Mathematical Modeling and Parameter Identification of a Planar Servo-Pneumatic Test Facility. Part I: Mathematical Modeling and Computer Simulation

High quality multi-axis test facilities used for testing heavy loads and large structures of industrial equipment are usually simulated, designed and controlled based on reduced model equations neglecting the inertia properties of the actuators. The design and control of servo-pneumatic test facilities used for testing small and light structures must take into account extended test facility models including the various inertia properties of the actuators. In this paper (Part I) an extended test facility model is presented including the various inertia properties and joints of the actuators. These extended model equations are represented in a form well suited to be directly implemented in control algorithms based on exact linearization techniques for real time control. This is done by stepwise projecting the inertia properties of the various actuator housings and actuator pistons down to the common mass of the test table and payload. The resulting extended model equations have the same form as the reduced model equations. They only include more complex system matrices and vector functions. These compact model equations turn out to be suitable for an efficient nonlinear controller design of these test facilities. Computer simulations and associated laboratory experiments show the necessity to use extended model equations in case of testing small and light structures. In Part II of this paper [1] the inertia parameters of the planar test facility will be identified in laboratory experiments.     

Identification of the Ten Inertia Parameters of a Rigid Body

Standard experiments for identifying inertia parameters of a rigid body only provide a subset of the inertia parameters of the body [1–10]. In addition, they do not use in the estimation process the complete information included in the equations of motion of the rigid test body. The objective of the work described in this paper is the simultaneous, automatic experimental identification of the ten inertia parameters of a rigid body using the complete information hidden in the nonlinear model equations of the test body. This task has been solved in several steps:– mathematical modelling of the special motions of a rigid body in space. These model equations have been mapped into a form suitable for identification purposes (identification hypothesis)– design of a special measurement robot for performing the identification experiments– laboratory experiments providing test data used for the identification experiments– identification of the inertia parameters and accuracy tests.The accuracy of the identified parameters is satisfactory.     

Hybrid approach for dynamic model identification of an electro-hydraulic parallel platform

In this paper, a hybrid optimization algorithm is proposed to identify the dynamic parameters of a 6-DOF electro-hydraulic parallel platform. The dynamic model of a parallel platform with arbitrary geometry, inertia distribution and frictions is obtained based on a structured Boltzmann–Hamel–d’Alembert formulation, and then the estimation equations are explicitly expressed in terms of a linear form with respect to the identified inertial and the friction coefficients in accordance with a linear friction model. However, when nonlinear friction models are considered, the parameter identification of the electro-hydraulic parallel platform is considered as an optimization process with an objective function minimizing the errors between the measurement and identification, and then an effective combination of the particle swarm optimization (PSO) method and the local quasi-Newton method is proposed to solve the identification problem. Experimental identification processes are carried out for the identified parameters, and the identified models are compared by the predicted forces between the LS method and the optimization technique as well as between the linear and nonlinear friction models.     

考虑关节摩擦的空间机器人动力学建模与参数辨识

研究了考虑关节摩擦影响的空间机器人系统的动力学建模与参数辨识问题．采用单向递推组集方法和虚功率原理建立了含有关节摩擦的多体系统动力学方程,推导了关节摩擦对系统动力学方程的贡献,采用基于腕力传感器信号和最小二乘法的辨识方法进行了系统惯性参数的辨识．数值仿真结果验证了数学模型的正确性与辨识方法的有效性．     

Experimental Nonlinear Identification of a Single Mode of a Transversely Excited Beam

A procedure is presented for using a primary resonance excitation in experimentally identifying the nonlinear parameters of a model approximating the response of a cantilevered beam by a single mode. The model accounts for cubic inertia and stiffness nonlinearities and quadratic damping. The method of multiple scales is used to determine the frequency-response function for the system. Experimental frequency- and amplitude-sweep data is compared with the prediction of the frequency-response function in a least-squares curve-fitting algorithm. The algorithm is improved by making use of experimentally known information about the location of the bifurcation points. The method is validated by using the extracted parameters to predict the force-response curves at other nearby frequencies.We then compare this technique with two other techniques that have been presented in the literature. In addition to the amplitude- and frequency-sweep technique presented, we apply a backbone curve- fitting technique and a time-domain technique to the second mode of a cantilevered beam. Differences in the parameter estimates are discussed. We conclude by discussing the limitations encountered for each technique. These include the inability to separate the nonlinear curvature and inertia effects and problems in estimating the coefficients of small terms with the time-domain technique.     

