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EIGEN-SENSITIVITY BASED METHOD FOR STATISTICAL ENERGY ANALYSIS PARAMETERS IDENTIFICATION USING TRANSIENT MEASURED DATA

机译:基于特征敏感度的暂态测量数据统计能量分析参数识别方法

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The Statistical Energy Analysis (SEA), at present, has been widely recognized as an efficient analysis tool for the high frequency structural vibrations of space vehicles. The coefficients of the SEA equations depend on the coupling loss factor (CLF), the internal loss factor (ILF) and the modal density. For complex systems, the values of such SEA parameters cannot be provided by analytical relationships and it is rather necessary to determine them experimentally to provide a reliable solution. This paper proposes an experimental method based on eigen-sensitivity analysis for SEA parameters identification using transient measured data. The sensitivity formulas of eigenvalue and eigenvector of quasi-transient SEA are derived, which then provide reasonable search directions-for iteratively adjusting the CLF and ILF. The objective of the method is to minimize the residuals between analytical and experimental eigen-parameters. The Levenberg-Marquardt algorithm is used during the adjust process to find a robust solution in the case that the sensitivity matrix tends to be ill-condition. And the experimental eigen-parameters of quasi-transient SEA are identified using subspace method in time domain from transient measured data. Both numerical and experimental examples are given to validate the proposed method. It is observed that a full measurement of input power and energy to every subsystem is not necessarily required for a successful identification, which indicates that the current method has the advantage over the traditional experiment technology that is power injection method (PIM). The proposed method can also provide a useful complement to experimental statistical energy analysis.
机译:目前,统计能量分析(SEA)已被广泛认为是用于航天器高频结构振动的有效分析工具。 SEA方程的系数取决于耦合损耗因子(CLF),内部损耗因子(ILF)和模态密度。对于复杂的系统,无法通过分析关系提供此类SEA参数的值,而是必须通过实验确定它们以提供可靠的解决方案。本文提出了一种基于特征敏感度分析的瞬态实测数据用于SEA参数识别的实验方法。推导了准瞬态SEA特征值和特征向量的灵敏度公式,为迭代调整CLF和ILF提供了合理的搜索方向。该方法的目的是最小化分析和实验特征参数之间的残差。在灵敏度矩阵趋于患病的情况下,在调整过程中使用Levenberg-Marquardt算法来找到鲁棒的解决方案。并利用子空间法在时域上从瞬态实测数据中识别出了准瞬态SEA的实验特征参数。数值和实验实例均验证了该方法的有效性。可以观察到,成功识别不一定需要对每个子系统的输入功率和能量进行完整测量,这表明当前方法比传统的实验技术即功率注入方法(PIM)具有优势。所提出的方法还可以为实验统计能量分析提供有用的补充。

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