Method and system for online measurement of lye concentration

Abstract

The present disclosure relates to the technical field of treatment of cold-rolled strip steel, and in particular to a method and system for online measurement of a lye concentration. The method comprises: measuring lye surface tension of a circulation tank in real time; substituting the lye surface tension into a trained model for calculation to obtain a lye concentration; and then automatically controlling the lye concentration to reach a preset value. The technical solution of the present disclosure achieves online measurement of the lye concentration, and on the basis of the online measurement of the lye concentration, achieves automatic control over the lye concentration, ensures that the lye concentration is stable, ensures the quality of strip steel cleaning, and achieves low hysteresis. The representation of the cleaning capacity of a lye by lye surface tension has good representativeness. A relationship between the lye concentration and the lye surface tension is established by means of a soft measurement method, and a lye concentration prediction model can perform continuous learning by means of training, thereby achieving very high precision. In addition, on the basis of the lye concentration, the supplementation of an original lye and desalted water and the discharge of a waste lye are achieved; and the fluctuation of the lye concentration is small.

Description

A method and system for online detection of alkali solution concentration Technical Field

[0001] The present disclosure relates to the technical field of cold-rolled strip steel processing, and in particular to an online detection method and system for alkali solution concentration. Background Art

[0002] In cold rolling or galvanizing lines, after the strip enters the annealing furnace, residue on the strip's surface can easily adhere to the rollers under high temperatures, forming roll nodules and roller marks on the strip surface, seriously affecting product quality. Furthermore, residue can affect the strip's coating and plating quality, affecting the paint film's adhesion and corrosion resistance.

[0003] In order to reduce the nodules of furnace rollers and improve the coating effect of strip steel, the surface residues of strip steel are generally cleaned by alkali spraying, alkali brushing, electrolytic cleaning, ultrasonic cleaning, water brushing and rinsing, etc., and the surface residues of strip steel are controlled within the allowable range (residual iron 10mg / ㎡, residual iron 10mg / ㎡).

[0004] During the cleaning process, alkali concentration significantly impacts the cleaning effect. Low alkali concentration can easily lead to incomplete cleaning, affecting the quality of the finished product and causing losses. Currently, alkali concentration testing relies on offline sampling, which has long intervals and significant hysteresis. Furthermore, alkali circulation tanks and electrolyte circulation tanks are intermittently replenished and drained, causing alkali concentration fluctuations that affect cleaning effectiveness.

[0005] Summary of the Invention

[0006] The present disclosure aims to solve at least one of the technical problems existing in the prior art, and proposes an online detection method and system for alkali solution concentration.

[0007] In a first aspect, the present disclosure provides a method for online detection of alkali solution concentration, comprising:

[0008] Obtain the alkali solution concentration and the corresponding alkali solution surface tension, take the alkali solution concentration as the dependent variable y, and the corresponding alkali solution surface tension as the independent variable x, and establish the alkali solution concentration prediction model y=a0+a1x+a2x 2 +…+a n x n ; Among them, a0, a1 to a n are model parameters;

[0009] Training the alkali solution concentration prediction model until the deviation of the predicted alkali solution concentration is controlled within an allowable range;

[0010] Get the real-time alkali solution surface tension as the independent variable x s , substitute the trained alkali solution concentration prediction model to obtain the corresponding real-time alkali solution concentration prediction value y s ;

[0011] According to the real-time alkali solution concentration prediction value y s , adjust the real-time alkali solution concentration to the alkali solution concentration set value.

[0012] Preferably, adjusting the real-time alkali solution concentration to the alkali solution concentration set value according to the real-time alkali solution concentration prediction value specifically includes:

[0013] Compare the alkali solution concentration set value data and the real-time alkali solution concentration prediction value y s , taking the liquid level of the electrolyte circulation tank and the liquid level of the alkali circulation tank as constraints, by adding desalted water or original alkali solution to the electrolyte circulation tank and the alkali circulation tank, the real-time alkali concentration of the electrolyte circulation tank and the alkali circulation tank is adjusted to reach the alkali concentration set value.

