DOI: https://doi.org/10.32515/2664-262X.2024.10(41).1.68-79
Justification of Diagnostic Parameters for a Comprehensive UAV-based Remote Diagnostic System for Overhead Power Lines
About the Authors
Oleksandr Kozlovskyi, Associate Professor, PhD in Technics (Candidate of Technics Sciences), Central Ukrainian National Technical University, Kropyvnytskyi, Ukraine , e-mail: kozlovskyioa@gmail.com, 0000-0001-6885-5994
Serhiy Rendzinyak, Professor, Doctor in Technics (Doctor of Technics Sciences), Ivan Franko National University of Lviv, Lviv, Ukraine, e-mail: serhii.y.rendziniak@edu.lpnu.ua, ORCID ID: 0000-0003-4544-4871
Abstract
The article presents the results of substantiating diagnostic parameters for a multiparametric remote monitoring system of overhead power lines based on the use of an unmanned aerial vehicle (UAV).
Significant wear of the structural elements of overhead power lines (OHL) in the IPS of Ukraine, exacerbated by the impact of climate change, leads to an increase in the number of damages. This makes proper maintenance of OHL a priority task. Existing technical diagnostic systems based UAVs are mainly aimed at solving narrow specialized tasks. Therefore, there is a need to develop more universal and comprehensive systems. The analysis of operational defects in the structural elements of OHL has shown that most of these defects manifest as visible mechanical damages, while others remain hidden. Detection of such defects is possible through remote non-destructive testing methods. Based on typical defects, a list of diagnostic parameters for a 110 kV overhead line was formulated. Considering that OHL elements have the same probability of failure, only those defects that may pose a threat to its operability in the near future were considered. Based on the selected defects and diagnostic parameters, a table of possible states of the OHL was compiled. The selection of the necessary and sufficient group of diagnostic parameters was carried out based on their average informativeness, which characterizes the degree of entropy reduction of the overhead line.
The main key aspects of the study are:
- existing technical diagnostic systems for overhead power lines based on UAVs are mainly focused on solving specialized tasks for specific power grid areas and are not universal. This limits their adaptation to different operating conditions and indicates the need for more comprehensive systems capable of addressing a wide range of power grid issues;
- the majority of defects in the structural elements of overhead power lines appear as various cracks, chips, fractures, breaks, loss of fastening elements, and corrosion, while the remaining defects are hidden, such as weakened wire connections and zero insulators. All these defects can be detected using remote non-destructive testing methods;
- given the accepted limitations, the most informative group for diagnosing the state of an overhead power line consists of seven parameters, including visual signatures of defects, temperatures of conductors and contact connections, as well as discharge activity of insulators and conductive parts
Keywords
overhead power line, operational defect, unmanned aerial vehicle, UAV, information theory, diagnosis, diagnostic parameter
Full Text:
PDF
References
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Citations
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4. Muhammad A., Shahpurwala A., Mukhopadhyay S., El-Hag A. H. Autonomous Drone-Based Powerline Insulator Inspection via Deep Learning. In: Silva M., Luís Lima J., Reis L., Sanfeliu A., Tardioli, D. (eds) Robot 2019: Fourth Iberian Robotics Conference. ROBOT 2019. Advances in Intelligent Systems and Computing. Vol. 1092. Springer, Cham. https://doi.org/10.1007/978-3-030-35990-4_5.
5. Waleed D., Mukhopadhyay D. S., Tariq U., El-Hag A. H. Drone-Based Ceramic Insulators Condition Monitoring. IEEE Transactions on Instrumentation and Measurement. 2021. Vol. 70. P. 1-12, DOI: 10.1109/TIM.2021.3078538.
6. Li Z., Zhang Y., Wu H., Suzuki S., Namiki A. et al. Design and Application of a UAV Autonomous Inspection System for High-Voltage Power Transmission Lines. Remote Sens. 2023. 15(3). 865 p. https://doi.org/10.3390/rs15030865.
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Copyright (c) 2024 Oleksandr Kozlovskyi, Serhiy Rendzinyak
Justification of Diagnostic Parameters for a Comprehensive UAV-based Remote Diagnostic System for Overhead Power Lines
About the Authors
Oleksandr Kozlovskyi, Associate Professor, PhD in Technics (Candidate of Technics Sciences), Central Ukrainian National Technical University, Kropyvnytskyi, Ukraine , e-mail: kozlovskyioa@gmail.com, 0000-0001-6885-5994
Serhiy Rendzinyak, Professor, Doctor in Technics (Doctor of Technics Sciences), Ivan Franko National University of Lviv, Lviv, Ukraine, e-mail: serhii.y.rendziniak@edu.lpnu.ua, ORCID ID: 0000-0003-4544-4871
Abstract
Keywords
Full Text:
PDFReferences
1. Plan rozvytku systemy peredachi na 2022-2031 roky [Transmission System Development Plan for 2022-2031]. Ukrenerho [in Ukrainian].
