MOTION ANALYSIS OF TAPER MACHINING USING FOUR-AXIS WEDM MACHINE TOOL

The configuration and the reference frame of the four-axis wire-electric discharge machining （WEDM） machine tool are introduced. Based on the motion analysis of the four-axis WEDM machine tool, an algorithm for controlling the four-axis motion is proposed. The algorithm is applicable to both the invariable and variable taper machining. Motion loci of the machining platform and the wire guiding head are deduced by the algorithm according to the bottom surface locus of the workpiece and the taper angle. The algorithm is used in the CNC system of the four-axis WEDM machine tool and confirmed to be effective.

A Probabilistic Method for Motion Analysis of Caisson Breakwaters

It is assumed that, during the design period, the waves acting on breakwaters are divided into three types： standing wave, broken wave and breaking wave,and the wave heights fit the Rayleigh distribution while the water depths, wave periods and duration of breaking wave impact force fit normal distribution. Based on the random samples of water depths, wave heights, wave periods and duration of breaking wave impact force, the types of waves acting on breakwaters are distinguished and the time-history model of the wave force is determined. The motions of caisson breakwaters under the wave force are simulated by a dynamic numerical model and the statistic characteristics of the dynamic responses are analyzed with the Monte Carlo method. A probabilistic procedure to analyze the motion of the breakwater is developed therein. The procedure is illustrated by an example.

MECHANISM DESIGN AND MOTION ANALYSIS OF A SPHERICAL MOBILE ROBOT

A new spherical mobile robot BHQ-1 is designed. The spherical robot is driven by two internally mounted motors that induce the ball to move straight and turn around on a fiat surface. A dynamic model of the robot is developed with Lagrange method and factors affecting the driving torque of two motors are analyzed. The relationship between the turning radius of the robot and the length of two links is discussed in order to optimize its mechanism design. Simulation and experimental results demonstrate the good controllability and motion performance of BHQ-1.

Motion Analysis of an Electric Vehicle with Two Independent Drive Motors

Motion analyses are performed with the help of stability and simulation analysis, which can provide theoretical bases for applications of an electric vehicle with two independent drive motors. Compared with one-motor drive electric vehicle, the two-motor drive electric vehicle has the advantage of easy layout, simple power train and good drivability and handling characteristics. Analysis shows the method connecting armatures of two DC motors in parallel can function as mechanical differential without a steering sensor, which can simplify structure and increase reliability of the controller. Computer simulations and experiment are carried out to verify conclusions.

Mechanism Design and Motion Analysis of Heavy⁃Load Transfer Robot with Parallel Four⁃Bar Mechanism

Heavy-load transfer robots are widely used in automobile production and machinery manufacturing to improve production efficiency.In order to meet the needs of large billet transfer,a 4-DOF transfer robot is designed in this paper,which consists of parallel four-bar mechanisms.The Jacobian matrix referring to the mapping matrix from the joint velocity to the operating space velocity of the transfer robot can be solved by the differential-vector method.The mean value of the Jacobian matrix condition number in the workspace is used as the global performance index of the robot velocity and the optimization goal.The constraint condition is established based on the actual working condition.Then the linkage length optimization is carried out to decrease the length of the linkage and to increase the global performance index of velocity.The total length of robot rods is reduced by 6.12%.The global performance index of velocity is improved by 45.15%.Taking the optimized rod length as the mechanism parameter,the distribution of the motion space of the transfer robot is obtained.Finally,the results show that the proposed method for establishing the Jacobian matrix of the lower-mobility robot and for the optimization of the rods based on the velocity global performance index is accurate and effective.The workspace distribution of the robot meets the design requirements.

Motion information analysis system based on acceleration signals

A motion information analysis system based on the acceleration data is proposed in this paper,consisting of filtering,feature extraction and classification.The Kalman filter is adopted to eliminate the noise.With the time-domain and frequency-domain analysis,acceleration features like the amplitude,the period and the acceleration region values are obtained.Furthermore,the accuracy of the motion classification is improved by using the k-nearest neighbor （KNN） algorithm.

Ultrasonographic visualization of lower eyelid structures and dynamic motion analysis

AIMTo define the ultrasonographic structure of normal lower eyelid anatomic compartments and their spacial relationship in dynamic motion.

Motion analysis of waste rock in gas-solids fluidized bed in coal dry beneficiation

Through the analysis of forces acting on the waste rock in the gas solid fluidized bed, the waste rock velocity equations and displacement equations in the gas solids fluidized bed were achieved and the influential factors of the waste rock motion in the fluidized bed were studied in this paper. The conclusions show that the primary factors influencing the waste rock motion are the waste rock grain size and the scraper velocity according to the computer simulation. This has provided the theoretical foundation both for improving the separating effect and ascertaining the length of the separating cell.

