Methods to improve the surface cleanliness of stainless steel by optimizing the final rinse water quality and spraying method

Abstract

This invention belongs to the field of metal surface treatment, specifically disclosing a method for improving the surface cleanliness of stainless steel by optimizing the final rinse water quality and spraying method. It aims to solve the problems of uneven cleanliness and stains caused by water quality fluctuations during stainless steel cleaning. The method includes: establishing a multi-dimensional water quality monitoring system, using a sensor array to collect conductivity and particle count values; dynamically controlling the purification process based on feedback-driven ion exchange and ultrafiltration components; constructing a hydrodynamic model of the spray field through operating parameters and calculating the spray parameter matrix; controlling the array nozzles to perform multi-degree-of-freedom variable frequency spraying, adjusting height and angle to achieve edge enhancement; and using online residual detection to perform feedback compensation and establishing a correlation function to correct the spray pressure. Through the above scheme, this invention achieves the linkage of ion-level purification and precise spraying, significantly improving surface reflectivity, eliminating cleaning dead zones, and reducing production energy consumption.

Description

Technical Field

[0001] This invention belongs to the field of metal surface treatment, and specifically relates to a method for improving the cleanliness of stainless steel surfaces by optimizing the final rinse water quality and spraying method. Background Technology

[0002] With the continuous advancement of stainless steel manufacturing processes, its applications in aerospace, medical devices, high-end home appliances, and precision instruments are becoming increasingly widespread, leading to higher requirements for material surface quality and cleanliness. Stainless steel surface treatment, as a crucial step in the production process, directly affects the product's corrosion resistance, aesthetic appearance, and subsequent coating effects. In modern industrial continuous production lines, removing residual oil, pickling solutions, and minute metal debris from the steel strip surface through multiple cleaning and rinsing processes is a core step in ensuring the final surface quality of the product.

[0003] The final rinse process, as the last critical step before the stainless steel strip leaves the cleaning section, aims to use a spray medium to thoroughly purify the surface, ensuring that any foreign matter residue is completely removed before the material enters the drying zone. This process involves the coordinated control of spray pressure, flow distribution, and water quality chemical parameters. It aims to achieve deep removal of micron-sized particles and chemical ions through a combination of physical rinsing and chemical dissolution, thereby imparting extremely high physical and chemical cleanliness to the stainless steel surface.

[0004] However, traditional final rinse systems lack dynamic management methods for water quality, making it difficult to accurately control conductivity, ion concentration, and microbial content in the water. This results in mineral residues or oxidation spots easily forming on stainless steel surfaces after drying. Simultaneously, conventional spray devices have relatively fixed nozzle arrangements, and the adjustment precision of spray pressure and flow rate is insufficient. They cannot dynamically adjust the flow field distribution according to the real-time specifications and operating speed of the steel belt, leading to cleaning dead zones at the edges of the steel belt or in specific micro-areas, severely affecting the uniformity of overall cleanliness. Furthermore, existing processes lack a linkage optimization mechanism between water quality parameters and spray execution parameters, making it difficult to simultaneously meet high cleanliness standards and ensure efficient water resource utilization. This results in production stability and product consistency that are difficult to achieve ideal levels.

[0005] Therefore, a method is desired to improve the surface cleanliness of stainless steel by optimizing the final rinse water quality and the spraying method. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to overcome the problems of mineral residue and stains on the surface of stainless steel caused by the lack of water quality management methods in the final rinse process in the prior art, as well as the problem of cleaning dead angles caused by insufficient adjustment precision of the spray device, and to provide a method to improve the cleanliness of stainless steel surface by optimizing the final rinse water quality and spraying method.

[0007] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A method for improving the surface cleanliness of stainless steel by optimizing the final rinse water quality and spraying method, characterized by comprising the following steps: Step 1: Use an online sensor array to collect the conductivity, total dissolved solids concentration, chloride ion concentration, silicate content and solid particle count in the final shower water in real time, and transmit them to the integrated water quality treatment terminal. Step 2: Based on the feedback from the integrated water treatment terminal, drive the multi-stage ion exchange unit and ultrafiltration membrane module to purify the final shower water, control the conductivity of the final shower water to be stable below the first preset conductivity threshold, and control the chloride ion concentration to be lower than the preset concentration threshold. Step 3: Collect the running speed of the stainless steel strip, the strip width, and the thickness of the residual liquid film from the previous process, and input them into the fluid calculation model to calculate the critical spray pressure parameters and flow distribution matrix; Step 4: Based on the calculated critical spray pressure parameters and flow distribution matrix, control the spray pressure and flow of multiple array nozzles located above the stainless steel strip, and adjust the vertical height and tilt angle of the nozzles to achieve non-uniform impact strengthening of the strip surface and edge area. Step 5: Use an online surface residue detection device to obtain the mineral residue distribution on the dried stainless steel surface, establish a correlation function between residue density and spray control parameters, and correct the spray pressure parameters based on this function.

[0008] Preferably, in step 1, the online sensing array includes a four-electrode conductivity sensor with a measurement range covering a predetermined conductivity range and a preset measurement accuracy. The sensor integrates a temperature compensation circuit to automatically calibrate the measured values ​​to a preset standard ambient temperature. The chloride ion monitoring employs an ion-selective electrode method, has a preset detection cycle, and the detection limit meets a preset concentration standard. The solid particle count is obtained through laser scattering, enabling statistical analysis of particle distribution across different particle size ranges within a predetermined volume of sample.

[0009] Preferably, in step 2, the multi-stage ion exchange unit includes a cation exchange bed, an anion exchange bed, and a mixed ion exchange bed. The cation exchange bed is filled with a strongly acidic styrene-based resin to remove calcium, magnesium, and sodium metal ions from the water. The anion exchange bed is filled with a strongly basic anion exchange resin to remove chloride, sulfate, and silicate ions. The cation and anion exchange resins in the mixed ion exchange bed have a predetermined volume ratio to ensure that the conductivity of the effluent is always lower than a second preset conductivity threshold.

[0010] Preferably, in step 2, the ultrafiltration membrane module uses a hollow fiber membrane made of polyethersulfone with a preset molecular weight cutoff. The operating pressure of the ultrafiltration membrane is controlled within a preset pressure range, and the flux decay rate is set below a preset change rate threshold. By performing backwashing and chemical cleaning procedures at regular intervals, the suspended solids content of the ultrafiltration effluent meets the predetermined purity standard, effectively preventing the residue of tiny particles on the stainless steel surface due to water quality fluctuations.

