Towards on-line quantification of flocs and filaments by means of image analysis for optimization and control of activated sludge plants.
One of the main reasons for failing of the sedimentation process in activated sludge waste water treatment systems is filamentous bulking. This is a problem of world-wide nature that occurs when the ratio of filamentous to floc forming bacteria is too large. A fully automatic image analysis method for recognizing flocs and filaments in an activated sludge sample is presented. Computer generated images of flocs and filaments, as well as images of activated sludge, are used to assess the capability of simple shape descriptors to distinguish between flocs and filaments. Five different shape descriptors are scrutinized, three of which are derived from size descriptors, namely, the aspect ratio, the roundness, and the form factor. The fractal dimension and the reduced radius of gyration complete the list. The results yield that the form factor is the least suitable and the reduced radius of gyration is the most suitable shape descriptor to accurately identify flocs and filaments in a random activated sludge sample. Based on this, the ratio of flocs to filaments can be estimated automatically. Furthermore, it is proposed that by combining this information with a total biomass concentration measurement, the individual concentrations of flocs and filaments can be determined. Consequently, the method presented may form the basis for a sensor that acts as an early warning system for filamentous bulking.
Jenné
R
R
BioTeC--Bioprocess Technology and Control, Katholieke Universiteit Leuven, Kasteelpark Arenberg 22, B-3001 Leuven, Belgium.
Cenens
C
C
Van Impe
J F
JF
D001515:Beer; D007220:Industrial Waste; D008962:Models, Theoretical; D012722:Sewage; D018505:Waste Management / Q000379:methods*
D007220:Industrial Waste; D012722:Sewage