High-strength steel continuous annealing surface point defect control method based on water cooling process

Abstract

The invention relates to the technical field of high-strength steel treatment, in particular to a high-strength steel continuous annealing surface point defect control method based on a water cooling process, and the method comprises the following steps: scanning the quality of surface residual oil and surface residual iron of a cold-rolled sheet, and screening the cold-rolled sheet; the strip steel is subjected to vertical spraying cleaning, and the strip steel subjected to vertical spraying cleaning is subjected to electrolytic cleaning; spraying a thermal barrier coating ceramic coating, depositing a chromium carbide coating, introducing protective gas, carrying out continuous annealing treatment, controlling annealing treatment parameters, and carrying out acid pickling on the strip steel subjected to annealing treatment; and nickel plating is conducted on the strip steel subjected to acid pickling, and the point defects of the continuous annealing surface of the high-strength steel are controlled. According to the method, precise control over the point defects on the continuous annealing surface of the high-strength steel is achieved.

Description

Technical Field

[0001] The present application relates to the technical field of high-strength steel processing, and in particular to a method for controlling surface point defects of high-strength steel continuous annealing based on a water cooling process. Background Art

[0002] In the field of car body manufacturing, cold-rolled advanced high-strength steel is widely used. Steel grades such as DP980, DP1180, TBF1180 and TBF980 have been routinely used in reinforcing components such as car body B-pillars, door frame reinforcement plates, and complex car body structural parts such as front and rear longitudinal beams. With the continuous development of the performance of cold-rolled high-strength steel, the precise control of the phase ratios of ferrite, martensite, bainite and residual austenite using water cooling technology has become more efficient. However, due to the increasingly stringent requirements of automobile factories on the surface quality of steel plates, more complex annealing process curves and more diverse alloy composition designs have brought adverse effects on the effective control of surface point defects, greatly limiting the surface quality of continuous annealing of high-strength steel based on water cooling technology, and hindering the stable production of products and the cost control and efficiency improvement of steel companies.

[0003] During the continuous annealing process of high-strength steel, the generation of surface point defects is caused by a variety of factors. From the perspective of raw materials, insufficient steel purity and differences in the original surface quality, such as the segregation of impurity elements, surface scratches or residual iron oxide scale, may all be the cause of defects. In the annealing process, improper temperature control at each stage, such as excessive heating speed resulting in excessive thermal stress, too high or too low annealing temperature causing abnormal structural changes, and unreasonable cooling speed causing thermal stress and structural inhomogeneity, will cause problems. In terms of equipment factors, such as uneven cooling water flow rate in the cooling system, the cooling effect on the steel surface will be inconsistent, which will in turn cause thermal stress and structural inhomogeneity, and ultimately lead to point defects. Traditional control methods are often limited to a single means, and do not fully and comprehensively consider the joint interference between different influencing factors, making it difficult for the deviation of defect control in the continuous annealing process of high-strength steel to meet production needs. Summary of the invention

[0004] In order to solve the above technical problems, the present application provides a method for controlling surface point defects of high-strength steel continuous annealing based on a water cooling process to solve the existing problems.

[0005] The method for controlling surface point defects of high-strength steel continuous annealing based on water cooling process in this application adopts the following technical solutions: One embodiment of the present application provides a method for controlling surface point defects of high-strength steel continuous annealing based on a water cooling process, the method comprising the following steps: S10, scanning the quality of residual oil and residual iron on the surface of the cold-rolled sheet to screen the cold-rolled sheet; S20, using a hot alkali washing solution to vertically spray wash the steel strip, and using an electrolytic washing alkali solution to electrolytically wash the vertically spray washed steel strip; S30, spraying thermal barrier coating ceramic coating on the high temperature zone and the medium temperature zone of the furnace area, depositing chromium carbide coating on the low temperature zone, introducing protective gas into the furnace, continuously annealing the strip steel after electrolytic cleaning, and controlling the parameters of the annealing treatment, and the control method is: S31, collecting each monitoring data during the continuous annealing process of high-strength steel; S32, based on the difference between the monitoring data and in combination with the mutation point detection algorithm, obtaining each joint response interval; S33, obtaining an annealing control deviation coefficient of each joint response interval based on the monitoring data of the joint response interval; S34, based on the disorder degree of the monitoring data in the joint response interval and the annealing control deviation coefficient, obtaining a feedback compensation error of each monitoring data, and adjusting each monitoring data in the annealing process; S40, pickling the strip steel after annealing; S50, nickel plating is performed on the strip steel after pickling to reduce the point defects on the surface of high-strength steel continuous annealing.

