## 1 Introduction  
There is a stable trend in the development of modern industrial production, which consists of the desire to minimize human presence in the area of implementation of production processes. For this purpose, the machinery is equipped with additional sensors and signal analysis systems designed not only to replace human organoleptic capabilities but also to perceive better information signals that are inaccessible to human capabilities. To automate production processes, it is not enough to supplement technological equipment with conveyors, manipulators, robots, and other similar devices that replace the manual labor of the operator. It is necessary to monitor the current state of all units, on the operation of which the reliability of the functioning of the equipment and the quality of the obtained products depend. If the process of such expensive equipment is accompanied by accidents, downtime, and the release of defective products, this will lead to a decrease in the economic effect of the automation of production processes. Among all the problems that arise when creating automated equipment, monitoring the treatment process remains the most difficult. This is because it is almost impossible to place sensors in the processing area, and indirect monitoring methods are associated with the impacts of various random factors and a decrease in the information content of equipment signals when it is located remotely from the core of the technological process [1; 2; 3; 4]. Many problems of monitoring the condition of the blade tool could be solved with systems for monitoring power parameters. However, for industrial applications, such systems should not degrade the dynamic characteristics of the machine and reduce its versatility. Piezoelectric converters made it possible to create dynamometric systems [5] that provide the necessary equipment rigidity and measurement quality, but their use was limited by laboratory conditions. Of all the attempts to measure the power parameters functionally related to the components of the cutting force, the control of the power consumed by the drives providing the relative movement of the tool and the workpiece has found actual industrial application. However, another problem arose here, which is that the drive power must meet the needs of both roughing and finishing. Under these conditions, small drills, cutters, taps and finishing tools are out of the observation area, since it is difficult to distinguish the power consumption for them from the idle power of a powerful engine. Namely, breakdowns of such a tool are the leading cause of equipment downtime and negative impacts on the processed product [6]. A lot of information about the condition of the tools could be obtained if there was a technique for measuring the temperature of the tool cutting edge. However, during cutting, the tool edge is usually covered with separated chips and coolant, and, therefore, is inaccessible for control using modern pyrometers [7; 8]. Although the monitoring of temperature changes in electrical equipment, friction surfaces, and bearing units is widely presented in the scientific literature [9; 10; 11; 12; 13; 14], the use of this technique for monitoring the cutting process can only be observed in experimental studies. An assessment of the condition of tools using direct measurements or an analysis of their images is relevant only outside the cutting process [15; 16; 17], which does not allow the method to be widely used for monitoring the technological process itself in the \"online\" mode. The analysis of vibroacoustic signals as a method of non-destructive testing has long won a firm place in the industry. It is widely used to control the quality of manufacturing of individual components and finished products, as well as to monitor their conditions during operation. Many studies are devoted to assessing the state of bearing units and gears based on the analysis of their noise and vibrations [18; 19; 20; 21] and the state of various rotary mechanisms [22; 23; 24; 25; 26].