of two PSI time series demonstrated high internal consistency (correlation > 0.9, RMSE < 1 mm), while validation against in situ measurements confirmed millimeter-level agreement with RMSE values between 2 and 5 mm and correlations up to 0.7. In addition, a dedicated web-based platform was developed to provide processed ECR-based PSI results to dam operators, offering interactive visualizations, time-series access, and standardized downloads. This integration of advanced interferometric synthetic aperture radar (InSAR) methods, innovative hardware, and user-oriented service delivery marks a significant step toward operational dam monitoring using satellite remote sensing. Full article

With the acceleration of urbanization, deep and large foundation pit projects have become increasingly common, posing challenges for retaining structural performance. This study investigates the mechanism of the recently proposed vertical–inclined pile wall (VIPW) through physical model tests. Six sets of large-scale model tests of foundation pit excavation under 1 g gravity conditions were carried out. Among these tests, one employed the soldier pile wall (SPW) as the support system, while the remaining five adopted the VIPW. By monitoring and analyzing the distribution and variation in the vertical pile deformation, surface settlement, pile bending moment, and inclined pile top axial force during the excavation process, the action mechanism of the VIPW was revealed, and it was verified that VIPWs exhibit better support performance than SPWs. Furthermore, four key parameters, including the embedded depth, the inclination angle, the support position of the inclined piles, and the embedded depth of the vertical piles, were varied to study their influence on the deformation and force characteristics of the VIPW, providing a theoretical basis for structural optimization design. Moreover, by comparing the instability and failure characteristics of the foundation pit, it was proved that the VIPW can effectively ensure the stability of the foundation pit. Full article

Wind turbine blades are subjected to complex environmental conditions during long-term operation, which may lead to structural degradation and performance loss. To ensure structural integrity, fatigue testing prior to deployment is essential. This paper proposes a vision-based method for measuring the full-cycle breathing deformation of wind turbine blades during fatigue testing. The method captures dynamic image sequences of the blade’s hotspot cross-section using industrial cameras and employs a feature-based template matching approach to reconstruct the three-dimensional coordinates of target points. Through coordinate transformation, the deformation trajectories are obtained, enabling quantitative analysis of the blade’s dynamic responses in both flapwise and edgewise directions. A dedicated hardware–software system was developed and validated through full-scale fatigue experiments. Quantitative comparison with strain gage measurements shows that the proposed method achieves mean absolute deviations of 0.84 mm and 0.93 mm in two independent experiments, respectively, with closely matched deformation trends under typical loading conditions. These results demonstrate that the proposed method can reliably capture the global deformation behavior of the blade with millimeter-level accuracy, while significantly reducing instrumentation complexity compared to conventional contact-based approaches. The proposed method provides an effective and practical solution for full-field dynamic deformation measurement in blade fatigue testing, offering strong potential for structural health monitoring and early damage detection in wind turbine systems. Full article

The particle size of aggregate is a key factor affecting the mechanical properties and deformation capacity of cemented gangue filling body. In this study, coal gangue with a particle size range of (0.05, 20) mm was sieved into six groups of aggregate particles. Based on the Talbot gradation theory, cubic specimens with gradation indices n = 0.3, 0.4, 0.5, 0.6, and 0.7 were prepared for acoustic emission (AE) monitoring tests. The microstructure of the filling body was analyzed, and the failure characteristics and damage evolution laws of the cemented gangue filling body with different gradation indices were explored. The results show that the compressive strength reaches its maximum when n = 0.5. As the gradation index increases, the compressive strength of the specimens first increases and then decreases, and the specimens shift from primarily experiencing cleavage failure to shear failure. The curve of cumulative AE ringing count shows a bimodal distribution pattern, with both surge points and fracture points coexisting. The surge points can be regarded as precursor signals of backfill failure. The spatiotemporal evolution of AE events exhibits complex phased changes. An excessively small gradation index tends to form micropores and striped microcracks, reducing the compactness of the microstructure. An excessively large gradation index can lead to the formation of penetrative weak channels. A reasonable gradation index enables the mutual interlocking of aggregate particles, constructing a stable three-dimensional spatial skeleton structure. The dynamic trend of damage in the filling body can be captured based on AE analysis, and reverse guidance can be provided for parameter optimization of Talbot gradation, achieving a dynamic closed loop of “gradation design-AE monitoring-damage assessment-parameter optimization”. This not only enriches the application scenarios of acoustic emission analysis in graded materials, but also provides a new research approach and technical method for gradation design and safety assessment in scenarios where particle sizes are missing in practical engineering. Full article

