scholarly journals Phase Reconstruction for Time-Frequency Inpainting

2018 ◽  
pp. 417-426
Author(s):  
A. Marina Krémé ◽  
Valentin Emiya ◽  
Caroline Chaux
Keyword(s):  
Phase Reconstruction ◽  
Time Frequency

scholarly journals Quantifying the Opportunity Limits of Automatic Residential Electric Load Shaping

Energies ◽  
2019 ◽  
Vol 12 (17) ◽  
pp. 3204
Author(s):  
Robert Cruickshank ◽  
Gregor Henze ◽  
Rajagopalan Balaji ◽  
Bri-Mathias Hodge ◽  
Anthony Florita
Keyword(s):  
Energy Use ◽  
Time Series Data ◽  
Supply And Demand ◽  
Electric Utility ◽  
Series Data ◽  
Stochastic Methods ◽  
Electric Load ◽  
Phase Reconstruction ◽  
Time Frequency ◽  
Reconstruction Methods

Electric utility residential demand response programs typically reduce load a few times a year during periods of peak energy use. In the future, utilities and consumers may monetarily and environmentally benefit from continuously shaping load by alternatively encouraging or discouraging the use of electricity. One way to shape load and introduce elasticity is to broadcast forecasts of dynamic electricity prices that orchestrate electricity supply and demand in order to maximize the efficiency of conventional generation and the use of renewable resources including wind and solar energy. A binary control algorithm that influences the on and off states of end uses was developed and applied to empirical time series data to estimate price-based instantaneous opportunities for shedding and adding electric load. To overcome the limitations of traditional stochastic methods in quantifying diverse, non-Gaussian, non-stationary distributions of observed appliance behaviour, recent developments in wavelet-based analysis were applied to capture and simulate time-frequency domain behaviour. The performance of autoregressive and spectral reconstruction methods was compared, with phase reconstruction providing the best simulation ensembles. Results show spatiotemporal differences in the amount of load that can be shed and added, which suggest further investigation is warranted in estimating the benefits anticipated from the wide-scale deployment of continuous automatic residential load shaping. Empirical data and documented software code are included to assist in reproducing and extending this work.

Fractional Fourier Transform Image Analysis

2012 ◽  
Vol 198-199 ◽  
pp. 288-293
Author(s):  
Hui Yan Xu
Keyword(s):  
Fourier Transform ◽  
Frequency Domain ◽  
Fractional Fourier Transform ◽  
Point Of View ◽  
Fourier Domain ◽  
Phase Reconstruction ◽  
Time Frequency ◽  
Space Frequency ◽  
The Fourier Transform ◽  
Simulation Point

As a generalized form of the Fourier transform, fractional Fourier transform (FRFT) ,which is integrated the signal in time domain and frequency domain, is a new time-frequency analysis. From the simulation point of view to image the distribution of energy in the fractional Fourier domain, the amplitude and phase characteristics, simulation results show that any fractional Fourier domain, can reflect the image of the space-frequency domain characteristics, with the order, the image The distribution of the space-frequency domain characteristics will change. The image of the fractional Fourier transform amplitude and phase reconstruction of the image information with the original image also showed some important conclusions for the fractional Fourier transform applied to image recognition and edge detection is of great significance.

A Fault Detection Approach Based on Sound Signal Analysis for Equipment Monitoring

2020 ◽  
pp. 129-139
Author(s):  
Weihai Sun ◽  
Lemei Han
Keyword(s):  
Fault Detection ◽  
Signal Analysis ◽  
Energy Analysis ◽  
Detection Method ◽  
Sound Signal ◽  
Practical Significance ◽  
Time Frequency ◽  
Detection Approach ◽  
Machine Fault ◽  
Learning Data

Machine fault detection has great practical significance. Compared with the detection method that requires external sensors, the detection of machine fault by sound signal does not need to destroy its structure. The current popular audio-based fault detection often needs a lot of learning data and complex learning process, and needs the support of known fault database. The fault detection method based on audio proposed in this paper only needs to ensure that the machine works normally in the first second. Through the correlation coefficient calculation, energy analysis, EMD and other methods to carry out time-frequency analysis of the subsequent collected sound signals, we can detect whether the machine has fault.

An Absolute Phase Estimation Method for Interferometry Imagery

2019 ◽  
Vol 1 (2) ◽  
pp. 14-19
Author(s):  
Sui Ping Lee ◽  
Yee Kit Chan ◽  
Tien Sze Lim
Keyword(s):  
Noise Suppression ◽  
Estimation Method ◽  
Phase Image ◽  
Phase Estimation ◽  
Phase Reconstruction ◽  
Estimation Algorithms ◽  
Absolute Phase ◽  
Filtering Rate ◽  
Interferometric Phase ◽  
Image Performance

Accurate interpretation of interferometric image requires an extremely challenging task based on actual phase reconstruction for incomplete noise observation. In spite of the establishment of comprehensive solutions, until now, a guaranteed means of solution method is yet to exist. The initially observed interferometric image is formed by 2π-periodic phase image that wrapped within (-π, π]. Such inverse problem is further corrupted by noise distortion and leads to the degradation of interferometric image. In order to overcome this, an effective algorithm that enables noise suppression and absolute phase reconstruction of interferometric phase image is proposed. The proposed method incorporates an improved order statistical filter that is able to adjust or vary on its filtering rate by adapting to phase noise level of relevant interferometric image. Performance of proposed method is evaluated and compared with other existing phase estimation algorithms. The comparison is based on a series of computer simulated and real interferometric data images. The experiment results illustrate the effectiveness and competency of the proposed method.

Time-Frequency Analysis of Partial Discharge Phenomena in SF6 gas using Wavelet Transform

1997 ◽  
Vol 117 (3) ◽  
pp. 338-345 ◽  
Author(s):  
Masatake Kawada ◽  
Masakazu Wada ◽  
Zen-Ichiro Kawasaki ◽  
Kenji Matsu-ura ◽  
Makoto Kawasaki
Keyword(s):  
Wavelet Transform ◽  
Frequency Analysis ◽  
Partial Discharge ◽  
Time Frequency Analysis ◽  
Time Frequency
Sign in / Sign up

Export Citation Format

Share Document