CN107363101B - A kind of other judgment method of hot-strip mathematical model data Layer - Google Patents
A kind of other judgment method of hot-strip mathematical model data Layer Download PDFInfo
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- CN107363101B CN107363101B CN201610312062.5A CN201610312062A CN107363101B CN 107363101 B CN107363101 B CN 107363101B CN 201610312062 A CN201610312062 A CN 201610312062A CN 107363101 B CN107363101 B CN 107363101B
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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
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Abstract
The present invention relates to a kind of other judgment method of hot-strip mathematical model data Layer, considers to influence belt steel rolling stability or influence the principal element of strip characteristic: steel grade, thickness, width, finishing temperature and coiling temperature, carry out mathematical model layer and do not divide；For different mathematical models, emphasis considers different strip characteristic factors when division layer is other；The other F of mathematical model layer is the function of many characteristic factor layer alias, and F=f (Gi, Hi, Wi, FTi, CTi) does not judge according to the layer that the other decision rule of mathematical model layer carries out hot-strip data finally.The present invention is not judged by dynamic layer, the continuity of self study coefficient can effectively be kept, it avoids in free regulation rolling especially tandem rolling, the self study as caused by the variation fluctuation of the molten steel composition of same steel grade difference furnace or the minor change of specification and setting are chaotic, it utmostly ensure that the setting reliability of mathematical model, improve mathematical model setting accuracy and rolling stability.
Description
Technical field
The present invention relates to hot-strip production technical fields more particularly to a kind of hot-strip mathematical model data Layer not to sentence
Disconnected method.
Background technique
On supermatic hot-rolled strip production line, mathematical model plays very important effect, stablizes to rolling
Property, strip dimensional accuracy etc. have large effect.
One conventional up to up to ten thousand kinds of strip description produced of hot-rolled strip production line, it is former when model calculates
Then each upper description requires a different set of initial data and participates in model calculating, in this case, in order to support mathematics
The normal calculating of model, it is desirable to which a huge database carrys out the initial data needed for storage model calculates.It is deposited to save
Store up space, convenient for model specification calculate, by mathematical model calculate needed for initial data by layer not carry out stepping division, i.e., will be upper
Ten thousand descriptions are divided into several groups by certain rule, and relevant parameter be saved in corresponding layer it is other among.It in this way can be with
The characteristic of different steel is distinguished, more accurately convenient for classification and the validity of self study effect.
Generally, for finishing mill setting model, layer other parameter is mainly true by three material, thickness, width parameters
It is fixed.When progress data model layer does not divide, the same or similar kind of characteristic is usually divided into one grade.What shelves divided
Few, the model cootrol parameter between strip and strip easily causes interference, and shelves divide excessive, between the strip of characteristic close again
Connection can be lacked.
But carry out layer in any case and do not divide, can all there are some unreasonable parameters.
Such as when steel strip thickness classification, > 2.5mm~≤3.0mm points are one grade, and > 3.0mm~≤4.0mm points are another
Shelves.According to such classification, 3.0mm strip and 3.01mm steel strip thickness difference very little will but use different initial data, and
3.01mm strip and 4.0mm steel strip thickness difference are larger but using same group of initial data.
For another example, most of all to locate for same batch strip when stepping other according to carbon equivalent mode progress steel grade layer
In in the other shelves of same layer, for example it is in the 2nd grade, it is likely that because of C, Si, the minor fluctuations of Mn ingredient, so that carbon equivalent numerical value
It has crossed in the 1st grade or the 3rd grade, this allows for model parameter and also collapses grade, not only influences the quality of this kind, simultaneously
Also influencing the product quality of another grade, (it is not frequent when steel strip thickness negative common difference or plus tolerance roll also to will appear thick layer
Across shelves such cases).
When the other strip continuous production of same layer, by self-learning function, model can be according to apparatus for production line shape at that time
State optimal setting data, such model computational accuracy can be higher and higher.If injecting one piece suddenly between the other strip of the same layer
Another layer of other strip (it is bigger that the other probability of happening of strip cross-layer caused by minor change occurs for material), due to using not
Same model parameter (including initial data and self study parameter), the calculated mill data setting value of model have biggish difference
Different, these differences can reduce the computational accuracy of model, and then influence product size precision even rolling stability.
