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adaptive modal identification of structures with equivariant adaptive separation via independence approach

JOURNAL OF SOUND AND VIBRATION 2018年 413卷 66-78页

作者： Amini, Fereidoun Ghasemi, Vida Univ Sci & Technol Sch Civil Engn Tehran Iran

An efficient output-only Blind Source separation (BSS) method was recently introduced for the modal identification of structures. BSS procedures recover a set of independent sources from their unknown linear mixtures when only mixtures are observed. Batch data is required for the separation in traditional blind source separation methods. These algorithms are however unfavorable, as some sets of data are observed one after another. In this paper, an adaptive blind source separation technique - equivariant adaptive separation via independence (EASI) - is introduced to overcome the mentioned disadvantage within the structures. The EASI algorithm is beneficial as it can provide solutions to real time problems, while also update the un-mixing matrix for each step. EASI not only avoids increases in size of the relevant matrices and vectors, but also decreases the analysis time. A synthetic example and a benchmark structure have been used in this paper to better investigate the efficiency of the proposed method. The simulation results demonstrate the effectiveness of the EASI algorithm in on-line identification of modal parameters of structures. (C) 2017 Published by Elsevier Ltd.

关键词： adaptive blind source separation equivariant adaptive separation via independence algorithm Modal identification Output-only system identification

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Online structural identification by Teager Energy Operator and blind source separation

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SMART STRUCTURES AND SYSTEMS 2020年第2期26卷 135-146页

作者： Ghasemi, Vida Amini, Fereidoun Iran Univ Sci & Technol Dept Civil Engn Tehran Iran

This paper deals with an application of adaptive blind source separation (BSS) method, equivariant adaptive separation via independence (EASI), and Teager Energy Operator (TEO) for online identification of structural modal parameters. The aim of adaptive BSS methods is recovering a set of independent sources from their unknown linear mixtures in each step when a new sample is received. In the proposed approach, firstly, the EASI method is used to decompose structural responses into independent sources at each instance. Secondly, the TEO based demodulation method with discrete energy separation algorithm (DESA-1) is applied to each independent source, and the instantaneous frequencies and damping ratios are extracted. The DESA-1 method can provide the fast time response and has high resolution so it is suitable for online problems. This paper also compares the performance of DESA-1 algorithm with Hilbert transform (HT) method. Compared to HT method, the DESA-1 method requires smaller amounts of samples to estimate and has a smaller computational complexity and faster adaption due to instantaneous characteristic. Furthermore, due to high resolution of the DESA-1 algorithm, it is very sensitive to noise and outliers. The effectiveness of the proposed approach has been validated using synthetic examples and a benchmark structure.

关键词： adaptive blind source separation discrete energy separation algorithm equivariant adaptive separation via independence algorithm online structural identification Teager-Energy Operator

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