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.About:
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.read more
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Innovations in earthquake risk reduction for resilience: recent advances and challenges
Fabio Freddi,Carmine Galasso,Gemma Cremen,Andrea Dall'Asta,Luigi Di Sarno,Agathoklis Giaralis,Fernando Gutiérrez-Urzúa,Christian Málaga-Chuquitaype,Stergios A. Mitoulis,Crescenzo Petrone,Anastasios Sextos,Luis Sousa,Karim Tarbali,Enrico Tubaldi,John Wardman,Gordon Woo +15 more
TL;DR: The Sendai Framework for Disaster Risk Reduction 2015-2030 (SFDRR) highlights the importance of scientific research, supporting the availability and application of science and technology to decision-making in disaster risk reduction.
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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.
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Location of Multiple Damage Types in a Truss-Type Structure Using Multiple Signal Classification Method and Vibration Signals
Carlos A. Perez-Ramirez,Jose M. Machorro-Lopez,Martin Valtierra-Rodriguez,Juan P. Amezquita-Sanchez,Arturo Garcia-Perez,David Camarena-Martinez,Rene de Jesus Romero-Troncoso +6 more
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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Bayesian compressive sensing for approximately sparse signals and application to structural health monitoring signals for data loss recovery
TL;DR: Compared with other state-of-the-art CS methods, including the previously-published Bayesian method, the new CS algorithm shows superior performance in reconstruction robustness and posterior uncertainty quantification, for approximately sparse signals.
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Real-time performance monitoring of tuned mass damper system for a 183 m reinforced concrete chimney
TL;DR: In this paper, the authors describe the chimney, the monitoring system and its installation, the data processing and system identification procedure, together with performance data before, during and after installation of the TMD.
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Modal Analysis With Compressive Measurements
TL;DR: This paper proposes and study three frameworks for Compressive Sensing in SHM systems and provides theoretical justification for each based on the equations of motion describing a simplified Multiple-Degree-Of-Freedom (MDOF) system, and supports the proposed techniques using simulations based on synthetic and real data.
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Compressive sensing based stochastic process power spectrum estimation subject to missing data
TL;DR: In this paper, a compressive sensing based approach for stationary and non-stationary stochastic process power spectrum estimation subject to missing data is developed, where Fourier and harmonic wavelet bases are utilized for expanding the signal recorded in the time domain.
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Vibration monitoring via spectro-temporal compressive sensing for wireless sensor networks
Roman Klis,Eleni Chatzi +1 more
TL;DR: This work proposes a remedy to heavy transmission costs by optimally combining the spectro-temporal information, which is already present in the signal, with a recently surfaced compressive sensing paradigm resulting in a robust signal reconstruction technique, which allows for reliable identification of modal shapes.