In-Process Monitoring and Estimation of Tool Wear on CNC Turning by Applying Multi-Sensor with Back Propagation Technique

Abstract:

The aim of this research is to propose and develop the in-process monitoring system of the tool wear for the carbon steel (S45C) in CNC turning process by utilizing the multi-sensor which are the force sensor, the sound sensor, the accelerometer sensor and the acoustic emission sensor. The progress of the tool wear results in the larger cutting force, the higher amplitude of the acceleration signal, and the higher power spectrum densities of sound and acoustic emission signals. Hence, their signals have been integrated via the neural network with the back propagation technique to monitor the tool wear. The experimentally obtained results showed that the in-process monitoring system proposed and developed in this research can be effectively used to estimate the tool wear level with the higher accuracy and reliability.

• Periodical: Advanced Materials Research (Volumes 291-294)
• Pages: 3036-3043
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.291-294.3036
• Online since: July 2011
• Authors: Somkiat Tangjitsitcharoen, Channarong Rungruang
• Keywords: Acceleration, Acoustic Emission (AE), Back Propagation Technique, Cutting Force, Sensor Fusion, Sound, Tool Wear, Turning

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