STRUCTURAL DAMAGE DETECTION BASED ON A MICRO-GENETIC ALGORITHM USING INCOMPLETE AND NOISY MODAL TEST DATA

By F. Au, Y. Cheng, L. Tham, Z. Bai. 2003

140 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Computer Vision and Pattern Recognition, Mechanics of Materials

View Paper: https://www.semanticscholar.org/paper/d57ec33016b7001d1531c26a7183f4bd815a7e80

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

In Computer Vision and Pattern Recognition

1. W. Heylen
2. Viviana Meruane

In Mechanics of Materials

1. W. Heylen
2. Viviana Meruane

Citations in the corpus

• An hybrid real genetic algorithm to detect structural damage using modal properties (2011, methodology): “[43] work with a two step procedure; first the element quotient dif170 ference is employed to locate the damage and second a micro-GA is used to 171 quantify it.”