Peen forming is a dieless manufacturing process used to shape large, thin aerospace panels through controlled shot impacts that induce residual stresses and curvature. Despite long-standing industrial use, process monitoring still depends largely on indirect proxies such as Almen intensity and coverage, limiting spatially resolved deformation assessment and hindering closed-loop control. In parallel, vision-based artificial intelligence (AI) has enabled adaptive monitoring and feedback in smart-manufacturing domains such as welding, additive manufacturing, and sheet forming. This review examines how such sensing and learning strategies can be transferred to adaptive peening forming. We compare six vision sensing modalities and assess major AI model families for surface mapping, temporal prediction, robustness, and deployment maturity. The synthesis shows that progress is primarily constrained by limited validated datasets, harsh in-cabinet sensing conditions, scarce closed-loop demonstrations, and weak validation on curved aerospace geometries. We conclude that the sensing and AI foundations for adaptive peen forming are already emerging, but industrial translation now depends on stronger experimental validation, standardized benchmarking, robust multi-sensor integration, and edge-capable feedback pipelines. Full article

Acoustic emission (AE) and digital image correlation (DIC) techniques enable real-time capture of damage signals and full-field deformation at anchored rock–concrete interfaces under shear loading, which is critical for quantitatively characterizing freeze–thaw (F-T) degradation and preventing geological disasters in cold regions. This study synchronously monitored full-shear-process AE signals using a broadband AE system (150 kHz resonant frequency, 5 MS/s sampling) and captured high-precision full-field deformation via a 5-megapixel monocular DIC system (25 fps). F-T cycle and direct shear tests were conducted on sandstone–concrete anchored specimens with varying F-T cycles and anchor depths to investigate their effects on shear mechanical properties, AE characteristics and failure modes. Results show that AE peak ring count first decreases by 44.9% then increases by 56.5%, while cumulative ring count exhibits a three-stage evolution. Shear crack proportion first decreases then increases, with tensile failure remaining dominant throughout. DIC reveals that F-T cycles shift failure from crack propagation to surface delamination and interface slip, while different anchor depths induce distinct failure patterns. This study confirms that AE and DIC can accurately characterize F-T degradation, providing a reliable non-destructive monitoring method for cold-region anchorage engineering. Full article

Time-series InSAR is an important means for early identification and monitoring of landslides. However, in complex mountainous areas, it still faces challenges such as significant geometric distortions and complicated deformation mechanisms. To address these issues, this paper proposes a landslide identification and prediction framework that integrates ascending and descending orbits InSAR observations with physics-guided deep learning. Taking Yangbi County, Yunnan Province, as a case study, we combined ascending and descending Sentinel-1A data and employed the SBAS-InSAR method to identify potential landslides, detecting a total of 41 hazardous sites. The cumulative displacement time series of typical landslides were further extracted along the slope aspect to more realistically reflect landslide movement characteristics. On this basis, wavelet decomposition was introduced to separate the displacement series into trend and periodic components. Gray relational analysis was then used to select influencing factors such as precipitation and temperature, and a stepwise prediction model based on LSTM (WT-LSTM) was constructed. The results indicate that the model achieves significantly higher prediction accuracy at characteristic points of the representative landslide (RMSE = 1.16–2.19 mm) compared to standalone LSTM and SVR models. These findings demonstrate its effectiveness and potential applicability in landslide deformation monitoring and prediction in complex mountainous areas, while also providing a useful reference for landslide risk early warning. Full article

Precise monitoring of forearm muscle groups is crucial for decoding motor intentions in human–machine interfaces (HMIs) and rehabilitation. However, traditional surface electromyography (sEMG) electrodes face significant challenges in densely packed muscle regions with large skin deformations, leading to severe signal crosstalk and unstable contact. Here, we report a flexible, low-cost 16-channel copper electrode array system designed for the high-density monitoring of multiple forearm muscle activities. Through a facile fabrication process, rigid copper is transformed into a conformable sensing interface. The optimized serpentine interconnects endow the array with excellent stretchability and effectively isolate motion-induced stress, ensuring high-quality signal acquisition under complex deformations. The high-density 2 × 8 array enables the spatiotemporal mapping of distributed flexor and extensor muscle groups. Integrated with a customized wireless data acquisition system, the array successfully demonstrates real-time, multi-channel sEMG monitoring of various hand movements (e.g., fist clenching, wrist flexion/extension), clearly revealing specific muscle activation patterns. This low-cost, high-performance flexible sensor array provides a highly promising tool for complex gesture decoding, electromyographic imaging, and next-generation wearable HMIs. Full article

