A non-oriented silicon steel cold rolling process

Abstract

The present application relates to the field of steel rolling control technology, and specifically to a non-oriented silicon steel cold rolling process, which includes: desulfurizing molten iron to obtain desulfurized molten iron, performing RH refining on the desulfurized molten iron to obtain refined molten steel, adding cerium-containing alloy to the refined molten steel to obtain treated molten steel; performing continuous casting, hot rolling, and pickling on the treated molten steel to obtain hot-rolled strip steel; using a five-stand cold rolling mill to perform cold rolling on the hot-rolled strip steel to obtain each suspected forward slip variation interval; calculating the forward slip significance value and forward slip hazard degree of each suspected forward slip variation interval; obtaining the frame tension adjustment index, using a PI control algorithm to control the tension, and obtaining cold-rolled silicon steel; performing annealing treatment on the cold-rolled silicon steel, performing coil cooling treatment, obtaining the treated strip steel, and obtaining non-oriented silicon steel through coiling. The present application improves the production efficiency of non-oriented silicon steel.

Description

Technical Field

[0001] The present application relates to the technical field of steel rolling control, and in particular to a non-oriented silicon steel cold rolling process. Background Art

[0002] Silicon steel is also called electrical steel. The grains of non-oriented silicon steel are randomly oriented in the strip after deformation and annealing. It has excellent magnetic properties and is widely used in new energy vehicles, high-efficiency industrial motors, high-end home appliances and other fields. It is an indispensable material for the electronics, power and military industries. Compared with hot-rolled plates, the non-oriented silicon steel obtained after cold rolling has better surface quality. The quality of the strip cutting is unstable, and the cold rolling unit needs to control the tension to effectively prevent the rolled piece from running off and ensure the quality of the cold rolling of non-oriented silicon steel.

[0003] At present, the tension control of the cold rolling unit adopts direct tension control, which obtains the actual tension value by installing a tension machine at the entrance of the cold rolling mill, and uses the control algorithm for real-time adjustment, but it is not conducive to the stable operation of the tension control system. The appropriate forward slip value is the prerequisite for ensuring the stable rolling of non-oriented silicon steel. The edge cutting quality of hot-rolled strip is unstable. In the actual cold rolling process of the cold rolling unit, cracks and brittle fractures are prone to occur, and the tension needs to be reduced. It is difficult to identify the actual situation of the rolling forward slip value of the frame based on the working condition of the strip after the frame rolling process, and to dynamically control the frame tension. Summary of the invention

[0004] In order to solve the above technical problems, the present application provides a non-oriented silicon steel cold rolling process to solve the existing problems.

[0005] A non-oriented silicon steel cold rolling process of the present application adopts the following technical solution:

[0006] An embodiment of the present application provides a non-oriented silicon steel cold rolling process, the process comprising the following steps:

[0007] S10, desulfurizing the molten iron to obtain desulfurized molten iron, performing RH refining on the desulfurized molten iron to obtain refined molten steel, adding a cerium-containing alloy to the refined molten steel, stirring, and obtaining treated molten steel;

[0008] S20, continuously casting, hot rolling, and pickling the treated molten steel to complete the pre-cold rolling treatment of the non-oriented silicon steel and obtain hot-rolled strip steel;

[0009] S30, using a five-stand cold rolling mill to perform cold rolling on the hot-rolled strip, and using a tension control module to perform tension control to obtain cold-rolled silicon steel;

[0010] The process of using the tension control module to perform tension control is as follows:

[0011] S31, obtaining tension data, vibration signals, linear velocity signals, and point cloud data sets at each sampling moment, and constructing tension sequences, vibration sequences, and linear velocity sequences for each preset sub-time period;

[0012] S32, obtaining each suspected forward slip change interval based on the difference between each element in the linear velocity sequence and the average of all elements;

[0013] S33, based on the correlation between the difference of the local linear velocity sequence and the absolute value of the corresponding local vibration sequence, and the difference between each element in the linear velocity sequence and the average of all elements, obtaining the forward slip significance value of each suspected forward slip change interval;

[0014] S34, based on the distribution of the Y coordinates of the point cloud data set and the clustering result, obtaining the forward slip hazard degree of each suspected forward slip change interval;

[0015] S35, obtaining a rack tension adjustment index based on the forward slip significance value and the forward slip hazard degree, and controlling the tension by using a PI control algorithm in combination with the rack tension adjustment index;

[0016] S40, annealing the cold-rolled silicon steel, performing coil cooling treatment, obtaining the processed strip steel, and coiling to obtain non-oriented silicon steel.

[0017] Furthermore, the mass ratio of the chemical components of the cerium-containing alloy is Ce: 60-100%, Si: 0-30%, and Mn: 0-10%.

[0018] Furthermore, the mass percentages of the chemical elements in the treated molten steel are: Si: 2.5-3%, Al: 0.10-0.5%, Mn: 0.10-0.5%, [C+Ti+N+O+S]: 80-100 ppm, Ce: 0.0025-0.0075%.

[0019] Furthermore, the continuous casting temperature is 1500°C.

