Search Results (3,099)

Spacecraft and launch-vehicle structures require lightweight multipoint monitoring under combined mechanical, thermal, and environmental loads. This study presents an analytical fiber Bragg grating (FBG) sensor-network workflow integrating reference-grating temperature compensation, regional strain assessment, opposite-surface curvature sensing, wavelength-division-multiplexing allocation, and strain-to-shape reconstruction. The deterministic compensation case is used only as a self-consistency check, whereas practical robustness is assessed through 10,000 Monte Carlo trials incorporating packaged-coefficient mismatch, temperature nonuniformity, wavelength noise, strain-transfer variation, drift, and calibration uncertainty. The calibrated estimator achieved a median strain mean absolute error of 1.73 με and a 95th-percentile error of 4.22 με. The defined finite-element benchmarks produced a maximum engine-mount truss strain of 456.2 με under the defined loads and a median full-field panel-reconstruction normalized root-mean-square error of 1.29% for 18 sensing locations with 2 με noise. Conservative WDM analysis yielded 54, 13, and 16 channels for three operating envelopes, and the prescribed random-vibration spectrum produced 6.78 g_rms. These results demonstrate a reproducible numerical proof of concept and define practical limits for compensation, spectral allocation, curvature interpretation, and inverse reconstruction; they do not constitute experimental validation or flight qualification. Full article

To overcome the limitations of existing evaluation methods and performance testing for wind power generation systems, this study proposes a modular framework for performance testing and comparative assessment. Methodologically, the approach establishes a baseline configuration for simulation and provides optional interfaces for experimental, hardware-in-the-loop, or bench testing under identical boundary conditions. By employing a unified metric system, the proposed method enables a comprehensive evaluation of annual energy production (AEP) gains, power curve deviations, damage equivalent loads (DEL) when cycle-resolved load histories are available, fatigue- and peak load proxy variations, efficiency fluctuations, temperature rise margins, and reliability proxy indicators. A demonstrative case study is conducted using illustrative numerical data parameterized for a generic 2.5 MW-class doubly fed wind turbine to compare three retrofit schemes: blade replacement, gearbox optimization (S2), and a pitch system upgrade. When annual energy production (AEP) is utilized as the sole metric, the blade replacement scheme yields a 3.32% increase. However, it concurrently increases the fatigue load and peak load proxies by 6.11% and 3.72%, respectively. Conversely, a comprehensive assessment incorporating load, temperature rise, vibration, and reliability identifies the gearbox optimization (S2 scheme) as the highest-ranked option under the current weighting configuration, with a reproducible overall score of 0.65. The weight sensitivity analysis further shows that the preferred scheme can change when engineering priorities change. Ultimately, this work demonstrates the proposed method’s capability to highlight the discrepancy between single-metric and holistic performance optimization, providing standardized support for scheme selection, project acceptance, and the evaluation of wind turbine retrofit schemes. Full article

Needle roller bearings are characterized by rolling elements with relatively high length-to-diameter ratios and are widely used in mechanical systems with limited radial installation space. In gear transmission systems, periodic impact loads induced by gear meshing may be superimposed on steady radial loads, thereby altering the dynamic response of the bearing. However, the effects of the amplitude and frequency of periodic impact loading on the dynamic characteristics of needle roller bearings remain insufficiently understood. In this study, a needle roller bearing test rig capable of applying periodic impact loading was developed, and a multi-sensor measurement system was configured to measure outer-ring vibration, inner-ring motion, cage motion, and the friction torque of the bearing system. Dynamic tests were conducted under different amplitudes and frequencies of periodic impact loading. A reduction in bearing motion stability was observed under periodic impact loading, as evidenced by increased outer-ring vibration and enlarged cage motion in both the horizontal and vertical directions. As the loading amplitude increased, the RMS values of outer-ring acceleration, inner-ring displacement, and cage displacement increased, while an increase in the mean friction torque was also observed. The inner-ring trajectory expanded along the loading direction, and the whirling range of the cage trajectory increased. As the loading frequency increased, the RMS values of outer-ring acceleration, inner-ring displacement, and cage displacement increased, and the mean friction torque increased. In contrast, the whirling range of the cage trajectory decreased. These findings clarify the distinct effects of periodic impact-loading amplitude and frequency on bearing vibration, internal motion, and friction-torque characteristics and provide experimental support for the dynamic performance evaluation of needle roller bearings under impact conditions. Full article

