OBRABOTKAMETALLOV technology Vol. 26 No. 3 2024 The business objective of using the proposed DS is to reduce the number of defects during program development and increase the economic efficiency of the machining process. Machining information is represented by various input data: name of the control program, tool identification number [63, 64], feed rate [65], spindle speed, etc. [66–68]. The monitoring method based on measurements of the VA signal, although it does not require accurate information about the absolute interaction of the cutting tool and the part, but in order to generate effective output data it is necessary to set restrictions. An FFT (Fast Fourier Transform) filter was used to isolate a narrow band of the sound wave [69–71]. This filter uses the FFT method, which allows to effectively analyze the frequency content of the signal. The FFT block size determines the frequency resolution of the analysis. The larger the block, the higher the frequency resolution [72]. For example, for a block size of 65,536 points and a sampling rate of 44.1 kHz, the frequency resolution is approximately 0.67 Hz. This allows to accurately determine the presence of certain frequencies in the signal. However, with a large block size, the temporal resolution deteriorates. To improve time resolution, a smaller FFT block can be used to better track rapid frequency changes, but frequency resolution will be significantly degraded. With an FFT size of 1,024, the frequency grid step will be approximately 43 Hz. This means that frequencies are 43, 86, 129 Hz, etc. will be determined with high accuracy, but intermediate frequencies, such as 50 Hz, may not be visible. Filtering is used to isolate useful frequency components of a signal and remove noise [73]. In machining applications, this can help isolate vibration frequencies of interest and eliminate unnecessary noise. The following types of filters are used: low-pass filters pass low-frequency components and suppress highfrequency ones; high-pass filters pass high-frequency components and suppress low-frequency ones; bandpass filters pass frequencies in a certain range and suppress frequencies outside this range. The use of window functions in FFT analysis is necessary to minimize side effects associated with window discontinuities in the time signal. When a signal is trimmed for analysis, abrupt changes may occur at the ends of the block, resulting in distortion in the spectrum (spectral leakage). The Hann window function has low sidelobes compared to the rectangular function, and low spectral leakage. Among the disadvantages, one can highlight the low frequency resolution. The Hamming window function has low side lobes compared to the Hann function, and low spectral leakage. Among the disadvantages, one can highlight the low frequency resolution in comparison with the Hann window function. The Blackman window function has a very low level of side lobes, which allows the level of spectral leakage to be minimized, but the frequency resolution is significantly reduced. Thus, the goal of this work is to develop an algorithm for the operation of an online monitoring system for monitoring the condition of a cutting tool, based on the creation of a digital shadow, using a vibroacoustic complex. To achieve this goal, it is planned to solve the following tasks: 1) to determine the frequency ranges of the frequency response of the acoustic signal obtained during machining used to analyze the level of wear of the cutting tool; 2) to determine the optimal window function when filtering the acoustic machining signal to isolate the useful signal; 3) to establish experimental relationships between the degree of tool wear, surface microrelief parameters and the frequency response of the vibroacoustic signal. Research methodology OM ТСС in machining plays a key role in improving production efficiency [74]. It allows for a quick response to wear and other changes in the active contact zone of the tool [35, 75] and the workpiece, thereby ensuring optimal use of the equipment and preventing the need for premature or delayed tool replacement, which in turn can lead to unnecessary downtime, such as planned, and unscheduled. In the case under consideration, optimization of the milling process was based on minimizing the target cost function: ( ) ( ) 1 min, n i i F x C x = → = ∑
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