SHM-based practical safety evaluation and vibration control model for steel pipes
Unexpected damages or failures of steel pipes in refineries cause significant disruption to economic activity. While research has been conducted on the prevention of damage to steel pipes, no systematic methods or practical techniques for monitoring of vibrations to estimate the state of pipeline system have been reported. In this study, vibration safety evaluation model consisting of design – evaluation – control steps was developed to measure and control the vibration level during operation of the piping system of an oil refinery. The measurement location was designed by examining the structure of the pipe, and the vibration level measured at each location was compared with the allowable vibration level. Subsequently, two types of vibration reduction measures, namely, dynamic absorbers and viscous dampers, were introduced to reduce the vibration level. The effect of the application of the monitoring system was evaluated by comparing the vibration levels of the steel pipes before and after the application of the dynamic absorbers and viscous dampers. The vibrations of steel pipes in the oil refinery during operation decreased by over 50%. Upon applying the dynamic absorbers and viscous dampers, the responses of the frequency component also exhibited local and global reductions of approximately 50–80%.
This work is licensed under a Creative Commons Attribution 4.0 International License.
American Society of Mechanical Engineers. (2001). Requirements for preoperational and initial start-up vibration testing of nuclear power plant piping systems (ASME OM3).
American Society of Mechanical Engineers. (2010). Boiler & pressure vessel code section III, division 1: Mandatory appendix I.
American Society of Mechanical Engineers. (2012). Operation and maintenance of nuclear power plants, Division 2: OM standards contents – Part 3: Vibration testing of piping systems. Nonmandatory appendix D, velocity criterion.
Amezquita-Sanchez, J. P., & Adeli, H. (2016). Signal processing techniques for vibration-based health monitoring of smart structures. Archives of Computational Methods in Engineering, 23, 1–15. https://doi.org/10.1007/s11831-014-9135-7
Ariaratnam, S. T., & Namachchivaya, N. S. (1986). Dynamic stability of pipes conveying pulsating fluid. Journal of Sound and Vibration, 107, 215–230. https://doi.org/10.1016/0022-460X(86)90233-6
Bhandari, S., & Jotautienė, E. (2022). Vibration analysis of a roller bearing condition used in a tangential threshing drum of a combine harvester for the smooth and continuous performance of agricultural crop carvesting. Agriculture, 12(11), 1969. https://doi.org/10.3390/agriculture12111969
Brunesi, E., Nascimbene, R., Pagani, M., & Beilic, D. (2015). Seismic performance of storage steel tanks during the May 2012 Emilia, Italy, earthquakes. Journal of Performance of Constructed Facilities, 29(5), 04014137. https://doi.org/10.1061/(ASCE)CF.1943-5509.0000628
Chock, G. (2006). Preliminary observations on the Hawaii earthquakes of October 15.
Escaler, X., Egusquiza, E., Farhat, M., Avellan, F., & Coussirat, M. (2006). Detection of cavitation in hydraulic turbines. Mechanical Systems and Signal Processing, 20(4), 983–1007. https://doi.org/10.1016/j.ymssp.2004.08.006
Gabbianelli, G., Perrone, D., Nascimbene, R., & Paolacci, F. (2022). Seismic vulnerability assessment and fragility functions derivation for steel storage legged tanks. In Pressure Vessels and Piping Conference (Vol. 86199). American Society of Mechanical Engineers. https://doi.org/10.1115/PVP2022-84416
Gabbianelli, G., Milanesi, R. R., Gandelli, E., Dubini, P., & Nascimbene, R. (2023). Seismic vulnerability assessment of steel storage tanks protected through sliding isolators. Earthquake Engineering & Structural Dynamics, 52(9), 2597–2618. https://doi.org/10.1002/eqe.3885
González, E., Almazán, J., Beltrán, J., Herrera, R., & Sandoval, V. (2010). Performance of stainless steel winery tanks during the 02/27/2010 Maule Earthquake. Engineering Structures, 56, 1402–1418. https://doi.org/10.1016/j.engstruct.2013.07.017
Guo, Y. Q., Zhang, H. Q., Wang, Y. N., & Dai, J. (2022). Research on seismic acceleration waveform reproduction based on time-frequency hybrid integration algorithm. IEEE Access, 10, 94887–94897. https://doi.org/10.1109/ACCESS.2022.3202969
Hussein, D. S., & Al-Waily, M. (2019). Active vibration control analysis of pipes conveying fluid rested on different supports using state-space method. International Journal of Energy and Environment, 10, 329–344.
