Many variables are normally measured in an activated sludge waste water treatment plant. Some of them are strongly cross-correlated. Partial least squares (PLS) and principal component analysis (PCA) have been widely used with these kind of processes because they both can be used with redundant data
Modeling of activated sludge plants treatment efficiency with PLSR: a process analytical case study
โ Scribed by Satu-Pia Mujunen; Pentti Minkkinen; Pekka Teppola; Riitta-Sisko Wirkkala
- Publisher
- Elsevier Science
- Year
- 1998
- Tongue
- English
- Weight
- 343 KB
- Volume
- 41
- Category
- Article
- ISSN
- 0169-7439
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โฆ Synopsis
The most common waste water purification method within Finnish pulp and paper industry is activated sludge method. Activated sludge method is a complex biological process, where several physical, chemical, and microbiological mechanisms simultaneously affect the purification result. There are tens of processes and control parameters determined at the plants. However, the parameter sets do not include any parameters describing the special features of the industrial influent nor any parameters directly describing microbial composition of the sludge. Thus there seems to be an obvious need for new parameters. As a part of a cooperation project empirical data sets from three pulp and paper mills were studied with multivariate methods. The main interest was focused on the information covered by the presently measured process and control parameters and their capability to predict purification result or approaching bulking state. The descriptor variables for PLSR models were selected by using a forward stepwise procedure with cross-validation criteria. As conclusion of PLSR modeling, the parameters included most of the information needed to predict the approaching process drift, which was caused by sludge bulking. However, the models for purification efficiency or for effluent quality indicated an obvious lack of relevant information. The average purification result could still be predicted.
๐ SIMILAR VOLUMES
A Kalman filter was developed to overcome the problems caused by process drifting. Different types of models were used to predict response variables of an activated sludge waste-water treatment plant. These models were constructed using MLR, PCR, and PLS. The MLR-type regression coefficients were ca