[0006] Furthermore, the mass of the residual oil on the surface is 200-300 mg / m² per side, and the mass of the residual iron on the surface is 30-50 mg / m² per side.

[0007] Furthermore, the hot alkaline washing solution has a concentration of 6% to 8% and a temperature of 75 to 85°C.

[0008] Furthermore, the spray pressure of the vertical spray cleaning is 23 MPa, and the spray flow rate is 700 L / h.

[0009] Furthermore, the concentration of the electrolytic cleaning alkali solution is 10% to 12% and the temperature is 75 to 85°C.

[0010] Further, the method for obtaining the joint response interval is: For each type of monitoring data, a sequence of monitoring data at each collection moment in time order is used as a monitoring data sequence of each type of monitoring data, and a difference calculation result between each element in the monitoring data sequence and the preset standard monitoring data is calculated respectively, and a sequence composed of the difference calculation results is used as a deviation data sequence of each type of monitoring data; The deviation data sequence of each type of monitoring data is used as each row element in the matrix, and the deviation data sequences of all types of monitoring data together form a deviation data matrix; The deviation data matrix is ​​taken as input, and the Radon algorithm is used to map the deviation data matrix vertically to obtain the comprehensive deviation data sequence of the deviation data matrix. The abnormal data detection algorithm is used to obtain the mutation points in the comprehensive deviation data sequence. The collection time corresponding to the mutation point is used as the segmentation time point, and each time interval is divided based on the segmentation time point. The time period between each segmentation time point is used as each joint response interval.

[0011] Further, the method for obtaining the annealing control deviation coefficient is: In the deviation data matrix, the matrix composed of all elements in each joint response interval is used as each sub-matrix of the deviation data matrix in each joint response interval; the rank of each sub-matrix of the deviation data matrix is ​​calculated; For each submatrix of the deviation data matrix, the mean of all data in each row of data in the submatrix is ​​calculated, and the sequence composed of the mean of each row of data in the submatrix is ​​used as the deviation accumulation sequence of each submatrix; The calculation formula of the annealing control deviation coefficient is: ; In the formula, Indicates Annealing control deviation coefficient for the joint response interval; and Respectively represent and The cumulative sequence of deviations of the submatrices of the joint response intervals, express and Euclidean distance between them; and Respectively represent and The rank of the submatrix of joint response intervals, represents an exponential function with a natural constant as base; Represents the number of joint response intervals.

[0012] Further, the method for obtaining the feedback compensation error is: Each monitoring data in each joint response interval is used as the input of the entropy weight method to obtain the relative change weight of each monitoring data in each joint response interval; For each monitoring data, the product of the relative change weight of each monitoring data in each joint response interval and the annealing control deviation coefficient of the joint response interval is calculated to obtain the normalized results of all the products; the normalized results of the products are used as the feedback compensation deviation coefficient of the annealing processing parameter control of each monitoring data in each joint response interval; The calculation formula of the feedback compensation error is: ; In the formula, represents the feedback compensation error of the i-th monitoring data; represents the mean of all data of the i-th monitoring data in the p-th joint response interval; and They represent the feedback compensation deviation coefficients of the i-th monitoring data in the p-th and t-th joint response intervals respectively; represents the number of joint response intervals.