If thick a bit (i.e. reduction layer do not classify span) that model layer is not divided, can reduce band to a certain extent
The other probability of steel cross-layer, but be not avoided that the generation of the other phenomenon of cross-layer, and do so and can also reduce model computational accuracy.
Summary of the invention
The present invention provides a kind of other judgment methods of hot-strip mathematical model data Layer, are not judged by dynamic layer,
The continuity that self study coefficient can effectively be kept avoids in free regulation rolling especially tandem rolling, due to same steel
Self study and setting confusion caused by the variation fluctuation of the molten steel composition of the different furnaces of kind or the minor change of specification, utmostly
It ensure that the setting reliability of mathematical model, improve mathematical model setting accuracy and rolling stability.
In order to achieve the above object, the present invention is implemented with the following technical solutions:
A kind of other judgment method of hot-strip mathematical model data Layer characterized by comprising
1) the other division rule of mathematical model layer:
The parameter for influencing belt steel rolling stability or influencing strip characteristic mainly has: steel grade, thickness, width, finishing temperature
And coiling temperature, the rule that mathematical model layer does not divide is carried out according to the different parameters for influencing strip characteristic are as follows:
A) material layers do not divide: the kind for strip characteristic without mutation, and material layers do not press carbon equivalent ce Q and carry out stepping,
The layer alias of each shelves is Gi, i=1~10；Each shelves carbon equivalent spacing LGi is 0.03~0.10；CEQ calculation formula are as follows:
CEQ=(C+Mn/6+Si/24) × 100%；Wherein C, Mn, Si be respectively in strip carbon containing, manganese, element silicon
Weight；
B) thick layer does not divide: carrying out stepping according to steel strip thickness, each shelves layer alias is Hi, i=1~20；Each shelves thickness
Spacing LHi is 0.2~5mm；And steel strip thickness is smaller, the thickness difference of each shelves is also smaller；
C) width layer does not divide: carrying out stepping according to strip width, each shelves layer alias is Wi, i=1~10, each shelves width
Spacing LWi is 50~200mm；
D) finishing temperature layer does not divide: according to strip finishing temperature carry out stepping, each shelves layer alias be FTi, i=1~5,
Each shelves temperature spacing LFTi is 20~50 DEG C；
E) coiling temperature layer does not divide: according to Strip Steel Coiling Temperature carry out stepping, each shelves layer alias be CTi, i=1~10,
Each shelves temperature spacing LCTi is 20~50 DEG C；
For different mathematical models, the strip characterisitic parameter that emphasis considers when division layer is other is as follows:
A) to roughing regional model, emphasis considers material, thickness, width totally three parameters；
B) to finish rolling regional model, emphasis considers material, thickness, width, finishing temperature totally four parameters；
C) for section cooling model, emphasis considers material, thickness, width, finishing temperature, coiling temperature totally five ginsengs
Number；
D) for batching setting model, emphasis considers material, thickness, width, coiling temperature totally four parameters；
2) the other decision rule of mathematical model layer；
It layer is codetermined by many characterisitic parameters for some mathematical model, i.e. the other F of mathematical model layer is
The function of many characterisitic parameter layer alias, F=f (Gi, Hi, Wi, FTi, CTi)；
A) within a precision rolling working roll period, the mathematical model layer of each parameter of first piece of strip of roll change open rolling is other, root
Corresponding layer alias is directly assigned by calculated result according to the initial data of strip；
B) since second piece of strip of roll change open rolling, the final mathematical model layer alias of each parameter is carried out by following below scheme
It calculates:
The first step carries out material G, thickness H, width W, finishing temperature FT, coiling temperature according to strip initial data respectively
The layer alias of CT calculates, and compares with the layer alias of the relevant parameter of upper one piece of strip；
Second step, if only one is identical for the layer alias of this block strip and upper one piece of strip, and this is not identical
Layer alias be adjacent layer alias, then execute third step, corresponding layer alias otherwise directly assigned by calculated result；
Third step, the strip characterisitic parameter different for layer alias calculate the original number of this block strip and upper one piece of strip
It is compared according to the absolute value A of difference, and with the other data variation tolerance limit value A-Lim of equivalent layer, this block band is judged with this
The layer alias of steel；That is:
If A≤A-Lim, this block strip takes the layer alias of one piece of strip, i.e. it is other to belong to a layer for the two blocks of steel in front and back；
If A > A-Lim, this block strip computation layer alias is taken, i.e. this block strip is not belonging to same with upper one piece of strip
A layer is other；
4th step, according to each characterisitic parameter layer alias of above-mentioned calculating, calculate this block strip layer other F, F=f (Gi, Hi,
Wi, FTi, CTi)；According to the other F of layer, corresponding model parameter is transferred in the other tables of data of layer.
