Tool Wear State Identification Based on SVM Optimized by the Improved Northern Goshawk Optimization.

Wang, Jiaqi; Xiang, Zhong; Cheng, Xiao; Zhou, Ji; Li, Wenqi

Wang, Jiaqi; Xiang, Zhong; Cheng, Xiao; Zhou, Ji; Li, Wenqi.

Afiliación

Wang J; School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China.
Xiang Z; School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China.
Cheng X; School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China.
Zhou J; Longgang Institute of Zhejiang Sci-Tech University, Wenzhou 325802, China.
Li W; School of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China.

Sensors (Basel) ; 23(20)2023 Oct 20.

Article en En | MEDLINE | ID: mdl-37896684

Palabras clave

improved northern goshawk optimization; recursive feature elimination; support vector machine; tool wear state identification

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2023 Tipo del documento: Article País de afiliación: China

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