A method for calculating and counting the deviation of rolling force in hot continuous rolling strip steel

Abstract

The application provides a hot continuous rolling strip steel rolling force deviation prediction calculation and statistics method, wherein the method comprises the following steps: extracting the required related data in a data source into a rolling force deviation table; calculating the time interval and the rolling force deviation between each rack by using the rolling force deviation table; statistically inputting the rolling process data and the measured rolling force deviation of the steel, displaying the corresponding steel name, obtaining the interval prediction rolling force deviation proportion of each rack of the continuous rolling mill unit, and specifically counting the related influence factors of the prediction rolling force deviation greater than 10%, and displaying the statistical results. The application effectively eliminates the problems of low processing efficiency, long processing period and high error rate in manual data processing. Through the operation of the operation expression about the cycle variable and the selection statement, the application realizes the data reference, calculation and statistics, and overcomes the defects that the manual screening is prone to errors or omissions.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of hot strip mill production, in particular to a kind of hot strip mill rolling force deviation prediction calculation and statistical method. BACKGROUND

[0002] Rolling force setting is the core of the computer setting model of hot strip mill finishing mill set, and its setting precision will directly affect the setting of roll gap, and then affect the stability of threading, plate thickness precision and the final plate shape quality, and its actual error size has a direct impact on the flow between stands, when exceeding the range of looper adjustment, it is easy to cause production accident.

[0003] At present, in the hot strip mill production, mainly based on the mathematical model of rolling force theoretical calculation is used to set the calculation of rolling force, and the adaptive technology is used to correct the rolling force online.

[0004] There are many theoretical calculation methods of rolling force, such as SIMS model, and its rolling force formula is:

[0005] F=w·l d ·k m ·Q p

[0006] Wherein: F——rolling pressure, w——strip width, l d ——flattening arc length, k m ——deformation resistance of rolled piece, Q p ——external friction stress state coefficient, and deformation resistance and external friction coefficient are related to rolled piece thickness, temperature, composition, etc. In addition, there are simplified formulas such as Hitachi formula, Sun Yikang formula, etc. From the formula, it can be seen that the influence of main process parameters and specifications on rolling model is analyzed, so as to improve the hit rate, and it has certain research significance.

[0007] Only relying on mathematical model to realize thickness control requires that the model itself has high prediction accuracy, but the model accuracy is limited, and it is difficult to meet the required value. At the same time, due to the continuous change of rolling mill and rolled piece parameters in actual rolling process, there is a certain deviation between the set rolling force and the actual value. At this time, adaptive technology is needed to correct the mathematical model. Adaptive technology is to use real-time information to modify model coefficients according to the change of system state in the process of hot strip mill, so as to ensure the accuracy of the model.

[0008] There are two ways for adaptive correction of the rolling force model, one is to correct the model coefficients by measured data of the same specification of the previous batch of material adjacent to the current batch of material, and then to calculate the current batch of material; the other is to correct the rolling force prediction value of each subsequent stand by the difference between the measured rolling force and the predicted rolling force after the current batch of material is rolled into the finishing mill train and the first two stands, and to accurately adjust the subsequent stand screwdown devices again, so that the accuracy of the entire set model is improved. SUMMARY

[0009] In order to overcome the shortcomings of the prior art, the purpose of the present application is to provide a hot continuous rolling strip steel predicted rolling force deviation calculation and statistical method.

[0010] To achieve the above purpose, the present application provides the following scheme:

[0011] A hot continuous rolling strip steel predicted rolling force deviation calculation and statistical method, comprising:

[0012] Step 1: copy the original rolling data in the rolling model to the "data source" worksheet; the "data source" worksheet includes: start rolling time, actual rolling force and calculated rolling force;

[0013] Step 2: extract the data in the "data source" worksheet to the "rolling force deviation" worksheet;

[0014] Step 3: calculate the time interval and rolling force deviation data of rolling by using the "rolling force deviation" worksheet, and form the rolling force deviation data of each steel grade;

[0015] Step 4: judge whether it is necessary to empty the current rolling force deviation data, if necessary, replace the "data source" worksheet and return to step 2 to recalculate, if not, input the steel grade code to be analyzed;

[0016] Step 5: according to the steel grade code to be analyzed, display the corresponding steel grade name, obtain the interval prediction rolling force deviation proportion of each stand of the continuous rolling mill train, and specifically count the steel grade with rolling force deviation greater than 10%, and display the alarm statistical result.

