scholarly journals Special issue : third domestic workshop for automatic instrumentation control of water systems.Introduction effect of an automatic control system on an established sewage treatment plant.

1990 ◽  
Vol 19 (3) ◽  
pp. 190-193
Author(s):  
Haruki Ohnishi ◽  
Masaru YAMAMURA ◽  
Kiyoshi TSUZIMOTO ◽  
Masakatsu HIRAOKA
Keyword(s):  
Control System ◽  
Automatic Control ◽  
Automatic Control System ◽  
Sewage Treatment ◽  
Sewage Treatment Plant ◽  
Treatment Plant ◽  
Special Issue

The Automatic Control System Based on PROFIBUS for the City Sewage Treatment

2013 ◽  
Vol 385-386 ◽  
pp. 857-861
Author(s):  
Xiao Ping Huang ◽  
Qi Xing Qing
Keyword(s):  
Control System ◽  
Automatic Control ◽  
Automatic Control System ◽  
Fuzzy Controller ◽  
Sewage Treatment ◽  
Sewage Treatment Plant ◽  
Treatment Plant ◽  
Difficult Problem ◽  
Urban Sewage ◽  
Treated Sewage

On the basis of the computerized technological process control of sewage treatment in a urban sewage treatment plant in the Zone of Nanning, the author had brought forward a plan of PROFIBUS that based on automatic control system for sewage treatment, and designed the automatic control system diagram and the PROFIBUS network diagram for sewage treatment plant. At the same time, the author also made a study of techniques to control the sewage aeration, which was the most difficult problem in sewage treatment process. The fuzzy controller could indicate the changes of the water quality in treated sewage, effectively controlled the volume of aeration and then cut down the operation costs,it had produced good economic and social benefits.

Intelligent Control of Flocculation Process Based on Radial Basis Probabilistic Neural Network for Sewage Treatment

2010 ◽  
Vol 44-47 ◽  
pp. 3289-3293
Author(s):  
Jing Wen Tian ◽  
Mei Juan Gao
Keyword(s):  
Neural Network ◽  
Control System ◽  
Process Model ◽  
Probabilistic Neural Network ◽  
Sewage Treatment ◽  
Sewage Treatment Plant ◽  
Treatment Plant ◽  
Least Square ◽  
Radial Basis ◽  
Flocculation Process

The flocculating process of sewage treatment is a complicated and nonlinear system, and it is very difficult to found the process model to describe it. The radial basis probabilistic neural network (RBPNN) has the ability of strong function approach and fast convergence. In this paper, an intelligent optimized control system based on radial basis probabilistic neural network is presented. We constructed the structure of radial basis probabilistic neural network that used for controlling the flocculation process, and adopt the K-Nearest Neighbor algorithm and least square method to train the network. We given the architecture of control system and analyzed the working process of system. In this system, the parameters of flocculation process were measured using sensors, and then the control system can control the flocculation process real-time. The system was used in the sewage treatment plant. The experimental results prove that this system is feasible.

Design of Sewage Treatment Automated Control System

2014 ◽  
Vol 644-650 ◽  
pp. 639-641
Author(s):  
Yun Hong
Keyword(s):  
Control System ◽  
Closed System ◽  
Sewage Treatment ◽  
Sewage Treatment Plant ◽  
Treatment Plant ◽  
Process Equipment ◽  
Automation System ◽  
Automated Control ◽  
Automated Control System ◽  
Plant Automation

Advanced fieldbus technology has solved the DCS system of communication caused by special network of the closed system defects, the closed, proprietary solutions into the open, standardized solution.Therefore, in this paper, according to the technological process in sewage treatment plant, combining with the distribution and characteristics of process equipment, the overall structure of the design of the sewage treatment plant automation system, and the overall structure of each component has carried on the detailed analysis and research.

