DOI QR코드

DOI QR Code

Automatic modal identification and variability in measured modal vectors of a cable-stayed bridge

  • Ni, Y.Q. (Department of Civil and Structural Engineering, The Hong Kong Polytechnic University) ;
  • Fan, K.Q. (School of Information, Wuyi University) ;
  • Zheng, G. (Chongqing Communications Research and Design Institute) ;
  • Ko, J.M. (Department of Civil and Structural Engineering, The Hong Kong Polytechnic University)
  • Received : 2003.06.09
  • Accepted : 2004.08.04
  • Published : 2005.01.30

Abstract

An automatic modal identification program is developed for continuous extraction of modal parameters of three cable-supported bridges in Hong Kong which are instrumented with a long-term monitoring system. The program employs the Complex Modal Indication Function (CMIF) algorithm for identifying modal properties from continuous ambient vibration measurements in an on-line manner. By using the LabVIEW graphical programming language, the software realizes the algorithm in Virtual Instrument (VI) style. The applicability and implementation issues of the developed software are demonstrated by using one-year measurement data acquired from 67 channels of accelerometers permanently installed on the cable-stayed Ting Kau Bridge. With the continuously identified results, variability in modal vectors due to varying environmental conditions and measurement errors is observed. Such an observation is very helpful for selection of appropriate measured modal vectors for structural health monitoring use.

