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Journal ArticleDOI

Output only modal identification and structural damage detection using time frequency & wavelet techniques

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.

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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

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

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.
References
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Book

Time-Frequency Analysis

Leon Cohen
TL;DR: In this article, the authors present a general approach and the Kernel Method for reduced interference in the representation of signal signals, which is based on the Wigner distribution and the characteristic function operator.
Book ChapterDOI

Time-Frequency Analysis

TL;DR: In this article, it is shown that the representation of a signal in the frequency domain is well localized in frequency, but is poorly localized in time, and as a consequence it is impossible to tell when certain events occurred in time.

On empirical mode decomposition and its algorithms

TL;DR: Empirical Mode Decomposition is presented, and issues related to its effective implementation are discussed, and an interpretation of the method in terms of adaptive constant-Q filter banks is supported.
Journal ArticleDOI

State of the art of structural control

TL;DR: In this paper, the authors review the recent and rapid developments in semi-active structural control and its implementation in full-scale structures, and present an alternative to active and hybrid control for structural vibration reduction.
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