Search Results (1,276)

As an essential component of dynamic loads, traditional time-domain identification methods exhibit notably insufficient accuracy when dealing with distributed dynamic load identification under unknown initial conditions. This paper explores a novel and effective methodology, utilizing the Bayesian framework and orthogonal polynomials fitting, to reconstruct the distributed dynamic loads of thin plate structures over any arbitrary time period under unknown initial conditions. The forced vibration under the orthogonal basis function loads and the free decay vibration after the removal of basis function loads are used to characterize the forced vibration induced by the identified distributed dynamic load and the decay vibration caused by unknown initial conditions, respectively. By integrating structural dynamic responses within a multi-layer Bayesian framework, the time history and spatial distribution of the load over any arbitrary time period are identified. The innovation of this methodology is that the contribution of the initial conditions to the response is independently characterized by the free decay response caused by the removal of the basis function loads, which effectively resolves the issue of insufficient identification accuracy in existing traditional time-domain methods due to unknown initial conditions. Consequently, the accuracy and reliability of the distributed dynamic load identification is significantly enhanced, which provides a new solution for distributed dynamic load identification under unknown initial conditions. Additionally, simulation cases involving various load conditions and noise levels are discussed under unknown initial conditions over arbitrary time periods. The results demonstrate that the proposed method achieves favorable identification accuracy and robustness under unknown initial conditions. Full article

Rolling bearings are critical components in rotating machinery, and their failures may cause unexpected downtime and safety risks. However, conventional deep diagnostic models are often difficult to deploy on resource-constrained edge devices because of their high computational cost and memory consumption. This paper proposes a lightweight time–frequency attention network (LTFANet) for multi-fault diagnosis of rolling bearings on an edge platform. The proposed model directly processes one-dimensional vibration signals and employs multi-scale depthwise separable convolutions to capture impact and periodic fault features with low computational complexity. A lightweight frequency branch is introduced to enhance fault-frequency representation, while an efficient channel attention module adaptively emphasizes fault-sensitive features. Moreover, a severity-aware multi-task extension is introduced to jointly identify the fault location and degradation level. To further improve edge inference efficiency, knowledge distillation, structured pruning, and TensorRT-based acceleration are integrated into the deployment pipeline. Experiments on CWRU-10 and Paderborn achieve 97.20% and 90.25% accuracy, respectively, while LTFANet contains only 0.020 M parameters and requires 0.610 M FLOPs. Knowledge distillation increases the CWRU-10 accuracy to 98.50%, and the severity-aware extension achieves 95.18% severity accuracy. On the NVIDIA Jetson Nano, the pruned TensorRT FP16 implementation achieves an average inference latency of 0.520 ms and a throughput of 1923.08 samples/s. The framework provides an effective solution for real-time and low-cost bearing condition monitoring at the edge. Full article

