Development of Features for Early Detection of Defects and Assessment of Bridge Decks
Ahmed Silik, Xiaodong Wang, Chenyue Mei, Xiaolei Jin, Xudong Zhou, Wei Zhou, Congning Chen, Weixing Hong, Jiawei Li, Mingjie Mao, Yuhan Liu, Mohammad Noori, Wael A. Altabey
Abstract
Damage detection is an important area with growing interest in mechanical and structural engineering. One of the critical issues in damage detection is how to determine indices sensitive to the structural damage and insensitive to the surrounding environmental variations. Current damage identification indices commonly focus on structural dynamic characteristics such as natural frequencies, mode shapes, and frequency responses. This study aimed at developing a technique based on energy Curvature Difference, power spectrum density, correlation-based index, load distribution factor, and neutral axis shift to assess the bridge deck condition. In addition to tracking energy and frequency over time using wavelet packet transform, in order to further demonstrate the feasibility and validity of the proposed technique for bridge condition assessment, experimental strain data measured from two stages of a bridge in the different intervals were used. The comparative analysis results of the bridge in first and second stage show changes in the proposed feature values. It is concluded, these changes in the values of the proposed features can be used to assess the bridge deck performance.