CN114101338B - Cold rolled silicon steel thickness control method and device based on full-flow data - Google Patents
Cold rolled silicon steel thickness control method and device based on full-flow data Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B21—MECHANICAL METAL-WORKING WITHOUT ESSENTIALLY REMOVING MATERIAL; PUNCHING METAL
- B21B—ROLLING OF METAL
- B21B37/00—Control devices or methods specially adapted for metal-rolling mills or the work produced thereby
- B21B37/16—Control of thickness, width, diameter or other transverse dimensions
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B21—MECHANICAL METAL-WORKING WITHOUT ESSENTIALLY REMOVING MATERIAL; PUNCHING METAL
- B21B—ROLLING OF METAL
- B21B37/00—Control devices or methods specially adapted for metal-rolling mills or the work produced thereby
- B21B37/58—Roll-force control; Roll-gap control
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- B—PERFORMING OPERATIONS; TRANSPORTING
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- B21B—ROLLING OF METAL
- B21B2261/00—Product parameters
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- B21B2261/04—Thickness, gauge
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Abstract
The invention relates to a cold rolled silicon steel thickness control method and device based on full-flow data, wherein the method comprises the following steps: aiming at a certain cold rolled steel coil, the monitoring AGC is used by default in the first pass, the production process and quality data of the whole preamble process are obtained before the cold rolling mill process is started for production, the pre-identification is carried out, and if the fluctuation of the silicon steel performance is found, the second flow AGC is additionally used in the first pass; if the fluctuation of the thickness of the silicon steel is not severe, the feedforward AGC is additionally used in the first pass. According to the invention, manual interference is not needed, the optimal AGC production mode can be automatically determined before production by adopting the rule, the thickness precision of the silicon steel product is ensured, and the defect of the thickness index of the silicon steel is avoided.
Description
Technical Field
The invention belongs to the technical field of cold-rolled silicon steel, and particularly relates to a cold-rolled silicon steel thickness control method and device based on full-flow data.
Background
The cold-rolled silicon steel is a steel variety with extremely high added value, is mainly used as iron cores of various motors, generators, compressors, motors and transformers, and is an indispensable raw material product in the industries of electric power, household appliances and the like.
Thickness deviation (thickness difference for short) of cold-rolled silicon steel is an important quality dimension. On one hand, a large thickness difference can affect the production efficiency of downstream processes; on the other hand, the lamination coefficient is reduced along with the increase of the thickness difference, and each time the lamination coefficient is reduced by 1%, the iron loss is increased by 2%, the magnetic induction is reduced by 1%, and the magnetic performance of the silicon steel sheet is indirectly influenced.
Because silicon steel needs to be striped, punched and laminated in the downstream processing process, a high lamination factor is required. Therefore, the silicon steel has extremely severe requirements on thickness precision in the production process. The final thickness accuracy is directly determined by the cold rolling mill process, and most scientific research workers and production practitioners focus on optimizing various thickness control modes of the cold rolling mill process.
In fact, the full-flow process of silicon steel has some effect on the final thickness of silicon steel. In the steelmaking stage, the composition control and the temperature control are strict, generally do not have too much fluctuation, and do not need to be further analyzed under the condition of meeting the process requirements. In the steel rolling process stage, the initial rolling temperature, rolling reduction regulation, final rolling temperature, coiling temperature and normalizing temperature of the normalizing pickling process have direct influence on the performance of the strip steel. And the thickness accuracy of the hot rolling also affects the thickness accuracy of the cold rolling.
Currently, in the production process of a silicon steel cold rolling mill, thickness control of the cold rolling mill is mainly performed by various thickness control systems (AGC), such as feedforward AGC, second flow AGC, monitoring AGC, and thickness control in the following three modes:
there are some studies in the prior art for each AGC control method.
