A robust singular value decomposition for damage detection under changing operating conditions and structural uncertainties

By S. Vanlanduit, E. Parloo, B. Cauberghe, Patrick Guillaume, P. Verboven. 2005

105 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Mechanics of Materials, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/5a7d244377a769e31707daad1a7a847109643b18

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Civil and Structural Engineering

1. J. J. Moughty
2. Nuno Maia
3. A. Ribeiro
4. J. Rius
5. D. Montalvão
6. R. Gibson

In Mechanics of Materials

1. J. J. Moughty
2. Nuno Maia
3. A. Ribeiro
4. J. Rius
5. D. Montalvão
6. R. Gibson

Citations in the corpus

• A review of vibration-based structural health monitoring with special emphasis on composite materials (2006, methodology): “Vanlanduit et al. (2005) introduced the robust singular value decomposition (RSVD) for damage detection from measurements taken under different operational conditions, i.e., different excitation levels, geometrical uncertainties and surface treatments.”
• A State of the Art Review of Modal-Based Damage Detection in Bridges: Development, Challenges, and Solutions (2017, methodology): “[100] also employed the same technique to increase their regression model’s robustness when used in conjunction with Single Value Decomposition (SVD) for damage detection.”