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A platform for research: civil engineering, architecture and urbanism
Improved structural damage identification using random decrement signatures: Application to FEM data
10.1002/stc.239.abs
This article describes detection of structural damage using statistical properties of randomdec signatures. Proposed technique is model free and does not require input measurements. The technique is evaluated using acceleration data obtained from a finite element model of a frame‐like structure. Damage in the model is represented by a structural member with nonlinear stiffness characteristic due to opening and closing cracks. The results suggest that reliability of damage detection would depend on the orientation of the crack and the richness of the response. Copyright © 2008 John Wiley & Sons, Ltd.
Improved structural damage identification using random decrement signatures: Application to FEM data
10.1002/stc.239.abs
This article describes detection of structural damage using statistical properties of randomdec signatures. Proposed technique is model free and does not require input measurements. The technique is evaluated using acceleration data obtained from a finite element model of a frame‐like structure. Damage in the model is represented by a structural member with nonlinear stiffness characteristic due to opening and closing cracks. The results suggest that reliability of damage detection would depend on the orientation of the crack and the richness of the response. Copyright © 2008 John Wiley & Sons, Ltd.
Improved structural damage identification using random decrement signatures: Application to FEM data
Shiryayev, Oleg V. (author) / Slater, Joseph C. (author)
Structural Control and Health Monitoring ; 15 ; 1006-1020
2008-11-01
15 pages
Article (Journal)
Electronic Resource
English
Improved structural damage identification using random decrement signatures: Application to FEM data
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