DOI QR코드

DOI QR Code

Detection of tube defect using the autoregressive algorithm

  • Halim, Zakiah A. (Faculty of Mechanical Engineering, Universiti Teknikal Malaysia Melaka) ;
  • Jamaludin, Nordin (Department of Mechanical Engineering & Materials, Faculty of Engineering and Built, Universiti Kebangsaan Malaysia) ;
  • Junaidi, Syarif (Department of Mechanical Engineering & Materials, Faculty of Engineering and Built, Universiti Kebangsaan Malaysia) ;
  • Yusainee, Syed (Faculty of Applied Science, Universiti Teknologi MARA)
  • 투고 : 2014.03.27
  • 심사 : 2014.12.29
  • 발행 : 2015.07.25

초록

Easy detection and evaluation of defect in the tube structure is a continuous problem and remains a significant demand in tube inspection technologies. This study is aimed to automate defect detection using the pattern recognition approach based on the classification of high frequency stress wave signals. The stress wave signals from vibrational impact excitation on several tube conditions were captured to identify the defect in ASTM A179 seamless steel tubes. The variation in stress wave propagation was captured by a high frequency sensor. Stress wave signals from four tubes with artificial defects of different depths and one reference tube were classified using the autoregressive (AR) algorithm. The results were demonstrated using a dendrogram. The preliminary research revealed the natural arrangement of stress wave signals were grouped into two clusters. The stress wave signals from the healthy tube were grouped together in one cluster and the signals from the defective tubes were classified in another cluster. This approach was effective in separating different stress wave signals and allowed quicker and easier defect identification and interpretation in steel tubes.

