The article deals with the problem of determining suboptimal spatial points and angles for diagnosing the technical state of elements of electrical facilities based on multispectral photography from an unmanned aircraft. As an object of analysis, a power plant with tube-mounted overhead connections is used. An important distinctive feature of data collection using unmanned aerial vehicles on the territory of critical infrastructure facility is the need to maximize flight safety. The article proposes a new formulation of the problem of using unmanned aerial vehicle for diagnosing electrical systems, taking into account the economic effect of data collection, the risks of both equipment failures and the probable accidents of an unmanned aircraft. At the same time, it is required to use a digital twin (digital instance) to assess the solutions generated by the neural network, since it is necessary to model how the diagnosed equipment elements will be viewed from the unmanned aerial vehicle route points, have a spatial traffic safety map at the substation and a map of all diagnosed objects with additional data. The developed technique can also be used in the design of new electrical facilities in order to increase the efficiency of their diagnostic procedures during subsequent operation.
Original languageEnglish
Title of host publication2022 IEEE International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages780-784
ISBN (Print)978-166546480-2
DOIs
Publication statusPublished - 11 Nov 2022
Event2022 IEEE International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON) - Yekaterinburg, Russian Federation
Duration: 11 Nov 202213 Nov 2022

Conference

Conference2022 IEEE International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON)
Period11/11/202213/11/2022

    ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Signal Processing
  • Information Systems and Management
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Health Informatics

ID: 34715615