An integrated friction model structure with improved preslidingbehavior for accurate friction compensation

Presents a dynamical friction model structure which allows accurate modeling both in the sliding and the presliding regimes. Transition between these two regimes is accomplished without a switching function. The model incorporates a hysteresis function with nonlocal memory and arbitrary transition curves. These last aspects prove essential for modeling presliding friction that is encountered in real physical situations. The model as a whole can also handle the Stribeck effect and stick-slip behavior as has been demonstrated by validation on a KUKA IR 361 robot. In this sense, this model can be considered as more complete in comparison with others found in the literature. The general friction model allows modeling of individual friction systems through the identification of a set of parameters that determine the complete behavior of the system. In this way, the model structure has been used to identify the friction behavior of a linear slide as well as that of the above mentioned KUKA robot. The results of the latter identification have been consequently used for feedforward friction compensation to obtain the most accurate tracking     

Modification of the Leuven integrated friction model structure

This note presents a modification of the integrated friction model structure proposed by Swevers et al. (2000), called the Leuven model. The Leuven model structure allows accurate modeling both in the presliding and the sliding regimes without the use of a switching function. The model incorporates a hysteresis function with nonlocal memory and arbitrary transition curves. This note presents two modifications of the Leuven model. A first modification overcomes a recently detected shortcoming of the original Leuven model: a discontinuity in the friction force which occurs during certain transitions in presliding. A second modification, using the general Maxwell slip model to implement the hysteresis force, eliminates the problem of stack overflow, which can occur with the implementation of the hysteresis force     

Predictive modeling of the lateral drift capacity of circular reinforced concrete columns using an evolutionary algorithm

The drift capacity of reinforced concrete (RC) columns is a crucial factor in displacement and seismic based design procedure of RC structures, since they might be able to withstand the loads or dissipate the energy applied through deformation and ductility. Considering the high costs of testing methods for observing the drift capacity and ductility of RC structural members in addition to the impact of numerous parameters, numerical analyses and predictive modeling techniques have very much been appreciated by researchers and engineers in this field. This study is concerned with providing an alternative approach, termed as linear genetic programming (LGP), for predictive modeling of the lateral drift capacity (Δ_max) of circular RC columns. A new model is developed by LGP incorporating various key variables existing in the experimental database employed and those well-known models presented by various researchers. The LGP model is examined from various perspectives. The comparison analysis of the results with those obtained by previously proposed models confirm the precision of the LGP model in estimation of the Δ_max factor. The results reveal the fact that the LGP model impressively outperforms the existing models in terms of predictability and performance and can be definitely used for further engineering purposes. These approve the applicability of LGP technique for numerical analysis and modeling of complicated engineering problems.

     

Modelling Bending Behaviour in Cloth Simulation Using Hysteresis

Real cloth exhibits bending effects, such as residual curvatures and permanent wrinkles. These are typically explained by bending plastic deformation due to internal friction in the fibre and yarn structure. Internal friction also gives rise to energy dissipation which significantly affects cloth dynamic behaviour. In textile research, hysteresis is used to analyse these effects, and can be modelled using complex friction terms at the fabric geometric structure level. The hysteresis loop is central to the modelling and understanding of elastic and inelastic (plastic) behaviour, and is often measured as a physical characteristic to analyse and predict fabric behaviour. However, in cloth simulation in computer graphics the use of hysteresis to capture these effects has not been reported so far. Existing approaches have typically used plasticity models for simulating plastic deformation. In this paper, we report on our investigation into experiments using a simple mathematical approximation to an ideal hysteresis loop at a high level to capture the previously mentioned effects. Fatigue weakening effects during repeated flexural deformation are also considered based on the hysteresis model. Comparisons with previous bending models and plasticity methods are provided to point out differences and advantages. The method requires only incremental extra computation time.     

