Time-Frequency and Ambiguity Function Approaches in Structural Identification

In the identification and control of some structures it is important to be able to resort to special techniques that may exploit environmental excitation in normal serviceability conditions. Hence, preliminary signal processing must be designed to extract significant data, even in the presence of unknown, weak, or transient excitations. In the processing and representation of nonstationary dynamic signals, great importance has been taken on in the literature by the transforms in the joint time-frequency domain. In this context, a method based on the time-frequency representation and some properties of the ambiguity function is proposed to identify the natural frequencies, draw the modal shapes, and detect nonlinearity in such testing conditions. To this end, the performances of the new Choi-Williams exponential kernel are compared with those of the Wigner-Ville transform. Finally techniques based on the instantaneous cross-correlation function are proposed to improve the performance of the identification method, and an application to a real bridge is discussed.