Search Results (74)

Modern logistics and manufacturing environments simultaneously demand mobility platforms that are compact enough to navigate narrow aisles and powerful enough to transport oversized or heavy components. We previously developed a compact Steering–Drive–Suspension (SDS) module that integrates steering, in-wheel drive, and suspension within a single wheel envelope, achieving $\pm {90}^{\circ }$ wide-angle steering with a single actuator. The present paper extends that hardware-centric work by treating the two-wheel (2WD) configuration assembled from two SDS modules as the unit module of the platform, building a four-wheel (4WD) operation by coupling two such 2WD units, and developing a unified balance and impedance-based control scheme. We derive a cart–pole inverted-pendulum model for the 2WD configuration and a planar 2-DOF bicycle model for the coupled and cooperative configurations, with full controllability proof and quantitative LQR robustness margins. Three Python 3.12 based scenarios validate the framework: (i) a 2WD inverted-pendulum tracking task, (ii) a forward and lateral relocation maneuver compared across SDS Crab, Ackermann, and four-wheel-steering modes, and (iii) cooperative transport of a $100\mathrm{kg}$ steel plate by two impedance-coupled 2WD units. Across all scenarios the proposed controllers achieve sub-centimetre tracking gap, pitch deviation within $\pm 2^{\circ }$, and well-damped cooperative behavior without payload sloshing. The results substantiate the central design claim that the SDS module’s compactness enables a single hardware platform to act simultaneously as an autonomous small-payload mover, a building block of a 4WD platform, and a cooperative agent for oversized loads. Full article

Top-heavy industrial towers, which carry large, concentrated masses of equipment at upper levels and feature open lower stories, are vertically irregular by design and tend to amplify seismic displacement and acceleration demands near the tower top. Although tuned mass dampers (TMDs) have been studied extensively for buildings, bridges and chimneys, their application to this particular class of slender industrial towers—where production-equipment vibration tolerance, retrofit accessibility and limited downtime drive the design—has received little dedicated attention. This paper reports a focused numerical investigation of seismic response mitigation for a 101.2 m molten-asphalt granulation tower retrofitted with a single pendulum-type TMD. A three-dimensional coupled finite element (FE) model was constructed in ABAQUS using C3D8R solid elements for the reinforced-concrete shaft and T3D2 truss elements for the embedded reinforcement; modal analysis returned a fundamental frequency of 0.912 Hz and a torsional-to-translational period ratio of 0.65, indicating a translational-mode-dominated response. Elastic time-history analyses under the El Centro and Taft records together with a code-spectrum-compatible synthetic accelerogram show that a pendulum TMD with mass ratio μ = 2.5%, tuning frequency offset Δf = 5% and damping ratio ξ = 10%—installed at the uppermost equipment level guided by the modal-displacement criterion—reduces the peak top displacement, peak top acceleration and peak base shear by roughly 23%, 23% and 22%, respectively, in both principal directions. The controlled top acceleration falls comfortably below the 2.94 m/s² operational tolerance of the on-tower melting equipment. To address the rationality of the chosen TMD parameters, a single-variable parametric sensitivity study spanning μ ∈ [1%, 5%], ξ ∈ [5%, 15%] and Δf ∈ [0%, 10%] is performed on an equivalent reduced model that captures the qualitative parameter-response trends; the chosen baseline values lie inside a stable performance plateau and are shown to be a balanced compromise among the three response measures. The principal contribution of the work is, therefore, (i) a complete TMD retrofit framework—modal-based placement, parameter design, coupled FE assembly and multi-record verification—adapted to top-heavy industrial towers, and (ii) qualitative evidence, supported by a sensitivity scan, with a robust proposed parameter set for small-to-moderate detuning. The study is restricted to elastic time-history analyses under frequent-earthquake-level excitation, three ground-motion records and a fixed-base assumption; nonlinear response, larger record sets and soil–structure interaction effects are explicitly identified as scope limitations and are left for follow-up work. Full article

