Early Fault Detection via Multiple Feature Fusion and Ensemble Learning

Early fault detection (EFD) of rotating machines is important to decrease the maintenance cost and improve the mechanical system stability. One of the key points of EFD is developing a generic and robust model for different equipment. Most existing EFD methods focus on learning fault representation...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	IEEE sensors journal Ročník 24; číslo 5; s. 7196 - 7204
Hlavní autori:	Song, Wenbin, Wu, Di, Shen, Weiming, Boulet, Benoit
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.03.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Datasets Early fault detection (EFD) Ensemble learning Fault detection Feature extraction Frequency domain analysis Maintenance costs Mechanical systems Noise reduction one-class support vector machine (SVM) Representations Rotating machinery Rotating machines stacked denoising autoencoder (SDAE) Stacking Support vector machines Systems stability
ISSN:	1530-437X, 1558-1748
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!