To elucidate the coupling characteristics between unsteady flow and hydrodynamic loads in the guide vane region of a pump–turbine under runaway conditions, a model pump–turbine of a high-head pumped storage power station was selected as the research object. A combined approach of model experiments and three-dimensional unsteady numerical simulations was employed to investigate the guide vane hydraulic torque, flow field structures, pressure distribution, and pressure fluctuation characteristics under different pre-opening guide vane conditions. In the experiments, the hydraulic torque of guide vanes was measured using a guide vane shaft strain testing method at five guide vane openings of 19 mm, 25 mm, 33 mm, 41 mm, and 45 mm. In the numerical simulations, a full-passage unsteady computational model was established based on the SST k-ω turbulence model, and the reliability of the numerical model was validated against experimental results. The results indicate that the guide vane hydraulic torque under runaway conditions exhibits pronounced periodic fluctuations, and the dominant period in the time domain is consistent with the blade passing frequency, demonstrating that rotor–stator interaction between the runner wake and guide vanes is the primary mechanism inducing unsteady hydraulic loads. As the guide vane opening decreases, the flow passage area in the guide vane region is reduced, and the high-speed swirling flow at the runner outlet generates significant jet impingement and local shear layers near the guide vane inlet, resulting in enhanced circumferential non-uniformity of the flow field and a substantial increase in the pressure difference across the guide vane surfaces. Among all operating conditions, the hydraulic torque fluctuation at a₀ = 19 mm is the most severe. Under small-opening conditions, flow separation, wake accumulation, and local backflow structures are prone to occur in the vicinity of the guide vanes, accompanied by pronounced high-frequency pressure disturbances and local impulsive pressure peaks. With increasing guide vane opening, the flow attachment behavior and flow field continuity are gradually improved, and the pressure fluctuations evolve from random oscillations to regular periodic pulsations, indicating a significant enhancement in flow stability. The study demonstrates that small guide vane opening conditions produce hydrodynamic load characteristics—specifically, higher-amplitude and more intermittent torque fluctuations, as well as lower minimum pressures—that are indicative of conditions conducive to increased vibration, fatigue accumulation, and cavitation risk; however, direct structural or two-phase cavitation analyses are required to confirm these implications. The present results can provide a theoretical basis for the optimal design of guide vane mechanisms and the safe operation of pump–turbines under runaway conditions, and quantitative coupling analysis reveals that the cross-correlation between inlet pressure and torque decreases from R = 0.87 at a₀ = 19 mm to R = 0.72 at a₀ = 45 mm, confirming that the flow–load coupling weakens substantially with increasing opening. Full article

In response to issues such as axial vibration, attenuation of drilling pressure transmission and increased impact loads on components near the drill bit that frequently occur during long-distance drilling in near-horizontal directional boreholes in underground coal mines, a multi-degree-of-freedom axial vibration model for directional long-hole drill-string systems has been established based on structural and stress analysis of the drill-string system. The model accounts for borehole-wall friction, buoyancy correction, self-weight, Rayleigh damping, drilling pressure input, and the velocity interaction between the drill bit and the coal–rock formation, and employs numerical integration to solve for the displacement, velocity, and spectral response of the drill bit and the pulse probe. The results indicate that an increase in the friction coefficient widens the vibration envelope, whilst the principal frequencies remain concentrated at approximately 5 Hz and its harmonics. When the drilling pressure is increased from 80 kN to 110 kN, the response increases gradually, and under high-pressure (120 kN) and heavy-duty drilling tool combinations, the displacement and velocity are significantly amplified; when the drill-string length was increased from 400 m to 550 m, the system’s response shifted from a relatively regular periodic response to a low-frequency, multi-peak response with amplitude modulation. The velocity response of the pulse probe was generally higher than that of the drill bit, indicating that it is a component sensitive to axial impacts near the drill bit. The research findings provide a theoretical basis for optimising drilling pressure, controlling frictional resistance and designing vibration-damping drill-string configurations for long directional boreholes in coal mines. Full article

In the era of intelligence, accurate remaining useful life (RUL) prediction is essential to ensure the reliable operation of smart equipment, particularly for rolling bearings—critical components that are highly susceptible to degradation in rotating machinery. However, as faults progressively develop, the vibration signals of rolling bearings exhibit strong non-stationarity and complex degradation patterns. Existing RUL prediction methods, particularly standard Transformer-based models, often struggle to capture local transient features within non-stationary signals and fail to effectively decouple long-term degradation trends from periodic variations. To overcome these limitations, a novel RUL prediction method that integrates time-series analysis techniques with the FEDformer architecture is proposed, termed TE-FEDformer. Firstly, a feature enhancement module is employed at the input stage to reconstruct and strengthen the original sequence, aiming to strengthen the representation of weak fault features that are often overlooked by global attention mechanisms. Then, deep time-series representations are extracted via the encoder. In the decoding stage, a frequency enhancement mechanism and a sequence decomposition mechanism are jointly utilized to explicitly model the coupling between degradation trends and periodic variations, thus resolving the spectral interference commonly encountered in complex degradation processes. Comparative experimental results on the PHM2012 and XJTU-SY datasets demonstrate that TE-FEDformer outperforms other benchmark models. Ablation studies further validate that each module contributes positively to the overall performance, confirming the effectiveness of the proposed approach for RUL prediction. Full article

