非高斯噪声和正弦周期力激励的阻尼谐振子系统的信息熵

阻尼谐振子广泛应用于固体理论、量子场论、量子力学和量子光学等不同的研究领域．信息熵在研究随机系统的动力学特性方面扮演着非常重要的角色．本文对非高斯噪声和正弦周期力激励的阻尼谐振子系统的信息熵变化率进行研究．首先通过路径积分近似,把非高斯噪声近似转化为高斯色噪声,得到了系统的Fokker-Planck方程,然后利用线性变换的方法简化了系统的Fokker-Planck方程,并结合Shannon信息熵的定义和Schwartz不等式原理得出了阻尼谐振子系统的信息熵变化率上界的表达式,最后分析了非高斯噪声和系统各参数对熵变化率上界的影响．     

参数激励驱动微陀螺系统的非线性振动特性研究

对于一类典型的切向梳齿驱动型微陀螺,建立两自由度、具有刚度立方非线性和参数激励驱动的微陀螺系统动力学模型。考虑主参数共振和1∶1内共振的情况,利用多尺度法获得周期解的解析形式,并利用分岔理论,得到Hopf分岔条件,结合数值模拟系统的动力学响应,揭示系统参数对驱动和检测模态振幅和分岔行为的影响机制。研究结果表明,在1∶1内共振和较大的载体角速度下,激励频率的变化容易引起微陀螺振动系统的多稳态解、振幅跳跃现象和概周期响应等复杂动力学行为。     

非高斯噪声激励下分段非线性系统的平均首次穿越时间

噪声诱导的逃逸问题出现在众多研究领域,平均首次穿越时间作为用来表征粒子逃逸现象的重要特征量,现已被广泛应用于电子器件的开关时间及双稳器件的寿命等问题的研究之中.本文研究了由乘性非高斯噪声和加性高斯白噪声共同驱动下分段非线性系统的平均首次穿越时间问题.运用路径积分法、统一色噪声近似和最速下降法,得到了系统平均首次穿越时间的表达式.通过数值计算发现,在非高斯噪声偏离参数、噪声关联时间和互关联强度的作用下,非高斯噪声强度的增加会导致平均首次穿越时间曲线出现单峰结构,而加性噪声强度的增加会导致平均首次穿越时间的单调减小,这表明在该模型中非高斯噪声和高斯噪声对平均首次穿越时间的影响是不同的.此外还进一步讨论了非高斯噪声偏离参数、噪声关联时间和噪声互关联强度对平均首次穿越时间的影响.     

混沌态杜芬振子与弱正弦信号参量估计

建立了一个对微弱正弦信号参量变化极其敏感的动力学系统.首先对多参量简化杜芬方程进行了改进,采用梅尔尼科夫过程函数讨论了方程的解和微分流形的演化情况;分析了非高斯色噪声对杜芬振子混沌运动行为的影响;进而提出了一种新的非高斯色噪声背景下正弦信号参量估计方法.理论分析和仿真实验都表明,此杜芬振子混沌状态下对任何零均值噪声具有免疫力,对正弦信号参量变化极为敏感.     

泊松白噪声激励下斜拉索的面内随机振动

目前针对斜拉索非线性随机振动的研究已广泛开展,但仅限于高斯随机激励情形。然而,现实中大部分的随机扰动都是非高斯的。若使用高斯激励模型将产生较大误差。假设拉索所受非高斯激励为泊松白噪声,研究了泊松白噪声激励下斜拉索面内随机振动。推导了受泊松白噪声激励的斜拉索面内振动的随机微分方程,建立了支配系统平稳响应概率密度函数的广义FPK方程。提出迭代加权残值法求解了四阶广义FPK方程,得到了系统响应概率密度函数的近似稳态闭合解。考察了垂跨比、阻尼系数以及脉冲到达率对拉索面内随机振动响应的影响。结果表明:拉索的响应随着垂跨比的增大,响应呈现不对称现象愈加明显;随阻尼比增加,系统响应得到显著抑制;当脉冲到达率增大,拉索的响应也随之增大,并逐渐接近于高斯白噪声激励的情形。另外,获得的理论结果与蒙特卡罗模拟的结果吻合地非常好。     

