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.

Automatic Extraction of the Sparse Prior Correspondences for Non-Rigid Point Cloud Registration

Non-rigid registration of point clouds is still far from stable,especially for the largely deformed one.Sparse initial correspondences are often adopted to facilitate the process.However,there are few studies on how to build them automatically.Therefore,in this paper,we propose a robust method to compute such priors automatically,where a global and local combined strategy is adopted.These priors in different degrees of deformation are obtained by the locally geometrical-consistent point matches from the globally structural-consistent region correspondences.To further utilize the matches,this paper also proposes a novel registration method based on the Coherent Point Drift framework.This method takes both the spatial proximity and local structural consistency of the priors as supervision of the registration process and thus obtains a robust alignment for clouds with significantly different deformations.Qualitative and quantitative experiments demonstrate the advantages of the proposed method.

Non-Rigid Medical Image Registration with Joint Histogram Estimation Based on Mutual Information

A mutual information-based non-rigid medical image registration algorithm is presented. An approximate function of Hanning windowed sinc is used as kernel function of partial volume (PV) interpolation to estimate the joint histogram, which is the key to calculating the mutual information. And a new method is proposed to compute the gradient of mutual information with respect to the model parameters. The transformation of object is modeled by a free-form deformation (FFD) based on B-splines. The experiments on 3D synthetic and real image data show that the algorithm can converge at the global optimum and restrain the emergency of local extreme.

Non-rigid registration and KLT filter to improve SNR and CNR in GRE-EPI myocardial perfusion imaging

The purpose of the study was to evaluate the effect of motion compensation by non-rigid registration combined with the Karhunen-Loeve Transform (KLT) filter on the signal to noise (SNR) and contrast-to-noise ratio (CNR) of hybrid gradient-echo echoplanar (GRE-EPI) first-pass myocardial perfusion imaging. Twenty one consecutive first-pass adenosine stress perfusion MR data sets interpreted positive for ischemia or infarction were processed by non-rigid Registration followed by KLT filtering. SNR and CNR were measured in abnormal and normal myocardium in unfiltered and KLT filtered images following nonrigid registration to compensate for respiratory and other motions. Image artifacts introduced by filtering in registered and nonregistered images were evaluated by two observers. There was a statistically sig- nificant increase in both SNR and CNR between normal and abnormal myocardium with KLT filtering (mean SNR increased by 62.18% ± 21.05% and mean CNR increased by 58.84% ± 18.06%;p = 0.01). Motion correction prior to KLT filtering reduced significantly the occurrence of filter induced artifacts (KLT only-artifacts in 42 out of 55 image series vs. registered plus KLT-artifacts in 3 out of 55 image series). In conclusion the combination of non-rigid registration and KLT filtering was shown to increase the SNR and CNR of GRE-EPI perfusion images. Subjective evaluation of image artifacts revealed that prior motion compensation significantly reduced the artifacts introduced by the KLT filtering process.

Relaxation labeling for non-rigid point matching under neighbor preserving

Non-rigid point matching has received more and more attention.Recently,many works have been developed to discover global relationships in the point set which is treated as an instance of a joint distribution.However,the local relationship among neighboring points is more effective under non-rigid transformations.Thus,a new algorithm taking advantage of shape context and relaxation labeling technique,called SC-RL,is proposed for non-rigid point matching.It is a strategy that joints estimation for correspondences as well as the transformation.In this work,correspondence assignment is treated as a soft-assign process in which the matching probability is updated by relaxation labeling technique with a newly defined compatibility coefficient.The compatibility coefficient is one or zero depending on whether neighboring points preserving their relative position in a local coordinate system.The comparative analysis has been performed against four state-of-the-art algorithms including SC,ICP,TPS-RPM and RPM-LNS,and the results denote that SC-RL performs better in the presence of deformations,outliers and noise.

Experiment and numerical simulation on the characteristics of fluid–structure interactions of non-rigid airships

Fluid-structure interaction is an important issue for non-rigid airships with inflated envelopes. In this study, a wind tunnel test is conducted, and a loosely coupled procedure is correspondingly established for numerical simulation based on computational fluid dynamics and nonlinear finite element analysis methods. The typical results of the numerical simulation and wind tunnel experiment, including the overall lift and deformation, are in good agreement with each other. The results obtained indicate that the effect of fluid-structure interaction is noticeable and should be considered for non-rigid airships. Flow- induced deformation can further intensify the upward lift force and pitching moment, which can lead to a large deformation. Under a wind speed of 15 m/s, the lift force of the non-rigid model is increased to approximatelv 60% compared with that of the rigid model under a high angle of attack.

Spectral Distance Distributions for Non-rigid Objects

Non-rigid shape deformation without tearing or stretching is called isometry. There are many difficulties to research non-rigid shape in Euclidean space. Therefore, non-rigid shapes are firstly embedded into a none-Euclidean space. Spectral space is chosen in this paper. Then three descriptors are proposed based on three spectral distances. The existence of zero-eigenvalue has negative effects on computation of spectral distance, Therefore the spectral distance should be computed from the first non-zcro-eigenvalue. Experiments show that spectral distance distributions are very effective to describe the non-rigid shapes.

