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Procedia Engineering
Article . 2017 . Peer-reviewed
License: CC BY NC ND
Data sources: Crossref
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Procedia Engineering
Article
License: CC BY NC ND
Data sources: UnpayWall
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Damage Identification Using Particle Filters

Authors: Chunfeng Wan; Rui Huang; Liyuan Huang; Bo Wen; Tadanobu Sato;

Damage Identification Using Particle Filters

Abstract

Abstract Structural health monitoring of civil engineering structures is a fundamental issue for structural safety and integrity, due to the fact that they will deteriorate after they are built and put into services. Within which, damage identification will be the most important problem. In this paper, a structural damage identification method based on particle filters, will therefore be introduced. The algorithm of the particle filter will be studied. The application of the proposed method to a lumped-mass shear frame structure will be made. The parameters of the stiffness and damping of each floor will be identified using the particle filters and analyzed. Parameters of the particle filter will be studied and their effect to the identification results will also be analyzed. Simulation of a single degree and multi-degree structure will be conduct to verify the effectiveness of the particle filter identification method. For each case, damage is deliberately introduced into the numerical model. Response signals will be collected and analyzed. Final identification results show that the proposed method can do the work very well and could be a promising approach for real applications.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Average
Average
Average
gold