Inspection of Aboveground Pipeline Using Vibration Responses
Publication: Journal of Pipeline Systems Engineering and Practice
Volume 11, Issue 3
Abstract
The purpose of this paper is to present a new kind of fast structural damage-detection method based on structural vibration responses that can be used for aboveground pipelines. This study proposes the use of structural health monitoring (SHM) for aboveground pipelines using the inner product vector (IPV) method. The IPV can be calculated from the vibrational responses signals (displacement or velocity or acceleration) under band pass white noise excitation. The vibrational responses signals were measured before and after damage. The case study is a type 304 stainless steel pipe with an internal defect. Because of difficulties in creating internal defects in practice, numerical simulation was used. This was achieved by the use of three-dimensional (3D) finite element (FE) modeling software (ABAQUS CAE version 6.10) with MATLAB R2015b (version 8.6) used to calculate the IPV method. To verify the simulation method, the results obtained from modeling in ABAQUS are compared with our previous experimental results that showed good agreement. The results indicate that the IPV method can be used for detecting damage in aboveground pipeline.
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Data Availability Statement
All data, models, and code generated or used during the study appear in the published article.
Acknowledgments
The authors are grateful to Dr. Le Wang (the University of Northwestern Polytechnical) and Dr. Muyu Zhang (the University of RWTH Aachen) for their kind help and valuable comments.
References
Brake, M. R. W. 2018. The mechanics of jointed structures, 292. Cham, Switzerland: Springer International Publishing. https://doi.org/10.1007/978-3-319-56818-8.
Kim, J. H. 2011. “Sensor-based autonomous pipeline monitoring robotic system.” Doctoral dissertations, Dept. of Computer Science, Louisiana State Univ. and Agricultural and Mechanical College.
Mohammadi Esfarjani, S., and M. Salehi. 2016a. “Damage identification in aluminium T3-2024 alloy via cross correlation functions.” In Proc., 15th Int. Conf. of Iranian Aerospace. Tehran, Iran: Iranian Aerospace Society.
Mohammadi Esfarjani, S., and M. Salehi. 2016b. “Detection of metallic impurities in alloys using the IPV and AMV methods.” Rom. J. Acoust. Vib. 13 (2): 131–137.
Mohammadi Esfarjani, S., and M. Salehi. 2016c. “Evaluation of the damage detection capability of inner product vector for LOP and LOSWF defects in V groove weld.” [In Persian.] Modares Mech. Eng. 16 (6): 7–16.
Mohammadi Esfarjani, S., and M. Salehi. 2017. “Optimization the inner product vector method and its application to structural health monitoring.” J Vibroeng. 19 (4): 2578–2585. https://doi.org/10.21595/jve.2017.18062.
Roberts, R. D. 2012. “Inspection of buried or inaccessable piping in nuclear power plants utilizing ultrasonic based intelligent pigging technology.” In Proc., 9th Int. Conf. on NDE in Relation to Structural Integrity for Nuclear and Pressurized Components. Seattle: Publications Office of the European Union. https://www.ndt.net/article/jrc-nde2012/papers/113.pdf.
Slessarev, D., V. Sukhorukov, S. Belitsky, N. Vasin, and E. Stepanov. 2006. “Magnetic in-line inspection of pipelines: Some problems of defect detection, identification and measurement.” In Proc., 9th European Conf. on NDT: European Federation for Non-Destructive Testing (ECNDT). Berlin: European Federation for Non-Destructive Testing. https://www.ndt.net/article/ecndt2006/doc/Tu.3.1.2.pdf.
Wang, L., and Z. Yang. 2012. “Structural damage detection using inner product vector and low pass filter technique.” Appl. Mech. Mater. 204–208 (1): 2942–2946. https://doi.org/10.4028/www.scientific.net/AMM.204-208.2942.
Wang, L., Z. Yang, T. P. Waters, and M. Zhang. 2011. “Theory of inner product vector and its application to multi-location damage detection.” J. Phys. Conf. Ser. 305 (1): 012003. https://doi.org/10.1088/1742-6596/305/1/012003.
Wang, L., Z. C. Yang, and T. P. Waters. 2010. “Structural damage detection using cross correlation functions of vibration response.” J. Sound Vib. 329 (24): 5070–5086. https://doi.org/10.1016/j.jsv.2010.06.020.
Yam, L. H., Y. J. Yan, and J. S. Jiang. 2003. “Vibration-based damage detection for composite structures using wavelet transform and neural network identification.” Compos. Struct. 60 (4): 403–412. https://doi.org/10.1016/S0263-8223(03)00023-0.
Yan, Y. J., L. Cheng, Z. Y. Wu, and L. H. Yam. 2007. “Development in vibration-based structural damage detection technique.” Mech. Syst. Sig. Process. 21 (5): 2198–2211. https://doi.org/10.1016/j.ymssp.2006.10.002.
Yan, Y. J., and L. H. Yam. 2004. “Detection of delamination damage in composite plates using energy spectrum of structural dynamic responses decomposed by wavelet analysis.” Comput. Struct. 82 (4–5): 347–358. https://doi.org/10.1016/j.compstruc.2003.11.002.
Yang, Z., L. Wang, H. Wang, Y. Ding, and X. Dang. 2009. “Damage detection in composite structures using vibration response under stochastic excitation.” J. Sound Vib. 325 (4–5): 755–768. https://doi.org/10.1016/j.jsv.2009.03.040.
Zhang, M., and R. Schmidt. 2013. “A comparative study of the correlation function based structural damage detection methods under sinusoidal excitation.” In Proc., 11th Int. Conf. on Vibration Problems. Lisbon, Portugal: AMPTAC.
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Published In
Journal of Pipeline Systems Engineering and Practice
Volume 11 • Issue 3 • August 2020
Copyright
©2020 American Society of Civil Engineers.
History
Received: Jan 17, 2019
Accepted: Dec 23, 2019
Published online: Apr 6, 2020
Published in print: Aug 1, 2020
Discussion open until: Sep 6, 2020
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