Identification of Material Damage Model Parameters: an Inverse Approach Using Digital Image Processing

A reliable prediction of ductile failure in metals is still a wide-open matter of research. Several models are available in the literature, ranging from empirical criteria, porosity-based models and continuum damage mechanics (CDM). One major issue is the accurate identification of parameters which describe material behavior. For some damage models, parameter identification is more or less straightforward, being possible to perform experiments for their evaluation. For the others, direct calibration from laboratory tests is not possible, so that the approach of inverse methods is required for a proper identification. In material model calibration, the inverse approach consists in a non-linear iterative fitting of a parameter-dependent load–displacement curve (coming from a FEM simulation) on the experimental specimen response. The test is usually a tensile test on a round-notched cylindrical bar. The present paper shows a novel inverse procedure aimed to estimate the material parameters of the Gurson–Tvergaard–Needleman (GTN) porosity-based plastic damage model by means of experimental data collected using image analysis. The use of digital image processing allows to substitute the load–displacement curve with other global quantities resulting from the measuring of specimen profile during loading. The advantage of this analysis is that more data are available for calibration thus allowing a greater level of confidence and accuracy in model parameter evaluation.     

AUTOMATIC IDENTIFICATION OF MESOSCOPIC PARAMETERS OF DISCRETE ELEMENTS OF SAND MATERIAL 1)

本文依照四川大学某理论力学教学班实际教学改革的经验,通过具体举例说明计算机技术在理论力学教学中尚未开发的巨大潜力,减小数学运算使学生重点关注理论力学基本原理,批量求解使学生提前接触实际应用案例,普适性求解使学生深化对处理多变量问题的认识。同时本文还探讨了理论力学教学改革的方向和目的,即把教学重点放在普适的教学方法上,借助计算机求解多刚体、多变量问题,以期有助于理论力学教材更好地适应时代发展。     

Identification of nonlinear hysteretic parameters by enhanced response sensitivity approach

Hysteresis is a ubiquitous phenomenon describing the special nonlinear memory-based relation between the input and the output in many physical systems. Identifying the hysteretic parameters is the first step towards practical application of hysteretic models. In this paper, a general framework for parameter identification of nonlinear hysteretic models is developed based on the enhanced response sensitivity approach. To do so, three typical hysteretic models—Bouc–Wen model, bilinear model with kinematic hardening and bilinear model with equal yielding force are analyzed at first and the general way to model a structure with such hysteretic components is established thereafter. Then, the enhanced response sensitivity approach is presented for inverse parameter identification where the key lies in the sensitivity analysis and the trust-region constraint. Particularly, smoothing procedure is introduced to overcome the non-differentiability of bilinear hysteretic functions for sensitivity analysis of bilinear models. Numerical examples are studied to testify the feasibility and performance of the proposed approach.     

Mathematical Modeling, Control, Computer Simulation and Laboratory Experiments of a Spatial Servopneumatic Parallel Robot

In this paper, the special construction of a parallel robot, called spatial servopneumatic multi-axis test facility, will be discussed. The investigations include the following aspects: (i) the laboratory set-up of the robot, (ii) various results obtained in laboratory experiments, taking into account quite different control algorithms and command-input signals, (iii) a comparison of the laboratory experiments with the computer simulations of Part I of this paper, and ({vi}) a quality check of the results compared with the cost of the different controller realizations. The results of both the computer simulations and the laboratory experiments show: (i) The dynamic behavior of the parallel structure can be tremendously improved by using sophisticated nonlinear control algorithms. (ii) This improvement has to be paid by a drastically increased amount of work for deriving the model equations and control algorithms, and by augmented hardware cost of the sensing elements and controller electronics. (iii) Carefully developed model equations and identified model parameters provide theoretical models of the complex parallel structure that are very close to reality. This enables the design engineer to systematically investigate constructive alternatives of the design parameters, sensor and actuator concepts, and control strategies of the MAP prior to their hardware realization.This work has been supported by the German Science Foundation (DFG) under Contract No. Ha 1666/6-3.     

