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基于改进同步挤压小波变换识别信号瞬时频率
引用本文:刘景良,郑锦仰,郑文婷,黄文金. 基于改进同步挤压小波变换识别信号瞬时频率[J]. 振动、测试与诊断, 2017, 37(4): 814-821
作者姓名:刘景良  郑锦仰  郑文婷  黄文金
作者单位:(1. 福建农林大学交通与土木工程学院,福州350002)(2. 福建工程学院土木工程学院,福州350118)
基金项目:国家自然科学基金资助项目(51608122);福建省自然科学基金青年科技人才创新资助项目(2016J05111);福建省教育厅科技资助项目(JAT160330)
摘    要:提出了改进同步挤压小波变换。首先,采用解析模态分解定理将非平稳响应信号分解为多个单分量信号;其次,通过频率转换将分解后的单分量信号从低频区域转换到高频区域以提高时间分辨率;然后,对频率重点关注区域的时频代表值进行局部挤压,提高时频曲线的频率精度;最后,通过两个数值算例和一个拉索试验验证了改进同步挤压小波变换方法的有效性和准确性。研究结果表明,改进同步挤压小波变换能够提高信号在特定区域内的瞬时频率识别精度,是一种可行的时变结构参数识别方法。

关 键 词:改进同步挤压小波变换;瞬时频率;时变结构;时频分析;非平稳信号

Instantaneous Frequency Identification of Signals Based on Improved Synchrosqueezing Wavelet Transform
LIU Jingliang,ZHENG Jinyang,ZHENG Wenting,HUANG Wenjin. Instantaneous Frequency Identification of Signals Based on Improved Synchrosqueezing Wavelet Transform[J]. Journal of Vibration,Measurement & Diagnosis, 2017, 37(4): 814-821
Authors:LIU Jingliang  ZHENG Jinyang  ZHENG Wenting  HUANG Wenjin
Affiliation:(1.School of Transportation and Civil Engineering, Fujian Agriculture and Forestry University Fuzhou, 350002, China)(2.School of Civil Engineering, Fujian University of Technology Fuzhou, 350118, China)
Abstract:Synchrosqueezing wavelet transform can get better frequency resolution by reassigning the time-frequency representation of wavelet transform. However, the diffusion along frequency domain can be suppressed while the diffusion along the time axis cannot be overcome. To address this issue, an improved synchrosqueezing wavelet transform is employed to enhance the accuracy of estimated instantaneous characteristic parameters in both time and frequency directions where we highly focus on. Two numerical simulations and a cable test with linearly and sinusoidal varying tension forces are used to verify the effectiveness and accuracy of the proposed method. The results demonstrate that the improved synchrosqueezing wavelet transform is appropriate for identifying parameters of time-varying structures with both better time and frequency resolutions in a specific region.
Keywords:improved synchrosqueezing wavelet transform   instantaneous frequency   time-varying structure   time-frequency analysis   non-stationary signal
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