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dc.rights.licenseLicencia de Creative Commons Reconocimiento-NoComercial-CompartirIgual 4.0 Internacionalspa
dc.contributor.authorQuintero-Parra, Andres F.
dc.contributor.authorCamacho-Navarro, Jhonatan
dc.contributor.authorFlórez, Marco
dc.contributor.authorVázquez-González, J.L.
dc.description.abstractIn this paper the results of using a Multi-agent system (MAS) for Structural Health Monitoring (SHM) are detailed. A study between different MAS architectures reported in literature is presented in order to select and adapt the most adequate one for SHM tasks. Requirements are established according to recent solutions, where main parameters are type and number of sensors and communication protocols, among others. MAS technique uses several intelligent agents, that are algorithms able to act in a reactive or active way. Their action depends on surrounding environment or collected data. These agents can work in a decentralized way, searching the fulfillment of an individual goal or they can work with another system to achieve a common goal. Decision is based on their internal state (beliefs, goals and commitments). MAS’ effectiveness depends on the interconnection between the agents. Type of agents is defined according to its communication method and protocol, common and individual goals, among others. Decentralization and versatility are two important characteristics of MAS technique useful to solve SHM problem. This is one of the main motivations to consider this technique to be a good approach for the studied problem. A benchmark numerical model, which consists of a metallic framework, was used to validate and demonstrate the feasibility of the selected architecture for SHM.eng
dc.publisherInternational Association of Online Engineeringspa
dc.sourceInternational Journal of Online Engineeringeng
dc.sourceVol. 13, No.06 (2017)eng
dc.subjectArtificial Intelligenceeng
dc.subjectIntelligent Agenteng
dc.subjectMultiagent Architectureeng
dc.subjectStructural Health Monitoringeng
dc.titleEvaluation of Multi-agent Architecture for Structural Damage Detection and Locationeng
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