Fishing buoys are confronted with the problems of insufficient power supply and loss. To address these challenges, a small innovative fishing buoy equipped with an internal pendulum and powered by wave energy is designed. Its structural shape enables it to maintain a stable surfing state, thereby facilitating more efficient wave energy capture. Free decay tests and wave energy capture tests were conducted via numerical and experimental simulations. A mathematical model was proposed and validated using experimental data. Through free decay tests, the natural periods of the device in heave and pitch motions were obtained, which ranged from 1.0 to 1.42 s. The results of the wave energy capture tests indicate that the device can capture approximately 300 mW of electrical power under small-wave conditions. Additionally, the mechanical damping coefficient of the buoy-pendulum system was estimated to be 0.15 Nms/rad, and the mechanical efficiency of the wave energy converter was 15%. Preliminary optimization was carried out through numerical model simulation, which is conducive to the refined design of the device. This study provides a reference for the development and design of similar wave energy conversion devices. Full article

Force rebalance-type accelerometers are mainly used in inertial navigation systems of aircraft, and the characterization of the resulting squeeze film damping (SFD) is essential for estimating dynamic response characteristics of these accelerometers. In this study, a methodology for modeling SFD and experimentally verifying this model for force rebalance-type accelerometers is presented. Modeling of the SFD effect involves determining an effective damping coefficient as a function of pendulum displacement. Damping force and pressure distribution due to SFD are obtained for a range of pendulum displacements via finite element analysis (FEA). The accelerometer is modeled as both an open- and closed-loop system, where an identified damping model for SFD is also used. The open-loop model is verified by comparing the step response of the system, and the closed-loop model is verified by comparing the frequency and shock responses of the system via simulations and experiments. Simulation and test results of both open- and closed-loop systems show close agreement. The presented results indicate that in systems with similar dimensions and material properties, damping due to SFD in a force rebalance accelerometer can be accurately modeled as a function of pendulum displacement using the method described in this research study. Full article

The driven damped pendulum is a foundational model in nonlinear dynamics, with applications ranging from Josephson junctions to MEMS oscillators. Conventional dimensionless treatments obscure the common physical origin of damping and driving in the inertia coefficient. Here we restore this dependence and establish inertia as a master control parameter governing stability, resonance, and bifurcations. Through linear analysis and perturbation theory, we derive universal scaling laws revealing a fundamental dichotomy: quantities at resonance—peak amplitude and nonlinear frequency shift—are independent of inertia due to exact algebraic cancellation between the inertia dependence of the effective driving amplitude and effective damping coefficient. Off resonance, however, amplitude scales inversely with inertia, bandwidth narrows proportionally, and the bistability threshold exhibits an even steeper dependence. A critical inertia separates underdamped from overdamped regimes, yielding non-monotonic relaxation times that maximize attractor memory at extreme inertia values. These scaling laws provide design guidelines: low inertia promotes broadband response for energy harvesting; high inertia suppresses off-resonant vibrations for precision timing and quantum applications. By establishing inertia as a physically realizable path through parameter space, this work unifies disparate phenomena and provides a framework for understanding stability in inertial-driven systems. Full article

This study presents a passive mechanical filter designed to enhance sub-Hertz Venusquake detection by shaping the seismic transfer path. The mechanism uses a tunable, high-Q pendulum mounted inside a cylindrical enclosure on a three-ring gimbal to ensure self-leveling and alignment in gravity on uneven terrain. Unlike approaches that rely on broadband digitization and require active control and a stable power supply, this housing–gimbal mechanism performs mechanical filtering for sub-Hz signal amplification and higher frequency attenuation without power. Response spectrum analysis shows that the transmissibility can be tuned to achieve peak sensitivities in the 0.5–0.8 Hz range. When tuned to 50–55 mm pendulum length and under assumed undamping, the pendulum-mounted mechanism improves detectability at best by 10–100× relative to a bare sensor for moderate magnitude ($M_s$ = 3–6) in a 12 h observation window, with signal-to-noise (SNR) ratio of 3, and amplitude spectrum density (ASD) of 10⁻⁸ m/s²/√Hz. Furthermore, we extrapolate that the predicted minimum detectable event rates follow $N_m^{min}\propto {\left(\mathrm{S}\mathrm{N}\mathrm{R}\right)}^{1.2}{\left(\mathrm{A}\mathrm{S}\mathrm{D}\right)}^{1.2}{f}_s^{0.6}$, where $f_s$ is the quake wave frequency. The damping ratio, considering both structural damping and viscous drag, is estimated to be in the order of 10⁻³ to 10⁻². A probabilistic sensitivity analysis is performed to account for the inherent uncertainty in the spectral mismatch between the narrowband sub-Hz resonance of the designed mechanical filter and the peak frequencies of seismic events; the derived probability model suggests strategies for improving the detection probability in the 0.01–1 Hz range. Full article

