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Development of Portable Boiler Tube Health Evaluation System

휴대용 보일러튜브 건전성 평가시스템 개발

  • Chang Min Lee (Power Generation Laboratory, KEPCO Research Institute) ;
  • Han Sang Lee (Power Generation Laboratory, KEPCO Research Institute) ;
  • Bum Shin Kim (Power Generation Laboratory, KEPCO Research Institute)
  • 이창민 (한국전력공사 전력연구원 발전연구소) ;
  • 이한상 (한국전력공사 전력연구원 발전연구소) ;
  • 김범신 (한국전력공사 전력연구원 발전연구소)
  • Received : 2023.08.04
  • Accepted : 2023.08.28
  • Published : 2023.09.30

Abstract

Although the proportion of coal-fired power generation is decreasing, efficient operating technology is needed to continuously invest in facilities and reduce maintenance costs until it is abolished. Boilers, one of the main facilities of power plants, operate for a long time in harsh environments of high temperature and high pressure. In addition, damage due to deterioration is likely to occur depending on the fuel and tube material used. It is very important to judge soundness because damage caused by deterioration adversely affects facility operation. Previously, replication method was used to analyze the progress of deterioration. In the replication method, pre-treatment such as chemical treatment is performed on the boiler tube in the field, the area is reproduced by attaching a film, and the replicated film is determined by an expert in the laboratory with an expensive microscope. However, this method involves substantial costs and time requirements, as well as the possibility of human errors. To address these issues, we developed a mobile health assessment system in this research. Since it is detachable and takes images in real time, this system enables swift evaluations across a broad range and facilitates the assessment of preprocessing quality. In addition, it was intended to reduce existing human mistakes by developing a degradation classification algorithm using the merger cluster method.

Keywords

References

  1. Ali, M.H., Zharakhmet, T., Atykhan, M., Yerbolat, A., and Batai, S., Development of a Robot for Boiler Tube Inspection, Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics, 2018, Vol. 2, pp. 544-551.
  2. Boonyaprapasorn, A., Maneewarn, T., and Thung-Od, K., A prototype of inspection robot for water wall tubes in boiler, Proceedings of the 2014 3rd International Conference on Applied Robotics for the Power Industry. IEEE, 2014, pp. 1-6.
  3. Gonzalez, R.C. and Woods, R.E., Digital Image Processing, 2010, Third Edition, Pearson Prentice Hall, pp. 760-785.
  4. Gowatski, S., Improving boiler reliability through NDT., ASME Power Conference, 2008, pp. 137-141.
  5. Jalal, M.F., Abdul, K.S., Mohamed, S., and Anuar, A., Development of magnetic wheeled boiler tube inspection robot, Jurnal Teknologi, 2015, Vol.76, No.4, pp. 19-23. https://doi.org/10.11113/jt.v76.5478
  6. Jana, S., Non-destructive in-situ replication metallography, Journal of Materials Processing Technology, 1995, Vol. 49, No. 1-2, pp. 85-114. https://doi.org/10.1016/0924-0136(94)01314-Q
  7. Johnston, B., Jones, A., and Kruger, C., Applied Unsupervised Learning with Python: Discover hidden patterns and relationships in unstructured data with Python, Packt Publishing Ltd, 2019.
  8. Kim, J.B., Oh, S.B., Park, J.K., Kim, C.B., and Yun, D.S., Thermal Degradation Analysis of Platen Super Heater Tubes in Thermal Power Plants using a Nonlinear Ultrasonic Technique, Journal of the Korean Society for Nondestructive Testing, 2022, Vol. 42, No. 3 pp. 216-221. https://doi.org/10.7779/JKSNT.2022.42.3.216
  9. Kim, M.Y., Chu, D.J., Lee, Y.K., Shim, J.H., and Jung, W.S., Residual lifetime assessment of cold-reheater pipe in coal-fired power plant through accelerated degradation test, Reliability Engineering & System Safety, 2019, Vol. 188, pp. 330-335. https://doi.org/10.1016/j.ress.2019.03.043
  10. Krasula, L., Fliegel, K., Le Callet, P., and Klima, M. , Using full-reference image quality metrics for automatic image sharpening. In Optics, Photonics, and Digital Technologies for Multimedia Applications III, 2014, Vol. 9138, pp. 54-64.
  11. Ku, D.H., Yoo, H.S., and Moon, S.J., Evaluation of the High Temperature Degradation of the Rotor of a 500 MW Tandem Steam Turbine, Plant Journal, 2014, Vol. 10, No. 1, pp. 40-46.
  12. Lara, C., Villamil, J., Abrahao, A., Aravelli, A., Daldegan, G., Sarker, S., Martinez, D., McDaniel, D., Development of an Innovative Inspection Tool for Superheater Tubes in Fossil Fuel Power Plants, Materials Evaluation, 2021, Vol.79, No. 7, pp. 728-738. https://doi.org/10.32548/2021.me-04212
  13. Minichino, J. and Howse, J., Learning OpenCV 3 computer vision with python, second ed., Packt Publishing Ltd, 2015, pp. 45-59
  14. Park, J.H., Seo, J.S., and Jung, G.J., Influence of Tensile Stress of Boiler Tube Materials on Metal Magnetic Memory Signal Characteristics, Journal of the Korean Society for Nondestructive Testing, 2022, Vol. 42, No. 2, pp. 120-128. https://doi.org/10.7779/JKSNT.2022.42.2.120
  15. Sahari K.S.M, et al., Development of robotic boiler header inspection device, The 6th International Conference on Soft Computing and Intelligent Systems, and The 13th International Symposium on Advanced Intelligence Systems, IEEE, 2012, pp. 769-773.
  16. Salonen, J. and Auerkari, P., Microstructural degradation of boiler tube steels under long term exposure to high temperature, VTT Manufacturing Technology, 1996.
  17. Song, X.C., Wu, X.J., and Kang, Y.H., An inspection robot for boiler tube using magnetic flux leakage and ultrasonic methods, Insight-Non-Destructive Testing and Condition Monitoring, 2004, Vol. 46, No.5, pp. 275-278. https://doi.org/10.1784/insi.46.5.275.55566
  18. Standard Practice for Production and Evaluation of Field Metallographic Replicas, ASTM International Committee, E1351-01, 2012.