[0020] Furthermore, the pickling temperature is 85°C.

[0021] Furthermore, the use of a five-stand cold rolling mill to cold-roll the hot-rolled strip includes: the roughness of the rolls of the five-stand cold rolling mill is 0.22 μm, the diameter of the rolls is 360 mm, and the temperature of the rolling emulsion of the five-stand cold rolling mill is 55° C.

[0022] Furthermore, the method for obtaining the suspected forward slip change interval is:

[0023] The average of all linear speeds in each linear speed sequence is calculated as the linear speed average, and the difference between the linear speed at each sampling moment in the linear speed sequence and the linear speed average is calculated as the linear speed difference at each sampling moment;

[0024] All linear velocity differences greater than 0 are used as inputs of the Otsu method, and the segmentation threshold is output. The sampling time of the linear velocity difference greater than the segmentation threshold is recorded as the suspected forward slip time.

[0025] In ascending order of time, take the first suspected forward slip moment as the starting point, and count the occurrence frequency of the suspected forward slip moments within the preset time after the starting point. When the occurrence frequency is greater than the preset frequency, record the time interval composed of the starting point and the preset time after the starting point as the suspected forward slip change interval, and take the first suspected forward slip moment after the suspected forward slip change interval as the next starting point; when the occurrence frequency is less than or equal to the preset frequency, take the first suspected forward slip moment after the first starting point as the next starting point. When the next starting point does not exist or the time after the starting point is less than the preset time, stop obtaining the suspected forward slip change intervals until all the suspected forward slip change intervals are obtained.

[0026] Further, the method for obtaining the forward slip significance value is:

[0027] A linear velocity subsequence whose time interval is the suspected forward slip change interval is obtained from the linear velocity sequence, and a differential sequence of the linear velocity subsequence is calculated as the linear velocity differential sequence of the suspected forward slip change interval; a vibration subsequence whose time interval is the suspected forward slip change interval is obtained from the vibration sequence, and a sequence composed of the absolute values ​​of each vibration signal of the vibration subsequence is used as the amplitude sequence of the suspected forward slip change interval;

[0028] Calculate the correlation coefficient between the linear velocity difference sequence and the amplitude sequence of the suspected forward slip change interval as the change correlation coefficient of each suspected forward slip change interval;

[0029] The calculation formula of the forward slip significance value is: ; Where B is the forward slip significance value of each suspected forward slip change interval; is the linear velocity difference at the i-th suspected forward slip moment in each suspected forward slip variation interval, is the number of all suspected forward slip moments in the suspected forward slip variation interval, is the correlation coefficient of the change of the suspected forward slip change interval.

[0030] Furthermore, the method for obtaining the forward slip hazard degree is:

[0031] For the point cloud data set at the i-th suspected forward slip moment in each suspected forward slip change interval, the standard deviation of the Y coordinate values ​​of all point cloud data in the point cloud data set is calculated, recorded as the first standard deviation of the i-th suspected forward slip moment in the suspected forward slip change interval, the Y coordinate values ​​of all point cloud data in the point cloud data set are used as the input of the clustering algorithm, the mean of the Y coordinates of the point cloud data in each clustering cluster is calculated as the first mean of each clustering cluster, and the number of point cloud data in the clustering cluster with the smallest first mean is recorded as the first point cloud number at the i-th suspected forward slip moment in the suspected forward slip change interval;

[0032] The calculation formula of the forward slip hazard degree is: ; In the formula, is the forward slip hazard degree of each suspected forward slip change interval; is the number of all point cloud data in the point cloud data set at the i-th suspected forward slip moment in each suspected forward slip change interval, is the number of the first point cloud at the i-th suspected forward slip moment in each suspected forward slip variation interval; is the first standard deviation of the i-th suspected forward slip moment in each suspected forward slip variation interval.

[0033] Further, the rack tension adjustment index is obtained, and the tension is controlled by using a PI control algorithm in combination with the rack tension adjustment index, including:

[0034] For each suspected forward slip variation interval, the product of the forward slip significance value and the forward slip hazard degree of the suspected forward slip variation interval is calculated as the first product; the normalized value of the sum of the first products of all suspected forward slip variation intervals is calculated as the rack tension adjustment index;

[0035] When the rack tension adjustment index is greater than or equal to the preset adjustment threshold, the tension target value is calculated using the following formula: ; In the formula, is the tension target value, is the rack tension adjustment index, is the mean of all tension values ​​in the tension sequence, is a preset constant;

[0036] The tension value and the tension target value of each preset sub-time period are used as the input of the PI control algorithm, and the direct tension torque adjustment amount is output to control the tension.

[0037] This application has at least the following beneficial effects:

[0038] The present application utilizes the correlation between the linear velocity differential sequence at the strip rolling exit and the rack amplitude sequence to evaluate the credibility of the data collected within the suspected forward slip variation interval. Its beneficial effect is to avoid the complex on-site conditions of cold rolling of non-oriented silicon steel, the linear velocity value obtained by the laser velocimeter may have noise interference, and it is difficult to evaluate the rolling forward slip value conditions.

