New energy steel type normalizing pickling process and pickling equipment

Abstract

The invention belongs to the technical field of steel production, and particularly relates to a new energy steel grade normalizing pickling process and pickling equipment, and the new energy steel grade normalizing pickling process comprises shot blasting machine parameter dynamic regulation and control, pickling process intelligent optimization, normalizing furnace temperature field reconstruction and rolling parameter collaborative matching. The product quality stability is improved through multi-parameter cooperative control, and real-time accurate regulation and control of key parameters such as the steel shot throwing amount and the acid liquor activation index are achieved through linkage of a shot blasting strength dynamic adjustment model and an acid pickling closed-loop compensation mechanism. And in combination with normalizing furnace temperature field gradient reconstruction and oxygen content three-level linkage control, surface oxide scale residues are effectively eliminated, the steel grain size level is improved, and the product yield strength fluctuation range is reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of steel production, and specifically relates to a normalizing pickling process and pickling equipment for new energy steel grades. Background Art

[0002] The manufacturing process of new energy steel grades faces multiple technical challenges in the context of the green and low-carbon transformation. The traditional normalizing pickling process has problems such as low pickling efficiency and excessive scale residue. Especially when the rolling speed is increased to more than 120 m / min, the conventional temperature field distribution (temperature difference in the soaking section > 100°C) is likely to cause uneven grain structure, affecting the corrosion resistance of the material.

[0003] In the prior art, the regulation of acid concentration mostly relies on manual experience, and the fluctuation range of the activation index often exceeds ±0.3, resulting in increased acid consumption and waste liquid treatment pressure. There are still data islands between the shot peening parameters and the rolling process, making it difficult to form a dynamic correlation between the feedback value of shot peening intensity and the rolling mill reduction rate, which restricts the improvement of the product yield of the production line.

[0004] Therefore, the present invention provides a normalizing pickling process and pickling equipment for new energy steel grades. Summary of the Invention

[0005] In order to make up for the deficiencies of the prior art and solve at least one of the technical problems proposed in the background art.

[0006] The technical solution adopted by the present invention to solve its technical problems is: A normalizing pickling process for new energy steel grades described in the present invention includes

[0007] Dynamic regulation of shot peening machine parameters: Real-time collect the steel shot throwing amount, projection angle and working pressure parameters of the shot peening machine, establish a dynamic adjustment model according to the feedback value of shot peening intensity, and generate control instructions;

[0008] Intelligent optimization of pickling process: In response to the control instructions, synchronously increase the acid solution temperature to 75 - 85°C and the hydrochloric acid concentration to 12 - 18 wt% through a PID controller, and establish a closed-loop compensation mechanism based on an online conductivity sensor to keep the activation index of the acid solution within the fluctuation range of 0.85 - 1.15;

[0009] Reconstruction of the normalizing furnace temperature field: Under the working condition that the rolling mill speed is increased to 120 - 150 m / min, adjust the temperature gradient of the soaking section of the normalizing furnace to 850 - 880°C in the front area, 900 - 920°C in the middle area, and 830 - 850°C in the rear area. At the same time, control the oxygen content in the furnace ≤ 50 ppm and extend the holding time by 15 - 25%;

[0010] Coordinated matching of rolling parameters: According to the real-time detection data of the online thickness gauge, dynamically adjust the rolling mill reduction rate to make it linearly correspond to the pickling activation index and the normalizing furnace temperature field, forming a process parameter interlock control system.

[0011] Preferably, the shot throwing amount, projectile angle and working pressure parameters of the shot blasting machine are collected in real time, specifically:

[0012] A high-precision weighing sensor is installed at the shot blasting machine outlet to record the steel shot flow in real time and obtain the current steel shot throwing amount Q; the laser rangefinder is linked with the encoder to measure the angle between the directional sleeve and the workpiece to obtain the current projectile angle J; a pressure transmitter is installed on the pneumatic pipeline of the shot blasting machine to collect the compressed air pressure value and obtain the current working pressure Y.

[0013] Preferably, the shot blasting intensity feedback value S under the current working condition is calculated by the current steel shot throwing amount Q, the current projectile angle J and the current working pressure Y;

[0014]

[0015] Wherein, D is the average particle size of the steel shot, and K is the equipment status correction coefficient; the equipment status correction coefficient is obtained by fitting historical data.

