KR102546802B1 - Integrated management system for sewage and wastewater treatment plants that can reduce greenhouse gas emissions using artificial intelligence - Google Patents

Abstract

The present invention relates to an integrated sewage and wastewater treatment plant management system capable of greenhouse gas emission reduction operation using artificial intelligence (AI). According to the present invention, the integrated sewage and wastewater treatment plant management system comprises: a sensor unit installed in each sewage and wastewater treatment plant to measure inflow water quality, inflow water quantity, operating factors, effluent water quality, effluent water quantity, by-product gas of a biological reactor, and greenhouse gas in real time or at predetermined time intervals; a prediction unit equipped with an AI program of collecting data from the sensor unit, analyzing the data through a learning algorithm to generate a prediction model for each sewage and wastewater treatment plant, and predicting the effluent quality and greenhouse gas concentration of the selected sewage and wastewater treatment plant on the basis of the prediction model; and a treatment process control unit selecting one or more control variables among the inflow water quantity and operation factors to control a process of the sewage and wastewater treatment plant when the outflow water quality and greenhouse gas concentration predicted by the prediction unit are outside the standard outflow water quality and standard greenhouse gas concentration.

Description

Integrated management system for sewage and wastewater treatment plants that can reduce greenhouse gas emissions using artificial intelligence}

The present invention relates to a system that enables greenhouse gas reduction operation while satisfying water quality standards at each sewage and wastewater treatment plant through the establishment of a predictive model using artificial intelligence.

Nitrous oxide (N ₂ O) as a greenhouse gas is mostly generated during the biological nitrogen removal process by nitrification/denitrification in sewage and wastewater treatment plants, and wastewater treatment plants occupy a very important position as a greenhouse gas emission source.

However, the technology for controlling greenhouse gases emitted from sewage and wastewater treatment plants is very lacking, and moreover, the effluent water quality standards are getting stricter every year. Operational skills are required.

As an example of the prior art, in Korean Patent Registration No. 10-1503688, a float having a buoyancy unit so as to float in an aeration tank; a by-product gas collection case installed on the upper part of the float; a dispersion cover installed on the top of the collecting case and composed of a dispersion unit having a perforated hole in the center; a measuring chamber installed above the dispersing unit and having one or more by-product gas outlets formed thereon; a sensor unit for measuring the by-product gas introduced into the measuring chamber; a controller for verifying and wirelessly transmitting the data measured by the sensor unit; A guide cover installed above the by-product gas outlet of the measurement chamber to protect the sensor unit and the control unit and guide the discharge flow of the by-product gas; the buoyancy unit cover covering the upper opening of the buoyancy unit at the lower side of the collecting case. Is formed, and a floating wireless by-product gas measuring device is proposed, characterized in that a fluid inlet is formed at one point of the buoyancy cover.

However, even in the case of the above technology, there is only a description of the monitoring of by-product gas in the bioreactor, and there is no suggestion of technology related to greenhouse gas reduction operation in sewage and wastewater treatment plants.

Republic of Korea Patent Registration No. 10-1503688

The present invention is to solve the above problems, and provides an integrated wastewater treatment plant management system that enables greenhouse gas reduction operation while satisfying water quality standards at each wastewater treatment plant through the establishment of a predictive model using artificial intelligence. is to do

As a means to achieve the above object, the integrated management system for sewage and wastewater treatment plants (hereinafter referred to as the "system of the present invention") capable of reducing greenhouse gas emissions using artificial intelligence is installed in each wastewater treatment plant in real time. Or a sensor unit for measuring inflow water quality, inflow water quantity, operation factor, outflow water quality, outflow water quantity, by-product gas and greenhouse gas of the bioreactor at predetermined time intervals; Artificial intelligence that collects data from the sensor unit, analyzes the data through a learning algorithm, creates a prediction model for each wastewater treatment plant, and predicts the effluent quality and greenhouse gas concentration of the selected wastewater treatment plant based on the prediction model. A prediction unit equipped with an intelligence program; If the effluent water quality and greenhouse gas concentration predicted by the prediction unit deviate from the standard effluent water quality and standard GHG concentration, the treatment process control unit controls the process of the corresponding sewage and wastewater treatment plant by selecting one or more control variables among the inflow water quantity and operating factors. It is characterized by including;

As an example, the inflow water quality, the outflow water quality, the by-product gas, and the greenhouse gas items are water quality analysis items such as temperature, BOD, TOC, COD, SS, TN, TP, NH ₄ -N, NO ₃ -N, It is characterized by including one or more of CO ₂ , O ₂ , and N ₂ O.

