Damage detection in vibrating bodies using genetic algorithms

By M. Rao, J. Srinivas, B. Murthy. 2004

125 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/bb55bee399fa5db9409432e9622e1711817dde0a

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. W. Heylen
2. Viviana Meruane
3. Hod Lipson
4. W. Aquino
5. Josh C. Bongard
6. B. Kouchmeshky

In Statistics and Probability

1. W. Heylen
2. Viviana Meruane
3. Hod Lipson
4. W. Aquino
5. Josh C. Bongard
6. B. Kouchmeshky

Citations in the corpus

• Co‐evolutionary algorithm for structural damage identification using minimal physical testing (2007, methodology): “Genetic algorithms have been successfully used for error minimization in various damage identification problems [2, 4–8] and have gained wide acceptance due to their inherent advantages such as convergence to global optima, noise tolerance, handling of multimodal problems (non-unique solutions), and”
• An hybrid real genetic algorithm to detect structural damage using modal properties (2011, methodology): “[29] also work with force residuals and BCGA optimization to detect damage of simulated truss structures.”