[0017] Preferably, the step 3: calculating the time interval and rolling force deviation data of rolling by using the "rolling force deviation" worksheet, and forming the rolling force deviation data of each steel grade, comprises:

[0018] The time interval of rolling is obtained by using the time function DateDiff to find the difference between the start rolling times of the two slabs;

[0019] The formula is:

[0020]

[0021] Calculate the rolling force deviation of each rack when rolling the corresponding strip steel; wherein, P 计算 P represents the calculated rolling force, 实际 P represents the actual rolling force.

[0022] Preferably, the step 5 comprises:

[0023] The statement "mycrr = Worksheets ("1"). Range ("a1"). CurrentRegion.Value" is used to store the data in table "1" into the array myarr; the data in the table "1" includes the rolling force deviation data of each steel grade; specifically, the rolling force deviation data of each steel grade is stored into the array myerr by using "for-next" loop;

[0024] The statement "Setuu = Worksheets.Add (after: = Sheets ("1"))" is used to create a new worksheet after the table "1";

[0025] The statement "uu.Name = "2"" is used to name the worksheet as "2";

[0026] The steel grade codes that need to be analyzed are selected from the table "1" and filled into the newly created table "2";

[0027] The proportion of each rack deviation in "<5%", "5%-10%", ">10%" range in the table "2" is counted by using loop counting;

[0028] The tables "F1"-"F7" are created, and the data with deviation >10% in the table "2" is selected and filled into the tables "F1"-"F7";

[0029] The data in each condition range in the tables "F1"-"F7" is counted and filled into the corresponding position in the "statistics" table;

[0030] The tables "1", "2" and "F1"-"F7" are deleted to form the alarm statistical result of the rolling force deviation greater than 10%.

[0031] Preferably, after the step 5, it further comprises:

[0032] It is judged whether to clear the page and calculate the new steel grade; if it is cleared, the code "Sheets ("statistics"). Range ("XX:XX"). ClearContents" is run to clear the cell range "XX:XX", and then the steps 4 to 5 are repeated; if it is not needed, the running is ended.

[0033] According to the specific embodiments provided by the present application, the following technical effects are disclosed:

[0034] The application provides a hot continuous rolling strip steel predicted rolling force deviation calculation and statistics method, wherein the method comprises the following steps: copying data into a "data source" table; extracting relevant data needed in the data source into a "rolling force deviation" table; calculating the time interval and the predicted rolling force deviation between each rack by using the "rolling force deviation" table; judging whether the existing data needs to be emptied, and if yes, replacing the data source to recalculate, and if no, inputting the steel grade code to be analyzed; calculating the rolling process data and the rolling force deviation of the input steel grade, displaying the corresponding steel grade name, obtaining the predicted rolling force deviation proportion of each interval of each rack of the continuous rolling unit, and specifically calculating the relevant influencing factors of the predicted rolling force deviation greater than 10%, and displaying the alarm statistics result. The application realizes the data reference, calculation and statistics by operating the operation expression of the cyclic variable and combining the selection statement, overcomes the defects that the manual screening is prone to errors or omissions, and further overcomes the defects that the corresponding table needs to be opened for operation in the traditional statistics method, and realizes the general use of one table. BRIEF DESCRIPTION OF DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments. Obviously, the drawings described below only show some of the embodiments of the present application, and the drawings can be obtained by those skilled in the art without any creative labor.