Iqbala, H., Tesfamariama, S., Haiderb, H., & Sadiqa, R. (2017). Inspection and maintenance of oil & gas pipelines: A review of policies. Structure and Infrastructure Engineering, 13, 794–815. https://doi.org/10.1080/15732479.2016.1187632
Jweeg, M. J., & Ntayeesh, T. J. (2015). Active vibration control analysis of cantilever pipe conveying fluid using smart material. Innovative Systems Design and Engineering, 6, 53–79.
Kabir, G., Sadiq, R., & Tesfamariam, S. (2016). A fuzzy Bayesian belief network for safety assessment of oil and gas pipelines. Structure and Infrastructure Engineering, 12(8), 874–889. https://doi.org/10.1080/15732479.2015.1053093
Kim, D., Oh, B. K., Park, H. S., Shim, H., & Kim, J. (2017). Modal identification for high-rise building structures using orthogonality of filtered response vectors. Computer-Aided Civil and Infrastructure Engineering, 32, 1064–1084. https://doi.org/10.1111/mice.12310
Miranda, E., Mosqueda, G., Retamales, R., & Pekcan, G. (2010). Performance of nonstructural components during the 27 February 2010 Chile earthquake. Earthquake Spectra, 28, 453–471. https://doi.org/10.1193/1.4000032
Miwa, S., Mori, M., & Hibiki, T. (2015). Two-phase flow induced vibration in piping systems. Progress in Nuclear Energy, 78, 270–284. https://doi.org/10.1016/j.pnucene.2014.10.003
Mossa, N. F., Shareef, W. F., & Shareef, F. F. (2018). Design of oil pipeline monitoring system based on wireless sensor network Iraqi. Iraqi Journal of Computers, Communications, Control & Systems Engineering, 18, 53–62. https://doi.org/10.33103/uot.ijccce.18.2.5
Olson, L. G., & Jamison, D. (1997). Application of a general purpose finite element method to elastic pipes conveying fluid. Journal of Fluids and Structures, 11(2), 207–222. https://doi.org/10.1006/jfls.1996.0073
Ozdemir, Z., Souli, M., & Fahjan, Y. (2010). Application of nonlinear fluid-structure interaction methods to seismic analysis of anchored and unanchored tanks. Engineering Structures, 32(2), 409–423. https://doi.org/10.1016/j.engstruct.2009.10.004
Park, H. S., & Oh, B. K. (2018). Real-time structural health monitoring of a supertall building under construction based on visual modal identification strategy. Automation in Construction, 85, 273–289. https://doi.org/10.1016/j.autcon.2017.10.025
Parvizsedghy, L., Senouci, A., Zayed, T., & Mirahadi, S. F. (2015). Condition-based maintenance decision support system for oil and gas pipelines. Structure and Infrastructure Engineering, 11(10), 1323–1337. https://doi.org/10.1080/15732479.2014.964266
Riveiro, B., DeJong, M. J., & Conde, B. (2016). Automated processing of large point clouds for structural health monitoring of masonry arch bridges. Automation in Construction, 72, 258–268. https://doi.org/10.1016/j.autcon.2016.02.009
Senouci, A., Elabbasy, M., Elwakil, E., Abdrabou, B., & Zayed, T. (2014). A model for predicting failure of oil pipelines. Structure and Infrastructure Engineering, 10, 375–387. https://doi.org/10.1080/15732479.2012.756918
Seo, Y. S., Jeong, W. B., Yoo, W. S., & Jeong, H. K. (2005). Frequency response analysis of cylindrical shells conveying fluid using finite element method. Journal of Mechanical Science and Technology, 19, 625–633. https://doi.org/10.1007/BF02916184
Sepehry, N., Ehsani, M., Zhu, W., & Bakhtiari-Nejad, F. (2020). Application of scaled boundary finite element method for vibration-based structural health monitoring of breathing cracks. Journal of Vibration and Control, 27(23–24), 2870–2886. https://doi.org/10.1177/1077546320968646
Sun, Y., Gu, Y., & Xiong, H. (2013). Studied and their application of vibration control technologies. International Journal of Computer Science Issues, 10(2), 311–318.
