瞬时相位
噪音(视频)
情态动词
窄带
希尔伯特变换
控制理论(社会学)
模式(计算机接口)
系列(地层学)
算法
频道(广播)
计算机科学
时频分析
希尔伯特-黄变换
光谱密度
白噪声
人工智能
电信
图像(数学)
操作系统
生物
古生物学
化学
高分子化学
雷达
控制(管理)
作者
Shuaishuai Liu,Rui Zhao,Kaiping Yu,Baopeng Liao,Bowen Zheng
标识
DOI:10.1177/10775463221109699
摘要
Operational modal identification of time-varying systems plays a crucial role in assessing the health condition and controlling the dynamic properties of engineering structures. However, only the response is measurable, making it challenging. Based on the variational mode decomposition (VMD) theory, this paper presents a short-time multivariate or multi-channel VMD (STMVMD) method for instantaneous frequency (IF) identification of time-varying structures in the case of output-only measurements. The idea of short-time windows overcomes the shortcoming of many VMD-based methods that employ the narrowband assumption of intrinsic mode functions (IMFs) and cannot decompose non-stationary signals involving closely-spaced wideband IMFs. After obtaining the multivariate IMFs by STMVMD, an average scheme is employed to estimate IFs, reducing the noise sensitivity of Hilbert Transform. Moreover, by tracking the center frequencies of STMVMD at different moments, another more noise-robust IF estimation method is also presented. A series of numerical and experimental examples illustrate the advantages of the proposal.
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