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Modal parameters based structural damage detection using artificial neural networks - a review

https://doi.org/10.12989/sss.2014.14.2.159

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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DYNAMIC FINITE ELEMENT MODEL UPDATING USING NEURAL NETWORKS

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CRACK IDENTIFICATION USING HYBRID NEURO-GENETIC TECHNIQUE

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HEALTH-MONITORING METHOD FOR BRIDGES UNDER ORDINARY TRAFFIC LOADINGS

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DAMAGE ASSESSMENT USING MODE SHAPE SENSITIVITIES

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DAMAGE ASSESSMENT USING NEURAL NETWORKS

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Analyses on structural damage identification based on combined parameters

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Crack identification in curvilinear beams by using ANN and ANFIS based on natural frequencies and frequency response functions

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Damage detection from changes in curvature mode shapes

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Multilayer perceptron in damage detection of bridge structures

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Neural-network applications in predicting moment-curvature parameters from experimental data

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Damage detection of a cracked column via a neural network approach

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Damage assessment of structures using hybrid neuro-genetic algorithm

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Neural network based nondestructive evaluation of sandwich composites

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Damage assessment of prestressed concrete beams using artificial neural network (ANN) approach

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Seismic damage identification in buildings using neural networks and modal data

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Damage identification for beams using ANN based on statistical property of structural responses

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Prediction of fracture parameters of concrete by Artificial Neural Networks

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Quantification and localisation of damage in beam-like structures by using artificial neural networks with experimental validation

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Damage detection using artificial neural network with consideration of uncertainties

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The selection of pattern features for structural damage detection using an extended Bayesian ANN algorithm

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Crack detection in beam-like structures

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Damage detection of truss bridge joints using Artificial Neural Networks

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Neural network modeling of the load-carrying capacity of eccentrically-loaded single-angle struts

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Neural networks-based damage detection for bridges considering errors in baseline finite element models

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Sequential damage detection approaches for beams using time-modal features and artificial neural networks

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Artificial neural network based delamination prediction in laminated composites

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Modeling of strength of high-performance concrete using artificial neural networks

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Substructural identification using neural networks

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Multi-stage identification scheme for detecting damage in cable-stayed Kap Shui Mun Bridge

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Prediction of concrete strength using artificial neural networks

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Detection of structural damage through changes in frequency: a review

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A patch load parametric analysis using neural networks

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Neural Networks Trained by Analytically Simulated Damage States

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Structural Damage Detection Using Artificial Neural Networks

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Vibration-based damage assessment in steel frames using neural networks

inferredcites →https://doi.org/10.1088/0964-1726/13/4/029openalex-snapshot

Identification of crack location and depth in a cantilever beam using a modular neural network approach

inferredcites →https://doi.org/10.1088/0964-1726/3/3/008openalex-snapshot

Damage detection in composite structures using piezoelectric materials (and neural net)

inferredcites →https://doi.org/10.1088/0964-1726/5/3/012openalex-snapshot

Delamination prediction in composite beams with built-in piezoelectric devices using modal analysis and neural network

inferredcites →https://doi.org/10.1106/xu88-uw1t-a6am-x7eaopenalex-snapshot

Structural Damage Detection Using an Iterative Neural Network

inferredcites →https://doi.org/10.1109/icicta.2010.733openalex-snapshot

Structural Damage Detection Based on BP Neural Network Technique

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Detection of multiple cracks in beams using particle swarm optimization and artificial neural network

inferredcites →https://doi.org/10.1109/nabic.2009.5393733openalex-snapshot

Application of Neural Network for fault diagnosis of cracked cantilever beam

inferredcites →https://doi.org/10.1111/1467-8667.00265openalex-snapshot

Decentralized Parametric Damage Detection Based on Neural Networks

inferredcites →https://doi.org/10.1111/j.1467-8667.1994.tb00364.xopenalex-snapshot

A Structural Damage Neural Network Monitoring System

inferredcites →https://doi.org/10.1111/j.1467-8667.2006.00431.xopenalex-snapshot

Structural Health Monitoring via Measured Ritz Vectors Utilizing Artificial Neural Networks

inferredcites →https://doi.org/10.1111/j.1467-8667.2006.00449.xopenalex-snapshot

Damage Detection in a Girder Bridge by Artificial Neural Network Technique

inferredcites →https://doi.org/10.11113/jt.v44.359openalex-snapshot

Vibration–Based Damage Detection Of Slab Structure Using Artificial Neural Network

inferredcites →https://doi.org/10.11113/jt.v52.122openalex-snapshot

Statistical Vibration Based Damage Identification Using Artificial Neural Network

