scholarly journals PROBABILITY ANALYSIS METHOD BY DISCRETE FAST FOURIER TRANSFORM

Author(s):  
Jun SAKAMOTO ◽  
Yasuhiro MORI ◽  
Takayoshi SEKIOKA
2015 ◽  
Vol 64 (1) ◽  
pp. 29-35 ◽  
Author(s):  
Witold Glowacz ◽  
Zygfryd Glowacz

Abstract In this article results of diagnostic investigations of separately excited DC motor were presented. In diagnostics were applied a Fourier analysis method based on the fast Fourier transform (FFT) and a recognition method using Bayes classifier. In training process a set of the most important frequencies has been determined for which differences of corresponding signals in two states are the largest. Three categories of signals have been recognized in identification process: faultless state, state of the rotor broken one coil and state of the rotor shorted three coils.


2011 ◽  
Vol 28 (2) ◽  
pp. 144-149 ◽  
Author(s):  
Jia Zhu ◽  
Zhangqin Zhu ◽  
Zhongfu Ye

AbstractAnovel profile detection method is proposed for astronomical fiber spectrum data with low signalto-noise ratio. This approach can be applied to the pretreatment for 2-D astronomical spectrum data before the extraction of spectra. The Wigner bispectrum, a classical higher-order spectrum analysis method, is introduced and applied to deal with the spectrumsignal in this article.After analyzing the Wigner higher-order spectra distribution of the target profile signal, the combination of the Wigner bispectrum algorithm and the fast Fourier transform algorithm is used to weaken the effect of the noise to obtain more accurate information. Both the reconstruction method of the Wigner bispectrum and inverse fast Fourier transform are used to acquire the detection signal. At the end of this paper, experiments with both simulated and observed data based on the Large Sky Area Multi-Object Fiber Spectroscopy Telescope project are presented to demonstrate the effectiveness of the proposed method.


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