A structural damage detection approach using train-bridge interaction analysis and soft computing methods

2014 ◽  
Vol 13 (5) ◽  
pp. 869-890 ◽  
Author(s):  
Xingwen He ◽  
Mitsuo Kawatani ◽  
Toshiro Hayashikawa ◽  
Chul-Woo Kim ◽  
F. Necati Catbas ◽  
...  
2016 ◽  
Vol 62 ◽  
pp. 24-44 ◽  
Author(s):  
Amir H. Alavi ◽  
Hassene Hasni ◽  
Nizar Lajnef ◽  
Karim Chatti ◽  
Fred Faridazar

2016 ◽  
Vol 20 (6) ◽  
pp. 896-905 ◽  
Author(s):  
Shaoqing Wu ◽  
Jixiang Zhou ◽  
Sheng Rui ◽  
Qingguo Fei

Structural damage detection method based on modal strain energy usually requires information at every degree of freedom. Due to the limited number of sensors and the difficulty in measuring rotational vibration, modal expansion is often adopted to match the degrees of freedom between the analytical and experimental models, which introduces errors. A novel modal strain energy–based structural damage detection approach is proposed in which the elemental modal strain energy is reformulated with strain modes. The method is introduced on an Euler–Bernoulli beam with uniform cross section. Only strain data are adopted in the newly proposed method and no rotational information of the structure is required. The numerical simulations and experimental validations are conducted to demonstrate the effectiveness of the proposed method. The results show that the proposed method has a better performance than the modal strain energy–based structural damage detection approach with displacement mode and modal expansion technique.


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