Fiducial marker-based decentralized computer vision for structural modal identification
Notice bibliographique
Résumé
• Introduces novel vision-based approach for decentralized vibration measurement in structural health monitoring. • Integrates multiple cameras in a decentralized setup for full-field measurement, capturing high-density spatial data in high resolution. • Uses fiducial markers as inexpensive virtual sensors for 3D time series extraction via camera calibration and pose estimation. • Offers contactless and remote measurements with high spatial density, reducing cost and time compared to traditional methods. • Validated through rigorous laboratory tests on building and beam models, and field tests on a truss bridge. Due to the advancement in optics and computer vision, the implementation of the vision-based technique is extensively being investigated for structural health monitoring. Compared with traditional contact sensing measurements, computer-vision technology offers contactless and remote measurements with high spatial density at low cost and instrumentation time. This study proposes an innovative contactless vision-based decentralized vibration measurement technique, where the fiducial marker is utilized as an inexpensive virtual sensor to extract structural vibration measurements using 3D pose estimation through camera calibration. Once the vibration measurements are extracted, covariance-driven stochastic subspace identification is employed due to its robustness for effective mode decomposition and noise reduction capabilities. This paper enables the extraction of 3D time series without deploying a stereo camera system and combines the multiple fields of view of different regions of interest from various cameras in a decentralized manner to capture high-density and high-resolution spatial data for full-field measurement. Two laboratory tests were conducted on a lab-scale building model and a lab-scale beam model to validate the robustness and effectiveness of the proposed methodology. Following the laboratory validation, field tests on a full-scale truss bridge were performed to demonstrate the efficacy of the proposed technique. The relative error in the estimation of the modal frequencies in lab-scale experimentation is <2 %, whereas, for the field study, it is <5.5 %, considering the working distance between the camera and field bridge is over 30 m. The modal assurance criterion (MAC) between the extracted mode shapes is also estimated, and the average MAC values for lab-scale building and lab-scale beam models are 98.61 % and 97.28 %, respectively. The proposed technique has proven to capture the minuscule vibration of the structure at a considerable distance between the structure and the vision-based system, including a detailed comparative study between the vision-based system and accelerometers.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».