An interrogable data collection node (D.C.N.); a microprocessor-based system for collection and transmission of low sample rate geophysical data

1982 ◽  
Author(s):  
Reese Cutler ◽  
M.J. Johnston
2017 ◽  
Author(s):  
Richard Saltus ◽  
◽  
Anjelique Morine ◽  
Anjelique Morine ◽  
Manoj Nair ◽  
...  

1997 ◽  
Vol 40 (4) ◽  
Author(s):  
G. Calderoni ◽  
B. De Simoni ◽  
F. M. De Simoni ◽  
L. Merucci

This article describes the ARGO Satellite Seismic Network (ARGO SSN) as a reliable system for monitoring, collection, visualisation and analysis of seismic and geophysical low-frequency data, The satellite digital telemetry system is composed of peripheral geophysical stations, a centraI communications node (master sta- tion) located in CentraI Italy, and a data collection and processing centre located at ING (Istituto Nazionale di Geofisica), Rome. The task of the peripheral stations is to digitalise and send via satellite the geophysical data collected by the various sensors to the master station. The master station receives the data and forwards them via satellite to the ING in Rome; it also performs alI the monitoring functions of satellite communications. At the data collection and processing centre of ING, the data are received and analysed in real time, the seismic events are identified and recorded, the low-frequency geophysical data are stored. In addition, the generaI sta- tus of the satellite network and of each peripheral station connected, is monitored. The procedure for analysjs of acquired seismic signals allows the automatic calculation of local magnitude and duration magnitude The communication and data exchange between the seismic networks of Greece, Spain and Italy is the fruit of a recent development in the field of technology of satellite transmission of ARGO SSN (project of European Community "Southern Europe Network for Analysis of Seismic Data" )


2013 ◽  
Vol 411-414 ◽  
pp. 1529-1534 ◽  
Author(s):  
Ying Jie Xu ◽  
Ming Yu Gao ◽  
Zhi Wei He

We have designed a photoelectric yarn signal acquisition system, which is based on the STM32 processor, having a sample rate up to 270kHz, and uploading data collection through synchronous parallel communication mode; Owing to the large noise of yarn signal and the unobviousness of yarn defect, we respectively adopting wiener filter and mean filter to filter this signal; The simulation result of matlab has manifested that both the wiener filter and mean filter can effectively decrease the noise level of the yarn signal and make the nep defects easier to identify, and that the wiener filter applies to application where the yarn speed is higher , while the mean filter is appropriate to the lower speed spinner.


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