A Machine Learning Approach for Wear Monitoring of End Mill by Self-Powering Wireless Sensor Nodes

A Machine Learning Approach for Wear Monitoring of End Mill by Self-Powering Wireless Sensor Nodes

There are many tool condition monitoring solutions that use a variety of sensors. This paper presents a self-powering wireless sensor node for shank-type rotating tools and a method for real-time end mill wear monitoring. The novelty of the developed and patented sensor node is that the longitudinal...

Full description

Bibliographic Details
Main Authors: Vytautas Ostasevicius, Paulius Karpavicius, Agne Paulauskaite-Taraseviciene, Vytautas Jurenas, Arkadiusz Mystkowski, Ramunas Cesnavicius, Laura Kizauskiene
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Sensors
Subjects:
sensor node
energy harvesting
tool vibrations
tool condition monitoring (TCM)
support vector machine (SVM)
end milling
Online Access:https://www.mdpi.com/1424-8220/21/9/3137

Internet

https://www.mdpi.com/1424-8220/21/9/3137

Similar Items