Statistical modal analysis for bridges under ambient excitation by using improved random decrement technique and wavelet transform

2021 ◽  
pp. 94-94
Author(s):  
J. Liu ◽  
Q. Zhang
Keyword(s):  
Wavelet Transform ◽  
Modal Analysis ◽  
Random Decrement Technique ◽  
Random Decrement ◽  
Ambient Excitation

Reliability of Extracted Modal Parameters by Random Decrement of Acceleration Signatures

2009 ◽  
Author(s):  
Babak Khodabandelou ◽  
Kaveh Abasi ◽  
Masud Asayesh
Keyword(s):  
Numerical Simulation ◽  
Free Vibration ◽  
Modal Analysis ◽  
Correlation Functions ◽  
Vibration Response ◽  
Modal Parameters ◽  
Random Decrement Technique ◽  
Random Decrement ◽  
Free Decay ◽  
Free Vibration Response

Modal parameters provide important information on dynamic properties of structures. In operating condition, since it is difficult to measure input loadings, methods should be applied where don’t require measuring inputs. Such methods which identify modal parameters of structures by measuring their responses are called Operational- or Output Only- Modal Analysis (OMA) techniques. There are many time and frequency domain operational modal analysis techniques. Generally a form of impulse or free vibration response is required to use most of these techniques. However, in practice structures are usually subjected to some immeasurable or unknown random inputs. In these situations Random Decrement (RD) transformation can reduce these responses to equivalent free decay or correlation functions. Therefore, RD technique coupled with those methods, which require a form of impulse or free vibration response offer a valuable tool for identifying the dynamic characteristics of structures from operational or ambient responses. Unfortunately, in the literature there are some constrains on using random decrement signatures. For example by complicated mathematical relations it is shown that random decrement technique is applicable only if the inputs are uncorrelated zero mean Gaussian white noises. In addition, it is proved that only random decrement of displacement and velocity is equivalent to the corresponding free decay responses or correlation functions the random decrement of acceleration response is never equivalent to the corresponding free decay responses or correlation functions. However, there are many papers which have used random decrement of acceleration responses and extracted modal parameters accurately! In this paper it is tried to show simply and clearly whether it is possible to obtain modal parameters from random decrement acceleration signatures or not. To do that, a numerical simulation of a discrete dynamic system with viscous damping is carried out and the results of numerical methods are compared with those come from analytical solution. Numerical simulation is used since it is completely controllable. Finally, it is tried to identify power and the Applicability cases of random decrement method.

A random decrement technique for operational modal analysis in the presence of periodic excitations

2009 ◽  
Vol 223 (7) ◽  
pp. 1525-1534 ◽  
Author(s):  
M Asayesh ◽  
B Khodabandeloo ◽  
A Siami
Keyword(s):  
White Noise ◽  
Modal Analysis ◽  
Degrees Of Freedom ◽  
Domain Decomposition Method ◽  
Gaussian White Noise ◽  
Operational Modal Analysis ◽  
Modal Parameters ◽  
Periodic Excitation ◽  
Random Decrement Technique ◽  
Random Decrement

Operational modal analysis (OMA) is a procedure that allows the identification of the modal parameters of a structure using measured responses to unknown excitation. OMA techniques are based on the assumption that the input to the structure is stationary white noise. One of the OMA techniques, which is based on the assumption of a zero mean Gaussian white noise excitation, is the random decrement (RD) technique. In many practical cases, however, periodic excitation is often present in addition to the white noise. In this study, a method based on the concept of RD transformation is proposed to extract the response of a structure to the random input from the measured response that is due to both random and periodic excitations. Applying the RD method to the extracted random response, RD signatures were estimated. Modal parameters were estimated from RD signatures using the Ibrahim time domain algorithm. It is assumed that the period of the periodic excitation is known a priori. To verify the applicability of the method, a numerical simulation of a discrete two-degrees-of-freedom (DOF) dynamic system with a viscous damping is carried out. The results of this method were also compared with the results obtained from the enhanced frequency domain decomposition method. The efficiency of the proposed method, in the cases where the frequencies of harmonic components of periodic excitation are located at the natural frequencies of the system, is also evaluated.

scholarly journals A System Identification-Based Damage-Detection Method for Gravity Dams

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Masoud Mirtaheri ◽  
Mojtaba Salkhordeh ◽  
Masoud Mohammadgholiha
Keyword(s):  
Wavelet Transform ◽  
Dynamic Properties ◽  
Structural Response ◽  
Cost Effective ◽  
The Body ◽  
Mode Shapes ◽  
Damage Scenarios ◽  
Hilbert Huang Transform ◽  
Random Decrement Technique ◽  
Random Decrement

Dams are essential infrastructures as they provide a range of economic, environmental, and social benefits to the local populations. Damage in the body of these structures may lead to an irreparable disaster. This paper presents a cost-effective vibration-based framework to identify the dynamic properties and damage of the dams. To this end, four commonly occurred damage scenarios, including (1) damage in the neck of the dam, (2) damage in the toe of the structure, (3) simultaneous damage in the neck and the toe of the dam, and (4) damage in the lifting joints of the dam, are considered. The proposed method is based on processing the acceleration response of a gravity dam under ambient excitations. First, the random decrement technique (RDT) is applied to determine the free-vibration of the structure using the structural response. Then, a combined method based on Hilbert–Huang Transform (HHT) and Wavelet Transform (WT) is presented to obtain the dynamic properties of the structure. Next, the cubic-spline technique is used to make the mode shapes differentiable. Finally, Continuous Wavelet Transform (CWT) is applied to the residual values of mode shape curvatures between intact and damaged structures to estimate the damage location. In order to evaluate the efficiency of the proposed method in field condition, 10% noise is added to the structural response. Results show promising accuracy in estimating the location of damage even when the structure is subjected to simultaneous damage in different locations.

scholarly journals Output-Only Modal Analysis Based on Improved Empirical Mode Decomposition Method

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Shiqiang Qin ◽  
Qiuping Wang ◽  
Juntao Kang
Keyword(s):  
Modal Analysis ◽  
Empirical Mode Decomposition ◽  
Modal Parameters ◽  
Band Pass Filter ◽  
Pass Filter ◽  
Random Decrement Technique ◽  
Mode Decomposition ◽  
Frequency Components ◽  
Output Only ◽  
Emd Method

The output-only modal analysis for bridge structures based on improved empirical mode decomposition (EMD) is investigated in this study. First, a bandwidth restricted EMD is proposed for decomposing nonstationary output measurements with close frequency components. The advantage of bandwidth restricted EMD to standard EMD is illustrated by a numerical simulation. Next, the modal parameters are extracted from intrinsic mode function obtained from the improved EMD by both random decrement technique and stochastic subspace identification. Finally, output-only modal analysis of a railway bridge is presented. The study demonstrates the mode mixing issues of standard EMD can be restrained by introducing bandwidth restricted signal. Further, with the improved EMD method, band-pass filter is no longer needed for separating the closely spaced frequency components. The modal parameters extracted based on the improved EMD method show good agreement with those extracted by conventional modal identification algorithms.

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