scholarly journals EEG data acquisition system 32 channels with relative power ratio based on Raspberry Pi 3

2019 ◽  
Author(s):  
H. Hendarwin ◽  
P. Prajitno ◽  
S. K. Wijaya
2019 ◽  
Author(s):  
Henry Hendarwin ◽  
Sastra Kusuma Wijaya ◽  
Prawito Prajitno ◽  
Nurhadi Ibrahim ◽  
Hendra Saputra Gani ◽  
...  

2007 ◽  
Vol 118 (7) ◽  
pp. 1633-1638 ◽  
Author(s):  
John R. Ives ◽  
Seyed M. Mirsattari ◽  
D. Jones

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3493
Author(s):  
César Ricardo Soto-Ocampo ◽  
José Manuel Mera ◽  
Juan David Cano-Moreno ◽  
José Luis Garcia-Bernardo

Data acquisition is a crucial stage in the execution of condition monitoring (CM) of rotating machinery, by means of vibration analysis. However, the major challenge in the execution of this technique lies in the features of the recording equipment (accuracy, resolution, sampling frequency and number of channels) and the cost they represent. The present work proposes a low-cost data acquisition system, based on Raspberry-Pi, with a high sampling frequency capacity in the recording of up to three channels. To demonstrate the effectiveness of the proposed data acquisition system, a case study is presented in which the vibrations registered in a bearing are analyzed for four degrees of failure.


2011 ◽  
Vol 35 (3-4) ◽  
pp. 185-190 ◽  
Author(s):  
N. Agarwal ◽  
M.S. Nagananda ◽  
S. M. K. Rahman ◽  
A. Sengupta ◽  
J. Santhosh ◽  
...  

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