The patent disclosed in 12 months and 20 days of 2019 (publication No. CN 110586660A) discloses a self-adaptive single-stand rolling mill feedforward thickness control method, which greatly eliminates the influence of inlet raw materials on thickness deviation of a finished product through feedforward and ensures the quality of strip steel products; the roll gap adjustment quantity is calculated according to the thickness calculation correction coefficient when the strip steel passes through the outlet thickness gauge, the roll gap is adjusted in a self-adaptive mode, the fact that the strip steel reaches the target thickness is guaranteed, and the dependence on high accuracy of the plastic coefficient is reduced; through reasonable time delay, the roll gap is ensured to be applied to the expected strip steel position by the pressing control system.
The patent (publication No. CN 110614274A) published in 2019, 12 and 27 discloses an improved single-stand reversible rolling mill second flow thickness control method, which is capable of almost treating thickness deviation caused by all reasons through second flow, guaranteeing the accuracy of thickness control, fully utilizing meters of the single-stand reversible rolling mill, particularly utilizing a high-accuracy thickness gauge, avoiding the influence of insufficient accuracy of a speed measuring state on the thickness control and guaranteeing the accuracy of control.
The method is characterized in that a monitoring AGC system based on a generalized predictive controller is designed according to the characteristics of a predictive model, rolling optimization, on-line feedback correction and the like of the generalized predictive control, wherein the response time of a conventional Smith predictor is less than that of the generalized predictive control when the model is matched, and the steady-state precision is higher than that of the generalized predictive controller; when the model is not matched due to inaccurate calculation of the plastic coefficient of the rolled piece or the system lag time, the conventional Smith predictor has the phenomenon of system overshoot or oscillation, and the generalized predictive controller is basically not influenced by the change of the model parameters.
As to which AGC is selected according to the operating conditions, there is no explicit qualitative data study. Basically, the decision is made by the operator based on experience with the same batch of strip and the AGC mode setting for a mill is set by the operator to be enabled or disabled by the picture setting as shown in fig. 2.
By manual setting, there are a number of disadvantages including:
the manual experience is not fixed, and the experiences of different operators are inconsistent.
Several coils of steel are often required to be tested for errors manually according to previous experience of the same batch of the same class of marks.
If the production of the upstream process is unstable, the manual adjustment cannot be performed.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, and provides a cold rolled silicon steel thickness control method and device based on full-flow data, which can determine an optimal AGC production mode before production without manual intervention, ensure the thickness precision of a silicon steel product and avoid the defects on the thickness index of the silicon steel.
The technical scheme of the invention is realized as follows: the invention discloses a cold rolled silicon steel thickness control method based on full-flow data, which comprises the following steps:
for a certain cold-rolled steel coil, acquiring silicon steel thickness data and parameters affecting the silicon steel performance of each procedure of the preamble thereof before entering the cold-rolling mill procedure for production;
judging whether the silicon steel performance fluctuation condition occurs according to the parameters of each procedure affecting the silicon steel performance in the preamble, and judging whether the silicon steel thickness fluctuation condition is severe according to the silicon steel thickness data;
if the conditions of silicon steel performance fluctuation and silicon steel thickness fluctuation are severe, the second flow AGC and the monitoring AGC are used in the first pass, if the conditions of silicon steel performance fluctuation but no silicon steel thickness fluctuation are severe, the feedforward AGC, the second flow AGC and the monitoring AGC are used in the first pass, if the conditions of silicon steel performance fluctuation but silicon steel thickness fluctuation are not severe, the monitoring AGC is used in the first pass, and if the conditions of silicon steel performance fluctuation and silicon steel thickness fluctuation are not both present, the feedforward AGC and the monitoring AGC are used in the first pass.
Further, judging whether the fluctuation condition of the silicon steel performance occurs according to the parameters of each procedure affecting the silicon steel performance, specifically comprising:
selecting a plurality of parameters of each procedure of the preamble, which influence the performance of the silicon steel, and acquiring a parameter change curve of the parameters along the length direction of the silicon steel;
calculating a coefficient of variation Cv of a parameter affecting the silicon steel performance of each process, wherein the coefficient of variation Cv of the parameter affecting the silicon steel performance of the ith process i The calculation formula of (2) is as follows: cv i Standard deviation = i Average value i ；
Calculating a performance fluctuation score: performance fluctuation score equal to Cv i Root mean square of (v), i.e. all Cv i The arithmetic square root of the average of the squares of the data;
and when the performance fluctuation score is larger than a first preset value, judging that the silicon steel has performance fluctuation.
