Sensor-based identification of tool wear in turning
Paper in proceeding, 2024

The online monitoring of tool wear using signal processing during machining has emerged as a prominent technological means in the advancement towards Industry 4.0. In this investigation, the potential of identifying worn cutting tools is assessed using a microphone, 3-axis accelerometer, and 3-axis dynamometer. A comparison of the signals from a sharp versus worn tool shows a potential to identify the wear state of the tool, provided that the suitable signal processing technique and feature selection are employed. The investigation suggests that the careful selection of the sensor’s position has a prominent role in the success of the wear identification.

wear

monitoring

sensor

machining

Author

Charlie Salame

Chalmers, Industrial and Materials Science, Materials and manufacture

Rico Rapold

Student at Chalmers

Bülent Tasdelen

Kistler Group

Amir Malakizadi

Chalmers, Industrial and Materials Science, Materials and manufacture

Procedia CIRP

22128271 (eISSN)

Vol. 121 228-233

11th CIRP Global Web Conference, CIRPe 2023
Virtual, Online, ,

Subject Categories

Control Engineering

DOI

10.1016/j.procir.2023.09.252

More information

Latest update

3/1/2024 1