SOURCE-LINKED INTELLIGENCE

Pathology-based Structural Health Monitoring

CORDIS · observation · Publication date unknown

nable real-time damage identification and simultaneous inverse calibration of all scenario-based models, these numerical models are replaced by computationally efficient meta-models constructed using artificial intelligence (AI) tools which form a multi-class DT. The resulting DT is capable of inferring, in quasi real-time, the probability of occurrence of the identified potential damage pathologies and their severity when supplied with continuous monitoring data. If an anomaly is detected, a Bayesian model selection approach identifies the damage mechanism, selecting the meta-model that explains the experimental data with the highest likelihood. This approach, therefore, enables rapid, robust, and comprehensive damage identification. Path-B SHM has the potential to revolutionize and advance the frontiers of SHM, offering unprecedented opportunities for data-informed decision-making in the preservation of CH constructions. Cultural Heritage Constructions, Damage Identification, Digital Twins, Monitoring, Structural Health Monitoring, Structural Maintenance

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recordType

award

status

SIGNED

region

EU

value

209914.56

unit

EUR