Towards online monitoring of concrete dam displacement subject to time-varying environments: An improved sequential learning approach

Data-based models are widely applied in concrete dam health monitoring. However, most existing models are restricted to offline modeling, which cannot continuously track the displacement behavior with dynamic evolution patterns, especially in time-varying environments. In this paper, sequential learning is introduced to establish an online monitoring model for dam displacement behavior. This approach starts by considering the timeliness difference between old and new data using the forgetting mechanism, and a novel adaptive forgetting extreme learning machine (AF-ELM) is presented. A primary predictor based on AF-ELM is then formulated, which aims to sequentially learn the complex nonlinear relationship between dam displacement and main environmental factors. Considering the chaotic characteristics contained in the residual sequence of the primary predictor, a multi-scale residual-error correction (REC) strategy is devised based on divide-and-conquer scheme. Specifically, time-varying filter-based empirical mode decomposition is adopted to decompose the raw chaotic residual-error series into a set of subseries with more stationarity, which are further aggregated and reconstructed by fuzzy entropy theory and suitable approximation criterion. Finally, the corrected residual sequence is superimposed with the preliminary predictions from AF-ELM to generate the required modeling results. The effectiveness of the proposed model is verified and assessed by taking a real concrete dam as an example and comparing prediction performance with state-of-the-art models. The results show that AF-ELM performs better in displacement prediction compared with benchmark models, and the multi-scale REC can effectively identify the valuable information within the residual sequence. The proposed online monitoring model can more closely track the dynamic variations of displacement data, which provides a fire-new solution for dam behavior prediction and analysis.     

联合样本输出与特征空间的半监督概念漂移检测法及其应用

城市固废焚烧(Municipal solid waste incineration, MSWI)过程受垃圾成分波动、设备磨损与维修、季节交替变化等因素的影响而存在概念漂移现象, 这导致用于污染物排放浓度的建模数据具有时变性. 为此, 需要识别能够表征概念漂移的新样本对污染物测量模型进行更新, 但现有漂移检测方法难以有效应用于建模样本真值获取困难的工业过程. 针对上述问题, 提出一种联合样本输出与特征空间的半监督概念漂移检测方法. 首先, 采用基于主成分分析(Principal component analysis, PCA)的无监督机制识别特征空间内的概念漂移样本; 然后, 在样本输出空间采用基于时间差分(Temporal-difference, TD)学习的半监督机制对上述概念漂移样本进行伪真值标注后, 再用Page-Hinkley检测法确认能够表征概念漂移的样本; 最后, 采用上述步骤获得的新样本结合历史样本对模型进行更新. 基于合成和真实工业过程数据集的仿真结果表明所提方法具有优于已有方法的性能, 能够在加强模型漂移适应性的同时有效缩减样本标注成本.     

Back analysis for rock model surrounding underground roadways in coal mine based on black hole algorithm

The huge plastic deformation is the characteristic of the underground roadways in coal mine. Therefore, to compute the stability of underground roadways, a elastic–plastic constitutive model of surrounding rock must be obtained. Many elastic–plastic constitutive models for rock mass have been proposed. In this study, a generalized constitutive law for an elastic–plastic constitutive model is applied. Using this generalized constitutive law, the problem of model identification is transformed to a problem of parameter back analysis, which is a typical and complicated optimization. To improve the efficiency of the traditional optimization method, a black hole algorithm is applied in this study. Combining the generalized constitutive law for an elastic–plastic constitutive model and black hole algorithm, a new back analysis method for model identification of rocks surrounding underground roadways in coal mine is proposed. Using this new method, the elastic–plastic constitutive models for two underground roadways in Huainan coal mine has been back-calculated. The results are compared with those of traditional genetic algorithm, fast genetic algorithm and immune continuous ant colony algorithm, that proposed in previous studies. The results show that the new model back analysis algorithm can significantly improve the computation efficiency and the computation effect, and is a very good method for back analysis the rock model surrounding underground roadways in coal mine.     

基于Petri网的数字系统建模和VHDL实现

基于Petri网的数字系统的建模及其硬件实现方法已经得到了广泛的研究,然而现有的方法主要适用于同步电路,由此提出了一种基于Petri网的数字系统建模和VHDL实现的新方法。首先定义了一种广义同步自控网系统,解决了数字系统的Petri网建模问题。基于一种带优先级的多输入多时钟D触发器,设计了对应的软IP核,进而探讨了广义同步自控网系统模型到VHDL代码的具体转换方法。设计的CAD工具支持数字系统的建模、功能分析与代码转换功能。通过设计示例表明了所述方法和相关工具的有效性。     

High-performance surface-micromachined inchworm actuator

This work demonstrates a polycrystalline silicon surface-micromachined inchworm actuator that exhibits high-performance characteristics such as large force (/spl plusmn/0.5 millinewtons), large velocity range (0 to /spl plusmn/4.4 mm/sec), large displacement range (/spl plusmn/100 microns), small step size (/spl plusmn/10, /spl plusmn/40 or /spl plusmn/100 nanometers), low power consumption (nanojoules per cycle), continuous bidirectional operation and relatively small area (600 /spl times/ 200/spl mu/m/sup 2/). An in situ load spring calibrated on a logarithmic scale from micronewtons to millinewtons, optical microscopy and Michelson interferometry are used to characterize its performance. The actuator consists of a force-amplifying plate that spans two voltage-controlled clamps, and walking is achieved by appropriately sequencing signals to these three components. In the clamps, normal force is borne by equipotential rubbing counterfaces, enabling friction to be measured against load. Using different monolayer coatings, we show that the static coefficient of friction can be changed from 0.14 to 1.04, and that it is load-independent over a broad range. We further find that the static coefficient of friction does not accurately predict the force generated by the actuator and attribute this to nanometer-scale presliding tangential deflections.     

概念漂移数据流分类中的多源在线迁移学习算法

现有概念漂移处理算法在检测到概念漂移发生后,通常需要在新到概念上重新训练分类器,同时“遗忘”以往训练的分类器。在概念漂移发生初期,由于能够获取到的属于新到概念的样本较少,导致新建的分类器在短时间内无法得到充分训练,分类性能通常较差。进一步,现有的基于在线迁移学习的数据流分类算法仅能使用单个分类器的知识辅助新到概念进行学习,在历史概念与新到概念相似性较差时,分类模型的分类准确率不理想。针对以上问题,文中提出一种能够利用多个历史分类器知识的数据流分类算法——CMOL。CMOL算法采取分类器权重动态调节机制,根据分类器的权重对分类器池进行更新,使得分类器池能够尽可能地包含更多的概念。实验表明,相较于其他相关算法,CMOL算法能够在概念漂移发生时更快地适应新到概念,显示出更高的分类准确率。     

Nonlinear inelastic uniform torsion of composite bars by BEM

In this paper the elastic–plastic uniform torsion analysis of composite cylindrical bars of arbitrary cross-section consisting of materials in contact, each of which can surround a finite number of inclusions, taking into account the effect of geometric nonlinearity is presented employing the boundary element method. The stress–strain relationships for the materials are assumed to be elastic–plastic–strain hardening. The incremental torque–rotation relationship is computed based on the finite displacement (finite rotation) theory, that is the transverse displacement components are expressed so as to be valid for large rotations and the longitudinal normal strain includes the second-order geometric nonlinear term often described as the “Wagner strain”. The proposed formulation does not stand on the assumption of a thin-walled structure and therefore the cross-section’s torsional rigidity is evaluated exactly without using the so-called Saint Venant’s torsional constant. The torsional rigidity of the cross-section is evaluated directly employing the primary warping function of the cross-section depending on both its shape and the progress of the plastic region. A boundary value problem with respect to the aforementioned function is formulated and solved employing a BEM approach. The influence of the second Piola–Kirchhoff normal stress component to the plastic/elastic moment ratio in uniform inelastic torsion is demonstrated.     

Finite element modelling of machining of AISI 316 steel: Numerical simulation and experimental validation

The objective of this research is to modeling the thermo mechanical behavior when machining a stainless steel (AISI 316) and to determine the influence of the friction coefficient in the tool-chip interface on cutting and feed forces, cutting temperature, plastic strain, plastic strain rate, maximum shear stress and residual stresses. An experimental validation of the cutting process was conducted in order to verify the numerical simulated results and the comparison shows that the friction modeling at the tool-chip interface has a significant influence on the final results.Therefore, it can be concluded that the friction coefficient has a strong effect in the cutting process and is crucial to obtain valuable predictions when machining with the FEM model.     

基于更新样本智能识别算法的自适应集成建模

选择表征建模对象特性漂移的新样本对软测量模型进行自适应更新,能够降低模型复杂度和运行消耗,提高模型可解释性和预测精度.针对新样本近似线性依靠程度（Approximate linear dependence, ALD）和预测误差（Prediction error, PE）等指标只能片面反映建模对象的漂移程度,领域专家结合具体工业过程需要依据上述指标和自身积累经验进行更新样本的有效识别等问题,本文提出了基于更新样本智能识别算法的自适应集成建模策略.首先,基于历史数据离线建立基于改进随机向量泛函连接网络（Improved random vector functional-link networks, IRVFL）的选择性集成模型;然后,基于集成子模型对新样本进行预测输出后采用在线自适应加权算法（On-line adaptive weighting fusion, OLAWF）对集成子模型权重进行更新,实现在线测量阶段对建模对象特性变化的动态自适应;接着基于领域专家知识构建模糊推理模型对新样本相对ALD（Relative ALD, RALD）值和相对PE（Relative PE, RPE）值进行融合,实现更新样本智能识别,构建新的建模样本库;最后实现集成模型的在线自适应更新.采用合成数据仿真验证了所提算法的合理性和有效性.     

Modeling of static friction in closed-loop kinematic chains—Uniqueness and parametric sensitivity problems

Problems with uniqueness and high parametric sensitivity of the solution of equations of motion, encountered in the static friction regime, are addressed. Friction in joints of a multibody system with closed-loop kinematic chains is discussed. Three different models of friction are studied: the discontinuous Coulomb model with stiction regime represented in terms of additional constraints; the approximate Coulomb model, smoothed in the vicinity of zero relative velocity; and the LuGre model with presliding displacements represented in terms of auxiliary state variables. Firstly, a rigid body model is investigated. It is shown that in the case of constraint addition approach, problems with uniqueness of solution emerge in the static friction regime. In the case of continuous models of friction, the solution in the stiction regime and its vicinity is highly sensitive to some hardly measurable or arbitrarily chosen parameters of the model of friction. Origins of nonuniqueness and high sensitivity are investigated, and the questionable credibility of the stiction regime simulation results is discussed. Secondly, a simplified model of body and joint elasticity is introduced to investigate the impact of flexibility on the mechanism frictional behavior. It is shown that taking the flexibility into consideration may eliminate the uniqueness and sensitivity problems. Moreover, the quantities that represent flexibility may be regarded as the key factors influencing the results of stiction regime simulation. Five examples are provided to illustrate the presented considerations.     

Mixed perfectly-matched-layers for direct transient analysis in 2D elastic heterogeneous media

We are concerned with elastic waves arising in plane-strain problems in an elastic semi-infinite arbitrarily heterogeneous medium. Specifically, we discuss the development of a new mixed displacement–stress formulation for forward elastic wave simulations in perfectly-matched-layer (PML)-truncated heterogeneous media.To date, most PML formulations split the displacement and stress fields, resulting in non-physical components for each field. In this work, we favor unsplit schemes, primarily for the relative ease by which the resulting forms can be incorporated into existing codes, the ease by which the resulting semi-discrete forms can be integrated in time, and the ease by which they can be used in adjoint formulations arising in inverse problems, contrary to most past and current developments. We start by following classical lines, and apply complex-coordinate-stretching to the governing equations in the frequency domain, while retaining both displacements and stress quantities as unknowns. With the aid of auxiliary variables the resulting mixed form is rendered second-order in time, thereby allowing the use of standard time integration schemes. We report on numerical simulations demonstrating the stability and efficacy of the approach.     

Classifying peer-to-peer applications using imbalanced concept-adapting very fast decision tree on IP data stream

Peer-to-Peer (P2P) applications generate streaming data in large volumes, where new communities of peers regularly attend and existing communities of peers regularly leave, requiring the classification techniques to consider concept drift, and update the model incrementally. Concept-adapting Very Fast Decision Tree (CVFDT) is one of the well-known streaming data mining techniques that can be applied to P2P traffic. However, we observe that P2P traffic data is class imbalanced, namely, only about 30 % of examples can be labeled as “P2P”, biasing the trained models (e.g. decision tree) towards the majority class (i.e. “NonP2P”). In this paper, we propose a new technique, the imbalanced CVFDT (iCVFDT), by integrating the CVFDT with an efficient resampling technique to address the issue of the class imbalanced data. The iCVFDT classification technique enjoys the advantages of CVFDT (such as stability), and at the same time, is not sensitive to imbalanced data. We captured the Internet traffic at a main gateway and prepared a real data stream with 3.5 million examples to which the iCVFDT classification technique was applied. The experimental results demonstrate a significant improvement in the performance of the iCVFDT compared to that of the CVFDT.     

