Search Results (416)

The deployment of wall-climbing robotic systems plays an important role for executing inspection and maintenance tasks in high-risk environments and minimizing the risk to operators tasked with the inspection. Conventional adhesion techniques, such as magnetic, suction, and dry adhesives, encounter significant challenges when applied to diverse surface types. This study presents a four-wheeled robotic platform utilizing dual electric ducted fans (EDFs) to produce adjustable adhesion forces, facilitating uninterrupted movement from horizontal to vertical planes. A comprehensive multibody dynamics model constructed using MSC Adams analyzed wheel–surface interaction, thrust forces, and system stability during transitional phases, revealing essential force parameters for stable vertical operation and determining minimum thrust levels required to sustain four-point contact during orthogonal transitions. These findings informed thrust distribution optimization between the two EDF units to reduce rotational effects while ensuring sufficient safety margins during the ground to vertical wall transition. The findings also allowed for appropriate thrust application ensuring the generation of the required normal force distribution at wheel contact interfaces during vertical movement. A physical prototype was developed and experimentally validated, demonstrating dependable adhesion and maneuverability across a spectrum of orientations and highlighting the efficacy of simulation-driven design for thrust-based adhesion systems. Full article

Inertial Measurement Units (IMUs) enable portable, multibody motion capture in diverse environments beyond the laboratory, making them a desirable choice for diagnosing mobility disorders and supporting rehabilitation in clinical or home settings. However, challenges associated with IMU measurements, including magnetic distortions and errors due to integration drift, complicate their broader use for motion capture. In this work, we propose a tightly coupled motion-capture approach that directly integrates IMU measurements with multibody dynamic models via an iterated extended Kalman filter to simultaneously estimate the system’s kinematics and kinetics. By enforcing the complete multibody system dynamics and utilizing only accelerometer and gyroscope data, our method accurately estimates joint kinematics and kinetics. Our algorithm is designed to fuse different sensor data, such as optical motion-capture measurements and joint torque readings, to further enhance estimation accuracy. We validated our approach using highly accurate ground-truth data from a 3-degree-of-freedom pendulum and a 6-degree-of-freedom collaborative robot. We demonstrate a maximum root-mean-square difference of 3.75° in the pendulum’s computed joint angles with respect to the marker motion-capture inverse kinematics. For the robot, we observed a maximum joint angle root-mean-square difference of 3.24° with respect to the joint encoders, while the maximum joint angle root-mean-square difference of the optical motion-capture inverse kinematics with respect to the encoders was 1.16°. With regard to kinetic estimates, we report a maximum joint torque root-mean-square difference of 3.02 Nm in the pendulum with respect to the marker motion-capture inverse dynamics and 4.27 Nm in the robot relative to its joint torque sensors. Full article

This study presents a design and performance analysis of a tethered-net-based space debris capture system using multibody dynamic simulation. The increasing accumulation of space debris in Low Earth Orbit (LEO) necessitates reliable capture mechanisms capable of handling non-cooperative targets with positional and velocity uncertainties. To address this, a node-based net model was developed, in which the net structure is represented by interconnected spring-damper elements to capture large deformation and nonlinear behavior. The dynamic analysis was conducted using the commercial multibody dynamics software RecurDyn, considering key design parameters such as ejection distance, angle, and velocity. The results show that the net deployment characteristics are strongly influenced by ejection conditions. An optimal configuration was identified at an ejection angle of 18° and an ejection velocity of 10 m/s, satisfying both deployment performance and the allowable tension limit of 300 N. The proposed capture mechanism enables the net to fully pass over the target before activating a winch to reel in the pulling rope, thereby minimizing impact forces and improving capture stability. Furthermore, the capture performance was quantitatively evaluated under relative position and velocity uncertainties. The maximum allowable lateral velocity was derived as a function of the available capture margin, yielding approximately 1.25 m/s without positional error and 0.30 m/s with a 1 m positional offset. These results provide practical design guidelines for net-based space debris capture systems and demonstrate the robustness of the proposed approach under realistic operational conditions. Full article

Over the course of long-term operation, wear to moving parts can significantly affect the dynamic behavior, reliability and service life of landing gear retraction and extension systems. The primary innovation of this paper is the proposal of a multi-body rigid-body dynamics modeling method for LGRES that accounts for irregular wear clearances, along with an analysis of its dynamic response under different system parameters. First, an exact dynamic model of the LGRES with joint clearance is developed. Secondly, the Archard wear model is introduced to characterize the wear evolution of the joint surfaces. Finally, the dynamic behavior of the mechanism under different wear cycles, initial clearance values, and drive speeds is compared to analyze the impact of these system parameters on wear characteristics. The results indicate that as these system parameters increase, wear significantly amplifies the impact forces on the joint and further exacerbates wear between the hinge pin and the bearing, as well as motion errors. Full article

