Remaining Useful-Life Prediction of the Milling Cutting Tool Using Time-Frequency-Based Features and Deep Learning Models.

Sayyad, Sameer; Kumar, Satish; Bongale, Arunkumar; Kotecha, Ketan; Abraham, Ajith

Sayyad, Sameer; Kumar, Satish; Bongale, Arunkumar; Kotecha, Ketan; Abraham, Ajith.

Afiliación

Sayyad S; Symbiosis Institute of Technology, Symbiosis International (Deemed University), Pune 412115, India.
Kumar S; Symbiosis Institute of Technology, Symbiosis International (Deemed University), Pune 412115, India.
Bongale A; Symbiosis Centre for Applied Artificial Intelligence, Symbiosis International (Deemed University), Pune 412115, India.
Kotecha K; Symbiosis Institute of Technology, Symbiosis International (Deemed University), Pune 412115, India.
Abraham A; Symbiosis Institute of Technology, Symbiosis International (Deemed University), Pune 412115, India.

Sensors (Basel) ; 23(12)2023 Jun 17.

Article en En | MEDLINE | ID: mdl-37420825

Asunto(s)

Aprendizaje Profundo; Comportamiento del Uso de la Herramienta; Inteligencia Artificial; Comercio; Ingeniería

Palabras clave

feature extraction; milling process; remaining useful life; timefrequency domain; tool wear

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Comportamiento del Uso de la Herramienta / Aprendizaje Profundo Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Sensors (Basel) Año: 2023 Tipo del documento: Article País de afiliación: India

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