A novel intelligent bearing fault diagnosis method based on signal process and multi-kernel joint distribution adaptation
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
online resource.
- Erschienen in
-
A novel intelligent bearing fault diagnosis method based on signal process and multi-kernel joint distribution adaptation ; volume:13 ; number:1 ; day:20 ; month:3 ; year:2023 ; pages:1-16 ; date:12.2023
Scientific reports ; 13, Heft 1 (20.3.2023), 1-16, 12.2023
- Urheber
-
Xiong, Jundi
Cui, Shihai
Tang, Haihong
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1038/s41598-023-31648-y
- URN
-
urn:nbn:de:101:1-2023080821021708106131
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
14.08.2025, 10:49 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Xiong, Jundi
- Cui, Shihai
- Tang, Haihong
- SpringerLink (Online service)
Ähnliche Objekte (12)
A motor bearing fault diagnosis model based on multi-adversarial domain adaptation
Dynamic Distribution Adaptation Based Transfer Network for Cross Domain Bearing Fault Diagnosis
Fault diagnosis of wind turbine bearing based on stochastic subspace identification and multi-kernel support vector machine
Correction to: Dynamic Distribution Adaptation Based Transfer Network for Cross Domain Bearing Fault Diagnosis
HUST bearing: a practical dataset for ball bearing fault diagnosis
Intelligent speed adaptation : Expertenstatements
Frequency Loss and Recovery in Rolling Bearing Fault Detection
Rolling bearing fault diagnosis based on quantum LS-SVM
Intelligent system for fault diagnosis in automotive applications
Bearing fault detection by using graph autoencoder and ensemble learning
Improved Multi-Bandwidth Mode Manifold for Enhanced Bearing Fault Diagnosis
M-Net: a novel unsupervised domain adaptation framework based on multi-kernel maximum mean discrepancy for fault diagnosis of rotating machinery
A motor bearing fault diagnosis model based on multi-adversarial domain adaptation
Dynamic Distribution Adaptation Based Transfer Network for Cross Domain Bearing Fault Diagnosis
Fault diagnosis of wind turbine bearing based on stochastic subspace identification and multi-kernel support vector machine
Correction to: Dynamic Distribution Adaptation Based Transfer Network for Cross Domain Bearing Fault Diagnosis
HUST bearing: a practical dataset for ball bearing fault diagnosis
Intelligent speed adaptation : Expertenstatements
Frequency Loss and Recovery in Rolling Bearing Fault Detection
Rolling bearing fault diagnosis based on quantum LS-SVM
Intelligent system for fault diagnosis in automotive applications
Bearing fault detection by using graph autoencoder and ensemble learning
Improved Multi-Bandwidth Mode Manifold for Enhanced Bearing Fault Diagnosis
M-Net: a novel unsupervised domain adaptation framework based on multi-kernel maximum mean discrepancy for fault diagnosis of rotating machinery
A motor bearing fault diagnosis model based on multi-adversarial domain adaptation
Dynamic Distribution Adaptation Based Transfer Network for Cross Domain Bearing Fault Diagnosis
Fault diagnosis of wind turbine bearing based on stochastic subspace identification and multi-kernel support vector machine
Correction to: Dynamic Distribution Adaptation Based Transfer Network for Cross Domain Bearing Fault Diagnosis
HUST bearing: a practical dataset for ball bearing fault diagnosis
Intelligent speed adaptation : Expertenstatements
Frequency Loss and Recovery in Rolling Bearing Fault Detection
Rolling bearing fault diagnosis based on quantum LS-SVM
Intelligent system for fault diagnosis in automotive applications
Bearing fault detection by using graph autoencoder and ensemble learning
Improved Multi-Bandwidth Mode Manifold for Enhanced Bearing Fault Diagnosis