0
  • DE
  • EN
  • FR
  • Internationale Datenbank und Galerie für Ingenieurbauwerke

Anzeige

Intelligent fault diagnosis of storage stacking machinery under variable working conditions using attention-based adaptive multimodal feature fusion networks

Autor(en): ORCID (School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China)
(Institute of Smart City and Intelligent Transportation, Southwest Jiaotong University, Chengdu, China)
(School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China)
(School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China)
(School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China)
(School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China)
(School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China)
(School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China)
(School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China)
(School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China)
(School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, China)
Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Structural Health Monitoring, , n. 6, v. 23
Seite(n): 3465-3485
DOI: 10.1177/14759217241227163
Structurae kann Ihnen derzeit diese Veröffentlichung nicht im Volltext zur Verfügung stellen. Der Volltext ist beim Verlag erhältlich über die DOI: 10.1177/14759217241227163.
  • Über diese
    Datenseite
  • Reference-ID
    10775648
  • Veröffentlicht am:
    29.04.2024
  • Geändert am:
    10.11.2024
 
Structurae kooperiert mit
International Association for Bridge and Structural Engineering (IABSE)
e-mosty Magazine
e-BrIM Magazine