2. Hryb O. H., Karpaliuk I. T., Shvets S. V., Zakharenko N. S. (2020). Pidvyshchennia nadiinosti systemy elektropostachannia za rakhunok bezpilotnykh litalnykh aparativ [Improving the Reliability of the Power Supply System through Unmanned Aerial Vehicles]. Naukovi pratsi VNTU. № 1. P. 1-6 [in Ukrainian].
3. Guan H., Sun. X., Su Y., Hu T., Wang H. et al. UAV-lidar aids automatic intelligent powerline inspection. (2021). Int. J. Electr. Power Energy Syst. 130 p. 106987. https:/doi.org/10.1016/j.ijepes.2021.106987 [in English].
4. Muhammad A., Shahpurwala A., Mukhopadhyay S. & El-Hag A. H. (2019). Autonomous Drone-Based Powerline Insulator Inspection via Deep Learning. In: Silva M., Luís Lima J., Reis L., Sanfeliu A., Tardioli, D. (eds) Robot 2019: Fourth Iberian Robotics Conference. ROBOT 2019. Advances in Intelligent Systems and Computing. Vol. 1092. Springer, Cham. https://doi.org/10.1007/978-3-030-35990-4_5 [in English].
5. Waleed D., Mukhopadhyay D. S., Tariq U. & El-Hag A. H. (2021). Drone-Based Ceramic Insulators Condition Monitoring. IEEE Transactions on Instrumentation and Measurement. Vol. 70, pp. 1-12, DOI: 10.1109/TIM.2021.3078538 [in English].
6. Li Z., Zhang Y., Wu H., Suzuki S., Namiki A. et al. (2023). Design and Application of a UAV Autonomous Inspection System for High-Voltage Power Transmission Lines. Remote Sens. 15(3), 865. https://doi.org/10.3390/rs15030865. [in English].
7. Kozlovskyi, O., Trushakov, D., Rendzinyak, S., Korud, V. (2023). Development of a UAV-based System for Technical Diagnostics of Overhead Power Lines. 24th International Conference on Computational Problems of Electrical Engineering, CPEE 2023, DOI: 10.1109/CPEE59623.2023.10285318 [in English].
8. Pravyla ulashtuvannia elektroustanovok. (2017). [Rules for Electrical Installations]. Kharkiv: Fort. [in Ukrainian].
9. Pravyla okhorony elektrychnykh merezh [Rules for the Protection of Electrical Networks]. Elektronnyi resurs. Rezhym dostupu: https://zakon.rada.gov.ua/laws/show/209-97-%D0%BF#Text. [in Ukrainian].
10. Pravyla tekhnichnoi ekspluatatsii elektroustanovok spozhyvachiv. (2018). [Rules for the Technical Operation of Electrical Installations of Consumers]. Kharkiv: Fort [in Ukrainian].
11. SOU-N EE 20.502:2007. Povitriani linii elektroperedavannia napruhoiu 35 kV i vyshche [SOU-N EE 20.502:2007. Overhead Power Transmission Lines with a Voltage of 35 kV and Above]. Kyiv: HRIFRE [in Ukrainian].
12. Bederak Ya. S., Taradai V. I. (2020). Zabezpechennia nadiinoi roboty elektroustanovok spozhyvachiv [Ensuring Reliable Operation of Consumer Electrical Installations]. Kharkiv: Fort [in Ukrainian].
13. Horobei R., Chernov V., Udod E. (2007). Diahnostuvannia elektroobladnannia 0,4-750 kV zasobamy infrachervonoi tekhniky [Diagnostics of Electrical Equipment from 0.4 to 750 kV Using Infrared Technology] / pid zah. red. E. Udoda. Kyiv: KVITs [in Ukrainian].
14. Wang S., Lv F., Y. Liu. (2014). Estimation of discharge magnitude of composite insulator surface corona discharge based on ultraviolet imaging method. IEEE Transactions on Dielectrics and Electrical Insulation. Vol. 21. No. 4. P. 1697-1704. DOI: 10.1109/TDEI.2014.004358 [in English]
15. Sokol, Yevgen I. & Artur O. Zaporozhets, eds. (2021). Control of Overhead Power Lines with Unmanned Aerial Vehicles (UAVs). Springer International Publishing [in English]
16. Kutin, V. M., Iliukhin, M. O., Kutina M. V. (2013). Diahnostyka elektroobladnannia [Diagnostics of Electrical Equipment]. Vinnytsia: VNTU [in Ukrainian].
17. Kazak V. M., Dotsenko B. I., Kuzmin V. P., Shepeliev Yu. I. & Shevchuk D. O. (2013). Nadiinist ta diahnostyka elektroobladnannia [Reliability and Diagnostics of Electrical Equipment]. Kyiv: NAU [in Ukrainian].