Motion Analysis Technologies for Biomechanical Gait and Postural Analysis in Ballet

The dominant element in ballet is the search for flawless performance. The specific training required from early years may cause some changes compared to the normal human anatomy and physiology. The aim of this study was to investigate the potential of motion analysis technologies for the evaluation of frequent changes in biomechanics of posture and dance. This paper presents an overview of the literature on the main postural compensation employed by the dancer; more specifically on the training effect of the fundamental basic techniques in ballet. It then focuses on the characteristics and potential of motion analysis technologies for the biomechanical evaluation of the dancer. The technologies investigated in this study are the optoelectronic system of gait analysis, which is one of the most advanced technologies for multifactorial motion analysis, integrated with the use of the force platform and the electromyography. These technologies enable a quantitative three-dimensional integrated multifactorial motion analysis in relation to kinematics and dynamics. Through specific systems of motion analysis, the instrumental analysis can describe objectively and with reasonable accuracy the biomechanics, the postural compensation, and the gait of the dancer.

Online Observability-Constrained Motion Suggestion via Efficient Motion Primitive-Based Observability Analysis

An active perception methodology is proposed to locally predict the observability condition in a reasonable horizon and suggest an observability-constrained motion direction for the next step to ensure an accurate and consistent state estimation performance of vision-based navigation systems. The methodology leverages an efficient EOG-based observability analysis and a motion primitive-based path sampling technique to realize the local observability prediction with a real-time performance. The observability conditions of potential motion trajectories are evaluated,and an informed motion direction is selected to ensure the observability efficiency for the state estimation system. The proposed approach is specialized to a representative optimizationbased monocular vision-based state estimation formulation and demonstrated through simulation and experiments to evaluate the ability of estimation degradation prediction and efficacy of motion direction suggestion.

Segmental Kinematic Coupling of the Human Spinal Column during Locomotion

As one of the most important daily motor activities, human locomotion has been investigated intensively in recent decades. The locomotor functions and mechanics of human lower limbs have become relatively well understood. However, so far our understanding of the motions and functional contributions of the human spine during locomotion is still very poor and simultaneous in-vivo limb and spinal column motion data are scarce. The objective of this study is to investigate the delicate in-vivo kinematic coupling between different functional regions of the human spinal column during locomotion as a stepping stone to explore the locomotor function of the human spine complex. A novel infrared reflective marker cluster system was constrncted using stereophotogrammetry techniques to record the 3D in-vivo geometric shape of the spinal column and the segmental position and orientation of each functional spinal region simultaneously. Gait measurements of normal walking were conducted. The preliminary results show that the spinal column shape changes periodically in the frontal plane during locomotion. The segmental motions of different spinal functional regions appear to be strongly coupled, indicating some synergistic strategy may be employed by the human spinal column to facilitate locomotion. In contrast to traditional medical imaging-based methods, the proposed technique can be used to investigate the dynamic characteristics of the spinal column, hence providing more insight into the functional biomechanics of the human spine.

Introducing semantic information into motion graph

To improve motion graph based motion synthesis,semantic control was introduced.Hybrid motion features including both numerical and user-defined semantic relational features were extracted to encode the characteristic aspects contained in the character's poses of the given motion sequences.Motion templates were then automatically derived from the training motions for capturing the spatio-temporal characteristics of an entire given class of semantically related motions.The data streams of motion documents were automatically annotated with semantic motion class labels by matching their respective motion class templates.Finally,the semantic control was introduced into motion graph based human motion synthesis.Experiments of motion synthesis demonstrate the effectiveness of the approach which enables users higher level of semantically intuitive control and high quality in human motion synthesis from motion capture database.

Video Analysis Based on Volumetric Event Detection

During the past decade, feature extraction and knowledge acquisition based on video analysis have been extensively researched and tested on many applications such as closed-circuit television （CCTV） data analysis, large-scale public event control, and other daily security monitoring and surveillance operations with various degrees of success. However, since the actual video process is a multi-phased one and encompasses extensive theories and techniques ranging from fundamental image processing, computational geometry and graphics, and machine vision, to advanced artificial intelligence, pattern analysis, and even cognitive science, there are still many important problems to resolve before it can be widely applied. Among them, video event identification and detection are two prominent ones. Comparing with the most popular frame-to-frame processing mode of most of today＇s approaches and systems, this project reorganizes video data as a 3D volume structure that provides the hybrid spatial and temporal information in a unified space. This paper reports an innovative technique to transform original video frames to 3D volume structures denoted by spatial and temporal features. It then highlights the volume array structure in a so-called ＂pre-suspicion＂ mechanism for a later process. The focus of this report is the development of an effective and efficient voxel-based segmentation technique suitable to the volumetric nature of video events and ready for deployment in 3D clustering operations. The paper is concluded with a performance evaluation of the devised technique and discussion on the future work for accelerating the pre-processing of the original video data.