[0016] Preferably, the dynamic adjustment model is a fuzzy PID control model, the input parameters include the shot blasting intensity deviation value, and the output parameters are the steel shot flow compensation amount, the projectile angle adjustment amount, and the working pressure correction amount.

[0017] Preferably, the shot blasting intensity deviation value is the difference SP between the current shot blasting intensity feedback value and the standard shot blasting intensity feedback value. (The standard shot blasting intensity feedback value is set by those skilled in the art based on historical experience)

[0018] Preferably, the control instructions include a first-level adjustment instruction and a second-level adjustment instruction, specifically:

[0019] When 0.02≤SP<0.05, a first-level adjustment instruction is generated;

[0020] The steel shot flow compensation amount is ΔQ = ±(0.1×SP)×Q0; where Q0 is the reference throwing amount;

[0021] The projectile angle adjustment step is ΔJ = ±0.5°;

[0022] When 0.05≤SP, a secondary adjustment instruction is generated;

[0023] The working pressure correction is ΔY = ±(0.02×SP)×Y0; where Y0 is the reference pressure.

[0024] Preferably, a closed-loop compensation mechanism is established based on an online conductivity sensor, specifically:

[0025] Collect the acid solution ion mobility data every 30 seconds through the conductivity sensor. When the activation index deviates from the range of 0.85 - 1.15, trigger the fuzzy PID controller to output a compensation signal to the heating coil and the concentrated hydrochloric acid metering pump to adjust the temperature value and the hydrochloric acid concentration value.

[0026] Preferably, the control of the oxygen content in the furnace adopts a three - level linkage. Real - time monitor data through the oxygen probe, and trigger the nitrogen curtain jet, the adjustment of the air - fuel ratio of the radiant tube combustion, and the opening compensation of the furnace micro - positive pressure control valve in sequence. Among them, the nitrogen injection flow rate V = 0.5×LT×(50 - PY) / 30, where LT is the furnace volume flow rate and PY is the real - time oxygen content ppm value.

[0027] Preferably, according to the real - time detection data of the online thickness gauge, dynamically adjust the rolling mill reduction rate, specifically including:

[0028] Obtain the rolling mill reduction rate XR through the formula XR=(0.0032×S + 0.015×TW)×(1 + 0.02×ΔA), where S is the current shot peening intensity feedback value, TW is the average temperature of the soaking section, and ΔA is the activation index fluctuation range. The response time of the reduction rate adjustment is ≤0.8 seconds, and it is synchronized with the sampling frequency of the thickness gauge at a ratio of 1:3.

[0029] A normalizing and pickling equipment for new - energy steel grades includes:

[0030] A shot peening control module, a pickling control module, a temperature field adjustment module, and a rolling mill coordination module;

[0031] The shot peening control module is equipped with a weighing sensor, a laser rangefinder, a pressure transmitter, and a fuzzy PID controller, and is used to dynamically adjust the steel shot throwing amount, the projection angle, and the working pressure;

[0032] The pickling control module is built - in with a PID temperature controller, a conductivity sensor, and a hydrochloric acid metering pump, and jointly adjusts the acid solution temperature and concentration;

[0033] The temperature field adjustment module includes a sub - temperature zone heating system, an oxygen content monitoring device, and a nitrogen injection mechanism, and is used for furnace temperature gradient control and oxygen content;

[0034] The rolling mill coordination module integrates an online thickness gauge and a reduction rate servo controller, and interlocks and responds to the shot peening intensity, the furnace temperature, and the acid solution activation index signals; forming a process parameter interlock control system.

[0035] The beneficial effects of the present invention are as follows:

[0036] 1. The present invention describes a normalizing pickling process and equipment for new energy steel grades, enhancing product quality stability through multi-parameter coordinated control. By integrating a dynamic shot blasting intensity adjustment model with a closed-loop pickling compensation mechanism, it enables real-time, precise control of key parameters such as shot delivery and acid activation index. Combined with normalizing furnace temperature gradient reconstruction and three-level linkage control of oxygen content, this effectively eliminates residual surface oxide scale, improves the steel's grain size by 1-2 grades, and reduces the yield strength fluctuation range of the product from ±35 MPa in conventional processes to ±15 MPa.

