scholarly journals Background noise estimation of the geomagnetic signal

2018 ◽  
Vol 7 (3) ◽  
pp. 189-193
Author(s):  
Xiuyi Yao ◽  
Suqin Zhang ◽  
Yuntian Teng ◽  
Dongmei Yang
Keyword(s):  
Fourier Transform ◽  
Diurnal Variation ◽  
Spectrum Analysis ◽  
Geomagnetic Field ◽  
Background Noise ◽  
Residual Error ◽  
Noise Estimation ◽  
Estimation Result ◽  
Polynomial Degree ◽  
Main Component

Abstract. A fast Fourier transform was applied to fit the geomagnetic diurnal variation. Fitting results showed that when the polynomial degree was greater than 160, the residual error was close to 0 nT. White noise is the main component of the residual error when the polynomial degree was greater than 160, so this method was adopted to calculate the background noise of the geomagnetic field. Spectrum analysis further demonstrated that the noise estimation result is reliable.

scholarly journals Background noise estimation of geomagnetic signal

2018 ◽  
Author(s):  
Xiuyi Yao ◽  
Suqin Zhang ◽  
Yuntian Teng ◽  
Dongmei Yang
Keyword(s):  
Fourier Transform ◽  
Fast Fourier Transform ◽  
Diurnal Variation ◽  
Spectrum Analysis ◽  
Geomagnetic Field ◽  
Background Noise ◽  
Residual Error ◽  
Polynomial Degree ◽  
Geomagnetic Data ◽  
Main Component

Abstract. A fast Fourier transform was applied to fit the geomagnetic diurnal variation. Fitting results showed that when the polynomial degree was greater than 160, the residual error was close to 0 nT. White noise is the main component of the residual error when the polynomial degree was greater than 160, so this method was adopted to calculate the background noise of the geomagnetic field. Spectrum analysis further demonstrated the necessity to remove background noise from geomagnetic data.

Research on Shearer Rocker Gearbox Fault Location Based on Wavelet Envelope Demodulation

2014 ◽  
Vol 528 ◽  
pp. 210-216
Author(s):  
Zeng Qiang Wang ◽  
Hong Wei Ma ◽  
Mei Hua Tao ◽  
Xu Hui Zhang ◽  
Qing Hua Mao
Keyword(s):  
Fourier Transform ◽  
Frequency Spectrum ◽  
Spectrum Analysis ◽  
Fault Location ◽  
Vibration Signal ◽  
Morlet Wavelet ◽  
Frequency Spectrum Analysis ◽  
Mechanical Faults ◽  
Faults Diagnosis ◽  
Feature Frequency

To solve the problem of faults location for shearer rocker gearbox, the multiple sites vibration signal of faulty rocker gearbox are collected, as well as the Morlet wavelet envelope demodulation is applied to demodulate vibration signal and Fourier transform is used to carry out frequency spectrum analysis of vibration signal. Experimental results show that this method can effectively extract the faults feature frequency from complex vibration signal. The faults location result is consistent with actual faults part. This mean realizes to locate faults accurately. It provides an effective method for mechanical faults diagnosis of shearer.

Wave Spectrum Analysis of Kerry Deepwater Port Sea in Cameroon

2014 ◽  
Vol 638-640 ◽  
pp. 1280-1284
Author(s):  
Hui Xiao ◽  
Yi Feng Zhang ◽  
Hong Bo Zhao
Keyword(s):  
Fourier Transform ◽  
Spectrum Analysis ◽  
Wave Spectrum ◽  
Transform Method ◽  
Long Period ◽  
Fast Fourier Transform Method ◽  
Spectrum Characteristics ◽  
One Year ◽  
Sea Area ◽  
Period Wave

According to the measured wave data for one year in Kerry deepwater port sea area, Cameroon, the wave spectrum characteristics calculate using fast Fourier transform method; the result shows that the bimodal spectrum is given priority to this sea area, and the big wave appears in summer and autumn, the long period wave influence is opposite bigger that should be pay attention.

Comments on Errors of DFT Spectrum

2014 ◽  
Vol 568-570 ◽  
pp. 189-192
Author(s):  
Feng Han ◽  
Yao Lin Liu ◽  
Zhen Liu ◽  
Hai Dong Zeng
Keyword(s):  
Fourier Transform ◽  
Error Analysis ◽  
Energy Loss ◽  
Discrete Fourier Transform ◽  
Spectrum Analysis ◽  
Analytical Error ◽  
Error Estimators ◽  
Asynchronous Sampling ◽  
Parseval’S Theorem ◽  
Further Development

Discrete Fourier transform (DFT/FFT) spectrums contain a variety of inherent errors in asynchronous sampling. Spectrum analysis with the accuracy above 10-3 are generally challenging issues. This work divides the DFT procedure into four signal transforms and exams six spectrum errors originated from these distortions. Besides the review of traditional errors, a so-called energy loss-gain (ELG) error is briefly introduced, which is proved to be a considerable error on the basis of Parseval's theorem. With the help of full error analysis mentioned here and the further development of analytical error estimators, it is expectable to obtain a DFT spectrum with a specified accuracy.

scholarly journals Preparation and Characterization of Chitosan/Agar Blended Films: Part 1. Chemical Structure and Morphology

2012 ◽  
Vol 9 (3) ◽  
pp. 1431-1439 ◽  
Author(s):  
Esam A. El-hefian ◽  
Mohamed Mahmoud Nasef ◽  
Abdul Hamid Yahaya
Keyword(s):  
Fourier Transform ◽  
Electron Microscope ◽  
Scanning Electron Microscope ◽  
Smooth Surface ◽  
Chemical Structure ◽  
Structure And Morphology ◽  
The Individual ◽  
Main Component ◽  
Scanning Electron

Chitosan/agar (CS/AG) films were prepared by blending different proportions of chitosan and agar (considering chitosan as the main component) in solution forms. The chemical structure and the morphology of the obtained blended films were investigated using Fourier transform infrared (FTIR) and field emission scanning electron microscope (FESEM). It was revealed that chitosan and agar form a highly compatible blend and their films displayed homogenous and smooth surface properties compared to the individual pure components.

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