Structural Engineering and Mechanics

Techno-Press (테크노프레스)
권호 표지
DOI QR코드

DOI QR Code

Movement identification model of port container crane based on structural health monitoring system

  • Kaloop, Mosbeh R. (Department of Civil and Environmental Engineering, Kunsan National University) ;
  • Sayed, Mohamed A. (Department of Civil and Environmental Engineering, Kunsan National University) ;
  • Kim, Dookie (Department of Civil and Environmental Engineering, Kunsan National University) ;
  • Kim, Eunsung (Korea Maintenance Company)
  • Received : 2013.07.05
  • Accepted : 2014.02.15
  • Published : 2014.04.10
⟨ Previous Next ⟩

Abstract

This study presents a steel container crane movement analysis and assessment based on structural health monitoring (SHM). The accelerometers are used to monitor the dynamic crane behavior and a 3-D finite element model (FEM) was designed to express the static displacement of the crane under the different load cases. The multi-input single-output nonlinear autoregressive neural network with external input (NNARX) model is used to identify the crane dynamic displacements. The FEM analysis and the identification model are used to investigate the safety and the vibration state of the crane in both time and frequency domains. Moreover, the SHM system is used based on the FEM analysis to assess the crane behavior. The analysis results indicate that: (1) the mean relative dynamic displacement can reveal the relative static movement of structures under environmental load; (2) the environmental load conditions clearly affect the crane deformations in different load cases; (3) the crane deformations are shown within the safe limits under different loads.

Keywords

References

  1. Belmont, M.R. and Hotchkiss, A.J. (1997), "Generalized cross-correlation functions for engineering applications, part i: basic theory", J. Appl. Mech., 64, 321-326. https://doi.org/10.1115/1.2787310
  2. Bhimani, A. and Soaderberg, E. (2010), "Quay crane accidents: lessons and prevention", Presentation TOC Asia 2010, Shanghai, China.
  3. Chan, W.S., Xu, Y.L., Ding, X.L. and Dai, W.J. (2006), "An integrated GPS-accelerometer data processing technique for structural deformation monitoring", Geodesy J., 80, 705-719. https://doi.org/10.1007/s00190-006-0092-2
  4. Deng, H. and Xu, J. (2009), "Construction safety monitoring and finite element analysis on the supporting system of tower crane in Guangzhou west-tower", Proceeding of the Second International Conference on Information and Computing Science, Manchester, England.
  5. Ding, K.Q., Wang, Z., Lina, N. and Song, Q. (2012), "Structural health monitoring system for the crane based on bragg grating sensors", Proceeding of 18th World Conference on Nondestructive Testing, Durban, South Africa.
  6. Elnabwy, M.T., Kaloop, M.R. and Elbeltagi, E. (2013), "Talkha steel highway bridge monitoring and movement identification using RTK-GPS technique", Measurement J., 46(10), 4282-4292. https://doi.org/10.1016/j.measurement.2013.08.014
  7. Erdogan, H. and Gulal, E. (2009), "Identification of dynamic systems using multiple input-single output (MISO) models", Nonlin. Anal., Real World Appl., 10(2), 1183-1196. https://doi.org/10.1016/j.nonrwa.2007.12.008
  8. Gentile, C. (2010), "Application of radar technology to deflection measurement and dynamic testing of bridges", Radar Technology, (Ed. Guy Kouemou), In Tech, 141-162.
  9. Gevers, M., Miskovic, L., Bonvin, D. and Karimi, A. (2006), "Identification of multi-input systems: variance analysis and input design issues", Automatica J., 42(4), 559-572. https://doi.org/10.1016/j.automatica.2005.12.017
  10. Gikas, V. (2012a), "Three-dimensional laser scanning for geometry documentation and construction management of highway tunnels during excavation", Sensor. J., 12(8), 11249-11270. https://doi.org/10.3390/s120811249
  11. Gikas, V. (2012b), "Ambient vibration monitoring of slender structures by microwave interferometer remote sensing", J. Appl. Geodesy, 6, 167-176.
  12. Godoy, H.Y., Schoefs, F., Nouy, A. and Lasne, M. (2008), "Reliability analysis of two in-service monitored pile-supported wharves during extreme storm loading events", Proceeding of 1st International Conference on Applications Heritage and Constructions in Coastal and Marine Environment, Lisbon, Portugal.
  13. Hart, G. and Yao, J. (1977), "System identification in structural dynamic", J. Eng. Mech. Div., ASME, 103(EM66), 1089-1104.
  14. Heij, C. and Schagen, F. (2007), Introduction to mathematical systems theory linear systems, identification and control, Ed. Ran, A., Springer, Basel, Switzerland.
  15. Heo, G. and Jeon, J. (2009), "A smart monitoring system based on ubiquitous computing technique for infrastructural system: centering on identification of dynamic characteristics of self-anchored suspension bridge", KSCE Journal of Civil Engineering, 13(5), 333-337. https://doi.org/10.1007/s12205-009-0333-z
  16. Kaloop, M.R. (2012), "Bridge safety monitoring based-GPS technique: case study Zhujiang Huangpu Bridge", Smart Struct. Syst., 9(6), 473-487. https://doi.org/10.12989/sss.2012.9.6.473
  17. Kaloop, M.R. and Li, H. (2014), "Multi input-single output models identification of tower bridge movements using GPS monitoring system", Measurement J., 47, 531- 539. https://doi.org/10.1016/j.measurement.2013.09.046
  18. Kosbab, B., Jacobs, L., DesRoches, R., and Leon, R. (2009), "Analysis and testing of container cranes under earthquake loads", TCLEE 2009, 1-11, doi: 10.1061/41050(357)80.
  19. Li, X., Ge, L., Ambikairajah, E., Rizos, C., Tamura, Y. and Yoshida, A. (2006), "Full-scale structural monitoring using an integrated GPS and accelerometer system", GPS Solut. J., 10, 233-247. https://doi.org/10.1007/s10291-006-0023-y
  20. Magalhaes, F., Caetano, E. and Cunha, A. (2007), "Challenges in the application of stochastic modal identification methods to a cable-stayed bridge", J. Bridge Eng., ASCE, 12(6), 746-754. https://doi.org/10.1061/(ASCE)1084-0702(2007)12:6(746)
  21. Martin, H. (2007), Matlab recipes for earth sciences, 2th Edition, Springer Berlin Heidelberg, New York, USA.
  22. Meng, X., Dodson, A.H. and Reborts, G.W. (2007), "Detecting bridge dynamics with GPS and triaxial accelerometers", J. Eng. Struct., 29(11), 3178-3184. https://doi.org/10.1016/j.engstruct.2007.03.012
  23. Moschas, F. and Stiros, S. (2011), "Measurement of the dynamic displacements and the modal frequencies of a short-span pedestrian bridge using GPS and an accelerometer", J. Eng. Struct., 33(1), 10-17. https://doi.org/10.1016/j.engstruct.2010.09.013
  24. Nickitopoulou, A., Protopsalti, K. and Stiros, S. (2006), "Monitoring dynamic and quasi-static deformations of large flexible engineering structures with GPS: accuracy, limitations and promises", J. Eng. Struct.,28(10), 1471-1482. https://doi.org/10.1016/j.engstruct.2006.02.001
  25. Norgaard, M. (2000), "Neural network based system identification toolbox", Version2. Tech. Report, 00-E-891, Department of Automation, Technical Un. of Denmark.
  26. Psimoulis, P., Moschas, F. and Stiros, S. (2011), "Measuring the displacements of a rigid footbridge using geodetic instruments and an accelerometer", Proceeding of JUSDM, Hong Kong, China.
  27. Richard, L.N., Seixas, N.S. and Ren, K. (2001), "A review of crane safety in the construction industry", Appl. Occup. Environ. Hyg. J., 16(12), 1106-1117. https://doi.org/10.1080/10473220127411
  28. Sohn, H., Farrar, C.R., Hemez, F.M., Shunk, D., Stinemates, D.W., Nadler, B.R. and Czarnecki, J.J. (2004), "A review of structural health monitoring literature: 1996-2001", Los Alamos National Laboratory Report, LA-13976-MS.
  29. Weng, J., Loh, C., Lynch, J., Lu, K, Lin, P. and Wang, Y. (2008), "Output-only modal identification of a cable-stayed bridge using wireless monitoring systems", J. Eng. Struct., 30, 1820-1830. https://doi.org/10.1016/j.engstruct.2007.12.002
  30. Zhiping, L., Tengfei, J., Qing, H. and Dang, W. (2011), "Research on mechanical condition monitoring technology for portal crane by wireless sensors", Proceeding of 3rd International Conference on Measuring Technology and Mechatronics Automation, Shanghai, China.