As an example, the treatment process control unit, when the effluent water quality and the greenhouse gas concentration predicted by the prediction unit deviate from the standard effluent water quality and the standard greenhouse gas concentration, virtually change one or more of the inflow water quantity and the operating factor, and the predicted It is characterized by controlling the process of the corresponding sewage and wastewater treatment plant by selecting one or more of the inflow water quantity and operating factors so that the effluent water quality and greenhouse gas concentration predicted by applying the model fall within the standard effluent water quality and standard greenhouse gas concentration range .

As an example, the prediction unit may include a data module for receiving and storing data from the sensor unit of each sewage and wastewater treatment plant; a feature derivation module for extracting one or more features for learning from the data collected from the data module; a learning module that performs deep learning based on the features extracted from the feature derivation module; A model generation module that receives the result information learned from the learning module and generates a predictive model for each sewage and wastewater treatment plant based on it; Characterized in that it includes; a prediction module for predicting effluent quality and greenhouse gas concentration of each wastewater treatment plant based on the prediction model of each wastewater treatment plant generated by the model generation module.

As an example, in the bioreactor of each sewage and wastewater treatment plant, it is configured inside the bioreactor, a floating port is formed at the bottom, a collection space is formed inside, and the gas collected in the collection space is released to the outside. A floating collection unit in which a gas discharge line discharged to is formed; a moisture absorbing unit connected to the lower end of the gas discharge line and having a moisture absorbing layer formed thereon so that moisture is removed while the gas flowing into the inside passes; A by-product gas and greenhouse gas monitoring device including a gas sensor unit for measuring the amount of by-product gas and greenhouse gas from the gas passing through the water absorption unit is further configured.

As an example, the by-product gas includes carbon dioxide and oxygen, and the greenhouse gas includes nitrous oxide.

As an example, the gas sensor unit is composed of a first gas sensor unit and a second gas sensor unit, and some of the gas that has passed through the moisture absorbing unit flows into the first gas sensor unit so that the mixed amount of carbon dioxide and oxygen in the gas It is characterized in that a part of the gas that has been sensed and passed through the moisture absorbing unit flows into the second gas sensor unit so that the amount of nitrous oxide in the gas is sensed.

As an example, the gas flowing into the second gas sensor unit is passed through the carbon dioxide absorbing unit having the carbon dioxide absorbing layer formed at the front end so that the gas from which carbon dioxide is removed is introduced into the second gas sensor unit.

As an example, the carbon dioxide absorbing unit includes a housing having an inlet line at the bottom and an exhaust line connected to the second gas sensor at the top, and a carbon dioxide absorbing layer filled with a carbon dioxide absorbing agent while dividing the housing into upper and lower portions. and a rotating shaft that is rotationally interlocked by a driving means and extends into the carbon dioxide absorption layer, and a plurality of stirring rods protruding from the rotation shaft into the carbon dioxide absorption layer and having hot wires embedded therein.

As an example, the floating collection unit includes a collection housing having a collection space formed therein, a floating sphere surrounding the collection housing, a second rotating shaft rotated by a driving means, and a plurality of fixings protruding from the second rotating shaft. It is characterized in that it is composed of a filter plate mounted with the same inclination gradient to the bar and the fixing bar and filtering foreign substances from colliding gas and pushing bubbles to expose the surface of the water.

As an example, a coating layer containing silicone oil is applied to the surface of the filter plate.

The system of the present invention has the advantage of enabling greenhouse gas reduction operation while satisfying water quality standards at each sewage and wastewater treatment plant through the establishment of a predictive model using artificial intelligence.

1 is a block diagram showing the system of the present invention;
Figure 2 is a block diagram showing the detailed configuration of the prediction unit shown in Figure 1,
Figure 3 is a schematic diagram showing a by-product gas and greenhouse gas monitoring device as one component of the system of the present invention,
4 is a schematic diagram showing an embodiment of a carbon dioxide absorbing unit as one configuration of the device shown in FIG. 3;
5 is a side cross-sectional view showing an embodiment of a floating collecting unit in one configuration of the device shown in FIG. 3;
6 is a plan view of the floating collection unit shown in FIG. 5;
Figure 7 is an operating state diagram of the wing in the floating collector shown in Figure 5.

