ISSN (print) 1995-2732
ISSN (online) 2412-9003

 

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DOI: 10.18503/1995-2732-2022-20-1-50-60

Narkevich M.Yu., Logunova O.S., Kornienko V.D., Kalitaev A.N., Surovtsov M.M., Luganskaya D.A., Chernysheva A.S. An Intelligent Decision Support System for Assessing the Quality of Buildings and Structures at Hazardous Industrial Facilities: Determining the Trajectory of the Unmanned Aircraft

Abstract

Problem Statement (Relevance). Prevention of emergency situations and destruction of buildings and structures at hazardous production facilities is a challenge for continuous monitoring of such facilities and the development of criteria for assessing their quality. Currently, over 75% of hazardous industrial facilities have reached the end of their service life, but continue to be operated in a working mode. At the same time, traditional methods and techniques of inspection and evaluation of buildings and structures remain widespread in the presence of new technologies. Methods used. The authors propose a new tool for obtaining information about the condition of the surface of the enclosing structures of buildings and facilities at an industrial enterprise. A main tool is an unmanned aerial vehicle, which allows you to get information about the condition of facilities in hard-to-reach places. The use of such unmanned aerial vehicle required: the introduction of the concept of a "useful" survey area, the development of flight paths, pilot tests and the determination of qualitative and quantitative indicators to assess the condition of the surface of the building's enclosing structures. Originality. The algorithm for designing the flight path of the unmanned aerial vehicle differs from the previously known ones because of a "useful" area for the study of buildings or structures and excludes areas inaccessible or uninformative for observation due to vegetation, closely spaced structural elements, as well as design features of enclosing structures. Result. The authors have studied how the distance between the quadcopter and the facility under study depend on the "useful" area for the study based on analytical and experimental information. Practical Relevance. Depending on the distance to the observed point, an expert receives information about the quality of the surface condition of the facility. The most complete information is provided for the expert and further automated processing only at a minimum distance from the point of study to the camera of the unmanned aerial vehicle. The outlook for the development of the research is to adapt the described methods and techniques used in laboratory conditions to the images obtained during the pilot experiments, to the assessment of a technical condition of buildings and structures of an industrial enterprise.

Keywords

assessment of the quality of buildings and structures, hazardous production facility, inspection of buildings and structures, unmanned aerial vehicle, trajectory, trajectory design technique, distortion effect.

For citation

Narkevich M.Yu., Logunova O.S., Kornienko V.D., Kalitaev A.N., Surovtsov M.M., Luganskaya D.A., Chernysheva A.S. An Intelligent Decision Support System for Assessing the Quality of Buildings and Structures at Hazardous Industrial Facilities: Determining the Trajectory of the Unmanned Aircraft. Vestnik Magnitogorskogo Gosudarstvennogo Tekhnicheskogo Universiteta im. G.I. Nosova [Vestnik of Nosov Magnitogorsk State Technical University]. 2022, vol. 20, no. 1, pp. 50–60. https://doi.org/10.18503/1995-2732-2022-20-1-50-60

Mikhail Yu. Narkevich – PhD (Eng.), Associate Professor of the Department of Design of Buildings and Building Structures, Nosov Magnitogorsk State Technical University, Magnitogorsk, Russia. Email: This email address is being protected from spambots. You need JavaScript enabled to view it.. ORCID 0000-0001-6608-8293

Oksana S. Logunova – DrSc (Eng.), Professor, Director of the Institute of Construction, Architecture and Art, Nosov Magnitogorsk State Technical University, Magnitogorsk, Russia. Email: This email address is being protected from spambots. You need JavaScript enabled to view it.. ORCID 0000-0002-7006-8639

Vladimir D. Kornienko – Category 1 Expert in Industrial Safety of Buildings and Structures, Lead Engineer in Industrial Safety Examination of the Research Institute of Industrial Safety, Nosov Magnitogorsk State Technical University, Magnitogorsk, Russia. Email: This email address is being protected from spambots. You need JavaScript enabled to view it.. ORCID 0000-0002-0637-5765

Alexander N. Kalitaev – PhD (Eng.), Associate Professor of the Department of Computer Engineering and Programming, Nosov Magnitogorsk State Technical University, Magnitogorsk, Russia. Email: This email address is being protected from spambots. You need JavaScript enabled to view it.. ORCID 0000-0002-5984-967X

Maksim M. Surovtsov – PhD (Eng.), Head of the Department of Property Management and Engineering Systems, Nosov Magnitogorsk State Technical University, Magnitogorsk, Russia. Email: This email address is being protected from spambots. You need JavaScript enabled to view it.. ORCID 0000-0003-3871-7755

Darya A. Luganskaya – student, Department of Business Informatics and Information Technologies, Nosov Magnitogorsk State Technical University, Magnitogorsk, Russia. Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

Alexandra S. Chernysheva – Master's Student, Department of Design of Buildings and Building Structures, Nosov Magnitogorsk State Technical University, Magnitogorsk, Russia. Email: This email address is being protected from spambots. You need JavaScript enabled to view it.

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