Diagnostics System of Automated Vehicle Electrical Equipment and its Impacts on Carbon Emissions

Abstract

© 2020. All Rights Reserved. Diagnostics of vehicle equipment is an urgent task during the production process. It allows you to ensure the required quality of finished products and improve the production process efficiency, along with environmental considerations. One of the ways to identify the malfunction of car components and assemblies is to take diagrams of various operation modes of electrical equipment using a digital oscilloscope and also evaluating its carbon dioxide emission. To solve this problem, you can use the recognition and classification of diagram images using an intelligent system and develop recommendations for maintenance and repair. Pattern recognition is one of the most demanded functions of modern control systems, used in a variety of activities: from equipment diagnostics to unmanned vehicle control. The article proposes the technique for electrical equipment malfunction diagnosing based on the use of artificial intelligence elements to ensure preserving the ecosystem health. The input information is the diagrams of various operating modes of electrical equipment obtained from a digital oscilloscope. The resulting diagrams are pre-processed and classified in order to determine the state of vehicle components and assemblies. Correlation of diagrams to a certain state of equipment is carried out using one of the classification algorithms. Support vector methods and k - nearest neighbors can be considered as the most promising classification methods in image recognition problems. Further, on the basis of the received state of electrical equipment, recommendations for maintenance and repair are formed using an expert system. A production model was used to develop an expert system, which makes it possible to apply simple and precise mechanisms for knowledge use.Thus, the intelligent system will allow diagnostics of production equipment faster and more efficiently, without imposing high requirements on service personnel qualifications.