scholarly journals A MULTI-SCALE MULTI-PHYSICS ANALYSIS METHOD FOR MASS CONCENTRATION AND DEFORMATION PROBLEMS

2006 ◽  
Vol 62 (2) ◽  
pp. 425-439
Author(s):  
Mao KURUMATANI ◽  
Kenjiro TERADA
2015 ◽  
Vol 58 (1) ◽  
pp. 41-53 ◽  
Author(s):  
YANG Wen-Cai ◽  
SUN Yan-Yun ◽  
HOU Zun-Ze ◽  
YU Chang-Qing

2005 ◽  
Vol 2005.5 (0) ◽  
pp. 185-186
Author(s):  
Yuichi SHOYAMA ◽  
Ryosuke MATSUMOTO ◽  
Michihiko NAKAGAKI

2018 ◽  
Vol 31 (1) ◽  
pp. 117-125 ◽  
Author(s):  
Xin LIU ◽  
Xiuli SHEN ◽  
Longdong GONG ◽  
Peng LI

2010 ◽  
Vol 44-47 ◽  
pp. 1807-1811
Author(s):  
Feng Lv ◽  
Hao Sun ◽  
Wen Xia Du ◽  
Shue Li

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.


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.


Materials ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4190
Author(s):  
Jincheng Zheng ◽  
Peiwei Zhang ◽  
Dahai Zhang ◽  
Dong Jiang

A multi-scale fatigue analysis method for braided ceramic matrix composites (CMCs) based on sub-models is developed in this paper. The finite element shape function is used as the interpolation function for transferring the displacement information between the macro-scale and meso-scale models. The fatigue failure criterion based on the shear lag theory is used to implement the coupling calculation of the meso-scale and micro-scale. Combining the meso-scale cell model and the fatigue failure criterion based on the shear lag theory, the fatigue life of 2D SiC/SiC is analyzed. The analysis results are in good agreement with the experimental results, which proves the accuracy of the meso-scale cell model and the fatigue life calculation method. A multi-scale sub-model fatigue analysis method is used to study the fatigue damage of 2D SiC/SiC stiffened plates under random tension–tension loads. The influence of the sub-models at different positions in the macro-model element on the analysis results was analyzed. The results shows that the fatigue analysis method proposed in this paper takes into account the damage condition of the meso-structured of composite material, and at the same time has high calculation efficiency, and has low requirements for modeling of the macro finite element model, which can be better applied to the fatigue analysis of CMCs structure.


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