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.

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.

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.

Effects of sludge settling characteristics in the BNR system

2000 ◽  
Vol 42 (3-4) ◽  
pp. 283-288 ◽  
Author(s):  
Z. Yun ◽  
W. Yo ◽  
Y. Yi ◽  
S. Choi ◽  
E. Choi ◽  
...  
Keyword(s):  
Settling Tank ◽  
Volume Index ◽  
Anoxic Zone ◽  
Sludge Volume Index ◽  
Analytical Accuracy ◽  
Fast Settling ◽  
Sludge Settling ◽  
Extracellular Polymer ◽  
Sludge Settleability ◽  
Settling Characteristics

Although the BNR system design assumes no sludge settling problems in the final settling tank, the fluctuation of daily loading and up to 40% of anaerobiosis in the BNR system would be considerable factors in determining the sludge settleability. The sludge volume index (SVI) is a classical parameter to examine the sludge settleability but it has a limited value to evaluate the overall settling characteristics. The extracellular polymer (ECP) content in sludge has long been considered as an indicator of biological flocculation in activated sludge process, but the skepticism on analytical accuracy limits the usage in settling study. This study focused on evaluating the BNR system performance related to the sludge settling characteristics under the controlled laboratory environment. A 5-stage BNR system (anaerobic-anoxic-3 stage oxic) was operated with the HRTs from 3.9 to 7.6 hours. In order to determine the sludge settling properties, both SVI and ECP content were monitored. The ECP contents in the sludge sample were measured by the slime-washing step followed by high-G centrifugation and sonication. The gel-electrophoresis was used to detect the DNA in the sonicated samples to determine the intracellular polymer contamination. It has been found that the anaerobiosis in the anaerobic and anoxic zone that consisted of 37% of reactor volume could not deteriorate the sludge settling properties even at the HRT of 3.9 hours. The SVI values of sludge taken from the reactor with the HRT of 7.2 hours averaged to less than 50 mL/gr. It was postulated that a fast settling sludge in the BNR system could not always ensure production of clear effluent. The sludge with very low SVI might not achieve a complete biological flocculation potential. In addition, the degree of denitrification in the BNR system could be related to the sludge settleability.

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

Use of image analysis and rheological studies for the control of settleability of filamentous bacteria: application in SBR reactor

2001 ◽  
Vol 43 (3) ◽  
pp. 27-33 ◽  
Author(s):  
C. Dagot ◽  
M. N. Pons ◽  
M. Casellas ◽  
G. Guibaud ◽  
P. Dollet ◽  
...  
Keyword(s):  
Image Analysis ◽  
Sequencing Batch Reactor ◽  
Batch Reactor ◽  
Automated Image Analysis ◽  
Volume Index ◽  
Filamentous Bacteria ◽  
Sludge Volume Index ◽  
Floc Size ◽  
First Results

To monitor the ability of flocs to settle in Sequencing Batch Reactor sludge, two methods were tested during two operation cycles. Firstly, an automated image analysis procedure has been tested to quantify the floc size and the length and number of filaments. Secondly, rheological measurements (Bingham viscosity and shear stress) have been used to characterise the dispersion of the sludge which can reflect the cohesive strength of aggregates and so the influence of filamentous bacteria on rheological properties. These results were compared with settling parameters such as Sludge Volume Index or settling velocity. Correlations between the measured parameters with image analysis and parameters such as Sludge Volume Index have been obtained. If it is more difficult to analyze rheological results, it seems however that the thixotropy and the Bingham viscosity distinguish poor settlement owing to some filamentous bulking. The first results are promising, although they require confirmation in the long term.

Study of filamentous bacteria by image analysis and relation with settleability

2002 ◽  
Vol 46 (1-2) ◽  
pp. 363-369 ◽  
Author(s):  
M. da Motta ◽  
M.N. Pons ◽  
N. Roche
Keyword(s):  
Image Analysis ◽  
Wastewater Treatment ◽  
Settling Velocity ◽  
Treatment Plant ◽  
Volume Index ◽  
Morphological Parameters ◽  
Filamentous Bacteria ◽  
Sludge Volume Index ◽  
Floc Size ◽  
Different Temperatures

An automated procedure for the characterisation by image analysis of the morphology of activated sludge has been used to monitor the biomass in a pilot wastewater treatment plant during two runs inoculated with a different sludge and operated at two different temperatures. The bulking events were easily detected by image analysis. Correlations were found between settleability properties (Sludge Volume Index and settling velocity) and the morphological parameters (filament total length, filament number and floc size).

Optimization of an Image Analysis Procedure for Monitoring Activated Sludge Settleability

2004 ◽  
Vol 37 (3) ◽  
pp. 345-350 ◽  
Author(s):  
R. Jenné ◽  
E.N. Banadda ◽  
I.Y. Smets ◽  
G. Gins ◽  
M. Mys ◽  
...  
Keyword(s):  
Image Analysis ◽  
Activated Sludge ◽  
Analysis Procedure ◽  
Sludge Settleability

Automated monitoring of activated sludge in a pilot plant using image analysis

2001 ◽  
Vol 43 (7) ◽  
pp. 91-96 ◽  
Author(s):  
M. da Motta ◽  
M. N. Pons ◽  
N. Roche
Keyword(s):  
Image Analysis ◽  
Wastewater Treatment ◽  
Activated Sludge ◽  
Size Distribution ◽  
Wastewater Treatment Plant ◽  
Pilot Plant ◽  
Settling Velocity ◽  
Treatment Plant ◽  
Volume Index ◽  
Sludge Volume Index

An automated procedure for the characterisation by image analysis of the morphology of activated sludge has been used to monitor the biomass in a pilot wastewater treatment plant, in complement to the usual settleability (sludge volume index, settling velocity) and size distribution (by laser granulometry) measurements.

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