Resumen
In the development of a tool wear monitoring system in milling, the complex cutting path always brings challenges to the system?s reliability in the production line. The cutting path effect on the acoustic emission (AE) and vibration signals during the micro milling processes was investigated in this study by implementing three types of cutting paths in a micro milling experiment. To generate the data for analysis, an experiment was conducted on a micro milling research platform using an AE sensor and an accelerometer installed on a fixture attached to the spindle housing. To demonstrate the effect of the cutting path on the performance in the monitoring of tool wear, a simple linear classifier is proposed, along with the signal features generated from the different signal lengths and the bandwidth size in the frequency domain. The results show that the signal features generated from the cutting of a straight line, the corner of the square path, and the circle path are different from each other. The increase in the signal length to generate features, which will reduce the corner effect, could improve the performance of the developed monitoring system. However, the results suggest that avoiding the complex cutting path for feature generation might be a better strategy for developing a micro milling tool wear monitoring system.