Robotic Aerial Work Platforms (RAWPs) are subjected to multi-source excitations including wind gusts and inertial loads, which result in strongly nonlinear and time-varying coupled triaxial attitude vibrations. Conventional recurrent architectures such as LSTM and GRU suffer from gradient vanishing when processing long sequences, while Transformer utilize self-attention mechanisms to learn simple periodic correlations; however, the vibrations in RAWPs exhibit a complex time-series pattern composed of low-frequency oscillations superimposed with high-frequency impacts and accumulates errors through autoregressive decoding. To address these limitations, this paper proposes an improved Transformer model featuring dual-channel periodic positional encoding and global–local hybrid multi-head attention for one-shot multi-step long-sequence prediction of RAWPs attitude vibrations. The proposed method designs a dual-channel independent sine–cosine positional encoding with a tunable periodic modulation factor to explicitly embed the multi-scale periodicity priors of vibration signals and introduces a global–local hybrid attention mechanism that parallelly extracts transient amplitude impact features in the time domain and periodic fluctuation features in the frequency domain. A full-scale aerial experimental platform is established to collect triaxial vibration data under two operating conditions at a sampling frequency of 20 Hz. The results determine the optimal periodic modulation factor and input window length, and ablation studies validate the synergistic gains of the two proposed modules. Comparative results demonstrate that the proposed model achieves substantially reduced prediction errors. In terms of pitch angle, the proposed model achieves a performance improvement of 53.89% over Transformer, 52.11% over LSTM, and 57.67% over GRU. The proposed model effectively provides a reliable data-driven prediction framework for attitude monitoring and active vibration suppression of aerial work platforms. Full article

Driven by the engineering requirement for high acoustic stealth of unmanned underwater vehicles (UUVs), this paper investigates the electromagnetic vibration of an 8-pole, 48-slot, surface-mounted permanent magnet synchronous motor (SPMSM) employed in the propulsion system through multi-physics coupling analysis and experimental testing. First, analytical calculations of electromagnetic force waves are performed based on the Maxwell stress tensor method and the magnetomotive force–permeance method to analyze the spatial orders, temporal orders, and sources of the harmonics. Then, a two-dimensional motor model is established using ANSYS electromagnetic field simulation software to investigate the temporal and spatial characteristics of electromagnetic force waves under both no-load and on-load conditions. Fourier decomposition is applied to obtain the amplitude-frequency characteristics, thereby verifying the correctness of the analytical results. Subsequently, three-dimensional models of the stator core and the complete stator assembly are constructed in the physical field, and their modal frequencies and mode shapes are obtained through simulation. On this basis, harmonic response analysis is conducted by applying electromagnetic force waves to the stator teeth, and vibration simulations are performed in ANSYS Workbench to acquire vibration characteristics. Vibration experiments are then carried out at multiple rotational speeds, and the experimental results are compared with the simulation results to validate the feasibility and accuracy of the finite element modeling approach. Since the measured motor vibration results are influenced not only by electromagnetic excitation forces, but also by various factors such as mechanical structure, instrument installation, and fixture conditions, while the simulation model in this paper inevitably simplifies damping, housing details, inverter control effects, and considers only the effect of radial electromagnetic forces, there exists a certain discrepancy between the simulated and measured motor vibration acceleration results. However, the main vibration trends in the low-frequency range below 800 Hz are basically consistent, particularly at the second and fourth harmonic frequencies, where the vibrations are electromagnetic vibrations caused by radial electromagnetic force waves, with relative errors between the measured and simulated values of 18% and 25%, respectively. This finite element model can be used for preliminary design evaluation of PMSMs and rapid prediction of electromagnetic vibration, providing researchers with a convenient and practical research approach and methodology. Finally, by analyzing factors that may influence motor vibration, this paper proposes design modifications to the stator structure and air-gap width, providing an optimized solution for reducing electromagnetic vibration of the permanent magnet synchronous motor and avoiding resonance. Full article