키워드

참고문헌

  1. Allahkaram, S.R., Zakersafaee, P. and Haghgoo, S.A.M. (2011), "Failure analysis of heat exchanger tubes of four gas coolers", Eng. Fail. Anal., 18(3), 1108-1114. https://doi.org/10.1016/j.engfailanal.2010.11.015
  2. Antaki, G.A. (2005), Piping and Pipeline Engineering-Design, Construction, Maintenance, Integrity, and Repair, Marcel Dekker, Inc., New York, NY, USA.
  3. Atamturktur, S., Bornn, L. and Hemez, F. (2011), "Vibration characteristics of vaulted masonry monuments undergoing differential support settlement", Eng. Struct., 33(9), 2472-2484. https://doi.org/10.1016/j.engstruct.2011.04.020
  4. Baxter, M.G., Pullin, R., Holford, K.M. and Evans, S.L. (2007), "Delta T source location for acoustic emission", Mech. Syst. Signal Process., 21(3), 1512-1520. https://doi.org/10.1016/j.ymssp.2006.05.003
  5. Birchall, M. (2007), "Internal ultrasonic pipe & tube inspection-IRIS", IV Conferencia Panamericana de END, Bueno Aires, Argentina, October.
  6. Birring, A.S. (1999), "Selection of NDT techniques for inspection of heat exchanger tubing", ASNT International Conference on Petroleum Industry Inspection, Houston, TX, USA, June.
  7. Broersen, P.M.T. (2006), Automatic Autocorrelation and Spectral Analysis, Springer-Verlag, London, United Kingdom.
  8. Bulloch, J.H., Callagy, A.G., Scully, S. and Greene, A. (2009), "A failure analysis and remnant life assessment of boiler evaporator tubes in two 250MW boilers", Eng. Fail. Anal., 16(3), 775-793. https://doi.org/10.1016/j.engfailanal.2008.06.020
  9. Carino, N.J. (2013), "Training: Often the missing link in using NDT methods", Construct. Build. Mater., 38, 1316-1329. https://doi.org/10.1016/j.conbuildmat.2011.03.060
  10. Chen, X., He, Z. and Xiang, J. (2005), "Experiments on crack identification in cantilever beams", Experim. Mech., 45(3), 295-300. https://doi.org/10.1007/BF02427954
  11. Cicero, S., Lacalle, R., Cicero, R. and Garcia, J. (2010), "Failure analysis of a steam generator superheater drain tube used in a dump", Eng. Fail. Anal., 17(1), 301-312. https://doi.org/10.1016/j.engfailanal.2009.06.012
  12. Da Silva, J.J., Lima, A.M.N., Neff, F.H. and Neto, J.S. (2009), "Non-invasive fast detection of internal fouling layers in tubes and ducts by acoustic vibration analysis", IEEE Trans. Instrument. Measure., 58(1), 108-114. https://doi.org/10.1109/TIM.2008.927206
  13. Da Silva, R.R., Soares, S.D., Caloba, L.P., Siqueira, M.H.S. and Rebello, J.M.A. (2006), "Detection of the propagation of defects in pressurised pipes by means of the acoustic emission technique using artificial neural networks", Insight-Non-Destructive Test. Condition Monit., 48(1), 45-51. https://doi.org/10.1784/insi.2006.48.1.45
  14. Elforjani, M. and Mba, D. (2010), "Accelerated natural fault diagnosis in slow speed bearings with acoustic emission", Eng. Fract. Mech., 77(1), 112-127. https://doi.org/10.1016/j.engfracmech.2009.09.016
  15. Gao, Y., Brennan, M.J., Joseph, P.F., Muggleton, J.M. and Hunaidi, O. (2005), "On the selection of acoustic/vibration sensors for leak detection in plastic water pipes", J. Sound Vib., 283(3-5), 927-941. https://doi.org/10.1016/j.jsv.2004.05.004
  16. Godin, N, Huguet, S., Gaertner, R. and Salmon, L. (2004), "Clustering of acoustic emission signals collected during tensile tests on unidirectional glass/polyester composite using supervised and unsupervised classifiers", NDT & E International, 37 (4), 253-264. https://doi.org/10.1016/j.ndteint.2003.09.010
  17. Gotoh, Y. and Takahashi, N. (2007), "Three-dimensional FEM analysis of electromagnetic inspection of outer side defects on steel tube using inner coil", IEEE Trans. Magn., 43(4), 1733-1736. https://doi.org/10.1109/TMAG.2007.892507
  18. Grad, L., Grum, J., Polajnar, I. and Slabe, J.M. (2004), "Feasibility study of acoustic signals for on-line monitoring in short circuit gas metal arc welding", Int. J. Mach. Tool. Manuf., 44 (5), 555-561. https://doi.org/10.1016/j.ijmachtools.2003.10.016
  19. Hall, L.D. and Mba, D. (2004), "Acoustic emissions diagnosis of rotor-stator rubs using the KS statistic", Mech. Syst. Signal Process., 18 (4), 849-868. https://doi.org/10.1016/S0888-3270(03)00050-5
