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Location of Multiple Damage Types in a Truss-Type Structure Using Multiple Signal Classification Method and Vibration Signals

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TLDR
The presented results show that the proposed MUSIC method can make an accurate and reliable estimation of the condition and location of three specific damage conditions, i.e., loosened bolts, internal corrosion, and external corrosion.
Abstract
A new multiple signal classification (MUSIC)-based methodology is presented for detecting and locating multiple damage types in a truss-type structure subjected to dynamic excitations. The methodology is based mainly on two steps: in step 1, the MUSIC method is employed to obtain the pseudo-spectra of vibration signatures, healthy and damaged, to be used for damage detection. In step 2, a new damage index, based on the obtained pseudo-spectra, is proposed to measure the structure condition. Furthermore, the damage location is estimated according to the variation in the amplitudes of the estimated pseudo-spectra. The presented results show that the proposed methodology can make an accurate and reliable estimation of the condition and location of three specific damage conditions, i.e., loosened bolts, internal corrosion, and external corrosion.

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Citations
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Vibration feature extraction using signal processing techniques for structural health monitoring: A review

TL;DR: A comprehensive review of the recent progress that used signal processing techniques for vibration-based structural health monitoring (SHM) approaches is presented in this article , where the feature extraction process through the signal processing technique is the basic skeleton of this review.
Journal ArticleDOI

Fluctuation-based reverse dispersion entropy and its applications to signal classification

TL;DR: Experimental results show that FRDE can represent the complexity of signals and have the better separability; and FRDE-KNN has higher classification recognition rate than DE, permutation entropy and FDE with KNN, which can better classify the ship signals and gear fault signals.
Journal ArticleDOI

Vibration-based structural damage detection via phase-based motion estimation using convolutional neural networks

TL;DR: In this article , the authors combine phase-based motion estimation (PME) with the use of convolutional neural networks (CNNs) for feature extraction and classification of vibration signals that reveal structural damage.
Journal ArticleDOI

Detection and localization of multiple small damages in beam

TL;DR: In this article, it was shown that small damages often require sensors be mounted in the proximity of damage to obtain high Signal-to-Noise Ratio in system frequency response to input excitation.
Journal ArticleDOI

Natural Frequencies Identification by FEM Applied to a 2-DOF Planar Robot and Its Validation Using MUSIC Algorithm

TL;DR: In this paper, a finite element method (FEM) is applied to a two-degree-of-freedom (2-DOF) planar robot, and its validation through a novel experimental methodology, the Multiple Signal Classification (MUSIC) algorithm, is presented.
References
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Journal ArticleDOI

Detection of structural damage through changes in frequency: a review

O.S. Salawu
TL;DR: The use of natural frequency as a diagnostic parameter in structural assessment procedures using vibration monitoring is discussed in this paper, based on the fact that natural frequencies are sensitive indicators of structural integrity.
Journal ArticleDOI

A New Approach for Health Monitoring of Structures: Terrestrial Laser Scanning

TL;DR: The proposed TLS method allows measurement of the entire bridge's deformed shape, and thus a realistic solution for monitoring structures at both structure and member level, and can be used to create a 3-D finite element model of a structural member or the entire structure at any point in time automatically.
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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

A literature review of next-generation smart sensing technology in structural health monitoring

TL;DR: The state‐of‐the‐art methods have been presented by conducting a detailed literature review of the recent applications of smartphones, UAVs, cameras, and robotic sensors used in acquiring and analyzing the vibration data for structural condition monitoring and maintenance.
Journal ArticleDOI

Pseudospectra, MUSIC, and dynamic wavelet neural network for damage detection of highrise buildings

TL;DR: In this article, a nonparametric system identification-based model is presented for damage detection of high-rise building structures subjected to seismic excitations using the dynamic fuzzy wavelet neural network (WNN) model developed by the authors.
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