[0037] 2. The new energy steel normalizing pickling process and equipment described in this invention optimize both process efficiency and energy consumption. With the mill speed increased to 150 m / min, a 0.8-second dynamic response is achieved through linear matching of rolling reduction, activation index, and temperature field. Combined with nitrogen curtain injection control in the normalizing furnace, this reduces unit energy consumption, improves the overall yield rate of the production line, and reduces acid consumption per ton of steel.

[0038] 3. The normalized pickling process and equipment for new energy steel grades described in this invention enhance process reliability through an intelligent closed-loop system. A detection network consisting of high-precision load cells, laser rangefinders, and online conductivity sensors is constructed. A fuzzy PID controller implements parameter interlocking between shot flow rate, acid solution temperature, and rolling mill reduction. This shortens the response time for self-diagnosis of process anomalies, reduces equipment failure rates, and improves process stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The present invention will be further described below with reference to the accompanying drawings.

[0040] Figure 1 This is a method flow chart of a normalized pickling process for new energy steel grades according to the present invention;

[0041] Figure 2 This is a system principle block diagram of a new energy steel normalizing pickling process according to the present invention. DETAILED DESCRIPTION

[0042] 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.

[0043] Example 1

[0044] like Figure 1 As shown, a new energy steel normalizing pickling process according to an embodiment of the present invention includes:

[0045] Dynamic control of shot blasting machine parameters: real-time collection of shot blasting machine parameters such as shot throwing amount, projectile angle and working pressure, establishment of dynamic adjustment model based on shot blasting intensity feedback value, and generation of control instructions;

[0046] Intelligent Optimization of Pickling Process: In response to a control instruction, the acid solution temperature is synchronously increased to 75°C and the hydrochloric acid concentration is increased to 12 wt% through a PID controller, and a closed-loop compensation mechanism is established based on an online conductivity sensor to keep the activation index of the acid solution within a fluctuation range of 0.85;

[0047] Reconstruction of Normalizing Furnace Temperature Field: Under the condition that the rolling mill speed is increased to 120 m / min, the temperature gradient in the soaking section of the normalizing furnace is adjusted to 850°C in the front zone, 900°C in the middle zone, and 830°C in the rear zone. At the same time, the oxygen content in the furnace is controlled to be ≤50 ppm, and the holding time is extended by 15%;

[0048] Coordinated Matching of Rolling Parameters: According to the real-time detection data of the online thickness gauge, the rolling mill reduction rate is dynamically adjusted to maintain a linear correspondence with the pickling activation index and the normalizing furnace temperature field, forming an interlocking control system for process parameters.

[0049] Example 2

[0050] A normalizing and pickling process for new energy steel grades, including

[0051] Dynamic Regulation of Shot Blasting Machine Parameters: The steel shot throwing amount, projection angle, and working pressure parameters of the shot blasting machine are collected in real time. A dynamic adjustment model is established based on the shot blasting intensity feedback value to generate control instructions;

[0052] Intelligent Optimization of Pickling Process: In response to a control instruction, the acid solution temperature is synchronously increased to 85°C and the hydrochloric acid concentration is increased to 18 wt% through a PID controller, and a closed-loop compensation mechanism is established based on an online conductivity sensor to keep the activation index of the acid solution within a fluctuation range of 1.15;

[0053] Reconstruction of Normalizing Furnace Temperature Field: Under the condition that the rolling mill speed is increased to 150 m / min, the temperature gradient in the soaking section of the normalizing furnace is adjusted to 880°C in the front zone, 920°C in the middle zone, and 850°C in the rear zone. At the same time, the oxygen content in the furnace is controlled to be ≤50 ppm, and the holding time is extended by 25%;

[0054] Coordinated Matching of Rolling Parameters: According to the real-time detection data of the online thickness gauge, the rolling mill reduction rate is dynamically adjusted to maintain a linear correspondence with the pickling activation index and the normalizing furnace temperature field, forming an interlocking control system for process parameters.

[0055] The steel shot throwing amount, projection angle, and working pressure parameters of the shot blasting machine are collected in real time, specifically:

[0056] A high-precision weighing sensor is installed at the outlet of the shot blasting machine to record the steel shot flow rate in real time to obtain the current steel shot throwing amount Q; the angle between the directional sleeve and the workpiece is measured by the linkage of a laser rangefinder and an encoder to obtain the current projection angle J, and a pressure transmitter is installed in the pneumatic pipeline of the shot blasting machine to collect the compressed air pressure value to obtain the current working pressure Y.

