Population based structural health monitoring framework using optimal sensor placement and pseudo-transfer learning

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dc.contributor.authorDahel, Ihab
dc.contributor.otherLarbi, H. Selma
dc.date.accessioned2026-09-10T14:39:19Z
dc.date.available2026-09-10T14:39:19Z
dc.date.issued2026-06-20
dc.description90 p. : ill. ; 30 cm. + (1cd-rom). Bibliogr.
dc.description.abstractAlgeria's mass-housing programs use identical reinforced concrete buildings, making traditional Structural Health Monitoring (SHM) economically unfeasible. This thesis develops a Population-Based SHM (PBSHM) framework. A Ground+9-story (G+9) reference building (RPA 2024, BAEL 91/99) is analyzed. A Genetic Algorithm determines an Optimal Sensor Placement (OSP), identifying 20 sensors using the Modal Assurance Criterion (MAC) matrix. Inter-structure variations are modeled as Gaussian noise. A dual-branch Denoising Autoencoder (DAE) reconstructs sensor fields and predicts damage, achieving a coefficient of determination (R²) >0.93 and Mean Squared Error (MSE) <0.02, validating scalable deployment.
dc.identifier.citationDahel, Ihab. Population based structural health monitoring framework using optimal sensor placement and pseudo-transfer learning. Mém. Ing., Alger, ENSTP-FJ, 2026.
dc.identifier.urihttp://dspace.enstp.edu.dz/handle/123456789/1237
dc.language.isoen
dc.publisherENSTP-FJ
dc.subjectPopulation-based SHMen
dc.subjectDenoising autoencoderen
dc.subjectOptimal Sensor Placement (OSP)en
dc.subjectModal Assurance Criterion (MAC)en
dc.subjectFlexibility-based damage indicatoren
dc.subjectCoefficient of determination (R²)en
dc.subjectRPA 2024 (code)en
dc.subjectSeismic monitoringen
dc.subjectSurveillance basée sur la population (PBSHM)
dc.subjectAuto-encodeur débruiteur (DAE)
dc.subjectPlacement optimal de capteurs (OSP)
dc.subjectCritère d'Assurance Modale (MAC)
dc.subjectIndicateur de dommage par flexibilité
dc.subjectCoefficient de détermination (R²)
dc.subjectRPA 2024 (règlement)
dc.subjectSurveillance sismique
dc.titlePopulation based structural health monitoring framework using optimal sensor placement and pseudo-transfer learning
dc.typeMémoire d'Ingénieur d'Etat
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