Overhead-line sensor platforms must satisfy electrical and mechanical installation constraints that vary with the operating scenario. This study evaluates separate phase-conductor electrostatic and 9 mm optical ground wire (OPGW) vibration-test scenarios for the same platform. A full Maxwell potential-coefficient matrix provides an analytical reference for a 500 kV line-to-line RMS four-bundle conductor. A three-dimensional COMSOL Multiphysics 6.3 model compares the prototype enclosure scale and fastening-hole configurations. The matrix gives a maximum bare-conductor surface field of 14.33 kV/cm RMS. The phase-RMS values for the hole-free, single-hole, and double-hole cases are 8.05, 12.27, and 12.91 kV/cm RMS, respectively. These values quantify local field enhancement at the hole edge and support geometry comparison. Under a 16.5 kN tensile load, 47.71 Hz vibration, ±2.4 mm cable amplitude, and 1 × 10⁷ cycles, the OPGW test showed no visually detectable slippage or cable damage. The two scenarios provide electrical-geometry and mechanical-interface evidence under the specified analysis and test conditions. Full article

A fluid–structure interaction (FSI) model of the guide vane and runner of a pump-turbine was developed by applying unsteady hydraulic pressure loads obtained from CFD simulations to the structural surfaces. The deformation behavior, stress distribution, and modal response of the stay vane, movable guide vane, and runner were investigated under different operating conditions. The maximum deformation of the stay vane occurs at the middle section of the blade leading edge, whereas the maximum deformation of the movable guide vane is located near the trailing edge. The maximum deformation of the runner occurs at the junction between the blade leading edge and the band. Modal analysis shows that the fourth natural frequency of the movable guide vane approaches the eighth-order guide-vane passing frequency, while the sixth natural frequency of the runner approaches the fourth-order runner blade-passing frequency, suggesting a potential risk of vibration amplification. Full article

Nutating mills offer intense comminution dynamics without the gravitational constraints of conventional tumbling mills; however, their structural response and charge–structure interaction mechanisms remain insufficiently characterized. This work examines the dynamic behavior of a laboratory-scale nutating mill (NuMill) with granular charge through combined experimental characterization and a two-way coupled numerical framework integrating multi-body dynamics (MBD) with the discrete element method (DEM). This study expands on previous work, extending the characterization of the NuMill to include mount stiffness, damping, and charge–structure coupling. The NuMill was adapted with vibration isolation mounts and internal chamber ribs to more closely emulate the operating behavior of industrial Hicom mills. Measurements of forces, torques, and accelerations were obtained across a range of mounting, charge, and chamber geometry configurations. Results show that approximating the granular charge in a ribbed chamber as a rigid body leads to substantial predictive error, overestimating crank-pin forces by 21% and underestimating driveshaft torque by 82% at 700 RPM. Incorporating experimentally characterized stiffness into the coupled MBD–DEM model showed good prediction accuracy for granular charge at 700 RPM. The simulation overestimated crank-pin force by 34%, underestimated driveshaft torque by 25%, and reproduced rigid-body natural frequencies within 1%. These findings demonstrate that structural compliance and charge–structure coupling play a central role in determining operational loads in nutating mills. The validated modeling framework developed here provides a more reliable basis for design assessment and parameter selection in industrial nutating milling applications and extends existing experimental foundations for laboratory-scale systems. Full article

