Damage detection of bridge structure based on SVM

Abstract

For bridge management and maintenance, it is important to detect the damage of bridge pier. Due to the complexity of damage detection, an effective method is very interesting. Support vector machine (SVM) is used to detect the damage of bridge pier in this paper. To improve the detection accuracy of SVM, Grubbs' test method is adopted to delete the outliers for SVM. Then, a numerical analysis is used to determine the input parameters for SVM. Lastly, the comparison results between the proposed SVM and the actual measure value suggested that the proposed SVM is a powerful tool for detecting damage of bridge pier. © 2013 Yaojin Bao et al.