The Persistent Scatterers InSAR (PSInSAR) technology, which utilizes pixels with stable phases to extract ground deformation, is an effective tool for large-scale, long-period surface monitoring applications. It has been widely applied to land subsidence monitoring, earthquake research, and infrastructure risk management. Furthermore, some studies have successfully employed this method to monitor the progressive motion of creeping in landslide areas. However, these regions containing active landslides are usually covered by canopy layers, which cause low coherence in InSAR processing and reduce the number of stable pixels, thereby preventing long-term period monitoring in those areas. In this study, the supervised deep learning model, U-Net, based on a convolutional neural network, is applied to the differential InSAR dataset acquired from Sentinel-1 to improve persistent scatterer selection. A well-processed PSInSAR result, utilizing 55 Sentinel-1 images acquired from 5 November 2014 to 19 December 2017, is introduced as a dataset for model training. The pixel-based Persistent Scatterer (PS) labels used for model training are identified using the StaMPS software. The model is designed to identify the distributed scatterer (iDS) index using a single pair of SAR images. As a result, more iDS pixels can be obtained from a single interferogram, indicating a significant improvement over the StaMPS algorithm. The line-of-sight velocity and time series of PS pixels from the model prediction show a long-term uplift on the upper slope, which represents downslope sliding in the target area. Furthermore, some iDS pixels exhibit a seasonal deformation on the lower part of the slope. The capability for these additional deformation analyses underscores the potential of this new deep-learning-based approach. Full article

Low-orbit thermal infrared bidirectional whisk-broom imaging offers wide-swath coverage and high spatial resolution for monitoring moving targets such as aircraft, but large scan angles and terrain undulation cause non-rigid geometric distortion and radiometric inconsistency between forward and backward scans. These effects generate strong clutter in difference images and degrade small and weak target detection. To address this problem, we propose an infrared small target detection method that fuses accurate registration and weighted difference. First, we propose a hybrid multi-scale registration algorithm that achieves coarse affine registration through sparse feature–point matching and then iteratively corrects nonlinear deformations by integrating a global grayscale-driven force with a local sparse-feature-guided force, yielding a registration error of 0.3281 pixels. On this basis, a multi-scale weighted convolutional morphological difference algorithm is proposed. A novel dual-structure hollow top-hat transform is constructed to accurately estimate the background, and a multi-directional convolution mechanism is introduced to effectively suppress anisotropic edge clutter and enhance target saliency. Experiments on SDGSAT-1 thermal infrared bidirectional whisk-broom data show an SCRG of 18.27, and a detection rate of 91.2% when the false alarm rate is below 0.15%. The method outperforms representative competing algorithms and provides a useful reference for space-based aerial moving target detection. Full article

The stability of retained roadways in closely spaced coal seams beneath a goaf is strongly affected by complex stress redistribution and the deterioration of roof structures under downward mining conditions. To address this issue, a combined approach involving theoretical analysis, numerical simulation, and field monitoring was adopted to investigate the deformation characteristics and stability control of gob-side retained roadways in short-distance coal seam groups. The movement characteristics of the roof and the deformation law of surrounding rock of the retained roadway under downward mining were revealed. An embedded short-arm beam structural model for a roof cutting retained roadway was established, and a calculation method for determining the required support resistance of the retained roadway was proposed. Based on this model, design criteria for the passive support system of the retained roadway were developed. A surrounding rock control technology with hollow grouting anchor cable support and low-disturbance directional roof cutting as the core was proposed, and the support resistance of a one-beam–four-column support system was determined to effectively limit roof subsidence. Field application results show that the surrounding rock displacement was controlled within 350 mm, and the roadway section shrinkage rate was maintained at 16.4%, indicating good stability of the retained roadway and satisfying the requirements of ventilation and transportation. This study provides a mechanical basis and practical guidance for stability control and support design of roof cutting retained roadways in closely spaced coal seams beneath goaf. Full article

