Damage Detection of Offshore Platforms with Noise Based on HHT and Neural Network

The paper studies the damage detection of jacket-type offshore platform and presents a new detection method based on Hilbert-Huang transform (HHT) and BP neural network (BPNN). We use HHT to decompose dynamical signals based on ANSYS model of offshore platform and get three damage indicators to determine the existence, location and severity of damage. For the damaged offshore platform, to detect damage location and severity, two kinds of neural networks are established using the damage indicators based on ANSYS model. The damage severity indicator is built from part layers of offshore platform instead of all layers. In the simulation part, we utilize a jacket-type offshore platform to verify the designed method. Simulation results show that the method can effectively determine the location and severity of damage when the noise exist. Compared with the method based on wavelet package and BPNN, the proposed method is more robust and efficient.