[0039] The present application utilizes the fact that the degree of harm caused by the change in slip value before rolling to non-oriented silicon steel with different mechanical properties is not the same. Based on the crack characteristics and thickness uniformity of the strip after rolling, the accuracy of the subsequent stand 1# tension control is improved, and the production efficiency of non-oriented silicon steel is improved while ensuring the surface quality of the strip. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] 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 paying any creative work.

[0041] Figure 1 A flow chart of the steps of a non-oriented silicon steel cold rolling process provided in this application;

[0042] Figure 2 A schematic diagram of data collection for rack 1# provided in one embodiment of the present application;

[0043] Figure 3 A schematic diagram of a cold rolling mill provided in one embodiment of the present application;

[0044] Figure 4 A schematic diagram of three-dimensional point cloud data provided for one embodiment of the present application. DETAILED DESCRIPTION

[0045] In order to further explain the technical means and effects adopted by the present application to achieve the predetermined application purpose, the following is a detailed description of the specific implementation method, structure, characteristics and effects of a non-oriented silicon steel cold rolling process proposed in the present application 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.

[0046] 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.

[0047] The specific scheme of the non-oriented silicon steel cold rolling process provided by the present application is described in detail below with reference to the accompanying drawings.

[0048] An embodiment of the present application provides a non-oriented silicon steel cold rolling process. Specifically, the following non-oriented silicon steel cold rolling process is provided. Figure 1 , the process comprises the following steps:

[0049] Step S10, desulfurizing the molten iron to obtain desulfurized molten iron, performing RH refining on the desulfurized molten iron to obtain refined molten steel, adding a cerium-containing alloy to the refined molten steel, stirring, and obtaining treated molten steel.

[0050] The molten iron is desulfurized to obtain desulfurized molten iron, and RH refining is performed to obtain refined molten steel. After the RH refining is completed, a cerium-containing alloy is added within 1 to a preset sub-time period, and the mixture is stirred to obtain treated molten steel, wherein the mass percentages of various chemical elements in the treated molten steel are: Si: 2.5-3%, Al: 0.10-0.5%, Mn: 0.10-0.5%, [C+Ti+N+O+S]: 80-100ppm, Ce: 0.0025-0.0075%, and the rest are Fe and unavoidable impurities. In this embodiment, the mass percentages of the chemical elements in the molten steel after treatment are: Si: 2.5%, Al: 0.10%, Mn: 0.10%, [C+Ti+N+O+S]: 80ppm, Ce: 0.0025%; in the second embodiment of the present application, the mass percentages of the chemical elements in the molten steel after treatment are: Si: 3%, Al: 0.5%, Mn: 0.5%, [C+Ti+N+O+S]: 100ppm, Ce: 0.0075%; in the third embodiment of the present application, the mass percentages of the chemical elements in the molten steel after treatment are: Si: 2.6%, Al: 0.2%, Mn: 0.2%, [C+Ti+N+O+S]: 90ppm, Ce: 0.0040%.

[0051] Among them, the mass ratio of each chemical component contained in the cerium-containing alloy is: Ce:Si:Mn=(60~100%):(0~30%):(0~10%), the mass ratio of each chemical component contained in the cerium alloy in this embodiment is: 6.5:2.5:1, in the second embodiment of the present application, the mass ratio of each chemical component contained in the cerium alloy is 7:2:1, in the third embodiment of the present application, the mass ratio of each chemical component contained in the cerium alloy is 7.5:1.5:1, the addition amount of the cerium-containing alloy is 0.5~1kg / t, and the stirring time is 2~10 minutes; the Ce element can be used as a desulfurizer or deoxidizer in the production process of non-oriented silicon steel, reduce the content of impurity elements, and combine the O and S element inclusions in the molten steel with the Ce element to form a high melting point compound.

[0052] Step S20, continuously casting, hot rolling and pickling the treated molten steel to complete the pre-cold rolling treatment of non-oriented silicon steel and obtain hot-rolled strip steel.

[0053] In the embodiment, the casting temperature during the continuous casting process is 1500° C., the continuous casting time is 30 to 60 minutes, and the pulling speed is controlled to be 2.5 to 4.5 m / min.

[0054] The starting rolling temperature is controlled at 950-1200°C, the final rolling temperature is 750-900°C, the coiling temperature is 400-700°C, and the steel is air-cooled to room temperature after coiling to obtain a hot-rolled sheet of non-oriented silicon steel.

[0055] The hot-rolled plate of non-oriented silicon steel was pickled by push-pull pickling, the pickling temperature was 85° C., and the pickling speed was 50 m / min.

[0056] Step S30, using a five-stand cold rolling mill to perform cold rolling on the hot-rolled steel strip, using a tension control module to perform tension control, and obtaining cold-rolled silicon steel.

[0057] The hot-rolled strip is subjected to cold rolling process by using a five-stand cold rolling mill. Specifically, the five-stand cold rolling mill is arranged in sequence according to the running direction of the non-oriented silicon steel, namely, stand 1# 1, stand 2# 2, stand 3# 3, stand 4# 4, and stand 5# 5.