Further, the selection of the various parameters of the pre-steps that affect the performance of the silicon steel includes the hot rolling coiling temperature and the normalizing temperature of the normalizing pickling step.
Further, judging whether the situation of severe fluctuation of the thickness of the silicon steel occurs according to the thickness data of the silicon steel, specifically comprising:
and acquiring a final thickness curve of the silicon steel in the hot rolling production process, calculating the thickness quality score of the silicon steel, and judging that the silicon steel has severe thickness fluctuation if the thickness quality score of the silicon steel is larger than a second preset value.
Further, a final thickness curve of the silicon steel in the hot rolling production process is collected, and a thickness quality score of the silicon steel is calculated, which specifically comprises the following steps: subtracting the actual measured thickness of the silicon steel from the set thickness of the silicon steel to obtain a real-time thickness difference;
the thickness difference in the whole length direction of the strip steel forms an array H= (H) 1 ,h 2 ,…h n )；
Sequentially searching key points, including:
function 1 is defined, named func1, func1 (h i )＝h i+1 -h i ；
Function 2, named func2, is defined when |func1 (h i )|<err, then func2 (h i ) =0, when |func1 (h i )|>When=err, then func2 (h i )＝func1(h i ) The method comprises the steps of carrying out a first treatment on the surface of the err represents the tolerance in μm;
function 3 is defined, named func3, func3 (h i )＝func2(h i )*func2(h i+1 ) When func3 (h i )<When 0, the corresponding i point is a key point;
the key point array is obtained as follows:
calculating absolute inclination of two adjacent key points:
and calculating the root mean square of absolute inclination data, namely, thickness quality score:
score＝sqrt(((J 1 ) 2 +(J 2 ) 2 +…+(J s ) 2 ) S), sqrt represents the root number of the evolution.
The invention also discloses a cold rolled silicon steel thickness control device based on the full-flow data, which comprises: a processor and a memory for storing a computer program capable of running on the processor, wherein the processor is adapted to perform the steps of the cold rolled silicon steel thickness control method based on full flow data as described above when running the computer program.
The invention has at least the following beneficial effects: according to the invention, aiming at a certain cold rolled steel coil, the monitoring AGC is used by default in the first pass, the production process and quality data of the whole preamble process are obtained and pre-identification is carried out before the cold rolling mill process is started to produce, and if the fluctuation of the silicon steel performance is found, the second flow AGC is additionally used in the first pass; if the thickness fluctuation of the silicon steel is not severe, the feedforward AGC is additionally used in the first pass, manual interference is not needed, the optimal AGC production mode can be automatically determined before production by adopting the rule, the thickness precision of the silicon steel product is ensured, and the defect on the thickness index of the silicon steel is avoided.
The invention provides a method for scoring raw materials, which is used for quantitatively analyzing the raw materials and automatically selecting a more suitable AGC control mode according to the scoring result (comprising performance fluctuation scoring and thickness quality scoring) of the raw materials, so as to improve the thickness control precision of the cold-rolled silicon steel.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a cold rolled silicon steel thickness control method based on full flow data provided by an embodiment of the invention;
fig. 2 is a schematic view of an AGC mode setting screen of a conventional rolling mill.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The monitoring AGC can solve the integral deviation of the strip steel, so that the monitoring AGC must be put into use. The feed-forward deviation can solve the thickness deviation of the finished product caused by the thickness fluctuation of the raw material, but once the raw material fluctuation is severe, the time is slightly calculated by a little due to the response time of the hydraulic cylinder and the time difference caused by the distance between the inlet thickness gauge and the roll gap, and even the thickness reaction is caused, for example, the thickness fluctuation of silicon steel is severe, the inlet thickness wave crest is pressed down, and the adjacent wave trough is acted on as a result, so that the thickness difference is increased. The main thought of second flow is to predict the outlet thickness according to the principle of consistent inlet and outlet second flow, and then to adjust the hydraulic cylinder according to the inlet thickness, inlet speed and outlet speed, so as to solve the thickness fluctuation caused by any reason in principle, but the method still has hysteresis of hydraulic cylinder adjustment, and has extremely high requirement on the precision of the instrument because of being used with cautions.