[0057] The shot peening intensity feedback value S under the current working conditions is calculated through the current steel shot throwing amount Q, the current projection angle J, and the current working pressure Y;

[0058]

[0059] where D is the average particle size of the steel shot, and K is the equipment status correction coefficient; the equipment status correction coefficient is obtained by fitting historical data.

[0060] The dynamic adjustment model is a fuzzy PID control model, the input parameters include the shot peening intensity deviation value, and the output parameters are the steel shot flow compensation amount, the projection angle adjustment amount, and the working pressure correction amount.

[0061] The shot peening intensity deviation value is the difference SP between the current shot peening intensity feedback value and the standard shot peening intensity feedback value. (The standard shot peening intensity feedback value is set by those skilled in the art according to historical experience)

[0062] The control instructions include a first-level adjustment instruction and a second-level adjustment instruction, specifically:

[0063] When 0.02 ≤ SP < 0.05, a first-level adjustment instruction is generated;

[0064] The steel shot flow compensation amount is ΔQ = ±(0.1 × SP) × Q0; where Q0 is the reference throwing amount;

[0065] The projection angle adjustment step is ΔJ = ±0.5°;

[0066] When 0.05 ≤ SP, a second-level adjustment instruction is generated;

[0067] The working pressure correction amount is ΔY = ±(0.02 × SP) × Y0; where Y0 is the reference pressure.

[0068] In one embodiment, a closed-loop compensation mechanism is established based on an on-line conductivity sensor, specifically:

[0069] The acid solution ion mobility data is collected by the conductivity sensor every 30 seconds. When the activation index deviates from the range of 0.85 - 1.15, the fuzzy PID controller is triggered to output a compensation signal to the heating coil and the concentrated hydrochloric acid metering pump to adjust the temperature value and the hydrochloric acid concentration value.

[0070] Specifically, the activation index A is a standardized activity parameter calculated by combining the acid solution ion mobility data measured by the conductivity sensor with temperature compensation, and the activation index A is calculated through the formula where K 实测 is the acid solution conductivity value after temperature compensation, and K 基准 is the target conductivity reference value (such as the standard value corresponding to a hydrochloric acid concentration of 15 wt%).

[0071] The temperature compensation method is to convert the measured value into the conductivity K at the standard temperature of 25°C according to the characteristic that the conductivity changes with temperature. 25 , where Kt is the measured conductivity at t°C; β is the temperature correction coefficient (usually taken as 0.02 for hydrochloric acid solution);

[0072] (1) Data acquisition and calibration

[0073] Collect the conductivity (±1% accuracy) and temperature value of the acid solution through the conductivity sensor every 30 seconds;

[0074] The sensor needs to be calibrated regularly: use a 1413 μS / cm standard solution to calibrate the electrode constant and ensure that the sensor is clean and free of bubbles.

[0075] (2) Temperature compensation and activation index calculation

[0076] Compensate the real-time conductivity value to K under the condition of 25°C according to the above formula 25 , and use the reference conductivity K 基准 (such as 2000 μS / cm) corresponding to the target hydrochloric acid concentration (such as 15 wt%) as the denominator to calculate the A value.

[0077] (3) Conditions for triggering fuzzy PID control

[0078] When A < 0.85 or A > 1.15, it is determined that the activity of the acid solution is abnormal:

[0079] A is too low (insufficient ion concentration): Trigger the heating coil to increase the temperature (such as increasing by 2 - 5°C) and increase the injection amount of concentrated hydrochloric acid (such as +5% - 10% flow rate);

[0080] A is too high (excessive ion concentration): Reduce the temperature and the injection amount of hydrochloric acid.

[0081] (4) Closed-loop compensation mechanism

[0082] The fuzzy PID controller dynamically adjusts the output signal according to the deviation amplitude:

[0083] Temperature compensation signal: Adjust the power of the heating coil (such as ±5 kW);

[0084] Concentration compensation signal: Control the flow rate of the metering pump (such as ±3 L / min).