[0013] Further, the adjusting of each monitoring data during the annealing process includes: The mean value of the feedback compensation deviation coefficients of all monitoring data is used as the judgment threshold, and the mean value of the feedback compensation deviation coefficients of all monitoring data in the joint response interval where the current acquisition moment is located is compared with the judgment threshold. If it is greater than or equal to the judgment threshold, the feedback compensation error of the monitoring data is used as the input of the automatic control system programmable controller PLC; if it is less than the judgment threshold, the absolute value of the difference between the mean value of the feedback compensation deviation coefficients of all monitoring data in the joint response interval where the current acquisition moment is located and the judgment threshold is used as the input of the automatic control system programmable controller PLC, and each type of monitoring data adjusted during the annealing process is output.

[0014] Furthermore, the nickel layer thickness of the nickel plating is 15-20 mg / m².

[0015] This application has at least the following beneficial effects: In the continuous annealing process of high-strength steel based on the water-cooling process, the generation of surface point defects is mainly due to the complex pollution sources on the surface of the cold-hardened finished product produced by the cold rolling unit, and it is difficult for the subsequent units to completely remove these pollution sources, resulting in frequent accumulation of oxides on the surface of the furnace rollers in the furnace; and in actual production, during the continuous annealing process under the water-cooling process, there is a joint interference phenomenon between various parameters, which seriously interferes with the stability of the strip annealing parameters, causing stress changes, and then causing point defects on the strip surface. In response to the above problems, this application first carries out the inspection and screening of raw materials in sequence, pre-treats the surface of the raw materials, and adopts vertical spray cleaning and electrolytic cleaning technology to effectively remove impurities on the surface of the raw materials. Secondly, in the annealing process, the long-term impact of the combined interference that the annealing parameters may suffer over a long time span is fully taken into consideration, and the feedback errors that occur in the control process are deeply analyzed and precisely adjusted; the beneficial effect is that, from the perspective of full-process surface control, a coupled design is carried out, which effectively reduces the incidence of point defects on the annealing surface caused by pollutant interference and the long-term impact of control deviations in the actual treatment process, thereby achieving precise control of point defects on the surface of continuous annealing of high-strength steel, and effectively ensuring product quality and production stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 A flow chart of a method for controlling surface point defects of high-strength steel continuous annealing based on a water cooling process provided in one embodiment of the present application; Figure 2 A flow chart of annealing process parameter control provided for one embodiment of the present application. DETAILED DESCRIPTION

[0018] In order to further explain the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the specific implementation method, structure, features and effects of the surface point defect control method of high-strength steel continuous annealing based on the water cooling process proposed in the present application are described in detail as follows in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0019] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0020] The specific scheme of the method for controlling surface point defects of high-strength steel continuous annealing based on water cooling process provided by the present application is described in detail below with reference to the accompanying drawings.

[0021] An embodiment of the present application provides a method for controlling surface point defects of high-strength steel continuous annealing based on a water cooling process. Specifically, the following method for controlling surface point defects of high-strength steel continuous annealing based on a water cooling process is provided. Figure 1 , the method comprises the following steps: The present application proposes a method for controlling point defects on the surface of high-strength steel continuous annealing based on a water cooling process, which specifically includes inspection and screening of raw materials, surface pretreatment, vertical spray cleaning, electrolytic cleaning, continuous annealing treatment, surface treatment of continuous annealing furnace rollers, furnace atmosphere design, pickling and nickel flash treatment. The specific control process is as follows: Step S10, scanning the quality of residual oil and residual iron on the surface of the cold-rolled sheet, and screening the cold-rolled sheet: using a laser scanning surface defect detector to conduct a comprehensive inspection of the cold-rolled sheet, and screening out the cold-rolled sheet that meets the requirements of 200-300 mg / m² of residual oil on each side and 30-50 mg / m² of residual iron on each side according to the preset quality standards.

[0022] Step S20, use hot alkali washing solution to vertically spray wash the strip, and use electrolytic cleaning alkali solution to electrolytically wash the vertically spray washed strip: be equipped with multiple groups of high-pressure nozzles, and the nozzle layout is optimized according to the strip width and transmission speed. The nozzle angle is accurately adjusted through the automatic control system (adjustable within the range of ±15°), the spray pressure is 23MPa, and the spray flow rate is 700L / h. The hot alkali washing solution is sprayed onto the strip under high pressure to achieve all-round, uniform and efficient cleaning of the strip surface; wherein the concentration of the hot alkali washing solution is 6%~8%, and the temperature of the hot alkali washing solution is 75~85℃.