Conventional thrust vector control nozzles are severely constrained by a single-pivot deflection paradigm, which induces asymmetric shock reflections and adverse boundary layer separation at large angles. Multi-segmented serial configurations offer a promising alternative to overcome these limitations by distributing the total deflection across multiple joint interfaces, thereby achieving large terminal angles and smooth flow-path curvatures. To realize such a configuration, this study draws inspiration from the abdominal bending mechanism of the damselfly Ischnura elegans during mating wheel formation. Real-time video recording and morphological characterizations identified abdominal segments VI and VII as critical for high-amplitude bending under load. Finite element analysis under muscular actuation elucidated the biomechanical synergy, which was rigorously verified through mesh convergence and material property sensitivity checks. Inspired by this biological system, a multi-segmented nozzle configuration incorporating discrete elastic elements and a centralized cable-driven layout was designed and evaluated using multibody dynamics and computational fluid dynamics. The nozzle achieved a continuous 61.20° deflection within 8 s under subsonic exhaust conditions, successfully stabilizing periodic supersonic shock structures and completely suppressing adverse boundary layer separation. These findings turn biological bending into a thrust vectoring method, giving insights for next-generation agile aerospace propulsion systems. Full article

This paper aims to develop an on-board shock absorber detection method for general aviation aircraft. The effects of common gas and oleo leakage are analyzed in this paper. Based on the principle of landing gear dynamics, it is found that gas leakage and oleo leakage would mainly affect air spring force of shock absorbers in various ways. A rigid–flexible coupled landing gear multi-body system (MBS) model is developed by considering strut flexibility, aiming to offer more accurate simulated responses. A database is developed that considers common leakage faults and typical landing conditions using the developed landing gear model. A deep learning model is proposed in this paper. The proposed model is trained and tested using the database simulated from the rigid–flexible coupling landing gear model. The proposed method demonstrates robust detection performance, achieving over 95% precision for most fault types. This work provides a practical, sensor-efficient solution for real-time health monitoring of landing gear shock absorbers, contributing to improved maintenance strategies and operational safety for general aviation aircraft. As this is a preliminary feasibility study, full validation requires future drop tests or instrumented flight tests. Full article

Extreme orbital thermal cycling and temperature-dependent clearance nonlinearity make it difficult to predict contact–impact, stick–slip, and bifurcation responses of flexible deployable space structures with sufficient stability, accuracy, and computational efficiency. An Adaptive Dissipation–Precision Coordinated Multi-Scale Implicit Integration Algorithm (ADPC-MSIIA) is proposed. First, an absolute nodal coordinate formulation (ANCF)-based thermo-mechanical clearance-joint model with thermal-viscosity-modified contact and frictional/impact heat feedback is established; second, a dual-time-scale implicit integration scheme with dual-$\alpha$ stability–dissipation control and third-order compensation is developed; finally, numerical validation is performed using a linear single-degree-of-freedom (SDOF) benchmark, a temperature-dependent clearance impact oscillator, finite-element and published benchmark comparisons, and a deployable annular truss antenna case. Simulation results show that ADPC-MSIIA achieves a high-frequency spectral radius of $0.867$, an effective convergence order of $2.98$, a maximum contact force error of $3.1\%$, and a $51.7\%$ reduction in the global cumulative error compared with the generalized-$\alpha$ method. This study contributes to knowledge by linking temperature-driven clearance evolution, frictional heat feedback, and adaptive numerical dissipation within a unified framework for predicting non-smooth thermo-mechanical deployment dynamics of large flexible space structures with clearance joints. Full article

