Search Results (96)

Recent advances in structural engineering have enabled lightweight and slender footbridges. However, these structures are often susceptible to excessive vibrations induced by pedestrian activities, primarily impacting urban footbridge serviceability. Most studies evaluate human–structure interaction (HSI) uniaxially based on peak dynamic sensitivity. Nevertheless, this approach may overlook multidirectional mechanisms in footbridges with similar vertical and lateral modal properties. This study presents an extensive experimental assessment of HSI effects on a functional urban pedestrian bridge, known as the Premier-Footbridge, which exhibits clear multiaxial dynamic sensitivity within the frequency range associated with human walking. The structure was characterized by using operational modal analysis (OMA) based on ambient vibration measurements. Subsequently, a comprehensive human gait campaign evaluated different pedestrian density loads (PDL) and gait conditions, including synchronized, non-synchronized, and random walking. The results show that the multiaxial interaction effects were predominantly concentrated around the first lateral vibration mode (1.07 Hz), despite concurrent dynamic sensitivity in both lateral (1.07 Hz) and vertical (1.98 Hz) directions. Increasing PDL levels led to higher vibration amplitudes and measurable changes in HSI-related structural dynamics, including apparent damping and pedestrian step frequency. The experimental results indicated an apparent increase in effective structural damping with increasing pedestrian density, as identified through nonlinear trend fitting of the measured modal response parameters. Despite the multiaxial dynamic sensitivity of the structure, lateral vibrations remained the dominant factor governing the serviceability response, even under moderate PDL conditions. Full article

This study investigates the use of magnetoelastic sensing for vibration-based structural health monitoring (SHM) of cementitious beam specimens under intact and damaged conditions. Prismatic mortar beams with dimensions of 160 × 40 × 40 mm³ were fabricated following standardized preparation procedures and equipped with annealed amorphous ferromagnetic ribbons, Metglas 2826MB3, for nondestructive magnetoelastic vibration sensing. The specimens were tested under free-vibration conditions in a simply supported configuration, and their vibration response was measured using a detection coil and subsequently analyzed using MATLAB software. The undamaged specimen exhibited a dominant resonance frequency at 6531 Hz, which closely corresponded to the fourth bending mode predicted by Euler–Bernoulli beam theory. Controlled notch-shaped cracks with varying locations and depths were subsequently introduced to evaluate the sensitivity of the sensing system to structural damage. Experimental results showed that the frequency shift is strongly influenced by the location of damage relative to the modal nodes, with maximum sensitivity observed between nodal regions and minimal variation near the nodes. Furthermore, increasing notch-shaped crack depth produced progressively larger frequency shifts, revealing a monotonic and non-linear relationship between damage severity and dynamic response. Polynomial fitting and 3D surface analysis further highlighted the combined influence of crack location and depth on the measured frequency variation. The findings confirm that the magnetoelastic sensor is capable of accurately detecting and magnetically transmitting the vibration state and damage-induced changes in cementitious structures, demonstrating high sensitivity and strong potential for application in vibration-based structural health monitoring systems, particularly in materials characterized by strong vibration damping. Full article

The development of electric bus superstructures requires an integrated engineering approach combining structural design, numerical simulation, experimental validation and durability assessment. This need is particularly important for electric buses, where heavy roof-mounted battery systems and auxiliary components influence structural load paths, fatigue durability and rollover crashworthiness. This paper presents a measurement-supported workflow for the development of a virtual electric bus superstructure model, including finite element analysis, multibody dynamics simulations, operational load assessment, fatigue-oriented evaluation and rollover crashworthiness analysis. The finite element model is used to assess static load cases, modal properties and structural response under selected design conditions. A multibody vehicle model with nonlinear suspension characteristics is applied to simulate representative operating scenarios and to support the definition of dynamic load cases. Operational measurement data from previous work are used as a basis for realistic load characterization. Experimental torsional stiffness and modal tests are used to validate the numerical model. The main contribution of the study is the integration of these numerical, experimental and operational-data-based activities into a consistent early-stage verification process. The proposed workflow supports early identification of critical structural regions, assessment of design modifications and reduction in prototype-based design iterations. Full article

