On static analysis of tensile structures with sliding cables: the frictional sliding case

In some structural systems, such as cable structures, membranes and tensegrity structures, the use of sliding cables allows to reduce the number of elements required to be controlled during tensioning or activation. However, using sliding cables modifies the structural behavior of tensile structures since it alters the distribution of axial forces in structural members. This has been experienced in structures with continuous cables under the assumption of frictionless sliding. However, sliding-induced friction can further alter the behavior of the system. An enhancement of the static analysis of tensile structures with sliding-induced friction is investigated in this paper. In the proposed formulations, the finite-element analysis method and the dynamic relaxation method are combined with a linear complementary approach. Sliding-induced friction is integrated in the formulations through the consideration of the Euler–Eytelwein equation. The importance of considering sliding-induced friction in the static analysis of tensile structures is demonstrated through a series of examples, where it is shown that friction significantly affects the mechanical behavior of the structures. The examples also reveal that the proposed formulations do not affect the computational time of the static analyses.

     

The use of local radial point interpolation method for solving two-dimensional linear fractional cable equation

An efficient numerical technique is formulated to solve two-dimensional time fractional cable equation. The fractional cable equation is an important mathematical model for describing anomalous diffusion processes in biological systems. The proposed computational technique is based on the combination of time stepping method and meshless weak formulation. At the first step, some implicit difference schemes are used to discrete the appearing integer and fractional time derivatives. Then, local radial point interpolation method (LRPI) is extended and used to solve the semi-discretized problem. The main aim of the paper is to show that the LRPI method is a powerful alternative computational technique to solve complicated fractional problems with high accuracy and low complexity. The performance and accuracy of the method are studied and verified through numerical experiments. Moreover, the convergence rate of the temporal discretization scheme is investigated numerically.

     

Thermohydrodynamic analysis of micro spherical spiral groove gas bearings under slip flow and surface roughness coupling effect

The effects of gas rarefaction and surface roughness are temperature-related and always neglected in macroscale. These effects were considered in the analysis of the thermohydrodynamic performance of micro spherical spiral groove bearings. The Reynolds equation and the energy equation incorporated with Wu’s slip model and the Weierstrass–Mandelbrot function to analysis the coupling effect of slip flow and surface roughness. The effects of spherical grooves on computational accuracy were reduced through parameter transformation and oblique coordinates. To describe the temperature boundary condition at the grooved region, a simple gas-mixing model was presented for the grooves. Prediction results showed that temperature reduced bearing forces and friction torque through the slip flow effect. Surface roughness increased not only temperature significantly but also bearing forces and friction torque through a high eccentricity ratio and a low bearing clearance.

     

A novel decomposition-based ensemble model for short-term load forecasting using hybrid artificial neural networks

Highly accurate short-term load forecasting (STLF) is essential in the operation of power systems. However, the existing predictive methods cannot achieve an effective balance between prediction accuracy and computational cost. Furthermore, the prediction residual is rarely used to improve the predictive accuracy in STLF. This paper proposes a novel decomposition-based ensemble model for the STLF task. First, an optimized empirical wavelet transform (OEWT) is developed to rationally decompose the STLF load by combining the approximate entropy method with the empirical wavelet transform. Particularly, OEWT improves both prediction accuracy and computational cost in STLF. Second, a new hybrid machine learning method (named master learner) is proposed by rationally combining long short-term memory networks (LSTMs) with broad learning system (BLS) in STLF, effectively strengthening the predictive accuracy without significantly increasing the computational cost. Third, a residual learning model (named residual learner) is developed in the master learner to extract the effective predictive information from residual results, further improving the prediction accuracy in STLF. Fourth, an auxiliary learner is proposed by introducing another BLS to connect the input and output of the proposed model, enhancing the predictive robustness. The proposed decomposition-based ensemble model is compared with state-of-the-art and traditional models in STLF. Experimental results show that the model not only has high predictive accuracy and robustness but also low computational cost.

