Intelligent System of Constructing Vector Diagrams of Electrical Circuits

Abstract

Phasor diagrams are a powerful tool for visualizing and understanding the distribution of current, voltage, and power in electrical systems. During Russia's war against Ukraine, our energy industry has become very vulnerable to enemy attacks, and therefore needs a quick and effective recovery. Energy specialists lack software tools for working with the power system, and in the period of development of artificial intelligence, creating such tools is not so difficult. For example, familiar specialists often have to build vector diagrams - tools for visualizing and understanding the distribution of current, voltage and power in electrical systems. Using a combination of frameworks for working with artificial intelligence and creating a graphic shell, you can achieve the desired result in a few months, and at the same time do a useful thing for our victory. The YOLO model (based on the PyTorch framework) and the QT framework are considered among the proposed tools for creating an intelligent vector diagram construction system. The role of artificial intelligence is to recognize electrical elements in circuits and their connections to each other. Creating a user interface is an equally important thing, which is already implemented in many places with the help of QT. As of today, there is no specialized software tool for solving the problems of manual construction of vector diagrams, but the proposed approaches are already used for its creation. The system uses the Yolov5 model to recognize electrical elements on the circuit. The model is trained on more than 150 images and is able to recognize hand-drawn diagrams. Recognition is run as a separate process from the main program written in C++. This part of the system processes the input data from Yolo, saves it in a convenient format, creates a user interface, and displays the result as a vector diagram.