Abstract
The paper discusses the use of an artificial neural network to control the operation of wastewater treatment plants with activated sludge. The task of the neural network in this case is to calculate (predict) the readings of the probe measuring the concentration of nitrate nitrogen (V) in one of the biological reactor tanks. Neural networks are known for their ability to universal approximation of virtually any relationship, including the function of many variables, but the process of “training” the network requires the presentation of many sets of input data and corresponding expected results. This is a difficulty in the case of wastewater treatment plants, because some key process parameters are usually not measured online (samples are taken and measurements are taken in the laboratory), and even if they are, the time intervals are large. Bearing in mind the aforementioned difficulty, this work uses a set of input data consisting only of information that can be measured with measuring probes. As a result of the conducted experiments a high compliance of the probe’s prediction with the expected values was obtained. The paper also presents data preparation and the network “training” process.
Highlights
Municipal wastewater treatment plants are installations operating under conditions of continuous variation of both substrate and hydraulic load
The acquisition of knowledge about the operating conditions of wastewater treatment plants can be divided into two main ways: online measurements and laboratory tests, the former being obviously suitable for the purpose of dynamic plant control
One of the techniques of detecting irregularities of the measuring probe indications or the occurrence of unusual conditions in the operation of a wastewater treatment plant is the use of artificial intelligence techniques to implement a virtual measuring sensor [4]
Summary
Municipal wastewater treatment plants are installations operating under conditions of continuous variation of both substrate and hydraulic load. In this work an artificial neural network was used as a base to create a virtual sensor of nitrate nitrogen (V) concentration in the denitrification chamber of a biological reactor with activated sludge. The indication of this probe shows whether the effect of removing nitrogen compounds from wastewater is correct. This means that the control system must be resistant to accidental fluctuations in the results, while these fluctuations can represent a large percentage of the measured value This creates an additional difficulty in detecting a situation in which the measuring probe for some reason loses the measurement precision or the measuring probe works properly but the working conditions of the treatment plant differ from the typical ones, e.g. as a result of industrial wastewater discharge disturbing the plant. The aim of the research described in this paper was to create a virtual nitrate nitrogen (V) sensor based on an artificial neural network, which as input data will use the indications of other probes located in different locations of the sewage treatment plant
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