     

Simulation of Wheels in Nonlinear,Flexible Multibody Systems

This paper is concerned with the modeling of wheels within the framework of finite element-based dynamic analysis of nonlinear, flexible multibody systems. The overall approach to the modeling of wheels is broken into four distinct parts: a purely kinematic part describing the configuration of the wheel and contacting plane, a unilateral contact condition giving rise to a contact force, the friction forces associated with rolling and/or sliding, and a model of the deformations in the wheel tire. The formulation of these various aspects of the problem involves a combination of holonomic and non-holonomic constraints enforced via the Lagrange multiplier technique. This work is developed within the framework of energy-preserving and decaying time integration schemes that provide unconditional stability for nonlinear, flexible multibody systems involving wheels. Strategies for dealing with the transitions from rolling to sliding and vice-versa are discussed and are found to be more efficient than the use of a continuous friction law. Numerical examples are presented that demonstrate the efficiency and accuracy of the proposed approach.     

基于Karnopp摩擦的柔性滑移铰的建模与仿真

对含Karnopp摩擦的柔性滑移铰系统进行动力学建模和仿真.将滑移铰中的滑块视为柔性体,滑道视为刚性接触面,考虑滑道与滑块之间的间隙.由于柔性滑块与滑道的接触状态和摩擦情况比较复杂,采用有限元方法建立了柔性滑块的力学模型,基于罚函数方法建立含Karnopp摩擦柔性滑移铰接触力模型,通过试算迭代法判断柔性滑块各节点的接触状态,基于KED方法和Newmark方法给出了含该滑移铰机械系统动力学方程的数值算法.最后,以含Karnopp摩擦的柔性滑移铰和驱动摆杆构成的机械系统为例进行动力学仿真,分析了其动力学特性,验证了本文给出的方法的有效性.     

Modeling and simulation of longitudinal dynamics coupled with clutch engagement dynamics for ground vehicles

During the engagement of the dry clutch in automotive transmissions, clutch judder may occur. Vehicle suspension and engine mounts couple the torsional and longitudinal models, leading to oscillations of the vehicle body that are perceived by the driver as poor driving quality. This paper presents an effective formulation for the modeling and simulation of longitudinal dynamics and powertrain torsional dynamics of the vehicle based on non-smooth dynamics of multibody systems. In doing so friction forces between wheels and the road surface are modeled along with friction torque in the clutch using Coulomb’s friction law. First, bilateral constraint equations of the system are derived in Cartesian coordinates and the dynamical equations of the system are developed using the Lagrange multiplier technique. Complementary formulations are proposed to determine the state transitions from stick to slip between wheels and road surface and from the clutch. An event-driven scheme is used to represent state transition problem, which is solved as a linear complementarity problem (LCP), with Baumgarte’s stabilization method applied to reduce constraint drift. Finally, the numerical results demonstrate that the modeling technique is effective in simulating the vehicle dynamics. Using this method stick-slip transitions between driving wheel and the road surface and from the clutch, as a form of clutch judder, are demonstrated to occur periodically for certain values of the parameters of input torque from engine, and static and dynamic friction characteristics of tire/ground contact patch and clutch discs.     

系统辨识算法的复杂性、收敛性及计算效率研究

实践中经常会遇到大型计算问题和优化问题, 使得求解问题算法的复杂性、计算量和计算精度等成为突出问题, 特别是大规模非线性多变量系统的辨识. 对此, 提出几个有趣的研究课题: 1) 利用信息滤波技术和多新息辨识理论研究能提高辨识精度的大规模系统辨识理论与方法; 2) 利用递阶辨识原理研究维数高、变量数目多、计算量小的多变量系统递阶辨识方法; 3) 利用鞅收敛理论建立非线性多变量系统辨识方法的收敛理论; 4) 利用并行计算与递阶计算技术提高辨识算法的计算效率, 以解决一类大规模非线性多变量系统的模型化问题.

     

A Constructive Globally Convergent Adaptive Speed Observer For Port‐Hamiltonian Mechanical Systems with Non‐Holonomic Constraints

This paper presents an adaptive speed observer for general port‐Hamiltonian mechanical systems with non‐holonomic constraints in the presence of unknown friction forces and constant disturbances. Unlike the observers recently reported in the literature, which have been designed either under the assumptions of no friction and the absence of disturbances or for a specific class of mechanical systems with the requirement of an explicit solution of certain Partial Differential Equations (PDEs) that cannot be derived a priori, this observer proposes a design that obviates the solution of PDEs and ensures global convergence for general mechanical systems with k‐non‐holonomic constraints. The observer is totally constructive and given by explicit expressions. The simulation results testify to the effectiveness and the robust features of the developed observer.     

