A Multi-Scale Scratch Analysis Method for Quantitative Interpretation of Regional Gravity Fields

2015 ◽  
Vol 58 (1) ◽  
pp. 41-53 ◽  
Author(s):  
YANG Wen-Cai ◽  
SUN Yan-Yun ◽  
HOU Zun-Ze ◽  
YU Chang-Qing
Keyword(s):  
Quantitative Interpretation ◽  
Analysis Method ◽  
Multi Scale ◽  
Gravity Fields ◽  
Regional Gravity

1222 Multi-scale analysis method on bone structure considering the osteosis

2005 ◽  
Vol 2005.5 (0) ◽  
pp. 185-186
Author(s):  
Yuichi SHOYAMA ◽  
Ryosuke MATSUMOTO ◽  
Michihiko NAKAGAKI
Keyword(s):  
Bone Structure ◽  
Scale Analysis ◽  
Analysis Method ◽  
Multi Scale ◽  
Multi Scale Analysis

scholarly journals Multi-scale thermodynamic analysis method for 2D SiC/SiC composite turbine guide vanes

2018 ◽  
Vol 31 (1) ◽  
pp. 117-125 ◽  
Author(s):  
Xin LIU ◽  
Xiuli SHEN ◽  
Longdong GONG ◽  
Peng LI
Keyword(s):  
Thermodynamic Analysis ◽  
Analysis Method ◽  
Guide Vanes ◽  
Multi Scale

Fault Signature Analysis Based on Transient Current for Induction Motors

2010 ◽  
Vol 44-47 ◽  
pp. 1807-1811
Author(s):  
Feng Lv ◽  
Hao Sun ◽  
Wen Xia Du ◽  
Shue Li
Keyword(s):  
Fault Diagnosis ◽  
Induction Motors ◽  
Scale Transformation ◽  
Stationary Condition ◽  
Analysis Method ◽  
Broken Rotor Bars ◽  
Multi Scale ◽  
Stator Current ◽  
Time Varying Frequency ◽  
Basic Characteristics

The characteristics of broken rotor bars in induction motors are reflected in the abnormal harmonic of the stator current. At present, fast Fourier transform( ) and time-varying frequency spectrum analysis method are used in such fault diagnosis, but non-stationary motors operation can bring a certain difficulties to the monitoring and diagnosis. This paper studies the basic characteristics of wavelet transform, adopting the wavelet analysis technologies of signal processing and selecting mother wavelet, the paper makes the multi-scale transformation to the motor starting current, excavates the harmonic informations on non-stationary condition, realizes fault diagnosis of motor broken rotor bars effectively, The consistent diagnostic results prove the effectiveness of the method.

scholarly journals MSBE Analysis with Frequency Spectra for Automated Identification of Epileptic Seizure

2019 ◽  
Vol 8 (12) ◽  
pp. 5869-5874
Keyword(s):  
Spectral Analysis ◽  
Seizure Detection ◽  
Detection Technique ◽  
Discriminative Power ◽  
Entropy Analysis ◽  
Analysis Method ◽  
Automated Identification ◽  
Frequency Spectra ◽  
Multi Scale ◽  
Spectral Analysis Method

Objective-This study introduces a reliable automated seizure detection technique based on MSBE (Multi scale bubble entropy) and frequency spectral analysis. Method- This paper aims to develop a novel seizure detection technique that incorporates AM FM model for decomposition of EEG into different sub bands. In our approach, integrated feature set is constructed using multi scale bubble entropy analysis at each sub band and frequency spectral analysis at each electrode. Result-In this paper, an application of bubble entropy with different frequency parameter such as PPF and PSD is provided in order to access its stable and outstanding performance on epileptic seizer detection. The experimental results show that classification accuracy is improved with this algorithm. These finding suggest that extracted features can be used for treatment of epilepsy. Significance- This method provides greater stability and discriminative power, so this technique could be used to detect wider range of seizures.

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