A Wavelet-energy based damage identification method for steel bridges

Strain is sensitive to damage, especially in steel structures. However, traditional strain gauges do not fit bridge damage identification because they only provide the strain information of the point where they are installed. While traditional strain gauges suffer from some drawbacks, long-gauge FBG strain sensor is capable of providing the strain information of a certain range and all the damage information within the range can be reflected by the strain information provided by FBG sensors. The wavelet transform is a signal processing method to analyze the signals and is capable of providing multiple levels of details and approximations of the signal. In this paper a wavelet packet transform-based damage identification is proposed for the steel bridge damage identifications. The strain data obtained via long-gauge FBG strain sensors are transformed into a modified wavelet packet energy rage index first to identify the location and severity of damage. The results of numerical simulations show that the proposed damage index is a good candidate and is capable of identifying both the location and severity of damage under noise effect.