Anomaly and damage detection for structural health monitoring based on computational intelligence
- Weitere Titel
-
Anomalie- und Schadenserkennung für die kontinuierliche Zustandsüberwachung basierend auf künstlicher Intelligenz
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
Rheinisch-Westfälische Technische Hochschule Aachen, Dissertation, 2022
- Erschienen in
-
Report. IAM, Institute of General Mechanics ; IAM-16
- Schlagwort
-
Zustandsüberwachung
Structural Health Monitoring
Schadenfrüherkennung
- Ereignis
-
Veröffentlichung
- (wo)
-
Aachen
- (wer)
-
Universitätsbibliothek der RWTH Aachen
- (wann)
-
2022
- Urheber
- Beteiligte Personen und Organisationen
-
Markert, Bernd
Fritzen, Claus-Peter
- DOI
-
10.18154/RWTH-2023-01619
- URN
-
urn:nbn:de:101:1-2023031101372827665798
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
25.03.2025, 13:52 MEZ
Datenpartner
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Beteiligte
- Hesser, Daniel Frank
- Markert, Bernd
- Fritzen, Claus-Peter
- Universitätsbibliothek der RWTH Aachen
Entstanden
- 2022
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