Physical defoaming alkali liquor circulation method

Abstract

The invention belongs to the technical field of cold-rolled sheet processing, and particularly relates to a physical defoaming alkali liquor circulation method which comprises the following steps: a foam capacitive monitoring array at the top of an alkali liquor tank generates a foam thickness gradient map in real time; real-time alkali liquor temperature, conductivity, circulating flow, strip steel running speed and historical foam thickness data are fused, a foam layer height prediction value is output, and when the prediction value exceeds a safety threshold value, a turbulence generator is automatically triggered to generate high-frequency pulse water flow; when the foam finally flows downwards to the top opening of the alkali liquor tank through the foam overflow pipe, the foam is crushed by high-frequency pulse water flow in the alkali liquor backflow pipeline and becomes alkali liquor to drop into the alkali liquor tank, the foam is physically crushed through fluid shear force and high-frequency vibration under the synergistic effect of the sectional type backflow pipeline and the capacitive foam monitoring array, the defoaming efficiency is high, and the defoaming effect is good. Dependent chemical defoaming agents are reduced, and the problems of strip steel surface residues and wastewater treatment are solved.

Description

Technical Field

[0001] The invention belongs to the technical field of cold-rolled plate processing, in particular to an alkali solution circulation method for physical defoaming. Background Art

[0002] Cold-rolled steel sheets require lye cleaning because they contain a lot of residual oil and iron on their surfaces. However, the recycling of this lye produces a lot of foam, causing significant environmental pollution. The more residual oil and iron in the raw material, the higher the concentration of the lye used, and the more foam is generated.

[0003] Existing systems mostly rely on chemical defoamers to suppress foam, but they have significant defects: excessive use of defoamers can easily form an oil film on the strip surface, affecting the quality of subsequent processing; and increase processing costs; there is a lack of coupled analysis of the spatial distribution of foam thickness, fluid shear force and defoaming efficiency, resulting in poor defoaming effect.

[0004] To this end, the present invention provides an alkali solution circulation method for physical defoaming. Summary of the Invention

[0005] In order to make up for the deficiencies of the prior art, at least one technical problem raised in the background technology is solved.

[0006] The technical solution adopted by the present invention to solve the technical problem is: the alkali solution circulation method for physical defoaming of the present invention comprises:

[0007] The circulation pump draws out alkali solution from the bottom of the alkali solution tank, transports it to the nozzle in the online cleaning tank, and sprays it onto the surface of the strip;

[0008] The liquid level in the online cleaning tank is monitored in real time by an ultrasonic level meter. The alkali liquid on the strip is squeezed by the squeeze roller assembly and drips into the online cleaning tank, and then returns to the alkali liquid tank through the alkali liquid return pipe.

[0009] A foam capacitive monitoring array on top of the lye tank generates a real-time map of the foam thickness gradient;

[0010] The system integrates real-time alkali solution temperature, conductivity, circulation flow, strip running speed and historical foam thickness data to output a predicted value of the foam layer height in the next 5 minutes. When the predicted value exceeds the safety threshold, the turbulence generator is automatically triggered to produce high-frequency pulse water flow.

[0011] When the foam finally flows down to the top of the alkali liquid tank through the foam overflow pipe, it is broken by the high-frequency pulse water flow in the alkali liquid return pipe and turns into alkali liquid that drips into the alkali liquid tank.

[0012] Preferably, the circulation pump is connected to the bottom of the alkali liquid tank, the outlet of the circulation pump is connected to the online cleaning tank through a pipeline, and a capacitive foam monitoring array is set on the top of the circulation pump for real-time detection of foam thickness and generation of a distribution map; the online cleaning tank and the alkali liquid tank are connected by an alkali liquid reflux pipeline;

[0013] An ultrasonic level gauge is integrated into the squeeze roller assembly to monitor the liquid level in the tank. The online cleaning tank is equipped with an adjustable-angle nozzle assembly to spray the strip surface. A foam overflow pipe is connected to the top of the lye tank, and a porous impact plate is installed at the outlet of the foam overflow pipe to break up the foam.

[0014] The circulation pump is connected to the intelligent control center, which dynamically adjusts the pump speed, nozzle angle and vibration frequency according to the foam data, and synchronizes the digital twin platform to realize fault prediction.

