Search Results (4,210)

The estimation of multijoint angles is of great significance in the fields of lower limb rehabilitation, motion control, and exoskeleton robotics. Accurate joint angle estimation helps assess joint function, assist in rehabilitation training, and optimize robotic control strategies. However, estimating multijoint angles in different movement patterns, such as walking, obstacle crossing, squatting, and knee flexion–extension, using surface electromyography (sEMG) signals remains a challenge. In this study, a model is proposed for the continuous motion estimation of multijoint angles in the lower limb (CB-TCN: temporal convolutional network + convolutional block attention module + temporal convolutional network). The model integrates temporal convolutional networks (TCNs) with convolutional block attention modules (CBAMs) to enhance feature extraction and improve prediction accuracy. The model effectively captures temporal features in lower limb movements, while enhancing attention to key features through the attention mechanism of CBAM. To enhance the model’s generalization ability, this study adopts a sliding window data augmentation method to expand the training samples and improve the model’s adaptability to different movement patterns. Through experimental validation on 8 subjects across four typical lower limb movements, walking, obstacle crossing, squatting, and knee flexion–extension, the results show that the CB-TCN model outperforms traditional models in terms of accuracy and robustness. Specifically, the model achieved R² values of up to 0.9718, RMSE as low as 1.2648°, and NRMSE values as low as 0.05234 for knee angle prediction during walking. These findings indicate that the model combining TCN and CBAM has significant advantages in predicting lower limb joint angles. The proposed approach shows great promise for enhancing lower limb rehabilitation and motion analysis. Full article

To address the issue of suboptimal clustering performance arising from the limitations of distance measurement in traditional trajectory clustering methods, this paper presents a novel trajectory clustering strategy that integrates the bag-of-words model with non-convex metric learning. Initially, the strategy extracts motion characteristic parameters from trajectory points. Subsequently, based on the minimum description length criterion, trajectories are segmented into several homogeneous segments, and statistical properties for each segment are computed. A non-convex metric learning mechanism is then introduced to enhance similarity evaluation accuracy. Furthermore, by combining a bag-of-words model with a non-convex metric learning algorithm, segmented trajectory fragments are transformed into fixed-length feature descriptors. Finally, the K-means method and the proposed non-convex metric learning algorithm are utilized to analyze the feature descriptors, and hence, the effective clustering of trajectories can be achieved. Experimental results demonstrate that the proposed method exhibits superior clustering performance compared to the state-of-the-art trajectory clustering approaches. Full article

Excessive spatter formation in conventional CO₂ arc welding significantly diminishes welding quality and efficiency, posing a critical challenge for industrial applications. To address this issue, this study investigated the mechanisms of metal transfer behavior and spatter formation under the influence of a longitudinal magnetic field (LMF) using a shadow-graph technique with high-speed imaging and back-laser illumination, also coupled with Computational Fluid Dynamics (CFD)-based arc-droplet numerical simulations. The results show that increasing the magnetic flux density (MFD) from 0 to 2 mT shifted the transfer mode from the repelled transfer to the globular transfer, while higher MFDs (3–4 mT) induced rotating repelled transfer. The globular transfer at 2 mT was considered to be primarily produced by the centrifugal effect due to the rotational motion of the molten metal inside the droplet, which was caused by the Lorentz force affected by LMF. The higher droplet temperature in this condition also contributed to forming this transfer mode, preventing the formation of repelled transfer through a decrease in the arc pressure. On the contrary, in the higher MFDs, the droplet temperature decreased to increase the arc pressure, lifting the droplet up. Furthermore, the very strong centrifugal effect rotated the molten metal column around the wire axis to induce the rotating repelled transfer. The spatter formation was found to occur with the two-stage motion of the curved long tail without LMF and at 4 mT, and also with the exploding molten metal column at 4 mT, due to an imbalance of the Lorentz force acting on the molten metal. On the other hand, the neck formation facilitated smooth droplet detachment without forming the curved long tail at 2 mT, reducing spatter significantly. These findings offer valuable insights for optimizing welding quality and efficiency by stabilizing globular transfer under an optimal LMF. Full article