Keywords

References

  1. Abdel Wahab, M. and De Roeck, G. (1997), 'Effect of temperature on dynamic system parameters of a highway bridge', Stntct. Eng. Int., 7, 266-270 https://doi.org/10.2749/101686697780494563
  2. Alampalli, S. (1998), 'Influence of in-service environment on modal parameters', Proc. of the 16th Int. Modal Analysis Conf, Santa Barbara, California, 1, 111-116
  3. Bergennann, R. and Schlaich, M. (1996), 'Ting Kau Bridge, Hong Kong', Stntct. Eng. Int., 6, 152-154 https://doi.org/10.2749/101686696780495563
  4. Endo, T., Iijima, T., Okukawa, A. and Ito, M. (1991), 'The technical challenge of a long cable-stayed bridges Tatara Bridge', Cable-Stayed Bridges: Recent Developments and Their Future, Ito, M., Fujino, Y., Miyata, T. and Narita, N. (eds.), Elsevier, Amsterdam, 417-436
  5. Farrar, C.R., Doebling, S.W., Cornwell, P.J. and Straser, E.G.(1997), 'Variability of modal parameters measured on the Alamosa Canyon Bridge', Proc. of the 15th Int. Modal Analysis Conf, Orlando, Florida, 1, 257-263
  6. Ko, J.M., Wang, J.Y., Ni, Y.Q. and Chak, KK (2003), 'Observation on environmental variability of modal properties of a cable-stayed bridge from one-year monitoring data', Structural Health Monitoring 2003: From Diagnostics & Prognostics to Structural Health Management, Chang, E-K. (ed.), DEStech Publications, Lancaster, Pennsylvania, 467-474
  7. Lau, C.K, Mak, W.P.N., Wong, K.Y., Chan, W.Y.K. and Man, K.L.D. (1999), 'Structural health monitoring of three cable-supported bridges in Hong Kong', Structural Health Monitoring 2000, Chang, E-K (ed.), Technomic, Lancaster, Pennsylvania, 450-460
  8. Lloyd, G.M., Wang, M.L. and Singh, V. (2000), 'Observed variations of mode frequencies of a prestressed concrete bridge with temperature', Proc. of ASCE 14th Eng. Mech. Conf. (in CD format), Austin, Texas
  9. Lloyd, G.M., Wang, M.L. Wang, X. and Love, J (2003), 'Recommendations for intelligent bridge monitoring systems: Architecture and temperature-compensated bootstrap analysis', Smart Structures and Materials 2003: Smart Systems and Nondestructive Evaluationfor Civil Infrastructures , Liu, S.-c. (ed.), SPIE, 5057, 247-258 https://doi.org/10.1117/12.488892
  10. Ni, Y.Q., Ko, J.M. and Zhou, X.T. (2001), 'Damage region identification of cable-supported bridges using neural network based novelty detectors', Structural Health Monitoring: The Demands and Challenges, Chang, E-K (ed.), CRC Press, Boca Raton, Florida, 449-458
  11. Peeters, B. and De Roeck, G. (2001), 'One-year monitoring of the Z24-Bridge: Environmental effect versus damage events', Earthq. Eng. Struct. Dyn., 30, 149-171 https://doi.org/10.1002/1096-9845(200102)30:2<149::AID-EQE1>3.0.CO;2-Z
  12. Roberts, G.P. and Pearson, A.J. (1996), 'Dynamic monitoring as a tool for long span bridges', Bridge Management 3: Inspection, Maintenance, Assessment and Repair, Harding, J.E., Parke, G.E.R. and Ryall, MJ. (eds.), E & FN Spon, London, 704-711
  13. Rohrmann, R.G., Baessler, M., Said, S., Schmid, W. and Ruecker, W.F. (2000), 'Structural causes of temperature affected modal data of civil structures obtained by long time monitoring', Proc. of the 18th Int. Modal Analysis Conf, San Antonio, Texas, 1, 1-7
  14. Shih, C.Y., Tsuei, Y.G., Allemang, R.J and Brown, D.L. (1988a), 'A frequency domain global parameter estimation method for multiple reference frequency response measurements', Mechanical Systems and Signal Proc., 2, 349-365
  15. Shih, C.Y., Tsuei, Y.G., Allemang, R.J. and Brown, D.L. (1988b), 'Complex mode indication function and its applications to spatial domain parameter estimation', Mechanical Systems and Signal Proc., 2, 367-377
  16. Sohn, H., Dzwonczyk, M., Straser, E.G., Kiremidjian, A.S., Law, K.H. and Meng, T. (1999), 'An experimental study of temperature effect on modal parameters of the Alamosa Canyon Bridge', Earthq. Eng. Struct. Dyn., 28, 879-897 https://doi.org/10.1002/(SICI)1096-9845(199908)28:8<879::AID-EQE845>3.0.CO;2-V
  17. Sohn, H., Worden, K and Farrar, C.R. (2002), 'Consideration of environmental and operational variability for damage diagnosis', Smart Structures and Materials 2002: Smart Systems for Bridges, Structures, and Highways, Liu, S.-C. and Pines, DJ. (eds.), SPIE, 4696, 100-111
  18. Sun, Z.G., Ko, J.M. and Ni, Y.Q. (2001), 'Modal indices for identifying damage location in cable-stayed Kap Shui Mun Bridge', Health Monitoring and Management of Civil Infrastructure Systems, Chase, S.B. and Aktan, A.E. (eds.), SPIE, 4337, 379-389
  19. Wong, K.Y., Lau, C.K. and Flint, A.R. (2000), 'Planning and implementation of the structural health monitoring system for cable-supported bridges in Hong Kong', Nondestructive Evaluation of Highways, Utilities, and Pipelines IV, Aktan, A.E. and Gosselin, S.R. (eds.), SPIE, 3995, 266-275
  20. Wong, K.Y., Man, K.L. and Chan, W.Y. (2001), 'Application of global positioning system to structural health monitoring of cable-supported bridges', Health Monitoring and Management of Civil Infrastructure Systems, Chase, S.B. and Aktan, AE. (ed.), SPIE, 4337, 390-401