18. Matrice 350 RTK. Specs: website. Retrieved from: URL: https://enterprise.dji.com/matrice-350-rtk/specs [in English].
19. Maidanyk O. O., Meleshko Ye. V., Matsui A. M., Shymko S.V. (2022). Doslidzhennia metodiv stabilizatsii video ta budovy hirostabilizovanykh pidvisiv videokamer dlia bezpilotnykh litalnykh prystroiv [Research of Video Stabilization Methods and of the Construction of Video Camera Gyro-stabilized Suspensions for Drones]. Tsentralnoukrainskyi naukovyi visnyk. Tekhnichni nauky – Central Ukrainian scientific bulletin: Technical sciences. 6(37). Pr 2. P. 26-36.
Citations
1. План розвитку системи передачі на 2022-2031 роки. Укренерго, 2021. 422 с.
2. Гриб О. Г., Карпалюк І. Т., Швець С. В., Захаренко Н. С. Підвищення надійності системи електропостачання за рахунок безпілотних літальних апаратів. Наукові праці ВНТУ. 2020. №1. С. 1-6.
3. Guan H., Sun. X., Su Y., Hu T., Wang H. et al. UAV-lidar aids automatic intelligent powerline inspection. Int. J. Electr. Power Energy Syst. 2021, 130, 106987. https:/doi.org/10.1016/j.ijepes.2021.106987.
4. Muhammad A., Shahpurwala A., Mukhopadhyay S., El-Hag A. H. Autonomous Drone-Based Powerline Insulator Inspection via Deep Learning. In: Silva M., Luís Lima J., Reis L., Sanfeliu A., Tardioli, D. (eds) Robot 2019: Fourth Iberian Robotics Conference. ROBOT 2019. Advances in Intelligent Systems and Computing. Vol. 1092. Springer, Cham. https://doi.org/10.1007/978-3-030-35990-4_5.
5. Waleed D., Mukhopadhyay D. S., Tariq U., El-Hag A. H. Drone-Based Ceramic Insulators Condition Monitoring. IEEE Transactions on Instrumentation and Measurement. 2021. Vol. 70. P. 1-12, DOI: 10.1109/TIM.2021.3078538.
6. Li Z., Zhang Y., Wu H., Suzuki S., Namiki A. et al. Design and Application of a UAV Autonomous Inspection System for High-Voltage Power Transmission Lines. Remote Sens. 2023. 15(3). 865 p. https://doi.org/10.3390/rs15030865.
7. Kozlovskyi O., Trushakov D., Rendzinyak S., Korud V. Development of a UAV-based System for Technical Diagnostics of Overhead Power Lines. 24th International Conference on Computational Problems of Electrical Engineering 2023, CPEE 2023. DOI: 10.1109/CPEE59623.2023.10285318.
8. Правила улаштування електроустановок. Х.: Форт, 2017. 760 с.
9. Правила охорони електричних мереж. Електронний ресурс. Режим доступу: https://zakon.rada.gov.ua/laws/show/209-97-%D0%BF#Text.
10. Правила технічної експлуатації електроустановок споживачів. Х.: Форт, 2018. 370 с.
11. СОУ-Н ЕЕ 20.502:2007. Повітряні лінії електропередавання напругою 35 кВ і вище. К.: ГРІФРЕ, 2007. 141 с.
12. Бедерак Я. С., Тарадай В. І. Забезпечення надійної роботи електроустановок споживачів. Х.: Форт, 2020. 170 с.
13. Горобей Р., Чернов В., Удод Е. Діагностування електрообладнання 0,4-750 кВ засобами інфрачервоної техніки / під заг. ред. Е. Удода. К.: КВІЦ, 2007. 374 с.
14. Wang S., Lv F. Liu Y. Estimation of discharge magnitude of composite insulator surface corona discharge based on ultraviolet imaging method. IEEE Transactions on Dielectrics and Electrical Insulation. 2014. Vol. 21. No. 4. P. 1697-1704. DOI: 10.1109/TDEI.2014.004358.
15. Sokol Y. I., Zaporozhets A. O., eds. Control of Overhead Power Lines with Unmanned Aerial Vehicles (UAVs). Springer International Publishing, 2021. 157 p.
16. Кутін В. М., Ілюхін М. О., Кутіна М. В. Діагностика електрообладнання. Вінниця: ВНТУ, 2013. 161 с.
17. Надійність та діагностика електрообладнання / В. М. Казак, Б. І. Доценко, В. П. Кузьмін та ін. К.: НАУ, 2013. 280 с.
18. Matrice 350 RTK. Specs: веб-сайт. URL: https://enterprise.dji.com/matrice-350-rtk/specs (дата звернення 30.08.2024).
19. Майданик О. О., Мелешко Є. В., Мацуй А. М., Шимко С. В. Дослідження методів стабілізації відео та будови гіростабілізованих підвісів відеокамер для безпілотних літальних пристроїв. Центральноукраїнський науковий вісник. Технічні науки: зб. наук. пр. Кропивницький: ЦНТУ, 2022. Вип. 6(37). Ч. 2. С. 26-36.