Active control of friction self-excited vibration using neuro-fuzzy and data mining techniques

Vibration caused by friction, termed as friction-induced self-excited vibration (FSV), is harmful to engineering systems. Understanding this physical phenomenon and developing some strategies to effectively control the vibration have both theoretical and practical significance. This paper proposes a self-tuning active control scheme for controlling FSV in a class of mechanical systems. Our main technical contributions include: setup of a data mining based neuro-fuzzy system for modeling friction; learning algorithm for tuning the neuro-fuzzy system friction model using Lyapunov stability theory, which is associated with a compensation control scheme and guaranteed closed-loop system performance. A typical mechanical system with friction is employed in simulation studies. Results show that our proposed modeling and control techniques are effective to eliminate both the limit cycle and the steady-state error.     

Tracking control design for nonholonomic mechanical systems with affine constraints

The trajectory tracking control is considered for nonholonomic mechanical systems with affine constraints and dynamic friction. A new state transformation is proposed to deal with affine constraints, and then an integral feedback compensation strategy is used to identify the dynamic friction. The proposed controller ensures that the output tracking errors converge to zero as t →∞.As an application, a detailed example is presented to illustrate the effectiveness of the control scheme.     

Reliability-based design optimization of crane bridges using Kriging-based surrogate models

Cranes as indispensable and important hoisting machines of modern manufacturing and logistics systems have been wildly used in factories, mines, and custom ports. For crane designs, the crane bridge is one of the most critical systems, as its mechanical skeleton bearing and transferring the operational load and the weight of the crane itself thus must be designed with sufficient reliability in order to ensure safe crane services. Due to extremely expensive computational costs, current crane bridge design has been primarily focused either on deterministic design based on conventional design formula with empirical parameters from designers’ experiences or on reliability-based design by employing finite-element analysis. To remove this barrier, the paper presents the study of using an advanced surrogate modeling technique for the reliability-based design of the crane bridge system to address the computational challenges and thus enhance design efficiency. The Kriging surrogate models are first developed for the performance functions for the crane system design and used for the reliability-based design optimization. Comparison studies with existing crane design methods indicated that employing the surrogate models could substantially improve the design efficiency while maintaining good accuracy.

     

Fairness of Transitions in Diagnosability of Discrete Event Systems

Failure diagnosability has been widely studied for discrete event system (DES) models because of modeling simplicity and computational efficiency due to abstraction. In the literature it is often held that for diagnosability, such models can be used not only for systems that fall naturally in the class of DES but also for the ones traditionally treated as continuous variable dynamic systems. A class of algorithms for failure diagnosability of DES models has been successfully developed for systems where fairness is not a part of the model. These algorithms are based on detecting cycles in the normal and the failure model that look identical. However, there exist systems with all transitions fair where the diagnosability condition that hinges upon this feature renders many failures non-diagnosable although they may actually be diagnosable by transitions out of a cycle. Hence, the diagnosability conditions based on cycle detection need to be modified to hold for many real-world systems where all transitions are fair. In this work, however, it is shown by means of an example that a system may have some transitions fair and some unfair. A new failure diagnosability mechanism is proposed for DES models with both fair and unfair transitions. Time complexity for deciding diagnosability of DES models with fair and unfair transitions is analyzed and compared with the time complexities of other DES diagnosability analysis methods reported in the literature.     

Constraint forces in holonomic mechanical systems

Constraint forces play important roles in the dynamic formulation of mechanical systems. In robotic and locomotion systems, implementing, maintaining, and deliberately violating contact and support conditions require either on-line sensing of constraint forces or indirect computation of them. In this paper three different methods for calculating constraint forces are compared with respect to computational complexity and accuracy, and computation time. In the first two methods, the nonlinear constraint equations and the system dynamic equations are combined such that the resulting set of equations is uniquely solvable for the constraint forces. In the third method, the mechanical system is embedded in a higher-dimensional state space, chosen in such a way that the constraint equations are linear in the new state of the system. Consequently the computation of the constraint forces simplifies. The complexity of the three methods and the computation time for a particular computer can be inferred from an operation count. The accuracy of the individual method is estimated by providing an upper bound of the relative error and the relative residual of the computed constraint forces.     

