Showing papers by "Jean-Claude Golinval published in 2018"
TL;DR: In this article, principal component analysis (PCA) is used for damage detection in structures excited by harmonic forces, and time responses are directly analysed by Singular Value Decomposition to deduct two dominant Proper Orthogonal Values corresponding to two proper Orthogonality Modes.
Abstract: Principal Component Analysis is used for damage detection in structures excited by harmonic forces. Time responses are directly analysed by Singular Value Decomposition to deduct two dominant Proper Orthogonal Values corresponding to two Proper Orthogonal Modes. Damage index is defined by the concept of subspace angle that a subspace is built from the two Proper Orthogonal Modes. A subspace angle reflects the coherence between two different structural health states. An example is given through the application on a part of a real prestressed concrete bridge in Luxembourg where different damage states were created by cutting a number of prestressed tendons in four scenarios with increasing levels. Results are better by using excitation frequency close to an eigenfrequency of the structure. The technique is convenient for practical application in operational bridge structures.
3 citations