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Nonlinear normal modes and proper orthogonal decomposition in inertially-coupled nonlinear conservative systems

机译:非线性正常模式在惯于耦合非线性保守系统中的正常正交分解

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In this study, the relationship between the nonlinear normal modes (NNM) and the proper orthogonal decomposition (POD) modes is explored through the nonlinear dynamics of the spring-mass-pendulum system. For this inertially-coupled two degrees-of-freedom nonlinear system, the principle of 'least action' is used to obtain the boundary value problem that governs the NNMs in configuration space. For a specified total energy and other system parameters, shooting method is used to solve the boundary value and numerical approximations to the NNMs are constructed. It is known that various bifurcations arise in the NNMs of the system as the system parameters and the total energy are varied. The proper orthogonal decomposition (POD) modes are then explored. In the case of a linear system with an identity mass matrix, it is seen that as the snapshot number N -> infinity and the total time record length T -> infinty, the POD mode approaches the corresponding linear modal eigenvector. Now, data from simulations of the spring-mass-pendulum system is used, and it is shown that the POM (or a POD mode) is a linear curve in the configuration space which represents the principle axis of inertia based at the mean of the data in the configuration space. This is the least squares approximation of the data. Finally, the nonlinear generalization of PCA -VQPCA is used to reanalyze the same data for the spring-mass-pendulum system. In the VQPCA analysis, a modified Linde-Buzo-Gray (LBG) algorithm, suitable for the modal analysis, is developed. The superiority of VQPCA over PCA in capturing the NNM is clearly seen in the simulation results.
机译:在该研究中,通过弹簧质型系统的非线性动力学探索非线性正常模式(NNM)与适当的正交分解(POD)模式之间的关系。对于这种惯性耦合的两个自由度非线性系统,“最小动作”的原理用于获得控制配置空间中NNMS的边界值问题。对于指定的总能量和其他系统参数,使用拍摄方法来解决边界值,并且构建对NNMS的数值近似。众所周知,在系统的NNMS中出现各种分叉作为系统参数和总能量变化。然后探讨适当的正交分解(POD)模式。在具有身份质量矩阵的线性系统的情况下,可以看出,作为快照号n - >无限度和总时间记录长度t - >传输,Pod模式接近相应的线性模态特征向量。现在,使用来自弹簧 - 质量摆动系统的模拟的数据,并示出了POM(或POD模式)是配置空间中的线性曲线,其表示基于惯性的惯性轴的原理轴线配置空间中的数据。这是数据的最小二乘近似。最后,使用PCA -VQPCA的非线性概括来重新分割弹簧 - 质量摆动系统的相同数据。在VQPCA分析中,开发了一种适用于模态分析的改进的Linde-Buzo-灰(LBG)算法。在仿真结果中清楚地看到了在捕获NNM时对PCA的VQPCA的优越性。

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