Skip to main content

System for Monitoring the Technical State of Heating Networks Based on UAVs

  • Conference paper
  • First Online:
Advances in Intelligent Systems and Computing IV (CSIT 2019)

Abstract

The article presents the causes of defects in pipelines of the centralized heat supply. The possibilities of thermal aerial photography for detecting different types of defects on pipelines in a functioning state are explored. The characteristics and capabilities of the proposed set of devices for monitoring thermal losses in pipelines based on quadrocopters are considered. A method for monitoring the technical condition of pipelines using UAVs is presented. A method for processing thermal images for highlighting anomalous areas is presented. The created hardware-software complex for monitoring the state of trunk pipelines of heat networks based on the UAV is considered. Experiments on the use of UAVs for monitoring heating networks have been conducted. The obtained experimental results, confirming the possibility of differences in the technical condition of pipelines.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Babak, S., Babak, V., Zaporozhets, A., Sverdlova, A.: Method of statistical spline functions for solving problems of data approximation and prediction of object state. In: CEUR Workshop Proceedings, vol. 2353, pp. 810–821 (2019). http://ceur-ws.org/Vol-2353/paper64.pdf

  2. Babak, V.P.: Hardware-Software for Monitoring the Objects of Generation Transportation and Consumption of Thermal Energy. Institute of Engineering Thermophysics of NAS of Ukraine, Kyiv (2016)

    Google Scholar 

  3. Prudyus, I., Shkliarskiy, V., Turkinov, G., Storozh, V., Kril, Y.: Analysis and choice of methods of monitoring technical condition of the heating systems. In: International Conference on “Modern Problems of Radio Engineering, Telecommunications and Computer Science (TCSET)”, p. 154 (2008)

    Google Scholar 

  4. Johnson, B., Barth, R., House, P., Kuntscher, J.: Controlling pipe and equipment operating temperatures with trace heating systems. In: PCIC Europe, pp. 1–10 (2013)

    Google Scholar 

  5. Friman, O., Follo, P., Ahlberg, J., Sjökvist, S.: Methods for large-scale monitoring heating systems using airborne thermography. IEEE Trans. Geosci. Remote Sens. 51(8), 5175–5182 (2014)

    Article  Google Scholar 

  6. Shang-bin, J., Le, F., Peng-yue, W., Lei, Q., Yong-ze, J., Qian-kun, S.: Assessment and prediction of leakage degree of expansion joints in underground network heating pipe network based on LS-SVM and ARIMA model. In: 13th IEEE Conference on Industrial Electronics and Applications (ICIEA), pp. 1697–1702 (2018)

    Google Scholar 

  7. Jiao, S.-B., Fan, L., Wu, P.-Y., Qiao, L., Wang, Y., Xie, G.: Assessment of leakage degree of underground heating primary pipe network based on chaotic simulated annealing neural network. In: Chinese Automation Congress (CAC), pp. 5895–5900 (2017)

    Google Scholar 

  8. Babak, V.P., Zaporozhets, A.A., Kovtun, S.I., Sergienko, R.V.: Diagnosing methods analysis of bulk heating systems technical condition. Sci. Heritage 1(14), 59–65 (2017)

    Google Scholar 

  9. Teng, Q., Wang, W.: The optimization and management research for central heating system. In: IEEE Workshop on Advanced Research and Technology in Industry Applications (WARTIA), pp. 175–177 (2014)

    Google Scholar 

  10. Fukuoka, M., Tang, L.: Wireless pipe inspection control system. In: The 5th International Conference on Automation, Robotics and Applications, pp. 497–502 (2011)

    Google Scholar 

  11. Babak, V., Zaporozhets, A., Kovtun, S., Serhiienko, R.: Methods and means of heat losses monitoring for heat pipelines. Int. J. “NDT Days” 1(2), 213–221 (2018)

    Google Scholar 

  12. Zaporozhets, A.A., Eremenko, V.S., Serhiienko, R.V., Ivanov, S.A.: Development of an intelligent system for diagnosing the technical condition of the heat power equipment. In: IEEE 13th International Scientific and Technical Conference on Computer Sciences and Information Technologies (CSIT), pp. 48–51 (2018)

    Google Scholar 

  13. Zaporozhets, A., Eremenko, V., Serhiienko, R., Ivanov, S.: Methods and hardware for diagnosing thermal power equipment based on smart grid technology. In: Shakhovska, N., Medykovskyy, M. (eds.) Advances in Intelligent Systems and Computing III, vol. 871, pp. 476–489. Springer, Cham (2019)

    Google Scholar 

  14. Eremenko, V., Zaporozhets, A., Isaenko, V., Babikova, K.: Application of Wavelet Transform for Determining Diagnostic Signs. In: CEUR Workshop Proceedings, vol. 2387, pp. 202–214 (2019). http://ceur-ws.org/Vol-2387/20190202.pdf

