A modified wavelet energy rate-based damage identification method for steel bridges

Strain is sensitive to damage, especially in steel structures. However, a traditional strain gauge does not t bridge damage identification because it only provides the strain information of the point, where it is set up. While traditional strain gauges suffer from drawbacks, a long-gage FBG strain sensor is capable of providing the strain information of a certain range, in which all the damage information within the sensing range can be re ected by the strain information provided by FBG sensors. The wavelet transform is a new way to analyze the signals, capable of providing multiple levels of details and approximations of the signal. In this paper, a wavelet packet transform-based damage identification is proposed to identify the steel bridge damage numerically and with experimentally to validate the proposed method. The strain data obtained via long-gage FBG strain sensors are transformed into a modified wavelet packet energy rate index rst to identify the location and severity of damage. The results of numerical simulations show that the proposed damage index is a good candidate that is capable of identifying both the location and severity of damage under noise effect.