CN107321801A - A kind of decision method of hot-strip and the online quality judging system of hot rolling - Google Patents
A kind of decision method of hot-strip and the online quality judging system of hot rolling Download PDFInfo
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- CN107321801A CN107321801A CN201710495184.7A CN201710495184A CN107321801A CN 107321801 A CN107321801 A CN 107321801A CN 201710495184 A CN201710495184 A CN 201710495184A CN 107321801 A CN107321801 A CN 107321801A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B21—MECHANICAL METAL-WORKING WITHOUT ESSENTIALLY REMOVING MATERIAL; PUNCHING METAL
- B21B—ROLLING OF METAL
- B21B38/00—Methods or devices for measuring, detecting or monitoring specially adapted for metal-rolling mills, e.g. position detection, inspection of the product
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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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- B—PERFORMING OPERATIONS; TRANSPORTING
- B21—MECHANICAL METAL-WORKING WITHOUT ESSENTIALLY REMOVING MATERIAL; PUNCHING METAL
- B21B—ROLLING OF METAL
- B21B2261/00—Product parameters
- B21B2261/02—Transverse dimensions
- B21B2261/04—Thickness, gauge
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B21—MECHANICAL METAL-WORKING WITHOUT ESSENTIALLY REMOVING MATERIAL; PUNCHING METAL
- B21B—ROLLING OF METAL
- B21B2261/00—Product parameters
- B21B2261/02—Transverse dimensions
- B21B2261/06—Width
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B21—MECHANICAL METAL-WORKING WITHOUT ESSENTIALLY REMOVING MATERIAL; PUNCHING METAL
- B21B—ROLLING OF METAL
- B21B2261/00—Product parameters
- B21B2261/20—Temperature
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B21—MECHANICAL METAL-WORKING WITHOUT ESSENTIALLY REMOVING MATERIAL; PUNCHING METAL
- B21B—ROLLING OF METAL
- B21B2263/00—Shape of product
- B21B2263/04—Flatness
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- Engineering & Computer Science (AREA)
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- Control Of Metal Rolling (AREA)
Abstract
The invention discloses the decision method and the online quality judging system of hot rolling that the present invention discloses a kind of hot-strip of class, N number of critical process control parameter curve of the hot-strip is obtained first, default judgment rule in the online quality judging system of the hot rolling is then based on to judge N number of parameter in N number of critical process control parameter curve, and provide specific judgement grade, and default judgment rule is the rule verified using historical data, so when being judged using this judgment rule, it is possible to increase the accuracy rate of judgement.
Description
Technical field
The application is related to hot-strip field, more particularly to a kind of decision method of hot-strip and hot rolling are sentenced in line mass
Determine system.
Background technology
The domestic quality judging for hot-rolled sheet coil is also rested in the stage manually judged, especially to some plate shapes at present
Parameter is such as：Glacing flatness, convexity, wedge shape etc. are judged according to PDO averages (average value of procedure parameter curve), it is impossible to met
Client's increasingly strict quality requirement.
There is following drawback in artificial decision method：
1) complete quality inspection coverage rate can not be met, defect missing inspection easily occurs, causes the circulation of defective work, causes matter
Measure objection；
2) quality inspection result is seriously delayed, easily occurs quality of lot accident；
3) during quality judging, the subjective consciousness of quality inspection personnel is different with experience, causes the result judged identical product not
Together.
Based on above reason, the online quality judging system of hot rolling is refer at present, by extracting hot rolling key process parameters
Curve, and total length judgement is carried out to curve according to the decision rule of system, but be due to the online quality judging system of current hot rolling
The accuracy rate of the judgement of system is not high, so often cause the situation of erroneous judgement to exist.
The content of the invention
Invention provides a kind of decision method of hot-strip and the online quality judging system of hot rolling, to solve at present
The online quality judging system of hot rolling judgement the not high technical problem of accuracy rate.
In order to solve the above technical problems, the invention provides a kind of decision method of hot-strip, methods described includes：
N number of critical process control parameter curve of the hot-strip is obtained, wherein, N is positive integer；
Based on default judgment rule in the online quality judging system of hot rolling to N number of critical process control parameter curve
In N number of parameter judged, and provide it is specific judge grade, wherein, the default judgment rule is to utilize history number
According to the rule verified.
It is preferred that, N number of critical process control parameter curve at least includes：
Width, thickness, convexity, glacing flatness, wedge shape, finishing temperature, coiling temperature, the hot rolling surface quality detecting system
Defect information.
