The matric algorithm of Lyapunov exponent for the experimental data obtained in dynamic analysis

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The influence of the different distributed phase-randomized on the experimental data obtained in dynamic analysis

I.IntroductionSince1980manyscholarsaroundtheworldhavepaidmoreattentiontothequestionsoftimeseries.Inthereallifesometimeseriesrepresentthecharacterthatisdeterminedasrandomprocesstimeseries,andothersrepresentthecharacterthatisdeterminedasnonlinearchaotictilneseries.Soitisveryimportanttodistinguishthepropertyoftherealtimeseries.Ref.[11gaveustheftlndamentalmethodtodifferentiatethenonlinearchaotictimeseriesfromrandomtimeseries(thatiscalledphase-randomizedmethod).Ref.[2]gaveusthecalculatingmethodofc…     

The state space reconstruction technology of different kinds of chaotic data obtained from dynamical system

Certain deterministic nonlinear systems may show chaotic behavior. We consider the motion of qualitative information and the practicalities of extracting a part from chaotic experimental data. Our approach based on a theorem of Takens draws on the ideas from the generalized theory of information known as singular system analysis. We illustrate this technique by numerical data from the chaotic region of the chaotic experimental data. The method of the singular-value decomposition is used to calculate the eigenvalues of embedding space matrix. The corresponding concrete algorithm to calculate eigenvectors and to obtain the basis of embedding vector space is proposed in this paper. The projection on the orthogonal basis generated by eigenvectors of timeseries data and concrete paradigm are also provided here. Meanwhile the state space reconstruction technology of different kinds of chaotic data obtained from dynamical system has also been discussed in detail. The project supported by the National Natural Science Foundation of China (19672043)     

STUDY ON PREDICTION METHODS FOR DYNAMIC SYSTEMS OF NONLINEAR CHAOTIC TIME SERIES＊

The prediction methods for nonlinear dynamic systems which are decided by chaotic time series are mainly studied as well as structures of nonlinear self-related chaotic models and their dimensions. By combining neural networks and wavelet theories, the structures of wavelet transform neural networks were studied and also a wavelet neural networks learning method was given. Based on wavelet networks, a new method for parameter identification was suggested, which can be used selectively to extract different scales of frequency and time in time series in order to realize prediction of tendencies or details of original time series. Through pre-treatment and comparison of results before and after the treatment, several useful conclusions are reached:High accurate identification can be guaranteed by applying wavelet networks to identify parameters of self-related chaotic models and more valid prediction of the chaotic time series including noise can be achieved accordingly.     

Threshold value for diagnosis of chaotic nature of the data obtained in nonlinear dynamic analysis

I.IntroductionInreallife,inengineering,innature,andinthesociety,thereexisteverykindoftimeseriesproblems.Becausenonlinearfactorsareextensivelyimplicatedilltiledynamicsystemsofvariousfields,thebehaviourofthesystemscantakethecomplicatedanddiverseforms.Atpresent,twodifferentmethodsareusedtostudytheproblemoftinleseries.Ollemethodistoadoptthetheoryofrandomprocessonthebasisofprobabilitytheory.Andthistheoryisusedtofoundthesystemlinearmodel.Thismethodhasalreadybeenstudiedperfectly.Forexample,determin…     

Study on the Prediction Method of Low-Dimension Time Series that Arise from the Intrinsic Nonlinear Dynamics

The prediction methods and its applications of the nonlinear dynamic systems determined from chaotic time series of low-dimension are discussed mainly. Based on the work of the foreign researchers, the chaotic time series in the phase space adopting one kind of nonlinear chaotic model were reconstructed. At first, the model parameters were estimated by using the improved least square method. Then as the precision was satisfied, the optimization method was used to estimate these parameters. At the end by using the obtained chaotic model, the future data of the chaotic time series in the phase space was predicted. Some representative experimental examples were analyzed to testify the models and the algorithms developed in this paper. The results show that if the algorithms developed here are adopted, the parameters of the corresponding chaotic model will be easily calculated well and true. Predictions of chaotic series in phase space make the traditional methods change from outer iteration to interpolations. And if the optimal model rank is chosen, the prediction precision will increase notably. Long term superior predictability of nonlinear chaotic models is proved to be irrational and unreasonable. Paper from Chen Yu-shu, Member of Editorial of Committee, AMM Foundation item: the National Natural Science Foundation of China (19990510); the National Key Basic Research Special Fund(G1998020316) Biography: Ma Jun-hai(1965-), Professor, Doctor     

