A multi‐objective genetic algorithm strategy for robust optimal sensor placement. (17th February 2021)

• Record Type: Journal Article
• Authors: Civera, Marco; Pecorelli, Marica Leonarda; Ceravolo, Rosario; Surace, Cecilia; Zanotti Fragonara, Luca
• Other Names: Beck James L. guestEditor.; Bursi Oreste S. guestEditor.; Mosalam Khalid guestEditor.
• Is Part Of: Computer-aided civil and infrastructure engineering. Volume 36:Number 9(2021)
• Page Start: 1185
• Page End: 1202
• Publication Date: 2021-02-17
• Subjects: Civil engineering -- Data processing -- Periodicals; Computer-aided engineering -- Periodicals; 624.0285
• DOI: 10.1111/mice.12646
• Languages: English
• ISSNs: 1093-9687

Abstract

Abstract: The performance of a monitoring system for civil buildings and infrastructures or mechanical systems depends mainly on the position of the deployed sensors. At the current state, this arrangement is chosen through optimal sensor placement (OSP) techniques that consider only the initial conditions of the structure. The effects of the potential damage are usually completely neglected during its design. Consequently, this sensor pattern is not guaranteed to remain optimal during the whole lifetime of the structure, especially for complex masonry buildings in high seismic hazard zones. In this paper, a novel approach based on multi‐objective optimization (MO) and genetic algorithms (GAs) is proposed for a damage scenario driven OSP strategy. The aim is to improve the robustness of the sensor configuration for damage detection after a potentially catastrophic event. The performance of this strategy is tested on the case study of the bell tower of the Santa Maria and San Giovenale Cathedral in Fossano (Italy) and compared to other classic OSP strategies and a standard GA approach with a single objective function.