Smart Structures and Systems

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Multi-type, multi-sensor placement optimization for structural health monitoring of long span bridges

  • Soman, Rohan N. (Department of Civil Engineering and Geomatics, Cyprus University of Technology) ;
  • Onoufrioua, Toula (Department of Civil Engineering and Geomatics, Cyprus University of Technology) ;
  • Kyriakidesb, Marios A. (Department of Civil Engineering and Geomatics, Cyprus University of Technology) ;
  • Votsisc, Renos A. (Department of Civil Engineering and Geomatics, Cyprus University of Technology) ;
  • Chrysostomou, Christis Z. (Department of Civil Engineering and Geomatics, Cyprus University of Technology)
  • Received : 2014.02.28
  • Accepted : 2014.06.25
  • Published : 2014.07.25
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Abstract

The paper presents a multi-objective optimization strategy for a multi-type sensor placement for Structural Health Monitoring (SHM) of long span bridges. The problem is formulated for simultaneous placement of strain sensors and accelerometers (heterogeneous network) based on application demands for SHM system. Modal Identification (MI) and Accurate Mode Shape Expansion (AMSE) were chosen as the application demands for SHM. The optimization problem is solved through the use of integer Genetic Algorithm (GA) to maximize a common metric to ensure adequate MI and AMSE. The performance of the joint optimization problem solved by GA is compared with other established methods for homogenous sensor placement. The results indicate that the use of a multi-type sensor system can improve the quality of SHM. It has also been demonstrated that use of GA improves the overall quality of the sensor placement compared to other methods for optimization of sensor placement.

Keywords

References

  1. ABAQUS (2011), Analysis User's Manual, version 6.11 ed.
  2. Chakraborty, S. and DeWolf, J.T. (2006), "Development and implementation of a continuous strain monitoring system on a multi-girder composite steel bridge", J. Bridge Eng., 11(6), 753-762. https://doi.org/10.1061/(ASCE)1084-0702(2006)11:6(753)
  3. Chan, T.H.T., Yu, Y., Wong, K.Y. and Li, Z.X. (2008), "Condition-assessment-based finite element modeling of long-span bridge by mixed dimensional coupling method", J. Mech. Mater., 260-270.
  4. COWI Internal Report (2000), East Bridge, Technical Services, Superstructure. Vurdering af Accelerationer for Storebae lt Hae ngebro, Teknisk rapport .
  5. Doebling, S.W., Farrar, C.R. and Prime, M.B. (1998), "A summary review of vibration-based damage identification methods", Shock Vib. Dig., 30(2), 91-105. https://doi.org/10.1177/058310249803000201
  6. Ewins, D.J. (2000), Modal testing; theory, practice and application, Research Studies Press
  7. Fedorov, V. and Hackl, P. (1994), "Optimal experimental design: spatial sampling", Calcutta Statistical Association Bulletin, 44, 173-174.
  8. Guyan, R.J. (1965), "Reduction of stiffness and mass matrices", AIAA J., 3(2), 380. https://doi.org/10.2514/3.2874
  9. Haupt, L.R. and Haupt, S.E. (2004), Practical genetic algorithms, 2nd Ed., John Wiley & Sons Inc.
  10. Heo, G., Wang, M.L. and Satpathi, D. (1997), "Optimal transducer placement for health monitoring of long span bridge", Soil Dynam. Earthq. Eng., 16(7-8), 495-502. https://doi.org/10.1016/S0267-7261(97)00010-9
  11. Kammer, D.C. (1991), "Sensor placement for on-orbit modal identification and correlation of large space structures", J. Guid. Control Dynam., 14(2), 251-259. https://doi.org/10.2514/3.20635
  12. Kidder, R.L. (1973), "Reduction of structural frequency equations", AIAA J., 11(6), 892. https://doi.org/10.2514/3.6852
  13. Larsen, A. (1993), "Aerodynamic aspects of the final design of the 1624 m suspension bridge across the Great Belt", J. Wind Eng. Ind. Aerod., 48, 261-285. https://doi.org/10.1016/0167-6105(93)90141-A
  14. Law, S.S., Li, X.Y., Zhu, X.Q. and Chan, S.L. (2005), "Structural damage detection from wavelet packet sensitivity", Eng. Struct., 27(9), 1339-1348. https://doi.org/10.1016/j.engstruct.2005.03.014
  15. Levine-West, M., Mihnan, M. and Kissil, A. (1994), "Evaluation of mode shape expansion techniques for prediction- experimental evaluation", AIAA J., 34(4), 821-829.
  16. Natarajan, S., Howells, H., Deka, D. and Walters, D. (2006), Optimization of sensor placement to capture riser VIV response, OMAE, Hamburg, Germany.
  17. O'callahan, J.C., Avitabile, P. and Riemer, R. (1989), "System equivalent reduction expansion process", Proceeding of the 7th International Modal Analysis Conference, Las Vegas, USA.
  18. Ortel, T., Wagner, J.F. and Saupe, F. (2012), "Integrated motion measurement illustrated by a cantilever beam", J. Mech. Syst. Signal Pr., 34(1-2), 131-145.
  19. Papadimitriou, C. (2004), "Optimal sensor placement methodology for parametric identification of structural systems", J. Sound Vib., 278(4-5), 923-947. https://doi.org/10.1016/j.jsv.2003.10.063
  20. Rytter, A. (1993), Vibrational-based inspection of civil engineering structures, PhD Dissertaion, University of Aalborg.
  21. Sim, S.H. (2011), Decentralized identification and multimetric monitoring of civil infrastructure using smart sensors, (Doctoral dissertation, University of Illinois).
  22. Talebinejad. I, Fischer, C. and Ansari, F. (2011), "Numerical evaluation of vibration-based methods for damage assessment of cable-stayed bridges", Comput. -Aided Civil Infrastruct. E., 26(3), 239-251. https://doi.org/10.1111/j.1467-8667.2010.00684.x
  23. Uhl, T. (2009), "Structural Health Monitoring (SHM)-a new interdisciplinary approach to damage detection in mechanical structures", Pomiary, Automatyka, Kontrola, 55(9), 703-706.
  24. Unger, J., Teughels, A. and De Roeck, G. (2005), "Damage detection of a prestressed concrete beam using modal strains", J. Struct. Eng. - ASCE, 131(9), 1456-1463. https://doi.org/10.1061/(ASCE)0733-9445(2005)131:9(1456)
  25. Weight, A.J. (2009), "Critical analysis of the Great Belt East Bridge, Denmark", Proceedings of Bridge Engineering 2 Conference, April 2009, University of Bath, Bath, UK
  26. Worden, K. and Burrows, A.P. (2001), "Optimal Sensor Placement for fault detection", Eng. Struct., 23(8), 885-901. https://doi.org/10.1016/S0141-0296(00)00118-8

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