Hereinafter, the present invention will be described in more detail through drawings and examples. Since the following description is for a specific example of the present invention, even if there is a conclusive and limited expression, it does not limit the scope of rights determined from the claims.

As shown in FIG. 1, the system 100 of the present invention is installed in each sewage and wastewater treatment plant (a), in real time or at predetermined time intervals, inflow water quality, inflow water quantity, operating factors, effluent water quality, effluent water quantity, by-products of the bioreactor A sensor unit 101 for measuring gas and greenhouse gas; Data of the sensor unit 101 is collected, and the data is analyzed through a learning algorithm to generate a prediction model for each wastewater treatment plant (a), and based on the prediction model, the effluent quality of the selected wastewater treatment plant and A prediction unit 102 equipped with an artificial intelligence program for predicting greenhouse gas concentration; When the effluent water quality and greenhouse gas concentration predicted by the prediction unit 102 deviate from the standard effluent water quality and greenhouse gas concentration, a process of controlling the process of the corresponding sewage and wastewater treatment plant by selecting one or more control variables from the inflow water quantity and operation factor It is characterized in that it includes; process control unit 103.

As shown in FIG. 1, the sensor unit 101 is installed in a plurality of sewage and wastewater treatment plants (a), and in real time or at predetermined time intervals, inflow water quality, inflow water quantity, operation factor, effluent water quality, effluent water quantity, by-products of the bioreactor As a configuration for measuring gas and greenhouse gases, the inflow water quality and inflow water quantity in the sewage and wastewater treatment plant (a), the operation factors of the unit processes in the treatment plant, and the effluent water quality and effluent water quantity are measured in real time or at predetermined time intervals to predict the prediction. Send to section 102.

The sensor unit 101 for measuring water quality includes sensors capable of measuring the flow rate and quality of inflow and outflow water (temperature, BOD, TOC, COD, SS, TN, TP, NH ₄ -N, NO ₃ -N, etc.) , It is made of a sensor that can measure the operating factors (DO, MLSS, sludge return flow rate, internal return flow rate, temperature, _etc. ) of the unit process in the treatment plant, and _the sensor part for measuring by-product gas and greenhouse gas It is made of a sensor that can measure N ₂ O.

In addition, it is natural that such a sensor may be installed in plurality in each reaction tank when the wastewater treatment plant and a plurality of reaction tanks are configured. In addition, the sensor may measure in real time, or at intervals of a predetermined time, for example, minutes or hours.

In particular, the sensor unit 101 includes a gas sensor unit 8 mentioned below, so that by-product gas and greenhouse gas mixing amount ( concentration) to be measured. The gas sensor unit 8 is configured in the bioreactor 2, and is configured in the by-product gas and greenhouse gas monitoring device 1 described below.

Here, the by-product gas includes carbon dioxide and oxygen, and the greenhouse gas includes nitrous oxide.

The prediction unit 102 collects data of the sensor unit 101, analyzes the data through a learning algorithm, generates a prediction model for each wastewater treatment plant, and selects a wastewater treatment plant based on the prediction model. It is characterized by being equipped with an artificial intelligence program that predicts the quality of runoff water and the concentration of greenhouse gases.

Here, various known technologies may be applied to the artificial intelligence program, but in the present invention, an example in which a learning algorithm based on deep learning is applied is presented.

Describing this in more detail, the prediction unit 102, as shown in FIG. 2, includes a data module 1021 for receiving and storing data from the sensor unit 101 of each sewage and wastewater treatment plant; a feature derivation module 1022 for extracting one or more features for learning from the data collected from the data module 1021; a learning module 1023 that performs deep learning based on the features extracted from the feature derivation module 1022; A model generation module 1024 for receiving the result information learned from the learning module 1023 and generating a predictive model for each sewage and wastewater treatment plant based on this; and a prediction module 1025 for predicting effluent quality and greenhouse gas concentration of each wastewater treatment plant based on the prediction model of each wastewater treatment plant generated by the model generation module 1024.

