唐达

个人信息Personal Information

副教授

硕士生导师

性别:男

毕业院校:大连理工大学

学位:硕士

所在单位:计算机科学与技术学院

电子邮箱:tangda@dlut.edu.cn

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Modal damping ratio analysis of dynamical system with non-stationary responses

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论文类型:期刊论文

发表时间:2016-09-01

发表刊物:APPLIED OCEAN RESEARCH

收录刊物:SCIE、EI、Scopus

卷号:59

页面范围:138-146

ISSN号:0141-1187

关键字:Prototype measurement; FPSO single point mooring system; Independent component analysis; The stationary filter using moving average; Damping ratio identification

摘要:During the long term monitoring of the structure, the damping ratio reflects the characteristics of the structure from perspective of energy loss, and its changes can reflect the structural damages to some extent. But in the structural modal analysis based on the prototype measurement, the damping ratio identification results are difficult to identify, especially for the non-stationary structural responses, besides, ICA loses accuracy in the presence of higher-level damping. In allusion to these problems, a modal identification method based on the stationary filter-time frequency independent component analysis (filter-TFICA) is proposed. First a stationary filter using moving average is used to eliminate the non-stationary components. Then the modal identification of mooring system is incorporated into the blind source separation formulation where TFICA is introduced. The validity of the proposed method is confirmed through the identification of a multi degree of freedom numerical simulation system under non-stationary random excitations. Further, the prototype measurement data of the floating production, storage and offloading (FPSO) single point mooring system are analyzed. Compared with the traditional method, the differences of identified damping ratios at the same frequency range by the proposed method are smaller. The distribution of identified modal frequencies is more scattered and the mutually coupled modes are decoupled well. Each of the calculated motion tracks corresponding to the mode shapes presents single form of motion more prominently. (C) 2016 Elsevier Ltd. All rights reserved.