Cited by

  1. Optimum ARX Model Prediction for Monthly Air Temperature Changes in Delta, Egypt vol.9, pp.3, 2015, https://doi.org/10.3923/rjes.2015.137.151
  2. Detection and parametric identification of structural nonlinear restoring forces from partial measurements of structural responses vol.54, pp.2, 2015, https://doi.org/10.12989/sem.2015.54.2.291
  3. Structural Performance Assessment Based on Statistical and Wavelet Analysis of Acceleration Measurements of a Building during an Earthquake vol.2016, 2016, https://doi.org/10.1155/2016/8902727
  4. Cross modal strain energy–based structural damage detection in the presence of noise effects vol.9, pp.12, 2017, https://doi.org/10.1177/1687814017744122
  5. Probabilistic real-time updating for geotechnical properties evaluation vol.54, pp.2, 2015, https://doi.org/10.12989/sem.2015.54.2.363
  6. Bridge Performance Assessment Based on an Adaptive Neuro-Fuzzy Inference System with Wavelet Filter for the GPS Measurements vol.4, pp.4, 2015, https://doi.org/10.3390/ijgi4042339
  7. Assessment of acceleration responses of a railway bridge using wavelet analysis vol.21, pp.5, 2017, https://doi.org/10.1007/s12205-016-1762-0
  8. Structural Health Monitoring for a Z-Type Special Vehicle vol.17, pp.6, 2017, https://doi.org/10.3390/s17061262
  9. Internet of things for smart ports: Technologies and challenges vol.21, pp.1, 2018, https://doi.org/10.1109/MIM.2018.8278808
  10. Explicit expressions for inelastic design quantities in composite frames considering effects of nearby columns and floors vol.64, pp.4, 2014, https://doi.org/10.12989/sem.2017.64.4.437