A contact force solution for non-colliding contact dynamics simulation

Rigid-body impact modeling remains an intensive area of research spurred on by new applications in robotics, biomechanics, and more generally multibody systems. By contrast, the modeling of non-colliding contact dynamics has attracted significantly less attention. The existing approaches to solve non-colliding contact problems include compliant approaches in which the contact force between objects is defined explicitly as a function of local deformation, and complementarity formulations in which unilateral constraints are employed to compute contact interactions (impulses or forces) to enforce the impenetrability of the contacting objects. In this article, the authors develop an alternative approach to solve the non-colliding contact problem for objects of arbitrary geometry in contact at multiple points. Similarly to the complementarity formulation, the solution is based on rigid-body dynamics and enforces contact kinematics constraints at the acceleration level. Differently, it leads to an explicit closed-form solution for the normal forces at the contact points. Integral to the proposed formulation is the treatment of tangential contact forces, in particular the static friction. These friction forces must be calculated as a function of microslip velocity or displacement at the contact point. Numerical results are presented for four test cases: (1) a thin rod sliding down a stationary wedge; (2) a cube pushed off a wedge by an applied force; (3) a cube rotating off the wedge under application of an external moment; and (4) the cube and the wedge both moving under application of a moment. To ascertain validity and correctness, the solutions to frictionless and frictional scenarios obtained with the new formulation are compared to those generated by using a commercial simulation tool MSC ADAMS.     

Comparison of models for finite plasticity: A numerical study

We introduce a general framework for the numerical approximation of finite multiplicative plasticity. The method is based on a fully implicit discretization in time which results in an iteratively evaluated stress response; the arising nonlinear problem is then solved by a Newton method where the linear subproblems are solved with a parallel multigrid method. The procedure is applied to models with different elastic free energy functionals and a plastic flow rule of von Mises type. In addition these models are compared to a recently derived frame indifferent approximation of finite multiplicative plasticity valid for small elastic strains which leads to linear balance equations. Rate independent and rate dependent realizations of the former models are considered. We demonstrate by various 3D simulations that the choice of the elastic free energy is not essential (for material parameters representative for metals) and that the new model gives the same response quantitatively and qualitatively as the standard models.     

Modeling of a joint-type flexible endoscope based on elastic deformation and internal friction

Flexible endoscopes are widely used in minimally invasive surgical robot systems. Various kinematic models have been developed for describing the deformation of such endoscopes. For joint-type flexible endoscopes, most existing models neglect the effect of internal friction and cannot precisely show the shape.

In this paper, we propose a new nonlinear bending model. The rubber tube and metal net at each joint are approximated as a tube under elastic deformation and are assigned an equivalent bending stiffness. The internal friction force is also taken into account to build the moment balance equation at each joint. Groups of experiments were performed to validate the nonlinear model. The results closely confirm the model’s predictions. The model’s tip position error during the bending and unbending phases are 1.48?±?0.99?mm and 1.68?±?0.91?mm respectively; the bending angle errors are ?5.50?±?2.54° and 1.68?±?3.66°, respectively The model can also take account of the hysteresis effect of the bending, which is quite common for cable-driven flexible robots. Moreover, the model has good computational efficiency, making it suitable for real-time control.     

Unsupervised statistical segmentation of nonstationary images using triplet Markov fields

Recent developments in statistical theory and associated computational techniques have opened new avenues for image modeling as well as for image segmentation techniques. Thus, a host of models have been proposed and the ones which have probably received considerable attention are the hidden Markov fields (HMF) models. This is due to their simplicity of handling and their potential for providing improved image quality. Although these models provide satisfying results in the stationary case, they can fail in the nonstationary one. In this paper, we tackle the problem of modeling a nonstationary hidden random field and its effect on the unsupervised statistical image segmentation. We propose an original approach, based on the recent triplet Markov field (TMF) model, which enables one to deal with nonstationary class fields. Moreover, the noise can be correlated and possibly non-Gaussian. An original parameter estimation method which uses the Pearson system to find the natures of the noise margins, which can vary with the class, is also proposed and used to perform unsupervised segmentation of such images. Experiments indicate that the new model and related processing algorithm can improve the results obtained with the classical ones.