Accurate identification of dynamic parameters, specifically natural frequency and damping ratio, is critical for optimizing the disturbance rejection performance of laser level self-leveling mechanisms. However, traditional Finite Element Analysis (FEA) often struggles to quantify micro-friction damping, while contact measurement methods introduce added mass interference. To address these challenges, this paper proposes an integrated framework combining Pulse-Window Software Lock-in (PWSL) sensing with a data-driven model updating strategy. Initially, a rigid-body dynamic model theoretically predicted a natural frequency (f_sim) of 2.987 Hz and a damping ratio (ζ_sim) of 0.1255. To acquire authentic responses, a non-contact Position Sensitive Detector (PSD) system was developed. The custom PWSL algorithm leverages the laser’s 10 kHz carrier to extract high-fidelity displacement signals, effectively suppressing broadband noise despite embedded hardware limitations. Experimental results demonstrated that the measured frequency (f_exp = 2.861 Hz) aligned well with predictions (4.22% error). In contrast, the measured damping ratio (ζ_exp = 0.1435) exceeded the simulation value by 14.34%, quantitatively revealing the energy dissipation caused by unmodeled bearing friction. Based on this disparity, the FEA model was inversely updated by introducing an equivalent friction coefficient, successfully reducing the damping prediction error to 0.97%. This study establishes a high-fidelity updated model, providing a reliable basis for the refined design of precision pendulum instruments. Full article

Extreme events often provoke critical structural vibrations, compromising building performance and resilience. Particle impact dampers (PIDs) are widely recognized as effective passive vibration control devices; however, their nonlinear dynamics and unpredictable particle motion limit adaptability under uncertain hazard conditions. This study introduces a pendulum-type PID configuration designed to enhance controllability and energy dissipation by tuning particle frequency through suspension. Both the primary structure and particles are modeled as pendulums, and their interactions are analyzed under free and forced vibration scenarios. A comprehensive parametric study reveals that increasing the frequency ratio (F.R), defined as the ratio of particle natural frequency to that of the structure, significantly improves damping efficiency. At F.R = 5.0, with clearance d = 0.1 and restitution coefficient e = 0.2, the system achieves an average damping ratio of approximately 0.28 in free vibrations. Under resonant forced vibration, the proposed damper reduces amplitude ratios to below 0.3 compared to undamped conditions. The results confirm that lower clearance and restitution values consistently yield superior damping performance. The findings demonstrate that the pendulum-type PID offers a customizable, cost-effective solution for mitigating structural vibrations, thereby contributing to risk-informed and resilience-oriented design strategies for building structures exposed to extreme events. Full article