MUTUAL INFORMATION BASED 3D NON-RIGID REGISTRATION OF CT/MR ABDOMEN IMAGES

A mutual information based 3D non-rigid registration approach was proposed for the registration of deformable CT/MR body abdomen images. The Parzen Windows Density Estimation (PWDE) method is adopted to calculate the mutual information between the two modals of CT and MRI abdomen images. By maximizing MI between the CT and MR volume images, the overlapping part of them reaches the biggest, which means that the two body images of CT and MR matches best to each other. Visible Human Project (VHP) Male abdomen CT and MRI Data are used as experimental data sets. The experimental results indicate that this approach of non-rigid 3D registration of CT/MR body abdominal images can be achieved effectively and automatically, without any prior processing procedures such as segmentation and feature extraction, but has a main drawback of very long computation time.

Non-Rigid Image Registration Algorithm Based on B-Splines Approximation

An intensity-based non-rigid registration algorithm is discussed, which uses Gaussian smoothing to constrain the transformation to be smooth, and thus preserves the topology of images. In view of the insufficiency of the uniform Gaussian filtering of the deformation field, an automatic and accurate non-rigid image registration method based on B-splines approximation is proposed. The regularization strategy is adopted by using multi-level B-splines approximation to regularize the displacement fields in a coarse-to-fine manner. Moreover, it assigns the different weights to the estimated displacements according to their reliabilities. In this way, the level of regularity can be adapted locally. Experiments were performed on both synthetic and real medical images of brain, and the results show that the proposed method improves the registration accuracy and robustness.

Non-rigid registration of medical images based on S^(1/2)(Δ_(mn)^((2)))non-tensor product Bspline

In this study,a non-tensor product B-spline algorithm is applied to the search space of the registration process,and a new method of image non-rigid registration is proposed.The tensor product B-spline is a function defined in the two directions of x and y,while the non-tensor product B-spline S^(1/2)(Δ_(mn)^((2)))is defined in four directions on the 2-type triangulation.For certain problems,using non-tensor product B-splines to describe the non-rigid deformation of an image can more accurately extract the four-directional information of the image,thereby describing the global or local non-rigid deformation of the image in more directions.Indeed,it provides a method to solve the problem of image deformation in multiple directions.In addition,the region of interest of medical images is irregular,and usually no value exists on the boundary triangle.The value of the basis function of the non-tensor product B-spline on the boundary triangle is only 0.The algorithm process is optimized.The algorithm performs completely automatic non-rigid registration of computed tomography and magnetic resonance imaging images of patients.In particular,this study compares the performance of the proposed algorithm with the tensor product B-spline registration algorithm.The results elucidate that the proposed algorithm clearly improves the accuracy.

Balanced Functional Maps for Three-Dimensional Non-Rigid Shape Registration

Three-dimensional(3D)shape registration is a challenging problem,especially for shapes under non-rigid transformations.In this paper,a 3D non-rigid shape registration method is proposed,called balanced functional maps(BFM).The BFM algorithm generalizes the point-based correspondence to functions.By choosing the Laplace-Beltrami eigenfunctions as the function basis,the transformations between shapes can be represented by the functional map(FM)matrix.In addition,many constraints on shape registration,such as the feature descriptor,keypoint,and salient region correspondence,can be formulated linearly using the matrix.By bi-directionally searching for the nearest neighbors of points’indicator functions in the function space,the point-based correspondence can be derived from FMs.We conducted several experiments on the Topology and Orchestration Specification for Cloud Applications(TOSCA)dataset and the Shape Completion and Animation of People(SCAPE)dataset.Experimental results show that the proposed BFM algorithm is effective and has superior performance than the state-of-the-art methods on both datasets.

Analysis and optimization of assembly variations for non-rigid parts

Traditional variation analysis methods are not applicable to non-rigid assemblies due to possible part deformation during the assembly process. This paper presents the use of finite element methods to simulate assembly deformation. The relationship between the parts’ variation and the variation of the key points in final assembly for quality control is set up by calculating the spring back deformation after assembly. Moreover, the optimization method for non-rigid assembly variations based on finite element analysis is presented. The optimal objective is to reduce the manufacturing cost. The approach is implemented by using ANSYS and MATLAB. The test example shows that the proposed method is effective and applicable.

A Local Deviation Constraint Based Non-Rigid Structure From Motion Approach

In many traditional non-rigid structure from motion(NRSFM)approaches,the estimation results of part feature points may significantly deviate from their true values because only the overall estimation error is considered in their models.Aimed at solving this issue,a local deviation-constrained-based column-space-fitting approach is proposed in this paper to alleviate estimation deviation.In our work,an effective model is first constructed with two terms:the overall estimation error,which is computed by a linear subspace representation,and a constraint term,which is based on the variance of the reconstruction error for each frame.Furthermore,an augmented Lagrange multipliers(ALM)iterative algorithm is presented to optimize the proposed model.Moreover,a convergence analysis is performed with three steps for the optimization process.As both the overall estimation error and the local deviation are utilized,the proposed method can achieve a good estimation performance and a relatively uniform estimation error distribution for different feature points.Experimental results on several widely used synthetic sequences and real sequences demonstrate the effectiveness and feasibility of the proposed algorithm.