[0015] Preferably, the foam capacitive monitoring array is composed of 8-12 groups of annular capacitive sensors distributed on the top of the alkali solution tank, which detects the change in the dielectric constant of the foam layer in real time and converts the data into a foam thickness gradient distribution map through an edge computing module.

[0016] Preferably, the change in the dielectric constant of the foam layer is detected in real time, specifically:

[0017] Get the real-time capacitance value C t , get the capacitance value C0 in no-load state, through the formula Get the dielectric constant ε of the foam layer t , where d is the electrode spacing, A is the effective plate area, and k is the sawtooth correction coefficient.

[0018] Preferably, the data is converted into a foam thickness gradient distribution map through the edge computing module, specifically:

[0019] According to the capacitance value C under full load (pure alkali solution) m , calculate the dielectric constant ε under full load m Based on the foam-alkali solution two-phase dielectric model, the dielectric constant ε t Convert to foam thickness h: Where α is the empirical coefficient of foam void ratio, is the foam volume fraction;

[0020] The edge computing module outputs thickness matrix data in JSON format, which is rendered into a dynamic heat map and color mapping range through the WebGL engine to obtain the foam thickness gradient distribution map.

[0021] Preferably, the intelligent control center includes a foam growth prediction module, which establishes a foam generation model based on a long short-term memory neural network. The input parameters include real-time alkali solution temperature, electrical conductivity, circulation flow, strip running speed and historical foam thickness data. The module outputs a predicted value of the foam layer height in the next 5 minutes. When the predicted value exceeds the safety threshold, the turbulence generator is automatically triggered to generate high-frequency pulse water flow.

[0022] Preferably, the input parameters are obtained in the following manner:

[0023] The alkali solution temperature is collected by infrared sensors, the conductivity is measured by online electrodes, the alkali solution circulation flow is measured by electromagnetic flowmeters, the strip running speed is obtained, and the 30-minute historical foam thickness is obtained through capacitor array data.

[0024] Preferably, a foam generation model is established, specifically:

[0025] The real-time alkali solution temperature, conductivity, circulation flow, strip running speed and historical foam thickness data are normalized and input into the LSTM model in a time series with a sampling interval of 1 second. The LSTM model contains 2 LSTM layers and 1 fully connected layer, with an input dimension of 5 parameters and an output dimension of 1 parameter. The foam generation model is obtained by training.

[0026] Preferably, the alkali solution reflux pipeline includes a vertical turbulent section and a horizontal defoaming section. The inner wall of the vertical turbulent section is provided with spiral guide ribs, and a piezoelectric ceramic vibration plate is installed at the bottom of the horizontal defoaming section. The vibration frequency of the piezoelectric ceramic vibration plate is adjusted in real time according to the foam capacitive monitoring array data.

[0027] Preferably, the intelligent control center is connected to a precise defoamer injection system. When the foam growth prediction module predicts abnormal foam generation, the system calculates the defoamer injection rate according to [(current foam thickness) × (alkali solution circulation flow rate)]. 0.5 ] / 100 formula to calculate the amount of defoamer to be added and complete the injection within 3 seconds.

[0028] The beneficial effects of the present invention are as follows:

[0029] 1. The physical defoaming alkali solution circulation method described in the present invention cooperates with a segmented reflux pipeline and a capacitive foam monitoring array to physically break up foam through fluid shear force and high-frequency vibration. It has high defoaming efficiency, reduces dependence on chemical defoaming agents, and avoids residues on the strip surface and wastewater treatment problems.

[0030] 2. The alkali solution circulation method for physical defoaming described in the present invention is connected to a precise defoaming agent injection system through an intelligent control center. When the foam growth prediction module predicts abnormal foam generation, the amount of defoaming agent added is calculated more accurately to avoid excessive use of defoaming agent and save costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The present invention will be further described below with reference to the accompanying drawings.

[0032] Figure 1 This is a method flow chart of an alkali solution circulation method for physical defoaming of the present invention;

[0033] Figure 2 This is a schematic diagram of the connection structure between the online cleaning tank and the alkali liquid tank of the present invention;

[0034] In the figure: 1. Circulation pump; 2. Lye tank; 4. Online cleaning tank; 5. Squeeze roller assembly; 6. Lye return line; 7. Foam overflow pipe. DETAILED DESCRIPTION

[0035] In order to make the technical means, creative features, objectives and effects achieved by the present invention easier to understand, the present invention is further described below in conjunction with specific implementation methods.

