Stepper motors are often used in automated laser cutting systems. The control circuit of a stepper motor requires a special electronic device - a driver, which receives logical signals as input and changes the current in the motor windings to provide motion parameters. This research study evaluated stepper motor drivers to determine the feasibility of their use - PLDS880, OSM-42RA, OSM-88RA. To control the system, software code was written, which was connected to the controller via a link board. With each driver, in different modes, optimal parameters were selected (initial speed, final speed and acceleration), that is, the movement of the carriage without stalling for ten passes with a minimum travel time. The results of the experiments are presented in the form of tables.
Keywords: laser, laser cutting, automation, technological process, stepper motor, performance, driver, controller, control circuit, optimal parameters
Stepper motors are often used in automated laser cutting systems. The control circuit of a stepper motor requires a special electronic device - a driver, which receives logical signals as input and changes the current in the motor windings to provide motion parameters. This research study evaluated stepper motor drivers to determine the feasibility of their use - PLDS880, OSM-42RA, OSM-88RA. To control the system, software code was written, which was connected to the controller via a link board. With each driver, in different modes, optimal parameters were selected (initial speed, final speed and acceleration), that is, the movement of the carriage without stalling for ten passes with a minimum travel time. The results of the experiments are presented in the form of tables.
Keywords: laser, laser cutting, automation, technological process, stepper motor, performance, driver, controller, control circuit, optimal parameters
This study is devoted to analyzing the capabilities of the Python programming language when creating information systems for detecting dangerous objects in luggage. As a result, a recognition system architecture was developed, including the following main components: an image processing module, a machine learning module, a database and a user interface. The software chosen is Python with the libraries PySide6, SQLite, Numpy, YOLO. The information system was implemented and tested on real data, which confirmed the correctness of the selected capabilities and technologies of the Python language for the development of security information systems.
Keywords: information system, security, neural network, machine learning, pattern recognition, performance