Simple water flow control for the Coulson electrolytic conductivity detector

1975 ◽  
Vol 47 (2) ◽  
pp. 367-368 ◽  
Author(s):  
J. F. Lawrence ◽  
N. P. Sen
Keyword(s):  
Flow Control ◽  
Water Flow ◽  
Electrolytic Conductivity

Screw Pump‐Type Water Triboelectric Nanogenerator for Active Water Flow Control

2020 ◽  
pp. 2000758
Author(s):  
Seh-Hoon Chung ◽  
Jihoon Chung ◽  
Banseok Kim ◽  
Seamin Kim ◽  
Sangmin Lee
Keyword(s):  
Flow Control ◽  
Water Flow ◽  
Triboelectric Nanogenerator ◽  
Screw Pump ◽  
Type Water

scholarly journals Cooling water flow control realized with systems based on fuzzy mechanism

2018 ◽  
Vol 294 ◽  
pp. 012063
Author(s):  
G O Tirian ◽  
C A Gheorghiu ◽  
T Hepuţ ◽  
C P Chioncel
Keyword(s):  
Flow Control ◽  
Water Flow ◽  
Cooling Water

Capacitance-Based Design of the Tap Water Flow Control Device

2013 ◽  
Vol 273 ◽  
pp. 694-698
Author(s):  
Ying Qi Zhang ◽  
You Feng Luo ◽  
Ming Feng Lin ◽  
Wei Xiong
Keyword(s):  
Flow Control ◽  
Water Flow ◽  
Control Function ◽  
Tap Water ◽  
Flow Regulation ◽  
Control Device ◽  
Step Motor ◽  
Switching Frequency ◽  
Frequency Signal ◽  
Flow Control Device

In this paper, a capacitance-based design of the tap water flow control device is introduced. It is designed to prevent the waste of water resources caused by the current taps. It collects the capacitance signal by means of C/F conversion module based on 555 timer. Then the switching frequency signal and the flow frequency signal are generated according to the capacitance signal collected. They will be analyzed and compared with the signal STC15F100 microcontroller stored and generating the switch commands and flow regulation instructions to control the step motor. Finally, the water flow control function is realized by the device.

scholarly journals A Water Flow Control with OnLine Neurofuzzy Controller using a Dynamic Learning Rate

2018 ◽  
Author(s):  
Hugo Gomes ◽  
Carolina Ferreira1 ◽  
Everthon Oliveira1 ◽  
Agnaldo Reis ◽  
Walmir Caminhas
Keyword(s):  
Flow Control ◽  
Water Flow ◽  
Pid Controller ◽  
Control Process ◽  
Learning Rate ◽  
Dynamic Learning ◽  
The Difference ◽  
Real Plant

This paper describes an ONFC (OnLine Neurofuzzy Controller) application with a dynamic learning rate to control the water flow of a real plant. A revision of ONFC is presented and the ONFCDw version is used, which has an action that minimizes the increase in the difference between the controller weights. The dynamic learning rate used to update the controller weights is described and the results of experiments performed in a water flow control process are presented, comparing the results with the PID controller used in the process.

A WUSN-based Smart System for Water Flow Control

2020 ◽  
Author(s):  
Nahom Aron ◽  
Bereket Yemane ◽  
Temesgen Mikael ◽  
Reem Salem ◽  
Fatna Belqasmi
Keyword(s):  
Flow Control ◽  
Water Flow ◽  
Smart System
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