[0036] Figure 1 A hot continuous rolling strip steel predicted rolling force deviation calculation and statistics method flow chart provided in an embodiment of the present application;

[0037] Figure 2 A process chart for screening rolling force deviation >10% data provided in the present application;

[0038] Figure 3 A "data source" worksheet provided in an embodiment of the present application;

[0039] Figure 4 A rolling force deviation statistics chart provided in an embodiment of the present application. DETAILED DESCRIPTION

[0040] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without any creative labor are within the protection scope of the present application.

[0041] Reference to "an embodiment" herein means that a particular feature, structure, or characteristic described in connection with an embodiment is included in at least one embodiment of the application. The appearances of the phrase "in an embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are they necessarily mutually exclusive of one another. It is expressly understood that any of the embodiments described herein can be combined with any of the other embodiments unless specifically noted otherwise.

[0042] The terms "first", "second", "third", and "fourth" and the like in the description and in the claims, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. Furthermore, the terms "comprises", "comprising", "includes", "including", "has", "having" and the like, are inclusive and are used as equivalents for "consisting of" and "consisting essentially of" and are open-ended, allowing for the inclusion of additional elements or steps without falling out of a claimed application or scope of an embodiment. These terms, therefore, expressly should not be interpreted to exclude additional elements or steps.

[0043] In order to make the above objectives, features and advantages of the present application more obvious and comprehensible, further specific embodiments and drawings will be described below.

[0044] In order to achieve the above-mentioned purpose, the present application provides the following scheme:

[0045] Please refer to Figures 1-4 A hot strip mill rolling force deviation prediction calculation and statistics method, comprising:

[0046] Step 1: copy the original rolling data in the rolling model to the "data source" worksheet; the "data source" worksheet includes: opening time, actual rolling force and calculated rolling force.

[0047] Step 2: extract the rolling time, actual rolling force and calculated rolling force in the data source, and extract the main parameters of the rolling process (in actual application, the rolling temperature, rolling speed, product specification and roll number of each steel grade are also needed) to the "rolling force deviation" table;

[0048] In the embodiment of the present application, the required related data in the data source is extracted through the Do While Worksheets("data source").Cells(countx,1)<>"" loop, that is, the last row is found, and the loop is run when the last row is not empty, to realize extraction, and the specific statement is as follows:

[0049] Do While Worksheets("data source").Cells(countx,1)<>""

[0050] Worksheets("Rolling Force Deviation").Cells(county, column of required data) = Worksheets("Data Source").Cells(countx, corresponding data column)

[0051] ……

[0052] countx = countx + 1

[0053] county = county + 1

[0054] Loop

[0055] Among them, "Data Source" and "Rolling Force Deviation" are worksheet names. The table headers and buttons in the "Rolling Force Deviation" table are fixed and will not change due to running the program. "Column of required data" and "Corresponding data column" are column numbers, which are specific numbers determined according to the required content.

[0056] Step 3: Use the "Rolling Force Deviation" worksheet to calculate the rolling time interval and rolling force deviation data, and form the rolling force deviation data for each steel grade.

[0057] Furthermore, Step 3 includes:

[0058] Use the time function DateDiff to find the difference between the rolling start times of two slabs to obtain the rolling time interval.

[0059] Adopt the formula:[[]]

[0060]

[0061] Calculate the predicted rolling force deviation between each rolling stand.

[0062] It should be noted that the time interval is the basis for judging whether it is the first slab. If it is greater than twenty minutes, it is the first slab; otherwise, it is not the first slab. The calculation is implemented through the following statements:[[]]

[0063] If TimeValue(Cells(countb - 1, column number of rolling start time)) < TimeValue(Cells(countb, column number of rolling start time)), it means to judge whether the rolling process crosses a natural day. If it does not cross a natural day, then execute the following statements:[[]]

[0064] Cells(countb, time interval column) = DateDiff("s", TimeValue(Cells(countb-1, opening time column)), TimeValue(Cells(countb, opening time column))) / 60, which uses the time function DateDiff to find the difference between the opening times of two slabs, i.e. the rolling time interval. It is worth noting that the data cell content needs to be converted to time format using the TimeValue function to avoid calculation errors caused by cell format problems. The result of this statement is in minutes.