[0023] The strip steel is used as an electrode to precipitate gas on the surface of the strip steel. The surface of the strip steel is deeply cleaned with electrolytic cleaning alkali solution. The electrolytic current density is 0.3~0.5A / dm², the voltage is 4~6V, the concentration of the electrolytic cleaning alkali solution is 10%~12%, and the temperature is 75~85℃. The electrolytic cleaning alkali solution is continuously delivered by a circulating pump with a flow rate of 800~1200L / h. The filter is automatically backwashed regularly to remove impurity particles in the electrolytic cleaning alkali solution, ensure the cleanliness and conductivity of the electrolyte, improve the cleaning effect and stability, and achieve deep cleaning.

[0024] Specifically, in this application, the parameters of 8 embodiments for raw material inspection and screening, surface pretreatment, vertical spray treatment and electrolysis treatment are shown in Table 1: Table 1 Process parameters of the embodiment Step S30, spraying thermal barrier coating ceramic coating on the high temperature zone and medium temperature zone of the furnace zone, depositing chromium carbide coating on the low temperature zone, introducing protective gas into the furnace, continuously annealing the strip steel after electrolytic cleaning, and selecting the tension coefficient: for the high temperature zone (700℃~900℃) and medium temperature zone (400℃~700℃) in the furnace zone, using automatic spraying equipment of thermal barrier coating to spray ceramic coating, wherein the spraying speed is 50~80mm / s, and the spraying thickness is 0.3~0.5mm, to ensure the uniformity and adhesion of the coating.

[0025] The chromium carbide coating sprayed in the low temperature zone (200℃~400℃) is prepared by chemical vapor deposition (CVD) process, where the deposition temperature is 400~500℃, the chromium source gas flow rate is 50~100sccm, and the deposition time is 3~5 hours, ensuring that the coating has appropriate hardness (HV1500~2000) and wear resistance. Different replacement cycles are formulated according to different zone temperatures, 11500KM for high temperature zone, 15000KM for low temperature zone, and 18400KM for medium temperature zone.

[0026] Into the furnace and Shielding gas flow rate, where The injection volume is 4.5%~5% (volume fraction). The injection amount is 95%~95.5% to ensure the effective coverage and reduction effect of the protective gas, and prevent oxidation and point defects on the surface of the steel plate and furnace roller.

[0027] The tension coefficient is set according to the specifications of the strip steel, as shown in Table 2: Table 2 Tension coefficients in different process stages During the annealing process, the automatic control system is used to control and adjust the annealing parameters to ensure that the strip is heated stably and the tension changes stably during the annealing process. The process of optimizing control by the automatic control system at different process stages is as follows: Step S31, collecting each monitoring data during the continuous annealing process of high-strength steel.

[0028] Sensors are used to collect each type of monitoring data during the continuous annealing process of high-strength steel. In this embodiment, the types of monitoring data include strip tension data, furnace temperature data, and strip transmission speed data. Tension sensors, temperature sensors, and speed sensors are used for data collection, respectively. Each type of monitoring data has a preset standard value, and the preset standard value of each type of monitoring data is used as the preset standard monitoring data. In this embodiment, the interval between each collection moment is 1s, and the implementer can select other values ​​according to actual conditions. Furthermore, each type of monitoring data is denoised. In this embodiment, Wiener filtering is used for denoising. Wiener filtering is a well-known technology and will not be described in detail in this embodiment.

[0029] At this point, the acquisition of each type of monitoring data during the continuous annealing process of high-strength steel has been completed.

[0030] Step S32, based on the differences between the monitoring data sequences and in combination with the mutation point detection algorithm, obtain each joint response interval.

