Modal Parameter Identification Of The Tank Platform

With the rapid development of the sea oil exploration, more and more oil tank platforms have been built in China. Monitoring the dynamic characteristics (modal parameters) is very important to mitigate the vibrations, detect the damages and evaluate the safety of the oil tank platform. The traditional methods of modal identification with artificial excitations have some limitations to large scale civil structures. Recently, more and more attentions have been paid to the modal parameter identification with ambient vibrations because it does not interrupt the normal operation of the monitored structure. However, the existing methods cannot effectively eliminate the spurious modes in modal parameter identification. In this study, the non-convergent property of the backward correlation functions was proposed to identify the system eigen-parameters. By using of the relationship between the magnitudes of the eigen-values and the unit circle, a method to eliminate the spurious modes was presented. The proposed algorithm was used to identify the modal parameters of the oil tank platform.The currently-used methods of modal identification were briefly summarized in the dissertation. The dynamic characteristics of the CB32A oil tank platform were studied by numerical simulations. The 3-D finite element model of the CB32A oil platform was built with different boundary conditions:elastic constraint, equivalent constraint and fixed constraint. The theoretically modal analysis was performed to obtain the dynamic characteristics of the oil tank platform. The transient analysis was also carried out to get the time history responses of the structure. Then the numerical results were simulated as the measured data for the following modal identification.Base on the equivalent relationship between the dynamic equation and state equation of the output vector, an auto-regressive model of the backward correlation function was built. The dynamic properties of the system as well as the convergence of the eigen-values were used to identify the systemic eigen-parameters. Then the spurious eigen-values were eliminated. The systemic modal parameters were correspondingly computed with the systemic eigen-parameters. The proposed method was used to identify the modal parameters of the CB32A oil tank platform. And the stochastic subspace identification (SSI) was compared with the proposed method. The results show the proposed method can effectively identify the systemic modal parameters of the oil tank platform.