[0011] Preferably, in step 3, the collection range of the stainless steel strip's running speed covers a predetermined speed range, and a preset measurement accuracy is achieved using a laser Doppler velocimeter. The measurement of the residual liquid film thickness from the preceding process is performed using infrared absorption, with measurement points distributed at the center of the strip width and at predetermined distances from the edge, providing data support for subsequent non-uniform spraying.

[0012] Preferably, in step 3, the calculation process of the critical spray pressure and flow distribution matrix involves solving discrete forms of the mass conservation equation and momentum conservation equation. By introducing a strip surface roughness correction factor, the expansion coefficient of the water flow on the stainless steel surface is calculated. The value of the correction factor is within a preset range and depends on different surface finishing grades. The calculated spray pressure is within a preset spray pressure range.

[0013] Preferably, in step 4, the array nozzles adopt a fan-shaped structure with a preset spray angle. Each array includes a predetermined number of nozzles, and the overlap rate between adjacent nozzles is within a preset overlap range to eliminate spray dead zones. The multi-degree-of-freedom variable frequency spraying process adjusts the speed of the high-pressure plunger pump through an AC frequency converter to achieve a preset pressure regulation accuracy.

[0014] Preferably, in step 4, the vertical height adjustment range of the nozzle is within a predetermined height range. For the edge area of ​​the stainless steel strip, a servo motor drives the edge-specific nozzle to tilt inward at a preset angle, increasing the shearing force in the edge area and ensuring that there are no yellow spots caused by pickling residue on the edge of the strip.

[0015] Preferably, in step 5, the online surface residue detection device utilizes multispectral imaging technology. By identifying the characteristic peak intensity of the reflectance spectrum of the stainless steel surface, the surface density of sodium and chloride ions is calculated. The correlation function is fitted using the least squares method. When the surface residue density exceeds a preset density threshold, the system automatically increases the spray pressure and flow rate of the corresponding area in step 4, with the increase conforming to a preset ratio.

[0016] Preferably, the method further includes precise control of the temperature of the final spray water. A plate heat exchanger is used to maintain the water temperature within a preset temperature range. Higher water temperatures not only help increase the solubility of chemical ions but also reduce the viscosity of the water, thereby achieving higher impact kinetic energy under the same pressure and further enhancing the physical scouring effect.

[0017] Preferably, the method employs differentiated strategies for different grades of stainless steel during operation. For specific series of austenitic stainless steel, the focus is on controlling electrical conductivity and particle size; for specific series of ferritic stainless steel, the monitoring weight of chloride ion concentration is increased, and the chloride ion concentration threshold is lowered according to process requirements to prevent the risk of stress corrosion cracking.

[0018] Preferably, the method also integrates a wastewater recovery and closed-loop circulation system. The final leaching wastewater is deeply treated using a reverse osmosis membrane module, achieving a product water recovery rate of a predetermined percentage. The recovered product water is returned to the storage tank from step 1, and the system balances water loss by adding high-purity deionized water, achieving extremely low water consumption.

[0019] Preferably, the array nozzles are made of 316L stainless steel or hard alloy to resist erosion and wear during high-pressure spraying. The nozzles are internally designed with spiral flow channels to generate high-frequency pulsed water flow. The pulse frequency switches within a preset frequency range, enhancing the ability to remove micron-sized metal debris.

[0020] Preferably, step 4 further includes an air knife cleaning auxiliary process. A high-pressure clean air purging device is installed at the outlet of the final spray section, with the air pressure within a preset range. The air knife forms a preset angle with the strip's running direction, forcing the residual water film on the strip surface to flow backward, thus cooperating with the subsequent drying process to prevent dry spots caused by uneven moisture evaporation.

[0021] Preferably, the method achieves fully automated control of the entire process through a programmable logic controller (PLC). The system's sampling period is set to a preset time interval to ensure real-time response to fluctuations in the strip steel's running speed. All monitoring parameters and control variables are recorded in an industrial database, supporting historical trajectory backtracking within a predetermined time period and providing support for stainless steel quality traceability.

[0022] Compared with the prior art, the present invention has the following beneficial effects: 1. Significantly improved surface cleanliness, achieving a technological breakthrough in ion-level purification: By real-time online monitoring of conductivity and ion concentration and linking multiple ion exchange units, the final rinse water quality is raised to the preset cleanliness standard. The mineral residue density on the stainless steel surface is reduced to below the preset density threshold, effectively eliminating drying spots and oxidation marks common in traditional processes, and significantly improving surface reflectivity. Elimination of cleaning dead zones and blind spots: The multi-degree-of-freedom variable frequency spray process combined with an edge-enhanced rinsing strategy solves the problem of uneven flow field distribution at the edges of the strip steel and under high-speed operation. The uniformity of cleanliness across the entire width range is greatly improved, ensuring the product's compliance in high-end applications.

[0023] 2. Extremely high production stability and consistency: A dynamic feedback mechanism based on fluid dynamics has been established. By constructing a spray field model and combining it with online surface residue detection, a shift from passive cleaning to active and precise purification has been achieved. The system can automatically adjust the spraying scheme according to the strip steel specifications and initial contamination level, ensuring high consistency in cleanliness indicators for different batches and specifications of stainless steel products, significantly improving the production yield. Enhanced adaptability to complex working conditions: Targeted process parameter matrices have been developed for different grades and roughnesses of stainless steel, effectively addressing the pressure of water quality contamination caused by fluctuations in previous processes, and ensuring reliable operation of the final rinsing process on a high-speed continuous production line.

[0024] 3. Superior resource utilization efficiency and environmental performance enable highly efficient water recycling: The integrated reverse osmosis recovery system ensures that the final spray water recovery rate reaches the predetermined target, significantly reducing the consumption of high-purity deionized water. Compared to traditional direct-flow cleaning processes, water consumption per unit area of ​​stainless steel production is significantly reduced. Precise optimization of energy consumption: Through frequency conversion control technology and targeted nozzle angle adjustment, energy waste caused by blindly increasing pump pressure is avoided while ensuring cleaning effectiveness. The overall system energy consumption is significantly reduced, aligning with the development trend of modern green manufacturing.

