Asperity Interactions In EHD Contacts

1978 ◽  
Vol 100 (2) ◽  
pp. 246-252 ◽  
Author(s):  
H. S. Nagaraj ◽  
D. M. Sanborn ◽  
W. O. Winer
Keyword(s):  
Frequency Domain ◽  
High Frequency ◽  
Narrow Band ◽  
Point Contact ◽  
Surface Profile ◽  
Frequency Component ◽  
Interaction Process ◽  
Contact Temperature ◽  
High Frequency Component ◽  
Before And After

Infrared temperature measurements, ferrographic analysis, and surface profilimetry were used to monitor asperity interactions in a sliding EHD point contact. The contact temperature and surface profile signals obtained both before and after a run-in period are compared in the frequency domain by means of a Fourier analyzer. The interaction of surface asperities is accompanied by the presence of a high frequency component in the infrared signal. It is also shown that only a relatively narrow band of wavelengths of the surface profile spectrum are relevant in the interaction process.

scholarly journals Reconstruction of MR Images using Sparse Signal Sequences in Frequency Domain

2020 ◽  
Vol 9 (3) ◽  
pp. 895-902
Keyword(s):  
Compressed Sensing ◽  
Frequency Domain ◽  
High Frequency ◽  
Low Frequency ◽  
Frequency Component ◽  
High Frequency Component ◽  
Sparse Signal ◽  
Reference Image ◽  
Signal Acquisition ◽  
Coarse Scale

A new strategy for signal acquisition has emerged called Compressed Sensing (CS). The compressed sensing has gained attention in the filed of computer science, electrical engineering and mathematics. The Compressed Sensing is a mathematical approach of reconstructing a signal that is acquired from the dimensionally reduced data coefficients/less number of samples i.e. less than the Niquist rate. The data coefficients are high frequency component and low frequency component. The high frequency components are due to the rapid changes in the images (edges) and low frequency correspond provide the coarse scale approximation of the image, i.e. fine continuos surface. The idea is to retain only coarse scale approximation of the image i.e. the significant components that constitute the compressed signal. This compressed signal is the sparse signal which is so helpful during medical scenarios. During the Medical Resonance Imaging (MRI) scans, the patient undergoes many kinds difficulties like uncomfortness, patients are afraid of the scanning devices, h/she cannot be stable or changing his body positions slightly. Due to all these reasons, there can be a chance of acquiring only the less number of samples during the process of MRI scan. Even though the numbers of samples are less than the Nyquist rate, the reconstruction is possible by using the compressed sensing technique. The work has been carried out in the frequency domain to achieve the sparsity. The comparative study is done on percentage of different levels of sparsity of the signal. This can be verified by using Peak Signal Noise Ratio (PSNR), Mean Square Error (MSE) and Structural similarity (SSIM) methods which are calculated between the reference image and the reconstructed image. The finite dimensional signal has a sparsity and compressible representation. This sparsified data can be recovered from small set of linear, non-adaptive measurements. The implementation is done by using MATLAB.

scholarly journals Preliminary Research on Radiance Fog Detection based on time series MTSAT data

2015 ◽  
Vol XL-7/W3 ◽  
pp. 243-246
Author(s):  
X. Wen ◽  
Z. Li ◽  
S. Zhang ◽  
S. Shen ◽  
D. Hu ◽  
...  
Keyword(s):  
Time Series ◽  
Frequency Domain ◽  
High Frequency ◽  
Optimization Method ◽  
Frequency Component ◽  
Interval Length ◽  
High Frequency Component ◽  
Weather Phenomenon ◽  
The Difference ◽  
Fog Detection

Fog is a kind of disastrous weather phenomenon. In this paper, the geostationary satellite MTSAT imagery is selected as the main data source to radiance fog detection. According to the unique feature of radiance fog from its generation to dissipation, especially considering the difference between clouds and fog during their lifecycle, the characteristics in frequency domain was constructed to discriminate fog from clouds, The time series MTSAT images were register with a modified Gauss Newton optimization method firstly, then, the Savitzky-Golay smoothing filter was applied to the time series remote sensing imageries to process the noises in the original signal, after that the non-orthogonal Haar wavelets was applied to convert the signal from time domain into frequency domain. The coefficient of high frequency component, including the properties: “max”, “min”, “the location of the min”, “the interval length between the max and min”, “the coefficient of linear fit for the high frequency”, these properties are selected as the characteristic parameters to distinguish fog from clouds. The experiment shows that using the algorithm proposed in this paper, the radiance fog could be monitored effectively, and it is found that although it is difficult to calculate the thickness of the fog directly, while the duration of fog could be obtained by using the frequency feature.

