Vibration measurement information processing
when automating recognition catastrophic cutter wear by dynamic system stability margin 

Aleksandr A. Ignat'ev, Doctor of engineering sciences, professor, professor of the sub-department of technical mechanics and mechatronics, Yuri Gagarin State Technical University of Saratov (77 Politehnicheskaya street, Saratov, Russia), E-mail: atp@sstu.ru
Vladimir A. Dobryakov, Candidate of engineering sciences, associate professor, associate professor of the sub-department of technical mechanics and mechatronics, Yuri GagarinState Technical University of Saratov (77 Politehnicheskaya street, Saratov, Russia), E-mail: atp@sstu.ru
Vladislav A. Revyakin, Senior lecturer of the sub-department of technical mechanics and mechatronics, Yuri Gagarin State Technical University of Saratov (77 Politehnicheskaya street, Saratov, Russia), E-mail: tmm@sstu.ru

Background. One of the dominant factors affecting the macro- and microgeometric accuracy parameters of parts is the dynamic quality of automated metal-cutting machines. It is evaluated based on the results of measuring vibroacoustic vibrations of the dynamic system (DS) of machines, which are then processed by various methods. Dynamic quality can vary for machines of the same model depending on their technical condition, as well as for each machine depending on the assigned cutting mode, cutter wear and other factors. Studies performed at the Yuri Gagarin State Technical University showed that it is advisable to assess the dynamic quality of the machines by the DS stability margin determined as a result of special processing of vibration measurement information and identification of the DS oscillation autocorrelation function (ACF). The purpose of the work is to algorithmize the process of processing vibration measuring information when generating estimates of the dynamic quality of the machine by the stability margin of the dynamic system in order to identify the initial phase of catastrophic wear of the cutter. To achieve the goal, firstly, a theoretical justification of the type of ACF vibrations during cutting is carried out, which is then used to identify ACF from experimental data, secondly, a method and algorithm for processing vibration measuring information is proposed, and thirdly, a practical test of the method for recognizing the beginning of catastrophic wear of a cutter on a CNC lathe is carried out. Materials and methods. Two main areas of analysis and evaluation of the dynamic quality of machines can be distinguished, the first being based on theoretical models, in which the results of experiments are used to a certain extent, and the second - on experimental studies of vibrations of various machines nodes with further mathematical processing of measurement information to identify the DS model and form estimates of dynamic quality. The results of many years of research of turning and grinding machines have shown that in production conditions it is the second direction that allows you to quickly assess the dynamic quality of the machines, subject to computer processing of measuring information. Results and conclusions. The results of theoretical analysis ofstochastic oscillations in the dynamic system of the machine and experimental studies of the accuracy of machining bearing rings on a CNC lathe with simultaneous automated measurement of vibroacoustic oscillations and calculation of oscillation indicators of the dynamic system confirmed their correlation and the possibility of determining the criterion for detecting the initial phase of catastrophic wear of the cutter by a significant change (by more than 50%) of the first differences in oscillation indicators.

machines, dynamic quality, vibroacoustic vibrations, autocorrelation function, spectral density, stability margin, integral estimates, processing quality

Ignatiev A.A., Dobryakov V.A., Revyakin V.A. Vibration measurement information processing when automating recognition catastrophic cutter wear by dynamic system stability margin. Izvestiya vysshikh uchebnykh zavedeniy. Povolzhskiy region. Tekhnicheskie nauki = University proceedings. Volga region. Engineering sciences. 2025;(1):75–91. (In Russ.). doi: 10.21685/2072-3059-2025-1-7