The article presents the successful project of the BDTR-500 robot, designed for diagnosing cracks in pipes with a silicate-enameled coating. Key achievements of the system include the use of GPS navigation and positioning methods that ensure precise location determination and rapid identification of emergency zones. New algorithms based on artificial intelligence and machine learning facilitate autonomous robot movement and high-quality data processing. High-megapixel cameras with a smart lighting system allow for effective visualization of defects, while the intelligent energy management system increases the operational time in autonomous mode. Real-time data processing ensures rapid localization and elimination of damages, while built-in sensors enhance image stability on uneven surfaces. The robot can detect cracks as small as 0.1 meters. The project results confirm the high efficiency of the BDTR-500 in diagnostics, opening new opportunities for the application of technologies in monitoring the condition of pipelines and in other challenging operating environments.
Ellada N. Ibrahimova – Candidate of Technical Sciences, Associate Professor at the Department of Computer Engineering, Azerbaijan State Oil and Industry University, Baku, Republic of Azerbaijan
Mehebbet A. Khudaverdieva – Candidate of Technical Sciences, director of “?nstrumentation Engineering” Laboratory, Azerbaijan State Oil and Industry University, Baku, Republic of Azerbaijan
Almaz A. Aliyeva – Candidate of Technical Sciences, Dean of the Faculty of Engineering, Mingechevir State University, Mingechevir, Republic of Azerbaijan
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DOI: 10.14489/glc.2025.03.pp.052-058
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