[0025] 4. Intelligent monitoring and quality traceability capabilities enable end-to-end digital management: By integrating sensor arrays and an industrial database, precise recording of water quality and spraying parameters is achieved for each roll of stainless steel during production. The system's automatic alarm and parameter correction functions significantly reduce the need for manual intervention and enhance the automation level of the production line. Simultaneously, it provides detailed data support for subsequent corrosion resistance evaluation and failure analysis of products. (See attached diagram) Figure 1 This is a schematic diagram of the overall architecture of the method proposed in this invention for improving the surface cleanliness of stainless steel by optimizing the final rinse water quality and spraying method; Figure 2This is a flowchart illustrating the logical flow of the present invention, which utilizes an online sensor array to collect water quality parameters in real time and drives a multi-stage ion exchange and ultrafiltration membrane assembly to dynamically regulate water quality. Figure 3 This is a flowchart illustrating the logical flow of the present invention, which involves performing multi-degree-of-freedom variable frequency spraying based on the calculated critical spray pressure and flow distribution matrix and using multispectral imaging for surface cleanliness feedback compensation. Figure 4 This is a schematic diagram of the core principle framework of the present invention based on multi-dimensional monitoring of final shower water quality, hydrodynamic modeling of the spray field, and feedback compensation for surface residue detection. Detailed Implementation Example 1 To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0026] In methods for improving the surface cleanliness of stainless steel by optimizing the final rinse water quality and spraying method, the execution of the process strictly relies on a technical closed loop (such as high-precision sensing, dynamic water quality control, fluid dynamics modeling, and closed-loop feedback compensation). Figure 1 (As shown). The specific implementation process of this embodiment is described in detail below: like Figure 2 As shown, Step 1: Establish a multi-dimensional monitoring system for the final shower water quality. Utilize an online sensor array to collect real-time data on conductivity, total dissolved solids concentration, chloride ion concentration, silicate content, and the count of solid particles larger than a predetermined size in the final shower water, and simultaneously transmit this data to the integrated water treatment terminal.

[0027] In this step, an online sensor array is deployed at the outlet pipe of the final shower tank and the inlet of the spray pump to ensure that the collected data reflects the immediate water quality status before entering the spraying process. The online sensor array includes a four-electrode conductivity sensor. This sensor employs constant current source driving technology, using four platinum electrodes to construct the current and voltage sensing fields, effectively eliminating the interference of electrode polarization effects and cable resistance on the measurement results. Its measurement range covers… to The measurement accuracy reaches full scale. Within [the specified range]. The sensor integrates a temperature compensation circuit and uses a Pt1000 platinum resistance thermometer as the temperature sensing element. Through a built-in compensation algorithm, the measured value is automatically calibrated to a standard ambient temperature of 25 degrees Celsius, ensuring the comparability of water conductivity data under different seasons and operating conditions.

[0028] The chloride ion monitoring employs an ion-selective electrode method. Specifically, a highly selective chloride ion-sensitive membrane electrode is selected, in conjunction with a saturated calomel electrode as a reference electrode. The system is set with a preset detection cycle, for example, performing automatic online sampling and potential measurement every 300 seconds. By measuring the logarithmic relationship between electrode potential and chloride ion activity, the mass concentration of chloride ions is calculated. Its detection limit reaches [value missing]. It meets the stringent requirements of extremely low chloride ion levels for the surface cleanliness of high-quality stainless steel.

[0029] The solid particle count is obtained through laser scattering. The laser particle size analyzer module is integrated into the sensor array. When circulating water flows through the sampling flow cell, the wavelength is... The system uses a laser beam to irradiate particles, generating scattered light, which is received by a polygonal photodetector. Utilizing the Mie scattering theory model, the system can statistically analyze the particle distribution across different size ranges in a 100 ml sample in real time, covering the number of particles from 1 micrometer to 50 micrometers. This data provides direct evidence for subsequent operational load assessment of the ultrafiltration membrane module.

[0030] The integrated water quality treatment terminal uses an industrial-grade embedded processor to receive digital signals from the sensor array via Modbus RTU or Profinet protocols. The terminal internally runs a real-time data smoothing and filtering algorithm to eliminate random noise caused by water flow fluctuations, forming a stable time-series sequence of water quality parameters.

[0031] Step 2: Dynamically control the final shower water purification process. Based on feedback from the integrated water treatment terminal, drive the multi-stage ion exchange unit and ultrafiltration membrane module to purify the circulating water, so that the conductivity of the final shower water is stabilized below the first preset conductivity threshold (e.g., 0.5 μS / cm), and the chloride ion concentration is less than the preset concentration threshold.

[0032] In this embodiment, the multi-stage ion exchange unit is configured sequentially along the water flow direction, including a cation exchange bed, an anion exchange bed, and a mixed ion exchange bed. The cation exchange bed is filled with a strong acidic styrene-based resin (e.g., 001x7 resin), which has extremely high exchange capacity and mechanical strength, used to remove metal cations such as calcium, magnesium, sodium, and potassium from the water. The anion exchange bed is filled with a strong basic anion exchange resin (e.g., 201x7 resin), which has a well-developed porous structure, specifically designed to remove anions such as chloride, sulfate, and silicate. The mixed ion exchange bed contains uniformly packed cation and anion resins at a volume ratio of 1:2. The mixed bed serves as a deep purification stage, ensuring that the conductivity of the effluent remains consistently below a certain level. This is the second preset conductivity threshold. When the integrated water treatment terminal detects that the effluent parameters are close to the set threshold, it automatically triggers the resin regeneration program, precisely injecting regeneration solution through an acid-base metering pump to restore the resin's exchange capacity.

[0033] The ultrafiltration membrane module is deployed downstream of the ion exchange unit or in parallel in the circulation loop, and uses a hollow fiber membrane made of polyethersulfone with a preset molecular weight cutoff of 50,000 Daltons. This material has excellent hydrophilicity and resistance to chemical fouling. The operating pressure of the ultrafiltration membrane is controlled by a variable frequency water pump. to Within the preset pressure range. The system monitors the pressure difference across the membrane in real time and sets the flux decay rate to less than [a certain value] per hour. The system ensures that the suspended solids and colloidal silica content of the ultrafiltration water meet the predetermined purity standards by performing high-pressure pulse backwashing and specific chemical cleaning procedures (such as using citric acid or sodium hypochlorite solution) at regular intervals, effectively preventing the residue of tiny particles on the stainless steel surface due to water quality fluctuations.

