Method and system for predicting ion concentration in pickling solution

Abstract

The invention relates to a method and a system for predicting ion concentration in a pickling solution, and belongs to the technical field of pickling solution ion prediction. The method comprises the following steps: acquiring pickling solution data, and obtaining normal-temperature pickling solution density and normal-temperature pickling solution conductivity through temperature correction; strip steel unit information is obtained, and according to the strip steel unit information and the normal-temperature pickling solution density, the pickling solution correction density is obtained through density correction calculation; calculating the concentration of H < + > ions and the concentration of Fe < 2 + > ions in the pickling solution through a pickling solution ion concentration prediction model according to the modified density of the pickling solution and the conductivity of the normal-temperature pickling solution; according to the information of the strip steel unit, a change curve of the acid concentration and the iron concentration in each tank is calculated through a pickling solution ion concentration change model, so that the problem of insufficient prediction precision of the pickling solution ion concentration caused by silicon sludge deposition is solved, and the performance of the pickling solution is accurately detected in real time; and the pickling solution process control in pickling production is optimized.

Description

Technical Field

[0001] The invention belongs to the technical field of pickling solution ion prediction, and in particular relates to a method and system for predicting ion concentration in a pickling solution. Background Art

[0002] Pickling is a key step in the production process of cold-rolled thin plates, which can remove the oxide scale on the surface of hot-rolled plates. The pickling process mainly interacts chemically and electrochemically, which is specifically manifested in the dissolution of the oxide scale by acid, the descaling effect of hydrogen, and the reduction effect of hydrogen atoms. The pickling speed and efficiency are affected by many factors, such as the condition of the iron oxide scale on the surface of the hot-rolled plate, the descaling process parameters, and the pickling process parameters. Once the production process parameters are not well controlled, over-pickling and under-pickling will occur, which will seriously affect the surface quality of the pickled plate and bring huge economic losses to the company.

[0003] During the pickling process, H + ions will continue to decrease, and the Fe 2+ The ion concentration will continue to rise, and the pickling capacity of the pickling solution will also decrease. In order to ensure the pickling capacity of the pickling solution and meet the needs of continuous pickling production, the pickling process requires continuous addition of new acid and continuous discharge of old acid. Therefore, real-time and accurate grasp of the performance of the pickling solution is crucial to pickling production.

[0004] At present, most continuous pickling production lines rely mainly on offline detection and post-adjustment strategies for the performance management of the pickling solution in the pickling section. The detection method of the iron ion concentration in the pickling solution is usually completed through regular manual sampling and analysis. Once the acid concentration is detected to drop to a certain level, new acid will be added to the circulation tank and the old acid will be discharged to increase the acid concentration. This operation mode has a slow response, resulting in unstable process control of the pickling solution, which is difficult to meet the production requirements of high-quality pickled plates. Even if some production lines adopt online detection solutions, these solutions are still intermittent measurement methods, and the response speed is still slow, and it is impossible to achieve accurate control of the ion concentration in the pickling solution. In addition, the current online detection system cannot eliminate the influence of silicon mud in the pickling solution during long-term online detection. The silicon mud will be deposited on the detection instrument, which will affect the measurement accuracy of the equipment, especially the density meter, resulting in deviations in the detection results. Summary of the invention

[0005] In order to solve the above problems existing in the prior art, the present invention proposes a method and system for predicting ion concentration in pickling liquid.

[0006] The purpose of the present invention can be achieved through the following technical solutions: A method for predicting ion concentration in a pickling solution, comprising: Acquiring pickling liquid data, wherein the pickling liquid data includes pickling liquid temperature, pickling liquid density, and pickling liquid conductivity; Obtaining the density and electrical conductivity of the room-temperature pickling solution according to the pickling solution data through temperature correction; Acquire strip steel unit information, wherein the strip steel unit information includes strip steel type, strip steel thickness, strip steel width, strip steel length, strip steel silicon content, strip steel coiling temperature, number of pickling tanks, pickling tank length, pickling tank width, pickling tank liquid level, strip steel pickling speed, acid feed amount, and regenerated acid concentration; According to the strip steel unit information and the density of the normal temperature pickling solution, a density correction calculation is performed to obtain a corrected density of the pickling solution; The H in the pickling solution is calculated based on the corrected density of the pickling solution and the conductivity of the pickling solution at room temperature using the pickling solution ion concentration prediction model. + Ion concentration and Fe in pickling solution 2+ Ion concentration; According to the strip mill information, the change curves of the acid concentration and the iron concentration in each tank are calculated by using the pickling liquid ion concentration change model.

