Search Results (353)

The micro-interface slip damping mechanism is insensitive to temperature, making it suitable for applications where the operating environment makes viscoelastic polymers ineffective. Damping material systems that rely on micro-interface slip typically embody randomly disposed interlocking units leading to complex material behaviors. This work studies a compressed coir vibration isolator that provides a lightweight, low cost and environmentally friendly alternative to common polymer devices. Under cyclic loading, it displays highly nonlinear hysteresis and a gradual change in properties based on the load history. The nonlinear hysteresis is captured with a Masing model, which has been shown to provide an adequate phenomenological representation of systems with large numbers of miniature stick-slip contacts. This study further explores a new way to enrich the Masing model by encoding time evolution using restoring force or displacement time integral, directly adopted from mem-models, a new family of models transferred from electrical engineering. In addition to using the data from the coir isolator, two additional datasets from clayey soil, another application of micro-interface slip damping, are used to validate the modeling approach. Full article

Wire-rope isolators (WRIs) are widely used in vibration and seismic protection due to their multidirectional flexibility and amplitude-dependent hysteretic damping. However, their complex nonlinear behavior, especially under inclined and combined-mode loading, poses challenges for predictive modeling. This study presents a simplified finite-element modeling framework using constant-property Timoshenko beam elements with tuned Rayleigh damping to simulate WRI behavior across various configurations. Benchmark validation against analytical ring deformation confirmed the model’s ability to capture geometric nonlinearities. The framework was extended to five WRI types, with effective cross-sectional properties calibrated against vendor-supplied quasi-static data. Dynamic simulations under sinusoidal excitation demonstrated strong agreement with experimental force-displacement loops in pure modes and showed moderate accuracy (within 29%) in inclined configurations. System-level validation using a rocking-control platform with four inclined WRIs showed that the model reliably predicts global stiffness and energy dissipation under base accelerations. While the model does not capture localized nonlinearities such as pinched hysteresis due to interstrand friction, it offers a computationally efficient tool for engineering design. The proposed method enables rapid evaluation of WRI performance in complex scenarios, supporting broader integration into performance-based seismic mitigation strategies. Full article

Electrification introduces additional NVH (noise, vibration and harshness) challenges during the development of powertrain mounting systems due to high-frequency excitations from the powertrain and the absence of masking effects from the combustion engine. In these frequency ranges, engine mounts can stiffen up to a factor of five due to continuum resonances, reducing their structure-borne sound isolation properties and negatively impacting the customer’s NVH perception. Common hardening factors used during elastomer mount development are therefore limited in terms of their applicable validation frequency range. This study presents a methodology for determining decoupled permissible stiffness ranges for a double-isolated mounting system up to 1500 Hz, based on solution space engineering. Instead of optimizing for a single best design, we seek to maximize solution boxes, resulting in robust stiffness ranges that ensure the fulfillment of the formulated system requirements. These ranges serve as NVH requirements at the component level, derived from the sound pressure level at the seat location. They provide tailored guidelines for mount development, such as geometric design or optimal resonance placement, while simultaneously offering maximum flexibility by spanning the solution space. The integration of machine learning approaches enables the application of large-scale finite-element models within the framework of solution space analysis by reducing the computational time by a factor of $7.19·{10}^3$. From a design process standpoint, this facilitates frontloading by accelerating the evaluation phase as suppliers can directly benchmark their mounting concepts against the permissible ranges and immediately verify compliance with the defined targets. Full article

As smart cities evolve, integrating new technologies into school transportation is becoming increasingly important to ensure student comfort and safety. Monitoring and enhancing comfort during daily commutes can significantly influence well-being and learning readiness. However, most existing research addresses isolated factors, which limits the development of comprehensive and scalable solutions. This study presents the design and implementation of a low-cost, generalized IoT-based system for monitoring comfort in school transportation. The system processes multiple environmental and operational signals, and these data are transmitted to a cloud computing platform for real-time analysis. Signal processing incorporates standardized metrics, such as root mean square (RMS) values from ISO 2631-1 for vibration assessment. In addition, machine learning techniques, including a Random Forest classifier and ensemble-based models, are applied to classify ride comfort levels using both road roughness and environmental variables. The results show that stacked multisensor fusion achieved a significant improvement in classification performance compared with vibration-only models. The platform also integrates route visualization with commuting time per student, providing valuable information to assess the impact of travel duration on school mobility. Full article

