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中文摘要：
利用统计能量分析法预示航天器结构高频动力学响应时，正确估计各子系统的统计能量分析参数至关重要。论文从实验参数辨识角度，基于子空间法的统一理论框架，提出功率流模型辨谢耦合矩阵修正方法（PMI／CMA）辨识系统的内损耗因子和耦合损耗因子参数。首先利用子空间法直接由时域测试数据辨识功率流模型的等价状态空间模型，然后利用辨识模型特征参数修正初始耦合矩阵。耦合矩阵修正方法考虑了子系统间的耦合信息，并通过寻求耦合矩阵初始值相对误差的最小范数解得到修正参数。最后利用两个实际结构分别对算法进行了仿真分析并与功率流实现／统计能量分析模型修正方法（PRM／SMI）进行了对比，验证了PMI／CMA方法的有效性。
英文摘要：
Proper estimate of SEA parameters for every subsystem is very important when statistical energy analysis （SEA） is used for response prediction of high-frequency aerospace structure dynamics. Power flow model identification combined with coupling matrix adjustment （PMI/CMA） is proposed for the identification of damping loss factor and coupling loss factor based on the uniform theoretical framework of subspace method from the point of experimental parameter identification. An equivalent power flow model of state space form can be identified from time domain measured data by using subspace method first, and then the eigen-parameters of identified model are extracted to adjust the initial coupling matrix. The coupling information among subsystems is considered as an additional constraint in the coupling matrix adjustment algorithm. In addition, the percentage change in all the loss factor which constitute the coefficients of coupling matrix is minimized to obtain improved parameters. The PMI/CMA is validated by using the experimental simulations of two actual structures. The method present in the paper is also compared with power flow realization method and SEA model improvement technique （PRM/SMI）.
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