Compared with prior art, the beneficial effects of the present invention are:
Do not judged by dynamic layer, can effectively keep the continuity of self study coefficient, avoid free regulation and roll
In system especially tandem rolling, as caused by the variation fluctuation of the molten steel composition of same steel grade difference furnace or the minor change of specification
Self study and setting be chaotic, utmostly ensure that the setting reliability of mathematical model, improve mathematical model setting accuracy and
Rolling stability.
Specific embodiment
A kind of other judgment method of hot-strip mathematical model data Layer of the present invention characterized by comprising
1) the other division rule of mathematical model layer:
The parameter for influencing belt steel rolling stability or influencing strip characteristic mainly has: steel grade, thickness, width, finishing temperature
And coiling temperature, the rule that mathematical model layer does not divide is carried out according to the different parameters for influencing strip characteristic are as follows:
A) material layers do not divide: the kind for strip characteristic without mutation, and material layers do not press carbon equivalent ce Q and carry out stepping,
The layer alias of each shelves is Gi, i=1~10；Each shelves carbon equivalent spacing LGi is 0.03~0.10；CEQ calculation formula are as follows:
CEQ=(C+Mn/6+Si/24) × 100%；Wherein C, Mn, Si be respectively in strip carbon containing, manganese, element silicon
Weight；
B) thick layer does not divide: carrying out stepping according to steel strip thickness, each shelves layer alias is Hi, i=1~20；Each shelves thickness
Spacing LHi is 0.2~5mm；And steel strip thickness is smaller, the thickness difference of each shelves is also smaller；
C) width layer does not divide: carrying out stepping according to strip width, each shelves layer alias is Wi, i=1~10, each shelves width
Spacing LWi is 50~200mm；
D) finishing temperature layer does not divide: according to strip finishing temperature carry out stepping, each shelves layer alias be FTi, i=1~5,
Each shelves temperature spacing LFTi is 20~50 DEG C；
E) coiling temperature layer does not divide: according to Strip Steel Coiling Temperature carry out stepping, each shelves layer alias be CTi, i=1~10,
Each shelves temperature spacing LCTi is 20~50 DEG C；
For different mathematical models, the strip characterisitic parameter that emphasis considers when division layer is other is as follows:
A) to roughing regional model, emphasis considers material, thickness, width totally three parameters；
B) to finish rolling regional model, emphasis considers material, thickness, width, finishing temperature totally four parameters；
C) for section cooling model, emphasis considers material, thickness, width, finishing temperature, coiling temperature totally five ginsengs
Number；
D) for batching setting model, emphasis considers material, thickness, width, coiling temperature totally four parameters；
2) the other decision rule of mathematical model layer；
It layer is codetermined by many characterisitic parameters for some mathematical model, i.e. the other F of mathematical model layer is
The function of many characterisitic parameter layer alias, F=f (Gi, Hi, Wi, FTi, CTi)；
A) within a precision rolling working roll period, the mathematical model layer of each parameter of first piece of strip of roll change open rolling is other, root
Corresponding layer alias is directly assigned by calculated result according to the initial data of strip；
B) since second piece of strip of roll change open rolling, the final mathematical model layer alias of each parameter is carried out by following below scheme
It calculates:
The first step carries out material G, thickness H, width W, finishing temperature FT, coiling temperature according to strip initial data respectively
The layer alias of CT calculates, and compares with the layer alias of the relevant parameter of upper one piece of strip；
Second step, if only one is identical for the layer alias of this block strip and upper one piece of strip, and this is not identical
Layer alias be adjacent layer alias, then execute third step, corresponding layer alias otherwise directly assigned by calculated result；
Third step, the strip characterisitic parameter different for layer alias calculate the original number of this block strip and upper one piece of strip
It is compared according to the absolute value A of difference, and with the other data variation tolerance limit value A-Lim of equivalent layer, this block band is judged with this
The layer alias of steel；That is:
If A≤A-Lim, this block strip takes the layer alias of one piece of strip, i.e. it is other to belong to a layer for the two blocks of steel in front and back；
If A > A-Lim, this block strip computation layer alias is taken, i.e. this block strip is not belonging to same with upper one piece of strip
A layer is other；
4th step, according to each characterisitic parameter layer alias of above-mentioned calculating, calculate this block strip layer other F, F=f (Gi, Hi,
Wi, FTi, CTi)；According to the other F of layer, corresponding model parameter is transferred in the other tables of data of layer.