[0085] In one embodiment, the control of the oxygen content in the furnace adopts a three - level linkage. By monitoring the real - time data through an oxygen probe, it triggers the injection of the nitrogen curtain, the adjustment of the air - fuel ratio of the radiant tube combustion, and the opening compensation of the furnace micro - positive pressure control valve in sequence. Among them, the nitrogen injection flow rate V = 0.5×LT×(50 - PY) / 30, where LT is the furnace volume flow rate and PY is the real - time oxygen content in ppm value.

[0086] According to the real - time detection data of the online thickness gauge, the rolling mill reduction rate is dynamically adjusted, specifically including:

[0087] The rolling mill reduction rate XR is obtained through the formula XR=(0.0032×S + 0.015×TW)×(1 + 0.02×ΔA), where S is the current shot peening intensity feedback value, TW is the average temperature of the soaking section, and ΔA is the activation index fluctuation range. The response time of the reduction rate adjustment is ≤0.8 seconds, and it is synchronized with the sampling frequency of the thickness gauge at a ratio of 1:3.

[0088] Specifically, the activation index fluctuation range ΔA can be obtained by selecting the A - value sequence of 10 consecutive sampling periods (i.e., 5 minutes) and calculating the range between its maximum value and minimum value as ΔA.

[0089] Embodiment Three

[0090] As Figure 2 shown, by comparing Embodiment One and Embodiment Two, another implementation manner of the present invention is:

[0091] A normalizing and pickling equipment for new - energy steel grades, including:

[0092] A shot peening control module, a pickling control module, a temperature field adjustment module, and a rolling mill coordination module;

[0093] The shot peening control module is equipped with a weighing sensor, a laser rangefinder, a pressure transmitter, and a fuzzy PID controller, and is used to dynamically adjust the steel shot throwing amount, the shot peening angle, and the working pressure;

[0094] The pickling control module is built - in with a PID temperature controller, a conductivity sensor, and a hydrochloric acid metering pump, and jointly adjusts the acid solution temperature and concentration;

[0095] The temperature field adjustment module includes a sub - temperature - zone heating system, an oxygen content monitoring device, and a nitrogen injection mechanism, and is used for furnace temperature gradient control and oxygen content;

[0096] The rolling mill coordination module integrates an online thickness gauge and a reduction rate servo controller, and interlocks and responds with the shot peening intensity, furnace temperature, and acid solution activation index signals; forming a process parameter interlock control system.

[0097] The foregoing has shown and described the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments, and what is described in the above embodiments and the specification is only to illustrate the principle of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements fall within the scope of the present invention claimed. The scope of the present invention claimed is defined by the appended claims and their equivalents.

Claims

1. A normalizing and pickling process for a new energy steel grade, characterized in that: Including Dynamic regulation of shot blasting machine parameters: Real-time collection of shot blasting machine parameters such as shot throwing amount, projection angle, and working pressure. Based on the shot blasting intensity feedback value, a dynamic adjustment model is established to generate control instructions; Intelligent optimization of pickling process: In response to the control instructions, the acid solution temperature is synchronously increased to 75 - 85 °C and the hydrochloric acid concentration is increased to 12 - 18 wt% through a PID controller. A closed-loop compensation mechanism is established based on an online conductivity sensor to keep the activation index of the acid solution fluctuating within the range of 0.85 - 1.15; Reconstruction of normalizing furnace temperature field: Under the condition that the rolling mill speed is increased to 120 - 150 m / min, the temperature gradient of the soaking section of the normalizing furnace is adjusted to 850 - 880 °C in the front zone, 900 - 920 °C in the middle zone, and 830 - 850 °C in the rear zone. At the same time, the oxygen content in the furnace is controlled ≤ 50 ppm, and the holding time is extended by 15 - 25%; Coordinated matching of rolling parameters: According to the real-time detection data of the online thickness gauge, the rolling mill reduction rate is dynamically adjusted to maintain a linear correspondence with the pickling activation index and the normalizing furnace temperature field, forming a process parameter interlock control system.

2. The normalizing and pickling process for a new energy steel grade according to claim 1, characterized in that: Real-time collection of shot blasting machine parameters such as shot throwing amount, projection angle, and working pressure, specifically: Install a high-precision weighing sensor at the outlet of the shot blasting machine to record the shot flow rate in real time to obtain the current shot throwing amount Q; Through the linkage of a laser rangefinder and an encoder, measure the angle between the orientation sleeve and the workpiece to obtain the current projection angle J. Install a pressure transmitter on the pneumatic pipeline of the shot blasting machine to collect the compressed air pressure value to obtain the current working pressure Y.

