K.A. Moroz1, R.R. Ibadov2, A. E. Merzlikina3

1-3 Don State Technical University (Rostov-on-Don, Russia)

1 kmoroz@donstu.ru; 2 ragim_ibadov@mail.ru; 3 angelinka-levchenko@mail.ru

During CNC turning, the quality of the machined surface and the life of the cutting tool depend on the dynamic state of the machine-tool-workpiece system. Tool vibration, uneven stock, and play in the kinematic chains significantly affect the output parameters of the process, complicating the prediction of machining quality and reliability. Existing monitoring methods either focus on individual parameters or require expensive equipment. A methodology for the comprehensive analysis of three information channels (vibration activity, cutting forces, and acoustic emission) using modern signal processing methods for adaptive control of machining modes is lacking.

Objective – to develop a methodology for comprehensive monitoring of the dynamic parameters of the cutting process during turning by integrating three information channels (tool vibration activity, cutting forces, and acoustic emission) using spectral analysis, correlation signal processing, and multivariate statistics.

A monitoring methodology has been developed, including a mathematical description of the dynamics of the SIPS using differential equations, spectral analysis algorithms based on the discrete Fourier transform, methods for integrating information channels through cross-correlation matrices, a system of threshold values for three process state classes, requirements for sensors and equipment (error no more than 2%), and a real-time signal processing algorithm with time synchronization of all channels.

The results are applied in the development of adaptive control systems for machining modes, allowing for a 15% increase in tool life, a 10-20% reduction in defective quality, and a 5-10% reduction in machine tool load. The methodology can be used in the development of predictive tool maintenance systems and digital twins of technological processes, particularly for manufacturing facilities with a diverse machine fleet. Keywords: CNC machines, cutting process dynamics, spectral analysis, vibrations, cutting forces, acoustic emission, adaptive control, diagnostic features, monitoring, signal processing.

Moroz K.A., Ibadov R.R., Merzlikina A.E. Analysis of information channels and methodology for integrate d monitoring of dynamic parameters of the cutting process during turning. Science Intensi ve Technologies. 2026. V. 27. № 2. P. 32−41. DOI: https://doi.org/ 10.18127/j19998465-202602-03 (in Russian)

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