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Fatigue predictions in entire body of metallic structures from a limited number of vibration sensors using Kalman filtering

Fatigue predictions in entire body of metallic structures from a limited number of vibration sensors using Kalman filtering
Fatigue predictions in entire body of metallic structures from a limited number of vibration sensors using Kalman filtering
A methodology is proposed for estimating damage accumulation due to fatigue in the entire body of a metallic structure using output-only vibration measurements from a sensor network installed at a limited number of structural locations. Available frequency domain stochastic fatigue methods based on Palmgren-Miner damage rule, S-N fatigue curves on simple specimens subjected to constant amplitude loads, and Dirlik's probability distribution of the stress range are used to predict the expected fatigue damage accumulation of the structure in terms of the power spectral density (PSD) of the stress processes. The PSD of stresses at unmeasured locations are estimated from the response time history measurements available at the limited measured locations using Kalman filter and a dynamic model of the structure. The effectiveness and accuracy of the proposed formulation is demonstrated using a multidegree-of-freedom spring-mass chain model and a two-dimensional truss model arising from structures that consist of members with uniaxial stress states
life prediction, stochastic fatigue, dynamic analysis, spectral methods, kalman filter
1545-2255
1-20
Papadimitriou, Costas
3be78708-ed90-4a1f-b18e-5fe4ec2c8de6
Fritzen, Claus-Peter
84c3f2c4-19eb-4a94-97c6-9e0362665d7f
Kraemer, Peter
b3a94708-02aa-4b34-8e72-87fd0ee9e12b
Ntotsios, Evangelos
877c3350-0497-4471-aa97-c101df72e05e
Papadimitriou, Costas
3be78708-ed90-4a1f-b18e-5fe4ec2c8de6
Fritzen, Claus-Peter
84c3f2c4-19eb-4a94-97c6-9e0362665d7f
Kraemer, Peter
b3a94708-02aa-4b34-8e72-87fd0ee9e12b
Ntotsios, Evangelos
877c3350-0497-4471-aa97-c101df72e05e

Papadimitriou, Costas, Fritzen, Claus-Peter, Kraemer, Peter and Ntotsios, Evangelos (2011) Fatigue predictions in entire body of metallic structures from a limited number of vibration sensors using Kalman filtering. Structural Control & Health Monitoring, 1-20. (doi:10.1002/stc.395).

Record type: Article

Abstract

A methodology is proposed for estimating damage accumulation due to fatigue in the entire body of a metallic structure using output-only vibration measurements from a sensor network installed at a limited number of structural locations. Available frequency domain stochastic fatigue methods based on Palmgren-Miner damage rule, S-N fatigue curves on simple specimens subjected to constant amplitude loads, and Dirlik's probability distribution of the stress range are used to predict the expected fatigue damage accumulation of the structure in terms of the power spectral density (PSD) of the stress processes. The PSD of stresses at unmeasured locations are estimated from the response time history measurements available at the limited measured locations using Kalman filter and a dynamic model of the structure. The effectiveness and accuracy of the proposed formulation is demonstrated using a multidegree-of-freedom spring-mass chain model and a two-dimensional truss model arising from structures that consist of members with uniaxial stress states

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e-pub ahead of print date: May 2010
Published date: August 2011
Keywords: life prediction, stochastic fatigue, dynamic analysis, spectral methods, kalman filter
Organisations: Faculty of Engineering and the Environment

Identifiers

Local EPrints ID: 372155
URI: http://eprints.soton.ac.uk/id/eprint/372155
ISSN: 1545-2255
PURE UUID: e6ae8ed5-9ccf-42fb-be8f-8419995804ee
ORCID for Evangelos Ntotsios: ORCID iD orcid.org/0000-0001-7382-0948

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Date deposited: 01 Dec 2014 12:37
Last modified: 18 Feb 2021 17:22

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Contributors

Author: Costas Papadimitriou
Author: Claus-Peter Fritzen
Author: Peter Kraemer

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