Page 11 - january

PRODUCTION AUTOMATION

defects are most often absent. At the same stage, the features of the influence of the operating
modes of the machine and changes in external conditions, such as temperature, quality of
electric power, etc., on the diagnostic parameters are identified and taken into account. This
reduces the likelihood of false triggering of the monitoring system when changing modes or
external conditions.
Most of the adaptive control and monitoring systems existing on the market react to
changes in cutting conditions based on electromagnetic signals from the power unit of the
electric drive and automatically adjust the feed to the maximum allowable level for each
operation [17]. If necessary, these systems stop the machine due to overload or when a tool
break is detected. Often, leading manufacturers of CNC systems, such as Siemens, Heidenhain,
Fanuc, etc., enter into partnerships with manufacturers of adaptive control systems and carry
out their full integration with each other. Thus, in the process of management, these systems
take into account numerous factors affecting the cutting process: cutting parameters, actual
tool load, level of allowable tool wear, material characteristics, etc., which makes it possible
to significantly reduce machining time, prevent or determine the moment of tool breakage,
and minimize equipment downtime. Such systems combine the collection of information from
sensors, calculation and finding the optimal processing parameters.
However, these systems also have a number of features that limit their use only to
certain operations and processing modes. The measurement result is influenced by the energy
characteristics of other drives included in the general power network, a relatively large time
constant caused by the inertia of the electromechanical system, insufficient sensitivity when
operating in finishing and semi-finishing modes. These and other disadvantages can be leveled
by introducing an additional measuring channel using VA signals generated by the cutting
process or by the operation of the most important units, for example, a spindle [15]. VA signals
are more sensitive to the dynamics of the cutting process,
which is especially important for finishing operations or when
working with a small tool [18].
Figure 1 shows a functional diagram of a model,
which includes a three-axis milling machine with a
motor-spindle and an information-measuring system
(IMS) based on monitoring the active power and
parameters of VA signals.
In the acquisition and processing device (USO), the ADC,
DAC and MC units are combined in one 32-bit STM32F417ZGT6
microcontroller with a Cortex-M4F core, a feature of which is
a floating-point arithmetic unit (FPU), which allows solving
signal-processing tasks simultaneously with its digitization and
management. Responsible for digitizing are three 12-bit ADCs
with performance up to 2.4 MSPS (Mega Sample Per Second,
sampling rate). The control signal is formed by the built-in 12-
bit DAC. The main technical characteristics of the developed
IMS are shown in Table 1.
Stanochniy park 11