scholarly journals Measurement of Complex Magnetic Permeability in High-Frequency Domain for Ring-Shaped Magnetic Woods.

1996 ◽  
Vol 43 (6) ◽  
pp. 777-781
Author(s):  
Hideo Oka
Keyword(s):  
Frequency Domain ◽  
Magnetic Permeability ◽  
High Frequency ◽  
Complex Magnetic Permeability

High-frequency magnetic permeability of single- and multilayered (Co41Fe39B20) x (SiO2)100–x nanocomposites

2016 ◽  
Vol 58 (12) ◽  
pp. 2453-2456 ◽  
Author(s):  
O. S. Tarasova ◽  
A. V. Sitnikov ◽  
Yu. E. Kalinin ◽  
S. N. Starostenko ◽  
A. B. Granovskii
Keyword(s):  
Magnetic Permeability ◽  
High Frequency

Efficient interpolation of high-frequency domain data by phase smoothing

Radio Science ◽  
2008 ◽  
Vol 43 (4) ◽  
pp. n/a-n/a
Author(s):  
Jie Yang ◽  
Mary C. Taylor ◽  
Yu Zhang ◽  
Tapan K. Sarkar
Keyword(s):  
Frequency Domain ◽  
High Frequency

scholarly journals An Investigation into Error Source Identification of Machine Tools Based on Time-Frequency Feature Extraction

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Dongju Chen ◽  
Shuai Zhou ◽  
Lihua Dong ◽  
Jinwei Fan
Keyword(s):  
Machine Tool ◽  
Frequency Domain ◽  
Surface Topography ◽  
High Frequency ◽  
Low Frequency ◽  
Frequency Signal ◽  
High Frequency Signal ◽  
Time Frequency ◽  
Cross Correlation Analysis ◽  
Correlation Analysis Method

This paper presents a new identification method to identify the main errors of the machine tool in time-frequency domain. The low- and high-frequency signals of the workpiece surface are decomposed based on the Daubechies wavelet transform. With power spectral density analysis, the main features of the high-frequency signal corresponding to the imbalance of the spindle system are extracted from the surface topography of the workpiece in the frequency domain. With the cross-correlation analysis method, the relationship between the guideway error of the machine tool and the low-frequency signal of the surface topography is calculated in the time domain.

scholarly journals The effect of temperature and frequency on magnetic properties of the Fe81B13Si4C2 amorphous alloy

2011 ◽  
Vol 43 (2) ◽  
pp. 175-182 ◽  
Author(s):  
S. Djukic ◽  
V. Maricic ◽  
A. Kalezic-Glisovic ◽  
L. Ribic-Zelenovic ◽  
S. Randjic ◽  
...  
Keyword(s):  
Signal Processing ◽  
Magnetic Properties ◽  
Amorphous Alloy ◽  
Frequency Domain ◽  
Magnetic Permeability ◽  
Structural Relaxation ◽  
Substantial Reduction ◽  
Effect Of Temperature ◽  
Influence Of Temperature ◽  
Mean Frequency

In this study it was investigated influence of temperature and frequency on permeability, coercivity and power loses of Fe81B13Si4C2 amorphous alloy. Magnetic permeability measurements performed in nonisothermal and isothermal conditions was confirmed that efficient structural relaxation was occurred at temperature of 663 K. This process was performed in two steps, the first one is kinetic and the second one is diffuse. Activation energies of these processes are: Ea1 = 52.02 kJ/mol for kinetic and Ea2 = 106.9 kJ/mol for diffuse. It was shown that after annealing at 663 K coercivity decrease about 30% and therefore substantial reduction in power loses was attained. Investigated amorphous alloy satisfied the criteria for signal processing devices that work in mean frequency domain.

scholarly journals Adaptive Weight Fusion Algorithm of Infrared and Visible Image Based on High-Frequency Domain CNN

2021 ◽  
Vol 2010 (1) ◽  
pp. 012121
Author(s):  
Chuanyun Wang ◽  
Guowei Yang ◽  
Dongdong Sun ◽  
Jiankai Zuo ◽  
Ershen Wang
Keyword(s):  
Frequency Domain ◽  
High Frequency ◽  
Fusion Algorithm ◽  
Visible Image ◽  
Adaptive Weight

scholarly journals Time–Frequency Domain Characteristics of Acoustic Emission Signals and Critical Fracture Precursor Signals in the Deep Granite Deformation Process

2021 ◽  
Vol 11 (17) ◽  
pp. 8236
Author(s):  
Le Zhang ◽  
Hongguang Ji ◽  
Liyuan Liu ◽  
Jiwei Zhao
Keyword(s):  
Acoustic Emission ◽  
Frequency Domain ◽  
High Frequency ◽  
Wavelet Packet ◽  
Confining Pressure ◽  
Wavelet Packet Decomposition ◽  
Evolution Law ◽  
Time Frequency ◽  
Characteristic Signal ◽  
Failure Precursor

To study the crack evolution law and failure precursory characteristics of deep granite rocks in the process of deformation and failure under high confining pressure, granite samples obtained from a depth of 1150 m are tested using a TAW-2000 triaxial hydraulic servo testing machine and a PCI-II acoustic emission monitoring system. Based on the stress–strain curve and IET function, the loading process of the sample is divided into five stages: crack closure, linear elastic deformation, microcrack generation and development, macroscopic fracture generation and energy surge, and post-peak failure. The evolution trend and fracture evolution law of the acoustic emission signal event interval function in different stages are analyzed. In particular, the signals with an amplitude greater than 85 dB, a peak frequency greater than 350 kHz, and a frequency centroid greater than 275 kHz are defined as the failure precursor signals before the rock reaches the peak stress. The defined precursor signal conditions agree well with the experimental results. The time–frequency analysis and wavelet packet decomposition of the precursor signal are performed on the extracted characteristic signal of the failure precursor. The results show that the time-domain signal is in the form of a continuous waveform, and the frequency-domain waveform has multi-peak coexistence that is mainly concentrated in the high-frequency region. The energy distribution obtained by the wavelet packet decomposition of the characteristic signal is verified with the frequency-domain waveform. The energy distribution of the signal is mainly concentrated in the 343.75–375 kHz frequency band, followed by the 281.25–312.5 kHz frequency band. The energy proportion of the high-frequency signal increases with the confining pressure.

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