[0058] First, the temperature of the electromagnetic induction heating furnace at the entrance of the five-stand cold rolling mill is set to 95-105°C. Since the five-stand cold rolling mill performs cold rolling on hot-rolled strip, it is necessary to control the cold rolling parameters of the five-stand cold rolling mill, wherein the roughness of the rolls of the five-stand cold rolling mill is 0.22μm, the diameter of the rolls is 360mm, and the temperature of the rolling emulsion of the five-stand cold rolling mill is 55°C. Then, the reduction rate of the 1# stand in the five-stand cold rolling mill is 22-25%, the reduction rate of the 2# stand is 35%-40%, the reduction rate of the 3# stand is 25-35%, the reduction rate of the 4# stand is 25-23%, and the reduction rate of the 5# stand is 20-22%. The rolling speed of the 1# stand in the five-stand cold rolling mill is 2.5-3m / s, and the rolling speeds of the 2# to 5# stands are 5-6m / s.

[0059] Finally, the tension of the 1# frame is 6~8kN, the tension of the 2# frame is 15~25kN, and the tension of the 3#~5# frames is 10~15kN. In the actual production process of non-oriented silicon steel, the quality of strip trimming is unstable and the thinning of the hot rolled edge is unstable. Under the front tension of the 1# frame, the non-oriented silicon steel is prone to cracks and brittle fractures. Therefore, in the actual cold rolling process, the tension control module needs to be used to control the tension of the 1# frame to prevent the brittle fracture of the non-oriented silicon steel.

[0060] The process of using the tension control module to perform tension control is as follows, wherein the tension control module includes: a collection unit, a calculation unit and a control unit:

[0061] Step S31, obtaining the tension data, strip line speed signal, and point cloud data set at each sampling moment, and constructing the tension sequence and vibration sequence of each preset sub-time period.

[0062] Collection unit:

[0063] Figure 2 This is a schematic diagram of data collection for rack 1#. Figure 2 Among them, 1 is 1# frame, 2 is a tensiometer, 3 is a laser velocimeter, 4 is a three-dimensional laser scanner, 5 is 2# frame, and 6 is strip steel, i.e., non-oriented silicon steel.

[0064] In order to avoid the high sampling frequency of the tension meter, which causes the inner loop of the torque control of the 1# frame to be constantly adjusted, which is not conducive to the stable operation of the tension module, and to prevent the tension of the 1# frame from fluctuating and having poor stability, which seriously affects the quality of the finished non-oriented silicon steel product. This application configures a tension meter on the 1# frame to measure the inlet tension (front tension) of the 1# frame and obtain the tension data of the 1# frame. The sampling frequency of the tension meter is 10Hz.

[0065] In the present application, an acceleration sensor is installed on the top of the 1# frame to measure the frame vibration signal in the vertical direction of the 1# frame, and the sampling frequency of the acceleration sensor is 100Hz; a laser velocimeter is placed behind the 1# frame to measure the linear speed signal of the strip after cold rolling of the 1# frame, and the sampling frequency of the laser velocimeter is 100Hz; the center position of the contact surface between the upper and lower rollers of the 1# frame and the strip is used as the rolling position of the 1# frame, and a three-dimensional laser scanner is arranged 0.3m behind the rolling position of the 1# frame to measure the thickness of the strip after cold rolling of the 1# frame, and the sampling frequency of the three-dimensional laser scanner is 100Hz.

[0066] Construct a preset sub-time period. In this embodiment, the value of the preset sub-time period is 5 minutes. The implementer can select other values ​​according to actual conditions. The acquisition unit uses the measurement value of the tensiometer in the preset sub-time period as a tension sequence, the acquisition unit uses the measurement value of the acceleration sensor in the preset sub-time period as a vibration sequence, the measurement value of the laser velocimeter in the preset sub-time period as a linear velocity sequence, and the point cloud data set at each sampling time obtained by the three-dimensional laser scanner in the preset sub-time period as a point cloud data set.

[0067] The acquisition unit transmits the tension value of the 1# frame obtained by the tension meter to the control unit in real time through the data line.

[0068] The acquisition unit transmits the tension sequence of the 1# frame obtained by the tension meter to the control unit through the data line at every preset sub-time period. The acquisition unit transmits the vibration sequence, line speed sequence, and point cloud data set to the calculation unit through the data line at every preset sub-time period. The calculation unit is used to process the vibration sequence, line speed sequence, and point cloud data set to obtain the frame tension adjustment index, which is used for the control unit to control the tension of the 1# frame.

[0069] Step S32: obtaining each suspected forward slip variation interval based on the difference between each element in the linear velocity sequence and the average of all elements.