[0034] Step 3: Construct a hydrodynamic model of the spray field. By collecting data on the running speed of the stainless steel strip, the strip width, and the thickness of the residual liquid film from the previous process, calculate the critical spray pressure and flow distribution matrix required to achieve full surface coverage cleaning.

[0035] The operating speed of the stainless steel strip is collected within a certain range. to The speed range is defined. A laser Doppler velocimeter is used for non-contact measurement, achieving a measurement accuracy of [insert accuracy here]. The above provides a high-frequency velocity input for calculating the dynamic evolution of the flow field. The strip width data is acquired in real time by an infrared scanning sensor at the inlet. The thickness of the residual liquid film from the preceding process is measured using infrared absorption, utilizing the attenuation characteristics of a specific wavelength (e.g., 1.94 micrometers) in the liquid film. Measurement points are distributed at the center of the strip width and near the edge. Place.

[0036] By introducing a surface roughness correction factor for strip steel, and based on the principles of mass conservation and momentum conservation, the critical spray pressure and flow distribution matrix required to achieve full surface coverage cleaning are calculated.

[0037] The fluid calculation model described in this invention aims to determine the critical spray pressure parameters and flow distribution matrix required for achieving full surface coverage cleaning, based on the collected data of the stainless steel strip's running speed, strip width, and residual liquid film thickness from the previous process. The core governing equations and solution process of this model are as follows: (a) Governing equations Assuming the sprayed fluid is an incompressible Newtonian fluid, its flow on the steel strip surface follows the laws of mass and momentum conservation. A two-dimensional steady-state boundary layer equation is used to describe this flow: mass conservation equation:

[0038] Momentum conservation equation (flow direction x):

[0039] in: , These are the velocity components (m / s) of the liquid film in the strip running direction (x) and perpendicular to the surface direction (y), respectively. The density of the spray water is (kg / m³, take 998 kg / m³, corresponding to 25℃). Let be the dynamic viscosity of water (Pa·s, taken as 0.89 × 10⁻⁶). - (³ Pa·s); The x-component of gravitational acceleration (m / s²) represents the acceleration due to gravity. The pressure inside the liquid film (Pa).

[0040] (ii) Boundary conditions At the surface of the strip (y=0): no-slip boundary condition. , .

[0041] The free surface of the liquid film (y=δ, where δ is the liquid film thickness): shear stress is continuous, and air resistance is negligible. .

[0042] At the inlet (x=0, nozzle impact zone): spray impact velocity With spray pressure The relationship is given by Bernoulli's equation in simplification:

[0043] in This is the nozzle velocity coefficient, with a value ranging from 0.85 to 0.95 (calibrated according to the nozzle model).

[0044] (iii) Surface roughness correction The microstructure of the strip surface affects the spreading resistance of the liquid film. A surface roughness correction factor is introduced. (Dimensionless) Correction to the wall shear stress in the momentum equation:

[0045] The value is based on the surface finish grade of the strip steel: BA (bright annealed) surface, , ; 2B (cold-rolled, annealed, and pickled) surface. , ; No.4 (belt grinding) surface, , .

[0046] (iv) Criteria for determining critical spray pressure Define the dimensionless liquid film coverage index :

[0047] in The average flow velocity of the liquid film is (m / s). The critical volumetric flow rate (m² / s) required per unit width. At that time, it was assumed that the liquid film could completely cover the surface of the strip steel, with no dry areas or missed areas.

[0048] For a given strip running speed Residual liquid film thickness (Based on actual measurements using infrared absorption method), the above boundary layer equations are solved iteratively to obtain the equations that satisfy... The minimum spray pressure is the critical spray pressure. .

[0049] (v) Calculation of the flow distribution matrix Discretize the strip width direction as follows One computing unit ( (Take a value of 10-20, corresponding to the number of array nozzles). For the first... Each unit, and the required spray flow rate per unit area. (L / (m²·s)) is calculated using the following formula:

[0050] in: This is a weighting factor in the width direction. For the center region (distance from the edge)... ), For edge regions (distance from the edge) Based on the measured distribution of the residual liquid film thickness in the preceding stage, Use a value of 1.2 to 1.5 to enhance edge scouring; For the first Critical spray pressure (MPa) obtained from unit calculations; Reference pressure (MPa, taken as 0.5 MPa); The pressure-flow index is calibrated based on nozzle characteristics and is typically taken as 0.5. The standard flow rate (L / (m²·s)) at the reference pressure is provided by the nozzle manufacturer or determined experimentally.

[0051] Each computing unit Combining these elements yields the flow distribution matrix. This matrix serves as the direct basis for controlling the flow distribution of the array nozzles in step 4.

[0052] (vi) Calculation example (taking 304 stainless steel with 2B surface as an example) Input parameters: strip running speed (Corresponding to 80 m / min); strip width ; Residual film thickness of the preceding process (Center), Edge ; Surface roughness correction factor (2B surface).

[0053] Solution results: Critical spray pressure in the central area ; Critical spray pressure in the edge area ; Flow distribution matrix (partial): Cell 1 (left edge) Unit 6 (Center) Unit 12 (right edge) .

[0054] The calculation results are sent from the PLC to the actuator, which drives the array nozzles to work with a non-uniform flow distribution to achieve enhanced spraying of the strip edge.

[0055] like Figure 3 As shown, step 4: Execute the multi-degree-of-freedom variable frequency spraying process. Based on the spraying pressure and flow distribution matrix, control multiple array nozzles located above the stainless steel strip to work in coordination, and adjust the vertical height and tilt angle of the nozzles to achieve non-uniform impact strengthening of the strip surface and edge areas.

[0056] The array nozzles are distributed on the upper and lower sides of the stainless steel strip, made of 316L stainless steel. Core wear-resistant components are made of hard alloy to resist erosion and wear during long-term high-pressure spraying. The nozzles have a fan-shaped structure with preset spray angles of 60 to 90 degrees. Each array includes 12 to 24 nozzles, with the overlap rate of the spray fan between adjacent nozzles set at... to Within the preset overlapping range, the spray dead zone is completely eliminated through spatial geometric misalignment.

[0057] The multi-degree-of-freedom variable frequency spraying process uses an AC frequency converter to adjust the speed of multiple parallel high-pressure plunger pumps to achieve a preset pressure regulation accuracy. The nozzle is designed with a spiral flow channel inside to generate a high-frequency pulsed water flow, with a pulse frequency of... to It can switch within a range to enhance its ability to peel off micron-sized metal debris.

