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A framework for assessing the reliability of crack luminescence – an automated fatigue crack detection system

  • The new crack luminescence method offers the possibility of making fatigue surface cracks in metallic materials more visible during inspections through a special coating system. This coating system consists of two layers, whereby the first layer has fluorescent properties and emits visible light as soon as it is irradiated by UV light. The top layer is black and is designed to prevent the fluorescent layer from emitting if no crack develops in the underlying material. The technique proved particularly useful in a wide variety of fatigue tests of steel components under laboratory conditions. Moreover, it has the potential to be used in various industrial applications. To enable industrial deployment and integration into maintenance strategies, a concept study is developed in this contribution, resulting in a qualification framework that can serve as a foundation for determining the reliability of the crack luminescence system in terms of a probability of detection curve. Within thisThe new crack luminescence method offers the possibility of making fatigue surface cracks in metallic materials more visible during inspections through a special coating system. This coating system consists of two layers, whereby the first layer has fluorescent properties and emits visible light as soon as it is irradiated by UV light. The top layer is black and is designed to prevent the fluorescent layer from emitting if no crack develops in the underlying material. The technique proved particularly useful in a wide variety of fatigue tests of steel components under laboratory conditions. Moreover, it has the potential to be used in various industrial applications. To enable industrial deployment and integration into maintenance strategies, a concept study is developed in this contribution, resulting in a qualification framework that can serve as a foundation for determining the reliability of the crack luminescence system in terms of a probability of detection curve. Within this study, factors causing measurement variability and uncertainty are being determined and their influences assessed. Due to the extension of the system by a moving computer vision system for automated crack detection using artificial intelligence, additional long-term effects associated with structural health monitoring systems need to be incorporated into an extended probability of detection study as part of the technical justification. Finally, important aspects and findings related to design of experiments are discussed, and a framework for reliability assessment of a new optical crack monitoring method is presented, emphasizing the influence of various uncertainty parameters, including long-term effects such as system ageing.zeige mehrzeige weniger

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Metadaten
Autor*innen:Paul Gerards-Wünsche, Mirjana Ratkovac, Ronald SchneiderORCiD, Falk Hille, Matthias Baeßler
Dokumenttyp:Beitrag zu einem Tagungsband
Veröffentlichungsform:Graue Literatur
Sprache:Englisch
Titel des übergeordneten Werkes (Englisch):SPIE Conference Smart Structures + Nondestructive Evaluation 2023
Jahr der Erstveröffentlichung:2023
Organisationseinheit der BAM:7 Bauwerkssicherheit
7 Bauwerkssicherheit / 7.2 Ingenieurbau
Aufsatznummer:Paper 12489-4
Erste Seite:1
Letzte Seite:15
DDC-Klassifikation:Technik, Medizin, angewandte Wissenschaften / Ingenieurwissenschaften / Angewandte Physik
Freie Schlagwörter:Artificial Intelligence; Computer Vision; Crack Luminescence; Non-Destructive Evaluation; Probability of Detection; Reliability; Structural Health Monitoring; Wind
Themenfelder/Aktivitätsfelder der BAM:Energie
Veranstaltung:SPIE Conference Smart Structures + Nondestructive Evaluation 2023
Veranstaltungsort:Long Beach, CA, USA
Beginndatum der Veranstaltung:24.03.2023
Enddatum der Veranstaltung:28.03.2023
DOI:10.1117/12.2658390
ISBN:978-1-5106-6086-1
Verfügbarkeit des Dokuments:Datei im Netzwerk der BAM verfügbar ("Closed Access")
Datum der Freischaltung:30.03.2023
Referierte Publikation:Ja
Datum der Eintragung als referierte Publikation:18.09.2023
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