Proper application of a kind of matrix construction method in physical parameter identification of dynamic model

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Lyapunov functions for a non-linear model of the X-ray bursting of the microquasar GRS 1915+105

This paper introduces a biparametric family of Lyapunov functions for a non-linear mathematical model based on the FitzHugh-Nagumo equations able to reproduce some main features of the X-ray bursting behaviour exhibited by the microquasar GRS 1915+105. These functions are useful to investigate the properties of equilibrium points and allow us to demonstrate a theorem on the global stability. The transition between bursting and stable behaviour is also analyzed.     

The analysis of the spectrum of Lyapunov exponents in a two-degree-of-freedom vibro-impact system

In the study of dynamical systems, the spectrum of Lyapunov exponents has been shown to be an efficient tool for analyzing periodic motions and chaos. So far, different calculating methods of Lyapunov exponents have been proposed. Recently, a new method using local mappings was given to compute the Lyapunov exponents in non-smooth dynamical systems. By the help of this method and the coordinates transformation proposed in this paper, we investigate a two-degree-of-freedom vibro-impact system with two components. For this concrete model, we construct the local mappings and the Poincaré mapping which are used to describe the algorithm for calculating the spectrum of Lyapunov exponents. The spectra of Lyapunov exponents for periodic motions and chaos are computed by the presented method. Moreover, the largest Lyapunov exponents are calculated in a large parameter range for the studied system. Numerical simulations show the success of the improved method in a kind of two-degree-of-freedom vibro-impact systems.     

基于等效阻尼理论的金属橡胶弹性迟滞力学模型及实验研究

针对弹性多孔金属橡胶非线性迟滞特性力学行为,将迟滞恢复力-位移曲线分解为非线性单值曲线和椭圆,并将等效阻尼理论用于动态力学性能参数识别,从而建立了一种新型的适用于黏弹性阻尼材料的宏观唯象力学模型。采用不同相对密度的环形金属橡胶进行动态实验测试,以验证理论模型的准确性,结果表明该模型可将具有非线性特性的金属橡胶系统进行降阶处理,提高金属橡胶力学模型的预测效率,并能很好地描述金属橡胶的迟滞力学行为。另外,研究了在不同激励频率条件下金属橡胶的阻尼耗能特性。实验结果表明:在高频加载的条件下,黏性阻尼系数对动态加载频率不敏感,阻尼耗能与加载幅值之间呈线性正相关。基于等效阻尼理论的弹性迟滞力学模型具有一定的普适性,可进一步推广应用于类似弹性多孔材料的力学性能表征,为其工程应用提供理论基础。     

拱坝-地基动力体系的简化计算模型及其在地震作用下的动力反应分析

通过对拱坝地基的半无限空间动力体系的分析,提出了拱坝－地基动力相互作用问题的简化求解途径,并结合小湾拱坝进行了实际分析。结果表明,这种直接应用于时域求解的简化模型,既反映了影响相互作用的主要因素,又使计算工作量大大减少,结果可靠合理,便于工程上的推广应用,同时为进一步进行非线性体系在时域中的简化计算打下了基础。     

Development of an efficient numerical model for hail impact simulation based on experimental data obtained from pressure sensitive film

Aircraft are subjects to a number of unpredictable loadings that can seriously affect their performance. In the spirit of ever increasing the safety of passengers, hail impact has been studied. This paper shows the progress that has been made using pressure sensitive film to measure the hail impact event. Moreover, the smooth particle hydrodynamics (SPH) method in LS-DYNA is used to create a numerical model in order to validate the numerical hail model so that it can be used in future advanced simulations of hail impact on components of aircraft. Results show that the SPH method can be effectively used to create a numerical hail model and that pressure sensitive film is a simple and inexpensive tool to capture the experimental data.     

