An hybrid real genetic algorithm to detect structural damage using modal properties

By Viviana Meruane, W. Heylen. 2011

157 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/232553e129fde64c59e9d178c6713d494a3bc38d

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. Serkan Kiranyaz
2. Moncef Gabbouj
3. Onur Avcı
4. Osama Abdeljaber
5. Daniel J. Inman
6. Alper Erturk
7. Abdessattar Abdelkefi
8. Muhammad R. Hajj

In Computer Vision and Pattern Recognition

1. Daniel J. Inman
2. Serkan Kiranyaz
3. Onur Avcı
4. Osama Abdeljaber
5. Moncef Gabbouj

In Electrical and Electronic Engineering

1. Daniel J. Inman
2. Moncef Gabbouj
3. Alper Erturk
4. Abdessattar Abdelkefi
5. Henry Sodano
6. Mohammed F. Daqaq
7. S. Anton
8. Lihua Tang

Citations in the corpus

• A Review of Vibration-Based Damage Detection in Civil Structures: From Traditional Methods to Machine Learning and Deep Learning Applications (2020, background): “A large number of techniques have been developed to detect, localize and quantify structural damage in an attempt to make the monitoring process more feasible [2–4].”