As a core crushing equipment in mining, building materials, and related industries, the cone crusher relies heavily on the optimal design and health state prediction of its mantle liner to enhance equipment reliability and reduce maintenance costs. This paper proposes a comprehensive approach integrating dynamic modeling, intelligent optimization, and health prognosis. First, a virtual prototype model is established based on laminated crushing theory and multibody dynamics simulation to analyze the motion and force characteristics of the mantle liner. Second, for the two key parameters—counterweight mass and motor speed—an improved butterfly optimization algorithm (IBOA) incorporating Cauchy mutation and an adaptive weight is proposed to achieve efficient global optimization. Furthermore, vibration signal features are extracted at different wear stages; a comprehensive health indicator curve is constructed by combining PCA dimensionality reduction with adaptive feature fusion (ASFF), and the Weibull degradation model is employed for life extrapolation prediction. Finally, fuzzy C-means (FCM) clustering is applied to autonomously partition the health states. Parameter optimization reduces the standard deviation of the force acting on the mantle liner by approximately 15.4%, markedly improving system operational stability. Health prognosis reveals that the liner enters a faulty state after 785 h, and the health condition is effectively classified into four stages: healthy, good, degraded, and faulty. The results demonstrate that the proposed optimization and health prognosis methods can effectively improve the operational efficiency and reliability of cone crushers, exhibit favorable engineering applicability, and provide a quantitative basis for condition monitoring and maintenance decision-making. Full article

An efficient hybrid modeling framework is developed for the dynamic analysis of offshore wind turbines (OWTs) by coupling an aero–servo–elastic rotor–nacelle superelement with a hydroelastic substructure. The complex rotor–nacelle dynamics are condensed into a reduced-order 14-DOF representation through a modal-based multibody formulation, while retaining blade deformation, spinning effects, nonlinear aerodynamic loading, and active servo controls. Its interface compatibility at the nacelle enables the coupling with either numerical or physical substructures, establishing a unified basis for system hybrid formulation, co-simulations, and real-time hybrid simulations. The validity of the superelement is verified by comparing the resulting fully coupled modal model against OpenFAST, demonstrating high consistency in time-domain responses. As a demonstration, the verified superelement is further coupled with a 1D finite element model of the supporting structure (tower–monopile substructure) to form a hybrid model, enabling accurate force analysis of the OWT structure. Dynamic analyses of the IEA 10 MW OWT reveal that while the blade flapwise responses and the operation-related edgewise responses are 1P-dominated, tower side–side responses and idling-related tower fore–aft and blade edgewise responses manifest at their corresponding resonance frequencies. The maximum displacement and maximum bending moment envelopes vary monotonically with height. Instead, the maximum stress envelope possesses high values in the mid-lower sections of the tower. This high-stress region undergoes a spatial shift driven by the blade feathering mechanism. Full article

The optimisation design of agricultural machinery is shifting from offline, experience-driven engineering towards adaptive, data-driven, and closed-loop intelligent optimisation. Conventional approaches based on computer-aided engineering (CAE), empirical testing, mathematical modelling, and static multi-objective optimisation have provided an important engineering foundation, but they remain limited under unstructured field conditions involving soil heterogeneity, crop variability, climatic disturbance, and nonlinear machinery–environment interactions. This review systematically examines the evolution of intelligent optimisation design for agricultural machinery from conventional simulation-based methods to artificial intelligence (AI)- and digital twin (DT)-enabled paradigms. First, mathematical modelling, response surface methodology, discrete element method (DEM), computational fluid dynamics (CFD), multi-body dynamics (MBD), heuristic algorithms, and early AI-assisted surrogate optimisation are reviewed to clarify their contributions and limitations. Second, frontier enabling technologies are analysed, including agriculture-specific large models, generative AI, lightweight edge intelligence, deep reinforcement learning (DRL), embodied AI, federated learning (FL), and privacy-preserving computing. Third, system-level applications integrating DT and AI are discussed, with emphasis on full-lifecycle machinery optimisation, device–edge–cloud collaborative control, multi-agent fleet coordination, predictive maintenance, and Agriculture 5.0-oriented intelligent equipment systems. Key deployment bottlenecks are further identified, including sim-to-real inconsistency, virtual–physical mismatch in DTs, edge-side trade-offs among accuracy, latency, energy consumption, and cost, insufficient validation standards, and economic adoption barriers. Finally, a 2025–2030 roadmap is proposed, highlighting large-model–DT closed loops, control biomimetics, green low-carbon optimisation, and trustworthy human–machine symbiosis for sustainable Agriculture 5.0. Full article