[0065] Else indicates that the result of the judgment is across natural days, and the following statements are executed:

[0066] Cells(countb, time interval column) = DateDiff("s", TimeValue(Cells(countb-1, opening time column)), TimeValue(Cells(countb, opening time column))) / 60+1440, where the constant 1440 is a compensation value.

[0067] End If, indicating the end of the judgment.

[0068] Rolling force deviation calculation

[0069] The formula for rolling force deviation calculation is:

[0070] Using the above formula to calculate all rolling force deviation values. It is worth noting that due to the existence of the situation of throwing the rack in actual production process, the calculated rolling force of some racks is 0, which will cause the program to appear error and terminate operation. At this time, we need to skip this situation and continue calculation. The statement used in this method is "On Error Resume Next".

[0071] To realize the reuse of the table and prevent the emptying of all contents due to misoperation, a clear button is set on the "Rolling Force Deviation" and "Statistics" table pages, with different functions.

[0072] (1) The "Rolling Force Deviation" page clears all contents and formats in the table except the table header and buttons, which is achieved by the statement: Sheets("Rolling Force Deviation").Range("4:65536").Clear.

[0073] (2) The "Statistics" page only needs to clear the statistical results, and the format does not change, which is achieved by the ClearContents statement:

[0074] Sheets("Statistics").Range("XX:XX").ClearContents. Here, XX:XX represents the specific range of cells to be cleared.

[0075] Step 4: Determine whether it is necessary to clear the existing data. If so, replace the data source and recalculate. If not, enter the code of the steel grade to be analyzed.

[0076] Step 5: Statistically analyze the rolling process data and rolling force deviation of the input steel grade, display the corresponding steel grade name, obtain the percentage of predicted rolling force deviation in each interval of each stand of the continuous rolling mill, and perform specific statistics on the relevant influencing factors with predicted rolling force deviation greater than 10%, and display the alarm statistics results.

[0077] Furthermore, step 5 includes:

[0078] The statement `mycrr = Worksheets("1").Range("a1").CurrentRegion.Value` stores the data of table "1" into the array `myarr`. The data in table "1" includes the rolling force deviation data for each steel grade. Specifically, a "for-next" loop is used to store the rolling force deviation data for each steel grade into the array `myerr`.

[0079] Use `Setuu = Worksheets.Add(after:=Sheets("1"))` to create a new worksheet after sheet "1";

[0080] Name the worksheet "2" using uu.Name="2";

[0081] Select the steel grade codes to be analyzed from table "1" and fill them into the newly created table "2";

[0082] Using cyclic counting, the percentage of each rack deviation in Table "2" that falls within the three ranges of "<5%", "5%-10%", and ">10%" is calculated respectively;

[0083] Create new tables “F1”-“F7”, and filter the data with a deviation >10% from table “2” and fill them into tables “F1”-“F7” respectively;

[0084] Calculate the data for each condition range in tables “F1”-“F7” and fill them into the corresponding positions in the “Statistics” table;

[0085] Delete tables “1”, “2” and “F1”-“F7” to generate alarm statistics for rolling force deviation greater than 10%.

[0086] In this embodiment of the invention, step 5 specifically includes:

[0087] Since the control system has a self-learning function, that is, according to the slab calculation value and the actual rolling force feedback, the relevant parameter modification is carried out, the rolling force calculation hit rate is improved, so after the third block of each flow, due to the intervention of system learning, the calculation model parameter has been modified, and the deviation caused by the rolling factor is analyzed again, the reference is poor, so it is necessary to preliminarily screen out the data of the first two blocks of each flow. The statement is as follows:

[0088] myarr = Worksheets ("rolling force deviation"). Range ("a1"). CurrentRegion. Value, indicates that the data of the rolling force deviation table is stored in the array myarr.

[0089] For j = 2 To UBound (myarr), indicates that the loop range is in the non-empty cells of the rolling force deviation table.

