A CNN Prediction Method for Belt Grinding Tool Wear in a Polishing Process Utilizing 3-Axes Force and Vibration Data

A CNN Prediction Method for Belt Grinding Tool Wear in a Polishing Process Utilizing 3-Axes Force and Vibration Data

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This paper presents a tool wear monitoring methodology on the abrasive belt grinding process using vibration and force signatures on a convolutional neural network (CNN). A belt tool typically has a random orientation of abrasive grains and grit size variation for coarse or fine material removal. De...

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Bibliographic Details
Main Authors: Wahyu Caesarendra, Triwiyanto Triwiyanto, Vigneashwara Pandiyan, Adam Glowacz, Silvester Dian Handy Permana, Tegoeh Tjahjowidodo
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Electronics
Subjects:
convolutional neural network
manufacturing
prediction
grinding process
vibration and force signal
Online Access:https://www.mdpi.com/2079-9292/10/12/1429

Internet

https://www.mdpi.com/2079-9292/10/12/1429

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