[0031] In the four key process stages of the continuous annealing process of high-strength steel, namely the heating stage, slow cooling stage, rapid cooling stage and aging stage, the three key process parameters of temperature, strip transmission speed and strip tension show an intertwined relationship in their respective dynamic changes. Among them, the rapid change of temperature will cause the corresponding fluctuation of strip tension, and this tension fluctuation will further affect the strip transmission speed, resulting in a more significant stress change in the whole system. Under the action of stress changes, the microstructure of the steel surface is very likely to change, for example, it may cause uneven surface grain growth, and then form local convex or concave shapes on the steel surface, and eventually evolve into point defects.

[0032] It can be seen that in the process of continuous annealing of high-strength steel, the more significant the combined interference effect between temperature change, strip transmission speed change and strip tension change, the higher the probability of point defects on the surface of high-strength steel obtained after continuous annealing. In view of the deviation characteristics presented by the combined interference effect of different monitoring data during the high-strength continuous annealing process, feedback control and adjustment are implemented for the process parameters at each stage of continuous annealing. The specific calculation and analysis process is as follows: In the continuous annealing process, the traditional monitoring data deviation feedback mechanism has limitations. Generally speaking, the feedback of monitoring data such as temperature, tension and speed in the space where the strip is located is judged only based on the instantaneous response characteristics at the current moment, that is, simply considering the error of these data deviating from the preset value at the current moment. However, in the actual processing process, the joint interference between different monitoring data is not instantaneous, but continues to change dynamically over a long period of time. This long-term continuous change will have a significant impact on the adjustment of parameter control response, resulting in large control errors; Therefore, based on the above analysis, for each type of monitoring data, the sequence composed of the monitoring data at each collection moment in chronological order is taken as the monitoring data sequence of each type of monitoring data, and the difference calculation results between each element in the monitoring data sequence and the preset standard monitoring data are calculated respectively, and the sequence composed of the difference calculation results is taken as the deviation data sequence of each type of monitoring data.

[0033] Furthermore, in order to compare the response relationship of monitoring data deviations in different time ranges, the deviation data sequence of each type of monitoring data is used as the row elements in the matrix, and the deviation data sequences of all types of monitoring data together constitute the deviation data matrix. In the deviation data matrix, each column element corresponds to the deviation of different monitoring data at each collection time.

[0034] Furthermore, the deviation data matrix is ​​used as input, and the Radon algorithm is used to map the deviation data matrix in the vertical direction to obtain the comprehensive deviation data sequence of the deviation data matrix. The LOF algorithm is used to obtain the mutation point in the comprehensive deviation data sequence, and the acquisition time corresponding to the mutation point is used as the segmentation time point. The time intervals are divided based on the segmentation time point, and the time period between the segmentation time points is used as each joint response interval. It should be noted that the time period between the start time of data acquisition and the first segmentation time point, and the time period between the last segmentation time point and the end time of data acquisition are also used as joint response intervals.

[0035] It should be noted that the purpose of abnormal detection after vertical mapping is to comprehensively analyze the nonlinear change characteristics of the joint interference between all monitoring data and accurately divide the interval of the change of the monitoring data deviation response. Among them, the Radon algorithm and the LOF algorithm are well-known technologies and will not be described in detail in this embodiment.

[0036] Step S33: acquiring the annealing control deviation coefficient of each joint response interval based on the monitoring data of the joint response interval.

[0037] Furthermore, the deviation data matrix is ​​divided according to the divided joint response intervals. The specific division method is as follows: in the deviation data matrix, the matrix composed of all elements in each joint response interval is used as each sub-matrix of the deviation data matrix in each joint response interval. The rank of each sub-matrix of the deviation data matrix is ​​calculated. The larger the value of the rank, the greater the influence of the joint interference effect within the corresponding joint response interval during the control process, that is, the more significant the nonlinear characteristics between the deviations of different monitoring data are; Furthermore, for each submatrix of the deviation data matrix, the mean of all data in each row of data in the submatrix is ​​calculated, and the sequence composed of the mean of each row of data in the submatrix is ​​used as the deviation accumulation sequence of each submatrix; it should be noted that the deviation accumulation sequence reflects the cumulative deviation of the combined interference effect of different monitoring data deviations in the corresponding joint response interval; based on the nonlinear characteristics of the annealing processing monitoring data in different joint response intervals and the deviation accumulation characteristics, the annealing control deviation coefficient is calculated, and the calculation formula is: ; In the formula, Indicates Annealing control deviation coefficient for the joint response interval; and Respectively represent and The cumulative sequence of deviations of the submatrices of the joint response intervals, express and Euclidean distance between them; and Respectively represent and The rank of the submatrix of joint response intervals, It represents the exponential function with the natural constant e as the base; represents the number of joint response intervals; wherein, the Euclidean distance is a well-known technology and will not be described in detail in this embodiment.

