Innovative Computing Techniques for Development of an Integrated Computer Control System

1992 ◽  
Vol 26 (5-6) ◽  
pp. 1365-1374 ◽  
Author(s):  
G. G. Patry ◽  
M. W. Barnett
Keyword(s):  
Wastewater Treatment ◽  
Object Oriented Programming ◽  
Plant Performance ◽  
Organic Load ◽  
Model Parameters ◽  
Process Data ◽  
Wastewater Treatment Process ◽  
Deterministic Modelling ◽  
Linear Differential ◽  
And Control

Over the past decade there has been a shift in emphasis from design and construction of wastewater treatment facilities to operation. Poor plant performance, high costs and damage to the environment have resulted from operational problems. Wastewater treatment consists of a complex sequence of inter-dependent biological, physical and chemical processes subject to time-varying hydraulic and organic load conditions. Wastewater treatment process operation and control is a knowledge intensive task. Research on improving operation and control has centred on identifying important mechanisms responsible for observed behaviour and modelling both the process and optimum ways of operating the process. These models have served as useful tools for improving operation and control. Many different approaches have been used, including deterministic modelling, stochastic modelling and, more recently, linguistic modelling. Complex mathematical models of wastewater treatment processes consisting of large numbers of non-linear differential equations can be constructed using tools such as the General Purpose Simulator (GPS) and, given appropriate data, model parameters can be evaluated and updated using existing optimization routines. Object oriented programming (OOP) and a model based reasoning (MBR) approach provides a useful framework for development of deep-knowledge expert systems (ES). Data-driven modelling methods, including both time series analysis and artificial neural network (ANN) techniques, can also be employed to make maximum use of information contained in process data. Each of these model types is a necessary component of a computer system for operational control of wastewater treatment but, in isolation, none are sufficient for making the system robust. An integrated environment for combining these techniques has been developed for this purpose and the basis for its development is described.

scholarly journals NEURO-FUZZY MODELLING IN ANAEROBIC WASTEWATER TREATMENT FOR PREDICTION AND CONTROL

2014 ◽  
pp. 51-56
Author(s):  
Snejana Yordanova ◽  
Rusanka Petrova ◽  
Nelly Noykova ◽  
Plamen Tzvetkov
Keyword(s):  
Wastewater Treatment ◽  
Prediction Models ◽  
Biogas Production ◽  
Organic Load ◽  
Model Parameters ◽  
Box Models ◽  
Neuro Fuzzy ◽  
Prediction And Control ◽  
And Control

The aim of the present paper is to develop neuro-fuzzy prediction models in MATLAB environment of the anaerobic organic digestion process in wastewater treatment from laboratory and simulated experiments accounting for the variable organic load, ambient influence and microorganisms state. The main contributions are determination of significant model parameters via graphical sensitivity analysis, simulation experimentation, design and study of two “black-box” models for the biogas production rate, based on classical feedforward backpropagation and Sugeno fuzzy logic neural networks respectively. The models application is demonstrated in process predictive control

Model-based evaluation of nitrogen removal in a tannery wastewater treatment plant

2004 ◽  
Vol 50 (6) ◽  
pp. 251-260 ◽  
Author(s):  
M.S. Moussa ◽  
A.R. Rojas ◽  
C.M. Hooijmans ◽  
H.J. Gijzen ◽  
M.C.M. van Loosdrecht
Keyword(s):  
Wastewater Treatment ◽  
Activated Sludge ◽  
Wastewater Treatment Plants ◽  
Computer Modelling ◽  
Treatment Plant ◽  
Domestic Wastewater ◽  
Plant Performance ◽  
Accurate Estimation ◽  
Model Parameters ◽  
Biological Tests