To address the challenge of anomaly detection in vibration signals from high-speed electric multiple unit (EMU) motor bearings, characterized by strong non-stationarity and multi-component coupling, this study proposes a synergistic approach integrating variational mode decomposition (VMD) and deep learning. Unlike datasets focused on fault diagnosis (identifying known fault types), anomaly detection identifies deviations into unknown states. The method utilizes real-world, non-real-time vibration data from ground monitoring systems to detect anomalies from early signs to significant deviations. Firstly, adaptive VMD parameter selection, guided by power spectral density (PSD), optimizes the number of modes and penalty factors to overcome mode mixing and bandwidth constraints. Secondly, a hybrid deep learning model integrates convolutional neural networks (CNNs), bidirectional long- and short-term memory (BiLSTM), and residual network (ResNet), enabling precise modal component prediction and signal reconstruction through multi-scale feature extraction and temporal modeling. Finally, the root mean square (RMS) features of prediction errors from normal operational data train a one-class support vector machine (OC-SVM), establishing a normal-state decision boundary for anomaly identification. Validation using CR400AF EMU motor bearing data demonstrates exceptional performance: under normal conditions, root mean square error $(RMSE=0.005)$, Mean Absolute Error $(MAE=0.002)$, and Coefficient of Determination $(R^2=0.999)$; for anomaly detection, accuracy = 95.2% and F1-score = 0.909, significantly outperforming traditional methods like Isolation Forest (F1-score = 0.389). This provides a reliable technical solution for intelligent operation and maintenance of EMU motor bearings in complex conditions. Full article

Interference lithography (IL) offers high throughput, excellent uniformity, and maskless patterning capabilities. Compared to other methods, IL enables large-area, cost-effective fabrication of periodic structures with subwavelength resolution, which is particularly valuable for sensing applications, enabling the development of more sensitive, high-resolution, and reliable sensors. This review provides a comprehensive analysis of IL from the perspective of optical field control. We first introduce the principles of interference field formation and summarize key system architectures, including Mach–Zehnder and Lloyd’s mirror configurations, as well as advanced schemes such as multi-beam interference and multi-step exposure for complex pattern generation. We then examine how wavefront engineering, polarization modulation, and phase stabilization influence pattern morphology, contrast, and large-area uniformity. To address dynamic drifts caused by environmental perturbations, both passive vibration isolation and active fringe-locking techniques are discussed. For fringe-locking systems, we review methods for drift monitoring, control algorithms, and feedback implementation. These developments enhance the capability of IL systems to deliver nanoscale accuracy under dynamic conditions, which is essential for stable and high-performance sensing. Looking ahead, IL is evolving into a versatile platform for sensor-oriented nanofabrication. By integrating physical modeling, precision optics, and real-time control, IL provides a robust foundation for advancing next-generation sensing technologies with higher sensitivity, resolution, and reliability. Full article

The rapid expansion of urban rail transit networks has raised concerns about metro-induced vibrations in over-track structures. Floor vibration isolation systems provide an adaptable and efficient mitigation strategy, offering flexibility in architectural design while enhancing vibration comfort. This study investigates the dynamic characteristics and parameter optimization of such systems under multi-point excitations. A four-degree-of-freedom (4-DOF) model is developed to analyze the dynamic behavior of the isolation floor system, revealing that the height difference between the horizontal bearing installation plane and the centroid of the isolation plate critically induces “translation–rotation” coupling. Theoretical stability analysis and finite element simulations are employed to evaluate the effects of key parameters, including the isolation plate length, number of bearings, bearing arrangement, isolation frequency, and damping ratio. The results demonstrate that increasing the number of bearings reduces floor acceleration and displacement while improving response uniformity. The optimal isolation frequency range is identified as 3–5 Hz, balancing both isolation efficacy and uniformity. Additionally, increasing the bearing damping ratio to 0.05–0.1 can comprehensively mitigate vibration responses and improve vibration uniformity. Sensitivity analysis confirms that these optimal parameters exhibit strong robustness against ±20% practical deviations, ensuring reliable performance in engineering applications. These findings provide theoretical and practical guidance for optimizing floor isolation systems in over-track buildings, contributing to the sustainable development of urban rail transit networks. Full article

