A Semi-Supervised Approach to Bearing Fault Diagnosis under Variable Conditions towards Imbalanced Unlabeled Data

Fault diagnosis of rolling element bearings is an effective technology to ensure the steadiness of rotating machineries. Most of the existing fault diagnosis algorithms are supervised methods and generally require sufficient labeled data for training. However, the acquisition of labeled samples is o...

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Autors principals:	Xinan Chen, Zhipeng Wang, Zhe Zhang, Limin Jia, Yong Qin
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2018-06-01
Col·lecció:	Sensors
Matèries:	rolling element bearing semi-supervised learning visibility graph imbalanced data
Accés en línia:	http://www.mdpi.com/1424-8220/18/7/2097
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