[0058] The nozzle's vertical height adjustment range is located at to Within the specified height range, stepless adjustment is achieved via an electric actuator. For the edge area of ​​the stainless steel strip, a servo motor drives a dedicated edge nozzle to tilt inward at a preset angle of 15 to 30 degrees, increasing the shearing force in the edge area and ensuring that there are no yellow spots caused by pickling residue on the strip edge. This non-uniform impact strategy effectively compensates for the decrease in cleaning force caused by the dispersion of the edge flow field.

[0059] At the outlet of this step, an auxiliary air knife cleaning process is also included. A high-pressure clean air purging device is installed, with the air pressure at [insert pressure here]. to Within the specified range, the air knife forms a 45-degree angle with the strip's running direction, forcing the residual water film on the strip's surface to flow backward and detach from the strip's edge. This, combined with subsequent drying processes, prevents dry spots caused by uneven moisture evaporation.

[0060] like Figure 4 As shown, step 5: Surface cleanliness feedback compensation. An online surface residue detection device is used to obtain the mineral residue distribution on the dried stainless steel surface, establishing a correlation function between residue density and spray control parameters, and real-time correcting the spray pressure in step 4.

[0061] The online surface residue detection equipment utilizes multispectral imaging technology. A high-power LED light source array illuminates the steel strip surface, and a high-sensitivity CCD sensor identifies the characteristic peak intensities of the stainless steel surface reflectance spectrum. The system focuses on extracting characteristic wavelengths representing sodium ions, chloride ions, and trace salts, and calculates the surface density of the residues. The correlation function is fitted using the least squares method, and the calculation model is as follows:

[0062] in, For the sum of squared errors, To measure the density of the residue, The corresponding area's spray pressure, This refers to the spray flow rate. These are the coefficients to be fitted. By making... Minimize and solve to obtain the optimal control correction parameters. When the density of surface residue exceeds When the preset density threshold is reached, the system automatically increases the spray pressure and flow rate of the corresponding area in step 4, with the increase rate conforming to... to The preset ratio.

[0063] To further verify the effectiveness of the correlation function, this embodiment provides a specific example of least squares fitting under typical working conditions.

[0064] Experimental conditions: Stainless steel grade: 304 (2B surface); Strip running speed: 80 m / min; Final spray water temperature: 50±0.5℃; Water quality parameters: Conductivity ≤0.1 μS / cm, chloride ion concentration ≤0.02 mg / L; Number of sampling points: (Take 30 sampling points at equal intervals along the width of the strip) Measured data: at each sampling point Simultaneously record: Measured residue density (Unit: ng / cm², determined by XRF method, mainly chloride ions and trace salts) Spray pressure of the corresponding area (Unit: MPa) Sprinkler flow rate for the corresponding area (Unit: L / (m²·s)) Some of the original data is shown in the table below (the sampling points are numbered as equal division points in the width direction, from the left edge to the right edge):

[0065] Fitting process: The least squares method is used, with a linear model. Fit the above 30 sets of data. The objective function is:

[0066] By solving the normal equations with partial derivatives of zero, the optimal estimates of the coefficients to be fitted are obtained: (Coefficients are rounded to two decimal places; unit: when) In MPa In L / (m²·s) Timed in ng / cm² The unit is ng / (cm²·MPa). The unit is ng·s / (cm²·L). The unit is ng / cm².

[0067] Since the fitting is based on data within the normal process parameter range (P≥0.5MPa, F≥0.25 L / (m²·s)), D is always positive within this range. The negative intercept c is only a mathematical fitting result and does not represent a physical meaning.

[0068] Goodness-of-fit test: Coefficient of determination This indicates that the model can explain 96.3% of the residual density variation. Residual standard deviation. The concentration of ng / cm² is less than the preset threshold of 1.0 ng / cm². The p-values ​​of all coefficients are less than 0.001, indicating statistical significance.

[0069] Model Validation: Ten validation points (not included in the fitting) were independently collected under the same working conditions, and the measured residual density was compared with the model prediction.

[0070] The maximum absolute error is ≤ 0.5 ng / cm², and the relative error is ≤ 5%, which meets the engineering accuracy requirements.

[0071] Application example: When an online surface residue detection device measures the residue density in a certain area. ng / cm², while the target threshold is set to When the flow rate is ng / cm², the system uses the fitted model to infer the spray pressure that needs to be adjusted (while maintaining the current flow rate). L / (m²·s) remains unchanged): Depend on have to: MPa The original pressure was 0.62 MPa, and the system automatically increased the pressure to 0.71 MPa (an increase of about 15%), completing the adjustment within 200 ms.

[0072] The above fitting examples demonstrate that the correlation function can accurately reflect the linear relationship between residue density and spray parameters, and can effectively guide the closed-loop correction of spray pressure.

[0073] The method in this embodiment also includes precise control of the temperature of the final spray water. A high-efficiency plate heat exchanger is used to maintain the water temperature within a preset range of 45 to 65 degrees Celsius. Higher water temperatures not only help increase the solubility of mineral ions but also reduce the kinematic viscosity of the water, allowing the water flow to achieve a higher Reynolds number and impact kinetic energy under the same pressure.

[0074] The entire method achieves fully automated control of the process through a programmable logic controller (PLC). Figure 1 (As shown). The system's sampling period is set to 50 milliseconds to ensure real-time response to fluctuations in the strip's running speed. All monitored parameters (such as conductivity, flow rate, pressure, and residual density) and control variables are recorded in real time in the industrial database, supporting historical trajectory backtracking for up to 360 days.

[0075] To verify the technical effects of this invention, the applicant conducted a systematic comparative experiment. As shown in Tables 1-2, compared with traditional cleaning processes, this invention achieves significant improvements in surface cleanliness, energy consumption, and water resource utilization efficiency through the synergistic optimization of water quality and spraying. In particular, for different types of stainless steel materials, ideal surface treatment results can be obtained by adjusting the process parameters.

[0076] Table 1: Performance Comparison of the Method of the Invention with Conventional Cleaning Processes

[0077] Table 2: Comparison of cleanliness under different process parameters (304 stainless steel)

[0078] Additional notes: 1. Test conditions: Strip speed: 80 m / min; Ambient temperature: 25±2℃; Relative humidity: 50±5%; Test sample size: n≥30.

[0079] 2. Data collection methods: Surface residues: X-ray fluorescence spectrometry (XRF); Reflectance: 60° gloss meter, D65 light source; Energy consumption: Real-time monitoring by three-phase energy meter.

