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A compressive MUSIC spectral approach for identification of closely-spaced structural natural frequencies and post-earthquake damage detection

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TLDR
Results suggest that the adopted approach for identifying resonant frequencies of white-noise excited structures using acceleration measurements acquired at rates significantly below the Nyquist rate is robust and noise-immune while it can reduce data transmission requirements in acceleration wireless sensors for natural frequency identification and damage detection in engineering structures.
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This article is published in Probabilistic Engineering Mechanics.The article was published on 2020-02-07 and is currently open access. It has received 15 citations till now. The article focuses on the topics: Sampling (signal processing) & Frequency domain.

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Citations
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Journal ArticleDOI

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

TL;DR: 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.
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High-dimensional data analytics in structural health monitoring and non-destructive evaluation: a review paper

TL;DR: In this paper , a review of high-dimensional data analytic (HDDA) methods for structural health monitoring (SHM) and non-destructive evaluation (NDE) applications is presented.
References
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Journal ArticleDOI

Compressive sensing with an adaptive wavelet basis for structural system response and reliability analysis under missing data

TL;DR: In this paper, a compressive sensing based framework in conjunction with an adaptive wavelet basis is presented for reconstructing the samples with missing data and estimating the underlying process EPS, where the source load data records are incomplete.
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Procedures for vibration serviceability assessment of high-frequency floors

TL;DR: In this article, the authors present a more rigorous approach based on first-principle modal analysis and modeling footfalls as effective impulses, and demonstrate that with both effective impulse and real footfall forces, there is not necessarily asymptotic response with rising floor mode frequency.

Wireless Sensor Advances and Applications for Civil Infrastructure Monitoring

TL;DR: A flexible wireless smart sensor framework for full-scale, autonomous SHM that integrates the necessary software and hardware while addressing key implementation requirements is developed and validated on a full- Scale cable-stayed bridge in South Korea.
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High-resolution spectral-analysis for identifying the natural modes of a truss-type structure by means of vibrations:

TL;DR: In this paper, a methodology based on the multiple signal classification (MUSIC) algorithm and its high-resolution properties was applied for identifying most of the natural modes and analyzing vibration signals in a truss-type structure by using a reduced sample data set and short sampling time window.
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Assessment of sub-Nyquist deterministic and random data sampling techniques for operational modal analysis

TL;DR: It is concluded that the power spectrum blind sampling–based approach reduces effectively data transmission requirements in wireless sensor networks for operational modal analysis, without being limited by signal sparsity and without requiring a priori assumptions or knowledge of sign sparsity.
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