anomaly region
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Author(s):  
Xiaohua Mo ◽  
Donghe Zhang ◽  
Jing Liu ◽  
Yongqiang Hao ◽  
Zuo Xiao ◽  
...  

2021 ◽  
pp. 1-9
Author(s):  
Rufus Sola Fayose

This paper investigate the variability of Total Electron Content TEC over a terrestrial point within equatorial anomaly region using the NovAtel GSV 4000B GPS-SCINDA system at Akure (7.3°N, 5.2°E), Nigeria. This system is capable of tracking up to 14 GPS satellites simultaneously. Total Electron Content (TEC) over equatorial region using a real time data collected via a GPS-SCINDA facility were analyzed to study the ionospheric variations in terms of Total Electron Content (TEC) for the period of three years. Diurnal variations and Monthly mean variations of Total Electron Content within the equatorial anomaly region were examined. The diurnal variation of TEC showed pre-dawn minimum for a short period of time, followed by a steep early morning increase and then reached maximum value between 14:00 UT and 16:00 UT. The influence of solar activity on VTEC was investigated by taking the correlation coefficients between VTEC, F10.7cm radio flux index and sunspot numbers. The range of solar flux variation during the period of observation is very limited; there is high positive correlation (Correlation Coefficient 0.61) between daytime peak TEC and the solar F10.7 flux.


Author(s):  
G.A. Akinyemi ◽  
L.B. Kolawole ◽  
O.F. Dairo ◽  
Alexander A. Willoughby ◽  
R.B. Abdulrahim ◽  
...  

An investigation on the diurnal and seasonal variability of ionospheric Total Electron Content (TEC) over Nigeria is carried out in this study using Global Positioning System (GPS) observable. Nigeria coordinates fall within the trough of equatorial ionization anomaly region of African sector. The TEC data used were obtained from the ground-based GPS receiver stations of the Nigerian GNSS network of stations (NIGNET). The stations with their respective geomagnetic latitudes are Abuja (−1.64º), Yola (−1.32º), Zaria (−0.13º) and Kebbi (0.72º). The results of the diurnal analysis of the relative variability index (VD) revealed higher nighttime values than daytime values. The diurnal variation of VD also showed two conspicuous peaks: the post-midnight and the post-sunset. The diurnal-seasonal variation does not reveal any consistent pattern (no particular season leads the others throughout). On the average, considering all the seasons together maximum TEC variability occurred in Zaria (62%) and least in Yola (54%). Seasonally, maximum VD was recorded during March equinox and the least was recorded during December equinox.


Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4531 ◽  
Author(s):  
Hongzhi Tian ◽  
Dongxing Wang ◽  
Jiangang Lin ◽  
Qilin Chen ◽  
Zhaocai Liu

Currently, surface defect detection of stamping grinding flat parts is mainly undertaken through observation by the naked eye. In order to improve the automatic degree of surface defects detection in stamping grinding flat parts, a real-time detection system based on machine vision is designed. Under plane illumination mode, the whole region of the parts is clear and the outline is obvious, but the tiny defects are difficult to find; Under multi-angle illumination mode, the tiny defects of the parts can be highlighted. In view of the above situation, a lighting method combining plane illumination mode with multi-angle illumination mode is designed, and five kinds of defects are automatically detected by different detection methods. Firstly, the parts are located and segmented according to the plane light source image, and the defects are detected according to the gray anomaly. Secondly, according to the surface of the parts reflective characteristics, the influence of the reflection on the image is minimized by adjusting the exposure time of the camera, and the position and direction of the edge line of the gray anomaly region of the multi-angle light source image are used to determine whether the anomaly region is a defect. The experimental results demonstrate that the system has a high detection success rate, which can meet the real-time detection rEquation uirements of a factory.


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