[0014] Preferably, the adjusting the real-time alkali solution concentration to the alkali solution concentration set value specifically includes:

[0015] If the real-time alkali solution concentration is too high, add desalted water; if the real-time alkali solution concentration is too low, add original alkali solution.

[0016] Preferably, the step of adjusting the real-time alkali solution concentration to the alkali solution concentration set value further comprises:

[0017] If the real-time alkali solution concentration is lower than the preset threshold, the waste alkali solution of the electrolyte circulation tank and the alkali solution circulation tank is discharged to adjust the real-time alkali solution concentration of the electrolyte circulation tank and the alkali solution circulation tank to the alkali solution concentration set value.

[0018] Preferably, the training of the alkali solution concentration prediction model specifically includes:

[0019] The alkali solution concentration prediction model is trained by regression using the least squares method.

[0020] In a second aspect, the present disclosure further provides an online detection system for alkali solution concentration, which can be used to implement the above-mentioned online detection method for alkali solution concentration. The online detection system for alkali solution concentration includes:

[0021] The modeling module is configured to obtain the alkali solution concentration and the corresponding alkali solution surface tension, with the alkali solution concentration as the dependent variable y and the corresponding alkali solution surface tension as the independent variable x, and establish the alkali solution concentration prediction model y=a0+a1x+a2x 2 +…+a n x n ; Among them, a0, a1 to a n are model parameters;

[0022] A training module is configured to perform regression training on the alkali solution concentration prediction model using the least squares method until the deviation of the predicted alkali solution concentration is controlled within an allowable range;

[0023] The detection module is configured to obtain the real-time alkali solution surface tension as the independent variable x s , substitute the trained alkali solution concentration prediction model to obtain the corresponding real-time alkali solution concentration prediction value y s ;

[0024] The alkali solution concentration automatic control module is configured to s , adjust the real-time alkali solution concentration to the alkali solution concentration set value.

[0025] Preferably, the detection module includes:

[0026] A first liquid level gauge and a first alkali solution surface tension online detector for real-time detection of the liquid level and surface tension of the electrolyte circulation tank;

[0027] The second liquid level meter and the second alkali liquid surface tension online detector are used for real-time detection of the liquid level and surface tension of the alkali liquid circulation tank.

[0028] Preferably, the alkali solution concentration automatic control module is further configured as follows:

[0029] Taking the liquid level of the electrolyte circulation tank and the liquid level of the alkali circulation tank as constraints, by adding desalted water or raw alkali solution to the electrolyte circulation tank and the alkali circulation tank, the real-time alkali concentration of the electrolyte circulation tank and the alkali circulation tank is adjusted to reach the set value of the alkali concentration;

[0030] If the real-time alkali solution concentration is too high, then add desalted water; if the real-time alkali solution concentration is too low, then add original alkali solution;

[0031] If the real-time alkali solution concentration is lower than the preset threshold, the waste alkali solution of the electrolyte circulation tank and the alkali solution circulation tank is discharged to adjust the real-time alkali solution concentration of the electrolyte circulation tank and the alkali solution circulation tank to the alkali solution concentration set value.

[0032] Preferably, the alkali solution concentration automatic control module includes a desalted water tank for replenishing desalted water, and an alkali raw liquid tank for replenishing raw alkali solution;

[0033] The desalted water or original alkali solution is replenished or the waste alkali solution is discharged through the shut-off valve group.

[0034] Preferably, the detection module further includes an alkali solution surface tension online detector for obtaining the real-time alkali solution surface tension, and the alkali solution concentration prediction model after training is substituted to obtain the corresponding real-time alkali solution concentration prediction value y s , and the real-time alkali solution concentration prediction value y s Feedback to the alkali solution concentration automatic control module. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] FIG1 is a flow chart of an online detection method for alkali solution concentration provided by an embodiment of the present disclosure;

[0036] FIG2 is a block diagram showing the principle of an online detection system for alkali solution concentration according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0037] In order to enable those skilled in the art to better understand the technical solutions of the present disclosure, the present disclosure is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0038] Unless otherwise defined, the technical or scientific terms used in this disclosure should have the usual meanings understood by people with ordinary skills in the field to which this disclosure belongs. The words "first", "second" and similar terms used in this disclosure do not indicate any order, quantity or importance, but are only used to distinguish different components. Similarly, words such as "one", "an" or "the" are not limited to quantity, but rather to the presence of at least one. Words such as "include" or "comprise" mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. Words such as "connect" or "connected" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used for relative positional relationships. When the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0039] In each accompanying drawing, identical elements are represented by similar reference numerals. For the sake of clarity, the various parts in the accompanying drawings are not all drawn to scale. In addition, some well-known parts may not be shown in the drawings.