Aiming at the deterioration in Noise, Vibration and Harshness (NVH) performance caused by broadband torsional vibration in the integrated electric drive system (IEDS) of electric vehicles, most existing studies independently focus on electromagnetic excitation suppression or torsional vibration control of mechanical transmissions. Few researchers consider the coupling characteristics between the electromagnetic nonlinearity of motors and the nonlinearity of gear transmissions, making it difficult to realize the coordinated suppression of high- and low-frequency torsional vibration. In this paper, a seven-degree-of-freedom electromechanical coupling dynamic model is firstly established, which incorporates the electromagnetic torque ripple of the motor, the time-varying meshing stiffness of gears, meshing errors, and gear backlash nonlinearity. Through modal analysis and Campbell diagram solution, the natural characteristics and critical speed range of the system are clarified, and the generation mechanism of full-frequency band torsional vibration as well as the high–low frequency coupling characteristics are systematically revealed. On this basis, a coordinated active control strategy based on PD pole placement and harmonic current injection (PD-HCI) is proposed. The PD pole placement controller is adopted to suppress the low-frequency torsional vibration (0–20 Hz) of the transmission system, and the 5th/7th harmonic current injection is used to counteract the high-frequency torque ripple (above 200 Hz) of the motor, thereby achieving the coordinated suppression of broadband torsional vibration. The Matlab/Simulink R2023a simulation results show that the proposed control strategy reduces the torque fluctuation rate from 3.11% to 1.96%, the speed fluctuation rate from 0.10% to 0.03%, and the total harmonic distortion (THD) of stator current from 8.69% to 1.77% under steady-state operating conditions. Under transient operating conditions with sudden load changes, the stabilization time of fluctuations in speed and half-shaft torque is shortened by more than 80%, the impact amplitude is significantly reduced, and there is no loss in the vehicle’s dynamic response and speed tracking performance. Experimental results show that the coefficients of determination R2 of vehicle speed, motor speed, acceleration and torque are 0.9990, 0.9982, 0.9997 and 0.9997, respectively, which verifies the reliability of the established model. Full article

Vibration-based Structural Health Monitoring (SHM) exploits automated Operational Modal Analysis (OMA) to track changes in modal parameters over time for subsequent statistical pattern recognition and anomaly detection. However, weak excitation, measurement noise, non-stationarities, non-linearities, and model inaccuracies can jeopardize the reliability of automated OMA and pollute the modal parameter time series with a number of outliers or spurious estimates. These have an impact on statistical pattern recognition and consequently, the anomaly detection accuracy. Thus, a preliminary data cleansing to enhance the robustness of modal parameter tracking is imperative to ensure the reliability of SHM outcomes. Clustering techniques represent an attractive solution to automatically identify underlying data patterns and discriminate possible spurious results. However, the curse of dimensionality is often an issue in the application of such techniques to time series of experimentally identified modal parameters. To mitigate this issue and, at the same time, the computational efforts, the present study proposes an innovative approach leveraging clustering techniques coupled with mode-pairing constraints for robust and automatic tracking of modal parameters in the context of vibration-based SHM applications. Different clustering algorithms have been embedded in the proposed data processing strategy and applied to a real dataset collected on a full-scale structure under operational conditions. The comparative performance assessment demonstrated how DBSCAN outperforms other clustering methods in the context of the proposed approach, allowing the effective separation of the physical poles from the spurious ones even in the presence of closely spaced modes and highly polluted feature space. Full article