3. The normalizing and pickling process for a new energy steel grade according to claim 2, characterized in that: Calculate the shot blasting intensity feedback value S under the current working condition through the current shot throwing amount Q, the current projection angle J, and the current working pressure Y; where D is the average particle size of the shot, and K is the equipment state correction coefficient; The equipment state correction coefficient is obtained by fitting historical data.

4. A normalizing and pickling process for a new energy steel grade according to claim 1, characterized in that: The dynamic adjustment model is a fuzzy PID control model. The input parameters include the shot blasting intensity deviation value, and the output parameters are the shot flow compensation amount, the projection angle adjustment amount, and the working pressure correction amount.

5. A normalizing and pickling process for a new energy steel grade according to claim 1, characterized in that: The shot blasting intensity deviation value is the difference SP between the current shot blasting intensity feedback value and the standard shot blasting intensity feedback value.

6. The normalized pickling process for a new energy steel grade according to claim 5, characterized in that: The control instructions include primary adjustment instructions and secondary adjustment instructions, specifically: When 0.02 ≤ SP < 0.05, generate primary adjustment instructions; The shot flow compensation amount is ΔQ = ±(0.1 × SP) × Q0; where Q0 is the reference throwing amount; The projection angle adjustment step is ΔJ = ±0.5 °; When 0.05 ≤ SP, generate secondary adjustment instructions; The working pressure correction amount is ΔY = ±(0.02 × SP) × Y0; where Y0 is the reference pressure.

7. A normalizing and pickling process for a new energy steel grade according to claim 3, characterized in that: Establish a closed-loop compensation mechanism based on an online conductivity sensor, specifically: Collect the acid solution ion mobility data every 30 seconds through the conductivity sensor. When the activation index deviates from the range of 0.85 - 1.15, trigger the fuzzy PID controller to output a compensation signal to the heating coil and the concentrated hydrochloric acid metering pump to adjust the temperature value and the hydrochloric acid concentration value.

8. A normalizing and pickling process for a new energy steel grade according to claim 1, characterized in that: The oxygen content control in the furnace adopts three - level linkage. By using the oxygen probe to monitor the real - time data, it triggers the nitrogen curtain injection, the adjustment of the air - fuel ratio of the radiant tube combustion, and the opening compensation of the furnace micro - positive pressure control valve in sequence. The nitrogen injection flow rate V = 0.5×LT×(50 - PY) / 30, where LT is the furnace volume flow rate and PY is the real - time oxygen content value in ppm.

9. A normalizing and pickling process for a new energy steel grade according to claim 4, characterized in that: According to the real - time detection data of the online thickness gauge, dynamically adjust the rolling reduction rate of the rolling mill, specifically including: The rolling reduction rate XR is obtained through the formula XR=(0.0032×S + 0.015×TW)×(1 + 0.02×ΔA), where S is the current feedback value of the shot peening intensity, TW is the average temperature in the soaking section, and ΔA is the fluctuation range of the activation index. The response time of the rolling reduction rate adjustment is ≤0.8 seconds, and it is synchronized with the sampling frequency of the thickness gauge at a ratio of 1:

3.

10. A normalizing and pickling equipment for new energy steel grades, which is applied to the normalizing and pickling process for new energy steel grades described in claim 1, and is characterized in that: Including: A shot peening control module, a pickling control module, a temperature field adjustment module, and a rolling mill coordination module; The shot peening control module is equipped with a weighing sensor, a laser rangefinder, a pressure transmitter, and a fuzzy PID controller, which are used to dynamically adjust the steel shot throwing amount, the projection angle, and the working pressure; The pickling control module is internally provided with a PID temperature controller, a conductivity sensor, and a hydrochloric acid metering pump, which are used to jointly adjust the temperature and concentration of the acid solution; The temperature field adjustment module includes a sub - temperature - zone heating system, an oxygen content monitoring device, and a nitrogen injection mechanism, which are used for furnace temperature gradient control and oxygen content control; The rolling mill coordination module integrates an online thickness gauge and a rolling reduction rate servo controller, and has an interlocking response with the shot peening intensity, the furnace temperature, and the acid solution activation index signals; Form a process parameter interlocking control system.

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