[0090] If <condition expression 1> Then, indicates that the first two blocks of slab are judged according to the volume number code.

[0091] t = t + 1, here introduces a parameter, which is used for new array row number loop.

[0092] <extract data statement sequence>

[0093] End If

[0094] Next j

[0095] Set uu = Worksheets. Add (after: = Sheets ("statistics")), indicates that a new worksheet is added after the statistics table

[0096] uu. Name = "1", indicates that the new table is named "1", which is fixed here, which is convenient for subsequent calculation.

[0097] With uu, indicates that the data is backfilled, the format is set, which has a transpose processing.

[0098] .Range ("A1:G1") = Array

[0099] .Range ("a2"). Resize (t, 7) =_

[0100] WorksheetFunction. Transpose (myerr)

[0101] .UsedRange. Borders. LineStyle = xlContinuous

[0102] EndWith

[0103] t = 0

[0104] Erase myerr(), indicates emptying the array, releasing memory.

[0105] (3) New table "2", from "1" table screening with the input steel grade code corresponding steel grade data filled into table "2", and from table "2" new table "F1"-"F7", from the "2" table screening deviation > 10% of the data filled in. Screening method is the same as (1), but different is that this screening may appear empty, resulting in running errors, need to add the statement "On Error ResumeNext" to ensure running.

[0106] (4) Statistics and display statistical results through the following statements:

[0107] Do While <condition expression 2>, the condition is table "2" is not empty when running.

[0108] If Worksheets <condition expression 3> Then, the condition is the data range

[0109] <Count statement sequence>

[0110] Loop

[0111] <cell value expression>, which means that the count results are filled into the corresponding cells of the "statistics" table after relevant calculation and processing.

[0112] (5) Output steel grade name through if conditional statement in table "steel code" to find.

[0113] (6) Delete temporary tables "1", "2", "F1"-"F7", through Worksheets ("table name"). Delete to achieve, for not pop-up delete inquiry need to add the statement "Application.DisplayAlerts = False" before closing the pop-up, after the end of the deletion through the statement "Application.DisplayAlerts = TURE" to restore the pop-up function.

[0114] Further, after step 5, also includes:

[0115] Determine whether to empty the page, calculate the new steel grade; if empty, run the empty code "Sheets ("statistics"). Range ("XX:XX"). ClearContents", where "XX:XX" is the cell range that needs to be emptied, and then repeat steps 4 to 5; if not, then run.

[0116] The calculation process of the present application is further described below in combination with specific examples:

[0117] Step one: copy the whole data table to the "data source" table.

[0118] Step two: extract the relevant data needed in the data source to the table "rolling force deviation". The "Do While" loop can be used to achieve this, and the loop condition is Do While Worksheets ("data source"). Cells (countx, 1)<> "", i.e. the last row is not empty, run the loop. The extraction value is realized by the following statements:

[0119] Worksheets ("rolling force deviation"). Cells (county, m) = Worksheets ("data source"). Cells (countx, n), "m, n" are the corresponding column numbers.

[0120] Step three: calculate the time interval and the predicted rolling force deviation between each stand.

[0121] (1) The time interval is calculated by the following statements:

[0122] Cells (countb, time interval column number) = DateDiff ("s", TimeValue (Cells (countb-1, start rolling time column number)), TimeValue (Cells (countb, start rolling time column number))) / 60, which uses the time function DateDiff to calculate the difference between the start rolling time of the two slabs, i.e. the rolling time interval. It is worth noting that the data cell content needs to be converted to time format using the TimeValue function to avoid calculation errors due to cell format problems. The running result of this statement is in minutes.

[0123] (2) The rolling force deviation is calculated according to the formula:

[0124] In order to avoid the running error caused by calculating the rolling force as zero when the stand is thrown, the "On Error ResumeNext" - "Exit Sub" statement needs to be added.

[0125] Step four: judge whether it is necessary to empty the existing data and replace the data source to recalculate. If not, execute step five, if it is necessary to replace the data source, execute the program "empty 1". "Empty 1" is realized by the statement: Sheets ("rolling force deviation"). Range ("4:65536"). Clear.