一类二阶迟滞非线性控制系统简谐激励响应的IHB分析方法

针对一类迟滞特性和线性特性可分离的二阶迟滞非线性控制系统,用Backlash神经网络模型逼近系统迟滞非线性部分,建立动力学模型,采用增量谐波平衡法（IHB法）求解该类含比例控制器的迟滞非线性闭环控制系统在简谐激励下的稳态周期解,并引入Floquet理论分析系统周期解的稳定性。通过Runge-Kutta数值积分法对近似迭代法的精确性进行了验证,最后分析了控制器参数对系统性能的影响。     

非高斯噪声中随机信号的渐近最优检测

本文研究了非高斯噪声中随机信号的检测问题。基于随机信号的参数模型和广义似然比检测理论,导出了非高斯噪声中随机信号Rao检测的数学解析式,其检测性能渐近等同于广义似然比检测但计算更有效。仿真结果表明,该检测器性能大大优于传统的能量检测器以及高斯噪声假设下的广义似然比检测器。     

基于FPK方程的一类非线性问题辨识方法

一类受高斯白噪声激励的非线性动力学方程能通过求解对应的ＦＰＫ方程得到精确稳态解。本文基于这一结果导出非线性恢复力与系统位移输出的概率度的关系,将动力学系统中非线性（恢复力的非线性）结构参数的辨识问题论为求解系统的概率密度,是一种新的尝试,结果经数值仿真是可行的。但所研究系统限于自由度非线性恢复力系统,其中线性部分的参数已知,待辨识部分为非线性恢复力。     

非自治旋转机械系统自同步与异结构同步的研究

摘要:研究一类非自治旋转机械系统的复杂动力学行为.通过系统运动的拉格朗日方程和牛顿第二定律,建立了机械式离心调速é器系统的动力学方程.通过系统的分岔图和Lyapunov指数研究系统的混沌行为,通过仿真Poincaré截面分析系统通向混凝沌的道路,并且验证该系统的分岔图与Lyapunov指数谱是完全吻合的.基于Lyapunov稳定性理论,采用非线性控制方法进行一类不同阶非自治混沌系统之间的同步控制的研究．通过构造合适的控制函数,成功地实现两个不同阶混沌系统之间的同步控制,并用数值的仿真进一步证明该方法的有效性．     

某混合动力汽车非稳态车内声品质评价研究

针对某混合动力汽车非稳态工况下的车内声品质评价进行研究。采集该车内不同位置、不同驱动模式以及不同车速情况下的车内噪声样本,对不同的非稳态工况进行客观参量分析,得出电机单独驱动模式下可以用尖锐度评价非稳态车内声品质、混合驱动与发动机单独驱动模式下可以用响度评价非稳态车内声品质的结论。基于BP神经网络模型,进行基于心理声学客观参量与临界频率带解析小波分解的非稳态车内声品质评价,预测结果表明后者的预测效果优于前者,且稳定性较高。     

Importance sampling for reliability assessment of dynamic systems under general random process excitation

This paper develops a reliability assessment method for dynamic systems subjected to a general random process excitation. Safety assessment using direct Monte Carlo simulation is computationally expensive, particularly when estimating low probabilities of failure. The Girsanov transformation-based reliability assessment method is a computationally efficient approach intended for dynamic systems driven by Gaussian white noise, and this approach can be extended to random process inputs that can be represented as transformations of Gaussian white noise. In practice, dynamic systems may be subjected to inputs that may be better modeled as non-Gaussian and/or non-stationary random processes, which are not easily transformable to Gaussian white noise. We propose a computationally efficient scheme, based on importance sampling, which can be implemented directly on a general class of random processes — both Gaussian and non-Gaussian, and stationary and non-stationary. We demonstrate that this approach is in fact equivalent to Girsanov transformation when the uncertain inputs are Gaussian white noise processes. The proposed approach is demonstrated on a linear dynamic system driven by Gaussian white noise and Brownian bridge processes, a multi-physics aero-thermo-elastic model of a flexible panel subjected to hypersonic flow, and a nonlinear building frame subjected to non-stationary non-Gaussian random process excitation.     

