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Structural Damage Assessment using an Artificial Immune System

Structural Damage Assessment using an Artificial Immune System

Maribel Anaya Vejar, Diego Alexander Tibaduiza Burgos, Francesc Pozo
Copyright: © 2015 |Pages: 17
ISBN13: 9781466684904|ISBN10: 1466684909|EISBN13: 9781466684911
DOI: 10.4018/978-1-4666-8490-4.ch005
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MLA

Vejar, Maribel Anaya, et al. "Structural Damage Assessment using an Artificial Immune System." Emerging Design Solutions in Structural Health Monitoring Systems, edited by Diego Alexander Tibaduiza Burgos, et al., IGI Global, 2015, pp. 86-102. https://doi.org/10.4018/978-1-4666-8490-4.ch005

APA

Vejar, M. A., Burgos, D. A., & Pozo, F. (2015). Structural Damage Assessment using an Artificial Immune System. In D. Burgos, L. Mujica, & J. Rodellar (Eds.), Emerging Design Solutions in Structural Health Monitoring Systems (pp. 86-102). IGI Global. https://doi.org/10.4018/978-1-4666-8490-4.ch005

Chicago

Vejar, Maribel Anaya, Diego Alexander Tibaduiza Burgos, and Francesc Pozo. "Structural Damage Assessment using an Artificial Immune System." In Emerging Design Solutions in Structural Health Monitoring Systems, edited by Diego Alexander Tibaduiza Burgos, Luis Eduardo Mujica, and Jose Rodellar, 86-102. Hershey, PA: IGI Global, 2015. https://doi.org/10.4018/978-1-4666-8490-4.ch005

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Abstract

Structural damage assessment methodologies allow providing knowledge about the current state of the structure. This information is important because allows to avoid possible accidents and perform maintenance tasks in the structure. This chapter proposes the use of an artificial immune system to detect and classify damages in structures by using data from a multi-actuator piezoelectric system that is working in several actuation phases. In a first step of the methodology, principal component analysis (PCA) is used to build a baseline model by using the collected data. In a second step, the same experiments under similar conditions are performed with the structure in different states (damaged or not). These data are projected into the different baseline models for each actuator, in order to obtain the damages indices and build the antigens. The antigens are compared with the antibodies by using an affinity function and the result of this process allows detecting and classifying damages.

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