Fatigue predictions in entire body of metallic structures from a limited number of vibration sensors using Kalman filtering
By Costas Papadimitriou, Claus-Peter Fritzen, P. Kraemer, E. Ntotsios. 2011
193 citations recorded by the source corpus.
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. Copyright © 2010 John Wiley & Sons, Ltd.
Subfields: Civil and Structural Engineering, Mechanics of Materials
View Paper: https://www.semanticscholar.org/paper/bb25937eeaf202b8e331cd4254c48bea54732a18
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In Civil and Structural Engineering
In Mechanics of Materials
Citations in the corpus
- A dual Kalman filter approach for state estimation via output-only acceleration measurements (2015, methodology): “[1]; where a technique was introduced that uses the Kalman filter for estimating power spectral densities of the strain in the body of the structure thereby predicting the remaining fatigue life.”