Predicting vibration signals of automobile engine using chaos theory

Condition monitoring and life prediction of the vehicle engine is an important and urgent problem during the vehicle development process. The vibration signals that are closely associated with the engine running condition and its development trend are complex and nonlinear. The chaos theory is used to treat the nonlinear dynamical system recently. A novel chaos method in conjunction with SVD (singular value decomposition) denoising skill are used to predict the vibration time series. Two types of time series and their prediction errors are provided to illustrate the practical utility of the method.     

混沌免疫多目标算法求解认知引擎参数优化问题

合理的认知引擎参数设置可以提高频谱的使用性能. 通过分析认知无线网络中的认知引擎参数配置, 给出了其数学模型, 并将其转化为一个多目标优化问题, 进而提出一种基于混沌免疫多目标优化的求解方法. 算法使用Logistic混沌映射初始化种群, 并在每一代将混沌特性用于最优解集的搜索; 设计了适合此问题的免疫克隆算子和抗体群更新算子, 保证了Pateto最优解集分布的多样性和均匀性. 最后, 在多载波环境下对算法进行了仿真实验. 结果表明, 算法可以根据信道条件和用户服务的动态变化, 自适应调整各个子载波的发射功率和调制方式, 可以求出更多满足偏好需求的解, 满足认知引擎参数优化要求.     

基于混沌理论的太阳黑子数平滑月均值预报

太阳黑子活动长期预报对航天、通讯、防灾等具有重要的指导意义. 针对加权一阶局域法在多步预测时存在累积误差效应, 建立了基于相空间重构技术的径向基函数神经网络预测模型. 用该模型对第22, 23 太阳周黑子数平滑月均值进行逐月预报, 并与实测值进行比较. 结果表明, 预报的绝对误差可以控制在15.00 以内, 平均绝对误差分别为5.47, 2.83, 相对误差控制在15.00%以内, 平均相对误差分别为5.45%, 4.60%, 验证了该模型在预测太阳黑子数时具有较高的精度. 将该预测模型用于第24 太阳周黑子数平滑月均值预报, 做出了自2009 年1月到2019年12月共132 个月的黑子数平滑月均值的预报, 指出黑子数平滑月均值的最大值为104.77, 将出现的时间为2013年1月.     

混沌中信号的投影滤波

根据混沌的确定性和几何结构特征,提出了预测性邻点选取方法和基于Delaunay三角化的邻点选取方法,改进了降低混沌中噪声的投影方法,建立了新的正交局部投影算法,给出了优化参数选择法则.这种方法成功地应用于提取Lorenz混沌中的微弱信号,在信噪比不低于-80dB条件下,能够准确提取信号信息.数值实验表明该投影滤波方法具有高度的稳定性和可靠性,是提取混沌中微弱信号的十分有效方法.     

Longitudinal vibration of cracked nanobeams using nonlocal elasticity theory

The aim of this paper is to study the longitudinal frequency of a cracked nanobeam. The frequency equation of the nanobeam with clamped–clamped and clamped–free boundary conditions is derived based on the nonlocal elasticity theory. According to the equation, it can be found that the effects of the crack parameter, crack location, and nonlocal parameter on the longitudinal frequency of the cracked nanobeam are significant. The frequency decreases with an increase of the crack parameter. However, the increasing nonlocal parameter results in a decrease of the crack effect on the frequency. In addition, when the crack location is near the support, a larger decrease in the frequency can be observed.     

双路激光混沌复用系统的混沌同步及安全性能研究

针对一种新型的双路激光混沌复用系统, 建立相应的速率方程模型, 详细分析了两个主激光器的单个参数失配、多个参数同时失配、反馈强度差异以及频率失谐对混沌同步性能的影响, 并对此复用系统的安全性能和频谱性能进行了研究. 研究结果表明: 采用参数失配方案, 通过合理选择两个主激光器的参数, 可以保证两个主激光器之间的同步性能较差而两对主从激光器间实现高品质的混沌同步, 因此满足双路激光混沌复用的条件; 两个主激光器之间的参数失配对它们之间的同步性能影响较大, 然而对配对主从激光器间同步性能的影响并不明显, 进一步说明参数失配方案的有效性和可行性. 另外, 通过自相关函数和频谱分别分析混沌复用信号的时域和频域特征, 发现双路激光混沌复用系统可提供更高的安全性.     

复摆振动中的混沌现象

利用组合物理实验仪,研究了复摆振动中的混沌现象,分析了产生混沌的物理条件,并给出不同条件下的混沌图形.     