[0038] It should be noted that the larger the calculated annealing control deviation coefficient is, the more significant the nonlinear characteristics of the deviation response of different monitoring data are during the annealing process, and the more serious the impact of the deviation accumulation on the joint interference effect is, which may lead to fluctuations in the control feedback deviation during the annealing process over a longer time range.

[0039] Step S34, based on the disorder degree of the monitoring data in the joint response interval and the annealing control deviation coefficient, the feedback compensation error of each monitoring data is obtained, and each monitoring data in the annealing process is adjusted.

[0040] Through the above analysis, in the continuous annealing process of high-strength steel, the response of the control error of its parameters is not only reflected in the instantaneous characteristics of the current control moment, but also in a longer control range, the more significant the joint response deviation of different monitoring data is, the greater the possibility of deviation in the feedback error is; Further, each monitoring data of each joint response interval is used as the input of the entropy weight method to obtain the relative change weight of each monitoring data of each joint response interval; it should be noted that the larger the relative change weight, the more significant the dynamic change characteristics of the data of the row corresponding to the relative change weight under the influence of the joint interference effect within the time range of the current joint response interval; Based on the time difference of each monitoring data in the control process affected by the joint interference during the annealing process, the deviation of the feedback error of each monitoring data is analyzed, and the feedback compensation error is calculated based on the analysis results. , the acquisition method is as follows: Specifically, for each monitoring data, the product of the relative change weight of each monitoring data in each joint response interval and the annealing control deviation coefficient of the joint response interval is calculated to obtain the normalized results of all the products; the normalized results of the products are used as the feedback compensation deviation coefficient of the annealing processing parameter control of each monitoring data in each joint response interval. The larger the feedback compensation deviation coefficient is, the greater the degree of parameter deviation in the control process is affected by the combined interference effect within the corresponding time range.

[0041] Furthermore, based on the joint interference effect characteristics of each monitoring data in different time ranges up to the current moment in the control process, feedback error correction analysis is performed to calculate the feedback compensation error. The calculation formula is: ; In the formula, represents the feedback compensation error of the i-th monitoring data; represents the mean of all data of the i-th monitoring data in the p-th joint response interval; and They represent the feedback compensation deviation coefficients of the i-th monitoring data in the p-th and t-th joint response intervals respectively; represents the number of joint response intervals.

[0042] It should be noted that the larger the calculated feedback compensation error is, the greater the impact of the combined interference of fluctuations in different monitoring data over a long period of time up to the current moment, resulting in a decrease in the accuracy of the feedback error at the current moment, and the larger the compensation correction value.

[0043] At this point, the feedback compensation error of each monitoring data during the high-strength steel annealing process was obtained.

[0044] The feedback compensation error of each monitoring data is used as the input of the programmable controller PLC of the automatic control system. The programmable controller uses the PID control algorithm to control and adjust each monitoring data in the annealing process according to the feedback compensation errors of different monitoring data received. It should be noted that in the real-time control process, for the adjustment of the feedback error of each monitoring data, the influence of the joint interference effect is judged at the current acquisition time. Specifically, the mean of the feedback compensation deviation coefficients of all monitoring data is used as the judgment threshold, and the mean of the feedback compensation deviation coefficients of all monitoring data in the joint response interval where the current acquisition time is located is compared with the judgment threshold. If it is greater than or equal to the judgment threshold, the feedback compensation error of the monitoring data is used as the input of the programmable controller PLC of the automatic control system; if it is less than the judgment threshold, the absolute value of the difference between the mean of the feedback compensation deviation coefficients of all monitoring data in the joint response interval where the current acquisition time is located and the judgment threshold is used as the input of the programmable controller PLC of the automatic control system, and each monitoring data adjusted in the annealing process is output, the purpose of which is to avoid the influence of the joint interference fluctuations of different monitoring data on the control deviation within a long time range during the control process. Among them, the annealing process parameter control flow chart is as follows Figure 2 shown.

