Mechanism of the effect of temperature on frequency based on long-term monitoring of an arch bridge

Abstract

In this study, the mechanism of the effect of temperature on structural frequency is investigated by integrating correlation analysis, numerical simulation, and neural network techniques. First, the different spatial–temporal influence patterns of the temperature field on frequency are observed using correlation analysis based on the long-term monitoring of an arch bridge. Subsequently, a numerical simulation is performed to quantitatively analyze the effect of temperature on frequency in terms of internal force, geometric size, elastic modulus, and boundary condition. It is observed that an unknown factor—except for the elastic modulus—leads to variation in the frequency of the beam mode. The spatial effect of the temperature field is separated by a genetic-algorithm-optimized backpropagation neural network. It is inferred that the frequency of the beam mode is influenced in terms of the boundary condition and the elastic modulus because of temperature, whereas the frequency of the arch mode is only influenced by the changing elastic modulus.

Keywords

Mechanism spatial–temporal temperature field frequency long-term monitoring arch bridge

Get full access to this article

View all access options for this article.

References

Zhou

Xia

Weng

. L1 regularization approach to structural damage detection using frequency data. Struct Health Monit Int J 2015; 14(6): 571–582.

Jesus

Brommer

Westgate

, et al. Bayesian structural identification of a long suspension bridge considering temperature and traffic load effects. Struct Health Monit 2018; 18(4): 1310–1323.

Wang

Zhang

. Frequency modification of continuous beam bridge based on co-integration analysis considering the effect of temperature and humidity. Struct Health Monit 2018; 18(2): 376–389.

Deraemaeker

Worden

. New trends in vibration based structural health monitoring. New York: Springer, 2010.

Meruane

Heylen

. Structural damage assessment under varying temperature conditions. Struct Health Monit Int J 2011; 11(3): 345–357.

Comanducci

Magalhaes

Ubertini

, et al. On vibration-based damage detection by multivariate statistical techniques: application to a long-span arch bridge. Struct Health Monit Int J 2016; 15(5): 505–524.

Siringoringo

Fujino

. System identification of suspension bridge from ambient vibration response. Eng Struct 2008; 30(2): 462–477.

Yuen

Kuok

. Modeling of environmental influence in structural health assessment for reinforced concrete buildings. Earthq Eng Eng Vib 2010; 9(2): 295–306.

Yang

Ding

. Structural condition assessment of long-span suspension bridges using long-term monitoring data. Earthq Eng Eng Vib 2010; 9(1): 123–131.

10.

Lloyd

Wang

. Thermomechanical analysis of long-term global modal and local deformation measurements of the Kishwaukee bridge using the bootstrap. Earthq Eng Eng Vib 2004; 3(1): 107–115.

11.

Peeters

Roeck

. One year monitoring of the Z24-bridge: environmental influences versus damage events. Earthq Eng Struct Dyn 2001; 30(2): 149–171.

12.

Caetano

Cunha

. Structural health monitoring of a stress-ribbon footbridge. Eng Struct 2013; 57: 578–593.

13.

Tang

Teng

, et al. Structural health monitoring of a prestressed concrete bridge based on statistical pattern recognition of continuous dynamic measurements over 14 years. Sensors 2018; 18(12): 4117.

14.

Moutinho

Caetano

, et al. Continuous dynamic monitoring of a lively footbridge for serviceability assessment and damage detection. Mech Syst Sig Proces 2012; 33: 38–55.

15.

. Vibration-based damage identification and health monitoring of civil structures. San Diego, CA: University of California, 2008.

16.

Xia

Chen

Weng

, et al. Temperature effect on vibration properties of civil structures: a literature review and case studies. J Civil Struct Health Monit 2012; 2(1): 29–46.

17.

Xia

Wei

, et al. Variation of structural vibration characteristics versus non-uniform temperature distribution. Eng Struct 2011; 33(1): 146–153.

18.

Mosavi

Seracino

Rizkalla

. Effect of temperature on daily modal variability of a steel-concrete composite bridge. J Bridge Eng 2012; 17(6): 979–983.

19.

, et al. The modal analysis of civil structure based on the remote laboratory. In: Proceedings of the EDUCON2020-IEEE, Porto, Portugal, 7 April 2020.

20.

Teng

Tang

Zhang

, et al. Automated modal analysis for tracking structural change during construction and operation phases. Sensors 2019; 19(4): 927.

21.

CEB-FIP. 1990 Model Code. London: Thomas Telford, 1993.

22.

Brockenbrough

Frederick

. Structural steel designer’s handbook. 3rd ed. New York: McGraw-Hill, 1999.

23.

JTG 3362:2018. Specification for design of highway reinforce concrete prestressed concrete bridge culverts in 2004.

24.

JT/T291-2009. Pot-type elastometric pad nearing for highway bridge.

25.

Montana

Davis

. Training feedforward neural networks using genetic algorithms. In: Proceedings of the 11th international joint conference on artificial intelligence, Vol. 1, Detroit, Michigan, August 1989. San Francisco, CA: Morgan Kaufmann

26.

Wang

Zhang

, et al. Wind speed forecasting based on the hybrid ensemble empirical mode decomposition and GA-BP neural network method. Renew Energy 2016; 94: 629–636.