Wireless Monitoring of Wear of the Vibration Self-Sensing Tool

The vibration sensor system based on Zigbee wireless technology has the problems of short communication distance and complex networking when used for monitoring cutting tool wear. Therefore, this paper proposes a tool wear monitoring method based on WiFi wireless sensor network to collect vibration signals. Firstly, a wireless vibration signal acquisition network with ESP8266 WiFi development board at its core and the high-precision vibration sensor ADXL345 as the sensitive element is established. Then according to the overall shape of the tool, the vibration sensor is pasted on the tool surface to make a self-sensing tool for collecting wireless vibration signals during the outer circle cutting experiment of 45 steel bar. At the same time, hard-wired vibration signals are collected under the same cutting conditions for comparison with wireless ones to verify the feasibility of the device. Finally, some statistics of the time domain signals are imported into the support vector machine regression model as feature vectors for training, and the tool wear prediction model is obtained. The experimental results show that the relative error of the wireless signals collected by the self-sensing tool is smaller than 3.61%, which means the method proposed is feasible; the resolution accuracy of the tool wear prediction model based on support vector machine regression is 94.38%, which proves that the designed wireless system can accurately monitor tool wear. © 2022 Xi'an Jiaotong University. All rights reserved.