Bridge Damage Detection using the Inverse Dynamics Optimization Algorithm

The current methods to identify the bridge damage depend on time-consuming visual inspection and/or based on the data collected from a sensor based monitoring, which make the assessment process very expensive. In this paper, the bridge damage is identified using the data collected from an ordinary strain transducer. In order to demonstrate the new method, 3-D finite element models followed by the Inverse Dynamics Optimization Algorithm are performed. The inverse algorithm utilized to calculate the weight of the force that pass on the bridge. Any change in the bridge stiffness by damage will influence the force history which calculated by the inverse algorithm. The proposed method divided into two stages: in the first one, two finite element models are used to simulate the bridge displacement due to quarter car model one representing the healthy bridge and the other for the damage one. In the second stage, the inverse dynamics optimization algorithm used to identify the damage locations.

References

1.  Herrmann, A.W. ASCE 2013 Report Card for America's Infrastructure. in IABSE Symposium Report. 2013. International Association for Bridge and Structural Engineering.

2.  Rowley, C.W., Moving force identification of axle forces on bridges. 2007: University College Dublin.

3.  Rowley, C., et al., Experimental testing of a moving force identification bridge weigh-in-motion algorithm. Experimental Mechanics, 2009. 49(5): p. 743-746.

4.  González, A., C. Rowley, and E.J. OBrien, A general solution to the identification of moving vehicle forces on a bridge. International journal for numerical methods in engineering, 2008. 75(3): p. 335-354.

5.  Zhu, X. and S. Law, Identification of moving loads on an orthotropic plate. TRANSACTIONS-AMERICAN SOCIETY OF MECHANICAL ENGINEERS JOURNAL OF VIBRATION AND ACOUSTICS, 2001. 123(2): p. 238-244.

6.  Zhu, X. and S. Law, Dynamic axle and wheel loads identification: laboratory studies. Journal of sound and vibration, 2003. 268(5): p. 855-879.

7.  Zakic, B. Vibrations in diagnosis of damages in concrete bridges. in Proceedings of the Second RILEM International Conference on Diagnosis of Concrete Structures, Strbské pleso, Slovakia. 1996.

8.  El-Hattab, A., N. Uddin, and E. Obrien, Drive-by Bridge Damage Detection using Apparent Profile.

9.  Elhattab, A., N. Uddin, and E. OBrien, Drive-by bridge damage monitoring using Bridge Displacement Profile Difference. Journal of Civil Structural Health Monitoring, 2016. 6(5): p. 839-850.

10.  Tikhonov, A.N., V.I.A.k. Arsenin, and F. John, Solutions of ill-posed problems. Vol. 14. 1977: Winston Washington, DC.

11.  Law, S., et al., Regularization in moving force identification. Journal of Engineering Mechanics, 2001. 127(2): p. 136-148.

12.  Zhu, X. and S. Law, Moving loads identification through regularization. Journal of Engineering Mechanics, 2002. 128(9): p. 989-1000.

13.  Hansen, P.C., Analysis of discrete ill-posed problems by means of the L-curve. SIAM review, 1992. 34(4): p. 561-580.

Metrics
Usage Shares
Total Views
20 Page Views
Total Shares
0 Tweets
20
0 PDF Downloads
0
0 Facebook Shares
Total Usage
20