[0007] Preferably, the mathematical expression of the temperature correction is: , , Among them, i is the pickling tank, k T is the conductivity of the pickling solution, ρ T is the pickling solution density, k 25 is the conductivity of the pickling solution at room temperature, ρ 25 is the density of the pickling solution at room temperature, T is the temperature of the pickling solution, and α and β are correction coefficients.

[0008] Preferably, the mathematical expression of the density correction is: , in, is the corrected density of the pickling liquid in the i-th pickling tank, is the room temperature pickling liquid density of the i-th acid tank, C Si is the silicon content of the strip steel, W s For the strip width, L s is the strip length, δ s is the strip thickness, A 1 is the correction factor.

[0009] Preferably, the mathematical expression of the pickling solution ion concentration prediction model is: , , in, H in the pickling solution + Ion concentration, Fe in pickling solution 2+ Ion concentration, B 1 , B 2 , B 3 , B 4 , B 5 , B 6 , B 7 , B 8 , B 9 are all correction coefficients, and m is a constant term.

[0010] Preferably, the mathematical expression of the pickling solution ion concentration variation model is: , , in, is the acid concentration of the i-th pickling tank, is the iron concentration of the i-th pickling tank, L t is the length of the pickling tank, W t is the pickling tank width, H t is the liquid level of the pickling tank, Q in is the amount of acid fed, Q e is the acid output, c o is the regeneration acid concentration, The pickling tank Fe is a reaction between acid and oxide scale. 2+ The change in ions, The pickling tank H is where the acid reacts with the oxide scale. + Ion change, M HCl is the average molar mass of the acid, M Fe is the average molar mass of iron.

[0011] A system for predicting ion concentration in pickling liquid, using the above-mentioned method for predicting ion concentration in pickling liquid, comprising an acidic liquid data acquisition module, a pickling liquid parameter correction module, and an acid concentration performance analysis module; The acid liquid data acquisition module is used to obtain pickling liquid data and strip steel unit information; The pickling solution parameter correction module is used to obtain the normal temperature pickling solution density and the normal temperature pickling solution conductivity through temperature correction according to the pickling solution data, and obtain the pickling solution corrected density through density correction calculation according to the strip steel unit information and the normal temperature pickling solution density; The acid concentration performance analysis module is used to calculate the H in the pickling solution through the pickling solution ion concentration prediction model. + Ion concentration and Fe in pickling solution2+ Ion concentration: The change curves of acid concentration and iron concentration in each tank are calculated by the pickling liquid ion concentration change model.

[0012] An electronic device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned method for predicting the ion concentration in the pickling solution when executing the computer program.

[0013] A storage medium containing computer executable instructions, wherein the computer executable instructions are used to execute the above-mentioned method for predicting the ion concentration in the pickling solution when executed by a computer processor.

[0014] The beneficial effects of the present invention are: (1) By real-time detection of pickling liquid data and strip mill information, the H2O2 in the pickling liquid is calculated using the pickling liquid ion concentration prediction model based on the corrected density of the pickling liquid and the conductivity of the pickling liquid at room temperature. + Ion concentration and Fe in pickling solution 2+ The ion concentration can be predicted through the unit strip information over a period of time. The change curve of acid and iron concentration in the pickling liquid can be accurately detected in real time, which is helpful to realize the instant automatic control of the pickling line acid inlet and outlet, optimize the pickling liquid process control in the pickling production, and solve the problems of slow response speed of the operation mode and unstable pickling liquid process control caused by the pickling liquid offline detection and post-adjustment strategy.

