Modal Analysis And Application Of The Structure Based On Blind Source Separation

Civil engineering structures are an essential part in our lives.However,due to the various impact from the outside and their own,the ability to against disasters would decrease which may cause accidents and economic losses.So taking some effective measures to make modal analysis for the structures is essential.Currently, the system identification has become one of the core issues of health monitoring technology. As an important means of structural dynamic charateristic studies, modal analysis is a specific application in the field of vibration engineering. This paper mainly used Blind Source Separation technique to make modal analysis.Thus, new effective means would been provided to make modal parameter identification under ambient excitation in civil engineering. The main works and studies are summarized as follows:1.The background and research status of modal parameter identification and the wide application prospect of BSS have been introuduced.The model and key technologies of BSS have been described in detail; then some typical algorithms of BSS were introduced: the basci theory of FastICA based on negative entropy、Joint anti-diagonalization——second-order blind identification algorithm、BSS algorithm based on the maximum SNR.2.The method of modal parameter identification based on BSS have been proposed. The relationship between the system response model and modal coordinates of BSS have been discussed in detail, and the basic principle of MDOF(Hilbert) has been introduced. The basic methods and procedures of modal parameter identification applied BSS have been summarized. Numerical experiments of a discrete system of three masses have been carried out respectively to support the previous theoretical findings. The results showed that these three algorithms can extract source signal from random vibration response exactly.3.In order to verify the practicability of BSS,the random response datas of three-tier framework from one US lab have been identified, and the source singles have been extracted successfully. Then, to verify the robustness against noise of different algorithm, the free response signals with different proportionate noise have been identified by BSS. The results showed that SOBI algorithm’s robustness against noise is better than FastICA and SNRMax.