Advanced monitoring and control of anaerobic wastewater treatment plants: diagnosis and supervision by a fuzzy-based expert system

2001 ◽  
Vol 43 (7) ◽  
pp. 191-198 ◽  
Author(s):  
A. Puñal ◽  
J. Rodríguez ◽  
A. Franco ◽  
E. F. Carrasco ◽  
E. Roca ◽  
...  
Keyword(s):  
Expert System ◽  
Expert Knowledge ◽  
Wastewater Treatment Plants ◽  
Rule Base ◽  
Monitoring And Control ◽  
Anaerobic Digesters ◽  
On Line ◽  
And Control ◽  
Logic Inference ◽  
Microsoft Windows

A fuzzy-based expert system (ES) for the diagnosis and supervision for anaerobic digesters is presented. The system was developed in a Microsoft Windows support using fuzzy logic inference together with a rule base for the implementation of expert knowledge. The ES runs on-line through three main modules, which determine the state and trend of the process, and the best set points for the actuation on the final control elements of the plant. Two further modules run in parallel, when they are required by the operator, using off-line and on-line information for the detection of inhibition due to toxic compounds in the process and for the validation of the on-line diagnosis. The diagnosis and supervision ES was tuned up in order to adjust the membership functions describing the process, and lately tested, running on-line, to study the response of the rule base.

On-line monitoring equipment for wastewater treatment processes: state of the art

2003 ◽  
Vol 47 (2) ◽  
pp. 1-34 ◽  
Author(s):  
P.A. Vanrolleghem ◽  
D.S. Lee
Keyword(s):  
Wastewater Treatment ◽  
Control Systems ◽  
Model Calibration ◽  
Wastewater Treatment Plants ◽  
Monitoring And Control ◽  
Monitoring Equipment ◽  
Automatic Control Systems ◽  
Treatment Processes ◽  
On Line ◽  
And Control

A (non-exhaustive) survey of new and existing technologies for the monitoring of wastewater treatment plants is presented. Emphasis is given to the way these sensors can provide insight in the ongoing (bio-) processes. Three different uses for sensors can be found: for monitoring (operator support), in automatic control systems and as tools for plant auditing/optimization/modelling by consultants. From this, sensors have been classified in two basic types: (i) reliable, simple and low maintenance sensors for day-to-day monitoring and control and (ii) advanced, higher maintenance sensors that are used in auditing, model calibration and optimisation. The paper is organized according to the typical unit processes of biological wastewater treatment systems: anaerobic digestion, activated sludge, nutrient removal and sedimentation. Attention is drawn to a number of practical problems associated with the use of sophisticated sensors in the harsh (dirty) conditions of wastewater treatment processes. The use of autocalibration and built-in sensor checks, cleaning systems and reliable sample preparation units is illustrated. The paper ends with a discussion of the applicability of the different sensors.

Advanced monitoring and control of anaerobic wastewater treatment plants: fault detection and isolation

2001 ◽  
Vol 43 (7) ◽  
pp. 183-190 ◽  
Author(s):  
J-Ph Steyer ◽  
A. Genovesi ◽  
J. Harmand
Keyword(s):  
Wastewater Treatment ◽  
Fault Detection ◽  
Wastewater Treatment Plants ◽  
Real Life ◽  
Practical Interest ◽  
Fault Detection And Isolation ◽  
Monitoring And Control ◽  
On Line ◽  
And Control ◽  
Large Improvement

In this paper, a fault detection and isolation approach using fuzzy logic is described for on-line analysis of problems occurring in anaerobic digestion processes. The measurements available on the process are preprocessed to build a vector of fault residuals indicating the magnitude of the problems. This vector is classified into a prespecified category (i.e., a class) which is a state of the system, according to discrimination fuzzy rules. Three different types of classes were defined in a hierarchical structure : sensors faults, sub-process faults and process faults. This approach was developed to handle in real time both technical and biological problems. Demonstration of the practical interest of this study was made using real life experiments and large improvement of the reliability and safety of the process was obtained, thus optimizing the overall wastewater treatment.

Standard signal processing using enriched sensor information for WWTP monitoring and control

2008 ◽  
Vol 57 (7) ◽  
pp. 1053-1060 ◽  
Author(s):  
I. Irizar ◽  
J. Alferes ◽  
L. Larrea ◽  
E. Ayesa
Keyword(s):  
Signal Processing ◽  
Wastewater Treatment Plants ◽  
Monitoring And Control ◽  
Standard Signal ◽  
Regression Parameters ◽  
Processing Module ◽  
On Line ◽  
Sensor Information ◽  
And Control

Important indicators for monitoring and control of wastewater treatment plants (WWTP) often have to be obtained from the processing of on-line signal trajectories. Therefore, the quality of sensor instantaneous measurements can be improved significantly if they are complemented with valuable information about the geometric features of their trajectories. The present paper describes the design and implementation of a Standard Signal Processing Architecture (SSPA) from which enriched sensor information is generated automatically. The SSPA has been made up of three complementary modules: the pre-processing module, the storage module and the post-processing module. Moreover, the SSPA has been parameterised so as to allow its adaptation to the specifications of every signal. By performing basic calculations on pre-processed signal trajectories, the storage module produces enriched vectors which collect information of the first and second time derivatives, average and variance values, peak values, linear regression parameters, curvature, etc. Then, the enriched information vectors can be exploited to implement customised monitoring and control tools. In this respect, the effectiveness of the SSPA has been demonstrated in three different practical cases: (1) OUR and KLa identification algorithms; (2) processing of measurements for real-time controllers; and, (3) detection of bend-points in on-line signals of SBR processes.

Infrared Sensing for On-Line Weld Geometry Monitoring and Control

1995 ◽  
Vol 117 (3) ◽  
pp. 323-330 ◽  
Author(s):  
P. Banerjee ◽  
S. Govardhan ◽  
H. C. Wikle ◽  
J. Y. Liu ◽  
B. A. Chin
Keyword(s):  
Plate Thickness ◽  
Welding Process ◽  
Temperature Gradients ◽  
Monitoring And Control ◽  
Depth Of Penetration ◽  
Bead Width ◽  
Weld Geometry ◽  
On Line ◽  
And Control ◽  
Welding Processes

This paper describes a method for on-line weld geometry monitoring and control using a single front-side infrared sensor. Variations in plate thickness, shielding gas composition and minor element content are known to cause weld geometry changes. These changes in the weld geometry can be distinctly detected from an analysis of temperature gradients computed from infrared data. Deviations in temperature gradients were used to control the bead width and depth of penetration during the welding process. The analytical techniques described in this paper have been used to control gas tungsten arc and gas metal arc welding processes.

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