[0070] Computational Unit:

[0071] In the actual process of rolling non-oriented silicon steel in the cold rolling mill, when the outlet speed of the strip is greater than the linear speed of the stand roll during cold rolling, the strip tends to slide forward relative to the roll. The forward slip is the result of the longitudinal extension of the strip and the friction during rolling. Figure 3 As shown, Figure 3 The schematic diagram of cold rolling mill is shown in Figure 3 In the figure, 6 is the strip steel, i.e. non-oriented silicon steel, 7 is the upper and lower rollers, and 8 is the front slip zone. When the tension decreases during the cold rolling process, the exit speed of the strip steel will decrease during the cold rolling process, and the front slip value will also decrease. The appropriate front slip value is the premise for ensuring the stable rolling of non-oriented silicon steel, and is also an important factor in improving the production efficiency of non-oriented silicon steel. Therefore, the degree of tension reduction must take into account the size of the rolling front slip value.

[0072] Specifically, the line speed can reflect the exit speed of the strip during cold rolling. For each preset sub-time period, the average of all line speeds in the line speed sequence is calculated as the line speed average, and the difference between the line speed at each sampling moment in the line speed sequence and the line speed average is calculated as the line speed difference at each sampling moment; the larger the line speed difference, the greater the degree of forward slip during rolling; otherwise, the degree of forward slip during rolling is decreasing.

[0073] Furthermore, all linear velocity differences greater than 0 are used as inputs of the Otsu method, and a segmentation threshold is output, and the sampling time of the linear velocity difference greater than the segmentation threshold is recorded as the suspected forward slip time. The Otsu method is a well-known technology and will not be described in detail here.

[0074] Since the increase of the front slip value during rolling is a dynamic process, the present application obtains all the suspected front slip change intervals of the strip rolling through an iterative method, and each suspected front slip change interval corresponds to a time series interval in which the front slip value dynamically increases.

[0075] Specifically, the iteration method is: in ascending order of time, take the first suspected forward slip moment as the starting point, count the frequency of occurrence of the suspected forward slip moment within the preset time length after the starting point, when the frequency of occurrence is greater than the preset frequency, record the time interval composed of the starting point and the preset time length after the starting point as the suspected forward slip change interval, and take the first suspected forward slip moment after the suspected forward slip change interval as the next starting point; when the frequency of occurrence is less than or equal to the preset frequency, take the first suspected forward slip moment after the first starting point as the next starting point, and so on, until all suspected forward slip change intervals are obtained, which will not be repeated here. The iteration stop rule is: when the next starting point does not exist or the moment after the starting point is less than the preset time length, stop the iteration. In this embodiment, the value of the preset time length is 0.5s, and the value of the preset frequency is 0.6. The implementer can select other values ​​according to actual conditions.

[0076] Step S33, based on the correlation between the difference of the local linear velocity sequence and the absolute value of the local vibration sequence, and the difference between each element in the linear velocity sequence and the average of all elements, the forward slip significance value of each suspected forward slip change interval is obtained.

[0077] The on-site working conditions of cold rolling of non-oriented silicon steel are complex, and the line speed value obtained by the laser velocimeter may be subject to noise interference, resulting in poor accuracy in judging the pre-rolling slip value based solely on the line speed value. At the same time, when the pre-rolling slip value of the cold rolling mill just begins to change, the vibration amplitude of the 1# frame diverges as the pre-rolling slip value increases. When the line speed is in a stable stage, the vibration amplitude of the 1# frame is also relatively stable. By analyzing the correlation between the line speed signal and the vibration signal, the degree of noise interference in the suspected pre-slip change range can be reflected, and the authenticity and credibility of the collected data can be evaluated.

[0078] A linear velocity subsequence whose time interval is a suspected forward slip change interval is obtained from the linear velocity sequence, and a differential sequence of the linear velocity subsequence is calculated as the linear velocity differential sequence of the suspected forward slip change interval. A vibration subsequence whose time interval is a suspected forward slip change interval is obtained from the vibration sequence, and a sequence composed of the absolute values ​​of each vibration signal of the vibration subsequence is used as the amplitude sequence of the suspected forward slip change interval. The present application uses the correlation between the changes of the linear velocity differential sequence and the amplitude sequence to evaluate the credibility of the collected data in the suspected forward slip change interval.

[0079] In order to reflect the change correlation of any suspected forward slip change interval, the change correlation coefficient is calculated by calculating the correlation coefficient between the linear velocity difference sequence and the amplitude sequence of the suspected forward slip change interval as the change correlation coefficient A of each suspected forward slip change interval. In this embodiment, the Pearson correlation coefficient is selected as the calculation method of the correlation coefficient, and the implementer can select other correlation coefficients according to actual conditions.

[0080] Specifically, when the correlation between the vibration signal and the linear velocity signal is more significant, The larger it is, the less the linear velocity signal in the suspected forward slip variation interval is shielded by noise from the detailed features of the rolling forward slip. The suspected forward slip variation interval should be able to judge the rolling forward slip value.

