Journal ArticleDOI
Output only modal identification and structural damage detection using time frequency & wavelet techniques
Satish Nagarajaiah,Biswajit Basu +1 more
TLDR
In this paper, the authors developed output only modal identification and structural damage detection based on Time-frequency (TF) techniques such as short-time Fourier transform (STFT), empirical mode decomposition (EMD), and wavelets.Abstract:
The primary objective of this paper is to develop output only modal identification and structural damage detection. Identification of multi-degree of freedom (MDOF) linear time invariant (LTI) and linear time variant (LTV—due to damage) systems based on Time-frequency (TF) techniques—such as short-time Fourier transform (STFT), empirical mode decomposition (EMD), and wavelets—is proposed. STFT, EMD, and wavelet methods developed to date are reviewed in detail. In addition a Hilbert transform (HT) approach to determine frequency and damping is also presented. In this paper, STFT, EMD, HT and wavelet techniques are developed for decomposition of free vibration response of MDOF systems into their modal components. Once the modal components are obtained, each one is processed using Hilbert transform to obtain the modal frequency and damping ratios. In addition, the ratio of modal components at different degrees of freedom facilitate determination of mode shape. In cases with output only modal identification using ambient/random response, the random decrement technique is used to obtain free vibration response. The advantage of TF techniques is that they are signal based; hence, can be used for output only modal identification. A three degree of freedom 1:10 scale model test structure is used to validate the proposed output only modal identification techniques based on STFT, EMD, HT, wavelets. Both measured free vibration and forced vibration (white noise) response are considered. The secondary objective of this paper is to show the relative ease with which the TF techniques can be used for modal identification and their potential for real world applications where output only identification is essential. Recorded ambient vibration data processed using techniques such as the random decrement technique can be used to obtain the free vibration response, so that further processing using TF based modal identification can be performed.read more
Citations
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Journal ArticleDOI
Signal Processing Techniques for Vibration-Based Health Monitoring of Smart Structures
TL;DR: The biggest challenge in realization of health monitoring of large real-life structures is automated detection of damage out of the huge amount of very noisy data collected from dozens of sensors on a daily, weekly, and monthly basis.
Journal ArticleDOI
Review of Bridge Structural Health Monitoring Aided by Big Data and Artificial Intelligence: From Condition Assessment to Damage Detection
TL;DR: This work has shown that structural health monitoring techniques have been widely used in long-span bridges but, due to limitations of computational ability and data analysis methods, the knowledge in these techniques is limited.
Journal ArticleDOI
Characterization of non-linear bearings using the Hilbert-Huang transform
Arturo González,Hussein Aied +1 more
TL;DR: In this paper, a lead rubber bearing is idealized using the hysteretic Bouc-Wen model and the Hilbert-Huang transform is employed to characterize the features of the non-linear system from the instantaneous frequencies of the bearing response to a time-varying force.
Journal ArticleDOI
Control of flapwise vibrations in wind turbine blades using semi-active tuned mass dampers
TL;DR: In this paper, a semi-active tuned mass dampers (STMDs) were used to reduce the vibration in the flapwise direction of wind turbine blades due to the stiffening of the nacelle.
Journal ArticleDOI
Output-only modal identification with limited sensors using sparse component analysis
Yongchao Yang,Satish Nagarajaiah +1 more
TL;DR: Numerical simulations and experimental example show that whether in determined or underdetermined situations, the SCA method performs accurate and robust identification of a wide range of structures including those with closely-spaced and highly-damped modes.
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