The purpose of this work is to study the applicability of the U-Net architecture for automatically determining the contours of natural skins using the TensorFlow and Keras libraries in Python. A software application has been developed based on methods including OpenCV libraries, as well as a model for implementing a deep convolutional neural network. The dataset for training and testing the network was created using augmentation. Training was carried out using the stochastic gradient descent method after splitting the data sample into training and test images. In the future, the results obtained will be used to create an automated system that will make it possible to determine the contours of the skin and its defects, which in turn will open up the possibility of calculating the useful area of ​​the skin and creating an automated layout of patterns taking into account the identified defects.

Keywords: computer vision, edge detection, natural skin, machine learning, convolutional neural networks, U-Net architecture, deep learning

This article explores a method for executing data collection systems based on the widely-used industrial protocol, Modbus TCP. In this configuration, the server is a program emulating the Modbus TCP protocol.To implement the client an algorithm and furnished a practical Python programming illustration that employs a lower-level socket library.

Keywords: python, socket, modbus

The article discusses correlation methods of image identification. An algorithm of the "rare grid" method has been developed.

Keywords: image identification, algorithm, recognition, cutting, reference frame, element correlations, minimum search

The article is devoted to the issues of accounting for various production disturbances that affect the temperature field in the drying chamber. The nature and nature of disturbances affecting the change in chamber temperature are taken into account using statistical methods for processing temperature curves over time. The temperature field in the plane of sensor installation was considered.In practice, the electrical model of the temperature field of the drying chamber can be represented as a three-dimensional grid, and the nature of the temperature field can be judged from the distribution of potentials at the corresponding grid nodes. By changing the grid parameters, it is possible to determine the appropriate temperature regimes for different materials and types of impregnations.

Keywords: temperature, statistical methods, drying chamber, autocorrelation function, spectral density, amplitude-phase characteristic

The article discusses the method of recognizing contours in the primary image. An algorithm has been developed for finding the absolute minimum of functionality in an image.

Keywords: contour, algorithm, defect, recognition, cut, reference frame, minimum search

The article presents the results of a full-factor experiment and analyzesthe impact of various factors, such as the number of transitions a tape machine, the characteristics of an infrared laser diode and a the humidity of the material on the magnitude of the signal response when infrared radiation passes through the tape.

Keywords: fiber mixing quality, infrared estimation method, planning matrix, regression equation, model adequacy

The article is devoted to the control system for the process of moving textile material in an apparatus for impregnating fabrics with periodic action. The control is implemented using a programmable logic controller (PLC). We consider a program developed in the Ladder Diagram (LD) programming language that implements motion control taking into account the change in torque.

Keywords: solution, immersion, technological process, algorithm, programming language LD

The control of the fabric in the technological chain determines the structure of this very chain. The article uses a probabilistic model to assess the feasibility of re-processing fabric in finishing production.

Keywords: fabric, marriage, quality, batch, product, technological defect, reprocessing, profit, loss

The article discusses the issue of creating an automated system for detecting defects on tissue based on the use of computer vision. The resulting system makes it possible to control, register and calculate defects in textile materials without human participation in the technological process, which improves the quality of analysis, eliminates the number of errors in fabric sorting and reduces the cost of the technological operation.

Keywords: automated system, defect detection, textile material, computer vision, microcomputer, image processing library