The feedforward AGC is used for eliminating thickness deviation of strip steel at an inlet of a rolling mill, and is open-loop control. The feedforward AGC is a thickness control method commonly used in the art, and can be referred to in patent publication No. CN110586660A, self-adaptive single-stand rolling mill feedforward thickness control method, and will not be described again here; the second flow AGC is a control mode with faster response, and is a main mode for eliminating thickness deviation of strip steel at the outlet of a rolling mill when the rolling speed is higher. The second flow AGC is also a thickness control method commonly used in the art, and can be seen in the patent with publication number CN110614274A, improved second flow thickness control method of single-stand reversible rolling mill, and will not be described again here; the monitoring AGC is used for eliminating the thickness deviation of the strip steel when the rolling speed is low or the error caused by the long-term rolling process, and correcting and compensating the thickness deviation. The monitoring AGC is also a thickness control method commonly used in the art, and may be referred to in the paper "application of generalized predictive control in monitoring AGC systems", which is not described here again. The thickness gauge and the speed measuring device are arranged before and after the rolling of the common single-stand reversible rolling mill, and the conditions for implementing a plurality of AGC are provided.
Example 1
Referring to fig. 1, the embodiment of the invention discloses a cold-rolled silicon steel thickness control method based on full-flow data, which comprises the following steps: for a certain cold rolled steel coil, before entering cold rolling mill working procedure production, acquiring silicon steel thickness data and parameters of each working procedure of the preamble of the silicon steel thickness data affecting silicon steel performance, judging whether silicon steel performance fluctuation conditions occur according to the parameters of each working procedure of the preamble affecting silicon steel performance, judging whether silicon steel thickness fluctuation is severe according to the silicon steel thickness data, if the silicon steel performance fluctuation and the silicon steel thickness fluctuation are severe, using second flow AGC and monitoring AGC in the first pass, if the silicon steel performance fluctuation is not occurring but the silicon steel thickness fluctuation is severe, using feedforward AGC, second flow AGC and monitoring AGC in the first pass, if the silicon steel performance fluctuation is not occurring but the silicon steel thickness fluctuation is severe, using monitoring AGC in the first pass, and if the silicon steel performance fluctuation is not occurring but the silicon steel thickness fluctuation is severe, using feedforward AGC and monitoring AGC in the first pass, wherein the specific tables are as follows:
one embodiment of the invention is: when a plurality of (two or more) AGC's are used in combination, the roll gap adjustment amount is the sum of the respective AGC adjustment amounts, for example, when the second flow AGC and the monitor AGC are used in combination, the roll gap adjustment amount output is the sum of the second flow AGC adjustment amount and the monitor AGC adjustment amount, and the feedforward AGC adjustment amount does not need to be calculated at this time. When the feedforward AGC, the second flow AGC and the monitoring AGC are used in combination, the roll gap adjusting quantity output is the sum of the feedforward AGC adjusting quantity, the second flow AGC adjusting quantity and the monitoring AGC adjusting quantity. When the feedforward AGC and the monitoring AGC are used in combination, the roll gap adjustment quantity is the sum of the feedforward AGC adjustment quantity and the monitoring AGC adjustment quantity, and the second flow AGC adjustment quantity does not need to be calculated at the moment. Of course, the invention is not limited to the above embodiment, and the calculation method of the roll gap adjustment amount can be replaced according to actual needs.
