In order to select the window function and window size adaptively before getting the results, we proposed adaptive moving window principle component analysis (AMWPCA) based OMA method to identify modal shapes and modal natural frequencies of slow LTV structures with weekly damped only from non-stationary vibration response signal online. The adaptive is achieved in two ways: change the window function or window size. We develop an adaptive indicator as the basis for window function and window size changes Our adaptive approach is to make the difference between adjacent eigenvalues not too small. The operational modal parameter identification results in non-stationarity response signal dataset of a three-degree-of-freedom structure with slow time-varying mass show that comparing with fixed size moving window principle component analysis, our AMWPCA method can identify the modal shapes and modal frequencies better.

中文翻译：

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线性时变结构的自适应窗口函数和基于窗口尺寸的操作模态参数识别

为了在获得结果之前自适应地选择窗函数和窗尺寸，我们提出了一种基于自适应移动窗主成分分析（AMWPCA）的OMA方法，以识别仅每周从非平稳位置阻尼的慢速LTV结构的模态形状和模态固有频率在线振动响应信号。自适应通过两种方式实现：更改窗口功能或窗口大小。我们开发了一种自适应指标，作为窗函数和窗尺寸变化的基础。我们的自适应方法是使相邻特征值之间的差异不太小。操作模态参数识别结果导致质量随时间变化缓慢的三自由度结构的非平稳响应信号数据集显示，与固定大小的移动窗口主成分分析相比，