Electric vehicles introduce new considerations for pedestrian safety because their lower operating noise at low speeds may reduce pedestrian detectability in urban traffic environments. This study proposes a simulation-based integrated active–passive pedestrian protection framework for electric vehicles by linking automatic emergency braking, active hood deployment, and post-crash head injury assessment. A total of 688 valid pedestrian–vehicle crash records from the National Highway Traffic Safety Administration database were analyzed, and 5 representative pedestrian crash scenarios were constructed through clustering-informed scenario screening and a benchmark pedestrian AEB scenario. The scenarios were reconstructed in a PreScan–Simulink co-simulation environment to evaluate a time-to-collision-based AEB strategy, while the active hood system was assessed using multi-body dynamics simulation and finite element head impact analysis. The AEB results showed that three scenarios were avoided before pedestrian contact, whereas two remained unavoidable, with residual impact speeds of approximately 31.5 km/h and 46 km/h. The hood reached a stable deployed posture within approximately 0.1 s under the modeled conditions. The HIC₁₅ results at eight selected impact points showed that speed reduction and hood deployment generally reduced head injury metrics, but full compliance with the reference HIC₁₅ threshold of 1000 was not achieved at all points. These findings suggest that the proposed strategy can improve simulated pedestrian head protection performance under selected electric vehicle crash scenarios, while further structural optimization, experimental validation, and cost–benefit assessments are still required. Full article

Wheeled inverted-pendulum robots with movable upper structures and variable payloads exhibit configuration-dependent equilibrium drift and payload-dependent dynamic variation, which complicate balancing control. This paper proposes a gain-scheduled controller–observer framework for payload-adaptive balancing of such a robot. First, the multi-body system is reduced to a control-oriented equivalent inverted-pendulum model through center-of-mass lumping, from which a parameter-varying linearized model is established. On this basis, an H∞ state-feedback controller with input constraints is synthesized in a linear matrix inequality (LMI) framework, and an augmented-state observer is designed to estimate the residual equilibrium offset induced by payload variation. To improve robustness over the operating range, the frozen-point design is extended to a sampled-model multi-model synthesis framework, and gain scheduling is implemented with respect to the measurable arm angle. Nonlinear Simscape simulations show that the proposed method can recover balance at representative fixed operating points, compensate effectively for load-induced equilibrium drifts, and preserve stable balancing performance under slow arm-angle variation. Quantitative comparisons with an LQR baseline further support the effectiveness of the proposed framework for payload-adaptive balancing control. Full article

To improve machining accuracy, a multi-axis linkage dimensional error calculation model was established based on multi-body system theory and validated by the experiment. A comprehensive sensitivity analysis for a CNC machining center was conducted. The results reveal that multi-axis machining errors depend not only on the machine’s structural dimensions but also dynamically vary with the axes’ motion positions. Specifically, X-axis machining errors are most sensitive to δx(z), δx(y), δx(x), εy(y). Y-axis machining error is more sensitive to δy(z), δy(y), and δy(x). Z-axis machining error is more sensitive to δz(z), δz(y), and δz(x). The practical implications of these findings identify the specific dimensional errors that most significantly impact overall accuracy, providing a targeted theoretical reference to prioritize the compensation of key dimensional errors and effectively enhance machine tool precision. Full article

Plunger pumps are widely used in high-pressure and high-flow applications and exhibit strong adaptability to different fluid media. In addition to the interaction between the valve and the fluid, a potential coupling effect may exist between the flow characteristics of the pump and the electromagnetic characteristics of the motor. To investigate the electromagnetic–mechanical–hydraulic coupling effect in a motor–pump system, a transient coupled dynamics model integrating electromagnetic fields (EMF), multi-body dynamics (MBD), and computational fluid dynamics (CFD) is developed. The motion of the valve is incorporated into the model through dynamic mesh and user-defined function (UDF) techniques. The different physical models are coupled through torque, speed, force, and displacement. Based on the proposed model, the coupling characteristics of the system are analyzed. The results show that pulsating components associated with the reciprocating frequency appear in both the rotational speed and torque of the motor, resulting in fluctuations of approximately 2.11% in speed and 29.57% in torque. These pulsations are also reflected in the stator current spectrum. In addition, the valve motion at different crank angles and the flow patterns in the pump chamber are analyzed. The electromagnetic characteristics of the motor have a limited influence on the internal flow behavior of the pump. Full article

The use of 3D printing in robotics enables lightweight, customized, and geometrically complex structures, but the resulting structural compliance challenges accurate dynamic prediction. Traditional rigid multibody models often neglect structural deformations and vibrations that can critically affect performance and control. This work presents initial advances toward a computational framework for flexible multibody dynamics of 3D-printed robotic structures. A two-link mechanism is modeled in MATLAB Simscape Multibody under both rigid and flexible assumptions, and parametric analyses are conducted to assess the influence of geometry, mass distribution, and stiffness on system dynamics. The proposed framework is formulated to accommodate reduced-order and data-driven modeling approaches for efficient simulation and analysis of flexible robotic mechanisms. Full article