To address the problems of enhanced non-stationarity, significant feature distribution shift, and insufficient cross-condition generalization capability of traditional fault diagnosis methods under variable operating conditions such as varying speed and load, a rolling bearing fault diagnosis method integrating group sparse reconstruction and a multi-strategy improved quantum particle swarm optimization-based relevance vector machine (RVM) is proposed. First, group sparse representation learning is employed to reconstruct the original vibration signals, thereby suppressing background noise and enhancing fault-related impulsive components to improve signal separability and stability. Subsequently, a modal component selection criterion combining kurtosis and correlation coefficients is introduced to optimize and reconstruct the decomposed modal components, enabling the reconstructed signals to retain more fault-sensitive information. On this basis, multiple information entropy features are extracted from the reconstructed signals to construct high-dimensional state feature vectors for comprehensively characterizing the dynamic operating states of rolling bearings. To further enhance the parameter optimization capability, Chebyshev chaotic mapping is incorporated into the quantum particle swarm optimization (QPSO) algorithm to improve the uniformity of population initialization. Meanwhile, a Cauchy mutation strategy is introduced to strengthen the global search capability and avoid premature convergence, thereby forming a multi-strategy improved QPSO algorithm. Finally, the improved optimization algorithm is utilized to adaptively optimize the key hyperparameters of the RVM, resulting in a fault diagnosis model with high accuracy, strong generalization capability, and sparse characteristics. Experimental validation on the HUST and XJTU-SY bearing datasets demonstrates that the proposed MIQPSO-RVM framework achieves diagnostic accuracies of 96.70% and 94.83%, respectively. Compared with several representative intelligent diagnosis methods and deep learning models, the proposed method exhibits superior diagnostic performance, robustness, and generalization capability under complex operating conditions. Full article

Pedestrian-induced vibration is a critical serviceability concern for flexible structures such as footbridges and long-span floors. Existing human–structure interaction models commonly rely on single-degree-of-freedom simplifications and time-domain simulations, making them less suitable for frequency-domain analysis. This paper proposes a spectral analysis model for crowd-structure interaction vibration under unrestricted pedestrian traffic. The structure was formulated as a multi-degree-of-freedom modal system, whereas each pedestrian is represented by an independent spring–mass–damper system. To address the time-varying nature of moving crowds, a piecewise stationary assumption was introduced: the continuous walking path was discretized into fixed position groups, within each of which a time-invariant coupled equation of motion was established. The response spectra obtained for different position groups were combined using residence-time weighting, thereby allowing nonuniform walking speeds to be considered. The corresponding frequency response function was derived using the state–space method, and the structural acceleration power spectral density and root mean square responses were obtained by incorporating an unrestricted crowd walking load spectral model. Comparisons with field measurements from two footbridges demonstrated reasonable agreement. The resulting framework offers an efficient frequency-domain approach for vibration serviceability assessment under unrestricted pedestrian traffic. Full article

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

Cross-condition bearing fault diagnosis requires models that remain reliable under load-induced distribution shifts while providing transparent and traceable reasoning. Conventional belief rule bases (BRBs) may repeatedly use correlated vibration evidence during inference, and their Cartesian-product rule construction can rapidly increase rule-base complexity. This study proposes a correlation-decoupled interval belief rule base (CD-IBRB) for cross-condition bearing fault diagnosis. Seven diagnostically relevant time-domain features are selected using XGBoost and transformed into a less-correlated feature space through a Kendall-rank-correlation-guided matrix estimated exclusively from the source training data. Attribute-wise referential points and intervals are then constructed from the transformed training attributes, allowing the rule base to grow additively rather than combinatorially. Initial belief distributions are obtained from interval-level class distributions. The projection covariance matrix adaptation evolution strategy (P-CMA-ES) jointly optimizes the belief degrees, rule reliabilities, and rule weights, while evidential reasoning aggregates the activated interval rules to produce the final diagnostic result. In the primary cross-load bearing experiment, CD-IBRB achieved an accuracy of 0.9702 and a macro-averaged F1 score of 0.9703. It outperformed the strongest BRB variant and data-driven baseline by 7.70 and 6.10 percentage points in accuracy, respectively. Ablation experiments confirmed that removing parameter optimization or attribute decoupling reduced accuracy to 0.9053 and 0.9303, respectively. Additional cross-load and noise-injection experiments further demonstrated the stability of CD-IBRB under load shifts and input disturbances. Across five public multiclass datasets, CD-IBRB achieved a mean accuracy of 0.9004 and consistently outperformed the compared BRB variants. These results demonstrate that CD-IBRB provides a compact, uncertainty-aware, and traceable framework for cross-condition bearing fault diagnosis. Full article