[0015] (2) The density and electrical conductivity of the room temperature pickling solution are obtained by temperature correction based on the pickling solution data, and the density of the room temperature pickling solution is compensated according to the silicon content of the strip, thereby solving the problem of insufficient detection accuracy caused by silicon mud deposition and improving the prediction accuracy of the pickling solution ion concentration. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0017] Figure 1 It is a schematic flow diagram of a method for predicting ion concentration in a pickling solution of the present invention; Figure 2 This is a schematic diagram of a pickling line in a cold rolling mill; Figure 3 This is a comparison chart of the predicted acid concentration of the pickling liquid in the 1# tank under the parameters of 100 coils of strip steel. DETAILED DESCRIPTION

[0018] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation methods, structures, features and effects of the present invention are described in detail below in conjunction with the accompanying drawings and preferred embodiments.

[0019] See also Figure 1 , a method for predicting ion concentration in a pickling solution, comprising: S1: Acquire pickling liquid data, wherein the pickling liquid data includes pickling liquid temperature, pickling liquid density, and pickling liquid conductivity; S2: obtaining the density and conductivity of the room temperature pickling solution through temperature correction according to the pickling solution data; S3: obtaining strip steel unit information, wherein the strip steel unit information includes strip steel type, strip steel thickness, strip steel width, strip steel length, strip steel silicon content, strip steel coiling temperature, number of pickling tanks, pickling tank length, pickling tank width, pickling tank liquid level, strip steel pickling speed, acid feed amount, and regenerated acid concentration; S4: obtaining a corrected density of the pickling solution by density correction calculation according to the strip steel unit information and the density of the normal temperature pickling solution; S5: Calculate the H in the pickling solution according to the corrected density of the pickling solution and the conductivity of the pickling solution at room temperature through the pickling solution ion concentration prediction model. + Ion concentration and Fe in pickling solution 2+ Ion concentration; S6: According to the strip mill information, the acid concentration and iron concentration variation curves in each tank are calculated by using the pickling liquid ion concentration variation model.

[0020] In this embodiment, the acquisition of pickling liquid data is specifically implemented by the following steps: Use a thermometer to detect the pickling liquid temperature in real time; Real-time detection of pickling liquid density through a density meter; The conductivity of the pickling solution is detected in real time by a conductivity meter.

[0021] Specifically, the current cold rolling pickling line is generally composed of 3 to 4 tanks, and the thermometer, the density meter and the conductivity meter are installed in each tank.

[0022] In this embodiment, the step of obtaining the density of the room temperature pickling solution and the conductivity of the room temperature pickling solution by temperature correction according to the pickling solution data specifically includes: The mathematical expression of the temperature correction is: , , Among them, i is the pickling tank, k T is the conductivity of the pickling solution, ρ T is the pickling solution density, k 25 is the conductivity of the pickling solution at room temperature, ρ 25 is the density of the pickling solution at room temperature, T is the temperature of the pickling solution, and α and β are correction coefficients.

[0023] Specifically, the conductivity and density of the pickling solution tested in each acid tank are temperature corrected, and the test values ​​are converted to the conductivity and density of the pickling solution at room temperature.

[0024] In this embodiment, the method of obtaining the corrected density of the pickling solution by density correction calculation according to the strip steel unit information and the density of the normal temperature pickling solution specifically includes: The mathematical expression of the density correction is: , in, is the corrected density of the pickling liquid in the i-th pickling tank, is the room temperature pickling liquid density of the i-th acid tank, C Si is the silicon content of the strip steel, W s For the strip width, L s is the strip length, δ s is the strip thickness, A 1 is the correction factor.

[0025] In this embodiment, the H in the pickling solution is calculated by the pickling solution ion concentration prediction model according to the corrected density of the pickling solution and the conductivity of the pickling solution at room temperature. + Ion concentration and Fe in pickling solution 2+ Ion concentrations include: The mathematical expression of the pickling solution ion concentration prediction model is: , , in, H in the pickling solution + Ion concentration, Fe in pickling solution 2+ Ion concentration, B 1 , B 2 , B 3 , B 4 , B 5 , B 6 , B 7 , B 8 , B 9 are all correction coefficients, and m is a constant term.