inferredcites →https://doi.org/10.1117/12.147985openalex-snapshot

Neural network damage detection in a bridge element

inferredcites →https://doi.org/10.1117/12.207718openalex-snapshot

Artificial neural networks for structural damage detection and classification

inferredcites →https://doi.org/10.1117/12.348682openalex-snapshot

Damage assessment of bridges with jacketed RC columns using vibration test

inferredcites →https://doi.org/10.1117/12.383151openalex-snapshot

Damage detection system of a real steel truss bridge by neural networks

inferredcites →https://doi.org/10.1155/2011/786535openalex-snapshot

A New Procedure for Damage Assessment of Prestressed Concrete Beams Using Artificial Neural Network

inferredcites →https://doi.org/10.1177/1045389x04042279openalex-snapshot

Damage Identification by the Dynamic Virtual Distortion Method

inferredcites →https://doi.org/10.1177/1045389x06066292openalex-snapshot

Damage Detection in Beams using Spatial Fourier Analysis and Neural Networks

inferredcites →https://doi.org/10.1177/1056789506065939openalex-snapshot

Damage Detection for Framed RCC Buildings using ANN Modeling

inferredcites →https://doi.org/10.1177/147592103031112openalex-snapshot

Damage Identification of Structural Members: Numerical and Experimental Studies

inferredcites →https://doi.org/10.1177/1475921704047502openalex-snapshot

Experimental Damage Identification of Carbon/Epoxy Composite Beams Using Curvature Mode Shapes

inferredcites →https://doi.org/10.1177/1475921708102088openalex-snapshot

Structural Damage Detection Using Modal Curvature and Fuzzy Logic

inferredcites →https://doi.org/10.1177/1475921710368201openalex-snapshot

Composite material and piezoelectric coefficient uncertainty effects on structural health monitoring using feedback control gains as damage indicators

inferredcites →https://doi.org/10.1201/b11837-74openalex-snapshot

Damage detection of steel bridge girder using Artificial Neural Networks

inferredcites →https://doi.org/10.1243/095440603321919581openalex-snapshot

Vibration-based damage identification in beam-like composite laminates by using artificial neural networks

inferredcites →https://doi.org/10.1260/1369-4332.13.1.1openalex-snapshot

Seismic Response of Double Concave Friction Pendulum Base-Isolated Structures considering Vertical Component of Earthquake

inferredcites →https://doi.org/10.1260/1369-4332.13.1.95openalex-snapshot

Structure Damage Detection Using Neural Network with Multi-Stage Substructuring

inferredcites →https://doi.org/10.12989/scs.2013.14.4.367openalex-snapshot

Structural damage detection of steel bridge girder using artificial neural networks and finite element models

inferredcites →https://doi.org/10.12989/sem.2013.45.6.779openalex-snapshot

Adaptive Neuro Fuzzy Inference System (ANFIS) and Artificial Neural Networks (ANNs) for structural damage identification

inferredcites →https://doi.org/10.12989/sss.2007.3.3.263openalex-snapshot

Vibration-based damage detection in beams using genetic algorithm

inferredcites →https://doi.org/10.12989/sss.2008.4.1.099openalex-snapshot

Damage evaluation through radial basis function network based artificial neural network scheme

inferredcites →https://doi.org/10.12989/sss.2009.5.1.001openalex-snapshot

A two-stage damage detection approach based on subset selection and genetic algorithms

inferredcites →https://doi.org/10.12989/sss.2009.5.5.507openalex-snapshot

Adaptive balancing of highly flexible rotors by using artificial neural networks

inferredcites →https://doi.org/10.12989/sss.2010.6.2.147openalex-snapshot

Experimental studies on impact damage location in composite aerospace structures using genetic algorithms and neural networks

inferredcites →https://doi.org/10.12989/sss.2010.6.8.905openalex-snapshot

Effect of boundary conditions on modal parameters of the Run Yang Suspension Bridge

inferredcites →https://doi.org/10.12989/sss.2011.7.2.117openalex-snapshot

Damage detection in plates based on pattern search and Genetic algorithms

inferredcites →https://doi.org/10.12989/sss.2012.10.1.047openalex-snapshot

A non-destructive method for elliptical cracks identification in shafts based on wave propagation signals and genetic algorithms

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Detection of Transverse Cracks in a Composite Beam Using Combined Features of Lamb Wave and Vibration Techniques in Ann Environment

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Damage identification and health monitoring of structural and mechanical systems from changes in their vibration characteristics: A literature review

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Structural damage detection and identification using neural networks

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An artificial neural network approach to structural damage detection using frequency response functions

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Neural Networks for Inverse Problems in Damage Identification and Optical Imaging

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Damage Identification of CFRP Laminated Cantilever Beam by Using Neural Network

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Neural computing: theory and practice

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Application of artificial neural networks to predict compressive strength of high strength concrete

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