The study of entropy generation in thermal non-equilibrium (TNE) states has significant implications for optimizing thermal management systems and understanding heat transfer mechanisms in permeable media. This study investigates the entropy properties in a thermal non-equilibrium (TNE) state within double-lid-driven enclosures filled with a permeable medium. Unlike the temperature equilibrium state, the entropy approach is described by two equations: one for the irreversibility of the mixture phase and one for the irreversibility of the medium phase. High mixed convection is considered due to the motion of the non-facing edges (left-side and upper edges). Four cases based on the direction of motion are examined: Case 1, where the left-side and top edges move in the negative and positive directions of the Y- and X-axes, respectively; Case 2, where the upper and left-side edges move in the negative and positive directions of the X- and Y-axes, respectively; and Cases 3 and 4, where the edges move in the positive and negative directions of the respective axes. Heat generation within the flow domain is considered for both the suspension and medium phases. The governing system is solved numerically using finite volume techniques with the SIMPLER algorithm. The obtained data are used to predict key quantities, such as the heat transfer rate, under the influence of major factors using an effective artificial neural network (ANN) analysis. The main findings show that the solid phase entropy is higher in Case 3 compared to the other cases. Additionally, Case 2 results in a minimum solid phase Nusselt coefficient at the center of the active boundary. Full article

The ‘dynamo problem’ requires that the origin of the primarily dipole geomagnetic
field be found. The source of the geomagnetic field lies within the outer core of
the Earth, which contains a turbulent magnetofluid whose motion is described by the
equations of magnetohydrodynamics (MHD). A mathematical model can be based on the
approximate but essential features of the problem, i.e., a rotating spherical shell containing
an incompressible turbulent magnetofluid that is either ideal or real but maintained in
an equilibrium state. Galerkin methods use orthogonal function expansions to represent
dynamical fields, with each orthogonal function individually satisfying imposed boundary
conditions. These Galerkin methods transform the problem from a few partial differential
equations in physical space into a huge number of coupled, non-linear ordinary differential
equations in the phase space of expansion coefficients, creating a dynamical system. In
the ideal case, using Dirichlet boundary conditions, equilibrium statistical mechanics has
provided a solution to the problem. As has been presented elsewhere, the solution also
has relevance to the non-ideal case. Here, we examine and compare Galerkin methods
imposing Neumann or mixed boundary conditions, in addition to Dirichlet conditions.
Any of these Galerkin methods produce a dynamical system representing MHD turbulence
and the application of equilibrium statistical mechanics in the ideal case gives solutions
of the dynamo problem that differ only slightly in their individual sets of wavenumbers.
One set of boundary conditions, Neumann on the outer and Dirichlet on the inner surface,
might seem appropriate for modeling the outer core as it allows for a non-zero radial component
of the internal, turbulent magnetic field to emerge and form the geomagnetic field.
However, this does not provide the necessary transition of a turbulent MHD energy spectrum
to match that of the surface geomagnetic field. Instead, we conclude that the model
with Dirichlet conditions on both the outer and the inner surfaces is the most appropriate
because it provides for a correct transition of the magnetic field, through an electrically
conducting mantle, from the Earth’s outer core to its surface, solving the dynamo problem.
In addition, we consider how a Galerkin model velocity field can satisfy no-slip conditions
on solid boundaries and conclude that some slight, kinetically driven compressibility must
exist, and we show how this can be accomplished. Full article

Based on the reconfigurable revolute (rR) pair, a reconfigurable decoupled parallel mechanism is proposed, which is composed of three serial chains. Traditional serial chain 1 and 2 are of types PRRR and URC, respectively, where P denotes a prismatic pair, R denotes a revolute pair, U denotes a universal pair, and C denotes a cylindric pair. The reconfigurable serial chain 3 can switch between PRRP and RRPP configurations by changing the axis of reconfigurable pair rR, thus enabling the parallel mechanism to switch between two motion modes of 2T1R (where R represents rotation and T represents translation) and 1T2R. By investigating the relationship between the mechanism’s motion output, input, and the Jacobian matrix, it is verified that the parallel mechanism is a completely decoupled mechanism in the 2T1R motion mode and a partially decoupled mechanism in the 1R2T motion mode. Finally, the performance indexes of the mechanism in both motion modes were discussed using screw theory, and the dimensions of the mechanism were optimized in scale, thereby enhancing the motion performance of the parallel mechanism. The results indicate that the decoupling characteristics of the reconfigurable parallel mechanism have significant advantages in both 2T1R and 1T2R motion modes, providing a theoretical basis for the study of reconfigurable and decoupled parallel mechanisms. Full article

Leg stretching devices are one of the main instruments used to improve human function. To solve the limitations of existing leg stretching products, such as single function and low degree of coincidence, a leg stretching device satisfying ergonomics was studied in this paper. Firstly, the Box–Behnken Design (BBD) response surface methodology was applied to establish a regression model for leg force. Secondly, a motion analysis was conducted on the leg lifting mechanism using analytical methods, and the model data were coupled by Creo Parametric and Automatic Dynamic Analysis of Mechanical System (ADAMS) 2019 software to develop the kinematic model. Then, the motion characteristics during the whole process were studied, and the motion parameter curves were obtained. Next, ABAQUS 2022 software was employed to create the finite element simulation model of the leg lifting device, and key component strength was also analyzed. Finally, a prototype of the device was made and experimentally validated with leg lifting. The results show that in the case of different heights and weights, the lifting angle of the human leg has a significant effect on the force state during the leg lifting process. When the leg is lifted 0–30°, the force on the leg is small. As the leg lifting angle increases, the force on the leg also increases. In the process of leg lifting, the angular velocity and angular acceleration of the leg lifting mechanism change more gently, and there is no obvious mutation. The maximum stress of the driving rod is 102.5 MPa, the maximum stress of the lifting rod is 88.12 MPa, and the maximum stress of the leg placing plate is 40.5 MPa, all of which meet the strength requirements and provide a reference for the research of the human leg stretching device. Full article

