共 50 条
A novel solution for improved performance of Time-frequency concentration
被引:7
|作者:
Guo, Juan
[1
,3
]
Hao, Guocheng
[1
,2
,3
]
Yu, Jiantao
[1
]
Wang, Panpan
[1
]
Jin, Yarui
[1
]
机构:
[1] China Univ Geosci, Sch Mech Engn & Elect Informat, Wuhan 430074, Hubei, Peoples R China
[2] Duke Univ, Dept Math, Durham, NC 27708 USA
[3] Hubei Key Lab Adv Control & Intelligent Automat Co, Wuhan 430074, Peoples R China
关键词:
Non-stationary signals;
short-time fractional Fourier transform;
Synchroextracting transform;
Time-frequency concentration;
Variational mode decomposition;
FRACTIONAL FOURIER-TRANSFORM;
REPRESENTATION;
SIGNALS;
D O I:
10.1016/j.ymssp.2022.109784
中图分类号:
TH [机械、仪表工业];
学科分类号:
0802 ;
摘要:
To improve the time-frequency (TF) concentration performance of the short-time fractional Fourier transform (STFrFT), and solve the multi-order matching problem of multi-component signals, this paper introduces a new algorithm that is referred to as the Variational mode decomposition-short-time fractional Fourier transform-Synchroextracting transform (VSSTFrFT). This work employs the Variational mode decomposition (VMD) algorithm to decompose multi -component signals into single-component sets, then the STFrFT algorithm matches the optimal rotation order of each component separately to solve the multi-order matching problem. Finally, this paper utilizes the Synchroextracting transform (SET) to extract the TF coefficient of ridgeline position in STFrFT distribution, improving the concentration performance. For different types of signals, the VSSTFrFT algorithm can get a higher TF concentration than the traditional TFA methods. In the application of engineering measured data, the VSSTFrFT algorithm can extract the modalities of the signals and display the frequency curve clearly, which can be used for structural complexity and time-varying characteristics analysis in practical engineering applications.
引用
收藏
页数:23
相关论文