Activated sludge image analysis system: monitoring settleability and effluent clarity

2005 ◽  
Vol 52 (10-11) ◽  
pp. 193-199 ◽  
Author(s):  
R. Jenné ◽  
E.N. Banadda ◽  
I.Y. Smets ◽  
A. Bamelis ◽  
L. Verdickt ◽  
...  
Keyword(s):  
Image Analysis ◽  
Activated Sludge ◽  
Suspended Solids ◽  
Analysis Procedure ◽  
Volume Index ◽  
Image Analysis System ◽  
Sludge Volume Index ◽  
Analysis System ◽  
The One

A fully automized image analysis procedure is presented for fast and reliable characterization of the activated sludge composition. In previous research, relations between filament abundance and floc shape on the one hand, and the Sludge Volume Index on the other hand were sought. This work aims at demonstrating the use of the image analysis information as an indication for the amount of suspended solids in the effluent.

Monitoring activated sludge settling properties using image analysis

2004 ◽  
Vol 50 (7) ◽  
pp. 281-285 ◽  
Author(s):  
R. Jenné ◽  
E.N. Banadda ◽  
I.Y. Smets ◽  
J.F. Van Impe
Keyword(s):  
Image Analysis ◽  
Activated Sludge ◽  
Volume Index ◽  
Filament Length ◽  
Sludge Volume Index ◽  
Filamentous Bulking ◽  
Sludge Properties ◽  
Fully Automatic ◽  
The One ◽  
Sludge Settling

The goal of this study is to develop a monitoring system for activated sludge properties, as this is an essential tool in the battle against filamentous bulking. A fully automatic image analysis procedure for recognising and characterising flocs and filaments in activated sludge images has been optimised and subsequently used to monitor activated sludge properties in a lab-scale installation. The results of two experiments indicate that the image information correlates well with the Sludge Volume Index. It is shown that, at the onset of filamentous bulking, there is an increase in total filament length on the one hand, and a change in floc shape on the other hand.

Application of Image Analysis System for Study of Activated Sludge Flocs

1986 ◽  
Vol 21 (1) ◽  
pp. 130-140 ◽  
Author(s):  
Da-hong Li ◽  
J. J. Ganczarczyk
Keyword(s):  
Image Analysis ◽  
Activated Sludge ◽  
Statistical Processing ◽  
Equivalent Diameter ◽  
Image Analysis System ◽  
Sectional Area ◽  
Cross Sectional ◽  
Computerized Image Analysis ◽  
Sludge Flocs ◽  
Analysis System

Abstract The computerized image analysis system has been successfully used for determination and statistical processing of the following geometric characteristics of activated sludge flocs: longest dimension, breadth, equivalent diameter, cross-sectional area, perimeter, elongation, and circularity. These parameters could be effectively and precisely determined by the system applied. In addition, the studied method, as compared to direct microscope observation and photography floc-sizing methods, was found to be more accurate, less time-consuming, and less dependent on the investigators.

Model-based frequency response characterization of a digital-image analysis system for epifluorescence microscopy

1992 ◽  
Vol 31 (8) ◽  
pp. 1083
Author(s):  
Rajeeb Hazra ◽  
Charles L. Viles ◽  
Stephen K. Park ◽  
Stephen E. Reichenbach ◽  
Michael E. Sieracki
Keyword(s):  
Image Analysis ◽  
Frequency Response ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Epifluorescence Microscopy ◽  
Image Analysis System ◽  
Model Based ◽  
Analysis System ◽  
Digital Image Analysis System

Use of image analysis for sludge characterisation: studying the relation between floc shape and sludge settleability

2006 ◽  
Vol 54 (1) ◽  
pp. 167-174 ◽  
Author(s):  
R. Jenné ◽  
E.N. Banadda ◽  
G. Gins ◽  
J. Deurinck ◽  
I.Y. Smets ◽  
...  
Keyword(s):  
Image Analysis ◽  
Principal Component ◽  
Analysis Procedure ◽  
Volume Index ◽  
Data Sets ◽  
Shape Descriptors ◽  
Automatic Image Analysis ◽  
Sludge Volume Index ◽  
Fully Automatic ◽  
Sludge Settleability

This paper starts by presenting a fully automatic image analysis procedure for characterisation of flocs and filaments in activated sludge images. Thereafter the attention is directed towards the results of four lab-scale experiments, in which image information is related to sludge settleability in terms of sludge volume index. This relation is statistically confirmed by applying a principal component analysis to the data. In addition, the redundancy in the data sets is studied with regard to floc shape descriptors and the monitoring potential of image analysis is demonstrated by means of a multiple linear regression exercise.