Pumped storage hydropower (PSH) is a key regulating resource for renewable energy integration and power system stability. Due to frequent start-stop operations, deep peak-load regulation, and bidirectional operating conditions, stator winding insulation degradation, rotor inter-turn short circuits, and end-winding vibration have become the dominant failure modes of pumped storage units. Conventional monitoring systems are limited by single-source sensing, asynchronous data acquisition, high misdiagnosis rates, and maintenance decisions that rely heavily on expert experience, making traditional periodic maintenance increasingly inadequate. To address these challenges, this study proposes an intelligent diagnosis and decision support system based on multi-source data fusion and hybrid intelligent algorithms. An Intelligent Electronic Device (IED)-based condition monitoring platform is developed by integrating multiple sensing technologies. Complete Variational Mode Decomposition (CVMD) and Kernel Principal Component Analysis (KPCA) are employed to extract representative features from multi-physical-field data, while an attention-enhanced Long Short-Term Memory (LSTM) network is introduced for accurate fault identification. In addition, adaptive time-alignment and joint denoising algorithms are developed to improve data quality and diagnostic robustness. A predictive maintenance framework incorporating health assessment and remaining useful life prediction is further established to optimize maintenance scheduling. Results demonstrate that the proposed system achieves a fault prediction accuracy of over 90% and reduces annual maintenance costs by approximately 15–20%. The proposed framework provides an effective solution for intelligent operation and maintenance of modern pumped storage units. Full article

Clarifying the dynamic mechanism of rock pillar fracture and its rock burst-inducing mechanism is fundamental for the prevention and control of rock burst disasters in steeply inclined extra-thick coal seam groups. In this study, field monitoring, theoretical analysis, and numerical simulation were combined to investigate the rebound vibration behavior and rock burst-inducing mechanism of fractured rock pillars, and corresponding mitigation measures for rock pillar-induced rock bursts were proposed. The results indicate that instantaneous rock pillar fracture induces reciprocating rebound vibration behavior within the coal seam rock pillar, causing the velocity, displacement, and strain energy density of the rock pillar to remain in a persistent fluctuation state. Meanwhile, periodic mutual conversion between strain energy and kinetic energy occurs throughout the vibration process. During any vibration cycle, the rock pillar cannot recover to its initial equilibrium position, resulting in a sharp increase in the loads acting on the floor side of the B3–6 coal seam and a significant decrease in the loads acting on the roof side of the B1–2 coal seam. Consequently, the B3–6 coal seam remains subjected to transient dynamic loading, whereas the B1–2 coal seam experiences transient unloading after rock pillar fracture. This asymmetric transient loading mechanism is identified as the intrinsic reason for the higher rock burst proneness of the B3–6 coal seam. Based on the dynamic response characteristics of the stope coal rock system, staggered-level mining of the B1–2 and B3–6 coal seams and slotting presplitting in the B3 roadway were proposed as mitigation measures for rock pillar-induced rock bursts. When the stagger distance of the working face increases from 25 m to 100 m, the stress drop of the B3–6 coal seam is 22.9%~28.7%. When the slotting depth of the rock pillar increases from 25 m to 80 m, the stress of the B3–6 coal seam decreases by 9.88%~24.1%. These findings provide theoretical support and engineering guidance for rock burst prevention and control in steeply inclined coal seam. Full article

Vortex-induced vibration (VIV) is one of the main causes of fatigue failure in subsea pipelines and has recently attracted significant attention from researchers. Previous studies have mainly focused on idealized straight pipes, with limited consideration of gravity-induced slight curvature in free-spanning fluid-conveying pipes. In reality, the deformation configuration of a free-spanning fluid-conveying pipe is not fixed but varies with parameters such as internal flow velocity and tension, which in turn affect its dynamic behavior. A theoretical model, taking into account the axial stretching effect and the gravity-induced initial slight curvature, is developed to predict the VIV responses of free-spanning fluid-conveying pipes. The governing equations are derived based on Hamilton’s principle. The interaction between the external flow and the pipe structure is simulated using the van der Pol equation. By combining the Galerkin method and the Runge–Kutta method, the vibration responses of the pipe are obtained. The accuracy of the proposed model is validated by comparing the predicted VIV response curves and bifurcation diagrams with those reported in previous studies. The initial static deformation of the structure under different tensions and internal velocities is obtained through numerical calculations. It is found that the gravity-induced slight curvature leads to a reduction in the VIV response mode. The static deformation of the pipe decreases with increasing axial tension, while it increases with increasing internal flow velocity. Under the same external flow velocity, the gravity-induced initial deformation reduces the dominant vibration frequency and causes the vibration response to transition from quasi-periodic to periodic motion. Full article