  20. Haritos, N. and Owen, J.S. (2004), "The use of vibration data for damage detection in bridges: a comparison of system identification and pattern recognition approaches", Struct. Health Monitor., 3(2), 141-163. https://doi.org/10.1177/1475921704042698
  21. Jamaludin, N. (2000), "Monitoring low speed rolling element bearing using stress waves technique", Ph.D. Dissertation; Cranfield University, Bedford, UK.
  22. Jamaludin, N. and Mba, D. (2002a), "Monitoring extremely slow rolling element bearings: Part I", NDT & E International, 35(6), 349-358. https://doi.org/10.1016/S0963-8695(02)00005-1
  23. Jamaludin, N. and Mba, D. (2002b), "Monitoring extremely slow rolling element bearings: Part II", NDT & E International, 35(6), 359-366. https://doi.org/10.1016/S0963-8695(02)00006-3
  24. Lee, T.H., Choi, I.H. and Jhang, K.Y. (2008), "Single-mode guided wave technique using ring-arrayed laser beam for thin-tube inspection", NDT & E International, 41(8), 632-637. https://doi.org/10.1016/j.ndteint.2008.03.012
  25. Mahjoob, M.J., Shahsavari, A. and Marzban, A. (2007), "A vibration-based damage detection method for pipes conveying fluid", Proceedings of the 48th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, Hawaii, USA, April.
  26. Ryu, K., Son, D., Park, D. and Jung, J. (2009), "Reactance change at defect in Inconel tube with nickel sleeving", IEEE Trans. Magn., 45(6), 2733-2735. https://doi.org/10.1109/TMAG.2009.2020540
  27. Sansalone, M. (1997), "Impact-echo: The complete story", ACI Struct. J., 94(6), 777-786.
  28. Sansalone, M. and Streett, W.B. (1997), Impact-echo: Nondestructive Evaluation of Concrete and Masonry, Bullbrier Press, Ithaca, NY, USA.
  29. Schubert, F., Wiggenhauser, H. and Lausch, R. (2004), "On the accuracy of thickness measurements in impact-echo testing of finite concrete specimens-numerical and experimental results", Ultrasonics, 42(1-9), 897-901. https://doi.org/10.1016/j.ultras.2004.01.076
  30. Shehadeh, M.F., Abdou, W., Steel, J.A. and Reuben, R.L. (2008), "Aspects of acoustic emission attenuation in steel pipes subject to different internal and external environments", Proceedings of the Institution of Mechanical Engineers, Part E: J. Process Mech. Eng., 222(1), 41-54. https://doi.org/10.1243/09544089JPME143
  31. Thanagasundram, S. and Schlindwein, F.S. (2006a), "Autoregressive based diagnostics scheme for detection of bearing faults", Proceedings of ISMA, Belgium, September.
  32. Thanagasundram, S. and Schlindwein, F.S. (2006b), "Autoregressive order selection for rotating machinery", Int. J. Acoust. Vib., 11(3), 1-11.
  33. Wilson, J.W. and Tian, G.Y. (2007), "Pulsed electromagnetic methods for defect detection and characterisation", NDT & E International, 40(4), 275-283. https://doi.org/10.1016/j.ndteint.2006.12.008
  34. Xueqin, L., Gang, L. and Shangqing, L. (2008), "The development of the boiler water wall tube inspection", Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies DRPT 2008, Nanjing, China, April.
  35. Yang, B. and Li, X. (2013), "Pulsed remote field technique used for nondestructive inspection of ferromagnetic tube", NDT & E International, 25(1), 3-12. https://doi.org/10.1016/0963-8695(92)90002-X
  36. Zakiah, A.H., Jamaludin, N., Syarif, J. and Yahya, S.Y.S. (2013), "Detection and analysis of defect in steel tube using Vibration Impact Acoustic Emission (VIAE) method", Int. Rev. Mech. Eng., 8(1), 277-282.
  37. Zalik, K.R. (2008), "An efficient k′-means clustering algorithm", Pattern Recogn. Lett., 29(9), 1385-1391. https://doi.org/10.1016/j.patrec.2008.02.014
  38. Zhan, Y.M. and Mechefske, C.K. (2007), "Robust detection of gearbox deterioration using compromised autoregressive modeling and Kolmogorov-Smirnov test statistic-Part I: Compromised autoregressive modeling with the aid of hypothesis tests and simulation analysis", Mech. Syst. Signal Process., 21(5), 1953-1982. https://doi.org/10.1016/j.ymssp.2006.11.005
  39. Zhang, Y., Ye, Z. and Xu, X. (2007), "An adaptive method for channel equalization in MFL inspection", NDT & E International, 40(2), 127-139. https://doi.org/10.1016/j.ndteint.2006.09.004

피인용 문헌

  1. Influence of Defects on Reinforced Concrete Fracture Performance in Improved Wedge Splitting Tests vol.47, pp.2, 2018, https://doi.org/10.1520/JTE20170176