  15. Kosar, O., Shakhovska, N. An overview of denoising methods for different types of noises present on graphic images. In: Shakhovska, N., Medykovskyy, M. (eds.) Advances in Intelligent Systems and Computing III, vol. 871, pp. 38–47. Springer, Cham (2019)

    Google Scholar 

  16. Gauci, J., Falzon, O., Formosa, C., Gatt, A., Ellul, C., Mizzi, S., Mizzi, A., Delia, C.S., Cassar, K., Chockalingam, N., Camilleri, K.P.: Automated region extraction from thermal images for peripheral vascular disease monitoring. J. Healthc. Eng. 5092064 (2018)

    Google Scholar 

  17. Duarte, A., Carrao, L., Espanha, M., Viana, T., Freitas, D., Bartolo, P., Faria, P., Almeida, H.A.: Segmentation algorithms for thermal images. Procedia Technol. 16, 1560–1569 (2014)

    Article  Google Scholar 

  18. Chen, X., Liu, L., Song, J., Li, J., Zhang, Z.: Corner detection and matching for infrared image based on double ring mask and adaptive SUSAN algorithm. Opt. Quant. Electron. 50, 194 (2018)

    Article  Google Scholar 

  19. Wang, X., Song, H., Cui, H.: Pedestrian abnormal event detection based on multi-feature fusion in traffic video. Optik 154, 22–32 (2018)

    Article  Google Scholar 

  20. Loginov, I.D.: Processing and segmentation of thermal images. Young Sci. 13(147), 62–71 (2017)

    Google Scholar 

  21. Babak, V.P., Mokiychuk, V., Zaporozhets, A., Redko, O.: Improving the efficiency of fuel combustion with regard to the uncertainty of measuring oxygen concentration. Eastern-Eur. J. Enterp. Technol. 6(8(84)), 54–59 (2016)

    Article  Google Scholar 

  22. Zaporozhets, A.O., Redko, O.O., Babak, V.P., Eremenko, V.S., Mokiychuk, V.M.: Method of indirect measurement of oxygen concentration in the air. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu 5, 105–114 (2018)

    Article  Google Scholar 

  23. Devitt, D., Morozov, R., Medvedev, M., Shapoval, I., Konovalov, G.: Implementation of the hybrid technology for quadcopter motion control in a complex non-deterministic environment. In: 18th International Conference on Control, Automation and Systems (ICCAS), pp. 451–456 (2018)

    Google Scholar 

  24. Talha, M., Asghar, F., Rohan, A., Rabah, M., Kim, S.H.: Fuzzy logic-based robust and autonomous safe landing for UAV quadcopter. Arab. J. Sci. Eng. 44(3), 2627–2639 (2018)

    Article  Google Scholar 

  25. Zaporozhets, A.: Development of software for fuel combustion control system based on frequency regulator. In: CEUR Workshop Proceedings, vol. 2387, pp. 223–230 (2019). http://ceur-ws.org/Vol-2387/20190223.pdf

  26. Zaporozhets, A.: Analysis of control system of fuel combustion in boilers with oxygen sensor. Periodica Polytechnica Mech. Eng. (2019). https://doi.org/10.3311/ppme.12572

  27. Gomez, C., Green, D.R.: Small unmanned airborne systems to support oil and gas pipeline monitoring and mapping. Arab. J. Geosci. 10, 202 (2017). https://doi.org/10.1007/s12517-017-2989-x

    Article  Google Scholar 

  28. Allred, B., Eash, N., Freeland, R., Martinez, L., Wishart, D.: Effective and efficient agricultural drainage pipe mapping with UAS thermal infrared imagery: a case study. Agric. Water Manag. 197, 132–137 (2018). https://doi.org/10.1016/j.agwat.2017.11.011

    Article  Google Scholar 

  29. Zaporozhets A., Kovtun S., Dekusha, O.: Determination of the technical condition of heating networks based on the processing of thermal imaging. In: Proceedings of International Scientific Conference Computer Sciences and Information Technologies (CSIT-2019), vol. 2, pp. 5–8 (2019)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Artur Zaporozhets .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Zaporozhets, A., Kovtun, S., Dekusha, O. (2020). System for Monitoring the Technical State of Heating Networks Based on UAVs. In: Shakhovska, N., Medykovskyy, M.O. (eds) Advances in Intelligent Systems and Computing IV. CSIT 2019. Advances in Intelligent Systems and Computing, vol 1080. Springer, Cham. https://doi.org/10.1007/978-3-030-33695-0_61

Download citation

Publish with us

Policies and ethics