Aluminium alloy honeycomb vibration isolators, owing to their thin-walled nature and periodic structure, offer numerous advantages, including lightweight construction, high strength, structural stability and simplicity of design parameters. Traditional honeycomb structures exhibit high stiffness in the coplanar direction but offer virtually no vibration isolation. To develop the vibration isolation performance of honeycomb structures in the coplanar direction and achieve vibration isolation protection for precision electronic instrument cabinets, this paper introduces a periodic corrugated structure based on traditional straight-hole honeycombs, designs a new type of corrugated honeycomb isolator, and screens and refines its vibration isolation performance. Using finite element simulation, multiple sets of orthogonal experiments were designed to perform range analysis on the simulation results, gradually eliminating the interference of irrelevant factors on the vibration transmission rate and optimising the dimensional parameters of the corrugated honeycomb isolator. To further optimise the vibration isolation performance of the corrugated honeycomb isolator, periodic circular holes were opened in the X and Y directions of the isolator, reducing its vibration transmission rate in the Z-direction and effectively improving the vibration isolation effect. Simultaneously, sweep frequency tests were designed to verify the accuracy of the finite element model. Full article

To elucidate the influence of operational conditions on the seismic responses of offshore wind turbines (OWTs) and the vibration mitigation efficacy of tuned mass dampers (TMDs) under multi-hazard scenarios, time-domain dynamic analyses are performed for OWT systems subjected to combined wind, wave and seismic excitations. Five typical operational conditions are considered, including cut-in operation, rated-power operation, cut-out shutdown, 1-year return-period extreme shutdown, and 50-year return-period extreme shutdown. The nacelle acceleration and tower-top displacement responses of the uncontrolled structure are comparatively characterized, the peak and root-mean-square (RMS) vibration reduction ratios of the TMD for fore-aft vibrations are quantitatively assessed, and the intrinsic mechanism governing the response discrepancies across operational conditions is elucidated. Numerical results demonstrate that seismic excitation dominates the extreme structural responses of the OWT system. Under the rated-power condition, the peak acceleration and displacement under coupled seismic loading reach 6.90 and 2.19 times the corresponding values under wind–wave loads alone, respectively. Substantial discrepancies in structural responses are observed across operational conditions, with aerodynamic damping magnitude and the spectral properties of hub rotational loads identified as the key influencing factors. The TMD exhibits reliable vibration control performance overall: the optimal control efficacy is achieved under the 1-year return-period shutdown condition, with a peak acceleration reduction ratio of 34.8%—by contrast, its mitigation performance degrades significantly under the 50-year return-period extreme-turbulence condition, with the peak acceleration reduction ratio dropping to merely 15.8%. Full article

Carbon fiber reinforced plastic (CFRP) composites have been widely adopted in the aerospace industry due to their excellent mechanical and physical properties. However, their anisotropy and weak interlaminar bonding make them prone to defects such as delamination and fiber pull-out during conventional drilling (CD). Longitudinal-torsional coupled ultrasonic vibration-assisted drilling (LTC-UAD) integrates axial and circumferential vibrations to suppress hole defects and is considered a promising machining method for improving the quality of holes drilled in CFRP. Based on kinematic analysis, a model for the working rake angle of the main cutting edge is established to obtain the variation law of the maximum working rake angle along the cutting edge. Compared with CD and longitudinal ultrasonic vibration-assisted drilling (L-UAD), LTC-UAD significantly increases and homogenizes the maximum working rake angle of the main cutting edge, which helps optimize its cutting performance. A three-dimensional finite element model of CFRP is constructed to analyze the dynamic fiber removal process under typical fiber orientations. Finally, drilling experiments are performed to observe the hole wall micro-morphology at various fiber angles. The simulation results indicate that ultrasonic vibration causes periodic changes in the fiber cutting angle, subjecting the fibers to a directional shear state and making them more prone to shear fracture. Two-dimensional ultrasonic vibration cutting enhances the directional shear effect, promotes fiber fracture, accelerates chip removal, and improves the quality of the machined surface. Experimental observations confirm LTC-UAD alleviates fiber crushing, bare fibers, and surface cavities with uniform resin coverage. Furthermore, ultrasonic vibration suppresses thrust force. L-UAD and LTC-UAD yield 10.6% and 17.1% reductions via periodic cutting depth variation and facilitated carbon fiber shear fracture. Full article