Further, judging whether the fluctuation condition of the silicon steel performance occurs according to the parameters of each procedure affecting the silicon steel performance, specifically comprising:
selecting a plurality of parameters of each procedure of the preamble, which influence the performance of the silicon steel, and acquiring a parameter change curve of the parameters along the length direction of the silicon steel;
calculating a coefficient of variation Cv of a parameter affecting the silicon steel performance of each process, wherein the coefficient of variation Cv of the parameter affecting the silicon steel performance of the ith process i The calculation formula of (2) is as follows: cv i Standard deviation = i Average value i ；
Calculating a performance fluctuation score: performance fluctuation score equal to Cv i Root mean square of (v), i.e. all Cv i The arithmetic square root of the average of the squares of the data;
and when the performance fluctuation score is larger than a first preset value, judging that the silicon steel has performance fluctuation. The first preset value is set according to actual conditions.
Further, the parameters affecting the performance of the silicon steel include the start rolling temperature, the finish rolling temperature, the coiling temperature and the normalizing temperature of the normalizing pickling process in the hot rolling process, and the hot rolling coiling temperature and the normalizing temperature of the normalizing pickling process are generally selected for calculating the variation coefficient.
Further, judging whether the situation of severe fluctuation of the thickness of the silicon steel occurs according to the thickness data of the silicon steel, specifically comprising:
and acquiring a final thickness curve of the silicon steel in the hot rolling production process, calculating the thickness quality score of the silicon steel, and judging that the silicon steel has severe thickness fluctuation if the thickness quality score of the silicon steel is larger than a second preset value. The second preset value is set according to actual conditions.
Further, a final thickness curve of the silicon steel in the hot rolling production process is collected, and a thickness quality score of the silicon steel is calculated, which specifically comprises the following steps: subtracting the actual measured thickness of the silicon steel from the set thickness of the silicon steel to obtain a real-time thickness difference;
the thickness difference in the full length direction of the silicon steel forms an array H= (H) 1 ,h 2 ,…h n )；
Sequentially searching key points, including:
function 1 is defined, named func1, func1 (h i )＝h i+1 -h i ；
Function 2, named func2, is defined when |func1 (h i )|<err, then func2 (h i ) =0, when |func1 (h i )|>When=err, then func2 (h i )＝func1(h i ) The method comprises the steps of carrying out a first treatment on the surface of the err represents the tolerance in μm, for example, a value of 0.5 μm. When |func1 (h i )|<err, then func2 (h i ) =0 means when h i+1 And h i If the absolute value of the difference is very small, i.e. less than the set tolerance err, then h is considered to be i+1 And h i Equal.
Function 3 is defined, named func3, func3 (h i )＝func2(h i )*func2(h i+1 ) When func3 (h i )<When 0, the corresponding i point is a key point;
the key point array is as follows:
calculating absolute inclination of two adjacent key points:
j units are μm/ms.
And calculating the root mean square of absolute inclination data, namely, thickness quality score: score=sqrt (((J) 1 ) 2 +(J 2 ) 2 +…+(J s ) 2 ) S), sqrt represents the root number of the evolution.
Further, the thickness difference in the whole length direction of the strip steel forms an original array A= (a) 1 ,a 2 ,…a p ) The data is processed according to the requirement, thus forming a new array H= (H) 1 ,h 2 ,…h n )。
Further, processing the data as needed includes: thinning the data, for example, selecting an average or median every 10ms in this embodiment, to form a new array b= (B) 1 ,b 2 ,…b q )。
Filtering the data with obvious abnormal U-tail to form a new array H= (H) 1 ,h 2 ,…h n )。
The invention has two schemes for filtering the data with obvious abnormality of turning around the tail:
scheme one: data with an absolute value of thickness difference greater than 100 μm in the head-tail data are filtered.
Scheme II: and filtering the data with the corresponding speed (such as the speed of strip steel, and the like, which can be selected according to actual needs) smaller than the specified speed in the head and tail data.