Functionally graded (FG) beams have been used more and more in highly designed structures under dynamic loading due to their graded mechanical properties and excellent performance. Their transient response on complex elastic foundations is, however, not easily predicted due to the material heterogeneity, shear deformation, rotary inertia, and coupled effect of the foundation parameters. The purpose of this study is thus to propose an accurate and efficient computational model for the dynamic analysis of FG Timoshenko beams supported by biparametric Vlasov foundations under harmonic excitation. The formulation takes into account the space-varying material properties, Timoshenko shear deformation, rotary inertia, and coupled Winkler–shear interaction of the Vlasov foundation. The governing equations are numerically solved in space with the high-order spectral element method (SEM) and in time with the Hilber–Hughes–Taylor (HHT) scheme. The resulting framework is used to study the transient displacement and vibration response with respect to the excitation frequency, material gradation index, and stiffness and damping properties of the foundation. The numerical results prove that the results converge quickly in space and time and also indicate that the dynamic response is significantly affected by the interaction between the gradation of material and the parameters of the foundation. The displacement amplitude, resonance behavior, and vibration characteristics are significantly altered by any variations in the gradation index and foundation characteristics. The results obtained with the proposed formulation are in good agreement with those available from the benchmark solutions, thus validating the correctness and reliability of the formulation. The SEM–HHT methodology offers a reliable, precise, and low-computational-cost solution for transient analysis of FG Timoshenko beams on biparametric Vlasov foundations under harmonic excitation. The proposed framework offers a powerful predictive tool for vibration analysis, response control, and design of advanced FG beam systems that can be applied in aerospace, marine, smart infrastructure, and other high-performance engineering structures. Full article

This paper presents a systematic experimental and computational investigation of the free-vibration characteristics of a Laser Powder Bed Fusion (LPBF) AlSi10Mg thick-walled cylinder, a geometry relevant to electric-machine housings, hydraulic sleeves, and pressure-carrying components exposed to resonance-critical service loads. The specimen has an outer diameter of 94 mm, an inner diameter of 64 mm, a wall thickness of 15 mm, and a height of 90 mm, placing it firmly in the thick-walled regime ($d/D=0.68$). A three-dimensional finite element model comprising 23,864 total elements (23,236 SOLID186 solid elements and 628 surface/contact elements) and 106,015 nodes was constructed in Ansys Mechanical using the AlSi10Mg material database entry (E = 75 GPa, $\rho$ = 2670 kg/m³, $\nu$ = 0.33) and solved with the Block Lanczos eigensolver under free–free boundary conditions. Experimental modal analysis (EMA) was conducted using Brüel & Kjær software with an impact hammer with a 260-node measurement grid covering the outer surface and both end rings; frequency response functions were acquired over 0–22,500 Hz. Fourteen flexible modes were identified in simulation; nine corresponding experimental modes were resolved with frequency deviations ranging from 0.13% to 1.10%. In addition to frequency correlation, this paper introduces a non-conservative damping characterization framework comprising: (i) Rayleigh (proportional) damping coefficient extraction from EMA data and assessment of its frequency-domain validity; (ii) a viscoelastic complex-modulus model relating the real storage modulus $E^{\prime }$ and imaginary loss modulus $E^{″}$ to the modal loss factor $\eta$ and damping ratio $\zeta$; and (iii) a practical design workflow for resonance mitigation of future AM structures including electric machine frames. Experimental damping ratios ($\zeta =0.013$–$0.311\%$) are converted to per-mode $E^{″}$ values and loss factors, revealing that energy dissipation in LPBF AlSi10Mg is strongly mode-shape-dependent and cannot be accurately represented by a single Rayleigh model. 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