Minimizing unplanned downtime is critical for maintaining productivity in modern manufacturing. While combining sensor networks with machine learning provides a practical way to detect mechanical failures early, conventional data-driven diagnostics often fail during highly transient stamping operations. This failure stems from severe spectral smearing and signal distortions caused by fluctuating process loads and variable operating speeds. To address these limitations, we present a field-tested fault diagnosis (FD) framework deployed in an active automotive components plant. Over a twelve-month observation period, we collected raw vibration and process data from two operational transfer presses, building a comparative dataset that captures both localized gear damage and healthy baseline dynamics. After preprocessing the data to isolate signal anomalies, we systematically evaluated the diagnostic performance of six algorithms: SVM, Random Forest, Naive Bayes, k-NN, Decision Trees, and Logistic Regression. By integrating angle-based position data from a high-resolution encoder, the developed framework successfully pinpointed specific defective gear teeth. Ultimately, the Random Forest model outperformed the others, delivering the most robust detection accuracy under real-world factory conditions. These results show that the proposed Condition Monitoring (CM) approach significantly reduces resource waste and prevents costly downtime, offering a practical and scalable asset management model for industrial applications. Full article

The Cretaceous shallow oil sands in the Dagang area, located on the western slope of the Songliao Basin, are characterized by a burial depth of ≤182 m, an average reservoir temperature of 11.8 °C, an extremely high crude oil viscosity of 1,750,000 mPa·s at 15 °C, and water-bearing layers in both the roof and floor. Conventional thermal recovery methods such as SAGD and CSS are geologically unsuitable for this deposit and suffer from high energy consumption and carbon emissions. As microbial oil recovery is a technically advanced enhanced oil recovery technology that leverages microbial growth, reproduction and metabolism in the reservoir to alter the properties of oil, rock, gas and water through interaction with these components, and petroleum biotechnology research confirms that microorganisms can degrade high-molecular-weight petroleum hydrocarbons to reduce crude oil viscosity and improve its fluidity, this study explores the technical feasibility of microbial cold recovery for in situ extraction of such low-temperature, high-viscosity oil sands. The study adopts a five-well pilot pattern (one injector and four producers) with an integrated approach combining reservoir unblocking, microbial viscosity reduction, and vibration-assisted production. Systematic screening identified Pseudomonas, Chryseobacterium, and Citrobacter as the most efficient indigenous microbial strains. Pseudomonas exhibited a crude oil degradation rate of 32.17%, reducing asphaltene content from 7.47% to 3.56%, and achieved large-scale proliferation (2.5 × 10⁸ cfu/mL) at 15 °C. It also achieved a 40.8% reduction in crude oil viscosity and a desulfurization rate, alongside 56.6% denitrification. With the optimal activator No. 3, the viscosity reduction rate reached 45.18%, and the viable cell count exceeded 9.45 × 10⁸ cfu/mL. The synergistic action of Pseudomonas and an A-type nano-microemulsion surfactant reduced the oil–water interfacial tension from 49.56 to 1.25 mN/m (a 97.48% reduction) and lowered the crude oil viscosity at 25 °C from 302,000 to 11,023 mPa·s (a 96.35% reduction). Core flooding tests demonstrated an incremental oil recovery of 7.38% compared with the water-flooded control, with interfacial tension dropping from 48.21 to 1.18 mN/m. In the field trial, composite perforation (32 shots/m, 1610 mm penetration) and two cycles of oil-based fermentation fluid huff-n-puff reduced injection pressure from 2.0 to 2.5 MPa to 1.0–1.8 MPa. A total of 1489 m³ of microbial agent was injected into five wells, followed by a 125-day shut-in period. Nano-microemulsion single-well huff-n-puff (579 m³ over 87 days) further decreased injection pressure to 0 MPa. A downhole harmonic vibration source (≤20 Hz) was also applied during the trial. During the production phase, Pseudomonas was found to dominate the produced fluid, with its peak relative abundance exceeding 70%. Cumulative fluid production reached 4114 m³, yielding 21 m³ of oil sand oil. Wells with vibration assistance showed significantly higher oil content and better emulsification performance than wells without vibration assistance. Full article