Dual 6 degrees of freedom (6-DOF) series-parallel cooperative robot actuators are core execution components in modern intelligent manufacturing systems, which are widely used in high-end manufacturing scenarios such as aerospace precision assembly, laser precision machining, and core component assembly of new energy vehicles. However, in actual manufacturing processes, the pose deviation between theoretical model prediction and actual motion execution of the actuator, caused by kinematic model mismatch, unquantified core parameters, incomplete error processing chain, and complex on-site environmental interference, severely restricts the assembly accuracy, product qualification rate and production efficiency of the manufacturing system. To address these critical pain points of robot actuators in precision manufacturing systems, this paper proposes a four-layer hierarchical decoupling multi-modal fusion calibration algorithm for high-precision pose control of dual series-parallel robot actuators. The algorithm integrates singular value decomposition (SVD) for cross-structure coordinate alignment of heterogeneous actuators, chaotic mapping-enhanced particle swarm optimization (PSO) for nonlinear error suppression of the actuator system, attention-enhanced deep residual network (DRN) for unmodeled residual learning of the actuator, and Kalman filter (KF) for dynamic noise reduction in the manufacturing process. Meanwhile, a full-chain error transfer model of the actuator system in the manufacturing process is constructed, and the core parameters of the algorithm are quantified via dimensional sensitivity analysis and orthogonal experiments. Experimental results show that the static position error of the actuator system after calibration reaches 1.4 ± 0.08 mm, and the static pose error reaches 0.0059 ± 0.0003 rad in the laboratory environment; in the engineering application of laser precision machining in an actual manufacturing line, the position error and pose error only increase by 8.6% and 6.8% respectively, maintaining high stability in industrial manufacturing scenarios. Compared with mainstream calibration methods, the proposed algorithm reduces the position error and pose error of the actuator by up to 55.7% and 17.9% respectively, with lower computational complexity and higher engineering reproducibility. This work constructs an end-to-end error suppression chain with quantitative parameter criteria for the series-parallel actuator system in manufacturing systems, which provides a reliable high-precision calibration solution for industrial dual-robot cooperative manufacturing and has important guiding significance for improving the motion accuracy and operation stability of actuators in precision manufacturing systems. Full article

Rolling bearing fault diagnosis is critical for ensuring the safe operation of rotating machinery, yet it faces significant challenges in noisy environments. This paper proposes BEAM-Net (Bearing-spectrum Enhanced by EMA and Weighted Spectral Convolution Network), a lightweight neural network designed specifically for rolling bearing fault diagnosis under strong noise conditions. Classifying bearing faults from vibration signals remains a challenging task when fault-related features are subtle and easily submerged in background noise—especially when the signal-to-noise ratio (SNR) is low. To address this challenge, BEAM-Net adopts a “decompose–enhance–extract” pipeline: first, an Exponential-Moving-Average Trend Decomposer (ETD) splits the frequency spectrum into a smooth trend component and a fault-sensitive residual component; second, a Spectral Residual Gate (SRG) reinjects detailed residual information through a learnable gating mechanism; finally, a Weighted Spectrum Convolution block (WSC) incorporates a symmetric center-emphasizing prior into the convolution kernel, ensuring that local spectral patterns receive greater attention. Experimental results on the Case Western Reserve University (CWRU) bearing dataset at SNR = −6 dB show that BEAM-Net achieves an F1 score of 99.15% with only 2835 parameters. Compared to the single-convolution baseline, this represents a $+0.78\%$ improvement in F1 score and a 50% reduction in the false positive rate (from $0.18\%$ to $0.09\%$). Cross-dataset validation on the Paderborn University (PU) and Machinery Failure Prevention Technology (MFPT) datasets further confirms the generalizability of the proposed approach, achieving F1 scores of 97.83% and 98.46%, respectively, under comparable noise conditions. These findings demonstrate that combining explicit spectral trend modeling with weighted convolution is not only effective but also parameter-efficient, making it well-suited for noise-robust rolling bearing fault diagnosis. It should be noted that the current method is primarily validated on spectral-analysis-based diagnostics of rolling bearings; its applicability to other vibroacoustic diagnostic modalities (e.g., tapping or nonlinear vibration excitation) and to quantitative defect severity grading remains to be investigated in future work. Full article