[0081] The higher the exit speed of the strip during cold rolling, the greater the front slip value. At this time, in order to ensure the uniformity and mechanical properties of non-oriented silicon steel rolling, the tension of the 1# stand should be adjusted in time. Based on the above analysis, the front slip significance value of each suspected front slip change interval is constructed. , the calculation formula is: ; Where B is the forward slip significance value of each suspected forward slip change interval; is the linear velocity difference at the i-th suspected forward slip moment in each suspected forward slip variation interval, is the number of all suspected forward slip moments in the suspected forward slip variation interval, is the correlation coefficient of the change of the suspected forward slip change interval.

[0082] It should be noted that when the correlation coefficient changes The larger the value is, the more detailed characteristics of rolling forward slip the linear velocity signal in the suspected forward slip variation interval has, the higher the signal credibility is, and the greater the weight should be given. The larger the value is, the more the exit speed of the strip during cold rolling in the suspected forward slip variation range continues to increase, and the more it can be shown that the increase in the forward slip value leads to the increase in the line speed, and the more obvious the phenomenon of large changes in the rolling forward slip value is. The bigger.

[0083] Step S34, based on the distribution of the Y coordinates of the point cloud data set and the clustering result, the forward slip hazard degree of each suspected forward slip change interval is obtained.

[0084] Different raw materials added to non-oriented silicon steel will result in different mechanical properties of non-oriented silicon steel, such as strength, and the degree of harm to non-oriented silicon steel caused by the change of slip value before rolling is also different. The quality of hot-rolled strip trimming is unstable. In the actual cold rolling process of the cold rolling unit, the degree of harm to non-oriented silicon steel caused by the change of slip value before rolling is relatively high. If the rack 1# has a high tension and a fast production rate, but the thickness of the non-oriented silicon steel is uneven, or even cracks and brittle fractures occur, the production risk is extremely high, and the control module should be used to reduce the tension of rack 1#.

[0085] In the point cloud data obtained by 3D laser scanner, Figure 4 As shown, Figure 4 is a schematic diagram of 3D point cloud data. Figure 4In the figure, the X-axis represents the length of the strip (cm), that is, the direction of movement of the strip, the Y-axis represents the width of the strip (cm), and the Z-axis represents the thickness of the strip (mm). The thicker the strip, the higher the Z coordinate value.

[0086] Furthermore, once a crack appears in the strip, the Y coordinate value of the strip point cloud data is significantly reduced, and the Y coordinate value caused by uneven thickness is generally larger than the Y coordinate value of the crack point cloud data. Taking the point cloud data set of the i-th suspected forward slip moment in each suspected forward slip change interval as an example, the standard deviation of the Y coordinate values ​​of all point cloud data in the point cloud data set is calculated and recorded as the first standard deviation of the i-th suspected forward slip moment in the suspected forward slip change interval. , the Y coordinate values ​​of all point cloud data in the point cloud data set are used as the input of the K-means clustering algorithm. In this embodiment, k is set to 2, and two clusters are obtained. The mean of the Y coordinates of the point cloud data in each cluster is calculated as the first mean of each cluster. The number of point cloud data in the cluster with the smallest first mean is recorded as the first point cloud number at the i-th suspected forward slip moment in the suspected forward slip change interval. .

[0087] Based on the above analysis, in order to analyze the possibility of cracks in the strip, the forward slip hazard degree C of each suspected forward slip variation interval is calculated as follows: ; In the formula, is the forward slip hazard degree of each suspected forward slip change interval; is the number of all point cloud data in the point cloud data set at the i-th suspected forward slip moment in each suspected forward slip change interval, is the number of the first point cloud at the i-th suspected forward slip moment in each suspected forward slip variation interval; is the first standard deviation of the i-th suspected forward slip moment in each suspected forward slip variation interval.

[0088] It should be noted that when The larger the value, the more uneven the thickness of the strip at the suspected forward slip moment. At the same time, when the Y coordinate value of the point cloud data is significantly lower and the number is larger, that is, The larger the value, the more likely the strip will crack when the forward slip is suspected. The crack caused by excessive forward slip is far more serious than the uneven thickness of the strip. The greater the forward slip hazard, the greater the forward slip hazard. The bigger.

[0089] Step S35, obtaining a rack tension adjustment index based on the forward slip significance value and the forward slip hazard degree, and using a PI control algorithm to control the tension in combination with the rack tension adjustment index.

[0090] During the actual rolling process of the cold rolling mill, the tension of stand 1# should be appropriately increased while ensuring the rolling quality of non-oriented silicon steel, so as to increase the exit speed of non-oriented silicon steel after rolling on stand 1#, thereby improving the production efficiency of the factory.

[0091] Based on the forward slip significance value and the forward slip hazard degree of each suspected forward slip change interval, the rack tension adjustment index is obtained to reflect the degree to which the rack 1# tension should be reduced. The calculation method is: for each suspected forward slip change interval, the product of the forward slip significance value and the forward slip hazard degree of the suspected forward slip change interval is calculated as the first product; the normalized value of the sum of the first products of all suspected forward slip change intervals is calculated as the rack tension adjustment index.

[0092] Among them, the larger the current slip significance value is, the more significant the phenomenon of large changes in the pre-rolling slip value is. During cold rolling, the exit speed of the strip is always high and unstable. At the same time, the greater the pre-slip hazard is, the greater the degree of damage to the surface quality of the strip is. In this case, stand 1# should use a smaller tension to ensure the rolling quality of the strip.