[0026] In this embodiment, the change curves of acid concentration and iron concentration in each tank calculated by the pickling liquid ion concentration change model according to the strip mill information specifically include: The mathematical expression of the pickling solution ion concentration variation model is: , , in, is the acid concentration of the i-th pickling tank, is the iron concentration of the i-th pickling tank, L t is the length of the pickling tank, W t is the pickling tank width, H t is the liquid level of the pickling tank, Q in is the amount of acid fed, Q e is the acid output, c o is the regeneration acid concentration, The pickling tank Fe is a reaction between acid and oxide scale. 2+ The change in ions, The pickling tank H is where the acid reacts with the oxide scale. + Ion change, M HCl is the average molar mass of the acid, M Fe is the average molar mass of iron.

[0027] Specifically, the changes in acid concentration and iron concentration are calculated based on the flow exchange between tanks and the reaction between acid and oxide scale. The evaporation of acid in the pickling tank and the acid inlet and outlet are also considered in the calculation process.

[0028] It should be noted that the acid in the pickling tank reacts with the oxide scale. 2+ The mathematical expression of the ion change is: , The acid reacts with the oxide scale in the pickling tank H + The mathematical expression of the ion change is: , Where v is the pickling speed of the strip steel, a(T C ) is the coiling temperature of the reaction strip, T C is the strip coiling temperature, is the mass of oxide scale of each coil of strip steel, is the average molar mass of the oxide scale, P() is the pickling degree of the strip in the pickling solution; Specifically, the mathematical expression of the mass of the oxide scale of each coil of strip steel is: , , , , , in, is the average thickness of the oxide scale of each coil, is the iron-oxygen ratio of the oxide, is the average density of the oxide scale, C 1 , C 2 , C 3 , C 4 , C 5 , C 6 , C 7 , C 8 , C 9 , C 10 , C 11 , C 12 , C 13 is the correction factor, Cal(Type S ) is the correction factor based on the strip steel category, and each category of strip steel corresponds to a value.

[0029] The mathematical expression of the pickling degree of the strip in the pickling solution is: , Where P(t) is the pickling degree of strip steel t in the pickling solution, K 0 is the chemical reaction rate, E a is the activation energy of the reaction, R is the molar gas constant, T i is the temperature of the i-th pickling tank, n (i) is the correction factor based on the tank body.

[0030] A system for predicting ion concentration in pickling liquid, comprising an acidic liquid data acquisition module, a pickling liquid parameter correction module, and an acid concentration performance analysis module; The acid liquid data acquisition module is used to obtain pickling liquid data and strip steel unit information; The pickling solution parameter correction module is used to obtain the normal temperature pickling solution density and the normal temperature pickling solution conductivity through temperature correction according to the pickling solution data, and obtain the pickling solution corrected density through density correction calculation according to the strip steel unit information and the normal temperature pickling solution density; The acid concentration performance analysis module is used to calculate the H in the pickling solution through the pickling solution ion concentration prediction model. + Ion concentration and Fe in pickling solution 2+ Ion concentration: The change curves of acid concentration and iron concentration in each tank are calculated by the pickling liquid ion concentration change model.

[0031] In this embodiment, the pickling tanks of the cold rolling pickling line are all equipped with thermometers, densitometers and conductivity meters, and are connected to the ion concentration prediction system in the pickling solution through the sensor interface; the temperature of the pickling solution is detected in real time by the thermometer, the density of the pickling solution is detected in real time by the densitometer, and the conductivity of the pickling solution is detected in real time by the conductivity meter, and the temperature of the pickling solution, the density of the pickling solution and the conductivity of the pickling solution are all transmitted to the pickling solution parameter correction module, specifically, the temperature correction unit is used to correct, the temperature of the pickling solution is converted by the correction coefficient α to obtain the density of the pickling solution at room temperature, and the conductivity of the pickling solution is converted by the correction coefficient β to obtain the conductivity of the pickling solution at room temperature; The strip steel unit information used in the test and the density of the normal temperature pickling solution are input into the density correction unit, and the correction coefficient is used according to the silicon content of the strip steel, the width of the strip steel, the length of the strip steel, and the thickness of the strip steel. A 1 Converting the room temperature pickling solution density to obtain a corrected pickling solution density; The conductivity of the room temperature pickling solution and the corrected density of the pickling solution are transmitted to the acid concentration performance analysis module, and the concentrations of H+ ions and Fe2+ ions in the pickling solution are obtained by solving the pickling solution ion concentration prediction model. Specifically, according to the corrected density of the pickling solution and the correction coefficient B 1 , Correction coefficient B 2 , Correction coefficient B 3 , Correction coefficient B 4 , establish the H + Ion concentration and Fe in pickling solution 2+ The relationship between the ion concentration; according to the conductivity of the room temperature pickling solution, the correction factor B 5 , Correction coefficient B 6 , Correction coefficient B 7 , Correction coefficient B 8 , Correction coefficient B 9 , establish the H + Ion concentration and Fe in pickling solution 2+ The relationship between the current pickling tank length, current pickling tank width, current pickling tank liquid level, current pickling tank acid inflow, current pickling tank acid outflow, current pickling tank regeneration acid concentration, acid and scale reaction acid tank Fe 2+ Ion change, acid tank H of acid and scale reaction + The ion change is input into the pickling liquid ion concentration change model to calculate the acid concentration and iron concentration of the pickling tank after the reaction between the acid and the oxide scale. The acid concentration and iron concentration change curves in each tank are drawn based on the acid concentration change data points and iron concentration change data points of the pickling tank obtained by multiple tests and calculations.