The study on the chaotic motion of a nonlinear dynamic system

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仿真转台伺服系统动态模型辨识与计算

仿真转台广泛应用于光电制导导引头及其对抗的仿真,对某型仿真转台进行高精度模型辨识可以有效提高系统的动态控制精度和设计效率。基于此,提出了一种转台伺服系统频率特性自动测试方法,根据测试数据采用参数递阶辨识方法分段拟合得到了被控对象的高精度传递函数模型。辨识结果与实测数据相比:在体现伺服系统重要特征的中低频段,幅度绝对误差1 d B,相位绝对误差2°;在高频段,得到了复杂的机械谐振环节特性,验证了被控对象传递函数模型的准确性。对于转台的动态精度计算,采用频率设计分析建模方法,结合被控对象高精度传递函数和实际校正环节模型得到了转台的动态精度计算模型,通过比较同一输入情况下实测动态误差与模型输出误差数据验证了模型准确性,结果表明了该方法的有效性。建立的动态精度计算模型能够反映实际系统的动态过程和动态误差变化规律,也为同类设备伺服系统的模型辨识和动态精度分析计算提供了方法。     

A method for calculating the lyapunov exponent spectrum of a periodically excited non-autonomous dynamical system

The relation between the Lyapunov exponent spectrum of a periodically excited non-autonomous dynamical system and the Lyapunov exponent spectrum of the corresponding autonomous system is given and the validity of the relation is verified theoretically and computationally. A direct method for calculating the Lyapunov exponent spectrum of non-autonomous dynamical systems is suggested in this paper, which makes it more convenient to calculate the Lyapunov exponent spectrum of the dynamical system periodically excited. Following the definition of the Lyapunov dimensionD _L ^(A) of the autonomous system, the definition of the Lyapunov dimensionD _L of the non-autonomous dynamical system is also given, and the difference between them is the integer 1, namely,D _L ^(A) −D_L=1. For a quasi-periodically excited dynamical system, similar conclusions are formed. Project supported by the National Natural Science Foundation of China (No. 19772027), the Science Foundation of Shanghai Municipal Commission of Education (99A01) and the Science Foundation of Shanghai Municipal Commission of Science and Technology (No. 98JC14032).     

Bammann-Chiesa-Johnson粘塑性本构模型材料参数的一种识别方法

粘塑性本构模型能否成功模拟金属高应变率大应变变形过程依赖于材料参数识别结果的好坏。由于BCJ模型考虑了应变率、温度与材料硬化之间的耦合效应以及应变率、温度历史效应,同时模型中包含了多个材料参数,因此很难通过试验直接识别模型的材料参数。本文针对BCJ模型中的耦合效应和历史效应,基于对模型中材料参数物理涵义的界定,给出了一种对材料参数解耦、分离并进行估计的方法,获得了模型材料参数估计公式,估计了材料参数的取值范围。在此基础上,编制了BCJ模型应力积分径向返回算法和粒子群优化算法的计算程序,应用重新设计了BCJ模型耦合效应和历史效应的反分析方法,在参数取值范围内对材料参数进行了优化识别。以OFHC Cu为例,应用提出的识别方法对BCJ模型的材料参数进行了识别,计算结果和试验结果符合较好。     

基于混合遗传算法的动力系统阻尼参数识别方法

将动力系统阻尼参数识别反问题转化为非线性优化问题处理,提出了基于遗传算法的动力系统阻尼参数识别方法。为了提高简单遗传算法的计算效率和处理早熟问题,将模拟退火算法与遗传算法相结合,建立了混合遗传算法。数值计算结果表明,本文所建立的方法对于求解参数识别反问题和非线性优化问题是非常有效的,并且具有良好的鲁棒性和全局收敛能力。     

The Lyapunov exponent for a codimension two bifurcation system that is driven by a real noise

For a co-dimension two bifurcation system on a three-dimensional central manifold, which is parametrically excited by a real noise, a model of enhanced generality is developed in the present paper by assuming the real noise to be a component of the output of a linear filter system—a zero-mean stationary Gaussian diffusion vectoral process, which conforms with the detailed balance condition. The strong mixing condition is removed in the present paper. To handle the complexities encountered in the present work, an asymptotic analysis approach and the eigenfunction expansion of the solution to the relevant FPK equation are employed in the construction of the asymptotic expansions of the invariant measure and the maximal Lyapunov exponents for the relevant system.     

基于数据驱动模型求解热传导反问题

热传导反问题求解在工程领域具有重要的应用价值.本文发展数据驱动模型识别了管道内壁几何形状和皮肤肿瘤生长参数等热传导反问题.在管道内壁几何形状识别问题中,首先采用随机生成模型结合有限元法求解热传导正问题,并采用有效导热系数转化的思想,建立机器学习模型,求解了测点温度与有效导热系数之间的抽象映射关系,进而实现管道内壁几何形...