Application Study on Nuclear Radiation Pulse Signal Noise Elimination Using Wavelet Analysis Method

2017 ◽  
Author(s):  
Yong-gang HUO ◽  
Peng XU ◽  
Zhi-yong LU ◽  
Su-fen LI
Keyword(s):  
Wavelet Analysis ◽  
Pulse Signal ◽  
Radiation Pulse ◽  
Nuclear Radiation ◽  
Analysis Method ◽  
Noise Elimination ◽  
Application Study ◽  
Signal Noise

scholarly journals Energy Analysis Method Based on Wavelet Transform for Sensor Fault Diagnosis

2011 ◽  
Vol 2-3 ◽  
pp. 117-122 ◽  
Author(s):  
Peng Peng Qian ◽  
Jin Guo Liu ◽  
Wei Zhang ◽  
Ying Zi Wei
Keyword(s):  
Wavelet Transform ◽  
Fault Diagnosis ◽  
Wavelet Analysis ◽  
Energy Analysis ◽  
Sensor Faults ◽  
Analysis Method ◽  
Sensor Fault ◽  
Fault Type ◽  
Ideal Tool ◽  
Non Stationary Signal

Wavelet analysis with its unique features is very suitable for analyzing non-stationary signal, and it can also be used as an ideal tool for signal processing in fault diagnosis. The characteristics of the faults and the necessary information on the diagnosis can be constructed and extracted respectively by wavelet analysis. Though wavelet analysis is specialized in characteristics extraction, it can not determine the fault type. So this paper has proposed an energy analysis method based on wavelet transform. Experiment results show the method is very effective for sensor fault diagnosis, because it can not only detect the sensor faults, but also determine the fault type.

Mine Ventilator Fault Diagnosis Based on Harmonic Wavelet Analysis

2011 ◽  
Vol 143-144 ◽  
pp. 613-617
Author(s):  
Shuang Xi Jing ◽  
Yong Chang ◽  
Jun Fa Leng
Keyword(s):  
Fault Diagnosis ◽  
Wavelet Analysis ◽  
Frequency Domain ◽  
Vibration Signal ◽  
Wavelet Function ◽  
Frequency Region ◽  
Analysis Method ◽  
Vibration Signals ◽  
Harmonic Wavelet ◽  
Frequency Components

Harmonic wavelet function, with the strict box-shaped characteristic of spectrum, has strong ability of identifying signal in frequency domain, and can extract weak components form vibration signals in frequency domain. Using harmonic wavelet analysis method, the selected frequency region and other frequency components of vibration signal of mine ventilator were decomposed into independent frequency bands without any over-lapping or leaking. Simulation and diagnosis example show that this method has good fault diagnosis effect, and the ventilator fault is diagnosed successfully.

Research on Goniometer Fault Detection of a Certain Missile Based on Wavelet Analysis

2012 ◽  
Vol 490-495 ◽  
pp. 1600-1604
Author(s):  
Zhu Lin Wang ◽  
Jiang Kun Mao ◽  
Zi Bin Zhang ◽  
Xi Wei Guo
Keyword(s):  
Wavelet Transform ◽  
Wavelet Analysis ◽  
Discrete Wavelet Transform ◽  
Frequency Analysis ◽  
Discrete Wavelet ◽  
Analysis Method ◽  
Frequency Method ◽  
Time Frequency Analysis ◽  
Time Frequency ◽  
Fault Characteristic

Aiming at the problem of existing time-frequency analysis methods was not effective to goniometer keeping fault of a certain missile, combined time -frequency analysis method of CWT and DWT for the fault was put forward based on the fault characteristic. The process of the method proposed was given and the time-frequency method of continuous and discrete wavelet transform was analysed. The signal when goniometer keeping fault occurred was analysed by the method that was put forward. The simulation showed that the method which was effective to the fault detecting could accurately detect the time and location of goniometer fault occurred.

Fourier and Wavelet Analysis of Water Quality Signals

2013 ◽  
Vol 765-767 ◽  
pp. 2848-2852
Author(s):  
Wei Zhang ◽  
Hong Li ◽  
Dan Feng Sun ◽  
Lian Di Zhou
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Wavelet Analysis ◽  
Temporal Pattern ◽  
Surface Water Quality ◽  
Small Scale ◽  
Analysis Method ◽  
Periodic Patterns ◽  
Quality Signals ◽  
Detailed Method

Taking the nitrogen monitoring data of two sites S1 and S2 in the period 1988-2003 in Baihe River lying Miyun reservoir stream watershed as a case, Fourier and Wavelet analysis were adopted to explore and compare the periodic patterns and temporal pattern characteristics of the two sites. The results showed that the periodic patterns of two sites were discovered using Fourier analysis. The site S1 had a period of two years, while the site S2 had no significant periodic patterns. The temporal pattern characteristics at different scales were obtained through wavelet analysis, which were at small scale for the site S1, while at moderate and small scales for the site S2. The Fourier and wavelet analysis method can both be used in the study of surface water quality temporal change pattern, the first is a coarse method and the latter is a more detailed method for analyzing surface water quality temporal pattern characteristics.

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