OBRABOTKAMETALLOV Vol. 25 No. 1 2023 technology ing the spectrum analyzer «ZetLab 017–U2», piezoelectric vibration sensors «BC 110», microphone «Zet BC 501» with a perceived frequency range of 20 Hz–13 kHz and Samson Meteor Mic cardioid directivity with a range of 20 Hz–20 kHz. The roughness parameter Rz (μm), vibration displacement S (μm) and the amplitude–frequency characteristic of the acoustic signal A (dB), ω (Hz) were used as the output evaluation of the processing efficiency. The use of a condenser microphone has a number of advantages – low frequency response, low level of non-linear and transient distortion, high sensitivity and low self-noise. Particular attention should be paid to improving the quality of the diagnostic signal, which consists of the sum of the spectrum of the “useful” signal and a large number of unequal noise levels coming from various objects. Spectral subtraction was used for real-time noise reduction. The most common method of denoising is spectral subtraction (Fig. 2). The decomposition of the signal during spectral subtraction was carried out using a special weight function [22] – the Blackman window. Research results In the process of machining, a change in the properties of the DS is observed, which is determined by various factors. The disclosure of the features of the loss of stability of the toolpath during milling (Fig. 3) makes it possible to determine ways to improve the reliability of the operation of technological equipment (TE). Fig. 1. Real-time monitoring in milling: 1 – vibration sensor and microphone with cardioid orientation; 2 – spectrum analyzer «ZetLab 017-U2»; 3 – PC with ZETLAB software (Formulated by the authors) Fig. 2. The proposed spectral subtraction algorithm scheme: x(t) – original signal; STFT – Short Time Fourier Transform; W(f) – is the function of the weighting window; y(t) – transformed signal (Formulated by the authors)
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