[0093] The calculation unit transmits the rack tension adjustment index to the control unit via a data line.

[0094] Control unit:

[0095] When the rack tension adjustment index is less than the preset adjustment threshold, it means that the strip exit speed after rack 1# rolling does not increase significantly, the strip thickness after cold rolling is uniform, and the surface quality is excellent, and there is no need to adjust the tension of rack 1#; in this embodiment, the preset adjustment threshold value is 0.4, and the implementer can select other thresholds according to actual conditions.

[0096] When the rack tension adjustment index is greater than or equal to the preset adjustment threshold, the tension target value of rack 1# can be obtained by the following formula:

[0097] This indicates that the forward slip value obtained by the tension of stand 1# is high, which may easily lead to an increase in the strip rolling exit speed after rolling on stand 1# and poor surface quality of the strip after cold rolling. Therefore, it should be adjusted by the following formula: ; In the formula, is the tension target value, is the rack tension adjustment index, is the mean of all tension values ​​in the tension sequence, is a preset constant, and in this embodiment, its value is 1.3. The implementer may select other values ​​according to the actual situation.

[0098] It should be noted that when The larger it is, the higher the forward slip value obtained by the tension of stand 1# is, which may easily lead to an increase in the rolling exit speed of the strip after rolling on stand 1# and uneven thickness of the strip after cold rolling. In order to ensure the surface quality of the strip after cold rolling, the tension of stand 1# should be reduced.

[0099] This application obtains a rack tension adjustment index every preset sub-time period, and uses the PI control algorithm to control the tension of rack 1#, specifically: the initial parameters of the proportional term and the integral term in the PI control algorithm are set to 0.5 and 0.45 respectively, and the tension value transmitted in real time by the acquisition unit is compared with the tension target value to obtain the tension error value, and the tension error value is calculated by the above-mentioned PI control algorithm to obtain the direct tension torque adjustment amount of rack 1#, and the tension of rack 1# is controlled to ensure the surface quality of the strip after cold rolling. The PI control algorithm is a well-known technology and will not be described in detail here.

[0100] Step S40, annealing the cold-rolled silicon steel, performing coil cooling treatment, obtaining the processed strip steel, and coiling to obtain non-oriented silicon steel.

[0101] After the cold rolling process, the cold-rolled silicon steel is annealed, the annealing temperature is controlled at 1000-1200℃, the holding time is controlled at 1-3 minutes, and then the coil is cooled to below 550℃ to obtain a high-strength strip steel. The annealing temperature is 800-1050℃, the annealing time is 0.5-3min; the steel coil is cooled to below 550-650℃, and then coiled to obtain non-oriented silicon steel.

[0102] 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. And the above-mentioned specific embodiments of this specification 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.

[0103] 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.

[0104] 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 non-oriented silicon steel cold rolling process, characterized in that: The process includes the following steps: S10, desulfurizing the molten iron to obtain desulfurized molten iron, performing RH refining on the desulfurized molten iron to obtain refined molten steel, adding a cerium-containing alloy to the refined molten steel, stirring, and obtaining treated molten steel; S20, continuously casting, hot rolling, and pickling the treated molten steel to complete the pre-cold rolling treatment of the non-oriented silicon steel and obtain hot-rolled strip steel; S30, using a five-stand cold rolling mill to perform cold rolling on the hot-rolled strip, and using a tension control module to perform tension control to obtain cold-rolled silicon steel; The process of using the tension control module to perform tension control is as follows: S31, obtaining tension data, vibration signals, linear velocity signals, and point cloud data sets at each sampling moment, and constructing tension sequences, vibration sequences, and linear velocity sequences for each preset sub-time period; S32, obtaining each suspected forward slip change interval based on the difference between each element in the linear velocity sequence and the average of all elements; S33, based on the correlation between the difference of the local linear velocity sequence and the absolute value of the corresponding local vibration sequence, and the difference between each element in the linear velocity sequence and the average of all elements, obtaining the forward slip significance value of each suspected forward slip change interval; S34, based on the distribution of the Y coordinates of the point cloud data set and the clustering result, obtaining the forward slip hazard degree of each suspected forward slip change interval; S35, obtaining a rack tension adjustment index based on the forward slip significance value and the forward slip hazard degree, and controlling the tension by using a PI control algorithm in combination with the rack tension adjustment index; S40, annealing the cold-rolled silicon steel, performing coil cooling treatment, obtaining the processed strip steel, and coiling to obtain non-oriented silicon steel; The obtaining of the rack tension adjustment index and the use of a PI control algorithm to control the tension in combination with the rack tension adjustment index include: For each suspected forward slip variation interval, the product of the forward slip significance value and the forward slip hazard degree of the suspected forward slip variation interval is calculated as the first product; the normalized value of the sum of the first products of all suspected forward slip variation intervals is calculated as the rack tension adjustment index; When the rack tension adjustment index is greater than or equal to the preset adjustment threshold, the tension target value is calculated using the following formula: ; In the formula, is the tension target value, is the rack tension adjustment index, is the mean of all tension values ​​in the tension sequence, is a preset constant; The tension value and the tension target value of each preset sub-time period are used as the input of the PI control algorithm, and the direct tension torque adjustment amount is output to control the tension.

