Bachelor's thesis project on "Automated axle weighing system for Vehicles." The project consists of an introduction, two chapters, conclusions, a list of references, and appendices. The project comprises 61 pages, 3 tables, 44 figures, a list of 11 cited sources, and 2 appendices. The aim of the project is to develop platform-based vehicle scales and enable axle weighing on them. The first chapter provides an overview and analysis of existing vehicle scales and load cells. The second chapter presents the design principles and electrical schematics, metrological characteristics calculations, and the development of the structure for the load cell and platform scales.
Diploma project of a fourth-year student, a member of group PK-91 from the instrument-making faculty, Koval Nazariy, on the topic: "Automated eddy current flaw detector based on chips of impedance meters." The diploma project consists of 50 pages, 7 drawings, and 16 literary sources.
The project focused on the design and implementation of an eddy current flaw detector. Calculations were performed, including the calculation of the eddy current converter. The graphic part of the diploma project presents a structural diagram of the flaw detector, created on a sheet of A3 format, a functional diagram on another sheet of A3 format, an assembly drawing of the eddy current converter on a sheet of A1 format, an electrical circuit diagram on another sheet of A1 format, and a specification for the electrical circuit diagram.
The diploma project is devoted to the development and research of the eddy current method of wire quality control. In the work, calculations of the output voltage of the eddy current converter were carried out, which were performed taking into account various influencing factors and system parameters. The main problem solved by the diploma project is to increase the efficiency of wire quality control by using the non-contact eddy current method, which ensures high accuracy of detecting defects such as dents and other violations of the wire diameter. The graphic part of the diploma project includes a structural diagram of the developed system, an assembly drawing of the eddy current converter and its detailing, an electrical schematic diagram and a poster "Physical principles of operation of the eddy current system for controlling the diameter of the wire" diagram. The purpose of the work: improvement of the process of controlling the diameter of the wire in the technological process of its manufacture by using the non-contact eddy current method, which provides high accuracy of detecting defects and the possibility of control in dynamic mode.
The diploma project consists of an introduction, 3 chapters, a conclusion, a list of used literature and 4 appendices. The work is completed on 60 pages and has 23 figures, 3 tables and 32 formulas. The goal of this diploma project is the development of an automatic transport and packaging line with a weight control system. To implement the set tasks, the following was done: 1) Analysis of already existing packaging lines and weight control systems and their detailed description;
Development of software for automated sorting of secondary waste is an urgent and important problem in the modern world. In this work, the use of neural networks in waste sorting was investigated, and a program capable of automatically classifying secondary waste was developed. Various sorting methods and technologies are reviewed, including neural networks, convolutional, recurrent, deep, transformer, and squeezed networks. The software architecture was carefully designed, the application requirements were defined, and the necessary tools and libraries were used for implementation. The program was modeled using usage, sequence, and activity diagrams, showing the interaction of components and the sequence of their execution. The developed software was also tested, and a description of the control example was given. The results indicate the effectiveness of using a neural network in the process of sorting secondary waste. The general conclusion of the work is that the use of neural networks in waste sorting has great potential for improving the accuracy and speed of the sorting process. However, in order to achieve optimal results, it is necessary to continue research and improve algorithms and models to ensure the efficient and stable operation of secondary waste sorting systems.