[0040] Many specific details of the present disclosure are described below, such as component structures, materials, dimensions, processing techniques, and technologies, to provide a clearer understanding of the present disclosure. However, as will be appreciated by those skilled in the art, the present disclosure may be implemented without following these specific details.

[0041] As shown in FIG1 , an online detection method for alkali solution concentration includes the following steps:

[0042] S1, obtain the alkali solution concentration and the corresponding alkali solution surface tension, take the alkali solution concentration as the dependent variable y, the corresponding alkali solution surface tension as the independent variable x, and establish the alkali solution concentration prediction model y=a0+a1x+a2x 2 +…+a n x n ; Among them, a0, a1 to a n are model parameters;

[0043] S2, training the alkali solution concentration prediction model until the predicted alkali solution concentration deviation is controlled within an allowable range;

[0044] S3, obtain the real-time alkali solution surface tension as the independent variable x s , substitute the trained alkali solution concentration prediction model to obtain the corresponding real-time alkali solution concentration prediction value y s ;

[0045] S4, according to the real-time alkali solution concentration predicted value y s , adjust the real-time alkali solution concentration to the alkali solution concentration set value.

[0046] In some embodiments, the supply end may specifically be a compressed air station.

[0047] Different from the off-line sampling and testing method used in the related art for alkali solution concentration detection, the technical solution disclosed in the present invention realizes online detection of alkali solution concentration. On the basis of online detection of alkali solution concentration, automatic control of alkali solution concentration is realized to ensure the stability of alkali solution concentration, the cleaning quality of strip steel is guaranteed, and hysteresis is small. The cleaning ability of alkali solution is represented by the surface tension of alkali solution, which has good representativeness. The relationship between alkali solution concentration and alkali solution surface tension is established by soft measurement method, and the alkali solution concentration prediction model can continuously learn through training, thereby achieving very high accuracy. In addition, the original alkali solution, desalted water or waste alkali solution can be replenished based on the alkali solution concentration, and the alkali solution concentration fluctuates little.

[0048] It should be noted that the technical solution of the present disclosure does not limit the order of steps S1, S2, S3, and S4. That is, step S1 can be executed before steps S2, S3, and S4, or after steps S2, S3, and S4, or simultaneously with steps S2, S3, and S4. The order of the steps is also not limited.

[0049] In a specific implementation scenario:

[0050] First, the surface tension data of alkali solution at different alkali solution concentrations are collected and stored in the alkali solution concentration online detection and automatic control computer. The alkali solution concentration data are collected through offline sampling and testing. The alkali solution concentration is used as the dependent variable y and the alkali solution surface tension is used as the independent variable x. The alkali solution concentration prediction model y = a0 + a1x + a2x is established. 2 +…+a n x n After accumulating a certain amount of sample data of alkali solution concentration and alkali solution surface tension, the least squares method is used to perform regression training based on the sample data of alkali solution concentration and alkali solution surface tension until the deviation of the predicted alkali solution concentration is controlled within the allowable range.

[0051] Secondly, the real-time data of the alkali solution surface tension is collected through the alkali solution surface tension online detector, and the trained alkali solution concentration prediction model is called to calculate the real-time alkali solution concentration.

[0052] Finally, the alkali solution concentration automatic control module is run. This module compares the set alkali solution concentration data with the real-time alkali solution concentration data. Using the electrolyte circulation tank level and the alkali solution circulation tank level as constraints, it replenishes desalted water if the real-time alkali solution concentration is too high. If the real-time alkali solution concentration is too low, it replenishes the original alkali solution. If the real-time alkali solution concentration falls below a certain threshold, the alkali solution is discharged, achieving automatic alkali solution concentration control. This ensures a stable alkali solution concentration and guarantees the strip cleaning quality.