Guided by principles of symmetry to achieve a proper balance among model consistency, accuracy, and complexity, this paper proposes a new approach for identifying the unknown parameters of nonlinear one-degree-of-freedom mechanical systems using nonlinear regression methods. To this end, the steps followed in this study can be summarized as follows. Firstly, given a proper set of input time histories and a virtual model with all parameters known, the dynamic response of the mechanical system of interest, used as output data, is evaluated using a numerical integration scheme, such as the classical explicit fixed-step fourth-order Runge–Kutta method. Secondly, the numerical values of the unknown parameters are estimated using the Levenberg–Marquardt nonlinear regression algorithm based on these inputs and outputs. To demonstrate the effectiveness of the proposed approach through numerical experiments, two benchmark problems are considered, namely a mass-spring-damper system and a simple pendulum-damper system. In both mechanical systems, viscous damping is included at the kinematic joints, whereas dry friction between the bodies and the ground is accounted for and modeled using the Coulomb friction force model. While the source of nonlinearity is the frictional interaction alone in the first benchmark problem, the finite rotation of the pendulum introduces geometric nonlinearity, in addition to the frictional interaction, in the second benchmark problem. To ensure symmetry in explaining model behavior and the interpretability of numerical results, the analysis presented in this paper utilizes five different input functions to validate the proposed method, representing the initial phase of ongoing research aimed at applying this identification procedure to more complex mechanical systems, such as multibody and robotic systems. The numerical results from this research demonstrate that the proposed approach effectively identifies the unknown parameters in both benchmark problems, even in the presence of nonlinear, time-varying external input actions. Full article

This study presents a simulation-based framework for PID controller design in strongly nonlinear dynamical systems. The proposed approach avoids system linearization by directly minimizing a performance index using metaheuristic optimization. Three strategies—Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), and their hybrid combination (PSO-GWO)—were evaluated on benchmark systems including pendulum-like, Duffing-type, and nonlinear damping dynamics. The chaotic Duffing oscillator was used as a stringent test for robustness and adaptability. Results indicate that all methods successfully stabilize the systems, while the hybrid PSO-GWO achieves the fastest convergence and requires the fewest cost function evaluations, often less than 10% of standalone methods. Faster convergence may induce aggressive transients, which can be moderated by tuning the ISO (Integral of Squared Overshoot) weighting. Overall, swarm-based PID tuning proves effective and computationally efficient for nonlinear control, offering a robust trade-off between convergence speed, control performance, and algorithmic simplicity. Full article

The vibration of the combine harvester header assembly directly affects harvesting efficiency and operational quality. To address the insufficient dynamic characterization of the cantilever conveying trough under complex field excitations, this study systematically analyzes the vibration response characteristics of the header assembly under multi-source coupled excitation through field experiments and theoretical modeling. Acceleration sensors arranged at three measurement points on the header bottom collected vibration data, revealing that the dominant vibration frequency of the header has a deterministic harmonic relationship with the threshing drum’s operating frequency (3rd harmonic on the left side, 1.5th harmonic on the right side), demonstrating dynamic coupling effects within the integrated system. Through acceleration response analysis at four symmetric measurement points on the connection, the external excitation force was quantified as a sinusoidal function correlated to the feed quantity (F = 1094.4 sin(50πt/3)). A damped pendulum model of the cantilever conveying trough was established using the Lagrange method. Validation results show that the error between the predicted steady-state swing amplitude and measured values is only 1.11–4.3%, confirming the effectiveness of this simplified model in characterizing the system’s steady-state response. This research provides a theoretical foundation and methodological support for dynamic characterization, parameter optimization, and stability control of the cantilever header system in combine harvesters. Full article

Friction pendulum bearings (FPBs) can effectively improve the seismic performance of bridges in class II sites. However, for class III and IV sites, using only FPBs under large earthquakes can easily cause significant displacement of the main beam, leading to beam collapse. In order to improve the seismic performance of railway simply supported beam bridges under poor geological conditions, this study proposes a new type of combined seismic isolation device, which extends the vibration period of the bridge through hyperbolic spherical bearings and provides energy dissipation through circular steel dampers. Based on the relevant design parameters of the steel damping and the bearing, their mechanical models are calculated and superimposed to obtain the mechanical model of the combined seismic isolation device, and the model is verified through experiments. Then, a bridge model using this device is established using OpenSees, and the effects of pier height, pier height difference, and far-field long-period seismic motion on pier bottom bending moment and support displacement under class III and IV sites are analyzed. The damage status and indicators of the combined device were provided, and the fragility of the device was analyzed. The results show that under design displacement (300 mm), the hysteresis curves of the combined seismic isolation device are with good consistency in mechanical properties in all directions and strong energy dissipation capacity, and the applicable pier height range of the device is determined under class III and IV sites. This study can provide a reference for the seismic isolation design and practical railway simply supported beam bridges. Full article