[0045] Specifically, the continuous annealing tension and furnace roller cycle parameters of the eight embodiments during the continuous annealing process are shown in Table 3: Table 3 Continuous annealing process parameters Step S40, pickling the strip after annealing: pickling the strip after continuous annealing, using dilute hydrochloric acid with a pickling concentration of 12-16%, an acid flow rate of 300-500 L / min, a temperature of 60-70°C, and a pickling time of 10-15 s to ensure that the strip is evenly immersed and reacted in the pickling tank.

[0046] Step S50, nickel-plating the steel strip after pickling to control the point defects on the surface of high-strength steel continuous annealing: flash nickel treatment is performed on the steel strip after pickling, the preset nickel layer thickness is 15~20mg / m², the nickel plating time is 35 minutes, the current density is 0.8~1.2A / dm², and the plating solution components are main salt nickel sulfate concentration of 250~300g / L, buffer boric acid concentration of 30~40g / L and appropriate amount of additives, to achieve precise nickel plating, ensure the improvement of the surface quality of the steel strip, and effectively prevent the occurrence of point defects and subsequent corrosion problems.

[0047] Specifically, the parameter settings of the furnace atmosphere design, pickling and nickel flash treatment in the 8 embodiments of the present application are shown in Table 4: Table 4 Parameter settings of the embodiment It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. The above-mentioned specific embodiments of the present application are described. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0048] The various embodiments in the present application are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0049] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Modifications to the technical solutions recorded in the aforementioned embodiments, or equivalent replacement of some of the technical features therein, do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for controlling surface point defects of high-strength steel continuous annealing based on a water cooling process, characterized in that: The method comprises the following steps: S10, scanning the quality of residual oil and residual iron on the surface of the cold-rolled sheet to screen the cold-rolled sheet; S20, using a hot alkali washing solution to vertically spray wash the steel strip, and using an electrolytic washing alkali solution to electrolytically wash the vertically spray washed steel strip; S30, spraying thermal barrier coating ceramic coating on the high temperature zone and the medium temperature zone of the furnace area, depositing chromium carbide coating on the low temperature zone, introducing protective gas into the furnace, continuously annealing the strip steel after electrolytic cleaning, and controlling the parameters of the annealing treatment, and the control method is: S31, collecting each monitoring data during the continuous annealing process of high-strength steel; S32, based on the difference between the monitoring data and in combination with the mutation point detection algorithm, obtaining each joint response interval; S33, obtaining an annealing control deviation coefficient of each joint response interval based on the monitoring data of the joint response interval; S34, based on the disorder degree of the monitoring data in the joint response interval and the annealing control deviation coefficient, obtaining a feedback compensation error of each monitoring data, and adjusting each monitoring data in the annealing process; S40, pickling the strip steel after annealing; S50, nickel plating is performed on the strip steel after pickling to reduce the point defects on the surface of high-strength steel continuous annealing.

2. The method for controlling surface point defects of high-strength steel continuous annealing based on water cooling process according to claim 1, characterized in that: The mass of the surface residual oil is 200-300 mg / m² per side, and the mass of the surface residual iron is 30-50 mg / m² per side.

3. The method for controlling surface point defects of high-strength steel continuous annealing based on water cooling process according to claim 1, characterized in that: The hot alkali washing solution has a concentration of 6% to 8% and a temperature of 75 to 85°C.

4. The method for controlling surface point defects of high-strength steel continuous annealing based on water cooling process according to claim 1, characterized in that: The spray pressure of the vertical spray cleaning is 23 MPa, and the spray flow rate is 700 L / h.

5. The method for controlling surface point defects of high-strength steel continuous annealing based on water cooling process according to claim 1, characterized in that: The concentration of the electrolytic cleaning alkali solution is 10%-12% and the temperature is 75-85°C.