Cited by

  1. Temperature effect on vibration properties of civil structures: a literature review and case studies vol.2, pp.1, 2012, https://doi.org/10.1007/s13349-011-0015-7
  2. Modal Identification of Sutong Cable-Stayed Bridge during Typhoon Haikui Using Wavelet Transform Method vol.30, pp.5, 2016, https://doi.org/10.1061/(ASCE)CF.1943-5509.0000856
  3. Modal parameter identification of a long-span footbridge by forced vibration experiments vol.20, pp.5, 2017, https://doi.org/10.1177/1369433217698322
  4. Constructing input to neural networks for modeling temperature-caused modal variability: Mean temperatures, effective temperatures, and principal components of temperatures vol.32, pp.6, 2010, https://doi.org/10.1016/j.engstruct.2010.02.026
  5. Investigation concerning structural health monitoring of an instrumented cable-stayed bridge vol.5, pp.6, 2009, https://doi.org/10.1080/15732470701627893
  6. Correlating modal properties with temperature using long-term monitoring data and support vector machine technique vol.27, pp.12, 2005, https://doi.org/10.1016/j.engstruct.2005.02.020
  7. Recent perspectives in dynamic testing and monitoring of bridges vol.20, pp.6, 2013, https://doi.org/10.1002/stc.1516
  8. VIBRATION-BASED STRUCTURAL DAMAGE DETECTION UNDER VARYING TEMPERATURE CONDITIONS vol.13, pp.05, 2013, https://doi.org/10.1142/S0219455412500824
  9. Generalization Capability of Neural Network Models for Temperature-Frequency Correlation Using Monitoring Data vol.135, pp.10, 2009, https://doi.org/10.1061/(ASCE)ST.1943-541X.0000050
  10. Temperature effect on service performance of high-speed railway concrete bridges vol.20, pp.6, 2017, https://doi.org/10.1177/1369433216665306
  11. Modeling of Temperature–Frequency Correlation Using Combined Principal Component Analysis and Support Vector Regression Technique vol.21, pp.2, 2007, https://doi.org/10.1061/(ASCE)0887-3801(2007)21:2(122)
  12. Eliminating Temperature Effect in Vibration-Based Structural Damage Detection vol.137, pp.12, 2011, https://doi.org/10.1061/(ASCE)EM.1943-7889.0000273
  13. Ensemble classification method for structural damage assessment under varying temperature 2017, https://doi.org/10.1177/1475921717717311
  14. Structural damage alarming using auto-associative neural network technique: Exploration of environment-tolerant capacity and setup of alarming threshold vol.25, pp.5, 2011, https://doi.org/10.1016/j.ymssp.2011.01.005
  15. Variability of measured modal frequencies of a cable-stayed bridge under different wind conditions vol.3, pp.3, 2007, https://doi.org/10.12989/sss.2007.3.3.341
  16. Environmental-effects-embedded model updating method considering environmental impacts 2017, https://doi.org/10.1002/stc.2116
  17. Two-step approaches for effective bridge health monitoring vol.23, pp.1, 2006, https://doi.org/10.12989/sem.2006.23.1.075
  18. Comparison of Analytical Approaches to Tall Building Structural Damage Identification Based on Measured Dynamic Characteristics vol.105-107, pp.1662-7482, 2011, https://doi.org/10.4028/www.scientific.net/AMM.105-107.1081
  19. Solar Radiation-Induced Temperature Variation of Concrete Bridge Piers vol.178-181, pp.1662-7482, 2012, https://doi.org/10.4028/www.scientific.net/AMM.178-181.2451
  20. Assessment on the Thermal Stresses of Concrete Bridge Piers under Solar Radiation vol.204-208, pp.1662-7482, 2012, https://doi.org/10.4028/www.scientific.net/AMM.204-208.2045
  21. Frequency modification of continuous beam bridge based on co-integration analysis considering the effect of temperature and humidity pp.1741-3168, 2018, https://doi.org/10.1177/1475921718755573
  22. Eliminating Temperature Effects in Damage Detection for Civil Infrastructure Using Time Series Analysis and Autoassociative Neural Networks vol.32, pp.2, 2019, https://doi.org/10.1061/(ASCE)AS.1943-5525.0000987
  23. Modeling of wind and temperature effects on modal frequencies and analysis of relative strength of effect vol.11, pp.1, 2005, https://doi.org/10.12989/was.2008.11.1.035
  24. Structural Damage Identification Under Temperature Variations Based on PSO-CS Hybrid Algorithm vol.19, pp.11, 2005, https://doi.org/10.1142/s0219455419501396