Damage detection in initially nonlinear systems
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TLDR
This work highlights the inadequacy of linear-based methodology in handling Initially nonlinear systems and shows how the recently developed autoregressive support vector machine (AR-SVM) approach to time-series modeling can be used for detecting damage in a system that exhibits initially nonlinear response.About:
This article is published in International Journal of Engineering Science.The article was published on 2010-10-01 and is currently open access. It has received 44 citations till now. The article focuses on the topics: Structural health monitoring.read more
Citations
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Review on the new development of vibration-based damage identification for civil engineering structures: 2010-2019
Rongrong Hou,Yong Xia +1 more
TL;DR: The progress in the area of vibration-based damage identification methods over the past 10 years is reviewed to help researchers and practitioners in implementing existing damage detection algorithms effectively and developing more reliable and practical methods for civil engineering structures in the future.
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Experimental studies on damage detection of beam structures with wavelet transform
TL;DR: In this article, the static profile of a cracked cantilever aluminum beam subjected to a static displacement at its free end is analyzed with Gabor wavelet to identify the crack.
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Data-driven damage diagnosis under environmental and operational variability by novel statistical pattern recognition methods:
TL;DR: An innovative residual-based feature extraction approach based on AutoRegressive modeling and a novel statistical distance method named as Partition-based Kullback–Leibler Divergence for damage detection and localization by using randomly high-dimensional damage-sensitive features under environmental and operational variability are proposed.
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Structural damage identification using improved Jaya algorithm based on sparse regularization and Bayesian inference
Zhenghao Ding,Jun Li,Hong Hao +2 more
TL;DR: Damage identification results demonstrate that the proposed method based on the I-Jaya algorithm and the modified objective function based on sparse regularization and Bayesian inference can provide accurate and reliable damage identification, indicating the proposed algorithm is a promising approach for structural damage detection using data with significant uncertainties and limited measurement information.
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Application of genetic algorithm-support vector machine (ga-svm) for damage identification of bridge
Han-Bing Liu,Yu-Bo Jiao +1 more
TL;DR: A support vector machine (SVM) optimized by genetic algorithm (GA)-based damage identification method is proposed, and numerical simulation shows that GA-SVM can assess the damage conditions with better accuracy.
References
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Numerical solution of the Euler equations by finite volume methods using Runge Kutta time stepping schemes
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ReportDOI
Damage identification and health monitoring of structural and mechanical systems from changes in their vibration characteristics: A literature review
TL;DR: A review of the technical literature concerning the detection, location, and characterization of structural damage via techniques that examine changes in measured structural vibration response is presented in this article, where the authors categorize the methods according to required measured data and analysis technique.