The data module 1021 may collect data online from the sensor units 101 of at least one wastewater treatment plant.

The feature derivation module 1022 may extract and separate one or more features for learning from data collected from the data module 1021 .

That is, the feature derivation module 1022 extracts the main factors required for learning from the vast amount of information collected by the data module 1021. For example, in each sewage and wastewater treatment plant, Features such as effluent quality, effluent quantity, by-product gas, and greenhouse gas can be extracted.

The learning module 1023 may perform learning based on the features extracted by the feature derivation module 1022 . Learning by the learning module 1023 may apply one or more selected from known learning algorithms.

The learning module 1023 may use a deep learning-based learning algorithm, and preferably may perform learning using a convolutional neural network (CNN) algorithm belonging to a deep learning neural network family.

The model generating module 1024 may receive the result information learned from the learning module 1023 and generate a predictive model for each sewage/wastewater treatment plant based on this. That is, the predictive model is a predictive model for each sewage and wastewater treatment plant, and this predictive model can be updated in real time by the collected information of the data module 1021.

The prediction module 1025 may predict effluent quality and greenhouse gas concentration of the selected wastewater treatment plant based on the prediction model of each wastewater treatment plant generated by the model generation module 1024 .

In this way, the system of the present invention creates a prediction model by learning input and stored data using artificial neural network technology, and predicts the effluent quality and greenhouse gas concentration of the selected sewage and wastewater treatment plant as a specific result based on the generated prediction model. This algorithm is implemented through various known technologies (Patent Publication No. 10-1629240, Patent Registration No. 10-1108031, Patent Registration No. 10-2190912, etc.) in the relevant technical field. Therefore, a detailed description thereof is omitted.

The treatment process control unit 103 controls the process of the corresponding sewage and wastewater treatment plant by selecting an adjustment variable when the effluent quality and greenhouse gas concentration predicted by the prediction unit 102 deviate from the standard effluent water quality and greenhouse gas concentration. corresponds to The control variable is characterized in that at least one of an inflow water amount and an operating factor.

To explain this in more detail, the treatment process control unit 103, when the effluent water quality and greenhouse gas concentration predicted by the prediction unit 102 deviate from the standard effluent water quality and greenhouse gas concentration, simulates one or more of the inflow water quantity and the operation factor. Controlling the process of the wastewater treatment plant will be.

By this control, the system of the present invention enables greenhouse gas reduction operation while satisfying the water quality standard discharged from the corresponding sewage and wastewater treatment plant.

Here, the operation factor as a control variable is not limited, but the flow rate of the blower, the flow rate of external carbon source, the flow rate inside the reaction tank, the flow rate of sludge returning, the flow rate of waste sludge, and the concentration of dissolved oxygen in the aerobic tank may be applicable.

For example, the treatment process control unit 103 may select the external carbon source flow rate and the internal conveyance flow rate as control variables when the concentration of NOx _- N among predicted effluent concentration values exceeds a reference concentration range. That is, by increasing the external carbon source flow rate and the internal return flow rate, it is possible to prevent the effluent concentration value from exceeding the reference range in the near future. It is possible to further include other control variables, but there is a burden of additional process time and cost.

In addition, when the concentration of NH ⁴⁺ -N exceeds the standard concentration range, you can select control variables including internal return flow rate and dissolved oxygen concentration in the aerobic tank. When the concentration of PO ₄ ^3- -P exceeds the standard concentration range, It is possible to select control variables including internal return flow rate, sludge return flow rate, and dissolved oxygen concentration in the aerobic tank.

The prediction unit 102 and the process control unit 103 may be configured in the central server (b).

With these configurations, the system 100 of the present invention refers to data on inflow water quality, inflow water quantity, operation factors of unit processes in the treatment plant, outflow water quality, outflow water quantity, by-product gas and greenhouse gas in the past, and the outflow of each device A water quality and GHG concentration prediction model is built, and the effluent quality and GHG concentration of the selected sewage and wastewater treatment plant are predicted by this prediction model to detect the time when control operation is required in advance, and the treatment process control unit 103 ) to select the type of control action (selection of control variable) and its size.