[0080] 3. Statistical methods: Data are expressed as mean ± standard deviation; Significance level P < 0.05; Analysis of variance was performed using SPSS 26.0.

[0081] Example 2 In the stainless steel cold-rolled sheet production line, for thicknesses of... to Austenitic stainless steels (such as the 304 series) require extremely high surface cleanliness. This embodiment demonstrates the application of the present invention under specific high-speed continuous operating conditions.

[0082] In step 1, the high-frequency sampling module of the online sensor array is activated. Since 304 stainless steel may carry a significant amount of fine metal powder during cold rolling, the monitoring focus for solid particle counts is set within the 1-micron to 5-micron range. The laser scattering module refreshes the data 10 times per second and packages the data for transmission to the processing terminal. At this point, the particulate load index calculated by the terminal guides the switching logic of the ultrafiltration membrane module in step 2.

[0083] In step 2, given the sensitivity of austenitic stainless steel to pitting corrosion, the removal of chloride ions was particularly emphasized. The water purification process lowered the preset threshold for chloride ion concentration to... The regeneration cycle of the mixed ion exchange bed is dynamically predicted based on the integral value of the influent conductivity. The ultrafiltration membrane module adopts a cross-flow filtration mode, and the membrane surface flow rate is maintained at... This reduces the deposition of particulate matter on the membrane surface.

[0084] In step 3, for the BA (bright annealed) surface finish grade, the stainless steel surface roughness correction factor is... Set as The strip speed was measured using a laser Doppler velocimeter. At this point, the flow distribution matrix calculated by the fluid dynamics model shows that the critical spray pressure required in the central region of the strip is... The edge region (distance from the edge) Within the specified range, due to the significant resistance to liquid film spreading, compensation is required. .

[0085] In step 4, multi-degree-of-freedom variable frequency spraying is performed. The AC frequency converter drives the high-pressure pump to maintain the main pipe pressure at... By adjusting the four sets of dedicated nozzles located above the edge of the strip, its vertical height is reduced to... The tilt angle was adjusted to 20 degrees, pointing outwards from the strip, creating a powerful shearing water curtain. This configuration not only completed the cleaning process but also utilized the directionality of the water flow to block the backflow of residual liquid from the preceding stage. The pulse frequency generated by the spiral flow channel inside the nozzle was locked at... The emulsion residue adhering to the microcracks is removed through the physical resonance effect.

[0086] In step 5, the multispectral imaging system performs a full-width scan of the dried strip. The detection system found that the density of residual material exceeded the standard (reaching the limit) in the left 1 / 4 of the strip. The system immediately activates a feedback compensation mechanism, using a correlation function fitted by the least squares method to calculate the required increase in the variable frequency pump pressure for that region. The actuator completes pressure adjustment within 200 milliseconds, and the cleanliness of the subsequently produced strip steel is restored to normal. It is at an excellent level.

[0087] For austenitic stainless steel, this embodiment also relates to the final water spraying. The value is monitored by adding trace amounts of high-purity ammonia to the circulating water. The value remains at to The weakly alkaline range is used to further inhibit the dissolution of metal ions and protect the passivation film on the steel strip surface.

[0088] The wastewater recycling and closed-loop circulation system operates efficiently in this embodiment. The final rinsing wastewater undergoes advanced treatment via a two-stage reverse osmosis (RO) membrane module, and the conductivity of the permeate remains stable at [value missing]. The recovery rate is as follows: The recycled water is returned to the storage tank before step 1, and the system automatically replenishes it based on the level sensor readings. The ultrapure water achieves extremely low water resource loss during operation.

[0089] Example 3 In the production scenario of ferritic stainless steel (such as the 430 series), this embodiment focuses on demonstrating the technical implementation of the present invention in preventing stress corrosion cracking and edge yellowing defects.

[0090] In step 1, considering that ferritic stainless steel is extremely sensitive to stress corrosion caused by chloride ions, the detection frequency of the ion-selective electrode is increased to once every 120 seconds. Simultaneously, real-time monitoring of silicate content is added to prevent the formation of difficult-to-remove white streaks after silicates dry on the strip surface.

[0091] In step 2, the operating logic of the multi-stage ion exchange unit was specifically optimized. The proportion of strongly basic resin packed in the anion exchange bed was increased, and a two-stage series arrangement was adopted to ensure that the chloride ion penetration concentration was absolutely lower than [a certain value]. The chemical cleaning cycle of the ultrafiltration membrane module is forcibly set based on the amount of steel strip passing through, to avoid slight fluctuations in water quality caused by membrane fouling.

[0092] In step 3, when constructing the spray field model, the relatively high surface roughness of ferritic stainless steel (No. 4 abrasive belt machined surface) was specifically considered. Roughness correction factor. Values The thickness of the residual liquid film from the upstream process, measured by infrared absorption, was approximately [thickness value missing] at the edge of the strip compared to the center. The traffic distribution matrix calculated by the model exhibits a clear U-shaped distribution, meaning that the traffic demand at the periphery is higher than that at the center. .

[0093] In step 4, the multi-degree-of-freedom spray system adopted a differentiated strategy. Addressing the tendency of 430 stainless steel to develop edge yellowing, the servo motor locked the vertical height of the edge nozzles at [specific value]. The spray pressure is set to a low position with a tilt angle of 25 degrees. At this point, the spray pressure provided by the variable frequency pump increases to... Through high-frequency pulsed water flow (frequency set to...) The edges are subjected to high-energy scrubbing. Subsequently, the air pressure of the air knife cleaning auxiliary process is increased to... Ensure that no droplets remain at the edges.

[0094] In step 5, the surface residue detection device not only monitors inorganic salt residues but also analyzes the presence of trace amounts of metal oxides through multispectral characteristic peak analysis. When an increase in the oxide index is detected, the correlation function automatically triggers step 4, increasing the spray pressure and simultaneously activating the plate heat exchanger to raise the water temperature by 5 degrees Celsius, using thermodynamic effects to accelerate the peeling of surface deposits.

[0095] The automated control system recorded the complete process curves during this process. Because the surface condition of ferritic stainless steel fluctuates significantly after annealing, the PLC performs strategy verification every minute, dynamically adjusting the flow distribution matrix. Data recorded in the industrial database shows that after adopting this method, the incidence of edge yellow spots on 430 stainless steel decreased from the original... Reduce to the following.