Self-oscillating systems are capable of transforming ambient energy directly into mechanical output, and exploring novel designs is of great value for energy harvesters, actuators, and engine applications. The inspiration for this study is drawn from the four-stroke engine; we designed a new self-rotating engine formed by a turnplate, a hinge, and an LCE fiber, operating with steady illumination applied. To analyze its rotation dynamics, a nonlinear theoretical framework was formulated constructed with the dynamic LCE model as a framework. The central discovery is that the light-driven LCE engine can operate in three distinct states under steady illumination—static equilibrium, pendulum-like oscillation and sustained self-rotation—switching between them through a supercritical Hopf bifurcation. The persistence of both the pendulum and rotary motions stems from an energy balance in which the positive work produced by photo-induced contraction of the LCE fiber is exactly offset by damping dissipation, while oscillation amplitude and rotation frequency are strongly governed by light intensity, contraction coefficient, damping coefficient, spring constant and turntable radius. Compared with many previously reported self-oscillating designs, the present self-rotating engine is distinctive for its lightweight and simple configuration, tunable size, and rapid operation. These features enable compact integration and broaden its potential applications in micro-scale systems and devices. The advancement in artificial muscles, medical instruments and micro sensors is strongly promoted by this, making it possible to create devices that are both smaller in size and superior in functionality. Full article

In this study, a nonlinear dynamic model is developed to examine the stability and vibration behavior of a self-balancing electric Segway operating over irregular stochastic terrains. The Segway is treated as a three-degrees-of-freedom cart–inverted pendulum system, incorporating elastic and damping effects at the wheel–ground interface. Road irregularities are generated in accordance with international standard using high-order filtered noise, allowing for representation of surface classes from smooth to highly degraded. The governing equations, formulated via Lagrange’s method, are transformed into a Lorenz-like state-space form for nonlinear analysis. Numerical simulations employ the fourth-order Runge–Kutta scheme to compute translational and angular responses under varying speeds and terrain conditions. Frequency-domain analysis using Fast Fourier Transform (FFT) identifies resonant excitation bands linked to road spectral content, while Kernel Density Estimation (KDE) maps the probability distribution of displacement states to distinguish stable from variable regimes. The Lyapunov stability assessment and bifurcation analysis reveal critical velocity thresholds and parameter regions marking transitions from stable operation to chaotic motion. The study quantifies the influence of the gravity–damping ratio, mass–damping coupling, control torque ratio, and vertical excitation on dynamic stability. The results provide a methodology for designing stability control systems that ensure safe and comfortable Segway operation across diverse terrains. Full article

Parkinson’s disease (PD) is characterized by motor symptoms, with key diagnostic features, such as rigidity, traditionally assessed through subjective clinical scales. This study proposes a novel hybrid framework integrating model-driven biomechanical features (damping ratio, decay rate) and data-driven statistical features (maximum detail coefficient) from wearable sensor data during a modified pendulum test to quantify shoulder girdle rigidity objectively. Using weak supervision, these features were unified to generate robust labels from limited data, achieving a 10% improvement in PD/healthy control classification accuracy (0.71 vs. 0.64) over data-driven methods and matching model-driven performance (0.70). The damping ratio and decay rate, aligning with Wartenberg pendulum test metrics like relaxation index, revealed velocity-dependent aspects of rigidity, challenging its clinical characterization as velocity-independent. Outputs correlated strongly with UPDRS rigidity scores (r = 0.78, p < 0.001), validating their clinical utility as novel biomechanical biomarkers. This framework enhances interpretability and scalability, enabling remote, objective rigidity assessment for early diagnosis and telemedicine, advancing PD management through innovative sensor-based neurotechnology. Full article