Physics-Based Model Assisted Age Prediction of Real- Serviced Thermal Barrier Coated Samples Using Infrared Thermography

  • In this study, an age prediction model is developed for the real serviced thermal barrier coated (TBC) samples. TBC is a multilayer coating applied on metallic structures exposed to high temperatures, such as gas turbine blades and aeroengine parts, to extend the operational life. One of the main challenges for developing an age prediction model is the unavailability of serviced samples and labelled datasets. So, in this study, experimentally validated numerical models are used for data generation. The study considers samples with three different service times, i.e., 0 (newly coated), 500 hours, and 1000 hours. The age prediction is done in two stages: thermal diffusivity prediction for blind real serviced samples with a trained 1D-CNN model and classification of samples based on the service hours into different classes using AI classification models. The results demonstrate that our approach provides reliable age estimations with a high correlation between actual and predicted agesIn this study, an age prediction model is developed for the real serviced thermal barrier coated (TBC) samples. TBC is a multilayer coating applied on metallic structures exposed to high temperatures, such as gas turbine blades and aeroengine parts, to extend the operational life. One of the main challenges for developing an age prediction model is the unavailability of serviced samples and labelled datasets. So, in this study, experimentally validated numerical models are used for data generation. The study considers samples with three different service times, i.e., 0 (newly coated), 500 hours, and 1000 hours. The age prediction is done in two stages: thermal diffusivity prediction for blind real serviced samples with a trained 1D-CNN model and classification of samples based on the service hours into different classes using AI classification models. The results demonstrate that our approach provides reliable age estimations with a high correlation between actual and predicted ages of samples. This method provides a non-destructive, efficient, and accurate method of evaluating the life of TBCs, which is a substantial improvement over traditional techniques that rely on complex destructive methods or microstructural analysis for the age evaluation.zeige mehrzeige weniger

Volltext Dateien herunterladen

Metadaten exportieren

Weitere Dienste

Suche bei Google Scholar Anzahl der Zugriffe auf dieses Dokument
Metadaten
Autor*innen:Sruthi Krishna Kunji PurayilORCiD
Koautor*innen:K. Balasubramaniam
Dokumenttyp:Posterpräsentation
Veröffentlichungsform:Präsentation
Sprache:Englisch
Jahr der Erstveröffentlichung:2024
Organisationseinheit der BAM:8 Zerstörungsfreie Prüfung
8 Zerstörungsfreie Prüfung / 8.3 Thermografische Verfahren
Veröffentlichende Institution:Bundesanstalt für Materialforschung und -prüfung (BAM)
DDC-Klassifikation:Technik, Medizin, angewandte Wissenschaften / Ingenieurwissenschaften / Ingenieurbau
Freie Schlagwörter:AI for NDT; Infrared Thermography; NDE 4.0; Thermal barrier coatings
Themenfelder/Aktivitätsfelder der BAM:Infrastruktur
Infrastruktur / Leichtbau
Veranstaltung:17th Quantitative InfraRed Thermography Conference (QIRT)
Veranstaltungsort:Zagreb, Croatia
Beginndatum der Veranstaltung:01.07.2024
Enddatum der Veranstaltung:05.07.2024
Verfügbarkeit des Dokuments:Datei für die Öffentlichkeit verfügbar ("Open Access")
Datum der Freischaltung:28.01.2025
Referierte Publikation:Nein
Schriftenreihen ohne Nummerierung:BAM Präsentationen
Einverstanden
Diese Webseite verwendet technisch erforderliche Session-Cookies. Durch die weitere Nutzung der Webseite stimmen Sie diesem zu. Unsere Datenschutzerklärung finden Sie hier.