Meanwhile, in the present invention, as shown in FIG. 3, an example of a wastewater treatment plant (a) is shown, and the sewage and wastewater treatment plant (a) of this embodiment includes a bioreactor 2 in which a bioreaction is performed by inflow of sewage and wastewater. In addition, the bioreactor 2 provides an example in which a by-product gas and greenhouse gas monitoring device 1 is further included.

The by-product gas and greenhouse gas monitoring device (1, hereinafter referred to as “the device of the present invention”) is configured inside the bioreactor 2 as shown in FIG. 3, and a floating port 32 is formed at the bottom, a floating collection unit 3 having a collection space formed therein and a gas discharge line 36 discharging the gas collected in the collection space to the outside at an upper portion thereof; a moisture absorption unit 4 having a moisture absorption layer connected to the lower end of the gas discharge line 36 and having a moisture absorption layer through which the gas introduced into the inside passes through; It is characterized in that it includes; a gas sensor unit 8 for measuring the mixing amount of by-product gas and greenhouse gas from the gas passing through the moisture absorbing unit 4.

As mentioned above, the by-product gas includes carbon dioxide and oxygen, and the greenhouse gas includes nitrous oxide.

That is, the apparatus (1) of the present invention can sense the by-product gas generated in the bioreactor (2) in real time in a sewage and wastewater treatment plant to provide data for diagnosing the condition of the bioreactor (2), as well as to provide greenhouse gas emissions. It is possible to reduce greenhouse gases while satisfying water quality standards at sewage and wastewater treatment plants by sensing in real time and providing data on the amount of greenhouse gases.

The floating collection unit 3 is configured inside the bioreactor 2, and a floating port 32 is formed at the bottom thereof to float in the bioreactor 2, and a collection space is formed inside the bioreactor. It is to capture by-product gas and greenhouse gas generated in (2).

The collected gas is discharged to the rear end through the gas discharge line 36 .

Preferably, as shown in the drawing, the floating collecting part 3 is configured in a shape with an open bottom and the floating part 32 forms a certain distance from the lower end of the side wall to the upper part, so that in the floating collecting part 3 The lower end of the float 32 forms a blocking edge submerged on the surface of the water.

The reason why the blocking border is formed is to block the mixing of air outside the floating collection unit 3 to by-product gas (Off-Gas) and greenhouse gas collected inside the floating collection unit 3, so that the gas sensor unit This is to increase the accuracy of the sensing of (8). That is, it is to prevent the collection space formed by the floating collection unit 3 from being exposed to the outside air even when the floating collection unit 3 is shaken by various causes.

The moisture absorbing part 4 is characterized in that the gas discharge line 36 is connected to the lower end and a moisture absorption layer is formed so that moisture is removed while the gas introduced into the inside passes.

Since various known materials may be used for the moisture absorption layer in the moisture absorption portion 4, a detailed description thereof will be omitted.

In addition, as shown in the drawing, a pump 5 is configured at the rear end of the water absorbing part 4 to pass gas through the water absorbing part 4.

As shown in the drawing, it is reasonable to configure one more water absorption unit 4 at the rear end of the pump 5 to increase the water removal rate from the gas.

In this way, water is separated from the collected gas to increase the accuracy of sensing in the gas sensor unit 8 at the rear end, and to control the deposition of foreign substances mixed in water in the pump 5 to cause failure it is for

As shown in the drawing, the gas that has passed through the moisture absorption unit 4 is allowed to pass through the drying unit 6 to further lower the moisture content. In the case of the drying unit 6, various well-known devices may be applied, so a detailed description thereof will be omitted.

In addition, the gas sensor unit 8 is composed of a first gas sensor unit 81 and a second gas sensor unit 82 as shown in FIG. 3 and the like.

Some of the gas that has passed through the moisture absorbing unit 4 and the drying unit 6 flows into the first gas sensor unit 81 so that the mixed amount of carbon dioxide and oxygen in the gas is sensed. In this way, the mixing amount of carbon dioxide and oxygen in the gas, that is, the mixing amount of by-product gas is measured in real time by the first gas sensor unit 81, and such a measured value is transmitted to the prediction unit 102 as mentioned above. is to do

In addition, some of the gas that has passed through the moisture absorbing unit 4 and the drying unit 6 flows into the second gas sensor unit 82 so that the amount of nitrous oxide contained in the gas is sensed. In this way, the mixing amount of nitrous oxide in the gas, that is, the mixing amount of greenhouse gas, is measured in real time by the second gas sensor unit 82, so that even in this case, such a measured value is transmitted to the prediction unit 102 as mentioned above is to do

In particular, the gas flowing into the second gas sensor unit 82 passes through the carbon dioxide absorbing unit 7, which means that when the second gas sensor unit 82 measures the amount of nitrous oxide in the gas, carbon dioxide is converted into noise. This is to control the over-measurement of the mixing amount of nitrous oxide in the gas.