Key Pose Frame Extraction Method of Human Motion Based on 3D Framework and X-Means

The key pose frames of a human motion pose sequence,play an important role in the compression,retrieval and semantic analysis of continuous human motion.The current available clustering methods in literatures are difficult to determine the number of key pose frames automatically,and may destroy the postures’ temporal relationships while extracting key frames.To deal with this problem,this paper proposes a new key pose frames extraction method on the basis of 3D space distances of joint points and the improved X-means clustering algorithm.According to the proposed extraction method,the final key pose frame sequence could be obtained by describing the posture of human body with space distance of particular joint points and then the time-constraint X-mean algorithm is applied to cluster and filtrate the posture sequence.The experimental results show that the proposed method can automatically determine the number of key frames and save the temporal characteristics of motion frames according to the motion pose sequence.

Gait Analysis of a Subject with Total Hip Arthroplasty

Introduction: gait analysis of a subject with total hip replacement is described. Objective: instrumental gait analysis of a subject 12 years after the total hip arthroplasty. Materials and Methods: in a movement analysis laboratory, locomotion studies were carried out at freely chosen walking speed by a 64-year-old subject, obtaining kinematic, kinetic and surface electromyographic data in time and space. All measurements were assessments by applying walking protocols on a straight surface of 8 m long. Results: abnormal slight activations of semitendinosus and tibialis anterior muscles, of the left limb, were observed throughout the gait cycle, no spatiotemporal parameters far from normal values were detected. Conclusions: it was possible to obtain an exhaustive analysis of the parameters associated with the gait of a subject after 12 years of total hip arthroplasty.

Gait Analysis of a Subject with Tarsometatarsal Prosthesis

Introduction: Gait analysis of an adult man after trans-metatarsal unilateral amputation is described. Objective: Instrumental gait analysis of a subject 15 years after trans-metatarsal unilateral amputation in two footwear conditions: while walking barefoot and with prosthesis. Materials and Methods: In a movement analysis laboratory, locomotion studies were carried out at freely chosen walking speed by a 65-year-old subject, obtaining kinematic, kinetic and surface electromyographic data in time and space. Gait analysis was performed using instrumental technologies from a digital eco-system applying walking protocols. Results: When the patient wore the prosthesis, several positive improvements were observed in various aspects of gait. These included enhancements in the base of support, gait speed, and joint range of movements. Additionally, there was a slight improvement in the vertical ground reaction forces pattern, indicating a positive effect of the assistive technology. Furthermore, the use of the prosthesis led to a more organized pattern of muscle activity, which further supports its beneficial impact. However, it is worth noting that some challenges still persisted, particularly regarding stabilizing the body during the double support phase. Despite this difficulty, the overall findings suggest that the use of the prosthesis offers valuable improvements to the patient’s gait dynamics. Conclusions: After conducting a thorough analysis of the parameters related to the gait of a subject who underwent a trans-metatarsal unilateral amputation fifteen years ago, it was found that the use of prosthesis had a positive impact. This study demonstrated important improvements in some kinematic and kinetic parameters, including muscle activation patterns, indicating an increase in comfort and confidence while utilizing the prosthetic device.

The use of the greater trochanter marker in the thigh segment model:Implications for hip and knee frontal and transverse plane motion

Background:The greater trochanter marker is commonly used in 3-dimensional(3D) models;however,its influence on hip and knee kinematics during gait is unclear.Understanding the influence of the greater trochanter marker is important when quantifying frontal and transverse plane hip and knee kinematics,parameters which are particularly relevant to investigate in individuals with conditions such as patellofemoral pain,knee osteoarthritis,anterior cruciate ligament(ACL) injury,and hip pain.The aim of this study was to evaluate the effect of including the greater trochanter in the construction of the thigh segment on hip and knee kinematics during gait.Methods:3D kinematics were collected in 19 healthy subjects during walking using a surface marker system.Hip and knee angles were compared across two thigh segment definitions(with and without greater trochanter) at two time points during stance:peak knee flexion(PKF) and minimum knee flexion(Min KF).Results:Hip and knee angles differed in magnitude and direction in the transverse plane at both time points.In the thigh model with the greater trochanter the hip was more externally rotated than in the thigh model without the greater trochanter(PKF:-9.34°± 5.21° vs.1.40°± 5.22°,Min KF:-5.68°± 4.24° vs.5.01°± 4.86°;p < 0.001).In the thigh model with the greater trochanter,the knee angle was more internally rotated compared to the knee angle calculated using the thigh definition without the greater trochanter(PKF:14.67°± 6.78° vs.4.33°± 4.18°,Min KF:10.54°± 6.71° vs.-0.01°± 2.69°;p < 0.001).Small but significant differences were detected in the sagittal and frontal plane angles at both time points(p < 0.001).Conclusion:Hip and knee kinematics differed across different segment definitions including or excluding the greater trochanter marker,especially in the transverse plane.Therefore when considering whether to include the greater trochanter in the thigh segment model when using a surface markers to calculate 3D kinematics for movement assessment,it is important to have a clear understanding of the effect of different marker sets and segment models in use.