最小二乘支持向量域的混沌时间序列预测

从支持向量域SVD(Support Vector Domain)出发，根据Takens延时相空间重构思想，利用支持向量机非线性映射，建立了混沌时间序列和混沌非线性相轨迹运动的SVD预测模型.采用数据集作为支持对象元素，机器自学习缩小模型泛化误差的上界，利用最小二乘支持向量域(SVD)，预测了Henon/Lorenz/Rossler三种混沌时间序列.预测结果表明，三种预测模型将集合映射到一个更高维特征空间，通过嵌入维数，实现了序列预测，误差随嵌入维数变化趋于恒定，与支持向量机(SVM)相比，SVD所需支持向量少，收敛速度快，鲁棒性强，核函数选择容易灵活，且存在自适应方法.网格点数提高了10—20倍，序列预测在小样本、非线性、未知概率密度条件下，预测和实际值取得了一致. 关键词： 支持向量域 混沌 最小二乘 时间序列预测     

Image quality assessment using the singular value decomposition theorem

In objective image quality metrics, one of the most important factors is the correlation of their results with the perceived quality measurements. In this paper, a new method is presented based on comparing between the structural properties of the two compared images. Based on the mathematical concept of the singular value decomposition (SVD) theorem, each matrix can be factorized to the products of three matrices, one of them related to the luminance value while the two others show the structural content information of the image. A new method to quantify the quality of images is proposed based on the projected coefficients and the left singular vector matrix of the disturbed image based on the right singular vector matrix of the original image. To evaluate this performance, many tests have been done using a widespread subjective study involving 779 images of the Live Image Quality Assessment Database, Release 2005. The objective results show a high rate of correlation with subjective quality measurements.     

混沌的模糊神经网络逆系统控制

提出用Sugeno型的模糊推理神经网络建立混沌系统的逆系统模型,并采用逆系统方法进行混沌的控制.这种方法的特点是可以不必建立混沌系统的解析模型,通过模糊神经网络学习混沌系统的运动规律,通过学习获得的规律对混沌进行有效的控制,并且该控制方法可以控制混沌系统以一定精度跟踪连续变化的给定信号.理论分析及针对虫口模型和Henon模型仿真研究证明了该方法的有效性 关键词： 混沌 模糊神经网络 逆系统控制     

利用阵发混沌现象测定未知信号参数

利用Duffing方程对频率的极端敏感性产生阵发混沌现象,研究了一种利用该现象定量检测未知的微弱周期信号的各项参数的新方法,通过理论分析和实例仿真证明了该方法的可行性,并针对仿真结果提出了改进措施,提高了检测精度.     

Geometrically qualified ESPI vibration analysis of an engine

This paper presents an application in the automotive industry where a combination of electronic speckle-pattern interferometry and laser doppler velocimetry were used at a critical stage in the design process of an internal combustion engine. Combined deformation and surface relief measurements were used to study the phase and amplitude of deformation of a vibrating engine. The relief data was combined with the interferometer geometry and used to geometrically correct the deformation data, in an effort to improve accuracy. The measurements allowed rapid identification and quantification of design weaknesses, particularly those causing undesirable resonances. This led to a significant reduction in the design time and lowering of costs, when compared with existing design optimisation methods.     

分子高激发振动态的动力学特性研究

运用经典哈密顿代数方法,结合单摆的运动特点表示两个化学键之间的振动耦合.对水分子高激发态下两个氧氢键(O—H)伸缩振动动力学的研究结果表明,靠近分界线的中间能级的相空间中较易出现混沌轨道,而较高或较低能级的相空间中则具有比较规则的周期运动 关键词： 高激发振动 共振 混沌     

采用优化极限学习机的多变量混沌时间序列预测

基于优化极限学习机理论, 提出一种多变量混沌时间序列预测方法. 该方法利用复合混沌和混沌变尺度算法对极限学习机的模型参数进行搜索和优化, 以提高极限学习机的泛化性能; 然后利用优化后的极限学习机对Rossler耦合系统的多变量混沌时序进行一步和多步预测, 并且与同类算法进行了比较, 结果表明了该方法的有效性, 且算法具有较强的抗噪能力; 最后讨论了预测结果和隐层神经元数目的关系.     

受迫振动非线性特性的教学拓展

受迫振动在大学物理和大学物理实验中均是重点教学内容,为了使学生更加深入理解受迫振动的非线性特性,本文基于波耳共振仪所涉及的非线性因素和实验数据,对受迫振动方程进行非线性修正,利用数值分析探讨其非线性特性.通过引入硬弹簧型杜芬方程,探讨系统由周期性运动进入混沌状态的演化,将受迫振动中相对稳定的平衡点与奇异吸引子进行类比,...     