[0053] The present disclosure also provides an online detection system for alkali solution concentration, which can be used to implement any of the above-mentioned online detection methods for alkali solution concentration. The online detection system for alkali solution concentration includes:

[0054] The modeling module is configured to obtain the alkali solution concentration and the corresponding alkali solution surface tension, with the alkali solution concentration as the dependent variable y and the corresponding alkali solution surface tension as the independent variable x, and establish the alkali solution concentration prediction model y=a0+a1x+a2x 2 +…+a n x n ; Among them, a0, a1 to a n are model parameters;

[0055] A training module is configured to perform regression training on the alkali solution concentration prediction model using the least squares method until the deviation of the predicted alkali solution concentration is controlled within an allowable range;

[0056] The detection module is configured to obtain the real-time alkali solution surface tension as the independent variable x s , substitute the trained alkali solution concentration prediction model to obtain the corresponding real-time alkali solution concentration prediction value y s ;

[0057] The alkali solution concentration automatic control module is configured to s , adjust the real-time alkali solution concentration to the alkali solution concentration set value.

[0058] As shown in Figure 2, the alkali solution concentration automatic control module includes an online alkali solution concentration detection and automatic control computer, industrial Ethernet, the alkali wash process section PLC, and shut-off valves 1, 2, 3, 4, 5, and 6. The detection module includes liquid level gauges 1 and 2, and online alkali solution surface tension detectors 1 and 2. The online alkali solution concentration detection and automatic control computer communicates with the alkali wash process section PLC via industrial Ethernet.

[0059] The alkali concentration online detection and automatic control computer communicates with the alkali wash process PLC to collect data and issue commands for the alkali wash process. The alkali wash process PLC is connected to liquid level gauges 1 and 2, online alkali surface tension detectors 1 and 2, shut-off valves 1, 2, 3, 4, 5, and 6, collecting real-time information such as the electrolyte circulation tank alkali level, the electrolyte circulation tank alkali level, the electrolyte circulation tank alkali surface tension, and the electrolyte circulation tank alkali surface tension. The alkali concentration automatic control module compares the set alkali concentration data with the real-time alkali concentration data. Using the electrolyte circulation tank level and the alkali circulation tank level as constraints, the module replenishes desalted water if the real-time alkali concentration is too high, and replenishes raw alkali water if the real-time alkali concentration is too low. If the real-time alkali concentration falls below a certain threshold, the waste alkali is discharged, achieving automatic alkali concentration control. This ensures stable alkali concentration and guaranteed strip cleaning quality.

[0060] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the aforementioned module, program segment, or a part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0061] It will be understood that the above embodiments are merely exemplary embodiments for illustrating the principles of the present invention, and the present invention is not limited thereto. Those skilled in the art will appreciate that various modifications and improvements can be made without departing from the spirit and substance of the present invention, and such modifications and improvements are also considered to be within the scope of protection of the present invention.

Claims

1. A method for online detection of alkali solution concentration, characterized in that: include: Obtain the alkali solution concentration and the corresponding alkali solution surface tension, take the alkali solution concentration as the dependent variable y, and the corresponding alkali solution surface tension as the independent variable x, and establish the alkali solution concentration prediction model y=a0+a1x+a2x 2 +…+a n x n ; Among them, a0, a1 to a n are model parameters; Training the alkali solution concentration prediction model until the deviation of the predicted alkali solution concentration is controlled within an allowable range; Get the real-time alkali solution surface tension as the independent variable x s , substitute the trained alkali solution concentration prediction model to obtain the corresponding real-time alkali solution concentration prediction value y s ; According to the real-time alkali solution concentration prediction value y s , adjust the real-time alkali solution concentration to the alkali solution concentration set value.

2. The online detection method for alkali solution concentration according to claim 1, wherein The step of adjusting the real-time alkali solution concentration to the alkali solution concentration set value according to the real-time alkali solution concentration prediction value specifically includes: Compare the alkali solution concentration set value data and the real-time alkali solution concentration prediction value y s , taking the liquid level of the electrolyte circulation tank and the liquid level of the alkali circulation tank as constraints, by adding desalted water or original alkali solution to the electrolyte circulation tank and the alkali circulation tank, the real-time alkali concentration of the electrolyte circulation tank and the alkali circulation tank is adjusted to reach the alkali concentration set value.