Computation of response moments of high dimensional MDOF structure excited by stationary non-Gaussian random fields

Output moments of a non-linear dynamical system excited by a non-Gaussian random field can be obtained in practice only by simulation techniques. When the dynamical system can be decomposed in a low dimension non-linear part acting on a high dimension linear part, the original problem reduces to calculate output moments of a high dimension linear system. The proposed method suggests that work should be directed in the frequency domain. Time trajectories are then obtained through Fourier transform. Such a procedure does not introduce any approximation errors due to the time integration numerical scheme nor does it introduce any transient state. Further quasi-static correction terms can be introduced when a truncated modal basis is utilized in order to describe the low frequency dynamic response.     

Non-Gaussian models for stochastic mechanics

Memoryless transformations of Gaussian processes and transformations with memory of the Brownian and Lévy processes are used to represent general non-Gaussian processes. The transformations with memory are solutions of stochastic differential equations driven by Gaussian and Lévy white noises. The processes obtained by these transformations are referred to as non-Gaussian models. Methods are developed for calibrating these models to records or partial probabilistic characteristics of non-Gaussian processes. The solution of the model calibration problem is not unique. There are different non-Gaussian models that are equivalent in the sense that they are consistent with the available information on a non-Gaussian process. The response analysis of linear and non-linear oscillators subjected to equivalent non-Gaussian models shows that some response statistics are sensitive to the particular equivalent non-Gaussian model used to represent the input. This observation is relevant for applications because the choice of a particular non-Gaussian input model can result in inaccurate predictions of system performance.     

Stationary probability density of a class of non-linear dynamical systems to stochastic excitation

The response of a dynamical system to Gaussian white-noise excitations may be represented by the Markov process whose probability density is governed by the well-known Fokker-Plank equation. In this paper a general procedure is developed to obtain the solution for Fokker-Plank equation in the state of statistical stationary. The dynamical systems considered are generally non-linear. This paper also demonstrates that the stationary joint probability density of the coordinates and velocity may possess the form of a separate product for the systems both non-linear damping and non-linear restoring forces.     

两种非高斯海洋环境噪声统计模型分析

海洋环境噪声是影响声呐工作的主要因素之一,噪声模型的选取十分重要,普遍采用的高斯噪声模型在很多情况下存在局限性。引出两种非高斯噪声模型匹配实际非平稳的海洋环境噪声:广义自回归条件异方差模型(Generalized Autoregressive Conditional Heteroscedasticity,GARCH)和双模模型,通过分析两种噪声的概率密度分布函数,并与高斯模型噪声和实测海洋环境噪声比较得出两种噪声模型的适用性。GARCH(1,1)模型通过调节参数可以吻合大部分浅海和深海海洋环境噪声,双模模型则只对浅海某些情况存在适用性,而对深海吻合性较差。两种噪声模型的统计特性分析表明它们可以适用于高斯噪声模型存在局限的非平稳环境下。     

Identification of stochastic loads applied to a non-linear dynamical system using an uncertain computational model and experimental responses

The paper is devoted to the identification of stochastic loads applied to a non-linear dynamical system for which experimental dynamical responses are available. The identification of the stochastic load is performed using a simplified computational non-linear dynamical model containing both model uncertainties and data uncertainties. Uncertainties are taken into account in the context of the probability theory. The stochastic load which has to be identified is modelled by a stationary non-Gaussian stochastic process for which the matrix-valued spectral density function is uncertain and is then modelled by a matrix-valued random function. The parameters to be identified are the mean value of the random matrix-valued spectral density function and its dispersion parameter. The identification problem is formulated as two optimization problems using the computational stochastic model and experimental responses. A validation of the theory proposed is presented in the context of tubes bundles in Pressurized Water Reactors.     

