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A refined Frequency Domain Decomposition tool for structural modal monitoring in earthquake engineering 被引量:2
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作者 Fabio Pioldi Egidio Rizzi 《Earthquake Engineering and Engineering Vibration》 SCIE EI CSCD 2017年第3期627-648,共22页
Output-only structural identification is developed by a refined Frequency Domain Decomposition(rFDD) approach, towards assessing current modal properties of heavy-damped buildings(in terms of identification challe... Output-only structural identification is developed by a refined Frequency Domain Decomposition(rFDD) approach, towards assessing current modal properties of heavy-damped buildings(in terms of identification challenge), under strong ground motions. Structural responses from earthquake excitations are taken as input signals for the identification algorithm. A new dedicated computational procedure, based on coupled Chebyshev Type Ⅱ bandpass filters, is outlined for the effective estimation of natural frequencies, mode shapes and modal damping ratios. The identification technique is also coupled with a Gabor Wavelet Transform, resulting in an effective and self-contained time-frequency analysis framework. Simulated response signals generated by shear-type frames(with variable structural features) are used as a necessary validation condition. In this context use is made of a complete set of seismic records taken from the FEMA P695 database, i.e. all 44 "Far-Field"(22 NS, 22 WE) earthquake signals. The modal estimates are statistically compared to their target values, proving the accuracy of the developed algorithm in providing prompt and accurate estimates of all current strong ground motion modal parameters. At this stage, such analysis tool may be employed for convenient application in the realm of Earthquake Engineering, towards potential Structural Health Monitoring and damage detection purposes. 展开更多
关键词 Operational Modal Analysis (OMA) modal dynamic identification refined frequency Domain Decomposition(rFDD) FEMA P695 seismic database earthquake response identification input
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High-Precision Vital Signs Detection Method Based on Spectrum Refinement and Extended DCMA 被引量:1
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作者 Mingxu Xiang Wu Ren +1 位作者 Weiming Li Zhenghui Xue 《Journal of Beijing Institute of Technology》 EI CAS 2022年第1期101-111,共11页
In this paper,the spectral estimation algorithm is extended to the detection of human vi-tal signs by mm-wave frequency modulated continuous wave(FMCW)radar,and a comprehensive algorithm based on spectrum refinement a... In this paper,the spectral estimation algorithm is extended to the detection of human vi-tal signs by mm-wave frequency modulated continuous wave(FMCW)radar,and a comprehensive algorithm based on spectrum refinement and the extended differentiate and cross multiply al-gorithm(DCMA)has been proposed.Firstly,the improved DFT algorithm is used to accurately obtain the distance window of human body.Secondly,phase ambiguity in phase extraction is avoided based on extended DCMA algorithm.Then,the spectrum range of refinement is determ-ined according to the peak position of the spectrum,and the respiratory and heartbeat frequency information is obtained by using chirp z-transform(CZT)algorithm to perform local spectrum re-finement.For verification,this paper has simulated the radar echo signal modulated by the simu-lated cardiopulmonary signal according to the proposed algorithm.By recovering the simulated car-diopulmonary signal,the high-precision respiratory and heartbeat frequency have been obtained.The results show that the proposed algorithm can effectively restore human breathing and heart-beat signals,and the relative error of frequency estimation is basically kept below 1.5%. 展开更多
关键词 vital signs detection frequency modulated continuous wave(FMCW)radar frequency spectrum refinement high-precision frequency estimation
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