PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Innovative acoustic emission method for monitoring the quality and integrity of ferritic steel gas pipelines

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This article presents a comprehensive improvement in the experimental analysis of cracking processes in smooth and sharp V-notched samples taken from gas transport pipelines, utilizing the acoustic emission (AE) method. The research aimed to establish a robust correlation between the failure mechanisms of uniaxially tensile samples and the distinct characteristics of AE signals for enhanced quality management in pipeline integrity. The study encompassed materials from two different straight pipe sections, encompassing both long-term used materials and new, unused materials. Through the application of the k-means grouping method to AE signal analysis, we achieved the identification of AE signal parameters characteristic of various stages of the material destruction process. This advancement introduces a significant improvement in monitoring and managing the operational safety of pipeline networks, offering a methodology that leverages advanced acoustic emission signal analysis. The outcomes present significant implications for the pipeline industry by proposing methods to enhance safety systems and more effectively manage the integrity and quality of gas infrastructure.
Rocznik
Strony
233--240
Opis fizyczny
Bibliogr 26 poz., rys., tab.
Twórcy
  • Faculty of Civil Engineering and Architecture, Kielce University of Technology, Av. 1000-an. of Polish State 7, 25-314 Kielce, Poland
  • Faculty of Civil Engineering, Czestochowa University of Technology, 69 Dabrowskiego street, 42-201 Czestochowa
autor
  • Faculty of Mechatronics and Mechanical Engineering, Kielce University of Technology, Av. 1000-an. of Polish State 7, 25-314 Kielce
  • Faculty of Civil Engineering and Architecture, Kielce University of Technology, Av. 1000-an. of Polish State 7, 25-314 Kielce, Poland
  • Faculty of Mechatronics and Mechanical Engineering, Kielce University of Technology, Av. 1000-an. of Polish State 7, 25-314 Kielce
  • Faculty of Civil Engineering and Architecture, Kielce University of Technology, Av. 1000-an. of Polish State 7, 25-314 Kielce, Poland
autor
  • Faculty of Mechatronics and Mechanical Engineering, Kielce University of Technology, Av. 1000-an. of Polish State 7, 25-314 Kielce
Bibliografia
  • 1. Aljaroudi, A., Khan, F., Akinturk, A., Haddara, M., Thodi, P., 2015. Risk assessment of offshore crude oil pipeline failure. Journal of Loss Prevention in the Process Industries, 37, 101-109. DOI: 10.1016/j.jlp.2015.07.004
  • 2. Alzyod, H., Ficzere, P., 2023. Correlation Between Printing Parameters and Residual Stress in Additive Manufacturing: A Numerical Simulation Approach. Production Engineering Archives, 29, 279-287.
  • 3. Amyotte, P.R., Berger, S., Edwards, D.W., Gupta, J.P., Hendershot, D.C., Khan, F.I., Mannan, M.S., Willey, R.J., 2016. Why major accidents are still occurring. Current Opinion in Chemical Engineering. Biotechnology and bioprocess engineering / Process systems engineering, 14, 1-8. DOI: 10.1016/j.coche.2016.07.003
  • 4. ASTM E8 / E8M-16ae1, 2016. ASTM E8 / E8M-16ae1, Standard Test Meth-ods for Tension Testing of Metallic Materials. ASTM International, West Conshohocken.
  • 5. Avelino, Á.M., de Paiva, J.Á., da Silva, R.E.F., de Araujo, G.J.M., de Azevedo, F.M., de O. Quintaes, F., Maitelli, A.L., Neto, A.D.D., Salazar, A.O., 2009. Real time leak detection system applied to oil pipelines using sonic technology and neural networks, in: 2009 35th Annual Conference of IEEE Industrial Electronics. Presented at the 2009 35th Annual Conference of IEEE Industrial Electronics, pp. 2109-2114. DOI: 10.1109/IECON.2009.5415324
  • 6. Benhamena, A., Fatima, B., Foudil, K., Baltach, A., Chaouch, M.I., 2023. Nu-merical Analysis of Fracture Behavior of Functionally Graded Materials using 3D-XFEM. Advances in Materials Science, 23, 33-46.
