Premium
Prediction of activated sludge filamentous bulking using ATP data and neural networks
Author(s) -
Brault JeanMartin,
Labib Richard,
Perrier Michel,
Stuart Paul
Publication year - 2011
Publication title -
the canadian journal of chemical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.404
H-Index - 67
eISSN - 1939-019X
pISSN - 0008-4034
DOI - 10.1002/cjce.20442
Subject(s) - activated sludge , segmented filamentous bacteria , artificial neural network , chemistry , pulp and paper industry , environmental science , computer science , artificial intelligence , environmental engineering , sewage treatment , engineering
Neural networks (NNs) were used to predict the onset of filamentous bulking, as described by trends in stirred sludge volume index, in a pulp and paper activated sludge treatment system. Variables related to activated sludge biomass viability, namely specific oxygen uptake rate (SOUR) and adenosine triphosphate (ATP), were used as inputs to the NN. ATP data were shown to improve NN performance in providing an early warning signal for bulking, both in terms of accuracy and prediction delay. A warning signal system was developed to provide operators with enough time to react and further investigate the causes of bulking.