6. The method for controlling surface point defects of high-strength steel continuous annealing based on water cooling process according to claim 1, characterized in that: The method for obtaining the joint response interval is: For each type of monitoring data, a sequence of monitoring data at each collection moment in time order is used as a monitoring data sequence of each type of monitoring data, and a difference calculation result between each element in the monitoring data sequence and the preset standard monitoring data is calculated respectively, and a sequence composed of the difference calculation results is used as a deviation data sequence of each type of monitoring data; The deviation data sequence of each type of monitoring data is used as each row element in the matrix, and the deviation data sequences of all types of monitoring data together form a deviation data matrix; The deviation data matrix is ​​taken as input, and the Radon algorithm is used to map the deviation data matrix vertically to obtain the comprehensive deviation data sequence of the deviation data matrix. The abnormal data detection algorithm is used to obtain the mutation points in the comprehensive deviation data sequence. The collection time corresponding to the mutation point is used as the segmentation time point, and each time interval is divided based on the segmentation time point. The time period between each segmentation time point is used as each joint response interval.

7. The method for controlling surface point defects of high-strength steel continuous annealing based on water cooling process according to claim 6, characterized in that: The method for obtaining the annealing control deviation coefficient is: In the deviation data matrix, the matrix composed of all elements in each joint response interval is used as each sub-matrix of the deviation data matrix in each joint response interval; Calculate the rank of each sub-matrix of the deviation data matrix; For each submatrix of the deviation data matrix, the mean of all data in each row of data in the submatrix is ​​calculated, and the sequence composed of the mean of each row of data in the submatrix is ​​used as the deviation accumulation sequence of each submatrix; The calculation formula of the annealing control deviation coefficient is: ; In the formula, Indicates Annealing control deviation coefficient for the joint response interval; and Respectively represent and The cumulative sequence of deviations of the submatrices of the joint response intervals, express and Euclidean distance between them; and Respectively represent and The rank of the submatrix of joint response intervals, represents an exponential function with a natural constant as base; represents the number of joint response intervals.

8. The method for controlling surface point defects of high-strength steel continuous annealing based on water cooling process according to claim 7, characterized in that: The method for obtaining the feedback compensation error is: Each monitoring data in each joint response interval is used as the input of the entropy weight method to obtain the relative change weight of each monitoring data in each joint response interval; For each monitoring data, the product of the relative change weight of each monitoring data in each joint response interval and the annealing control deviation coefficient of the joint response interval is calculated to obtain the normalized results of all the products; the normalized results of the products are used as the feedback compensation deviation coefficient of the annealing processing parameter control of each monitoring data in each joint response interval; The calculation formula of the feedback compensation error is: ; In the formula, represents the feedback compensation error of the i-th monitoring data; represents the mean of all data of the i-th monitoring data in the p-th joint response interval; and They represent the feedback compensation deviation coefficients of the i-th monitoring data in the p-th and t-th joint response intervals respectively; represents the number of joint response intervals.

9. The method for controlling surface point defects of high-strength steel continuous annealing based on water cooling process according to claim 1, characterized in that: The step of adjusting each monitoring data during the annealing process includes: The mean value of the feedback compensation deviation coefficients of all monitoring data is used as the judgment threshold, and the mean value of the feedback compensation deviation coefficients of all monitoring data in the joint response interval where the current acquisition moment is located is compared with the judgment threshold. If it is greater than or equal to the judgment threshold, the feedback compensation error of the monitoring data is used as the input of the automatic control system programmable controller PLC; if it is less than the judgment threshold, the absolute value of the difference between the mean value of the feedback compensation deviation coefficients of all monitoring data in the joint response interval where the current acquisition moment is located and the judgment threshold is used as the input of the automatic control system programmable controller PLC, and each type of monitoring data adjusted during the annealing process is output.

10. The method for controlling surface point defects of high-strength steel continuous annealing based on water cooling process according to claim 1, characterized in that: The nickel layer thickness of the nickel plating is 15-20 mg / m².

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