Design and Application of Direct Signal Acquisition Circuit in Fast Terahertz Spectral System

Author(s):  
Zhaohui Zhang ◽  
Hui He ◽  
Xinyong Zhu ◽  
Yongli Liu
2013 ◽  
Vol 718-720 ◽  
pp. 1295-1299
Author(s):  
Zu Min Wang ◽  
Xian Cheng Luo ◽  
Hui Lin Sun

This paper introduces one method to design a vibration diagnosis device from several sides such as components choosing, circuit designing and soft programming. This device consists of ATmega128 MCU, acceleration transducer, TLC2543 and other peripheral components and it can conveniently acquire and analysis signal. The resource used to test the device was supported by Function Generator and amplified by Power Amplifier. The data was exported to PC and graphed by MatLAB application, and then made a comparison with the theoretical graph to prove the method validity. This design has simple circuit and small codes, but it can capture mechanical working state accurately, so it has preferably practical value and economic benefit.


2020 ◽  
Vol 3 (1) ◽  
pp. 346-353
Author(s):  
Naim Suleyman Tinğ ◽  
Huseyin Ozel ◽  
Lokman Celik ◽  
Enes Ganidagli ◽  
Hilal Akkamis

In this paper, the design and application of smart wheelchair and charging station for disabled citizen is realized. The first stage of the paper is to make the wheelchair used by our disabled citizens able to access smart home technology via the vehicle via touch screen. The ability of citizens with disabilities to call with direct access via touch screen is also in the wheelchair designed. Thanks to the touch screen placed on the vehicle, disabled citizens are provided with the control of smart automation to control many objects such as curtains and doors in the home. In the second part of the paper, a solar powered charging station is designed and installed in order to charge battery powered wheelchairs. In the charging station made a special card reader system and has the charger to charge the card with disabilities to actively and means are provided.


2005 ◽  
Vol 63 (5) ◽  
pp. 389-403 ◽  
Author(s):  
D. Djebouri ◽  
A. Djebbari ◽  
M. Djebbouri

2017 ◽  
Vol 13 (9) ◽  
pp. 6480-6488 ◽  
Author(s):  
A.D. Jeyarani ◽  
Reena Daphne ◽  
Solomon Roach

The main contribution of this paper has been to introduce nonlinear classification techniques to extract more information from the PCG signal. Especially, Artificial Neural Network classification techniques have been used to reconstruct the underlying system’s state space based on the measured PCG signal. This processing step provides a geometrical interpretation of the dynamics of the signal, whose structure can be utilized for both system characterization and classification as well as for signal processing tasks such as detection and prediction.


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