转子系统随机支撑刚度参数的识别

基于Riccati摄动随机传递矩阵方法建立的转子系统特征值与随机参数变量间的函数关系,给出了转子系统随机参数的识别方法和详细步骤,可用于识别随机参数的均值和方差。以改装的Bently实验转子为研究对象,通过大量测试,识别出了转子系统的随机支撑刚度参数,建立了该转子系统的随机参数动力学模型。该模型可用于研究转子系统的随机参数动力学问题。     

基于广义卡尔曼滤波的桥梁结构物理参数识别

基于广义卡尔曼滤波提出了随机荷载作用下桥梁结构物理参数的识别方法。首先,以荷载为观测对象,推导出基于有限元模型的桥梁结构系统的观测方程,以结构待识别的物理参数为状态向量,建立系统状态方程;然后,对该状态方程和观测方程构成的非线性参数系统应用广义卡尔曼滤波,从而识别出结构的物理参数。对一座简支梁桥和一座三跨连续梁桥在不同工况下的物理参数识别进行了数值仿真,结果表明本文方法能够准确地识别桥梁结构全部刚度参数、质量参数和阻尼参数,且具有很强的抗噪性能,从而验证了本文方法的有效性和鲁棒性,可应用于识别大型桥梁结构的物理参数。     

优化方法用于模型校核

在工程实际中,常常会遇到需要选择本构模型和校准参数的模型校核问题。文中采用优化方法实现了复杂模型校核的自动化。文中,首先将各种本构模型映射为整数编号,并根据这些编号来激活相应的本构模型和本构模型参数,解决了本构模型的参数化问题;另外,根据模型校核问题的特点选择了试验结果和计算结果相对误差的平方和作为目标函数。通过这些步骤,用实现了优化方法模型校核自动化。     

Identification of Nonlinear and Viscoelastic Properties of Flexible Polyurethane Foam

Analysis of the steady-state response of a polyurethane foam and masssystem to harmonic excitation is presented. The foam's uni-directionaldynamic behavior is modeled by using nonlinear stiffness, linearviscoelastic and velocity proportional damping components. Therelaxation kernel for the viscoelastic model is assumed to be a sum ofexponentials. The harmonic balance method is used to develop one- andtwo-term approximations to periodic solutions, and the equationsdeveloped are utilized for system identification. The identificationprocess is based on least-squares minimization of a sub-optimal costfunction that uses response data at various excitation frequencies andamplitudes. The effects of frequency range, spacing and amplitudes ofthe harmonic input on the results of the model parameter estimation arediscussed. The identification procedure is applied to measurements ofthe steady-state response of a base-excited foam-mass system. Estimatesof the system parameters at different levels of compression and inputamplitudes are thus determined. The choice of model-order and thefeasibility of describing the system behavior at several inputamplitudes with a single set of parameters are also addressed.     

Identification of nonlinear anti-vibration isolator properties

Vibrations are classified among the major problems for engineering structures. Anti-vibration isolators are used to absorb vibration energy and minimise transmitted force which can cause damage. The isolator is modelled as a parallel combination of stiffness and damping elements. The main purpose of the model is to enable designers to predict the dynamic response of systems under different structural excitations and boundary conditions. A nonlinear identification method, discussed in this paper, aims to provide a tool for engineers to extract information about the nonlinear dynamic behaviour using measured data from experiments. The proposed method is demonstrated and validated with numerical simulations. Thus, this technique is applied to determine the nonlinear parameters of a commercial metal mesh isolator. Nonlinear stiffness and nonlinear damping can decrease with the increase in the amplitude of the base excitation. The softening behaviour of the mesh isolator is clearly visible.     

Identification of the four orthotropic plate stiffnesses using a single open-hole tensile test

The identification of mechanical parameters for real structures is still a challenge. With the improvement of optical full-field measurement techniques, it has become easier, but in spite of many publications showing the feasibility of such methods, experimental results are still scarce. In this paper we present a first step towards a global approach of mechanical identification for composite materials. The chosen mechanical test is an open-hole tensile test according to standard recommendations. For the moment, experimental data are provided by a moiré interferometry setup. The global principle of the identification developed in this paper is to minimize a discrepancy between experimental and theoretical results, expressed as a cost function, using a Levenberg-Marquardt algorithm. This approach has the advantage of having high adaptability, largely because the optical system, the signal processing as well as the mechanical aspects, can be taken into consideration by the model. In this paper we consider different types of cost functions, which are tested using an identifiability criterion. Although mechanically based cost functions have been studied, a simpler mathematical form is finally more efficient. Two different models were tested. The first is an analytical model based on the Lekhnitskii approach. This approach has the advantage of being a meshless solution; however, the results appeared to be partially false due to boundary effects, leading to a second approach, a classical finite element analysis. The resulting identified values are similar to values from classical mechanical tests (within 6%). which, in practice, validates our approach.     

