Global framework for the assessment, development and demonstration of structural health and load monitoring systems
Notice bibliographique
Résumé
Properly deployed Structural Health Monitoring (SHM) has the potential to benefit the design, operation and maintenance of aircraft. For current aircraft, SHM could help extend operational lives while reducing operational (and maintenance) costs and increasing availability and operational safety. In addition, the implementation of SHM during the design stage of new aircraft could result in weight reduction through optimized design and the incorporation of active safety measures. However, a significant level of development, testing and demonstration is still required for SHM systems to attain the required maturity for deployment on ground and flight tests, and operational aircraft. With this intent, the National Research Council of Canada (NRC) has created a global framework, complete with a set of structural platforms facilitating an accurate assessment, development and demonstration of SHM systems. These platforms, with increasing levels of structural complexity, can accommodate SHM systems at different Technology Readiness Levels (TRL). The first level of structural complexity presents a simple 2 m long aluminium beam, with solid, rectangular cross section, the behaviour of which is well characterized through analytical and numerical methods. The second platform presents a slightly increased structural complexity, consisting of a typical representative 2 m long aircraft wing skin with riveted z-stringers, containing two different aluminium alloys. The third level of complexity presents a hybrid material aircraft wing box representative structure, with internal aluminium structures and carbon fibre reinforced epoxy composite skins. The final platforms consist of a full scale CF188 aircraft wing and a Bell 407 helicopter tail boom, representative of the current aerospace structures to trial sensors and measurement systems. In all of these platforms, representative load conditions applied during full scale tests or observed during flight operations can be applied through the use of several hydraulic actuators and actuation configurations. These load conditions range from static and quasi-static bending, torsion and coupled load conditions, to low frequency cyclic loading (either constant amplitude or operational spectra) and higher frequency vibration associated with buffet and flutter. Beyond the assessment, development and demonstration of load monitoring techniques and sensor systems, these platforms also offer the opportunity for the development and assessment of SHM techniques and systems capabilities to detect and monitor damage growth. In order to assess the TRL of the different SHM systems, replaceable components are introduced, either in a pristine condition, or with existing or artificially introduced representative damage, which can be grown during the application of the testing loads. Furthermore, these test platforms are being prepared to introduce representative flight operation environmental conditions, such as temperature and humidity.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,047 | 0,039 |
| Méta-épidémiologie (sens strict) | 0,004 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,004 |
| Bibliométrie | 0,008 | 0,006 |
| Études des sciences et des technologies | 0,002 | 0,005 |
| Communication savante | 0,009 | 0,007 |
| Science ouverte | 0,012 | 0,010 |
| Intégrité de la recherche | 0,014 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,013 | 0,010 |
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 source (Gemma direct ou Codex distillé), 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 ».