Non-Gaussian solution for random rocking of slender rigid block

This paper adopts a random vibration approach to study the response of the slender rigid block to seismic action. The problem is strongly non-linear because of (i) the restoring term and (ii) the quadratic dissipation of energy due to the inelastic impacts, modeled as an impulsive process. The excitation process is firstly assumed to be a Gaussian white noise; secondly, a non-stationary filtered Gaussian white noise is assumed to simulate seismic shaking more accurately. The solution of the associated Fokker-Planck equation in terms of moments of the response is obtained by means of a non-Gaussian closure technique, that enables the complete statistical definition of the approximated transient response process to be achieved. The mean upcrossing rates and the response spectra in terms of displacement are evaluated. The reliability of the solutions derived is assessed by comparing them with Monte Carlo simulations.     

A copula-based Gaussian mixture closure method for stochastic response of nonlinear dynamic systems

Gaussian closure method is commonly used in the analysis of nonlinear stochastic systems. However, Gaussian closure may lead to unacceptable errors when system response is very much different from being Gaussian, and accuracy of the method decreases as the nonlinearity of the system increases. The need for better accuracy in strongly non-linear problems has caused the development of non-Gaussian closure schemes. In this paper, we develop a new copula-based Gaussian mixture closure method for randomly excited nonlinear systems. Our method relies on the assumption of marginal PDF of response in terms of finite Gaussian mixture model, and the derivation of joint PDF with aid of dependence modeling of Gaussian copula. By substituting the non-Gaussian PDF representation into moment equations of nonlinear system, we further develop an optimization-based closure scheme for the solution of the unknown parameters in joint PDF. In this way, PDF and thus, moments of response of highly nonlinear system can be described in a more flexible and robust way. Effectiveness of the new closure method is demonstrated by a nonlinear and a Duffing oscillator that are subjected to Gaussian white noise. The results are compared with the Gaussian closure and exact solution. It has been shown that Gaussian closure is a special case of the new closure method, and accuracy of Gaussian closure is the lower bound of that of the new closure method.     

Characteristic function equations for the state of dynamic systems with Gaussian, Poisson, and Lévy white noise

The Itô formula for semimartingales is applied to develop equations for the characteristic function of the state of linear and non-linear dynamic systems with Gaussian, Poisson, and Lévy white noise, viewed as the formal derivatives of Brownian, compound Poisson, and Lévy processes, respectively. These equations can be obtained if the drift and diffusion coefficient of a dynamic system are polynomials of the system state and the driving noise is Gaussian or Poisson. It was not possible to derive equations for the characteristic function for the state of systems driven by Lévy white noise. Numerical results are presented for dynamic systems with real-valued states driven by Gaussian, Poisson, and Lévy white noise processes.     

基于现场实测临海地区特大型冷却塔风振响应非平稳特性研究

忽视特大型冷却塔风振响应的非平稳特征可能会导致对结构响应极值的估算偏差和风振作用特性的错误理解。为此,以某沿海地区特大型冷却塔(高190 m)为研究对象,通过现场实测获取了超高雷诺数和真实湍流条件下特大型冷却塔的风振响应信号;在对实测信号进行降噪滤波处理后进行了不同时距的信号非平稳识别,并分别基于平稳分析模型和非平稳分析模型对特大型冷却塔的响应统计值、峰值因子和极值响应进行对比研究。研究结果表明:临海地区特大型冷却塔风振响应表现出较强的非平稳性,部分响应信号的"大偏斜"或"高峰态"现象是由非平稳特征引起,采用非平稳模型可以更有效地判别信号的真实非高斯特征;此外,响应峰值因子普遍大于3.5,忽视非平稳特性将导致极值估计的缺陷,既无法提供足够的保证率,又降低了响应极值计算结果的经济性。