A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Simulation studies of damage location in Tsing Ma Bridge deck
This paper addresses the identification of damage region and location in the Tsing Ma Suspension Bridge deck using modal data. A two-stage identification method is proposed and implemented through numerical simulation for damage detection of the bridge deck. In the first stage, the main span deck of 1377 m length is divided into seventy-six segments and the target in this stage is to determine the deck segment that contains damaged member(s). An index vector derived from mode shape curvatures in both intact and damaged states is presented to identify the damage region (segment). In the second stage, the specific damaged member(s) within the damage region is identified by means of a neural network technique. The combined modal parameters in terms of natural frequencies and a few incomplete modal vectors are adopted as input vector to the neural networks. Two back-propagation networks are trained for the damage location detection. The simulation results show that despite very low modal sensitivity of the bridge to deck member damage, the developed method can still locate the damage at longitudinal structural members such as bottom chords, top chords, and diagonal members.
Simulation studies of damage location in Tsing Ma Bridge deck
This paper addresses the identification of damage region and location in the Tsing Ma Suspension Bridge deck using modal data. A two-stage identification method is proposed and implemented through numerical simulation for damage detection of the bridge deck. In the first stage, the main span deck of 1377 m length is divided into seventy-six segments and the target in this stage is to determine the deck segment that contains damaged member(s). An index vector derived from mode shape curvatures in both intact and damaged states is presented to identify the damage region (segment). In the second stage, the specific damaged member(s) within the damage region is identified by means of a neural network technique. The combined modal parameters in terms of natural frequencies and a few incomplete modal vectors are adopted as input vector to the neural networks. Two back-propagation networks are trained for the damage location detection. The simulation results show that despite very low modal sensitivity of the bridge to deck member damage, the developed method can still locate the damage at longitudinal structural members such as bottom chords, top chords, and diagonal members.
Simulation studies of damage location in Tsing Ma Bridge deck
Ni, Yi-Qing (author) / Wang, Bai S. (author) / Ko, Jan Ming (author)
Nondestructive Evaluation of Highways, Utilities, and Pipelines IV ; 2000 ; Newport Beach,CA,USA
Proc. SPIE ; 3995
2000-06-09
Conference paper
Electronic Resource
English
Vibration Measurement of Tsing Ma Bridge Deck Units during Erection
| British Library Conference Proceedings | 1998
Dynamic Tests on a Deck Module of Tsing Ma Bridge
| British Library Conference Proceedings | 1996
Tsing Ma bridge deck under skew winds-Part I: Aerodynamic coefficients
| Online Contents | 2002
Tsing Ma bridge deck under skew winds-Part II: flutter derivatives
| Online Contents | 2002
Vibration Studies of Tsing Ma Suspension Bridge
| Online Contents | 1997