Trivariate Empirical Mode Decomposition via Convex Optimization for Rolling Bearing Condition Identification.

Lv, Yong; Zhang, Houzhuang; Yi, Cancan

Lv, Yong; Zhang, Houzhuang; Yi, Cancan.

Afiliação

Lv Y; Key Laboratory of Metallurgical Equipment and Control Technology, Wuhan University of Science and Technology, Ministry of Education, Wuhan 430081, China. lvyong@wust.edu.cn.
Zhang H; Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan 430081, China. lvyong@wust.edu.cn.
Yi C; Key Laboratory of Metallurgical Equipment and Control Technology, Wuhan University of Science and Technology, Ministry of Education, Wuhan 430081, China. houzhuangwust@163.com.

Sensors (Basel) ; 18(7)2018 Jul 18.

Article em En | MEDLINE | ID: mdl-30021945

Palavras-chave

convex optimization; low-rank matrix approximation; rolling bearing condition identification; trivariate empirical mode decomposition

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Revista: Sensors (Basel) Ano de publicação: 2018 Tipo de documento: Article País de afiliação: China

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