OBRABOTKAMETALLOV Vol. 23 No. 3 2021 MATERIAL SCIENCE EQUIPMENT. INSTRUMENTS 7 1 5 As can be seen from Fig. 1, the vibration monitoring system relies on piezoelectric vibration sensors of the cutting tool. However, new intelligent sensors are becoming increasingly prevalent, offering the capability to digitally display vibration accelerations, speeds, and tool displacements directly [17‑20]. To illustrate the system’s operation, consider a turning example where a steel shaft (steel 45) with a diameter of 50 mm was machined on a 1K625 lathe. The processing mode was: a cutting speed of 124 m/ min, a depth of cut of 1 mm, and a feed rate of 0.11 mm/rev. We performed sequential double integration of the measured vibration acceleration signals using a program written in the Matlab environment. The resulting vibration acceleration signals from the x, y, and z channels, along with the calculated vibration velocity and displacement values, are presented for a single measurement case in the aforementioned figures. The adequacy of the program for step-by-step integration of the captured vibration acceleration signal can be conveniently examined by analyzing the main carrier frequencies in the signal’s spectrum, as illustrated in Fig. 5. As observed in Fig. 5, the main carrier frequencies remain unchanged. However, the high-frequency component of the vibration signal is significantly attenuated. This attenuation is attributed to the fact that the integration process involves summation and averaging operations, which aligns with the inertial properties of the object (tool). The actual wear of the cutting tool can be influenced by random factors not accounted for in digital twin mathematical models. To assess the actual wear of the cutting tool, a separate experiment was conducted on the 1K625 lathe, machining the shaft (steel 45) using the previously specified cutting mode. To measure a b c d Fig. 1. Vibration monitoring system on the 1K625 lathe: a, b – industrial accelerometers; c, d – amplifier converter and ADC
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