Following embodiment is implemented under the premise of the technical scheme of the present invention, gives detailed embodiment and tool
The operating process of body, but protection scope of the present invention is not limited to following embodiments.Method therefor is such as without spy in following embodiments
Not mentionleting alone bright is conventional method.
[embodiment]
To hot-strip finish rolling plate shape mathematical model, the other stepping of layer is carried out according to strip steel grade, width, the different of thickness.
Layer Hua Fen not be as shown in Table 1 and Table 2 with the other data variation tolerance limit value of each layer, wherein being divided into 10 grades by steel grade, by width point
Be 9 grades, be divided into 20 grades by thickness, total layer not Ji Lu number be 10 × 9 × 20=1800.Opening up one in a computer has
The data fields of 1800 records place model coefficient in each data field, are accessed and read, the band other calculation formula of steel layer
It is as follows:
The band other F=(Gi-1) of steel layer × 20 × 9+ (Hi-1) × 9+Wi；
1 layer of table Hua Fen not table
2 layers of table other data variation tolerance limit value A-Lim
Table 3 and table 4 are that strip actual layer does not determine example during producing.
Table 3 Pan Ding one of example with steel layer
Table 4 with steel layer not Pan Ding example two
The foregoing is only a preferred embodiment of the present invention, but scope of protection of the present invention is not limited thereto,
Anyone skilled in the art in the technical scope disclosed by the present invention, according to the technique and scheme of the present invention and its
Inventive concept is subject to equivalent substitution or change, should be covered by the protection scope of the present invention.
Claims (1)
1. a kind of other judgment method of hot-strip mathematical model data Layer characterized by comprising
1) the other division rule of mathematical model layer:
The parameter for influencing belt steel rolling stability or influencing strip characteristic mainly has: steel grade, thickness, width, finishing temperature and volume
Temperature is taken, carries out the rule that mathematical model layer does not divide according to the different parameters for influencing strip characteristic are as follows:
A) material layers do not divide: the kind for strip characteristic without mutation, and material layers do not press carbon equivalent ce Q and carry out stepping, each shelves
Layer alias be Gi, i=1~10；Each shelves carbon equivalent spacing LGi is 0.03~0.10；CEQ calculation formula are as follows:
CEQ=(C+Mn/6+Si/24) × 100%；Wherein C, Mn, Si be respectively in strip carbon containing, manganese, element silicon weight；
B) thick layer does not divide: carrying out stepping according to steel strip thickness, each shelves layer alias is Hi, i=1~20；Each shelves thickness spacing
LHi is 0.2~5mm；And steel strip thickness is smaller, the thickness difference of each shelves is also smaller；
C) width layer does not divide: carrying out stepping according to strip width, each shelves layer alias is Wi, i=1~10, each shelves width spacing
LWi is 50~200mm；
D) finishing temperature layer does not divide: carrying out stepping according to strip finishing temperature, each shelves layer alias is FTi, i=1~5, each shelves
Temperature spacing LFTi is 20~50 DEG C；
E) coiling temperature layer does not divide: carrying out stepping according to Strip Steel Coiling Temperature, each shelves layer alias is CTi, i=1~10, each shelves
Temperature spacing LCTi is 20~50 DEG C；
For different mathematical models, the strip characterisitic parameter that division layer considers when other is as follows:
A) to roughing regional model, consider material, thickness, width totally three parameters；
B) to finish rolling regional model, consider material, thickness, width, finishing temperature totally four parameters；
C) for section cooling model, consider material, thickness, width, finishing temperature, coiling temperature totally five parameters；
D) for batching setting model, consider material, thickness, width, coiling temperature totally four parameters；
2) the other decision rule of mathematical model layer；
It layer is codetermined by many characterisitic parameters for some mathematical model, i.e. the other F of mathematical model layer is many
The function of characterisitic parameter layer alias, F=f (Gi, Hi, Wi, FTi, CTi)；