Estimation of suspended solids concentrations in activated sludge settling tanks

1997 ◽  
Vol 35 (8) ◽  
pp. 127-135 ◽  
Author(s):  
Youngchul Kim ◽  
Wesley O. Pipes ◽  
Paul-Gene Chung
Keyword(s):  
Activated Sludge ◽  
Suspended Solids ◽  
Marked Effect ◽  
Treatment Plant ◽  
Accurate Method ◽  
Volume Index ◽  
Sludge Volume Index ◽  
Solids Concentration ◽  
Exponential Decrease ◽  
Sludge Settling

This is a report of a field study based on data from an activated sludge process in a wastewater treatment plant in Chester, Pennsylvania, USA. The objective was to develop an accurate method for estimation of the average suspended solids concentration (SSB) of the layer of sludge in the settling tanks (the “sludge blanket”). Plant operators estimated SSB by averaging the mixed liquor suspended solids (Sm) and the return sludge suspended solids (Su) concentrations. Measurement of SSB showed that averaging Sm and Su frequently overestimated SSB by a large amount. A different relationship between SSB and parameters which are normally measured for operational purposes was developed. The parameters are Su, the overflow rates and data from the sludge volume index (SVI) measurement. It was found that an increasing overflow rate will result in an exponential decrease in the ratio of SSB to Su. Also, the SVI has a marked effect on the ratio of SSB to Su and thus on the amount of suspended solids which can be stored in the settling tanks. The proposed estimation equation was found to be statistically superior to estimation by averaging the Sm and Su.

Prediction of sludge volume index bulking using image analysis and neural network at a full-scale activated sludge plant

2015 ◽  
Vol 57 (37) ◽  
pp. 17195-17205 ◽  
Author(s):  
Halime Boztoprak ◽  
Yüksel Özbay ◽  
Dünyamin Güçlü ◽  
Murat Küçükhemek
Keyword(s):  
Neural Network ◽  
Image Analysis ◽  
Activated Sludge ◽  
Full Scale ◽  
Volume Index ◽  
Sludge Volume Index

Physical Characterization of PM10 and PM2.5 in Belgrade Atmosphere by SEM/EDX and Image Analysis System

2007 ◽  
Author(s):  
Velibor T. Novaković ◽  
Mirjana D. Tasić ◽  
Branislava urić-Stanojević ◽  
Slavica F. Rajšić ◽  
Zoran R. Mijić
Keyword(s):  
Image Analysis ◽  
Physical Characterization ◽  
Image Analysis System ◽  
Pm10 And Pm2.5 ◽  
Analysis System

Operating Experiences at Low Solids Retention Time

1984 ◽  
Vol 16 (12) ◽  
pp. 661-672 ◽  
Author(s):  
T E Wilson ◽  
W A Ambrose ◽  
H O Buhr
Keyword(s):  
Activated Sludge ◽  
Retention Time ◽  
Suspended Solids ◽  
Volume Index ◽  
Sludge Volume Index ◽  
Effluent Quality ◽  
Mixed Liquor ◽  
Solids Retention Time ◽  
Solids Retention ◽  
Typically Achieving

Five full scale activated sludge plants have been operated at low solids retention time (SRT, monthly averages as low as 0.8 days) and mixed liquor suspended solids (MLSS, monthly averages as low as 500 mg/l) values for 2 to 3 years. Operating results for this period are compared to 3 to 3-1/2 years of operation at conventional, higher, SRT and MLSS values. The data show that the lower SRT operation provided better effluent quality, typically achieving less than 15 mg/l of BOD5 or suspended solids, while not significantly increasing either the total (dry) sludge production or the sludge volume index (SVI). These data indicate that plants can be built and operated using significantly smaller tankage than conventionally accepted.

Specific Shape Characterization of Carbon Black Primary Units

1973 ◽  
Vol 46 (1) ◽  
pp. 204-231 ◽  
Author(s):  
W. M. Hess ◽  
G. C. McDonald ◽  
E. Urban
Keyword(s):  
Image Analysis ◽  
Carbon Black ◽  
Full Range ◽  
Image Analysis System ◽  
Unit Size ◽  
Shape Information ◽  
Dimensional Shape ◽  
Specific Shape ◽  
Analysis System

Abstract A full field feature specific image analysis system has been developed for direct morphological characterization of carbon black in the electron microscope. The system provides quantitative size and non-dimensional shape information, as well as qualitative classification into specific shape categories using pattern recognition programming methods. Data on samplings of 500–1000 primary black units can be recorded on magnetic tape in less than 10 minutes. Although not yet tested on a full range of rubber grade blacks, the new system has demonstrated good sensitivity in resolving morphological differences among a series of four HAF blacks of varied DBP absorption. The blacks exhibited large frequency variations across nine specific shape categories which range from spheroidal to fibrous types. Within each category, the unit size and non-dimensional shape factors were similar for all four blacks. On a composite average basis, however, large differences in unit size (longest dimension or projected area), anisometry (length/width ratio), and irregularity (perimeter/area ratio) were observed. The new image analysis system also has the capability of volume measurements based on microdensitometry. Although data is limited at this time, such measurements should provide more three-dimensional approximations of carbon black unit size. It is also anticipated that microdensitometry will aid in the determination of domain (particle) size.

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