| Independent component analysis (ICA) is an innovative method developed in the field of signal processing recently years. This method takes the non-gaussian source signals as the research object and assumes that the signals are statistical independent. Through taking the observed mixed signals to blind source separation (BSS), ICA separate the implicit independent source signals from the mixed signals. This method does not require the prior knowledge of the input and it can conduct the output-only based identification. The independent component analysis technology has got more and more extensive attention in the modal identification of the large-scale complex structures such as bridges.Based on the background of bridge health monitoring, this paper proposes the concept of the damage identification based on vibration and introduces the importance of modal identification in bridge health monitoring and its current research situation.The basic theory of ICA is introduced, including various independence criterions and some popular algorithms. Take a classic dynamic model for research object, four different ICA algorithms are used for model identification based on numerical displacement responses with different damping and noise condition under MATLAB environment. Through the comparison of identification results of the previous four ICA algorithms, take the most stable SOBI algorithm to follow-up study.Respectively by using the finite element software ANSYS and field test, establish a steel-beam model. Use SOBI algorithm for modal identification with the acceleration response data; The results show that the modal dynamic parameters identified by SOBI coincide with the theoretical ones,either the simulation analysis or the field test.Finally, the SOBI algorithm is employed to identify the dynamic characteristic based on the dynamic responses of Hengxiang bridge under environmental excitation, and compare with frequency domain decomposition (FDD) and Stochastic Subspace Identification (SSI). |
PDF Full Text Request