Frequency Constant Pressure Control System Based on PLC

2013 ◽  
Vol 579-580 ◽  
pp. 798-803
Author(s):  
Qi Zhu ◽  
Zhi Wen Feng
Keyword(s):  
Wastewater Treatment ◽  
Control System ◽  
Constant Pressure ◽  
Sewage Treatment ◽  
Sewage Treatment Plant ◽  
Treatment Plant ◽  
Pressure Control ◽  
Pipe Network ◽  
Pumping Station ◽  
Pressure Control System

Sewage pumping station is pumping station import at the sewage treatment plant. Its role is to collect the wastewater from the sewage pipe network to subsequent wastewater treatment process facilities. The water level is usually low in sewage collection pipe network. And many wastewater treatment facilities is based on elevation settings. So it is necessary to use lift pump to improve lift of the collected sewage, using high gravity sewage errands subsequent process in order to reduce energy consumption. The traditional way of pumping generally has the shortcomings: the waste of power resources, low efficiency, poor reliability, low degree of automation, which seriously affects the urban sewage treatment capacity. This paper, views pump station control system at the sewage treatment plant as the background, researches frequency control constant pressure control system based on PLC, realizes the energy efficient, automated and reliable direction of development of the sewage pumping station.

scholarly journals Smart management and control system for liquid radioactive waste in hospitals using neural network techniques

2020 ◽  
Vol 9 (3) ◽  
pp. 607
Author(s):  
Khaled S. Ahmed ◽  
Fayroz F. Sherif
Keyword(s):  
Control System ◽  
Liquid Radioactive Waste ◽  
Sewage Treatment ◽  
Sewage Treatment Plant ◽  
Treatment Plant ◽  
Maximum Level ◽  
Design Stage ◽  
Monitoring And Control ◽  
Hospital Design ◽  
And Control

In tertiary hospitals where the nuclear medicine services have been introduced, the radioactive materials used in diagnosis and / or treatment need to be handled. The hospital design and medical planning should consider such these materials and their policy for treatment. The nuclear wastes have been divided into solid and liquid based on the used materials and for their half-life times which start from few minutes till reaching years. In our study, the most common radioactive liquid materials (wastes) have been treated by smart system. The system will detect the material of the waste via nuclear sensors and based on its HLT (activities), it will be distributed in two shielded storage tanks classified based on capacity then to the sewage treatment plant (STP) of the hospital after keeping for required times. The location and capacity of these tanks together with their monitoring and control system should be considered in design stage which determines the treatment processes. By applying our proposed technique on two hospitals, the results have reduced the storage tank capacity by 87% (reduction) and space area leading to cost reduction by 72% keeping the maximum level of safety.  

scholarly journals Control System and Algorithm of Sewage Treatment Plant Based on Artificial Intelligence

2021 ◽  
Vol 2066 (1) ◽  
pp. 012025
Author(s):  
Yunzhu Liu ◽  
Jinbao Cao
Keyword(s):  
Artificial Intelligence ◽  
Water Pollution ◽  
Wastewater Treatment ◽  
Control System ◽  
Pid Control ◽  
Sewage Treatment ◽  
Sewage Treatment Plant ◽  
Treatment Plant ◽  
Treated Wastewater ◽  
Self Tuning

Abstract With the improvement of people’s awareness of environmental protection in recent years, the related problems of water pollution treatment have gradually come into people’s view. As the source of life, water accounts for a huge proportion in our lives, but at the same time, water pollution is quietly spreading in places we don’t know. The continuous discharge of heavy industrial wastewater, agricultural wastewater and domestic sewage leads to increasingly serious water pollution. Sewage treatment(ST) is imperative, and its social benefits are huge, but the corresponding cost is high, and the return on investment is low. Traditional ST methods can not load large-scale ST. How to carry out ST based on artificial intelligence(AI), build ST plant control system, and make ST enter the era of automation is the problem to be solved. The purpose of this paper is to put forward the reform of control system for ST plant based on AI, apply AI into ST, and realize the automation and precision of ST plant. This paper mainly uses the fuzzy self-tuning PID control system algorithm, through the analysis of ST control object, analysis of fuzzy self-tuning PID controller design to complete the ST control system settings. In this paper, the literature review method and data analysis method are used. By collecting relevant data, the control system of ST plant is constructed to simulate ST, and the real-time data of ST is analyzed. The traditional PID control and fuzzy self-tuning PID control are compared. The experimental results show that the wastewater treatment plant system based on AI input, in the aspect of wastewater treatment, the concentration of COD and BOD in the treated wastewater are reduced by a certain proportion, the dissolved oxygen content in the wastewater reaches about 2.0mg/l, which meets the national discharge standard, and its rising time is reduced to 25 seconds, and the adjustment time is saved by 50 seconds.

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