Model-based identification of damage from sparse sensor measurements using Neumann series expansion

DOI10.1080/17415977.2016.1160393zbMath1359.74361OpenAlexW2314985588MaRDI QIDQ2974008

Gholamreza Ghodrati Amiri, Seyed Ali Seyed Razzaghi, Ali Zare Hosseinzadeh

Publication date: 5 April 2017

Published in: Inverse Problems in Science and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/17415977.2016.1160393

zbMATH Keywords

inverse problemmodal datadamage detectionmodel reduction approachGeneralised Flexibility Matrix (GFM)Particle Swarm Optimization-Colonial Competitive Algorithm (PSO-CCA)

Mathematics Subject Classification ID

Related Items (3)

Damage assessment in plate-like structures using a two-stage method based on modal strain energy change and Jaya algorithm ⋮ An iterated IRS technique for cross-sectional damage modelling and identification in beams using limited sensors measurement ⋮ An improved generalized flexibility matrix approach for structural damage detection

Cites Work

• Model reduction by Neumann series expansion
• Statistical detection of structural damage based on model reduction
• A numerical technique for structural damage detection
• An iterative system equivalent reduction expansion process for extraction of high frequency response from reduced order finite element model.
• THE CONVERGENCE OF THE ITERATED IRS METHOD
• Application of a hybrid of particle swarm and genetic algorithm for structural damage detection

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