Information properties of vibroacoustic emission in diagnostic systems for cutting tool wear

OBRABOTKAMETALLOV Vol. 23 No. 3 2021 MATERIAL SCIENCE EQUIPMENT. INSTRUMENTS 7 5 Fig. 3. Example of changes in deformation autospectra depending on chip pressure ρ on the tool’s rake face Fig. 4. Sensitivity of amplitudes at resonances to variations ρ overall vibration spectrum toward the low-frequency range is observed. If ω(C) is specified, then ω ∞ ω ω ω = ω ω ∫ ∫ ( ) ( ) 0 ( ) ( ) Ñ i i i i Ñ X X X X S d S d is valid. The increment ω (C) depends less significantly on variations in the initial parameters, disturbances, and modes. As wear increases, two interrelated processes can be observed. The first process characterizes the determination of the state (Fig. 5). In this case, the peaks in the spectra become more pronounced and exhibit increased quality factors. The second process characterizes the degradation of properties, manifested in the formation of chaos. Dispersion estimation is used to evaluate evolution − σ ρ = σ ρ σ ρ     1 1 1 1 1 1 1 , , , 0 ( ) ( ) ( ) X X i X X i X X  , (4) where ∞ σ ρ = ω ρ ω = π ∫ 1 1 1 1 , , 0 1 ( ) ( , ) , 0,1, 2... X X i X X i S d i k; ρ = {ρ0, ρ1,…ρr} is sequence of ρi values, each of which corresponds to a variance. In this regard, when considering the total variance, there are two stages (Fig. 5, b).

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