[0126] Step five: input the steel grade code that needs to be analyzed.

[0127] Step six: statistics of the rolling process data of the input steel grade and the rolling force deviation, display the corresponding steel grade name, get the prediction rolling force deviation proportion of each interval of each rack of the continuous rolling mill unit, and specifically statistics the related influencing factors of the prediction rolling force deviation greater than 10%, and display the statistical results. The specific process of this step is shown in Figure 2 .

[0128] (1) New table "1", filter out the data of the first two blocks of each flow and fill in. This process is mainly realized by the following statements:

[0129] mycrr=Worksheets("1").Range("a1").CurrentRegion.Value, indicates that the data of table "1" is stored in the array myarr.

[0130] Use "for-next" loop to store the data meeting the conditions in the array myerr.

[0131] Set uu=Worksheets.Add(after:=Sheets("1")), which means a new worksheet is created after table "1".

[0132] uu.Name="2" means that the worksheet is named "2"

[0133] Use With statement to fill the array myerr into table "2".

[0134] Erase myerr(), which means to clear the array, the purpose is to release the memory.

[0135] (2) New table "2", filter out the corresponding steel grade data from table "1" and fill in. The method is the same as (1).

[0136] (3) Use loop count to respectively count the proportion of each rack deviation in "<5%", "5%-10%", ">10%" three ranges in table "2".

[0137] The proportion n=FormatPercent(qa / m)

[0138] Where qa=the number of cells meeting the condition of this range, which is obtained by if loop counting.

[0139] m=total data amount, obtained by the statement "Application.counta(Worksheets("2").Range("A:A"))-1".

[0140] (4) New table "F1" - "F7", from "2" table screening deviation > 10% of the data are filled into the table "F1" "F7". Method same as (1).

[0141] (5) respectively statistics table "F1" - "F7" in each condition range of data, filled into the corresponding position in table "statistics". Method same as (3).

[0142] (6) delete table "1", "2", "F1" - "F7". Through Worksheets ("table name"). Delete, for not pop up delete inquiry need to add the statement "Application.DisplayAlerts=False" before, close pop-up, after the end of the deletion through the statement "Application.DisplayAlerts=TURE" to restore the pop-up function.

[0143] Step seven: judge whether to empty the page, calculate new steel. If empty, run empty code "Sheets ("statistics"). Range ("XX:XX"). ClearContents", wherein "XX:XX" is the range of cells that need to be emptied, and then repeat steps five to six; If not, then run end.

[0144] For example, when the data of a month is calculated and counted, the data source is copied to the "data source" table, after starting statistics, the VBA program will decompose the copied data, extract the rolling time, actual rolling force and calculated rolling force, and extract the main parameters of the rolling process (in actual application, the rolling temperature, rolling speed, product specification and coil number of each steel grade) to the table "rolling force deviation", and use the defined formula: DateDiff ("s", TimeValue (Cells (countb-1, the column number where the rolling time is located)), TimeValue (Cells (countb, the column number where the rolling time is located))) / 60, The rolling force deviation value and interval time of each coil are calculated, and then the data of the coils meeting the conditions are classified and counted according to the input product code and output to the table. This process is automatically performed without other manual operation.

[0145] According to the specific embodiments provided by the present application, the following technical effects are disclosed:

[0146] The application provides a hot continuous rolling strip steel rolling force deviation prediction calculation and statistics method, which comprises the following steps: copying data into a "data source" table; extracting relevant data needed in the data source into a "rolling force deviation" table; calculating the time interval and the rolling force deviation between each rack by using the "rolling force deviation" table; judging whether the existing data needs to be emptied, and if so, replacing the data source to recalculate, or inputting the steel grade code to be analyzed; calculating the rolling process data and the rolling force deviation of the input steel grade, displaying the corresponding steel grade name, obtaining the interval prediction rolling force deviation proportion of each rack of the continuous rolling mill group, and specifically calculating the related influence factors of the prediction rolling force deviation greater than 10%, and displaying the statistical results. The application effectively eliminates the problems of low processing efficiency, long processing period and high error rate in manual data processing. The application realizes the reference, calculation and statistics of data by operating the operation expression of the cyclic variable, and overcomes the defects of easy error or omission in manual screening. In addition, the application overcomes the defect of the traditional statistical method that needs to open the corresponding table for operation, and realizes the general use of one table.