[0032] In this embodiment, the pickling line of a cold rolling mill adopts turbulent hydrochloric acid pickling, see Figure 2 The pickling line is divided into three sections. Newly regenerated acid is added from the 3# tank. The pickling liquid flows from the 3# tank into the 2# tank by overflow, and then overflows into the 1# tank. The waste acid is discharged from the 1# tank. In order to accurately determine the amount of discharged waste acid, it is necessary to monitor the performance of each pickling tank on the pickling line in real time, obtain the acid concentration and iron ion concentration in the pickling liquid, and the change curve of the acid and iron concentration in the pickling liquid. The pickling liquid ion concentration prediction system described in the present invention is installed in the pickling line equipment.

[0033] Specifically, according to the actual situation at the pickling unit site, the pickling liquid ion concentration prediction system is installed next to the 1#, 2#, and 3# pickling tanks. Each acid tank has a pipeline for testing the conductivity of the pickling liquid. The inlet of the pipeline is connected to the outlet of the acid tank pickling liquid circulation pump, and the acid at the outlet flows directly into the acid tank.

[0034] It should be noted that the density meter in the pickling liquid ion concentration prediction system uses a side-mounted XY883 density meter with a test range of 0 to 2 g / cm3; the conductivity meter uses the FMD2000 conductivity meter and its matching transmitter produced by Yokogawa Corporation of Japan, with a test range of 0 to 2000mS / cm; the temperature sensor uses Emerson PT100-385 temperature sensor with a test range of 0 to 100°C; the liquid storage tank is made of PPH material, with a tank wall thickness of 10mm, a tank diameter of 200mm, a height of 1100mm, and a distance between the density meter and the pickling liquid inlet and outlet pipes of 220mm; the flow rate of the metering pump when the system is running is 150L / min.

[0035] In this embodiment, the pickling liquid performance analysis module calculates the H in the pickling liquid. + Ion concentration and Fe in pickling solution 2+ For ion concentration, please refer to Table 1. The predicted values ​​of hydrochloric acid concentration and iron ion concentration in the pickling liquid in tank 1# are within 3g / L compared with the measured values.

[0036]

[0037] Table 1 In this example, see Figure 3 The comparison results of the predicted value and the measured value of the acid concentration of the pickling solution in the 1# tank under the strip parameters of 100 coils show that the ion concentration prediction method in the pickling solution of the present invention has a good prediction effect, especially for the relatively front steel coils.

[0038] The computer storage medium of the embodiment of the present invention may adopt any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device.