Taghavi, S., & Miranda, M. M. (2003). Response assessment of nonstructural building elements. Pacific Earthquake Engineering Research Center.
Tan, J., Ho, M., Zhang, S. C., & Jiang, P. (2019). Experimental study on vibration control of suspended piping system by single-sided pounding tuned mass damper. Applied Sciences, 9(2), 285. https://doi.org/10.3390/app9020285
Valentín, D., Presas, A., Valero, C., Egusquiza, M., & Egusquiza, E. (2019). Detection of hydraulic phenomena in francis turbines with different sensors. Sensors, 19(18), 4053. https://doi.org/10.3390/s19184053
Vela, M., & Nascimbene, B. E. (2019). Seismic assessment of an industrial frame-tank system: development of fragility functions. Bulletin of Earthquake Engineering, 17, 2569–2602. https://doi.org/10.1007/s10518-018-00548-2
Wang, S., Ren, Q., & Qiao, P. (2006). Structural damage detection using local damage factor. Journal of Vibration and Control, 12, 955–973. https://doi.org/10.1177/1077546306068286
Wang, J., Zhao, J., Liu, Y., & Shan, J. (2021). Vision‐based displacement and joint rotation tracking of frame structure using feature mix with single consumer‐grade camera. Structural Control and Health Monitoring, 28(12), e2832. https://doi.org/10.1002/stc.2832
Whittaker, A. S., & Soong, T. T. (2003). An overview of nonstructural components research at three US Earthquake Engineering Research Centers. In Proceedings of ATC Seminar on Seismic Design, Performance, and Retrofit of Nonstructural Components in Critical Facilities (pp. 271–280).
Xiao, F., Chen, G. S., & Hulsey, Z. W. (2021). Signature extraction from the dynamic responses of a bridge subjected to a moving vehicle using complete ensemble empirical mode decomposition. Journal of Low Frequency Noise, Vibration and Active Control, 40, 278–294. https://doi.org/10.1177/1461348419872878
Xue, F., Lin, L., Ti, W., & Lu, N. (2007). Vibration assessment method and engineering applications to small bore piping in nuclear power plant. In Second International Symposium on Nuclear Power Plant Life Management, Shanghai, China.
Yildirim, U., Oguz, O., & Bogdanovic, N. (2013). A prediction-error-based method for data transmission and damage detection in wireless sensor networks for structural health monitoring. Journal of Vibration and Control, 19, 2244–2254. https://doi.org/10.1177/1077546313501538
Yun, D. Y., Kim, M., Bae, S. G., Choi, J. W., Shim, H. B., Hong, T., & Park, L. D. (2021). Field measurements for identification of modal parameters for high-rise buildings under construction or in use. Automation in Construction, 121, 103446. https://doi.org/10.1016/j.autcon.2020.103446
Zhang, Y. L., Gorman, D., & Reese, J. M. (2001). A finite element method for modelling the vibration of initially tensioned thin-walled orthotropic cylindrical tubes conveying fluid. Journal of Sound and Vibration, 245, 93–112. https://doi.org/10.1006/jsvi.2000.3554
Zhang, R., Cao, Y., & Dai, K. (2021). Response control of wind turbines with ungrounded tuned mass inerter system (TMIS) under wind loads. Wind and Structures, 32, 573–586.
Zhou, Y. L., Maia, N. M., & Wahab, A. (2018). Damage detection using transmissibility compressed by principal component analysis enhanced with distance measure. Journal of Vibration and Control, 24, 2001–2019. https://doi.org/10.1177/1077546316674544
Zhu, H., Zhou, Y., & Hu, Y. (2020). Displacement reconstruction from measured accelerations and accuracy control of integration based on a low-frequency attenuation algorithm. Soil Dynamics and Earthquake Engineering, 133, 106122. https://doi.org/10.1016/j.soildyn.2020.106122