Increasing the importance of infrastructures demands an effective and timely structural health monitoring (SHM) systems. In this regard, the current study focuses on improving a two-stage MSE-based damage detection method to accurately detect and quantify the damage in bridges.
The improved MSE method for detecting the structural damage has two consequent stages, stage one, locating the damage, and stage two, quantifying the damage. The crucial key for identifying the location of damage in the structure is to calculate the elemental MSE change of the structure before and after the damage. Therefore, initially, an elemental MSE and a sensitivity matrix were mathematically established. Then, an elemental MSE-based indicator was used to show the ratio of the MSE change for each element.
The elements with the higher amount of MSE change ratio are the most likely elements to be damaged and are nominated for further investigation in the second stage. Sensitivity matrix was used to quantify the damage which is a matrix derived from MSE change with respect to extent of the damage as an unknown independent variable. To validate the improved method, numerical studies were performed on some structures including, a fixed-end beam, a three-story frame, a steel truss bridge and a concrete bridge frame model. Consequently, experimental verifications were conducted on a simply supported beam, a cantilever beam and a three-story steel frame model.
To examine the application of the improved method to a real model also, it was applied to the 4-DOF three-story structure of Los Alamos National Laboratory (LANL). Finally, to observe the applicability of the improved method in reality, it was applied to the I-40 Bridge in New Mexico; the USA using the available data. The results showed the capability of the proposed method. The research findings will contribute to academic studies and bridge industry to minimize the loss of lives and property by identifying the structural damages.
Funding / Grants
- Queensland University of Technology Postgraduate Research Award (QUTPRA), the QUT Science and Engineering Scholarship and Science and Engineering Faculty Top Up, and the Research Studentship of the Hong Kong Polytechnic University (PolyU).
Other Team Members
- Parviz Moradi Pour
- Professor Y.Q. Ni
- Dr Chaminda Gallage