The carbon dioxide absorbing portion 7 has a carbon dioxide absorbing layer 72 formed therein, so that the gas introduced from the lower end of the carbon dioxide absorbing portion 7 passes through the carbon dioxide absorbing layer 72 while the carbon dioxide is removed. It is to be discharged to the second gas sensor unit (82).

The carbon dioxide adsorption layer 72 is formed by filling the carbon dioxide adsorbent, and various known materials such as soda lime may be applied to the carbon dioxide adsorbent.

In this way, the carbon dioxide absorbing unit 7 is configured at the front end of the second gas sensor unit 82 so that the second gas sensor unit 82 accurately measures the amount of nitrous oxide mixed in, thereby more accurately monitoring the emission of greenhouse gases is to do

Meanwhile, in the present invention, as shown in FIG. 4, an embodiment of the carbon dioxide absorbing unit 7 is proposed.

The carbon dioxide absorbing unit 7 of this embodiment includes a housing 71 having an inlet line 711 at the bottom and a discharge line 712 connected to the second gas sensor unit 82 at the top, and the housing ( 71) is partitioned into upper and lower parts, the carbon dioxide adsorbing layer 72 filled with the carbon dioxide absorbent, and the rotating shaft 74 extending into the carbon dioxide adsorbing layer 72 in rotational interlock by the driving means 73; It is characterized in that it includes a stirring bar 75 protruding in plurality from the inside of the carbon dioxide adsorption layer 72 from the rotating shaft 74 and having a hot wire 752 therein.

As mentioned above, the carbon dioxide absorbing unit 7 for removing carbon dioxide from the gas is configured in front of the second gas sensor unit 82, and the carbon dioxide absorbing layer 72 of the carbon dioxide absorbing unit 7 continues to When carbon dioxide is over-adsorbed on the carbon dioxide absorbent of the carbon dioxide adsorption layer 72 according to normal operation, the carbon dioxide removal efficiency of the carbon dioxide adsorption layer 72 is reduced, so that the second gas sensor unit 82 cannot accurately sense nitrous oxide. There is a problem that doesn't work.

Accordingly, in the present invention, the rotating shaft 74 and the stirring bar 75 are configured in the carbon dioxide absorbing unit 7 so that when the carbon dioxide adsorption layer 72 is clogged, the carbon dioxide in the carbon dioxide adsorption layer 72 is removed by heat while stirring. It is to allow carbon dioxide adsorbed from the absorbent to be desorbed.

The rotating shaft 74 is to be interlocked with rotation by a driving means 73 such as a motor, and the stirring rod 75 protrudes from the rotating shaft 74 to achieve stirring and to dissipate heat at the same time will be.

To this end, the stirring bar 75 has an outer shell 751 of heat transfer material and a hot wire 752 inside the outer shell 751. ) It is connected to the wire inside so that heat is generated in the hot wire 752 by applying electricity from the electricity supply means.

With this configuration, heat is uniformly transferred to the carbon dioxide adsorption layer 72 by stirring as well as heat generated by the rotation of the stirring bar 75 to increase the desorption efficiency.

The desorbed carbon dioxide is stored in the carbon dioxide storage tank 76 to be recycled for other purposes.

In addition, in the present invention, an embodiment of the floating collecting unit 3 is presented in FIGS. 5 to 7.

The floating collection unit 3 of this embodiment is composed of a collection housing 31 having a collection space 311 formed therein, a float 32 surrounding the collection housing 31, and a driving means 33. It is characterized in that it includes a second rotating shaft 34 that rotates, and wings 35 protruding from the second rotating shaft 34 and performing rotational interlocking at a portion where the water level is formed.

When bubbles are deposited on the inner water surface of the floating collector 3, the gas is not smoothly collected in the floating collector 3, so that the gas sensor unit 8 senses by-product gases and greenhouse gases by the collected gas. It may not be easy, but in this embodiment, when the gas covers the inner water surface of the floating collector 3, the water surface is exposed from the gas so that the gas can be collected smoothly.

The shape of the collecting housing 31 is not limited, but as shown in FIG. 5 and the like, a mountain-shaped rim is formed on the rim of the upper end, and the gas discharge line 36 is formed on this rim.

The wing 35 has a plurality of fixing bars 351 protruding from the second rotating shaft 34 and is mounted on the fixing bar 351 with the same inclination, respectively, so that foreign substances are filtered from the colliding gas g. And an example consisting of a filter plate 352 that pushes out the bubbles to expose the surface of the water is presented.

Preferably, as shown in the drawing, the filter plate 352 is such that an inclination gradient is formed in a state in which the lower end is submerged under the water surface so that the water surface is exposed by pushing the bubble B while contacting the rising gas g. .

As shown in FIG. 7, the gas (g) discharged to the water surface passes (g2) through the filter plate 352 or rises (g2) through the filter plate 352 so that foreign substances mixed in the gas (g) are removed. will be.

In this way, as the wings 35 filter foreign substances from the discharged gas, the foreign substances contained in the gas cause a load on the moisture absorbing part 4, the drying part 6, and the carbon dioxide absorbing part 7 at the rear, The problem of being deposited on the gas sensor unit 8 and causing an error in the sensing value is to be controlled.

As the filter plate 352, various known materials may be used, and a detailed description thereof will be omitted.

More preferably, a coating layer containing silicone oil is applied to the surface of the filter plate 352. By this configuration, in addition to pushing the bubbles on the water surface as mentioned above by the filter plate 352 to expose the water surface, the bubbles in contact with the filter plate 352 are defoamed.

The silicone oil is an inorganic antifoaming agent, and the silicone oil contains an organic group.

Silicon (organosilicone) and oxygen are chemically bonded, and it is artificially synthesized that does not exist in nature and has a side chain on an alkyl group.

The coating layer allows the surfactant to contain the silicone oil, and it is appropriate that the silicone oil is preferably blended in an amount of 10 to 20 parts by weight based on the total weight of the coating layer.

Through the above description, those skilled in the art will know that various changes and modifications are possible without departing from the technical idea of the present invention. Therefore, the technical scope of the present invention should not be limited to the contents described in the detailed description of the specification, but should be defined by the claims.

2: bioreactor
3: floating collection unit
4: moisture absorption part
5: pump
6: drying part
7: carbon dioxide absorption unit
8: gas sensor unit

Claims (11)