[0036] Example 1

[0037] like Figures 1 to 2 As shown, a physical defoaming alkali solution circulation method according to an embodiment of the present invention comprises:

[0038] The circulation pump 1 draws out alkali solution from the bottom of the alkali solution tank 2, transports it to the nozzle 3 in the online cleaning tank 4, and sprays it onto the surface of the strip;

[0039] The liquid level in the online cleaning tank 4 is monitored in real time by an ultrasonic level meter. The alkali solution on the strip is squeezed by the squeeze roller assembly 5 and drips into the online cleaning tank 4, and then returns to the alkali solution tank 2 through the alkali solution return pipe 6;

[0040] The foam capacitive monitoring array on top of the lye tank 2 generates a foam thickness gradient map in real time;

[0041] The system integrates real-time alkali solution temperature, conductivity, circulation flow, strip running speed and historical foam thickness data to output a predicted value of the foam layer height in the next 5 minutes. When the predicted value exceeds the safety threshold, the turbulence generator is automatically triggered to produce high-frequency pulse water flow.

[0042] When the foam finally flows down to the top of the alkali liquid tank 2 through the foam overflow pipe 7, it is broken by the high-frequency pulse water flow in the alkali liquid return pipe 6 and turns into alkali liquid that drips into the alkali liquid tank 2.

[0043] Specifically, such as Figure 2 As shown, the circulation pump 1 is connected to the bottom of the alkali liquid tank 2, and the outlet of the circulation pump 1 is connected to the online cleaning tank 4 through a pipeline. A capacitive foam monitoring array is set on the top of the circulation pump 1 to detect the foam thickness in real time and generate a distribution map;

[0044] An ultrasonic level gauge is integrated into the squeeze roller assembly 5 to monitor the liquid level in the tank. An adjustable-angle nozzle 3 is built into the online cleaning tank 4 to spray the strip surface. A foam overflow pipe 7 is connected to the top of the alkali liquid tank 2, and a porous impact plate is installed at the outlet of the foam overflow pipe 7 to break up the foam.

[0045] The circulation pump 1 is connected to the intelligent control center, which dynamically adjusts the pump speed, nozzle angle and vibration frequency according to the foam data, and synchronizes the digital twin platform to realize fault prediction.

[0046] Specifically, the foam capacitive monitoring array consists of 8-12 groups of annular capacitive sensors distributed on the top of the alkali liquid tank. Each group of sensors contains a serrated electrode pair with an interval of 0.5-3mm, which detects the change in the dielectric constant of the foam layer in real time and converts the data into a foam thickness gradient distribution map through the edge computing module.

[0047] Specifically, the change in the dielectric constant of the foam layer is detected in real time, specifically:

[0048] Get the real-time capacitance value C t , get the capacitance value C0 in no-load state, through the formula Get the dielectric constant ε of the foam layer t , where d is the electrode spacing, A is the effective plate area, and k is the sawtooth correction factor. The sawtooth correction factor k is calibrated by experimental electrode geometry (typical value is 1.2-1.5).

[0049] Specifically, the edge computing module converts the data into a foam thickness gradient distribution map, specifically:

[0050] According to the capacitance value C under full load (pure alkali solution) m , calculate the dielectric constant ε under full load m Based on the foam-alkali solution two-phase dielectric model, the dielectric constant ε t Convert to foam thickness h: Where α is the empirical coefficient of foam void ratio, is the foam volume fraction (nonlinearly related to the dielectric constant);

[0051] The edge computing module outputs thickness matrix data in JSON format, which is rendered into a dynamic heat map and color mapping range through the WebGL engine to obtain the foam thickness gradient distribution map.

[0052] Specifically, the segmented return line 6 comprises a vertical turbulent flow section and a horizontal defoaming section. The vertical turbulent flow section is equipped with spiral guide ribs on its inner wall, whose height decreases along the flow direction according to the Fibonacci sequence. A piezoelectric ceramic vibration plate is mounted at the bottom of the horizontal defoaming section. The vibration frequency of the piezoelectric ceramic vibration plate is adjusted in real time based on data from a foam capacitive monitoring array.

