A New Bearing Fault Diagnosis Method Based on Deep Transfer Network and Supervised Joint Matching

A New Bearing Fault Diagnosis Method Based on Deep Transfer Network and Supervised Joint Matching

In practical industrial environment, variable working condition can result in shifts in data distributions, and the labeled fault data in various working conditions is difficult to collect because rotating machines often works in normal status, and the insufficient labeled fault data brings data sam...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Chengyao Liu, Fei Dong, Kunpeng Ge, Yuanyuan Tian
Format: Artikel
Sprache:Englisch
Veröffentlicht: IEEE 2024-01-01
Schriftenreihe:IEEE Photonics Journal
Schlagworte:
Deep learning
domain adaptation
fault diagnosis
time-frequency images
Online-Zugang:https://ieeexplore.ieee.org/document/10506734/
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge