Ozone utilization rate on-line monitoring regulation and control system

Abstract

The invention provides an ozone utilization rate on-line monitoring regulation and control system. The system comprises an ozone contact tank regulation and control module, an ozone generator, multi-stage ozone column gas inlet pipes, gas flowmeters mounted on the multi-stage ozone column gas inlet pipes, ozone concentration detectors mounted on a gas inlet header pipe and a tail gas discharge pipe respectively, and an in-water ozone concentration detector mounted on a water outlet pipe, ozone generated by the ozone generator respectively enters the multi-stage ozone column gas inlet pipes through a gas inlet main pipe; gas inlet pipes of the multiple stages of ozone columns are connected with a tail gas discharge pipe; the ozone contact tank regulation and control module is connected with the gas flowmeter, the ozone concentration detector and the in-water ozone concentration detector, and calculates the ozone utilization rate of the ozone contact tank according to the obtained ozone inlet flow, ozone inlet concentration and ozone tail gas average concentration of each stage of contact column, and the effluent residual ozone concentration and water inlet flow of the ozone contact tank; the precise regulation and control of the ozone oxidation process of the water supply plant are realized. Low-energy-consumption stable operation of a water plant is guaranteed, and effluent stably reaches the standard.

Description

Technical Field

[0001] The present invention belongs to the technical field of ozone utilization rate monitoring, and particularly relates to an on-line monitoring and regulation system for ozone utilization rate. Background Art

[0002] Ozone-activated carbon is a commonly used advanced treatment process for drinking water. The ozone unit generally adopts the form of an ozone contact tank. By adding ozone to water and utilizing the oxidation of ozone, macromolecular organic matter can be oxidized into small-molecular organic matter, improving the biodegradability of water. Activated carbon adsorbs or biodegrades the small-molecular substances after ozonation. The synergistic effect of ozone and activated carbon significantly improves the removal rate of organic matter.

[0003] The ozone utilization rate is a key index affecting the ozone oxidation effect. The ozone utilization rate is related to factors such as water quality and ozone dosage. However, at present, the ozone dosage in most water treatment plants is only added based on experience. Excessive or too low ozone dosage will affect the ozone utilization rate. Especially when the water quality changes, the ozone dosing system cannot be adjusted in time, and the ozone utilization rate is only 30%-50%. Low ozone utilization rate can lead to fluctuations in the effluent quality of the water treatment plant, an increase in the concentration of organic matter in the effluent, an increase in energy consumption and operating costs, and an increase in the difficulty of process regulation in the water treatment plant. The ozone oxidation process in the water treatment plant only simply detects the inlet ozone concentration and the residual ozone concentration in the water, lacking on-line monitoring of the ozone utilization rate, and the ozone dosing fails to be dynamically adjusted according to the water quality changes. Summary of the Invention

[0004] In order to solve the above technical problems, the present invention proposes an on-line monitoring and regulation system for ozone utilization rate to ensure the stable operation of the water treatment plant with low energy consumption and the stable compliance of the effluent.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] An on-line monitoring and regulation system for ozone utilization rate, comprising: an ozone contact tank regulation module, an ozone generator 3, a multi-stage ozone column inlet pipe, a gas flowmeter installed on each stage of the ozone column inlet pipe, an ozone concentration detector respectively installed on the inlet main pipe 4 and the tail gas discharge pipe 8, and a dissolved ozone concentration detector 11 installed on the outlet pipe 2;

[0007] The ozone generated by the ozone generator 3 enters the multi-stage ozone column inlet pipe through the inlet main pipe 4 respectively; all the multi-stage ozone column inlet pipes are connected to the tail gas discharge pipe 8;

[0008] The ozone contact tank regulation module is communicatively connected to the gas flowmeter, the ozone concentration detector and the dissolved ozone concentration detector 11, and calculates the ozone utilization rate of the ozone contact tank according to the obtained ozone inlet flow rate, ozone inlet concentration, average ozone tail gas concentration, dissolved ozone concentration in the effluent of the ozone contact tank, and the inlet water flow rate.

[0009] Further, a first water quality detector is installed on the water inlet pipe 1 of the device to detect the water quality indicators of the water in the water inlet pipe; a second water quality detector is installed on the water outlet pipe 2 to detect the water quality indicators of the water in the water outlet pipe.

[0010] The water inlet pipe 1 is connected to the water inlet of the multi-stage ozone column inlet pipe; the water outlet of the multi-stage ozone column inlet pipe is connected to the water outlet pipe 2.

[0011] Further, the water quality indicators include the pH, turbidity, temperature and UV of the water. 254 .

[0012] Further, the ozone column inlet pipe is three-stage, including a first-stage ozone column inlet pipe 5, a second-stage ozone column inlet pipe 6 and a third-stage ozone inlet pipe 7.

[0013] Further, a first gas flowmeter is arranged on the inlet pipe of the first-stage ozone column inlet pipe 5; a second gas flowmeter is arranged on the inlet pipe of the second-stage ozone column inlet pipe 6; a third gas flowmeter is arranged on the inlet pipe of the third-stage ozone column inlet pipe 7.

[0014] Further, the process of calculating the ozone utilization rate of the ozone contact tank includes:

[0015]

[0016] Among them, Q is the influent flow rate; ρ is the residual ozone concentration in the effluent of the ozone contact tank; c0 is the ozone inlet concentration; c e is the average ozone tail gas concentration; q1 is the ozone inlet flow rate of the first-stage contact column; q2 is the ozone inlet flow rate of the second-stage contact column; q3 is the ozone inlet flow rate of the third-stage contact column.

[0017] Further, the ozone contact tank regulation module is also used to determine the ozone regulation strategy according to the relationship between the ozone utilization rate of the ozone contact tank and the preset ozone utilization rate, and adjust the ozone dosage based on the predicted water quality change situation.

[0018] Further, the ozone contact tank regulation module uses a machine learning algorithm to capture the time series characteristics and non-linear and state relationships in the operation process of the ozone contact tank; the machine learning algorithm uses a bidirectional long short-term memory network.

[0019] Further, the bidirectional long short-term memory network includes an input layer, three LSTM cell layers and an output layer; and each LSTM cell layer includes a forward LSTM layer and a reverse LSTM layer.

[0020] The input layer is used to input the sample time series samples composed of ozone regulation data; the ozone regulation data set includes the ozone inlet flow rate, ozone inlet concentration, average ozone tail gas concentration, residual ozone concentration in the effluent of the ozone contact tank, and influent flow rate at each stage of the contact column.

[0021] The forward LSTM layer is used to process the forward sample time series samples to generate a forward hidden state sequence; the reverse LSTM layer processes the reverse sample time series samples to generate a reverse hidden state sequence.

[0022] The output layer is used to output the connection of the forward hidden state sequence and the reverse hidden state sequence, and output the ozone regulation strategy.

[0023] Further, the ozone regulation strategy also needs to add constraint conditions, where the constraint conditions include: the ozone utilization rate is not less than the preset utilization rate threshold, the ozone concentration in the effluent is within the preset range, and the UV 254 removal rate is not less than the preset threshold.

[0024] The effects provided in the invention content are only the effects of the embodiments, rather than all the effects of the invention. One of the above technical solutions has the following advantages or beneficial effects:

[0025] The present invention proposes an on-line monitoring and regulation system for ozone utilization rate. The device includes: an ozone contact tank regulation module, an ozone generator, a multi-stage ozone column inlet pipe, a gas flow meter installed on each stage of the ozone column inlet pipe, an ozone concentration detector installed on the intake main pipe and the tail gas discharge pipe respectively, and a dissolved ozone concentration detector installed on the outlet pipe; the ozone generated by the ozone generator enters the multi-stage ozone column inlet pipe through the intake main pipe respectively; the multi-stage ozone column inlet pipes are all connected to the tail gas discharge pipe; the ozone contact tank regulation module is communicatively connected with the gas flow meter, the ozone concentration detector and the dissolved ozone concentration detector, and calculates the ozone utilization rate of the ozone contact tank according to the obtained ozone inlet flow rate, ozone inlet concentration, average ozone tail gas concentration, residual ozone concentration in the effluent of the ozone contact tank, and influent flow rate at each stage of the contact column. The present invention monitors the change of ozone utilization rate in real time, predicts the water quality change in time according to the ozone utilization rate model established based on machine learning, and proposes an ozone dosing regulation strategy, realizing the precise regulation of the ozone oxidation process in the waterworks, effectively solving the problem of low ozone utilization rate in the waterworks, and ensuring the stable operation of the waterworks with low energy consumption and the stable compliance of the effluent. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a schematic diagram of the hardware connection of an on-line monitoring and regulation system for ozone utilization rate according to Embodiment 1 of the present invention;

[0027] Figure 2 It is a schematic diagram of the bidirectional long short-term memory network structure proposed in Embodiment 1 of the present invention;

[0028] Legend: 1 - water inlet pipe; 2 - water outlet pipe; 3 - ozone generator; 4 - main air inlet pipe; 5 - first-stage ozone column air inlet pipe; 6 - second-stage ozone column air inlet pipe; 7 - third-stage ozone column air inlet pipe; 8 - tail gas discharge pipe; 9-1 - first ozone concentration detector; 9-2 - second ozone concentration detector; 10-1 - first water quality detector; 10-2 - second water quality detector; 11 - ozone concentration detector; 12-1 - first gas flowmeter; 12-2 - second gas flowmeter; 12-3 - third gas flowmeter. Detailed implementation manners

[0029] To clearly illustrate the technical features of this solution, the present invention will be elaborated in detail below through specific implementation manners and in conjunction with its attached drawings. The following disclosure provides many different embodiments or examples for implementing different structures of the present invention. To simplify the disclosure of the present invention, the components and settings of specific examples are described below. In addition, the present invention may repeat reference numerals and / or letters in different examples. This repetition is for the purpose of simplification and clarity, and does not itself indicate the relationship between the various embodiments and / or settings discussed. It should be noted that the components illustrated in the drawings are not necessarily drawn to scale. The present invention omits the description of well-known components, processing technologies and processes to avoid unnecessarily limiting the present invention.

[0030] Embodiment 1

[0031] Embodiment 1 of the present invention proposes an on-line monitoring and regulation system for ozone utilization rate, which is used to solve the technical problem in the prior art that the ozone utilization rate cannot be accurately monitored, resulting in fluctuations in the water quality of the water plant's effluent. Figure 1 FIG. is a schematic diagram of the hardware connection of an on-line monitoring and regulation system for ozone utilization rate according to Embodiment 1 of the present invention; the device includes: an ozone contact tank regulation module, an ozone generator 3, a multi-stage ozone column air inlet pipe, gas flowmeters installed on each stage of the ozone column air inlet pipe, ozone concentration detectors respectively installed on the main air inlet pipe 4 and the tail gas discharge pipe 8, and an ozone concentration detector 11 in the water installed on the water outlet pipe 2;

[0032] The ozone generated by the ozone generator 3 enters the multi-stage ozone column air inlet pipe through the main air inlet pipe 4 respectively; the multi-stage ozone column air inlet pipes are all connected to the tail gas discharge pipe 8;

[0033] The ozone contact tank regulation module is communicatively connected to the gas flowmeter, the ozone concentration detector and the ozone concentration detector 11 in the water, and calculates the ozone utilization rate of the ozone contact tank according to the obtained ozone inlet air flow rate, ozone inlet concentration, average ozone tail gas concentration, residual ozone concentration in the effluent of the ozone contact tank, and the inlet water flow rate.

[0034] A first water quality detector 10-1 is installed on the water inlet pipe 1 of the device to detect the water quality indexes of the water in the water inlet pipe; a second water quality detector 10-2 is installed on the water outlet pipe 2 to detect the water quality indexes of the water in the water outlet pipe; the water quality indexes include the pH, turbidity, temperature and UV of the water 254 .

[0035] The water inlet pipe 1 is connected to the water inlet of the multi-stage ozone column inlet pipe; the water outlet of the multi-stage ozone column inlet pipe is connected to the water outlet pipe 2.

[0036] The ozone contact tank generally consists of three ozone columns, including a first-stage ozone column inlet pipe 5, a second-stage ozone column inlet pipe 6 and a third-stage ozone inlet pipe 7.

[0037] A first gas flowmeter 12-1 is arranged on the inlet pipe of the first-stage ozone column inlet pipe 5; a second gas flowmeter 12-2 is arranged on the inlet pipe of the second-stage ozone column inlet pipe 6; a third gas flowmeter 12-3 is arranged on the inlet pipe of the third-stage ozone column inlet pipe 7.

[0038] In this application, the data obtained by on-line monitoring is analyzed to obtain the ozone utilization rate of the ozone contact tank. The process of calculating the ozone utilization rate of the ozone contact tank includes:

[0039]

[0040] where Q is the influent flow rate, m 3 / h; ρ is the residual ozone concentration in the effluent of the ozone contact tank, mg / L; c0 is the ozone inlet concentration, mg / L; c e is the average ozone tail gas concentration, mg / L; q1 is the ozone inlet flow rate of the first contact column, L / h; q2 is the ozone inlet flow rate of the second contact column, L / h; q3 is the ozone inlet flow rate of the third contact column, L / h.

[0041] q1 is obtained through the first gas flowmeter 12-1; q2 is obtained through the second gas flowmeter 12-2; q3 is obtained through the third gas flowmeter 12-3.

[0042] ρ is obtained through the ozone concentration detector 11; c e is obtained through the second ozone concentration detector 9-2; the ozone inlet concentration is obtained through the second ozone concentration detector 9-1.

[0043] The ozone contact tank control module evaluates the operating state of the ozone contact tank through the obtained ozone utilization rate, and can set the ozone utilization rate threshold according to the current situation of the water plant. When the ozone utilization rate is lower than the threshold, the ozone dosing system needs to be adjusted. The ozone control system can predict the water quality change according to the model and adjust the ozone dosing amount according to the water quality change to ensure that the ozone absorption rate operates within the set range.

[0044] The ozone utilization rate is correlated with the influent water quality of the ozone contact tank (water temperature, turbidity, pH, UV254), influent flow rate Q, ozone inlet concentration c0, and ozone inlet flow rates q1, q2, q3 of each ozone column, etc. The ozone contact tank regulation system uses a Bidirectional Long Short-Term Memory Network (BiLSTM) as the core machine learning algorithm to more accurately capture the temporal characteristics and non-linear and state relationships during the operation of the ozone contact tank. BiLSTM simultaneously learns the data dependency relationships at historical and future moments through a bidirectional structure, significantly improving the prediction accuracy of the ozone utilization rate and the regulation response speed.

[0045] The bidirectional long short-term memory network includes an input layer, three LSTM cell layers, and an output layer; and each LSTM cell layer includes a forward LSTM layer and a backward LSTM layer;

[0046] The input layer is used to input the sample time series samples composed of ozone regulation data; the ozone regulation data set includes the ozone inlet flow rates of each contact column, ozone inlet concentration, average ozone tail gas concentration, residual ozone concentration in the effluent of the ozone contact tank, and influent flow rate;

[0047] The forward LSTM layer is used to process the forward sample time series samples to generate a forward hidden state sequence; the backward LSTM layer processes the backward sample time series samples to generate a backward hidden state sequence;

[0048] The output layer is used to output the connection of the forward hidden state sequence and the backward hidden state sequence, and output the ozone regulation strategy.

[0049] Figure 2 It is a schematic diagram of the bidirectional long short-term memory network structure proposed in Embodiment 1 of the present invention; a double-layer BiLSTM is used, with 64 neurons in each layer, followed by a fully connected layer and a Dropout layer (dropout rate 0.2), and the output layer uses a Sigmoid activation function to ensure that the predicted value is within the range of 0 to 1. The loss function is selected as the mean square error (MSE), and the optimizer uses the Adam algorithm, and the learning rate decays dynamically. Specifically, the BiLSTM neural network structure of the prediction model includes two independent LSTM layers, one for processing the forward sequence and the other for processing the backward sequence. Its output is the combination of the outputs of these two LSTM layers. Specifically, for the input sequence X=(x1,x2,…,x T )X=(x1,x2,…,x T ), the forward LSTM layer generates a forward hidden state sequence (h1→,h2→,…,h T →)(h1,h2,…h T ), and the backward LSTM layer generates a backward hidden state sequence (h1←,h2←,…,h T ←)(h1,h2,…,h T)。The final output of the BiLSTM is the concatenation of these two hidden state sequences ($h_{t\rightarrow}, h_{t\leftarrow}$)(h t ,h t ). The LSTM neural network mentioned above includes an input layer, three LSTM cell layers, and an output layer. Each LSTM cell layer contains a forget gate, an input gate, and an output gate.

[0050] The process of training the bidirectional long short-term memory network is as follows: Obtain the data related to the training of the ozone regulation model, perform preprocessing, divide the training set and the test set according to 8:2, and generate time series samples using a sliding window. The scope of protection of this application is not limited to the division ratio listed in Embodiment 1.

[0051] The data related to the training mentioned above includes the influent flow rate Q, the UV of the influent and effluent 254 , turbidity, pH, and water temperature, the ozone inlet concentration c0, the ozone inlet flow rates q1, q2, q3 of each contact column;

[0052] Construct an online learning mechanism for the BiLSTM model. After the BiLSTM model is deployed, collect the data related to the sensors in the ozone contact tank in real time. The data collection frequency is set to be collected once every 0.5 hours, and the model parameters are dynamically adjusted to adapt to sudden changes in water quality or seasonal fluctuations. This setting of the data collection frequency conforms to the flow rate in the ozone contact tank and the change rate of the internal chemical content, which can improve the prediction accuracy and will not generate redundant and useless data due to overly frequent collection.

[0053] After the BiLSTM model is trained, based on the feedforward data such as the influent flow rate Q, the UV of the influent and effluent 254 , turbidity, pH, and water temperature, etc., propose an ozone system adjustment strategy, and adjust the ozone system operation parameters such as the ozone inlet concentration c0, the ozone inlet flow rates q1, q2, q3 of each contact column on the basis of predicting water quality changes, so as to realize the efficient and intelligent operation of the ozone system.

[0054] The ozone system adjustment strategy also adds constraint conditions: ozone utilization rate ≥ 85%, effluent ozone concentration 0.01 - 0.03 mg / L, UV 254 removal rate ≥ 30%.

[0055] Through the real-time online monitoring system of ozone utilization rate and the dynamic adjustment feedback of the BiLSTM model, improve the ozone utilization rate in the ozone contact tank and further improve the removal effect of the ozone activated carbon process on organic matter.

[0056] Embodiment 1 of the present invention provides an on-line monitoring and regulation system for ozone utilization rate, which can monitor the change of ozone utilization rate in real time. According to the ozone utilization rate model established based on machine learning, it can timely predict the water quality change and put forward the ozone dosing regulation strategy, realizing the precise regulation of the ozone oxidation process in the waterworks, effectively solving the problem of low ozone utilization rate in the waterworks, and ensuring the stable operation of the waterworks with low energy consumption and the stable compliance of the effluent.

[0057] It should be noted that in this text, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that the elements inherent in a process, method, article or device including a series of elements are included. Without further limitation, the element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, article or device including the said element. In addition, the parts of the above technical solutions provided by the embodiments of the present application that are consistent with the corresponding technical solutions in the prior art in terms of implementation principles are not described in detail to avoid excessive elaboration.

[0058] Although the specific implementation manners of the present invention are described above in conjunction with the accompanying drawings, it is not a limitation on the protection scope of the present invention. For those skilled in the art, other different forms of modification or variation can be made based on the above description. It is not necessary and impossible to list all the implementation manners here. Various modifications or variations that can be made by those skilled in the art without creative labor on the basis of the technical solutions of the present invention are still within the protection scope of the present invention.

Claims

1. An on-line monitoring and regulation system for ozone utilization rate, characterized in that Including: An ozone contact tank regulation module, an ozone generator (3), a multi-stage ozone column inlet pipe, gas flow meters installed on each stage of the ozone column inlet pipe, ozone concentration detectors installed on the intake main pipe (4) and the tail gas discharge pipe (8) respectively, and a dissolved ozone concentration detector (11) installed on the outlet pipe (2); The ozone generated by the ozone generator (3) enters the multi-stage ozone column inlet pipes through the intake main pipe (4) respectively; the multi-stage ozone column inlet pipes are all connected to the tail gas discharge pipe (8); The ozone contact tank regulation module is communicatively connected to the gas flow meters, the ozone concentration detectors and the dissolved ozone concentration detector (11), and calculates the ozone utilization rate of the ozone contact tank according to the obtained ozone intake flow rate of each contact column, the ozone intake concentration, the average ozone tail gas concentration, the residual ozone concentration in the outlet water of the ozone contact tank, and the influent flow rate.

2. The on-line monitoring and control system for ozone utilization rate according to claim 1, characterized in that A first water quality detector is installed on the influent pipe (1) of the device to detect the water quality indexes of the water in the influent pipe; a second water quality detector is installed on the outlet pipe (2) to detect the water quality indexes of the water in the outlet pipe; The influent pipe (1) is connected to the water inlet of the multi-stage ozone column inlet pipe; the water outlet of the multi-stage ozone column inlet pipe is connected to the outlet pipe (2).

3. The on-line monitoring and regulation system for ozone utilization rate according to claim 1, characterized in that, The water quality indicators include the pH, turbidity, temperature and UV of water 254 .

4. An on-line monitoring and control system for ozone utilization rate according to claim 1, characterized in that, The ozone column inlet pipe has three stages, including a first-stage ozone column inlet pipe (5), a second-stage ozone column inlet pipe (6) and a third-stage ozone inlet pipe (7).

5. An on-line monitoring and regulation system for ozone utilization rate according to claim 4, characterized in that, A first gas flow meter is arranged on the inlet pipe of the first-stage ozone column inlet pipe (5); a second gas flow meter is arranged on the inlet pipe of the second-stage ozone column inlet pipe (6); a third gas flow meter is arranged on the inlet pipe of the third-stage ozone column inlet pipe (7).

6. The on-line monitoring and control system for ozone utilization rate according to claim 5, characterized in that, The process of calculating the ozone utilization rate of the ozone contact tank includes: Wherein, Q is the influent flow rate; ρ is the residual ozone concentration in the effluent of the ozone contact tank; c0 is the ozone inlet concentration; c e is the average ozone concentration in the tail gas; q1 is the ozone inlet flow rate of the first contact column; q2 is the ozone inlet flow rate of the second contact column; q3 is the ozone inlet flow rate of the third contact column.

7. An on-line monitoring and regulation system for ozone utilization rate according to claim 1, characterized in that, The ozone contact tank regulation module is further configured to determine an ozone regulation strategy according to the relationship between the ozone utilization rate of the ozone contact tank and a preset ozone utilization rate, and adjust the ozone dosage based on the predicted water quality change situation.

8. An on-line monitoring and control system for ozone utilization rate according to claim 7, characterized in that, The ozone contact tank regulation module uses a machine learning algorithm to capture the time series characteristics and non-linear and state relationships in the operation process of the ozone contact tank; the machine learning algorithm uses a bidirectional long short-term memory network.

9. An on-line monitoring and control system for ozone utilization rate according to claim 8, characterized in that, The bidirectional long short-term memory network includes an input layer, three LSTM cell layers and an output layer; and each LSTM cell layer includes a forward LSTM layer and a backward LSTM layer; The input layer is used to input a sample time series sample composed of ozone regulation data; the ozone regulation data set includes the ozone intake flow rate of each contact column, the ozone intake concentration, the average ozone tail gas concentration, the residual ozone concentration in the outlet water of the ozone contact tank and the influent flow rate; The forward LSTM layer is used to process the forward sample time series sample to generate a forward hidden state sequence; the backward LSTM layer processes the backward sample time series sample to generate a backward hidden state sequence; The output layer is used to output the connection of the forward hidden state sequence and the backward hidden state sequence, and output the ozone regulation strategy.

10. An on-line monitoring and control system for ozone utilization rate according to claim 9, characterized in that, The ozone regulation strategy also needs to add constraint conditions, where the constraint conditions include: the ozone utilization rate is not less than the preset utilization rate threshold, the ozone concentration in the effluent is within the preset range, and the UV 254 removal rate is not less than the preset threshold.

Images