Example two
The embodiment of the invention discloses a cold rolled silicon steel thickness control device based on full-flow data, which comprises the following components: a processor and a memory for storing a computer program capable of running on the processor, wherein the processor is adapted to perform the steps of the cold rolled silicon steel thickness control method based on full flow data as described above when running the computer program.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
Claims (5)
1. The cold rolled silicon steel thickness control method based on the full-flow data is characterized by comprising the following steps:
for a certain cold-rolled steel coil, acquiring silicon steel thickness data and parameters affecting the silicon steel performance of each procedure of the preamble thereof before entering the cold-rolling mill procedure for production; and acquiring a parameter change curve of the silicon steel along the length direction of the silicon steel;
judging whether the silicon steel performance fluctuation condition occurs according to the parameters of each procedure affecting the silicon steel performance in the preamble, and judging whether the silicon steel thickness fluctuation condition is severe according to the silicon steel thickness data;
judging whether the fluctuation condition of the silicon steel performance occurs according to the parameters of each procedure affecting the silicon steel performance, specifically comprising:
selecting a plurality of parameters of each procedure of the preamble, which influence the performance of the silicon steel, and acquiring a parameter change curve of the parameters along the length direction of the silicon steel;
calculating a coefficient of variation Cv of a parameter affecting the silicon steel performance of each process, wherein the coefficient of variation Cv of the parameter affecting the silicon steel performance of the ith process i The calculation formula of (2) is as follows: cv i Standard deviation = i Average value i ；
Calculating a performance fluctuation score: performance fluctuation score equal to Cv i Root mean square of (v), i.e. all Cv i The arithmetic square root of the average of the squares of the data;
when the performance fluctuation score is larger than a first preset value, judging that the silicon steel has performance fluctuation;
if the conditions of silicon steel performance fluctuation and silicon steel thickness fluctuation are severe, the second flow AGC and the monitoring AGC are used in the first pass, if the conditions of silicon steel performance fluctuation but no silicon steel thickness fluctuation are severe, the feedforward AGC, the second flow AGC and the monitoring AGC are used in the first pass, if the conditions of silicon steel performance fluctuation but silicon steel thickness fluctuation are not severe, the monitoring AGC is used in the first pass, and if the conditions of silicon steel performance fluctuation and silicon steel thickness fluctuation are not both present, the feedforward AGC and the monitoring AGC are used in the first pass.
2. The cold rolled silicon steel thickness control method based on full flow data as claimed in claim 1, wherein: the various parameters of the selected preamble sequences that affect the performance of the silicon steel include the hot rolling coiling temperature and the normalizing temperature of the normalizing pickling sequence.
3. The cold rolled silicon steel thickness control method based on full flow data as claimed in claim 1, wherein: judging whether the situation of severe fluctuation of the silicon steel thickness occurs according to the silicon steel thickness data, and specifically comprising the following steps:
and acquiring a final thickness curve of the silicon steel in the hot rolling production process, calculating the thickness quality score of the silicon steel, and judging that the silicon steel has severe thickness fluctuation if the thickness quality score of the silicon steel is larger than a second preset value.
4. The cold rolled silicon steel thickness control method based on full flow data as claimed in claim 3, wherein: the final thickness curve of the silicon steel in the hot rolling production process is collected, and the thickness quality score of the silicon steel is calculated, which comprises the following steps: subtracting the actual measured thickness of the silicon steel from the set thickness of the silicon steel to obtain a real-time thickness difference;
the thickness difference in the whole length direction of the strip steel forms an array H= (H) 1 ,h 2 ,…h n )；
Sequentially searching key points, including:
function 1 is defined, named func1, func1 (h i )＝h i+1 -h i ；
Function 2, named func2, is defined when |func1 (h i )|<err, then func2 (h i ) =0, when |func1 (h i )|>When=err, then func2 (h i )＝func1(h i ) The method comprises the steps of carrying out a first treatment on the surface of the err represents the tolerance in μm;
function 3 is defined, named func3, func3 (h i )＝func2(h i )*func2(h i+1 ) When func3 (h i )<When 0, the corresponding i point is a key point;
the key point array is obtained as follows:
calculating absolute inclination of two adjacent key points:
and calculating the root mean square of absolute inclination data, namely, thickness quality score:
score＝sqrt(((J 1 ) 2 +(J 2 ) 2 +…+(J s ) 2 )/s)。
5. cold rolled silicon steel thickness control device based on full flow data, characterized by comprising: a processor and a memory for storing a computer program capable of running on the processor, wherein the processor is adapted to perform the steps of the method according to any of claims 1 to 4 when the computer program is run.
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