3. The online detection method for alkali solution concentration according to claim 2, wherein: The adjusting of the real-time alkali solution concentration to the alkali solution concentration set value specifically includes: If the real-time alkali solution concentration is too high, add desalted water; if the real-time alkali solution concentration is too low, add original alkali solution.

4. The online detection method for alkali solution concentration according to claim 3, wherein The step of adjusting the real-time alkali solution concentration to the alkali solution concentration set value further comprises: If the real-time alkali solution concentration is lower than the preset threshold, the waste alkali solution of the electrolyte circulation tank and the alkali solution circulation tank is discharged to adjust the real-time alkali solution concentration of the electrolyte circulation tank and the alkali solution circulation tank to the alkali solution concentration set value.

5. The method for online detection of alkali solution concentration according to claim 1, wherein The training of the alkali solution concentration prediction model specifically includes: The alkali solution concentration prediction model is trained by regression using the least squares method.

6. An online detection system for alkali concentration, characterized in that: The alkali solution concentration online detection system can be used to implement the alkali solution concentration online detection method described in any one of claims 1 to 5 above, and the alkali solution concentration online detection system includes: The modeling module is configured to obtain the alkali solution concentration and the corresponding alkali solution surface tension, with the alkali solution concentration as the dependent variable y and the corresponding alkali solution surface tension as the independent variable x, and establish the alkali solution concentration prediction model y=a0+a1x+a2x 2 +…+a n x n ; Among them, a0, a1 to a n are model parameters; A training module is configured to perform regression training on the alkali solution concentration prediction model using the least squares method until the deviation of the predicted alkali solution concentration is controlled within an allowable range; The detection module is configured to obtain the real-time alkali solution surface tension as the independent variable x s , substitute the trained alkali solution concentration prediction model to obtain the corresponding real-time alkali solution concentration prediction value y s ; The alkali solution concentration automatic control module is configured to s , adjust the real-time alkali solution concentration to the alkali solution concentration set value.

7. The alkali solution concentration online detection system according to claim 6, characterized in that: The detection module includes: A first liquid level gauge and a first alkali solution surface tension online detector for real-time detection of the liquid level and surface tension of the electrolyte circulation tank; The second liquid level meter and the second alkali liquid surface tension online detector are used for real-time detection of the liquid level and surface tension of the alkali liquid circulation tank.

8. The alkali solution concentration online detection system according to claim 7, characterized in that: The alkali solution concentration automatic control module is also configured as follows: Taking the liquid level of the electrolyte circulation tank and the liquid level of the alkali circulation tank as constraints, by adding desalted water or raw alkali solution to the electrolyte circulation tank and the alkali circulation tank, the real-time alkali concentration of the electrolyte circulation tank and the alkali circulation tank is adjusted to reach the set value of the alkali concentration; If the real-time alkali solution concentration is too high, then add desalted water; if the real-time alkali solution concentration is too low, then add original alkali solution; If the real-time alkali solution concentration is lower than the preset threshold, the waste alkali solution of the electrolyte circulation tank and the alkali solution circulation tank is discharged to adjust the real-time alkali solution concentration of the electrolyte circulation tank and the alkali solution circulation tank to the alkali solution concentration set value.

9. The alkali solution concentration online detection system according to claim 7, characterized in that: The alkali solution concentration automatic control module includes a desalted water tank for replenishing desalted water and an alkali raw liquid tank for replenishing original alkali solution; The desalted water or original alkali solution is replenished or the waste alkali solution is discharged through the shut-off valve group.

10. The alkali solution concentration online detection system according to claim 6, characterized in that: The detection module also includes an online alkali solution surface tension detector for obtaining the real-time alkali solution surface tension, and the alkali solution concentration prediction model after training is substituted to obtain the corresponding real-time alkali solution concentration prediction value y s , and the real-time alkali solution concentration prediction value y s Feedback to the alkali solution concentration automatic control module.

Images