[Analyse comparative de l’identification des fissures dans le cadre de la surveillance de la santé des structures : Prédiction expérimentale de la longueur des fissures avec YUKI et POD-RBF]
Ces dernières années, des investissements substantiels dans la construction structurelle ont mis en évidence l’importance primordiale de l’intégrité structurelle pour la sécurité et la fiabilité. La surveillance de la santé des structures (SHM) est devenue un outil essentiel pour évaluer la santé des structures, en mettant l’accent sur la détection, la localisation et la quantification des dommages, en particulier grâce à des méthodes basées sur les vibrations qui exploitent les variations des propriétés modales en tant que précurseurs des dommages structurels. Cette étude présente une méthodologie innovante qui combine de manière synergique la décomposition orthogonale appropriée (POD) et l’interpolation de la fonction de base radiale (RBF) pour prédire les réponses structurelles basées sur les paramètres des fissures. En outre, l’algorithme YUKI, qui tire parti du regroupement de populations pour l’optimisation, est présenté. L’approche est rigoureusement évaluée par l’analyse expérimentale de deux poutres distinctes (poutre I et poutre II) présentant différentes profondeurs de fissures. Les résultats démontrent l’efficacité de l’approche POD-RBF-YUKI, indiquant un niveau notable de précision et de cohérence. Les évaluations comparatives avec les algorithmes d’optimisation conventionnels, à savoir Cuckoo, Bat et Particle Swarm Optimisation, révèlent des valeurs d’erreur moyenne similaires mais avec une variabilité accrue des résultats, tandis que les modèles de réseaux neuronaux artificiels profonds (ANN) avec des tailles de couches cachées variées.
In recent years, substantial investments in structural construction underscore the paramount importance of ensuring structural integrity for safety and dependability. Structural Health Monitoring (SHM) has emerged as a pivotal tool for assessing structural health, with an emphasis on damage detection, localisation, and quantification, particularly through vibration-based methods that exploit variations in modal properties as precursors to structural damage. This study presents an innovative methodology that synergistically combines Proper Orthogonal Decomposition and Radial Basis Function interpolation for predicting structural responses based on crack parameters. Additionally, the YUKI algorithm, leveraging population clustering for optimisation, is introduced. The approach is rigorously assessed through experimental analysis of two distinct beams (Beam I and Beam II) exhibiting varying crack depths. The results demonstrate the effectiveness of the POD-RBF-YUKI approach, indicating a notable level of accuracy and consistency. Comparative evaluations with conventional optimisation algorithms, namely Cuckoo, Bat, and Particle Swarm Optimisation, reveal similar Mean Percentage Error values but with increased result variability, whereas Deep Artificial Neural Network models with varied hidden layer sizes.
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Mot clés : Identification des fissures, Réduction du modèle, Analyse modale expérimentale, Analyse inverse, Algorithme YUKI
CC-BY 4.0
@article{CRMECA_2024__352_G1_55_0,
author = {Roumaissa Zenzen and Ayoub Ayadi and Brahim Benaissa and Idir Belaidi and Enes Sukic and Tawfiq Khatir},
title = {A comparative analysis for crack identification in structural health monitoring: a focus on experimental crack length prediction with {YUKI} and {POD-RBF}},
journal = {Comptes Rendus. M\'ecanique},
pages = {55--70},
publisher = {Acad\'emie des sciences, Paris},
volume = {352},
year = {2024},
doi = {10.5802/crmeca.241},
language = {en},
}
TY - JOUR AU - Roumaissa Zenzen AU - Ayoub Ayadi AU - Brahim Benaissa AU - Idir Belaidi AU - Enes Sukic AU - Tawfiq Khatir TI - A comparative analysis for crack identification in structural health monitoring: a focus on experimental crack length prediction with YUKI and POD-RBF JO - Comptes Rendus. Mécanique PY - 2024 SP - 55 EP - 70 VL - 352 PB - Académie des sciences, Paris DO - 10.5802/crmeca.241 LA - en ID - CRMECA_2024__352_G1_55_0 ER -
%0 Journal Article %A Roumaissa Zenzen %A Ayoub Ayadi %A Brahim Benaissa %A Idir Belaidi %A Enes Sukic %A Tawfiq Khatir %T A comparative analysis for crack identification in structural health monitoring: a focus on experimental crack length prediction with YUKI and POD-RBF %J Comptes Rendus. Mécanique %D 2024 %P 55-70 %V 352 %I Académie des sciences, Paris %R 10.5802/crmeca.241 %G en %F CRMECA_2024__352_G1_55_0
Roumaissa Zenzen; Ayoub Ayadi; Brahim Benaissa; Idir Belaidi; Enes Sukic; Tawfiq Khatir. A comparative analysis for crack identification in structural health monitoring: a focus on experimental crack length prediction with YUKI and POD-RBF. Comptes Rendus. Mécanique, Volume 352 (2024), pp. 55-70. doi : 10.5802/crmeca.241. https://comptes-rendus.academie-sciences.fr/mecanique/articles/10.5802/crmeca.241/
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