Development of a Robust Scrubber Level Controller

2021 ◽  
Author(s):  
Carolyn M. Day ◽  
Griffin C. Beck ◽  
Scott A. Schubring

Abstract Gas-liquid scrubbers rely on level control systems (generally consisting of a level indicator, a level controller, and a pneumatic control valve for liquid release) to maintain an appropriate liquid level within the vessel. Scrubbers are often upstream of turbomachinery and failures at the scrubber can cause liquid ingestion or downtime. In natural gas service, these control systems are subject to harsh environments due to the influx of liquid slugs, high-velocity gases, corrosive fluids, vibrations, and a chaotic gas-liquid interface. In these severe conditions, level control system failures are commonplace and lead to safety and environmental hazards, equipment damage, and lost production. A need exists to augment or replace the typical liquid level control system with an alternative solution that is cost-effective, robust, and can operate reliably in the harsh natural gas environment. A project investigated failures related to scrubber level control systems, identified improvements to these systems, developed a prototype level controller, and tested the prototype controller and a variety of commercially available controllers at various conditions that emulated certain field conditions. The results of these tests gave insight into what type of controller may be best suited to the tested conditions and what controller options should be pursued further.

2015 ◽  
Vol 7 (3) ◽  
pp. 317-322
Author(s):  
Dominykas Beištaras

This paper presents liquid level control system model and analysis of dynamic characteristics. The system consists of scalar controlled induction motor drive, fuzzy logic controller, water tank and centrifugal pump. Simulink models of water tank, pump and controller are presented. The simulation of the system shows that the use of fuzzy logic controller reduces valve opening time and reservoir filling time. Nagrinėjamas skysčio lygio valdymo sistemos imitacinių modelių sudarymas, analizuojamos dinaminės charakteristikos. Valdymo sistema sudaryta iš skaliariniu būdu valdomos dažninės elektros pavaros su neraiškiosios logikos reguliatoriumi, vandens rezervuaro ir išcentrinio siurblio. Sudaryti rezervuaro, siurblio ir reguliatoriaus Simulink modeliai. Atlikus imitacijas gauta nedimensinė siurblio charakteristika, apibūdinanti siurblio veikimą, esant bet kokiam sukimosi greičiui. Nustatyta, kad sistemoje su neraiškiosios logikos reguliatoriumi vožtuvas yra atidaromas greičiau nei sistemoje su proporcinguoju integraliniu (PI) reguliatoriumi, ir todėl sumažinama rezervuaro pripildymo trukmė.


2013 ◽  
Vol 336-338 ◽  
pp. 1292-1295
Author(s):  
Min Zhao ◽  
Cai Yun Ren ◽  
Dong Liang Lei ◽  
Feng Lian Qi

Based on the PLC control technique and WinCC configuration technology,the control system for the liquid level of the tank was designed. After receiving liquid level signal that transferred from radar tester,the PLC process it ,and then output related control signal to the actuator.The actuator is composed of two AC motors,one is for the main pump ,and another for the auxiliary pump.The function of human-machine interface is achieved with the help of Smart700 touch screen of Siemens.Communication functions between the WinCC project and the PLC site and pictures of the control process which enabals real-time monitoring of the entire system are finished by designing configuration.Finally,the validity of the system and the feasibility of the design have been proved by debugging and the use of enterprises.


2012 ◽  
Vol 591-593 ◽  
pp. 1629-1632
Author(s):  
Li Zhang ◽  
Jian Hui Wang ◽  
Hou Yao Zhu

This thesis mainly elaborated the PID neural network feed-forward algo-rithm and back propagation algorithm and the structure form of its controller, then make use of MATLAB to simulate the liquid level adjusting system, analysis its control perform-ance and choose appropriate neural network parameters, and compared with the traditional PID control effect, analyzes the advantages of PID neural network. Through the comparison with the conventional PID control, PID neural network is superior to the traditional PID. The traditional PID control tuning parameters has a large number of thumb rules for reference, but the setting out of the parameters is not necessarily good. And sometimes we have to modify the parameters if we wound the better control effect. PID neural network is set up as long as the learning step in accordance with the PID rule set. this paper has show that Liquid Level Control System based on Computer Nerve Network has good control effect of rapid and effective.


Sign in / Sign up

Export Citation Format

Share Document