[0053] Specifically, the intelligent control center is connected to a precise defoamer injection system. When the foam growth prediction module predicts abnormal foam generation, the system calculates the defoamer injection rate according to [(current foam thickness) × (alkali solution circulation flow rate)]. 0.5 ] / 100 formula to calculate the amount of defoamer to be added and complete the injection within 3 seconds.

[0054] The difference in dielectric constant between foam and alkali solution (the difference between the dielectric constant of foam and the dielectric constant of alkali solution) is used to detect the change in capacitance value through a ring capacitance sensor to invert the foam thickness.

[0055] Example 2

[0056] Comparative Example 1, wherein another embodiment of the present invention is:

[0057] The intelligent control center includes a foam growth prediction module, which establishes a foam generation model based on a long-short-term memory neural network. The module takes as input parameters real-time alkali solution temperature, conductivity, circulation flow, strip running speed and historical foam thickness data, and outputs a predicted value of the foam layer height in the next 5 minutes. When the predicted value exceeds the safety threshold, the turbulence generator is automatically triggered to generate high-frequency pulse water flow.

[0058] In a specific embodiment, first: data collection and model input include:

[0059] Real-time parameter acquisition:

[0060] The alkali solution temperature is collected by infrared sensors, the conductivity is measured by online electrodes, the circulation flow is measured by electromagnetic flowmeters, the strip running speed is obtained, and the 30-minute historical foam thickness is obtained through capacitance array data;

[0061] Data preprocessing:

[0062] After normalizing the above parameters, they are input into the LSTM model in time series (sampling interval is 1 second).

[0063] Second: LSTM model runs

[0064] Model structure:

[0065] The network consists of 2 LSTM layers (with 64 hidden layer nodes) and 1 fully connected layer. The input dimension is 5 (5 parameters, real-time alkali solution temperature, conductivity, circulation flow, strip running speed and historical foam thickness), and the output dimension is 1 (predicted foam height).

[0066] Prediction output:

[0067] The model predicts that the height of the foam layer will rise from the current 120mm to 185mm (the safety threshold is 180mm) in the next 5 minutes, triggering an early warning.

[0068] Finally: Turbulence Generator Control

[0069] High frequency pulse triggering:

[0070] The intelligent control center sends instructions to the turbulence generator in the vertical turbulence section: mode: adjust from steady state to pulse mode, increase the pulse frequency from 10Hz to 35Hz, and increase the peak flow rate of water by 40%. This enhances the turbulent shear force and breaks large bubbles into tiny bubbles.

[0071] Step 4: Effect verification and feedback optimization.

[0072] Actual monitoring: After 5 minutes, the measured foam height was 178 mm (lower than the predicted value of 185 mm), proving that the control was effective.

[0073] Establishment of foam generation model:

[0074] The system adds the current operating condition data to the training set and updates the LSTM weight parameters through online transfer learning to improve the accuracy of the next prediction.

[0075] The basic principles, main features, and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the foregoing embodiments. The foregoing embodiments and descriptions are merely illustrative of the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. A physical defoaming alkali solution circulation method, characterized in that: include: A circulation pump (1) draws alkali solution from the bottom of the alkali solution tank (2), transports it to the nozzle (3) in the online cleaning tank (4), and sprays it onto the surface of the steel strip; The liquid level in the online cleaning tank (4) is monitored in real time by an ultrasonic level meter. The alkali solution on the steel strip is squeezed by the squeeze roller assembly (5) and drips into the online cleaning tank (4). The alkali solution then flows back to the alkali solution tank (2) through the alkali solution return line (6). A foam capacitance monitoring array on the top of the alkali solution tank (2) generates a foam thickness gradient map in real time; The system integrates real-time alkali solution temperature, conductivity, circulation flow, strip running speed and historical foam thickness data to output a predicted value of the foam layer height in the next 5 minutes. When the predicted value exceeds the safety threshold, the turbulence generator is automatically triggered to produce high-frequency pulse water flow. When the foam finally flows downward to the top of the alkali liquid tank (2) through the foam overflow pipe (7), it is broken by the high-frequency pulse water flow in the alkali liquid return pipe (6) and becomes alkali liquid that drips into the alkali liquid tank (2).