[0096] In this embodiment, the array nozzle is made of cemented carbide with an embedded structure. This material exhibits excellent erosion resistance against hard oxide scale debris that may be introduced by the 430 stainless steel strip. The spiral flow channel design ensures that even... Under high pressure, the jet still maintains good convergence, and the energy is highly concentrated on the surface of the strip steel.

[0097] Example 4 This embodiment describes the emergency handling and recovery mechanism of the present invention under extreme operating conditions (such as sudden deceleration of strip steel or shutdown protection) to ensure continuous consistency of surface cleanliness.

[0098] When deceleration occurs on the production line (such as by...) Down to During this process, the fluid dynamics model in step 3 acquires the signal from the laser Doppler velocimeter in real time. Due to the speed... The pressure drops significantly. Based on the pressure calculation formula, the system automatically calculates a lower critical spray pressure requirement to prevent physical damage to the strip surface caused by excessive pressure at low speeds. At this point, the frequency converter rapidly reduces the high-pressure pump speed, lowering the pressure to [a lower value]. .

[0099] In step 4, the vertical height of the nozzle is automatically raised to [the desired height] by an electric push rod. This design maximizes the coverage area of ​​individual nozzles, ensuring a uniform water film coverage on the surface even at low speeds. The tilt angle of the edge-dedicated nozzles automatically adjusts back to 5 degrees to reduce lateral shear forces.

[0100] In steps 1 and 2, due to the reduced water consumption, the circulating water system enters a small circulation mode. The integrated water treatment terminal controls a pneumatic three-way valve to directly return most of the treated water to the storage tank, maintaining the dynamic flow rate within the ion exchange resin tank and preventing stagnant water from causing bacterial growth or ion precipitation.

[0101] Once the production line resumes high-speed operation, the feedback compensation system in step 5 immediately performs a scan of the first roll. The multispectral imaging equipment performs intensive sampling on the recovered first strip, increasing the sampling frequency to once every 10 milliseconds. If the density of local surface residue increases due to the shutdown, the system will quickly perform step pressure compensation until the residue index returns to below the preset threshold.

[0102] This embodiment also involves automatic diagnosis of nozzle blockage. By monitoring the comparison between the electromagnetic flowmeter and the pressure sensor on each group of nozzle branches, when an increase in pressure and a decrease in flow are detected, the PLC determines that there is a risk of blockage in that group of nozzles, automatically switches to the backup nozzle array, and issues a maintenance alarm to the operation interface. This intelligent monitoring mechanism ensures zero interruption of cleanliness control in large-scale continuous production.

[0103] Throughout the operation of all embodiments, the system adheres to stringent environmental standards in its use of water resources. Through osmotic pressure regulation of the reverse osmosis components, the quality of the recycled permeate water is consistently superior to that of the raw water supply. The logic for adding deionized water is based on dual control of the water tank level and conductivity, ensuring the entire closed-loop system remains in a quasi-equilibrium state. This, in turn, enhances the cleanliness of the stainless steel surface while minimizing environmental impact.

[0104] Example 5 For ultra-thin stainless steel precision strip (thickness less than) In the production of [the product], this embodiment details how the present invention achieves ultimate surface quality by finely adjusting spray parameters and water quality indicators.

[0105] In step 1, because the ultrathin strip is extremely sensitive to surface pits and scratches, the online sensing array adds monitoring of dissolved oxygen (DO) and carbon dioxide in the water to prevent microscopic deformation caused by the bursting of dissolved gas bubbles during spraying. The solid particle counting standard is raised to: particles larger than 5 micrometers are not allowed.

[0106] In step 2, the ultrafiltration membrane module is replaced with a fine membrane with a molecular weight cutoff of 20,000 Daltons, and the flux attenuation rate is tightened to a preset threshold. The ion exchange unit adds a microfiltration stage to prevent resin debris from entering the final leaching stage.

[0107] In step 3, to address the flatness requirements of the precision strip, a spray pressure difference balance coefficient was introduced into the fluid dynamics model. This coefficient ensures that the spray pressure deviation between the upper and lower surfaces of the strip is less than [a certain value]. This is to prevent the strip steel from vibrating in the spraying section.

[0108] In step 4, when performing multi-degree-of-freedom spraying, the vertical height increases to The injection angle is adjusted to a narrow-angle fan shape (45 degrees) to reduce the instantaneous impact load per unit area. The frequency converter maintains a pressure pulsation rate of less than [value missing] through closed-loop control. The air knife blowing uses ultra-clean hot air that has undergone multi-stage filtration and is set at 80 degrees Celsius. While blowing away the water film, it also completes the initial preheating, preventing the ultra-thin strip from warping due to uneven thermal stress.

[0109] In step 5, the resolution of the multispectral detection system is improved to the micrometer level, enabling the identification of nanoscale salt crystal distributions on the surface. By establishing a high-order nonlinear correlation function between residue density and nozzle height and tilt angle, the system achieves microgram-level precise cleaning control.

[0110] Example 6 This embodiment focuses on describing the application of the present invention on large stainless steel sheets (width exceeding...). Scheme for controlling the uniformity of span distribution in production.

[0111] In step 1, due to the large span, conductivity sampling points were set up at both the main water supply pipeline and the remote return water branch in the water quality acquisition terminal. By comparing the conductivity difference between the two points, the real-time load of contaminant stripping from the steel strip surface during the spraying process was evaluated.

[0112] In step 3, the critical spray pressure distribution matrix was calculated using a two-dimensional spatial grid. Because the water flow towards the center of large panels during spraying creates a water wall effect, a flow correction coefficient was added to the model in the central region. The calculated flow distribution matrix exhibits a nonlinear characteristic of being sparse in the middle and dense at the edges.

[0113] In step 4, the array nozzles are divided into 5 independent control zones. Each zone is equipped with an independent variable frequency control valve and a servo height adjustment device. Based on data from the width detector, the PLC automatically blocks nozzles that exceed the width of the plate, reducing ineffective water waste. For nozzles in the central zone, the servo motor increases their tilt angle in the running direction, guiding the water flow to the edge for rapid discharge.

[0114] In step 5, the surface residue detection equipment uses multi-camera stitching imaging technology to cover the entire surface. Size. The system algorithm automatically identifies the density of residue at the seams, ensuring that the cleanliness deviation within the size area is less than [specified value]. The correlation function automatically optimizes the pressure parameters of the five control zones, achieving extremely high consistency in cleanliness under large-span operating conditions.