Bearing fault diagnosis based on combined multi-scale weighted entropy morphological filtering and bi-LSTM

With the development of industry and technology, mechanical systems’ safety has strong relations with the diagnosis of bearing faults. Accurate fault diagnosis is essential for the safe and stable operation of rotating machinery. Most former research depends too much on the fault signal specificity and learning model’s choices. To overcome the disadvantages of lacking intrinsic mode function (IMF) modal aliasing, low degree of discrimination between data of different fault types, high computational complexity. This paper proposes a method that combines multi-scale weighted entropy morphological filtering (MWEMF) signal processing and bidirectional long-short term memory neural networks (Bi-LSTM). The developed rolling bearing fault diagnosis strategy is then implemented to different databases and potential models to demonstrate the greatly improved system’s ability to reconstruct the time-to-frequency domain characteristics of fault signature signals and reduce learning cost. After verification, the classification accuracy of the proposed model reaches 99%.

     

基于事件触发传输机制的非线性系统模糊H∞ 控制

针对离散时间非线性系统, 提出事件触发传输机制下网络化T-S 模糊控制器设计方法. 在事件发生器中引入前提变量偏差触发条件, 从而取消模糊控制器与被控对象的前提变量之间的同步要求. 通过引入一组基于模糊前提变量特性的松弛等式/不等式, 对于无传输时滞和定常传输时滞两种情况, 分别提出具有较小保守性的控制器/事件发生器联合设计算法. 最后, 通过数值算例表明所提出方法的可行性和有效性.

     

Two-Stage Method for Diagonal Recurrent Neural Network Identification of a High-Power Continuous Microwave Heating System

This paper proposes a diagonal recurrent neural network (DRNN) based identification scheme to handle the complexity and nonlinearity of high-power continuous microwave heating system (HPCMHS). The new DRNN design involves a two-stage training process that couples an efficient forward model selection technique with gradient-based optimization. In the first stage, an impact recurrent network structure is obtained by a fast recursive algorithm in a stepwise forward procedure. To ensure stability, update rules are further developed using Lyapunov stability criterion to tune parameters of reduced size model at the second stage. The proposed approach is tested with an experimental regression problem and a practical HPCMHS identification, and the results are compared with four typical network models. The results show that the new design demonstrates improved accuracy and model compactness with reduced computational complexity over the existing methods.

     

On the Modeling of Friction and Rolling in Flexible Multi-Body Systems

This paper is concerned with the dynamic analysis of flexible, nonlinear multi-body systems undergoing contact involving friction and rolling. A continuous friction law is used to model the friction forces between contacting bodies. This avoids the numerical problems associated with the discontinuity inherent to Coulomb's friction law and eliminates the need for different sets of equations modeling sliding and rolling as distinct phenomena. On the other hand, continuous friction laws eliminate specific physical phenomena implied by Coulomb's friction law. The condition of vanishing relative velocity between two contacting bodies is not possible: sticking or rolling are replaced by creeping with a small relative velocity. Discrete events such as transition from slipping to rolling or rolling to slipping are eliminated, together with the high frequency phenomena they are likely to cause. The computational issues associated with the continuous friction law and with the enforcement of the non-holonomic rolling constraint are addressed in this paper. This work is developed within the framework of energy preserving and decaying time integration schemes that provide unconditional stability for nonlinear, flexible multi-body systems undergoing contact involving friction and rolling.     

A novel approach for forward dynamic analysis of 3-PRS parallel manipulator with consideration of friction effect

In this paper, a novel decomposition approach to formulate the dynamic model of a 3-Prismatic, Revolute, Spherical (3-PRS) parallel manipulator is proposed. Since the constraint forces arising from the holonomic constraints would not generate a net force or torque to manipulate the motion of the moving platform, the fact motivates to decompose the reaction forces applied to the connecting joints. The decomposition leads to a transformation matrix which can project the dynamic forces of the moving platform formulated in the task space into the joint space. A sufficient condition is determined to guarantee the existence of the projection matrix. Based on the proposed approach, the inverse of 21×21 augmented matrix formulated by conventional approach in solving forward dynamic problem can be decomposed into that of 6×6 and 15×15 matrices. The computational efficiency can therefore be improved about 23.5%. Besides, since the reaction forces can be calculated simultaneously, each of the actuated legs can be decoupled to calculate the normal forces applied to the sliding planes of the prismatic joints. This feature makes it possible to include the effect of corresponding friction forces into consideration. Since the normal forces applied to the sliding planes vary with the reaction forces, the corresponding friction forces are not only the function of sliding velocities but also the dynamics of the whole mechanism. Computer simulations are performed to verify the proposed approach and analyze the effect of the friction forces on the motion accuracy of the moving platform.