To meet the vibration isolation requirements of engines under diverse operating conditions, this paper proposes a novel magnetorheological fluid-elastomer isolator with high load and tunable parameters. The mechanical and magnetic circuit structures of the isolator were designed and optimized through theoretical calculations and finite element simulations, achieving effective vibration isolation within confined spaces. The dynamic performance of the isolator was experimentally evaluated using a hydraulic testing system under varying excitation amplitudes, frequencies, initial positions, and magnetic fields. Experimental results indicate that the isolator achieves a static stiffness of 3 × 10⁶ N/m and a maximum adjustable compression load range of 105.4%. In light of the asymmetric nonlinear dynamic behavior of the isolator, an improved nine-parameter Bouc–Wen model is proposed. Parameter identification performed via a genetic algorithm demonstrates a model accuracy of 95.0%, with a minimum error reduction of 28.8% compared to the conventional Bouc–Wen model. Full article

Shaft alignment is adversely affected by the increasingly severe coupled hull–raft deformation in deep-diving, highly integrated submersibles, thereby compromising operational safety and potentially amplifying vibration noise. To address to this issue, this paper investigates an intelligent alignment control method for the floating raft air spring mounting system (ASMS) applied to marine propulsion unit (MPU) under coupled hull–raft deformation conditions. A multi-objective alignment control algorithm was developed based on the NSGA-II optimization method within an N-step receding horizon optimal control framework, enabling simultaneous achievement of shaft alignment attitude adjustment, hull deformation compensation, raft deformation suppression, and pneumatic energy consumption. Experimental validation was conducted on two distinct ASMS prototypes to evaluate the control algorithm. Tests performed on the ASMS for MPU (MPU-ASMS) prototype demonstrated effective compensation of hull-induced deformations, maintaining shaft alignment offsets within ±0.3 mm and angularities within ±0.5 mm/m. Concurrently, experiments on the floating raft ASMS for the stern compartment (SC-FR-ASMS) achieved precise control of axial offsets within ±0.3 mm, angularities within ±0.5 mm/m, and vertical displacements of critical monitoring points within ±1 mm. The adaptive control strategy additionally proved effective in suppressing raft deformation while simultaneously optimizing pneumatic energy consumption. This research provides robust theoretical and technical foundations for intelligent vibration isolation systems in deep-sea equipment to accommodate extreme-depth-induced hull deformation and large-scale raft deformation. Full article

In recent years, with the rapid development of the unmanned aerial vehicle industry, aviation optoelectronic turrets have been widely applied in fields such as terrain exploration, disaster prevention and mitigation, and national defense. Vibration isolation systems play a critical role in ensuring their imaging performance. This paper proposes a novel eight-leg six-degree-of-freedom (6-DOF) passive vibration isolation system tailored to the characteristics of aviation optoelectronic turrets, addressing the limitations of traditional Stewart passive vibration isolation platforms. A static analysis of the system is conducted, deriving the general form of the mass matrix under application conditions for aviation optoelectronic turrets. Structural configuration conditions are established to ensure that the stiffness matrix and damping matrix are diagonal matrices. In dynamic analysis and simulations, the transmissibility in each direction is simulated, and the impact of leg failure on the vibration isolation performance of this redundant system is further investigated. Under random vibration excitation, the maximum rotational vibration angles of a specific aviation optoelectronic turret are simulated and analyzed, confirming its stable tracking capability and validating the effectiveness of the redundant leg design in the vibration isolation system. Full article

Traffic-induced vibrations from road and rail systems pose a significant threat to the structural integrity and operational safety of buildings, especially masonry structures located near planned infrastructure such as tunnels. This study investigates the dynamic impact of such vibrations on a representative early 20th-century masonry building situated within the influence zone of a design railway tunnel. A comprehensive analysis combining geological, structural, and vibration propagation data was conducted. A detailed 3D finite element model was developed in Diana FEA v10.7, incorporating building material properties, subsoil conditions, and anticipated train-induced excitations. Various vibration isolation strategies were evaluated, including the use of block supports and vibro-isolation mats. The model was calibrated using pre-construction measurements, and simulations were carried out in the linear-elastic range to prevent resident-related claims. Results showed that dynamic stresses in masonry walls and wooden floor beams remain well below critical thresholds, even in areas with stress concentration. Among the tested configurations, vibration mitigation systems significantly reduced the transmitted forces. This research highlights the effectiveness of integrated numerical modelling and vibration control solutions in protecting structures from traffic-induced vibrations and supports informed engineering decisions in tunnel design and urban development planning. Full article