Although polylactic acid (PLA) and acrylonitrile–butadiene–styrene (ABS) are among the most widely used polymers in material extrusion, their limited toughness and energy-absorption capacity often restrict the structural performance of 3D-printed functional components. To address the limited comparative understanding of how thermoplastic polyurethane (TPU) modifies the deformation behavior and phase characteristics of these two polymer systems, this study presents a multi-analytical evaluation of TPU-reinforced PLA and ABS blends. To this end, both polymers were blended with TPU at 10–50 wt% and processed into filaments via single-screw extrusion. The resulting filaments were used to fabricate ASTM D638 Type I tensile specimens via material extrusion under matrix-specific, but internally consistent, printing parameters. For each composition, five specimens were tested to obtain representative values of tensile strength, elongation at break, and toughness. In addition to conventional tensile testing, the evolution of strain during deformation was monitored using digital image correlation (DIC), enabling full-field characterization of local deformation behavior. To ensure experimental reliability, specimen masses were carefully controlled, and the datasets were analyzed using MATLAB. Thermal properties were investigated by differential scanning calorimetry (DSC) to determine the influence of TPU on glass transition, melting behavior, and phase mobility, and to relate these thermal characteristics to the mechanical response of the blends. The incorporation of TPU significantly increased ductility and energy absorption in both polymer matrices, although the magnitude of improvement differed. ABS/TPU blends exhibited the highest toughness enhancement, reaching 221.4% at 30 wt% TPU, while PLA/TPU systems showed nearly a twofold increase at 20 wt% TPU. DIC analysis further revealed a transition from localized brittle deformation in neat polymers to more distributed plastic deformation with increasing TPU content. DSC results indicated reduced crystallinity in PLA-rich blends and enhanced segmental mobility in ABS-based systems, consistent with the observed mechanical behavior. Overall, the combined mechanical, optical, and thermal analyses demonstrate that the optimal TPU content is matrix-dependent, providing practical guidelines for tailoring PLA- and ABS-based filaments to achieve a controlled balance between stiffness, ductility, and energy absorption in material extrusion applications. Full article

In this work, the deformation behavior of a long-span steel–concrete composite girder cable-stayed bridge under temperature loads and its subsequent impact on ballastless track systems were investigated. An integrated finite element model (FEM) of the bridge–track system was developed by taking the Taiziping Wujiang River Bridge (with a main span of 300 m) in Chongqing, China, as a case study. The model incorporates composite girders, pylons, stay cables, rails, and double-block slab tracks. Then, the integrated FEM systematically analyzed structural responses to various temperature loading scenario, namely uniform temperature change, differential temperatures among key components (girder, deck, pylons, and cables), and deck–girder temperature difference. The results show that the girder’s maximum vertical displacement linearly correlates with the temperature variations of the composite girder, upper pylon, and cables, with corresponding temperature sensitivity coefficients of 2.3 mm/°C, 2.78 mm/°C, and −5.8 mm/°C. While the ballastless track coordinates well with the composite girder in vertical deformation, the maximum longitudinal relative displacement occurs between rail and track at the ends of the bridge. Moreover, field monitoring data were used to establish a high-precision relationship between ambient temperature and structural temperatures of key components, enabling successful prediction of girder’s vertical deformation. The findings provide a theoretical basis for the control of thermal deformation during the operation and maintenance of similar long-span composite girder cable-stayed bridges. Full article

Utilizing excavated waste soil to level gullies offers significant advantages in terms of engineering economy and construction efficiency. However, the stability and deformation risks of high-fill embankments in mountainous gullies under rainfall conditions have attracted significant attention, particularly when such structures are located adjacent to residential areas. This study compares two design schemes for highway high-fill embankments, Scheme 1: high-fill slope supported by stabilizing piles and prestressed anchors, and Scheme 2: ordinary waste soil as the core, foamed lightweight soil (EPS) as the edge band, and reinforcement by a micro-pile retaining wall system. Finite element analysis was used to evaluate the Factor of Safety (FOS), displacements of retaining structures, and characteristic slope points under three conditions (no rainfall, heavy rainfall, and heavy rainfall with soil strength deterioration). The results show that Scheme 2 reduces total costs by 3.5%, shortens the construction period by 14%, and cuts maintenance costs by 65%, with a minimum FOS of 1.56 under extreme rainfall. Further parametric analysis of Scheme 2 optimized key design parameters, and field monitoring data over 6 months verified the reliability of the numerical simulation. This study provides a transferable design-verification pathway for combining lightweight and conventional fills in high embankments, offering technical support for similar projects in complex mountainous areas. Full article