Method for building filamentous bacterium SVI (sludge volume index) characteristic model

Abstract

A method for building a filamentous bacterium SVI (sludge volume index) characteristic model is an important branch of the technical field of advanced manufacture, and is also an important part of the field of water treatment. In order to solve the problems that filamentous bacterium sludge expansion is caused by numerous factors and a mechanism model is difficultly built, based on filamentous bacterium sludge expansion causation factor analysis, dynamic characteristics of filamentous bacterium growth are extracted, and model parameters are corrected by a data statistical method. An SVI is predicted by the aid of relevant process variables and a filamentous bacterium sludge expansion mechanism, the problem of difficulty in building a sludge expansion model is solved, adaptability of the model to environmental differences in the sewage treatment process is improved, and monitoring of abnormal conditions of the sewage treatment process is guaranteed. Experimental results indicate that the model can rapidly and effectively predict the SVI, is high in prediction accuracy and has excellent adaptability to the environmental differences, and efficient stable operation and monitoring of the abnormal conditions of the sewage treatment process are guaranteed.

Description

technical field [0001] The present invention uses data regression analysis to design a filamentous bacteria sludge bulking index SVI characteristic model based on filamentous bacteria dynamics. The sludge volume index (SVI) is an important index to reflect the sludge settling compression performance and to judge the sludge bulking phenomenon in abnormal sewage treatment conditions. Predicting this index is of great significance to realize the prevention and suppression of sludge bulking. There are many causes of filamentous bacteria sludge bulking, and the formation mechanism is complex. The research on the SVI characteristic model of filamentous bacteria sludge bulking is aimed at realizing the normal and stable operation of the sewage treatment process. It is an important branch in the field of advanced manufacturing technology. An important part of the water treatment field. Background technique [0002] With the rise of the sewage treatment industry across the country, ...

AI Technical Summary

Problems solved by technology

The former mainly depends on the accuracy and stability of the measurement tools. The measurement process is easily affected by the environment, takes a lot of time, and lacks a standard calibration model. In addition, the biggest defect of this method is that it cannot be measured online in real time, and it is difficult to formulate a suitable control strategy in time.

The data-driven soft measurement predicts SVI through relevant auxiliary variable data. The prediction results of this method have high accuracy, but the biochemical reaction and microbial growth process of activated sludge are ignored, and only the input data and output data are analyzed. The correlation between the results does not describe the formation mechanism of filamentous bacteria sludge bulking, which is likely to cause data loss of related variables and cannot adapt to environmental differences

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