Cold bending provides a cost-effective method for fabricating triangular glass units for free-form architectural envelopes. Replacing conventional continuous edge constraints with discrete point clamps reduces over-constraint but introduces pronounced bending–membrane coupling in the unsupported spans between adjacent clamps. Consequently, the mechanisms governing local instability and optical-quality degradation remain insufficiently understood. In this study, cold-bending tests were performed on isosceles triangular fully toughened glass plates to measure out-of-plane deflection and surface-strain evolution. The experimental data were then used to establish and validate an Abaqus finite element model for systematic parametric analysis. Based on von Kármán’s large-deflection theory, a semi-empirical reduced-order framework that combines modal superposition with the response-surface method was developed to identify instability-sensitive configurations. The results show that, under weak constraints and large vertex angles, the panel response changes from a bending-dominated regime to a strongly nonlinear large-deflection regime governed by membrane effects; this transition is marked by a reversal of mid-span deflection and a compressive-to-tensile stress transition. Increasing the number of clamps from two to four substantially suppresses both global and local distortion by shortening the free spans and redistributing membrane strain energy, reducing peak mid-span deflection by 47–68%, and satisfying the EN 12150-1 limits for both bow deformation and local distortion. The height-to-base ratio is the dominant geometric parameter controlling instability. Under two-point support, a critical response turning point occurs at a height–base ratio of approximately 0.5 before the material fracture limit is reached, defining a geometric boundary below which optical serviceability failure accelerates. These findings provide a theoretical basis and quantitative engineering guidance for optimizing the cold-bending process of isosceles triangular fully toughened glass plates. Full article

Percussion instruments exhibit complex vibrational behavior characterized by transient excitation, high modal density, and strong structural–acoustic coupling. Numerical modeling—especially the finite element method (FEM)—has become essential for analyzing realistic geometries, material heterogeneity, and fluid–structure interaction. This review systematically synthesizes FEM-based studies on percussion instruments, organized by their physical classification into idiophones and membranophones. The present work thematically compares modeling strategies and their trade-offs and highlights actionable research gaps. FEM and coupled FEM–boundary element (BEM) approaches applied to bars, plates, shells, membranes, and vibroacoustic systems are reviewed, with emphasis on modal behavior, tuning strategies, excitation mechanisms, nonlinear phenomena, and fluid–structure interaction. A key feature is the consistent validation of simulations against experimental measurements. The analysis reveals that while FEM is mature for modeling bars, plates, shells, and single-membrane systems, significant gaps remain: bar–resonator coupling and damping/residual stress modeling in idiophones, coupled clapper–bell–air simulations for bells, and fully coupled double-membrane simulations for drums. The latter directly affects predictions of modal frequencies, decay rates, and timbre. The review concludes by identifying priority research directions: fully coupled double-membrane models, material nonlinear viscoelasticity, efficient FEM–BEM coupling, and integration of performer-informed excitation for sound synthesis. Full article

Medical image registration is a fundamental task in medical image analysis, enabling the alignment of images from different modalities or time points. However, intensity inconsistencies and nonlinear tissue deformations pose significant challenges to the robustness of registration methods. Recent approaches leveraging self-supervised representation learning show promise by pre-training feature extractors to generate robust anatomical embeddings, that further used for the registration. In this work, we propose a novel framework that integrates equivariant contrastive learning directly into the registration model. Our approach leverages the power of contrastive learning to learn robust feature representations that are invariant to tissue deformations. By jointly optimizing the contrastive and registration objectives, we ensure that the learned representations are not only informative but also suitable for the registration task. We evaluate our method on abdominal and thoracic image registration tasks, including both intra-patient and inter-patient scenarios. Experimental results demonstrate that the integration of contrastive learning directly into the registration framework significantly improves performance, surpassing strong baseline methods. Full article

