Sliding discrete Fourier transform-based mono-component amplitude modulation–frequency modulation signal decomposition

2015 ◽  
Vol 9 (9) ◽  
pp. 1221-1229 ◽  
Author(s):  
Parasuraman Sumathi ◽  
Ksh Milan Singh
Keyword(s):  
Fourier Transform ◽  
Discrete Fourier Transform ◽  
Amplitude Modulation ◽  
Frequency Modulation ◽  
Modulation Frequency ◽  
Signal Decomposition ◽  
Modulation Signal ◽  
Component Amplitude

The Stochastic Resonance of Noise Frequency Modulation Signal Using Motion-Group Fourier Transform

2015 ◽  
Vol 713-715 ◽  
pp. 1452-1455
Author(s):  
Jing Bo He ◽  
Sheng Liang Hu
Keyword(s):  
Signal Processing ◽  
Fourier Transform ◽  
Stochastic Resonance ◽  
Frequency Modulation ◽  
Planck Equation ◽  
Motion Group ◽  
Noise Frequency ◽  
Modulation Signal ◽  
Group Fourier Transform ◽  
Linear Differential

In this paper stochastic resonance was studied in radar driven by noise frequency modulation signal. According to the intrinsic relations between the stochastic differential and the radar jamming signal processing, the stochastic calculus was used in the radar jamming signal processing in this paper. The noise frequency modulation signal was particularly analyzed. The Fokker-Planck equation of noise frequency modulation was presented and the Motion-Group Fourier Transform was used by converting the partial differential equation into the variable coefficient homogenous linear differential equations. Then the solutions were given.

Probing the Adsorption of Weak Acids on Graphite Using Amplitude Modulation–Frequency Modulation Atomic Force Microscopy

Langmuir ◽  
2015 ◽  
Vol 31 (10) ◽  
pp. 3069-3075 ◽  
Author(s):  
Ahmed M. A. Moustafa ◽  
Jun Huang ◽  
Kerry N. McPhedran ◽  
Hongbo Zeng ◽  
Mohamed Gamal El-Din
Keyword(s):  
Atomic Force Microscopy ◽  
Amplitude Modulation ◽  
Frequency Modulation ◽  
Modulation Frequency ◽  
Weak Acids ◽  
Force Microscopy ◽  
Atomic Force

scholarly journals Application of VMD and Hilbert Transform Algorithms on Detection of the Ripple Components of the DC Signal

Energies ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 935 ◽  
Author(s):  
Derong Luo ◽  
Ting Wu ◽  
Ming Li ◽  
Benshun Yi ◽  
Haibo Zuo
Keyword(s):  
Fourier Transform ◽  
Direct Current ◽  
Hilbert Transform ◽  
Amplitude Modulation ◽  
Modulation Frequency ◽  
Variational Mode Decomposition ◽  
Instantaneous Amplitude ◽  
Modal Number ◽  
Dc Power ◽  
Mode Decomposition

Accurate detection of ripple components of the direct-current (DC) signals is essential for evaluating DC power quality. In this study, the combination algorithm based on variational mode decomposition (VMD) and Hilbert transform (HT) is applied to detect and analyze the characteristics of the ripple components of the DC disturbance signals. Firstly, the optimal modal number of VMD algorithms is comprehensively determined by observing the center frequencies of the mode components and the Index of Orthogonality (IO) of mode components. Through utilizing the VMD algorithm, the DC disturbance signal is accurately decomposed into a series of amplitude modulation-frequency modulation (AM-FM) functions. Then, the HT algorithm is applied to each AM-FM function to obtain the corresponding instantaneous amplitude and frequency, and the characteristics of DC disturbance signal are determined. Some case studies are implemented to analyze the ripple components of the DC disturbance signal with the VMD-HT and empirical mode decomposition (EMD) algorithm. Finally, the experiment results of Gree Photovoltaic Cabin have verified the feasibility and effectiveness of the proposed combination VMD-HT algorithm by comparison with EMD and the window interpolation fast Fourier transform (WIFFT) algorithms.

Rolling Element Defect Diagnosis Based on Local Mean Decomposition

2011 ◽  
Vol 117-119 ◽  
pp. 33-37 ◽  
Author(s):  
Tian He ◽  
Xian Dong Liu ◽  
Ying Chun Shan ◽  
Qiang Pan
Keyword(s):  
Fourier Transform ◽  
Amplitude Modulation ◽  
Simulation Analysis ◽  
Vibration Signals ◽  
Local Mean Decomposition ◽  
Spectrum Method ◽  
Rolling Element ◽  
Modulation Signal ◽  
Local Mean ◽  
Envelope Spectrum

A method to extract rolling element fault characteristics from fault signal, based on local mean decomposition (LMD) and Fourier transform (FT), is introduced in this study. The LMD’s characteristics are obtained by processing multi-component frequency and amplitude modulation signal, which are usually used to describe the bearing fault signals. Base on the simulation analysis, the envelope spectrum method called LMD-FT is presented to deal with the vibration signals of rolling balling bearing with element fault. The results show that the rolling element defect can be diagnosed by LMD-FT effectively

A 2D amplitude-modulation frequency-modulation representation for motion estimation

2016 ◽  
Author(s):  
Victor Murray ◽  
Alvaro Dasso ◽  
Juan Llanos ◽  
Paul Rodriguez ◽  
Marios S. Pattichis
Keyword(s):  
Motion Estimation ◽  
Amplitude Modulation ◽  
Frequency Modulation ◽  
Modulation Frequency
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