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Journal ArticleDOI

Damage detection in bridges using accurate modal parameters

TLDR
In this article, eigenvalue analysis is carried out using Lanczos algorithm in an adaptive h-version finite element environment in order to control the discretization error for accurate evaluation of modal parameters.
About
This article is published in Finite Elements in Analysis and Design.The article was published on 2004-01-01. It has received 101 citations till now. The article focuses on the topics: Discretization & Finite element method.

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Citations
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Structural Damage Detection with Automatic Feature-Extraction through Deep Learning

TL;DR: A novel damage detection approach to automatically extract features from low‐level sensor data through deep learning using a deep convolutional neural network, leading to an excellent localization accuracy on both noise‐free and noisy data set.
Journal ArticleDOI

Vibration‐based structural state identification by a 1‐dimensional convolutional neural network

TL;DR: In this paper, a vibration-based structural damage detection by CNNs is presented. But the vibration is not considered in the analysis of the CNNs' performance in detecting structural damage.
Journal ArticleDOI

Optimal spatial sampling interval for damage detection by curvature or strain energy mode shapes

TL;DR: In this paper, the optimal sampling interval for non-destructive damage detection utilizing curvature or strain energy mode shapes has been investigated, which is based on the most commonly used numerical methods for the computation of the curvature and the strain energy modes.
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Damage assessment of structures with uncertainty by using mode-shape curvatures and fuzzy logic

TL;DR: In this paper, a fuzzy logic-based approach for damage detection is proposed, where the authors show that geometric and measurement uncertainty cause considerable problem in damage assessment, which can be alleviated by using a probabilistic approach.

A review of damage detection and health monitoring of mechanical systems from changes in the measurement of linear and non-linear vibrations

TL;DR: This Chapter 13 presents a review of damage detection and structural health monitoring of mechanical systems from changes in the measurement of both linear and non-linear vibrations.
References
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Journal ArticleDOI

The superconvergent patch recovery and a posteriori error estimates. Part 1: The recovery technique

TL;DR: In this article, a general recovery technique is developed for determining the derivatives (stresses) of the finite element solutions at nodes, which has been tested for a group of widely used linear, quadratic and cubic elements for both one and two dimensional problems.
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Damage detection from changes in curvature mode shapes

TL;DR: In this article, a new parameter called curvature mode shape is investigated as a possible candidate for identifying and locating damage in a structure, and it is shown that the absolute changes in the curvature shape are localized in the region of damage and hence can be used to detect damage.
Journal ArticleDOI

The location of defects in structures from measurements of natural frequencies

TL;DR: In this article, a method of non-destructively assessing the integrity of structures using measurements of the structural natural frequencies is described, where measurements made at a single point in the structure can be used to detect, locate and quantify damage.
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Analysis of thick and thin shell structures by curved finite elements

TL;DR: In this article, a general formulation for the curved, arbitrary shape of thick shell finite elements is presented along with a simplified form for axisymmetric situations, which is suitable for thin to thick shell applications.
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The superconvergent patch recovery and a posteriori error estimates. Part 2: Error estimates and adaptivity

TL;DR: In this paper, the authors derived a theorem showing the dependence of the effectivity index for the Zienkiewicz-Zhu error estimator on the convergence rate of the recovered solution.
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