Computer modelling has been used in the last 15 years as a powerful tool for understanding the behaviour of activated sludge wastewater treatment systems. However, computer models are mainly applied for domestic wastewater treatment plants (WWTPs). Application of these types of models to industrial wastewater treatment plants requires a different model structure and an accurate estimation of the kinetics and stoichiometry of the model parameters, which may be different from the ones used for domestic wastewater. Most of these parameters are strongly dependent on the wastewater composition. In this study a modified version of the activated sludge model No. 1 (ASM 1) was used to describe a tannery WWTP. Several biological tests and complementary physical-chemical analyses were performed to characterise the wastewater and sludge composition in the context of activated sludge modelling. The proposed model was calibrated under steady-state conditions and validated under dynamic flow conditions. The model was successfully used to obtain insight into the existing plant performance, possible extension and options for process optimisation. The model illustrated the potential capacity of the plant to achieve full denitrification and to handle a higher hydraulic load. Moreover, the use of a mathematical model as an effective tool in decision making was demonstrated.

Energy and process data processing and visualisation for optimising wastewater treatment plants

2015 ◽  
Vol 10 (1) ◽  
pp. 10-18 ◽  
Author(s):  
Christian M. Thürlimann ◽  
David J. Dürrenmatt ◽  
Kris Villez
Keyword(s):  
Wastewater Treatment ◽  
Performance Indicator ◽  
Wastewater Treatment Plants ◽  
Data Communication ◽  
Decision Support Tool ◽  
Plant Performance ◽  
Process Data ◽  
Support Tool ◽  
Effluent Quality ◽  
Visualisation Tool

For complex systems such as wastewater treatment plants (WWTPs), effective data communication is an important step to enable operators to assess their plant. However, examples in practice show that this step is insufficiently considered. In this article, we describe a fast, relevant, and intuitive decision-support tool for operators. We have developed a key performance indicator (KPI) visualisation tool for energy and process data embedded in a larger process optimisation software. The KPI set consists of indicator values relating to energy and effluent quality. In order to ensure that the visualisation tool will be used and cover the needs of the plant staff, we developed this part of the software in collaboration with two WWTPs. At the time of writing, the tool is used in the daily operation of both plants. The operators see the tool's most important advantages as its ability to quickly assess current plant performance and to simplify the tracking and analysis of inter- and intra-process relationships and dynamics.

On-line microwave total solids sensoring in sewage characterization

2009 ◽  
Vol 59 (7) ◽  
pp. 1291-1297
Author(s):  
H. Poutiainen ◽  
S. Laitinen ◽  
P. Juntunen ◽  
H. Heinonen-Tanski
Keyword(s):  
Wastewater Treatment ◽  
Municipal Wastewater ◽  
Treatment Plant ◽  
Organic Load ◽  
Measured Signal ◽  
Municipal Wastewater Treatment ◽  
Wastewater Treatment Process ◽  
Total Solids ◽  
Wastewater Stream ◽  
On Line

We describe a novel application for a microwave on-line sensor to measure the total solids (TS) load entering a municipal wastewater treatment plant (WWTP) from slaughterhouse sewage and some sanitary wastewaters. Measuring this kind of wastewater stream is very challenging, because it contains a high, but varying organic load with nitrogen, phosphorus and microorganisms. The reliability of the measured signal was studied by comparison with laboratory analyses and a correlation is presented of TS-value with other parameters that are typically followed in a wastewater treatment process. The results suggest that on-line microwave sensoring could be used to monitor total solids in wastewater influent. Our results show that the on-line microwave sensor and laboratory reference analyses give similar results with a good correlation between the two techniques. Furthermore, we demonstrate that the total solids values correlate well with conductivity, total nitrogen and BOD7 values but not with phosphorus, pH and temperature.

scholarly journals A Feasible Data-Driven Mining System to Optimize Wastewater Treatment Process Design and Operation

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1342 ◽  
Author(s):  
Yong Qiu ◽  
Ji Li ◽  
Xia Huang ◽  
Hanchang Shi
Keyword(s):  
Data Mining ◽  
Wastewater Treatment ◽  
Data Warehouse ◽  
Process Design ◽  
High Efficiency ◽  
Data Driven ◽  
Process Data ◽  
Mining System ◽  
Wastewater Treatment Process ◽  
Data Mining System