基于转角模态和小波神经网络的连续梁损伤识别研究

基于小波奇异性检测原理和神经网络非线性映射能力,结合结构基本模态参数,提出了一种结合小波神经网络与结构转角模态的损伤识别方法．首先,建立三跨连续梁的有限元模型获取结构模态参数,并对其进行Mexihat小波变换,通过系数图突变点判断结构损伤位置．然后,将小波系数模特征向量作为BP神经网络的输入,分别研究了该方法在单损伤和多损伤工况下的识别能力．最后将不同工况下神经网络预测值与结构实际损伤程度进行对比,得到单处损伤预测误差平均值为0.22%,多处损伤预测误差平均值分别为0.22%和0.18%,结果表明该方法在结构损伤识别方面的有较高有效性及精确度．     

Displacement modal identification method of elastic system under operational condition

Modal identification of engineering structure in operation deals with the estimation of modal parameters from vibration data obtained in working conditions rather than laboratory conditions. After one structure destruction during a flight test, it was strongly required to carry out full-scale model testing to acquire the low-frequency vibration acceleration data of the investigated rocket (its structural dynamic properties could be represented by a beam). These vibration data were used to assess the modal properties of the modified structure. In this paper, a new modal identification method based on vibration displacement is suggested. The displacements of the measured points on the rocket are obtained by the integration of the low-frequency vibration accelerations during free flight test. In the method, the data are filtered through wavelet transform. For comparison, several methods are used to extract the modal frequencies of the investigated beam. In terms of the results of standard deviation of identified frequencies, it is believed that the generalized displacement-based modal identification method is more practicable in modal identification for similar problems.     

平流层飞艇气动参数辨识

进入21世纪以来,随着科技的飞速发展,世界上掀起了研究和开发平流层平台的热潮。飞艇作为平流层平台可以实现无线通信、空间观测、大气测量以及军事侦查等目的。本文首先将飞艇所受的气动力分成由于来流速度产生的定常气动力和飞艇转动引起的非定常气动力两部分,通过理论分析建立了飞艇的气动力模型,从而得到需要辨识的气动参数。其次建立了以浮心为原点的六自由度非线性动力学模型和一种基于混合遗传算法的气动力系数辨识方法——混合遗传算法（遗传算法＋单纯型法）与极大似然法相结合的方法,并利用该方法对飞艇的气动参数进行辨识。通过仿真结果验证了该方法实用性和有效性。最后通过对气动参数的准确值与辨识值的分析比较,得出各个参数对飞艇运动性能的影响情况。     

Identification of material parameters for inelastic constitutive models: Stochastic simulations for the analysis of deviations

For parameter identification a distance function between the measured and the simulated data has to be minimized. Therefore, the influence of three different norms used in the definition of such a distance function is investigated. The nonlinear optimization problem is solved using a modified random search algorithm originally proposed by Price (1978). Next a stochastic model for the generation of artificial test data is presented. This model is used for a stochastic simulation of test data (constant strain rate tension with relaxation and creep). From these artificial data the material parameters of the model of Chan, Bodner and Lindholm are identified. To measure the quality of the identified material parameters their mean values and empirical standard deviations are computed. Furthermore, the coefficients of the empirical correlation matrix for the material parameters are computed. The model responses for tensile tests with the parameter vector generated from all tests and with the estimated parameters (from stochastic simulations) differ not considerably. However, for the creep tests the different parameter estimations lead to quite different model responses. Received October 22, 1999     

Nonlinear System Identification of Multi-Degree-of-Freedom Systems

A nonlinear system identification methodology based on theprinciple of harmonic balance is extended tomulti-degree-of-freedom systems. The methodology, called HarmonicBalance Nonlinearity IDentification (HBNID), is then used toidentify two theoretical two-degree-of-freedom models and anexperimental single-degree-of freedom system. The three modelsand experiments deal with self-excited motions of afluid-structure system with a subcritical Hopf bifurcation. Theperformance of HBNID in capturing the stable and unstable limitcycles in the global bifurcation behavior of these systems is alsostudied. It is found that if the model structure is well known,HBNID performs well in capturing the unknown parameters. If themodel structure is not well known, however, HBNID captures thestable limit cycle but not the unstable limit cycle.