Laser-Generated Ultrasonic Technique for Inspecting Delamination in CFRP

2006 ◽  
Vol 321-323 ◽  
pp. 968-971
Author(s):  
Won Su Park ◽  
Sang Woo Choi ◽  
Joon Hyun Lee ◽  
Kyeong Cheol Seo ◽  
Joon Hyung Byun
Keyword(s):  
High Frequency ◽  
Ultrasonic Method ◽  
Piezoelectric Sensor ◽  
Frequency Component ◽  
Guided Wave ◽  
Center Frequency ◽  
High Frequency Component ◽  
Ultrasonic Technique ◽  
Non Destructive Evaluation ◽  
Non Destructive

For improving quality of a carbon fiber reinforced composite material (CFRP) by preventing defects such as delamination and void, it should be inspected in fabrication process. Novel non-contacting evaluation technique is required because the transducer should be contacted on the CFRP in conventional ultrasonic technique during the non-destructive evaluation and these conventional contact techniques can not be applied in a novel fiber placement system. For the non-destructive evaluation of delamination in CFRP, various methods for the generation and reception of laser-generated ultrasound are applied using piezoelectric transducer, air-coupled transducer, wavelet transform technique etc. The high frequency component of laser-generated guided wave received with piezoelectric sensor disappeared after propagating through delamination region. Air-coupled transducer was tried to be adopted in reception of laser-generated guided wave generated by using linear slit array in order to generate high frequency guided wave with a frequency of 1.1 MHz. Nevertheless, it was failed to receive high frequency guided wave in using air-coupled transducer and linear slit array. Transmitted laser-generated ultrasonic wave was received on back-wall and its frequency was analyzed to establish inspecting technique to detect delamination by non-contact ultrasonic method. In a frequency spectrum analysis, intensity ratio of low frequency and center frequency was approvable parameter to detect delamination.

Hierarchal Predefined Codebook for High-Frequency Component Augmentation Image Enlargement

2010 ◽  
Author(s):  
Hakaru Tamukoh ◽  
Hideaki Kawano ◽  
Noriaki Suetake ◽  
Masatoshi Sekine ◽  
Byungki Cha ◽  
...  
Keyword(s):  
High Frequency ◽  
Frequency Component ◽  
High Frequency Component ◽  
Image Enlargement

Force fluctuations are modulated by alternate muscle activity of knee extensor synergists during low-level sustained contraction

2004 ◽  
Vol 97 (6) ◽  
pp. 2121-2131 ◽  
Author(s):  
Motoki Kouzaki ◽  
Minoru Shinohara ◽  
Kei Masani ◽  
Tetsuo Fukunaga
Keyword(s):  
Correlation Coefficient ◽  
Muscle Activity ◽  
High Frequency ◽  
Vastus Lateralis ◽  
Frequency Component ◽  
Knee Extension ◽  
Voluntary Contraction ◽  
High Frequency Component ◽  
Knee Extensors ◽  
Force Fluctuations

The study examined the hypothesis that altered synergistic activation of the knee extensors leads to cyclic modulation of the force fluctuations. To test this hypothesis, the force fluctuations were investigated during sustained knee extension at 2.5% of maximal voluntary contraction force for 60 min in 11 men. Surface electromyograms (EMG) were recorded from the rectus femoris (RF), vastus lateralis (VL), and vastus medialis (VM) muscles. The SD of force and average EMG (AEMG) of each muscle were calculated for 30-s periods during alternate muscle activity. Power spectrum of force was calculated for the low- (≤3 Hz), middle- (4–6 Hz), and high-frequency (8–12 Hz) components. Alternate muscle activity was observed between RF and the set of VL and VM muscles. The SD of force was not constant but variable due to the alternate muscle activity. The SD was significantly greater during high RF activity compared with high VL and VM activity ( P < 0.05), and the correlation coefficient between the SD and AEMG was significantly greater in RF [0.736 (SD 0.095), P < 0.05] compared with VL and VM. Large changes were found in the high-frequency component. During high RF activity, the correlation coefficient between the SD and high-frequency component [0.832 (SD 0.087)] was significantly ( P < 0.05) greater compared with other frequency components. It is suggested that modulations in knee extension force fluctuations are caused by the unique muscle activity in RF during the alternate muscle activity, which augments the high-frequency component of the fluctuations.

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