Gravity energy storage systems (GESS) have emerged as a promising long-duration energy storage technology capable of supporting large-scale renewable integration and enhancing grid resilience. However, the modeling framework for the hoisting electromechanical subsystem in wire-rope-based GESS remains underdeveloped, thereby limiting the accurate characterization of its transient grid-connected behavior, dynamic operating response, and cross-domain coupling effects. Existing studies commonly simplify wire ropes and related transmission components as rigid bodies or low-dimensional mechanical elements, failing to adequately account for their flexibility and the resulting high-dimensional nonlinear dynamics. Although related studies in mine hoisting and elevator systems have addressed mechanical vibration phenomena, they primarily focus on mechanical-side effects, such as shock loading and guide-structure response, whereas the mechanism by which flexible mechanical vibrations propagate through electromechanical coupling and influence electrical dynamic performance remains inadequately understood. To address this gap, this study establishes a distributed-parameter model for the wire-rope hoisting mechanism based on Hamilton’s principle and solves the corresponding vibration governing equations using the Galerkin method to capture nonlinear multi-modal dynamics. An electromechanical coupling model is then developed to elucidate how rope-vibration-induced tension fluctuations propagate through the drive chain, resulting in torque ripple, electrical interharmonics, and low-frequency grid-side oscillations. A Bessel-function-based analytical representation is further introduced to explain the formation of interharmonic clusters and beat-frequency phenomena under converter modulation. An experimental prototype is constructed to validate the proposed modeling framework. The measured vibration spectra, beat-frequency characteristics, and torque ripple align closely with analytical predictions, confirming the model’s capability to capture key propagation paths from rope vibration to electromechanical oscillation and grid-side dynamic response. The results provide a solid theoretical foundation for vibration mitigation, dynamic analysis, and control design of hoisting electromechanical subsystems in gravity energy storage applications. Full article

This study experimentally investigates the evolution of natural frequencies of premium threaded connections under varying interface contact stiffness, aiming to establish a non-destructive vibration-based method for evaluating sealing contact conditions. The sealing interface features a sphere-on-cone configuration, and Hertzian contact theory is used to derive the contact pressure distribution, which shows a nonlinear increase in peak pressure with increasing normal load. Modal experiments were conducted under free–free boundary conditions using an impact hammer on a Φ88.9 mm × 6.45 mm P110 premium threaded connection. Three make-up torque levels (4081 N·m, 4393 N·m and 4691 N·m) were applied to create distinct contact states, and the first five orders of natural frequencies were extracted from the measured acceleration responses, using frequency response function (FRF) analysis with peak-picking identification. The results demonstrate that natural frequencies increase significantly with make-up torque, following a power-law relationship f = αT^β with R² > 0.97 for the first three modes. A critical torque range of 4200–4400 N·m is identified, below which frequencies rise sharply and above which the increase slows due to contact stiffness saturation. Lower-order modes are more sensitive to contact stiffness variations than higher-order modes. The findings confirm that natural frequency can serve as an effective non-destructive indicator for assessing tightening quality and detecting loosening in premium threaded connections, offering practical guidance for torque optimisation and structural health monitoring in oilfield operations. Although only three torque levels are used, the observed trend is physically consistent with contact mechanics theory and widely reported joint stiffening behavior. Therefore, the fitted relationship should be interpreted as a physically guided empirical model rather than a purely statistical fit. Full article