Achieving low costs and high efficiency in wastewater treatment plants (WWTPs) is a common challenge in developing countries, although many optimizing tools on process design and operation have been well established. A data-driven optimal strategy without the prerequisite of expensive instruments and skilled engineers is thus attractive in practice. In this study, a data mining system was implemented to optimize the process design and operation in WWTPs in China, following an integral procedure including data collection and cleaning, data warehouse, data mining, and web user interface. A data warehouse was demonstrated and analyzed using one-year process data in 30 WWTPs in China. Six sludge removal loading rates on water quality indices, such as chemical oxygen demand (COD), total nitrogen (TN), and total phosphorous (TP), were calculated as derived parameters and organized into fact sheets. A searching algorithm was programmed to find out the five records most similar to the target scenario. A web interface was developed for users to input scenarios, view outputs, and update the database. Two case WWTPs were investigated to verify the data mining system. The results indicated that effluent quality of Case-1 WWTP was improved to meet the discharging criteria through optimal operations, and the process design of Case-2 WWTP could be refined in a feedback loop. A discussion on the gaps, potential, and challenges of data mining in practice was provided. The data mining system in this study is a good candidate for engineers to understand and control their processes in WWTPs.

Pilot plant performance and model calibration of a sequencing batch air-lift reactor

1997 ◽  
Vol 35 (1) ◽  
pp. 121-128
Author(s):  
A. Brenner ◽  
N. Ben-Shushan ◽  
M. H. Siegel ◽  
J. C. Merchuk
Keyword(s):  
Optimization Technique ◽  
Plant Performance ◽  
Upflow Anaerobic Sludge Blanket ◽  
Synthetic Wastewater ◽  
Anaerobic Sludge ◽  
Model Parameters ◽  
Wastewater Treatment Process ◽  
Air Lift Reactor ◽  
Anaerobic Sludge Blanket ◽  
Air Lift

A sequencing batch wastewater treatment process was studied in a 200 L air-lift reactor (ALR), using a synthetic wastewater. A modification of the SBR process was introduced to exploit the ALR's geometric structure using an upflow anaerobic sludge blanket (UASB) mode of feeding. The mean COD removal efficiency of the process was extremely high. A study was made of the change in the filtered COD concentration in the reactor as a function of time during a cycle. A partial reduction in the COD was observed after the UASB Fill stage. Further removal of the residual COD was achieved within a very short time once air was supplied to the system. These phenomena required the inclusion of a biosorption-storage concept in the mathematical description of the system, in order to predict more precisely the COD transformations. The mathematical model parameters were evaluated experimentally and then calibrated with the aid of an optimization technique. Experimental results including COD, MLVSS, DO and OUR changes showed good agreement with model predictions.

Wastewater treatment plant, process control experiences using a minicomputer

1983 ◽  
Vol 10 (2) ◽  
pp. 214-222 ◽  
Author(s):  
Brian A. Monaghan
Keyword(s):  
Wastewater Treatment ◽  
Process Control ◽  
Activated Sludge ◽  
Data Acquisition ◽  
Real Time ◽  
Treatment Plant ◽  
Plant Performance ◽  
Oxygen Control ◽  
Dissolved Oxygen Control ◽  
And Control

Since 1978, the Wastewater Technology Centre has investigated the use of continuous monitoring sensors and real-time computers for automated data acquisition and control of the activated sludge process. The aim of this work is to improve plant performance and reliability through the application of effective process control strategies.This paper highlights our experiences pertaining to: (a) evaluation of online instrumentation; (b) software development for data acquisition and control; and (c) process control strategies investigated. The majority of this study was carried out using two parallel 16.4 m3∙d pilot plants interfaced to an HP 1000 minicomputer. Keywords: Activated sludge, automated process control, wastewater treatment, dissolved oxygen control, online instrumentation, real-time computer, energy saving, minicomputer, step feed aeration.

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