[0039] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0040] The program code included on the computer readable medium can be transmitted with any appropriate medium, including but not limited to wireless, electric wire, optical cable, RF, etc., or any suitable combination of the above. The computer program code for performing the operation of the present invention can be written in one or more programming languages ​​or their combinations, and the programming language includes object-oriented programming languages-such as Java, Smalltalk, C++, and also includes conventional procedural programming languages-such as "C" language or similar programming languages. The program code can be executed completely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on the remote computer, or completely on the remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0041] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention without departing from the content of the technical solution of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A method for predicting ion concentration in a pickling solution, characterized in that: include: Acquiring pickling liquid data, wherein the pickling liquid data includes pickling liquid temperature, pickling liquid density, and pickling liquid conductivity; Obtaining the density and electrical conductivity of the room-temperature pickling solution according to the pickling solution data through temperature correction; Acquire strip steel unit information, wherein the strip steel unit information includes strip steel type, strip steel thickness, strip steel width, strip steel length, strip steel silicon content, strip steel coiling temperature, number of pickling tanks, pickling tank length, pickling tank width, pickling tank liquid level, strip steel pickling speed, acid feed amount, and regenerated acid concentration; According to the strip steel unit information and the density of the normal temperature pickling solution, a density correction calculation is performed to obtain a corrected density of the pickling solution; The H in the pickling solution is calculated based on the corrected density of the pickling solution and the conductivity of the pickling solution at room temperature using the pickling solution ion concentration prediction model. + Ion concentration and Fe in pickling solution 2+ Ion concentration; According to the strip mill information, the change curves of the acid concentration and the iron concentration in each tank are calculated by using the pickling liquid ion concentration change model.

2. The method for predicting ion concentration in pickling liquid according to claim 1, characterized in that: The mathematical expression of the temperature correction is: ， ， Among them, i is the pickling tank, k T is the conductivity of the pickling solution, ρ T is the pickling solution density, k 25 is the conductivity of the pickling solution at room temperature, ρ 25 is the density of the pickling solution at room temperature, T is the temperature of the pickling solution, and α and β are correction coefficients.

3. The method for predicting ion concentration in pickling liquid according to claim 1, characterized in that: The mathematical expression of the density correction is: ， in, is the corrected density of the pickling liquid in the i-th pickling tank, is the room temperature pickling liquid density of the i-th acid tank, C Si is the silicon content of the strip steel, W s For the strip width, L s is the strip length, δ s is the strip thickness, A 1 is the correction factor.

4. The method for predicting ion concentration in pickling liquid according to claim 1, characterized in that: The mathematical expression of the pickling solution ion concentration prediction model is: ， ， in, H in the pickling solution + Ion concentration, Fe in pickling solution 2+ Ion concentration, B1, B2, B3, B4, B5, B6, B7, B8, B9 are all correction coefficients, and m is a constant term.

5. The method for predicting ion concentration in pickling liquid according to claim 1, characterized in that: The mathematical expression of the pickling solution ion concentration variation model is: ， ， in, is the acid concentration of the i-th pickling tank, is the iron concentration of the i-th pickling tank, L t is the length of the pickling tank, W t is the pickling tank width, H t is the liquid level of the pickling tank, Q in is the amount of acid fed, Q e is the acid output, c o is the regeneration acid concentration, The pickling tank Fe is a reaction between acid and oxide scale. 2+ The change in ions, The pickling tank H is where the acid reacts with the oxide scale. + Ion change, M HCl is the average molar mass of the acid, M Fe is the average molar mass of iron.

6. A system for predicting ion concentration in pickling liquid, using the method for predicting ion concentration in pickling liquid according to any one of claims 1 to 5, characterized in that: It includes acid liquid data acquisition module, pickling liquid parameter correction module and acid concentration performance analysis module; The acid liquid data acquisition module is used to obtain pickling liquid data and strip steel unit information; The pickling solution parameter correction module is used to obtain the normal temperature pickling solution density and the normal temperature pickling solution conductivity through temperature correction according to the pickling solution data, and obtain the pickling solution corrected density through density correction calculation according to the strip steel unit information and the normal temperature pickling solution density; The acid concentration performance analysis module is used to calculate the H in the pickling solution through the pickling solution ion concentration prediction model. + Ion concentration and Fe in pickling solution 2+ Ion concentration: The change curves of acid concentration and iron concentration in each tank are calculated by the pickling liquid ion concentration change model.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method for predicting the ion concentration in the pickling solution as described in any one of claims 1 to 5 is implemented.

8. A storage medium containing computer executable instructions, characterized in that: The computer executable instructions are used to execute the method for predicting the ion concentration in the pickling solution as described in any one of claims 1 to 5 when executed by a computer processor.

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