Real-time Animation Technique for a Kind of Non-rigid Objects

A real-time animation technique for a kind of non-rigid objects, flexible and thin objects, is proposed, which can update with stability the state of n mass points of the mass-spring (MS) modei with time complexity of O (n ). The new implicit numerical integration technique of the authors, which is based on a simple approximation of the linear system, has great advantages over the existing implicit integration methods. Moreover, experiment shows that the new technique is highly efficient in animating a kind of non-rigid objects, and suitable for the draping module of the 3D garment CAD system.

Computing the Full Non-Rigid Group of Trimethylborane and Cyclohaxane Using Wreath Product

This paper computes the group and character table of Trimethylborane and Cyclohaxane. Results show that the groups are isomorphic to the wreath products C3wrC2 and C2wrC6 with orders 81 and 384 and with 17 and 28 conjugacy classes respectively, where Cn denotes a cyclic group of order n.

Non-rigid 3D models retrieval based on hierarchical matching

In 3D models retrieval, feature description and retrieval of non-rigid model face more complex problems due to the isometry transformation of itself. We introduce the hierarchical combination matching into the feature comparison, and build a map between the divided regions of two models, and then achieve accurate feature matching based on patch-by-patch, which successfully introduces the spatial information into feature matching. Verified by experiment, the 3D model retrieval method proposed in this paper based on hierarchical combination matching can make sure more accurate feature matching, so as to enhance the precision of retrieval.

Numerical simulation of fluid-thermal-structural coupling characteristics of stratospheric non-rigid airship

The voluminous stratospheric non-rigid airship is very sensitive to the external thermal environment.The temperature change of internal gas caused by the variation in the external ther-mal environment and wind speed will lead to a change in the shape and buoyancy of the airship,thereby affecting its flight control.The traditional static analysis method is difficult to accurately reflect this fuid-thermal-structural coupling process.In this paper,the iterative analysis method was established for the fluid-thermal-structural coupling effect of stratospheric non-rigid airship based on the models of fluid,thermal,and structural deformation.Considering the load such as the internal thermal effect and external flow field of the airship,the simulation of the thermo-induced structural deformation effect was conducted using Fluent and Abaqus software.The influ-ence of local time and external wind speed on the structural deformation,volume,and equilibrium altitude of the airship was analyzed.The results demonstrate that,at low wind speed,the influence of aerodynamic pressure on the deformation of the airship is negligible.However,a great amount of heat is carried away by the wind,then the structural deformation caused by internal and external pressure difference is alleviated and the equilibrium altitude of the airship change obviously.This can serve as a guideline for the design and flight test of the long-endurance stratospheric non-rigid airship.

Facial optical flow estimation via neural non-rigid registration

Optical flow estimation in human facial video,which provides 2D correspondences between adjacent frames,is a fundamental pre-processing step for many applications,like facial expression capture and recognition.However,it is quite challenging as human facial images contain large areas of similar textures,rich expressions,and large rotations.These characteristics also result in the scarcity of large,annotated realworld datasets.We propose a robust and accurate method to learn facial optical flow in a self-supervised manner.Specifically,we utilize various shape priors,including face depth,landmarks,and parsing,to guide the self-supervised learning task via a differentiable nonrigid registration framework.Extensive experiments demonstrate that our method achieves remarkable improvements for facial optical flow estimation in the presence of significant expressions and large rotations.

Differentiable Deformation Graph-Based Neural Non-rigid Registration

The traditional pipeline for non-rigid registration is to iteratively update the correspondence and alignment such that the transformed source surface aligns well with the target surface.Among the pipeline,the correspondence construction and iterative manner are key to the results,while existing strategies might result in local optima.In this paper,we adopt the widely used deformation graph-based representation,while replacing some key modules with neural learning-based strategies.Specifically,we design a neural network to predict the correspondence and its reliability confidence rather than the strategies like nearest neighbor search and pair rejection.Besides,we adopt the GRU-based recurrent network for iterative refinement,which is more robust than the traditional strategy.The model is trained in a self-supervised manner and thus can be used for arbitrary datasets without ground-truth.Extensive experiments demonstrate that our proposed method outperforms the state-of-the-art methods by a large margin.

非刚体运动特征提取在武术运动中的应用

受光照与环境因素的影响,非刚体运动中的图像会存在视差干扰,导致非刚体运动特征提取效果不佳,因此提出一种针对非刚体运动的特征提取方法。对非刚体运动图像进行高斯滤波处理,在高斯差分尺度空间内,采用特征描述算子提取初始特征点。根据特征点提取结果,计算非刚体运动特征提取的代价。引入引导滤波方法对非刚体运动图像进行视差效果优化处理,在最小视差约束下,根据置信度聚合与传播策略进行非刚体运动的特征精确提取。以武术运动作为实验对象,实验结果表明:所提方法的特征点提取精度较高,且视差提取误差率不超过2.0%。