Lower-order modal parameters identification for offshore jacket platform using reconstructed responses to a sea test

Usually only a few of lower-order modes of interest extracted from stochastic response under the excitation of environmental forces, such as waves, winds or ice, could be obtained from sea tests of offshore jacket platforms; and what is more serious, this lower-order modal information is often buried in noises, which will be a challenge for identifying the modal parameters of interest. In this article, we propose an improved modal parameter identification method by reconstructing a new response consisting of only lower-order frequencies, and apply this method to a real offshore jacket platform located in the north of Liaodong Bay, China. One theoretical contribution is that the fainter modes could be isolated as one expected by defining reasonable pass band width and centering frequency. The elimination of noisy modes is realized by reconstructing the Eigensystem Realization Algorithm (ERA) block data matrix using the reconstructed responses. The other contribution is that the difficulty in judging whether an identified mode is due to noise or a genuine one has been resolved properly. A numerical offshore jacket platform is chosen to illustrate the procedure and demonstrate the performance of the proposed scheme. Numerical results indicate that: (1) lower-order frequencies can be isolated successfully using FFT filtering, and unexpected peaks in auto spectral density can be removed effectively using our smoothing procedure; (2) modal parameters of interest such as frequencies and damping ratios both can be identified properly by reconstructing Hankel matrix with a small dimension of ERA. Using sea test data measured from accelerometers mounted at the joints of the test platform, we find that our approach outperforms traditional ERA because no noisy modes are introduced. Though traditional ERA could identify two of the first three modal frequencies and damping ratios using the same segment of measured sea data, the dimension of Hankel matrix reaches 1000 times 1000, with a large amount of noisy modes. The achievement may contribute to two research areas: (1) signal processing when fainter frequencies are expected to be isolated, and (2) modal parameters identification when amount of noisy modes exist using traditional methods, such as ERA. Specifically, accuracy and efficiency of modal parameters identification (interested) of offshore jacket platforms can be improved.