Volume 20, Issue 5 (2020)                   MCEJ 2020, 20(5): 89-102 | Back to browse issues page

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zayeri baghlani nejad A, Mahmoudi M. A new method for determining the natural frequencies of structures from their ambient vibration. MCEJ 2020; 20 (5) :89-102
URL: http://mcej.modares.ac.ir/article-16-38767-en.html
1- Ph.D. Candidate, Department of Civil Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran. , amir.zayeri@sru.ac.ir
2- Associate Professor, Department of Civil Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran.
Abstract:   (1717 Views)
The load type imposed on the structures is one of the important issues of the modal identification Experimental methods. Generally the loads applied to a structure for dynamic testing are divided into two categories: artificial stimulation and ambient loads. Applying artificial loads to large structures such as bridges and tall buildings is difficult, costly and in some cases impossible. For this reason, modal identification of such structures is generally done by ambient vibration tests. However this experimental methods, also include problems such as large noise amplitude relative to the measured responses that this causes errors in the results and in some cases leads to unrealistic modes. As a solution, modal information can be calculated from several different methods and compared with each other to ensure the accuracy of the results. In this paper, a new scheme for natural frequencies extraction of structures from their ambient vibration is presented. For this purpose, the combination of two mathematical techniques of random decrement (RD) and proper orthogonal decomposition (POD) methods were used. The reason for using these two methods, is their ability to reduce the noise effects. In other words, combining of these two methods can lead to a very powerful tool for extracting structural frequencies from its ambient vibration under high amplitude noise conditions. The proposed algorithm consists of three steps: In the first step, after measuring the acceleration response of the structure at the appropriate points, the effects of random vibration are eliminated from the response by RD method and only dynamic properties of the structure remain in the acceleration records. Secondly, the acceleration records are separated into several structural modes using the proper orthogonal decomposition technique and finally, at the last step, the proceeded responses are transformed by the fast Fourier transform into the frequency domain to extract the natural frequencies of the structure. The strength of the proposed method is its robustness to the use of very high amplitude noise data, which is one of the challenges in the ambient vibration experiments. The accuracy of the proposed algorithm was evaluated by numerical modeling and experimental study. To investigate the efficiency of the new method, the numerical and experimental results were compared with the frequencies obtained from commonly modal identification methods such as extended frequency domain decomposition (EFDD) and stochastic subspace identification (SSI). A very good agreement was observed between the results of methods. Furthermore, Studying the effect of noise on the new algorithm results shows that increasing the ratio of noise to acceleration amplitude up to 250, did not affect the results precision and the main frequencies of the structure can be obtained with good accuracy. In this study, the effect of the number of sensors used in the ambient vibration test also was investigated on the accuracy of the new algorithm results. It was concluded that the minimum number of sensors (even one number) and repetition of the experiment can be used to extract structural frequencies from its ambient vibration with high accuracy. The results of this study showed that the new method can be used as a suitable tool to determine the natural frequencies of structures from its ambient vibration under severe noise conditions and to control the results obtained from other methods.
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Article Type: Original Research | Subject: Civil and Structural Engineering
Received: 2019/12/6 | Accepted: 2020/09/16 | Published: 2020/11/30

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