[0147] The embodiments in the specification are described in a progressive manner, and each embodiment focuses on the difference from other embodiments. The same or similar parts of each embodiment can be referred to each other. For the method disclosed by the embodiments, since it corresponds to the device disclosed by the embodiments, the description is relatively simple, and the relevant parts can be referred to the device part.

[0148] The principles and implementation modes of the application are described by using specific examples in this paper. The above embodiment description is only used to help understand the method and core idea of the application. For those skilled in the art, according to the idea of the application, the specific implementation mode and application range can be changed. In summary, the content of the specification should not be understood as a limitation of the application.

Claims

1. A method for calculating and statistically analyzing predicted rolling force deviation in hot-rolled strip steel, characterized in that, include: Step 1: Copy the original rolling data from the rolling model to the "Data Source" worksheet; The "Data Source" worksheet includes: rolling start time, actual rolling force, and calculated rolling force; Step 2: Extract the data from the "Data Source" worksheet to the "Rolling Force Deviation" worksheet; Step 3: Calculate the rolling time interval and rolling force deviation data using the "Rolling Force Deviation" worksheet to generate rolling force deviation data for each steel grade; Step 3: Calculate the rolling time interval and rolling force deviation data using the "Rolling Force Deviation" worksheet to generate rolling force deviation data for each steel grade, including: The time interval of rolling is obtained by using the time function DateDiff to calculate the difference between the rolling start times of the two slabs. Formula used: Calculate the rolling force deviation n for each stand when rolling the corresponding strip; where P 计算 P represents the calculated rolling force. 实际 Indicates the actual rolling force; Step 4: Determine whether the current rolling force deviation data needs to be cleared. If so, replace the "Data Source" worksheet and return to Step 2 to recalculate. If not, enter the steel grade code to be analyzed. Step 5: Based on the steel grade code to be analyzed, display the corresponding steel grade name, obtain the predicted rolling force deviation percentage of each interval of each stand in the continuous rolling mill, and perform specific statistics on steel grades with rolling force deviation greater than 10%, and display the alarm statistics results. Step 5 includes: The statement `mycrr = Worksheets("1").Range("a1").CurrentRegion.Value` stores the data of table "1" into the array `myarr`. The data in table "1" includes the rolling force deviation data for each steel grade. Specifically, a "for-next" loop is used to store the rolling force deviation data for each steel grade into the array `myerr`. Use `Setuu = Worksheets.Add(after:=Sheets("1"))` to create a new worksheet after sheet "1"; Name the worksheet "2" using uu.Name="2"; Select the steel grade codes to be analyzed from Table "1" and fill them into the newly created Table "2"; Using cyclic counting, the percentage of each rack deviation in Table "2" that falls within the three ranges of "<5%", "5%-10%", and ">10%" is counted respectively; Create new tables "F1"-"F7", and filter the data with a deviation >10% from table "2" to fill them into tables "F1"-"F7" respectively; Calculate the data for each condition range in tables "F1"-"F7" and fill them into the corresponding positions in the "Statistics" table; Delete tables "1", "2" and "F1"-"F7" to generate alarm statistics for rolling force deviation greater than 10%.

2. The method for calculating and statistically analyzing predicted rolling force deviation of hot-rolled strip steel according to claim 1, characterized in that, Following step 5, the following is also included: Determine whether to clear the current page and calculate the new steel grade; if clearing, run the clear code "Sheets("Statistics").Range("XX:XX").ClearContents", where "XX:XX" is the range of cells to be cleared, and then repeat steps 4 and 5; if not, the process ends.

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