h. karegar

One of the most common methods of identifying modal parameters in the field of operational modal testing is the method of identifying sub-random space and frequency domain analysis. Unfortunately, the scope of these methods' application is limited to static signals with a long pick-up time, and if the above conditions are violated, the results will be erroneous; This is in the context that the above two conditions are not met regarding the earthquake signal, and so far the reliability of these methods and their error rate in the face of this group of signals have not been studied. In this regard, in this study, the performance of these methods in earthquake conditions (both conditions are violated) is studied.
For this purpose, an numerical model of two two-dimensional frames with different heights (five and ten floors) is created and stimulated by using 20 earthquake records in the near and far fields. Using the obtained results and comparing them with the results of the numerical model, the error values for the modal parameters are obtained; Also, with the statistical study of the errors in the estimation of the frequency of the structure, the probability distribution function of the error and an estimate of the distance of the error are suggested .The results of the study showed that (a) the method of identifying random subspace has a better performance than the method of frequency domain analysis; (B) The random subspace detection method is not able to detect the first modes and is proposed to identify higher modes; (C) the efficiency of the frequency domain decomposition method decreases with increasing structural height; (D) By optimizing and locating the sensors, the performance of the frequency domain analysis method is dramatically improved. However, in the random subspace detection method, the detectability increases with the number of sensors.

In this paper, an enhanced method for extraction of modal parameters (frequencies and damping ratios) of a structure from stationary or non-stationary measurement dynamic responses recorded by a sensor is presented. Surely, one of the simplest methods in area of ambient modal identification (operational modal analysis) is autoregressive method. Major problem of autoregressive method is that for identification of m modes of a structure, at least m sensors are needed. Besides, this method like other similar methods in this area such as frequency domain decomposition and stochastic subspace identification is appropriate for extraction of modal parameters from stationary measured dynamic structural responses. To address these issues, in this study, the Hilbert vibration decomposition method, which is a simple method for time-varying vibration decomposition based on the Hilbert transform, is adopted to improve the performance of the autoregressive method for extraction of frequencies and damping ratios of a structure from stationary or non-stationary responses recorded by a sensor. The efficiency and performance of the newly enhanced method are investigated through two numerical examples and a verification example. The first numerical example deals with a single-degree-of-freedom system subjected to a non-stationary force and the second one presents a two-degree-of-freedom structure excited by a stationary force. Finally, by using the proposed method, the frequencies and damping ratios of a support tower of the segmental bridge via an experimental test are obtained. The results indicated that the proposed method adequately estimated the frequencies and damping ratios of a structure from stationary and non-stationary responses recorded by only one sensor. Moreover, it is found that this method outperforms other relevant methods when dealing with non-stationary responses. Consequently, the enhanced method is strongly recommended for extraction of the frequencies and damping ratios of the structures from stationary or non-stationary responses, especially when the dynamic response of the structure is non-stationary and measured using only one sensor.