  • 7. Bokůvka, O., Jambor, M., Trško, L., Nový, F., Lisiecka, B., 2018. Fatigue lifetime of 20MnV6 steel with holes manufactured by various methods. Production Engineering Archives, 19, 3-5. DOI: 10.30657/pea. 2018.19.01
  • 8. Cataldo, A., Cannazza, G., De Benedetto, E., Giaquinto, N., 2012. A New Method for Detecting Leaks in Underground Water Pipelines. IEEE Sensors Journal, 12, 1660-1667. DOI: 10.1109/JSEN.2011.2176484
  • 9. Cui, X., Yan, Y., Ma, Y., Ma, L., Han, X., 2016. Localization of CO2 leakage from transportation pipelines through low frequency acoustic emission detection. Sensors and Actuators A: Physical, 237, 107-118. DOI: 10.1016/j.sna. 2015.11.029
  • 10. Kubicki, K., 2023. Technical and economic aspects of load-bearing welded joints in reinforcing steel. Construction of Optimized Energy Potential, 12(1), 228-235. DOI: 10.17512/bozpe.2023.12.25
  • 11. Feng, J., Li, F., Lu, S., Liu, J., Ma, D., 2017. Injurious or Noninjurious Defect Identification From MFL Images in Pipeline Inspection Using Convolutional Neural Network. IEEE Transactions on Instrumentation and Meas-urement, 66, 1883-1892. DOI: 10.1109/TIM.2017.2673024
  • 12. Gumen, O., Ujma, A., Kruzhkova, M., 2021. Research into the process of spraying complex titanium and zirconium nitride on structural steel and reaction times relating to the final finish and quality obtained. Construc-tion of Optimized Energy Potential, 10, 71-76. DOI: 10.17512/bozpe.2021.1.07
  • 13. Hu, Z., Tariq, S., Zayed, T., 2021. A comprehensive review of acoustic based leak localization method in pressurized pipelines. Mechanical Systems and Signal Processing, 161, 107994. DOI: 10.1016/j.ymssp.2021.107994
  • 14. Jin, H., Zhang, L., Liang, W., Ding, Q., 2014. Integrated leakage detection and localization model for gas pipelines based on the acoustic wave method. Journal of Loss Prevention in the Process Industries, 27, 74-88. DOI: 10.1016/j.jlp.2013.11.006
  • 15. Li, J., Zheng, Q., Qian, Z., Yang, X., 2019. A novel location algorithm for pipeline leakage based on the attenuation of negative pressure wave. Pro-cess Safety and Environmental Protection, 123, 309-316. DOI: 10.1016/j.psep. 2019.01.010
  • 16. Li, Z., Zhang, H., Tan, D., Chen, X., Lei, H., 2017. A novel acoustic emission detection module for leakage recognition in a gas pipeline valve. Process Safety and Environmental Protection, 105, 32-40. DOI: 10.1016/j.psep. 2016.10.005
  • 17. Liu, C., Li, Y., Meng, L., Wang, W., Zhang, F., 2014. Study on leakacoustics generation mechanism for natural gas pipelines. Journal of Loss Preven-tion in the Process Industries, 32, 174-181. DOI: 10.1016/j.jlp. 2014.08.010
  • 18. PN-EN ISO 6892-1:2020-05, 2019. PN-EN ISO 6892-1:2020-05, Metallic materials - Tensile testing - Part 1: Method of test at room temperature. International Organization for Standardization, Geneva.
  • 19. Sun, J., Xiao, Q., Wen, J., Zhang, Y., 2016. Natural gas pipeline leak aperture identification and location based on local mean decomposition analysis. Measurement, 79, 147-157. DOI: 10.1016/j.measurement.2015.10.015
  • 20. Świt, G., Dzioba, I., Adamczak-Bugno, A., Krampikowska, A., 2022. Identification of the Fracture Process in Gas Pipeline Steel Based on the Analysis of AE Signals. Materials, 15, 2659. DOI: 10.3390/ma15072659
  • 21. Świt, G., Dzioba, I., Ulewicz, M., Lipiec, S., Adamczak-Bugno, A., Krampi-kowska, A., 2023. Experimental numerical analysis of the fracture process in smooth and notched V specimens. Production Engineering Archives, 29, 444–451. DOI: 10.30657/pea.2023.29.49
  • 22. Wang, F., Lin, W., Liu, Z., Wu, S., Qiu, X., 2017. Pipeline Leak Detection by Using Time-Domain Statistical Features. IEEE Sensors Journal, 17, 6431–6442. DOI: 10.1109/JSEN.2017.2740220
  • 23. Wang, L., Narasimman, S.C., Reddy Ravula, S., Ukil, A., 2017. Water Ingress Detection in Low Pressure Gas Pipelines Using Distributed Temperature Sensing System. IEEE Sensors Journal, 17, 3165–3173. DOI: 10.1109/JSEN.2017.2686982
  • 24. Xiao, R., Hu, Q., Li, J., 2019. Leak detection of gas pipelines using acoustic signals based on wavelet transform and Support Vector Machine. Measurement, 146, 479–489. DOI: 10.1016/j.measurement.2019.06.050
  • 25. Xu, Q., Zhang, L., Liang, W., 2013. Acoustic detection technology for gas pipeline leakage. Process Safety and Environmental Protection, 91, 253-261. DOI: 10.1016/j.psep.2012.05.012
  • 26. Zadkarami, M., Shahbazian, M., Salahshoor, K., 2017. Pipeline leak diagnosis based on wavelet and statistical features using Dempster-Shafer classifier fusion technique. Process Safety and Environmental Protection, 105, 156-163. DOI: 10.1016/j.psep.2016.11.002
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-2260b031-c981-4c30-99ce-933470566f49
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.