2. A non-oriented silicon steel cold rolling process as claimed in claim 1, characterized in that: The mass ratio of the chemical components of the cerium-containing alloy is Ce: 60-100%, Si: 0-30%, and Mn: 0-10%.

3. The non-oriented silicon steel cold rolling process according to claim 1, characterized in that: The mass percentages of the chemical elements in the treated molten steel are: Si: 2.5-3%, Al: 0.10-0.5%, Mn: 0.10-0.5%, [C+Ti+N+O+S]: 80-100ppm, Ce: 0.0025-0.0075%.

4. A non-oriented silicon steel cold rolling process as claimed in claim 1, characterized in that: The continuous casting temperature is 1500°C.

5. The non-oriented silicon steel cold rolling process according to claim 1, characterized in that: The pickling temperature is 85°C.

6. The non-oriented silicon steel cold rolling process according to claim 1, characterized in that: The method of using a five-stand cold rolling mill to cold-roll the hot-rolled strip comprises: the roughness of the rolls of the five-stand cold rolling mill is 0.22 μm, the diameter of the rolls is 360 mm, and the temperature of the rolling emulsion of the five-stand cold rolling mill is 55° C.

7. The non-oriented silicon steel cold rolling process according to claim 1, characterized in that: The method for obtaining the suspected forward slip change interval is: The average of all linear speeds in each linear speed sequence is calculated as the linear speed average, and the difference between the linear speed at each sampling moment in the linear speed sequence and the linear speed average is calculated as the linear speed difference at each sampling moment; All linear velocity differences greater than 0 are used as inputs of the Otsu method, and the segmentation threshold is output. The sampling time of the linear velocity difference greater than the segmentation threshold is recorded as the suspected forward slip time. In ascending order of time, take the first suspected forward slip moment as the starting point, and count the occurrence frequency of the suspected forward slip moments within the preset time after the starting point. When the occurrence frequency is greater than the preset frequency, record the time interval composed of the starting point and the preset time after the starting point as the suspected forward slip change interval, and take the first suspected forward slip moment after the suspected forward slip change interval as the next starting point; when the occurrence frequency is less than or equal to the preset frequency, take the first suspected forward slip moment after the first starting point as the next starting point. When the next starting point does not exist or the time after the starting point is less than the preset time, stop obtaining the suspected forward slip change intervals until all the suspected forward slip change intervals are obtained.

8. A non-oriented silicon steel cold rolling process as claimed in claim 7, characterized in that: The method for obtaining the forward slip significance value is as follows: A linear velocity subsequence whose time interval is the suspected forward slip change interval is obtained from the linear velocity sequence, and a differential sequence of the linear velocity subsequence is calculated as the linear velocity differential sequence of the suspected forward slip change interval; a vibration subsequence whose time interval is the suspected forward slip change interval is obtained from the vibration sequence, and a sequence composed of the absolute values ​​of each vibration signal of the vibration subsequence is used as the amplitude sequence of the suspected forward slip change interval; Calculate the correlation coefficient between the linear velocity difference sequence and the amplitude sequence of the suspected forward slip change interval as the change correlation coefficient of each suspected forward slip change interval; The calculation formula of the forward slip significance value is: ; Where B is the forward slip significance value of each suspected forward slip change interval; is the linear velocity difference at the i-th suspected forward slip moment in each suspected forward slip variation interval, is the number of all suspected forward slip moments in the suspected forward slip variation interval, is the correlation coefficient of the change of the suspected forward slip change interval.

9. A non-oriented silicon steel cold rolling process as claimed in claim 7, characterized in that: The method for obtaining the forward slip hazard degree is as follows: For the point cloud data set at the i-th suspected forward slip moment in each suspected forward slip change interval, the standard deviation of the Y coordinate values ​​of all point cloud data in the point cloud data set is calculated, recorded as the first standard deviation of the i-th suspected forward slip moment in the suspected forward slip change interval, the Y coordinate values ​​of all point cloud data in the point cloud data set are used as the input of the clustering algorithm, the mean of the Y coordinates of the point cloud data in each clustering cluster is calculated as the first mean of each clustering cluster, and the number of point cloud data in the clustering cluster with the smallest first mean is recorded as the first point cloud number at the i-th suspected forward slip moment in the suspected forward slip change interval; The calculation formula of the forward slip hazard degree is: ; In the formula, is the forward slip hazard degree of each suspected forward slip change interval; is the number of all point cloud data in the point cloud data set at the i-th suspected forward slip moment in each suspected forward slip change interval, is the number of the first point cloud at the i-th suspected forward slip moment in each suspected forward slip variation interval; is the first standard deviation of the i-th suspected forward slip moment in each suspected forward slip variation interval.

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