Control of chaos in Frenkel–Kontorova model using reinforcement learning

It is shown that we can control spatiotemporal chaos in the Frenkel–Kontorova(FK) model by a model-free control method based on reinforcement learning. The method uses Q-learning to find optimal control strategies based on the reward feedback from the environment that maximizes its performance. The optimal control strategies are recorded in a Q-table and then employed to implement controllers. The advantage of the method is that it does not require an explicit knowledge of the system, target states, and unstable periodic orbits. All that we need is the parameters that we are trying to control and an unknown simulation model that represents the interactive environment. To control the FK model, we employ the perturbation policy on two different kinds of parameters, i.e., the pendulum lengths and the phase angles. We show that both of the two perturbation techniques, i.e., changing the lengths and changing their phase angles, can suppress chaos in the system and make it create the periodic patterns. The form of patterns depends on the initial values of the angular displacements and velocities. In particular, we show that the pinning control strategy, which only changes a small number of lengths or phase angles, can be put into effect.     

Elimination of spiral waves and spatiotemporal chaos by the synchronization transmission technology of network signals

A method to eliminate spiral waves and spatiotemporal chaos by using the synchronization transmission technology of network signals is proposed in this paper. The character of the spiral waves and the spatiotemporal chaos in the Fitzhugh—Nagumo model is presented. The network error evolution equation with spatiotemporal variables and the corresponding eigenvalue equation are determined based on the stability theory, and the global synchronization condition is obtained. Simulations are made in a complex network with Fitzhugh—Nagumo models as the nodes to verify the effectiveness of the synchronization transmission principle of the network signal.     

混沌量子克隆优化求解认知无线网络决策引擎

通过分析认知无线网络引擎决策, 给出了其数学模型, 并将其转化为一个多目标优化问题, 进而提出一种基于混沌量子克隆的优化求解算法, 并证明了该算法以概率1收敛. 算法采用量子编码, 利用Logistic映射初始化抗体种群, 设计了一种基于混沌扰动的量子变异方案. 最后, 在多载波环境下对算法进行了仿真实验. 结果表明, 与QGA-CE(基于量子遗传算法的认知引擎)算法相比, 本文算法收敛速度较快, 具有较高的目标函数值, 可以对无线参数优化调整, 满足认知引擎的实时性要求.     

Study of sawtooth oscillations on the HT-7 tokamak using 2D tomography of soft x-ray signal

It is the first time so far as we know that two arrays of multi-channel soft x-ray detectors are used to generate twodimensional （2D） images of sawtooth oscillation on the HT-7 tokamak using the Fourier-Bessel harmonic reconstruction method, and using the singular value decomposition to analyse the data from soft x-ray cameras. By these two arrays, 2D image reconstruction of soft x-ray emissivity can be obtained without assumption of plasma rigid rotation. Tomographic reconstruction of the m=1 mode structure is obtained during the precursor oscillation of the sawtooth crash. The crescent-shaped mode structure appearing on the contour map of the soft x-ray emissivity is consistent with the quasiinterchange mode. The characteristics of the m=1/n=1 mode structure observed in the soft x-ray tomography are as follows： the magnetic surface is made up of the crescent-shaped “hot core” and the circular “cold bubble”. The structure of the magnetic surface rotates in the direction of the electron diamagnetic drift and the rotation frequency is the oscillation frequency of soft x-ray signals.     

Effect of metal oxide arrester on the chaotic oscillations in the voltage transformer with nonlinear core loss model using chaos theory

In this paper, controlling chaos when chaotic ferroresonant oscillations occur in a voltage transformer with nonlinear core loss model is performed. The effect of a parallel metal oxide surge arrester on the ferroresonance oscillations of voltage transformers is studied. The metal oxide arrester(MOA) is found to be effective in reducing ferroresonance chaotic oscillations. Also the multiple scales method is used to analyze the chaotic behavior and different types of fixed points in ferroresonance of voltage transformers considering core loss. This phenomenon has nonlinear chaotic dynamics and includes sub-harmonic, quasi-periodic, and also chaotic oscillations. In this paper, the chaotic behavior and various ferroresonant oscillation modes of the voltage transformer is studied. This phenomenon consists of different types of bifurcations such as period doubling bifurcation(PDB), saddle node bifurcation(SNB), Hopf bifurcation(HB), and chaos. The dynamic analysis of ferroresonant circuit is based on bifurcation theory. The bifurcation and phase plane diagrams are illustrated using a continuous method and linear and nonlinear models of core loss. To analyze ferroresonance phenomenon, the Lyapunov exponents are calculated via the multiple scales method to obtain Feigenbaum numbers. The bifurcation diagrams illustrate the variation of the control parameter. Therefore, the chaos is created and increased in the system.