A sensor unit installed in each sewage and wastewater treatment plant to measure inflow water quality, inflow water quantity, operation factor, effluent water quality, effluent water quantity, by-product gas and greenhouse gas of the bioreactor in real time or at predetermined time intervals;
Artificial intelligence that collects data from the sensor unit, analyzes the data through a learning algorithm, generates a predictive model for each wastewater treatment plant, and predicts the effluent quality and greenhouse gas concentration of the selected wastewater treatment plant based on the prediction model. A prediction unit equipped with an intelligence program;
When the effluent water quality and greenhouse gas concentration predicted by the prediction unit deviate from the standard effluent water quality and standard GHG concentration, the treatment process control unit controls the process of the corresponding sewage and wastewater treatment plant by selecting one or more control variables from the inflow water quantity and operation factor. including;
Each sewage and wastewater treatment plant includes a bioreactor in which sewage and wastewater flows in and biological reactions occur,
In the bioreactor,
It is configured inside the bioreactor and has an open bottom, and a collection space is formed therein, and a floating port forming a certain distance from the bottom of the side wall to the top is provided, and the gas discharges the gas collected in the collection space to the outside at the top. A floating collection unit having a discharge line and a blocking edge formed so that the lower end is wound on the surface of the water; a moisture absorbing unit connected to the lower end of the gas discharge line and having a moisture absorbing layer formed thereon so that moisture is removed while the gas flowing into the inside passes; A by-product gas and greenhouse gas monitoring device including a gas sensor unit for measuring the amount of by-product gas and greenhouse gas mixing from the gas passing through the moisture absorbing unit is further configured,
The floating collection unit,
A collection housing having a collection space formed therein and having a mountain-shaped rim at an upper end and connected to the gas discharge line to the mountain-shaped rim, a floating sphere surrounding the collection housing, and a second rotating by a driving means in the collection space A rotating shaft, a plurality of fixed bars protruding from the second rotating shaft, and a lower end are mounted on the fixed bar with the same inclination gradient so that they are submerged in the water surface to make contact with the rising gas, filtering foreign substances from the colliding gas and pushing out bubbles An integrated management system for sewage and wastewater treatment plants capable of reducing greenhouse gas emissions using artificial intelligence, characterized in that it consists of a filter plate that exposes the surface of the water.
According to claim 1,
The inflow water quality, the outflow water quality, the by-product gas, and the greenhouse gas items are water quality analysis items such as temperature, BOD, TOC, COD, SS, TN, TP, NH ₄ -N, NO ₃ -N, CO ₂ , O ₂ , N ₂ O integrated management system for sewage and wastewater treatment plants capable of greenhouse gas reduction operation using artificial intelligence, characterized in that it includes at least one of N 2 O.
According to claim 1,
The treatment process control unit, when the effluent water quality and the greenhouse gas concentration predicted by the prediction unit deviate from the standard effluent water quality and the standard GHG concentration, virtually changes one or more of the inflow water quantity and operation factor, and applies the prediction model to make a prediction. By using artificial intelligence, which is characterized by controlling the process of the corresponding sewage and wastewater treatment plant by selecting one or more of the inflow water quantity and operation factor to ensure that the effluent water quality and greenhouse gas concentration are within the range of the standard effluent water quality and standard GHG concentration. An integrated management system for sewage and wastewater treatment plants that can reduce greenhouse gas emissions.
According to claim 1,
The prediction unit,
A data module for receiving and storing data from the sensor unit of each sewage and wastewater treatment plant;
a feature derivation module for extracting one or more features for learning from the data collected from the data module;
a learning module that performs deep learning based on the features extracted from the feature derivation module;
A model generation module that receives the result information learned from the learning module and generates a predictive model for each sewage and wastewater treatment plant based on it;
A prediction module for predicting effluent quality and greenhouse gas concentration of each sewage and wastewater treatment plant based on the prediction model of each wastewater and wastewater treatment plant generated by the model generation module;
An integrated management system for sewage and wastewater treatment plants capable of reducing greenhouse gas emissions using artificial intelligence, comprising:
delete According to claim 1,
The by-product gas includes carbon dioxide and oxygen, and the greenhouse gas includes nitrous oxide.
According to claim 6,
The gas sensor unit is composed of a first gas sensor unit and a second gas sensor unit, and some of the gas that has passed through the moisture absorbing unit is allowed to flow into the first gas sensor unit so that the mixed amount of carbon dioxide and oxygen in the gas is sensed, and the moisture A sewage and wastewater treatment plant integrated management system capable of greenhouse gas reduction operation using artificial intelligence, characterized in that some of the gas passing through the absorption unit flows into the second gas sensor unit so that the amount of nitrous oxide in the gas is sensed.
According to claim 7,
The gas flowing into the second gas sensor unit passes through the carbon dioxide absorbing unit formed with the carbon dioxide absorbing layer formed at the front end so that the gas from which carbon dioxide is removed is introduced into the second gas sensor unit. Greenhouse using artificial intelligence, characterized in that Integrated management system for sewage and wastewater treatment plants capable of gas reduction operation.
According to claim 8,
The carbon dioxide absorption unit,
A housing having an inlet line at the bottom and a discharge line connected to the second gas sensor at the top, a carbon dioxide adsorption layer filled with a carbon dioxide absorbent while partitioning the housing up and down, and a driving means rotationally interlock, It is possible to reduce greenhouse gas emissions by using artificial intelligence, characterized in that it includes a rotating shaft extending into the inside of the carbon dioxide adsorption layer, and a stirring bar protruding in plurality from the rotation shaft to the inside of the carbon dioxide absorption layer and having a hot wire embedded therein. Integrated management system for sewage and wastewater treatment plants.
delete According to claim 1,
A sewage and wastewater treatment plant integrated management system capable of greenhouse gas reduction operation using artificial intelligence, characterized in that a coating layer containing silicone oil is applied to the surface of the filter plate.

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