DPT‐tracker:Dual pooling transformer for efficient visual tracking

Transformer tracking always takes paired template and search images as encoder input and conduct feature extraction and target‐search feature correlation by self and/or cross attention operations,thus the model complexity will grow quadratically with the number of input images.To alleviate the burden of this tracking paradigm and facilitate practical deployment of Transformer‐based trackers,we propose a dual pooling transformer tracking framework,dubbed as DPT,which consists of three components:a simple yet efficient spatiotemporal attention model(SAM),a mutual correlation pooling Trans-former(MCPT)and a multiscale aggregation pooling Transformer(MAPT).SAM is designed to gracefully aggregates temporal dynamics and spatial appearance information of multi‐frame templates along space‐time dimensions.MCPT aims to capture multi‐scale pooled and correlated contextual features,which is followed by MAPT that aggregates multi‐scale features into a unified feature representation for tracking prediction.DPT tracker achieves AUC score of 69.5 on LaSOT and precision score of 82.8 on Track-ingNet while maintaining a shorter sequence length of attention tokens,fewer parameters and FLOPs compared to existing state‐of‐the‐art(SOTA)Transformer tracking methods.Extensive experiments demonstrate that DPT tracker yields a strong real‐time tracking baseline with a good trade‐off between tracking performance and inference efficiency.

Nonlinear dynamic modeling of planar moving Timoshenko beam considering non-rigid non-elastic axial effects

Due to the importance of vibration effects on the functional accuracy of mechanical systems,this research aims to develop a precise model of a nonlinearly vibrating single-link mobile flexible manipulator.The manipulator consists of an elastic arm,a rotary motor,and a rigid carrier,and undergoes general in-plane rigid body motion along with elastic transverse deformation.To accurately model the elastic behavior,Timoshenko’s beam theory is used to describe the flexible arm,which accounts for rotary inertia and shear deformation effects.By applying Newton’s second law,the nonlinear governing equations of motion for the manipulator are derived as a coupled system of ordinary differential equations(ODEs)and partial differential equations(PDEs).Then,the assumed mode method(AMM)is used to solve this nonlinear system of governing equations with appropriate shape functions.The assumed modes can be obtained after solving the characteristic equation of a Timoshenko beam with clamped boundary conditions at one end and an attached mass/inertia at the other.In addition,the effect of the transverse vibration of the inextensible arm on its axial behavior is investigated.Despite the axial rigidity,the effect makes the rigid body dynamics invalid for the axial behavior of the arm.Finally,numerical simulations are conducted to evaluate the performance of the developed model,and the results are compared with those obtained by the finite element approach.The comparison confirms the validity of the proposed dynamic model for the system.According to the mentioned features,this model can be reliable for investigating the system’s vibrational behavior and implementing vibration control algorithms.

A deep Koopman operator-based modelling approach for long-term prediction of dynamics with pixel-level measurements

Although previous studies have made some clear leap in learning latent dynamics from high-dimensional representations,the performances in terms of accuracy and inference time of long-term model prediction still need to be improved.In this study,a deep convolutional network based on the Koopman operator(CKNet)is proposed to model non-linear systems with pixel-level measurements for long-term prediction.CKNet adopts an autoencoder network architecture,consisting of an encoder to generate latent states and a linear dynamical model(i.e.,the Koopman operator)which evolves in the latent state space spanned by the encoder.The decoder is used to recover images from latent states.According to a multi-step ahead prediction loss function,the system matrices for approximating the Koopman operator are trained synchronously with the autoencoder in a mini-batch manner.In this manner,gradients can be synchronously transmitted to both the system matrices and the autoencoder to help the encoder self-adaptively tune the latent state space in the training process,and the resulting model is time-invariant in the latent space.Therefore,the proposed CKNet has the advantages of less inference time and high accuracy for long-term prediction.Experiments are per-formed on OpenAI Gym and Mujoco environments,including two and four non-linear forced dynamical systems with continuous action spaces.The experimental results show that CKNet has strong long-term prediction capabilities with sufficient precision.