A) within a precision rolling working roll period, the mathematical model layer of each parameter of first piece of strip of roll change open rolling is other, according to band
The initial data of steel is directly assigned corresponding layer alias by calculated result；
B) since second piece of strip of roll change open rolling, based on the final mathematical model layer alias of each parameter is carried out by following below scheme
It calculates:
The first step carries out according to strip initial data material G, thickness H, width W, finishing temperature FT, coiling temperature CT respectively
Layer alias calculates, and compares with the layer alias of the relevant parameter of upper one piece of strip；
Second step, if only one is identical for the layer alias of this block strip and upper one piece of strip, and this different layer
Alias is adjacent layer alias, then executes third step, and corresponding layer alias is otherwise directly assigned by calculated result；
Third step, the strip characterisitic parameter different for layer alias, the initial data for calculating this block strip and upper one piece of strip are poor
The absolute value A of value, and being compared with the other data variation tolerance limit value A-Lim of equivalent layer judges this block strip with this
Layer alias；That is:
If A≤A-Lim, this block strip takes the layer alias of one piece of strip, i.e. it is other to belong to a layer for the two blocks of steel in front and back；
If A > A-Lim, this block strip computation layer alias is taken, i.e. this block strip and upper one piece of strip is not belonging to the same layer
Not；
4th step, according to each characterisitic parameter layer alias of above-mentioned calculating, calculate this block strip layer other F, F=f (Gi, Hi, Wi,
FTi, CTi)；According to the other F of layer, corresponding model parameter is transferred in the other tables of data of layer.
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| CN108817103B (en) * | 2018-06-06 | 2020-01-14 | 武汉科技大学 | Steel rolling model steel family layer classification optimization method |
| CN112024613B (en) * | 2020-07-31 | 2022-04-26 | 马鞍山钢铁股份有限公司 | Visualized and intelligent steel coil hot rolling temperature judgment system and judgment method |
| CN114101346B (en) * | 2021-10-26 | 2023-06-23 | 中冶南方工程技术有限公司 | Cold rolled silicon steel thickness defect identification method, device and system |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0591291A1 (en) * | 1991-06-28 | 1994-04-13 | Siemens Ag | Regulation system in the manufacture of hot rolled strips by means of a multi-stand hot rolling mill. |
| JP4280351B2 (en) * | 1999-03-10 | 2009-06-17 | 東芝三菱電機産業システム株式会社 | Rolling control model learning device |
| CN102371279A (en) * | 2010-08-26 | 2012-03-14 | 宝山钢铁股份有限公司 | Adaptive control method for increasing thickness precision of finish-rolled band steel by utilizing roll gap |
| CN102658297A (en) * | 2012-04-28 | 2012-09-12 | 北京科技大学 | Self-learning method for improving quality of first band steel plate shape with changed specification |
| CN102688894A (en) * | 2011-03-23 | 2012-09-26 | 宝山钢铁股份有限公司 | A controlling method for hot rolled strip threading of a continuous mill set |
| CN103611730A (en) * | 2013-11-19 | 2014-03-05 | 北京首钢自动化信息技术有限公司 | Method for improving precision of size control for continuous hot-rolled novel first coil |
-
2016
- 2016-05-12 CN CN201610312062.5A patent/CN107363101B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0591291A1 (en) * | 1991-06-28 | 1994-04-13 | Siemens Ag | Regulation system in the manufacture of hot rolled strips by means of a multi-stand hot rolling mill. |
| JP4280351B2 (en) * | 1999-03-10 | 2009-06-17 | 東芝三菱電機産業システム株式会社 | Rolling control model learning device |
| CN102371279A (en) * | 2010-08-26 | 2012-03-14 | 宝山钢铁股份有限公司 | Adaptive control method for increasing thickness precision of finish-rolled band steel by utilizing roll gap |
| CN102688894A (en) * | 2011-03-23 | 2012-09-26 | 宝山钢铁股份有限公司 | A controlling method for hot rolled strip threading of a continuous mill set |
| CN102658297A (en) * | 2012-04-28 | 2012-09-12 | 北京科技大学 | Self-learning method for improving quality of first band steel plate shape with changed specification |
| CN103611730A (en) * | 2013-11-19 | 2014-03-05 | 北京首钢自动化信息技术有限公司 | Method for improving precision of size control for continuous hot-rolled novel first coil |
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