2. A lye circulation method for physical defoaming according to claim 1, characterized in that, The circulation pump (1) is connected to the bottom of the alkali liquid tank (2), and the outlet of the circulation pump (1) is connected to the online cleaning tank (4) through a pipeline. A capacitive foam monitoring array is set on the top of the circulation pump (1) for real-time detection of foam thickness and generation of a distribution map; the online cleaning tank (4) and the alkali liquid tank (2) are connected via an alkali liquid return pipeline (6); An ultrasonic level meter is integrated on the squeeze roller assembly (5) for monitoring the liquid level in the tank; an adjustable-angle nozzle (3) is built into the online cleaning tank (4) for spraying the surface of the strip steel; a foam overflow pipe (7) is connected to the top of the alkali liquid tank (2), and a porous impact plate is provided at the outlet of the foam overflow pipe (7) for breaking the foam; The circulation pump (1) is connected to an intelligent control center, which dynamically adjusts the pump speed, nozzle angle, and vibration frequency according to foam data, and synchronizes the digital twin platform to achieve fault prediction.

3. A lye circulation method for physical defoaming according to claim 2, characterized in that, The foam capacitive monitoring array consists of 8-12 groups of annular capacitive sensors distributed on the top of the alkali liquid tank, which detects the change in the dielectric constant of the foam layer in real time and converts the data into a foam thickness gradient distribution map through the edge computing module.

4. A lye circulation method for physical defoaming according to claim 3, characterized in that, Real-time detection of the change in the dielectric constant of the foam layer, specifically: Get the real-time capacitance value C t , get the capacitance value C0 in no-load state, through the formula Get the dielectric constant ε of the foam layer t , where d is the electrode spacing, A is the effective plate area, and k is the sawtooth correction coefficient.

5. A lye circulation method for physical defoaming according to claim 4, characterized in that, The edge computing module converts the data into a foam thickness gradient distribution map, specifically: According to the capacitance value C under full load (pure alkali solution) m , calculate the dielectric constant ε under full load m Based on the foam-alkali solution two-phase dielectric model, the dielectric constant ε t Convert to foam thickness h: Where α is the empirical coefficient of foam void ratio, is the foam volume fraction; The edge computing module outputs thickness matrix data in JSON format, which is rendered into a dynamic heat map and color mapping range through the WebGL engine to obtain the foam thickness gradient distribution map.

6. A lye circulation method for physical defoaming according to claim 2, characterized in that, The intelligent control center includes a foam growth prediction module, which establishes a foam generation model based on a long-short-term memory neural network. The module takes as input parameters real-time alkali solution temperature, electrical conductivity, circulation flow, strip running speed, and historical foam thickness data. The module outputs a predicted value of the foam layer height in the next five minutes. When the predicted value exceeds a safety threshold, the module automatically triggers a turbulence generator to generate high-frequency pulsed water flow.

7. A lye circulation method for physical defoaming according to claim 6, characterized in that: The input parameters are obtained in the following ways: The alkali solution temperature is collected by infrared sensors, the conductivity is measured by online electrodes, the alkali solution circulation flow is measured by electromagnetic flowmeters, the strip running speed is obtained, and the 30-minute historical foam thickness is obtained through capacitor array data.

8. A lye circulation method for physical defoaming according to claim 6, characterized in that: Establish a foam generation model, specifically: The real-time alkali solution temperature, conductivity, circulation flow, strip running speed and historical foam thickness data are normalized and input into the LSTM model in a time series with a sampling interval of 1 second. The LSTM model contains 2 LSTM layers and 1 fully connected layer, with an input dimension of 5 parameters and an output dimension of 1 parameter. The foam generation model is obtained by training.

9. A lye circulation method for physical defoaming according to claim 1, characterized in that: The alkali solution return pipeline (6) comprises a vertical turbulent section and a horizontal defoaming section, wherein the inner wall of the vertical turbulent section is provided with spiral guide ribs, and the bottom of the horizontal defoaming section is provided with a piezoelectric ceramic vibration plate, and the vibration frequency of the piezoelectric ceramic vibration plate is adjusted in real time according to the foam capacitive monitoring array data.

10. The alkali solution circulation method for physical defoaming according to claim 2, characterized in that: The intelligent control center is connected to the defoamer precision injection system. When the foam growth prediction module predicts abnormal foam generation, the defoamer is injected according to [(current foam thickness) × (alkali solution circulation flow)]. 0.5 ] / 100 formula to calculate the amount of defoamer to be added and complete the injection within 3 seconds.

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