In a hypergravity environment, the complex stress conditions and the change in gravity field intensity will significantly affect the interaction force inside solid- and liquid-phase materials. In particular, the driving force for the relative motion of the phase material, the interphase contact interaction, and the stress gradient are enhanced, which creates a nonlinear effect on the movement mode of the phase material, resulting in a change in the material’s behavior. These changes include increased stress and contact interactions; accelerated phase separation; changes in stress distribution; shear force and phase interface renewal; enhanced interphase mass transfer and molecular mixing; and increased volume mass transfer and heat transfer coefficients. These phenomena have significant effects on the synthesis, structural evolution, and properties of materials in different phases. In this paper, the basic concepts of hypergravity and the general rules of the effects of hypergravity on the synthesis, microstructure evolution, and properties of materials are reviewed. Based on the development of hypergravity equipment and characterization methods, this review is expected to broaden the theoretical framework of material synthesis and mechanical property control under hypergravity. It provides theoretical reference for the development of high-performance materials under extreme conditions, as well as new insights and methods for research and application in related fields. Full article

This paper presents a biologically inspired model, the Stereoscopic Direction Detection Mechanism (SDDM), designed to detect motion direction in three-dimensional space. The model addresses two key challenges: the lack of biological interpretability in current deep learning models and the limited exploration of binocular functionality in existing biologically inspired models. Rooted in the fundamental concept of ’disparity’, the SDDM is structurally divided into components representing the left and right eyes. Each component mimics the layered architecture of the human visual system, from the retinal layer to the primary visual cortex. By replicating the functions of various cells involved in stereoscopic motion direction detection, the SDDM offers enhanced biological plausibility and interpretability. Extensive experiments were conducted to evaluate the model’s detection accuracy for various objects and its robustness against different types of noise. Additionally, to ascertain whether the SDDM matches the performance of established deep learning models in the field of three-dimensional motion direction detection, its performance was benchmarked against EfficientNet and ResNet under identical conditions. The results demonstrate that the SDDM not only exhibits strong performance and robust biological interpretability but also requires significantly lower hardware and time costs compared to advanced deep learning models. Full article

Studying the interactions between biological organisms and their environment provides engineers with valuable insights for developing complex mechanical systems and fostering the creation of novel technological innovations. In this study, we introduce a novel bio-inspired three degrees of freedom (DOF) spherical robotic manipulator (SRM), designed to emulate the biomechanical properties observed in nature. The design utilizes the transformation of spherical Complex Spatial Kinematic Pairs (CSKPs) to synthesize bio-inspired robotic manipulators. Additionally, the use of screw theory and the Levenberg–Marquardt algorithm for kinematic parameter computation supports further advancements in human–robot interactions and simplifies control processes. The platform directly transmits motion from the motors to replicate the ball-and-socket mobility of biological joints, minimizing mechanical losses, and optimizing energy efficiency for superior spatial mobility. The proposed 3DOF SRM provides advantages including an expanded workspace, enhanced dexterity, and a lightweight, compact design. Experimental validation, conducted through SolidWorks, MATLAB, Python, and Arduino, demonstrates the versatility and broad application potential of the novel bio-inspired 3DOF SRM, positioning it as a robust solution for a wide range of robotic applications. Full article

The main goal of this paper is to develop a simplified model of the human body motion system that enables its application for movement simulations and the analysis of the kinematic and dynamic parameters occurring during the performance of activities. The model is established on the basis of the modified Hanavan model and consists of rigid solids with simple geometry that are connected mostly with spherical joints. Based on anthropometric data from the literature, a complete set of equations parameterizing the dimensions and mass of each segment was formulated. The equations depend on only two body measurements (height and mass). The model is built in the Adams system as a 3D numerical dynamic model and tested using data gathered with an IMU sensors system. A volunteer lifting an object with a bent spine from the ground with both hands is used for this purpose. Three angles (from the IMUs) are applied to each model’s joint to best simulate human movement and to analyze the angular displacements, velocities, and torques. These results are consistent with theoretical expectations and assumptions, thus proving that reproducing human movements with the developed model is possible and that it also allows various parameters of the human body to be obtained. Full article

