Article ID Journal Published Year Pages File Type
559422 Mechanical Systems and Signal Processing 2013 23 Pages PDF
Abstract

The estimation of modal parameters of a structure from ambient measurements has attracted the attention of many researchers in the last years. The procedure is now well established and the use of state space models, stochastic system identification methods and stabilization diagrams allows to identify the modes of the structure. In this paper the contribution of each identified mode to the measured vibration is discussed. This modal contribution is computed using the Kalman filter and it is an indicator of the importance of the modes. Also the variation of the modal contribution with the order of the model is studied. This analysis suggests selecting the order for the state space model as the order that includes the modes with higher contribution. The order obtained using this method is compared to those obtained using other well known methods, like Akaike criteria for time series or the singular values of the weighted projection matrix in the Stochastic Subspace Identification method. Finally, both simulated and measured vibration data are used to show the practicability of the derived technique. Finally, it is important to remark that the method can be used with any identification method working in the state space model.

► The acceleration response due to each identified mode is estimated by mean of the Kalman filter. ► The contribution of the identified modes to the measured acceleration is computed. ► The modal contribution is used to select the order of the state space model. ► We propose to plot the modal contribution next to the stabilization diagram. ► The joint analysis of both plots is useful for selecting physical modes.

Related Topics
Physical Sciences and Engineering Computer Science Signal Processing
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