To address the collaborative demand for low-frequency vibration control and energy recovery, this paper proposes a dual-functional structure integrating low-frequency vibration isolation and broadband energy harvesting. The structure consists of two core components: one is a quasi-zero stiffness (QZS) vibration isolation module composed of a linkage-horizontal spring (negative stiffness) and a vertical spring; the other is an energy-harvesting component with an array of parameter-differentiated piezoelectric cantilever beams. Aiming at the conflict between the structural dynamic stiffness approaching zero and broadening the effective working range, this paper establishes a dual-objective optimization function based on the Pareto principle on the basis of static analysis and uses the grid search method combined with actual working conditions to determine the optimal parameter combination. By establishing a multi-degree-of-freedom electromechanical coupling model, the harmonic balance method is used to derive analytical solutions, which are then verified by numerical simulations. The influence laws of external excitations and system parameters on vibration isolation and energy-harvesting performance are quantitatively analyzed. The results show that the optimized structure has an initial vibration isolation frequency below 2 Hz, with a vibration isolation rate exceeding 60% in the 3 to 5 Hz ultra-low frequency range and a minimum transmissibility of the order of 10⁻² (vibration isolation rate > 98%). The parameter-differentiated piezoelectric array effectively broadens the energy-harvesting frequency band, which coincides with the vibration isolation range. Synergistic optimization of both performances can be achieved by adjusting system damping, parameters of piezoelectric vibrators, and load resistance. This study provides a theoretical reference for the integrated design of low-frequency vibration control and energy recovery, and its engineering implementation requires further experimental verification. Full article

This study explores the application of Time Synchronous Averaging (TSA) for diagnosing Noise, Vibration, and Harshness (NVH) characteristics in an automotive sunroof assembly powered by a Direct Current (DC) motor. TSA is an advanced signal-processing technique that isolates periodic signals from noise, enhancing fault detection. The research identifies rotor misalignment as the dominant cause of excessive NVH. To address this, an experimental modification to the motor’s end washer was implemented, resulting in a significant reduction in vibration amplitudes at upper harmonics. These findings demonstrate TSA’s effectiveness in optimizing NVH characteristics for smaller rotating systems and demonstrate an effective approach for optimizing NVH performance in small-scale rotating systems, particularly in automotive applications. Full article

To improve both ride comfort and energy efficiency, this study proposes a semi-active suspension system equipped with an electromagnetic linear energy-regenerative magnetorheological damper (ELEMRD). The ELEMRD integrates a magnetorheological damper (MRD) with a linear generator. A neural network-based surrogate model was employed to optimize the key parameters of the linear generator for better compatibility with semi-active suspensions. A prototype was fabricated and tested. Experimental results show that with an excitation current of 1.5 A, the prototype generates a peak output force of 1415 N. Under harmonic excitation at 5 Hz, the no-load regenerative power reaches 11.1 W and 37.3 W at vibration amplitudes of 5 mm and 10 mm, respectively. An energy-regenerative magnetorheological semi-active suspension model was developed and controlled using a Linear Quadratic Regulator (LQR). Results indicate that, on a Class C road at 20 m/s, the proposed system reduces sprung mass acceleration and suspension working space by 14.2% and 7.5% compared to a passive suspension. The root mean square and peak regenerative power reach 49.8 W and 404.2 W, respectively. The proposed semi-active suspension also exhibits enhanced low-frequency vibration isolation, demonstrating its effectiveness in improving ride quality while achieving energy recovery. Full article

Piping systems can be analogized to the “vascular systems” of vessels, but their transmission characteristics often result in loud noises and large vibrations. The integration of flexible inserts within these piping systems has been shown to isolate and/or mitigate such vibrations and noise. In this work, a novel sandwich flexible insert (NSFI) was presented specifically to reduce the vibrations and noise associated with piping systems on vessels. In contrast to conventional flexible inserts, the NSFI features a distinctive three-layer configuration, comprising elastic inner and outer layers, along with a honeycomb core exhibiting a zero Poisson’s ratio. The dynamic characteristics, specifically axial impedance, of the fluid-filled NSFI are examined utilizing a fluid–structure interaction (FSI) four-equation model. The validity of the theoretical predictions is corroborated through finite element analysis, experimental results, and comparisons with existing literature. Furthermore, the study provides a comprehensive evaluation of the effects of geometric and structural parameters on the dynamic characteristics of the NSFI. It is worth noting that axial impedance is significantly affected by these parameters, which suggests that the dynamic characteristics of the NSFI can be customized by parameter adjustments. Full article