[0115] For this type of large sheet material, the air knife cleaning auxiliary process in this embodiment employs segmented air pressure compensation. Because the airflow at the edges tends to disperse, the air pressure at the edges is higher than that at the center. This precise aerodynamic configuration completely solves the problem of cloud-like spots caused by uneven drying of large panels.

[0116] Example 7 In the production process of stainless steel decorative panels (such as mirror panels and etched panels), surface cleanliness not only affects corrosion performance but also directly determines optical visual quality. This embodiment demonstrates the implementation details of the present invention in improving surface reflectivity.

[0117] In step 1, to address the extremely high requirements for surface roughness and gloss of the decorative panels, the online sensor array was supplemented with monitoring of total organic carbon (TOC) in the water. The TOC content was strictly controlled within [specific parameters]. The following measures are taken to prevent organic matter from forming a micron-sized molecular film on the mirror surface, which would affect the gripping force of subsequent PVD coating.

[0118] In step 2, to achieve extremely low TOC and conductivity, a UV oxidation (UV) and nuclear-grade resin refining unit is added after the ultrafiltration membrane module in the purification process. The effluent conductivity is stabilized at... The ultimate purity.

[0119] In step 3, for the extremely low roughness of the mirror panel ( ), correction factor Values The critical pressure calculated by the fluid dynamics model is relatively low, but it has extremely high requirements for the uniformity of the flow rate.

[0120] In step 4, the multi-degree-of-freedom variable frequency spray creates a low-pressure, high-frequency cleaning field by reducing the flow rate per nozzle and increasing the number of nozzles. The pulse frequency generated by the spiral flow channel is increased to... High-frequency micro-vibration is used to remove residual polishing paste from the micropores of the mirror surface. All nozzles are treated with Teflon coating to prevent secondary pollution from metal particles.

[0121] In step 5, surface residue detection utilizes multispectral imaging to identify differences in residual surface tension. The correlation function not only corrects for the spray pressure but also controls the plate heat exchanger to precisely lock the spray temperature at [specific value]. Temperature in degrees Celsius. Experimental data shows that the surface reflectivity of decorative panels treated with this method is improved compared to traditional processes. The above, and the surface sodium ion density decreased to the following.

[0122] The entire process is monitored by an industrial database. The cleanliness spectrum of each board is linked to its unique QR code, enabling precise quality traceability.

[0123] 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 to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A method for improving the surface cleanliness of stainless steel by optimizing the final rinse water quality and spraying method, characterized in that, Includes the following steps: The conductivity, total dissolved solids concentration, chloride ion concentration, silicate content and solid particle count in the final shower water are collected in real time using an online sensor array and transmitted to the integrated water quality treatment terminal. Based on the feedback from the integrated water quality treatment terminal, the multi-stage ion exchange unit and ultrafiltration membrane module are driven to purify the final shower water, and the conductivity of the final shower water is controlled to be stable below the first preset conductivity threshold, and the chloride ion concentration is lower than the preset concentration threshold. The running speed, strip width, and residual liquid film thickness of the stainless steel strip are collected and input into the fluid calculation model to calculate the critical spray pressure parameters and flow distribution matrix. Based on the calculated critical spray pressure parameters and flow distribution matrix, the spray pressure and flow of multiple array nozzles located above the stainless steel strip are controlled, and the vertical height and tilt angle of the nozzles are adjusted to achieve non-uniform impact strengthening of the strip surface and edge area. The distribution of mineral residues on the dried stainless steel surface was obtained using an online surface residue detection device. A correlation function between residue density and spray control parameters was established, and the spray pressure parameters were corrected based on this function.

2. The method according to claim 1, characterized in that, The online sensing array includes a four-electrode conductivity sensor, an ion-selective electrode, and a laser scattering measurement module. The four-electrode conductivity sensor has a temperature compensation function. The ion-selective electrode includes a chloride ion-sensitive membrane electrode. The laser scattering measurement module is equipped with a laser beam emitter and a polygonal photodetector.

3. The method according to claim 1, characterized in that, The multi-stage ion exchange unit includes a cation exchange bed, an anion exchange bed, and a mixed ion exchange bed arranged sequentially. The cation exchange bed is filled with a strongly acidic styrene-based resin, the anion exchange bed is filled with a strongly basic anion exchange resin, and the mixed ion exchange bed is filled with both cation and anion exchange resins.

4. The method according to claim 1, characterized in that, The ultrafiltration membrane module uses a hollow fiber membrane made of polyethersulfone and is equipped with a variable frequency water supply pump, a differential pressure monitoring device, and a chemical cleaning system.

5. The method according to claim 1, characterized in that, The fluid calculation model incorporates a strip surface roughness correction factor to calculate the expansion coefficient of the sprayed liquid flow on the strip surface.

6. The method according to claim 1, characterized in that, The array nozzle has a fan-shaped spray structure with a spiral flow channel inside, which can generate high-frequency pulsed water flow with adjustable pulse frequency.

7. The method according to claim 1, characterized in that, The vertical height of the array nozzles is adjusted by an electric push rod, and the nozzles in the edge area are driven by a servo motor to tilt at a preset angle relative to the normal direction of the strip.

8. The method according to claim 1, characterized in that, After the spraying operation, the method also performs an air knife cleaning auxiliary process. A high-pressure clean air blowing device is set at the outlet of the final spraying process. The spraying direction of the air knife forms a preset angle with the running direction of the stainless steel strip to be treated. The pressure impact of the airflow forces the residual liquid film on the surface of the strip to flow backward and to the edge and detach from the surface of the strip. The air knife cleaning auxiliary process, in conjunction with the subsequent drying process, controls the uniformity of moisture evaporation on the surface of the strip.

9. The method according to claim 1, characterized in that, The correlation function between the residual density and the spray control parameters is established using the least squares method for fitting, and its objective function is: in, For the sum of squared errors, For the first Measured residue density at each sampling point The corresponding area's spray pressure, This refers to the spray flow rate for the corresponding area. , , The coefficients to be fitted are minimized. The optimal control correction parameters are obtained by solving the problem.

10. The method according to claim 1, characterized in that, The online surface residue detection device uses multispectral imaging technology to identify the intensity of characteristic peaks in the reflection spectrum of stainless steel surface and calculate the mass density distribution map of surface residues.

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