Forced resonance induced by rotor–stator interaction (RSI) is a primary driver of high-cycle fatigue (HCF) failure in aero-engine blisks. To overcome the inability of traditional non-contact excitation methods to replicate authentic three-dimensional aerodynamic forces and the predictive biases of pure numerical approaches regarding complex flow excitation energy, this study investigates the forced resonance characteristics of a rotating blisk using a novel aerodynamic excitation system through integrated numerical and experimental approaches. First, a one-way fluid–structure interaction (FSI) framework, coupling the Nonlinear Harmonic (NLH) method with Finite Element Analysis (FEA), was established to efficiently reconstruct the unsteady aerodynamic loads on blade surfaces. The analysis reveals an excitation mechanism dominated by the upstream propagation of the downstream potential field, based on which the numerical resonance response was predicted. In addition, investigating rotor–stator axial clearance as a key variable indicates that there is a strictly monotonically decreasing dependence of the aerodynamic excitation magnitude on the rotor–stator axial clearance. However, the spatial patterns of the primary first-order harmonic excitation remain relatively insensitive to changes in the rotor–stator axial clearance. Finally, by leveraging these excitation characteristics, broadband aero-resonance of the first three modes was successfully induced within the 2600 Hz frequency range under experimental conditions. This validates both the effectiveness of the experimental apparatus and the fidelity of the numerical model. This research not only clarifies the excitation mechanism under vortex generator-induced RSI but also provides a novel testing platform and theoretical framework for rotating modal analysis in advanced propulsion systems. Full article

The impact hammer, equipped with a force transducer, is a portable and practical tool for inducing measurable excitations in structural health monitoring (SHM). However, its reliability is often limited by uncontrolled factors such as swing power, angle, impact location, and operator consistency, particularly in nonlinear structures operating at low frequencies. While many researchers have avoided hammer testing by instead using better controlled drop mass systems or operational modal analysis (OMA) techniques, this study presents a new experimental modal analysis (EMA) approach that improves the accuracy of impact hammer testing: variable impulse hammer impact testing (VIHIT) using a single-input single-output (SISO) roving hammer and single fixed accelerometer. For a mode of interest, the imaginary component of the frequency response function (FRF) is evaluated at each test location using multiple impulses of varying magnitude. This output quantity exhibits an inverse power relationship with the input autopower spectral density (APSD) at the modal frequency. Evaluating the trend at a reference input APSD from sufficiently excited tests produces a very accurate mode shape for that input. For a given structure, nonlinear damping ratios vary with excitation and can be extracted using inverse FRF analysis. This method addresses variability in impact hammer testing by establishing reproducible trends for different impulse levels and test locations. Application to degraded timber beams demonstrated reductions in mode shape variability relative to conventional averaging and revealed impulse-dependent damping ratios ranging from approximately 0.02 to 0.04, highlighting the method’s ability to characterize nonlinear dynamic behavior. The result is a more accurate approach for extracting modal properties and mode shapes and characterizing nonlinear dynamic behavior using a SISO roving impact hammer system. Full article

The nonlinear dynamic response of aerospace thin-walled structures in a post-buckling state under thermo-acoustic loads is critical for their design. This study investigates this phenomenon through integrated experimental and numerical approaches. Acoustic tests on thermally stressed flat plates yielded results in close agreement with finite element and reduced-order modal (FEM/ROM) simulations, with first-order frequency deviations within ±2 Hz and strain values of the same order of magnitude (10.7 µε vs. 9.5 µε at 50 °C). A key observation is the non-monotonic variation in the thermal modal frequency, which initially decreases then increases with the buckling coefficient, while dynamic strain data further validate the computational model. Comparative analysis of three Haynes 188 alloy geometries—flat plates, cylindrical shells, and spherical shells—reveals distinct behaviors rooted in their critical buckling temperatures (68.46 °C, 151.20 °C, and 698.28 °C, respectively): flat plates exhibit softening–hardening transitions with a frequency range of 491–624 Hz; cylindrical shells show irregular responses with a dramatic frequency drop from 1120 Hz to 360 Hz; and spherical shells maintain the highest stability and frequency range (1913–2109 Hz), governed by the buckling coefficient’s linear effect. Time-domain and probability density function (PDF) analyses elucidate the snap-through phenomena and the modulating roles of the buckling coefficient and sound pressure level (SPL). These findings underscore that geometric configuration and inherent stiffness are critical to post-buckling performance, providing a theoretical basis for designing aerospace components in extreme environments. Full article