Frequency Feature Learning from Vibration Information of GIS for Mechanical Fault Detection.

Yuan, Yang; Ma, Suliang; Wu, Jianwen; Jia, Bowen; Li, Weixin; Luo, Xiaowu

Yuan, Yang; Ma, Suliang; Wu, Jianwen; Jia, Bowen; Li, Weixin; Luo, Xiaowu.

Afiliación

Yuan Y; School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China. sy1703415@buaa.edu.cn.
Ma S; School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China. masuliang@buaa.edu.cn.
Wu J; School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China. wujianwen@buaa.edu.cn.
Jia B; School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China. jiabowen109@126.com.
Li W; School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China. 13031041@buaa.edu.cn.
Luo X; School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China. humourluo@163.com.

Sensors (Basel) ; 19(8)2019 Apr 25.

Article en En | MEDLINE | ID: mdl-31027269

Palabras clave

coherent coefficient; gas insulated switchgear; mechanical fault diagnosis; one-class support vector machine; support vector machine

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Revista: Sensors (Basel) Año: 2019 Tipo del documento: Article País de afiliación: China

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