IMUs (inertial measurement units) and cameras are widely utilized and combined to autonomously measure the motion states of mobile robots. This paper presents a loosely coupled algorithm for autonomous localization, the ICEKF (IMU-aided camera extended Kalman filter), for the weighted data fusion of the IMU and visual measurement. The algorithm fuses motion information on the velocity layer, thereby mitigating the excessive accumulation of IMU errors caused by direct subtraction on the positional layer after quadratic integration. Furthermore, by incorporating a weighting mechanism, the algorithm allows for a flexible adjustment of the emphasis placed on IMU data versus visual information, which augments the robustness and adaptability of autonomous motion estimation for robots. The simulation and dataset experiments demonstrate that the ICEKF can provide reliable estimates for robot motion trajectories. Full article

This paper presents, for the first time, a rotary actuator functionalized by an inclined disc rotor that serves as a distal optical scanner for endoscopic probes, enabling side-viewing endoscopy in luminal organs using different imaging/analytic modalities such as optical coherence tomography and Raman spectroscopy. This scanner uses a magnetic rotor designed to have a mirror surface on its backside, being electromagnetically driven to roll around the cone-shaped hollow base to create a motion just like a precessing coin. An optical probing beam directed from the probe’s optic fiber is passed through the hollow cone to be incident and bent on the back mirror of the rotating inclined rotor, circulating the probing beam around the scanner for full 360° sideway imaging. This new scanner architecture removes the need for a separate prism mirror and holding mechanics to drastically simplify the scanner design and thus, potentially enhancing device miniaturization and reliability. The first proof-of-concept is developed using 3D printing and experimentally analyzed to reveal the ability of both angular stepping at 45° and high-speed rotation up to 1500 rpm within the biologically safe temperature range, a key function for multimodal imaging. Preliminary optical testing demonstrates continuous circumferential scanning of the laser beam with no blind spot caused by power leads to the actuator. The results indicate the fundamental feasibility of the developed actuator as an endoscopic distal scanner, a significant step to further development toward advancing optical endoscope technology. Full article

Microreactors have the advantages of high heat and mass transfer efficiency, strict control of reaction parameters, easy amplification, and good safety performance, and have been widely used in various fields such as chip manufacturing, fine chemicals, and biomanufacturing. However, narrow microchannels in microreactors often become filled with catalyst particles, leading to blockages. To address this challenge, this study proposes a multiphase flow heat transfer model based on the lattice Boltzmann method (LBM) to investigate the dynamic changes during the bubble collapse process and temperature distribution regularities. Based on the developed three-phase flow dynamics model, this study delves into the shock dynamic evolution process of bubble collapse and analyzes the temperature distribution regularities. Then, the flow patterns under different particle density conditions are explored. The study found that under the action of shock wave, the stable structure of the liquid film of the bubble is destroyed, and the bubble deforms and collapses. At the moment of bubble collapse, energy is rapidly transferred from the potential energy of the bubble to the kinetic energy of the flow field. Subsequently, the kinetic energy is converted into pressure waves. This results in the rapid generation of extremely high pressure in the flow field, creating high-velocity jets and intense turbulent vortices, which can enhance the mass transfer effects of the multiphase flows. At the moment of bubble collapse, a certain high temperature phenomenon will be formed at the collapse, and the high temperature phenomenon in this region is relatively chaotic and random. The pressure waves generated during bubble collapse have a significant impact on the motion trajectories of particles, while the influence on high-density particles is relatively small. The results offer a theoretical basis for understanding mass transfer mechanisms and particle flow patterns in three-phase flow. Moreover, these findings have significant practical implications for advancing technologies in industrial applications, including chip manufacturing and chemical process transport. Full article

This paper presents a novel design of a continuum robot driven by electromagnets and springs, offering enhanced precision in multi-degree-of-freedom bending for diverse applications. Traditional continuum robots, while effective in navigating constrained environments, often face limitations in actuation methods, such as wire-based systems or pre-curved tubes. Our design overcomes these challenges by utilizing electromagnetically driven actuation, which allows each segment of the robot to bend independently at any angle, providing unprecedented flexibility and control. The technical challenges discussed emphasize the goals of this work, with the main aim being to develop a motion control system that uses electromagnets and springs to improve the accuracy and consistency of the robot’s movements. By balancing magnetic and spring forces, our system ensures predictable and stable motion in 3D space. The integration of this mechanism into multi-segmented robots opens up new possibilities in fields such as medical devices, search and rescue operations, and industrial inspection. Finite element method (FEM) simulations validate the efficiency of the proposed approach, demonstrating the precise control of the robot’s motion trajectory and enhancing its operational reliability in complex scenarios. Full article