Background/Objectives: Traditional Mongolian Rhythmical Vibration Therapy (RVT) is a manual intervention utilizing low-frequency mechanical oscillations, yet its biomechanical effects lack objective quantification. The present study aimed to evaluate the impact of manual RVT on paraspinal muscle stiffness and its long-term sustainability on the quality of life (QoL) in patients with chronic low back pain (LBP). Methods: To evaluate treatment mechanisms and long-term sustainability, this investigation utilized an acute comparative framework (n = 60) alongside a three-year longitudinal observational study design (n = 60) using consecutive convenience sampling. To assess biomechanical efficacy, paraspinal stiffness was measured via mytonometry, contrasting manual RVT against mechanical percussive vibration. Additionally, the long-term sustainability of outcomes was evaluated where clinical efficacy was quantified using the Roland-Morris Disability Questionnaire (RMQ) and the WHOQoL instrument, supported by a post-treatment metered walking regimen (Terrenkur). Within- and between-group changes were analyzed using paired and independent t-tests. Results: A Manual RVT yielded statistically significant and greater reduction in paraspinal muscle stiffness compared to mechanical vibration (p < 0.05). Immediate clinical outcomes revealed significant reductions in RMQ scores, which dropped from 13.33 ± 2.046 to 3. 40 ± 1.522 (p < 0.001, Cohen’s d = 4.20). At the three-year follow-up, participants maintained significantly high quality of life scores across physical, psychological, and social domains (p < 0.001, effect sizes d > 0.80). Conclusions: Manual RVT is associated with reduced paraspinal muscle stiffness in chronic LBP patients. The integration of this manual therapy with a Terrenkur maintenance regimen appears to support the maintenance of functional and quality of life improvements over a three-year period. However, given the observational design of the study, these outcomes must be interpreted cautiously, and randomized controlled trials are required to establish absolute therapeutic efficacy. Full article

The transition from internal combustion engine vehicles to battery electric vehicles has changed the acoustic design problem in automotive engineering. The absence of combustion-related masking increases the perceptibility of tonal and narrowband sources, including gear whine, electric motor orders, inverter-related components, tire cavity resonances, auxiliary system noise, and lightweight-panel radiation. At the same time, mass-based acoustic treatments conflict with electric vehicle lightweighting, range, cost, and sustainability targets. Vibroacoustic metamaterials offer an alternative route by manipulating elastic and acoustic wave propagation through architected geometries, local resonances, periodicity, membranes, lattice architectures, and adaptive or topological wave-control mechanisms. This review examines vibroacoustic metamaterials for low-frequency electric vehicle noise, vibration, and harshness (EV NVH) from an engineering perspective. It covers mechanisms, EV-specific NVH problems, component applications, materials, manufacturing, modeling, validation, AI-assisted design, sustainability, and technology readiness. Particular emphasis is placed on order-targeted, path-oriented, manufacturable, and experimentally validated solutions for electric-drive (e-drive) housings, wheel arches, battery enclosures, body panels, covers, and auxiliary systems. The review concludes that vibroacoustic metamaterials are most promising when integrated into conventional NVH workflows through order analysis, transfer path ranking, robust resonator tuning, durability validation, and multi-objective design optimization. Full article