It is preferred that, when N number of critical process control parameter curve includes width, thickness,
The default decision rule is：
Setting is not involved in judging end to end apart from A meters；
Setting control bound；
Width is according to segmentation decision method, and head B meters of setting allows super upper limit C millimeters of the not super D% of point, and center section surpasses
The not super E% of point of the upper limit；
Wherein, A values are 3-10, and B values are 10-30, C values 3-8, D value 0-50, E value 0-10.
It is preferred that, when N number of critical process control parameter curve includes convexity, wedge shape, glacing flatness,
The default decision rule is：
Setting is not involved in judging end to end apart from A meters；
Wedge shape judges that B meters of wedge-shaped differences are not more than C microns end to end for setting according to segmentation decision method using differential technique, in
Between the wedge-shaped difference in part be not more than D microns；
Flatness control interval E, Crown control interval F are set, is less than G meters beyond control interval or is less than beyond ratio
H%；
Wherein, A values are 5-10, and B values are 10-30, and C values 45-80, D value 30-60, E are that [- 150,150] are interval
Subset, F is [0,100] interval subset, and G values are 0-50, and F values are 0-30.
It is preferred that, when N number of critical process control parameter curve includes：Finish to gauge, coiling temperature；
The default decision rule is：
Setting is not involved in judging end to end apart from A meters；
Design temperature control interval is positive and negative 30 degree on the basis of desired value, is less than B meters beyond control interval or exceeds
Ratio is less than C%；
Wherein, A values are 10-20, and B values are 30-100, and C values are 10-30.
It is preferred that, when N number of critical process control parameter curve includes lacking for the hot rolling surface quality detecting system
Information is fallen into, then the default decision rule is：
Be not involved in judging that distance is set as 2-10 meter end to end, according to the size of defect, area, density, apart from end to end and side
The distance in portion is judged.
The invention discloses a kind of online quality judging system of hot rolling, including：
Acquisition module, N number of critical process control parameter curve for obtaining the hot-strip, wherein, N is just whole
Number；
Determination module, for based on default judgment rule in the online quality judging system of the hot rolling to it is described it is N number of close
N number of parameter in key process control parameters curve is judged, and provides specific judgement grade.
It is preferred that, N number of critical process control parameter curve at least includes：
Width, thickness, convexity, glacing flatness, wedge shape, finishing temperature, coiling temperature, the hot rolling surface quality detecting system
Defect information.
It is preferred that, when N number of critical process control parameter curve includes width, thickness,
The default decision rule is：
Setting is not involved in judging end to end apart from A meters；
Setting control bound；
Width is according to segmentation decision method, and head B meters of setting allows super upper limit C millimeters of the not super D% of point, and center section surpasses
The not super E% of point of the upper limit；
Wherein, A values are 3-10, and B values are 10-30, C values 3-8, D value 0-50, E value 0-10.
It is preferred that, when N number of critical process control parameter curve includes convexity, wedge shape, glacing flatness,
The default decision rule is：
Setting is not involved in judging end to end apart from A meters；
Wedge shape judges that B meters of wedge-shaped differences are not more than C microns end to end for setting according to segmentation decision method using differential technique, in
Between the wedge-shaped difference in part be not more than D microns；
Flatness control interval E, Crown control interval F are set, is less than G meters beyond control interval or is less than beyond ratio
H%；
Wherein, A values are 5-10, and B values are 10-30, and C values 45-80, D value 30-60, E are that [- 150,150] are interval
Subset, F is [0,100] interval subset, and G values are 0-50, and F values are 0-30.
It is preferred that, batch and finishing temperature：In positive and negative 30 degree of target temperature fluctuation, surpass 50 meters, judge block.Pass through tracking
Finish to gauge and positive and negative 30 degree of coiling temperature change will not produce influence to performance substantially, therefore, according to positive and negative 30 degree as in control
Lower limit.
It is preferred that, surface quality：Distance according to the size of defect, area, density, distance end to end with edge is sentenced
It is fixed.Hole and side split defect and occur blocking, and it is to block to scratch defect number to be more than 100, and iron sheet defect number is more than 30 and sealed
Lock, roll marks defect area is more than 300mm2Block.
By one or more technical scheme of the present invention, the invention has the advantages that or advantage：
The present invention discloses a kind of decision method of hot-strip of class, and N number of critical process of the hot-strip is obtained first
Control parameter curve, is then based in the online quality judging system of the hot rolling default judgment rule to N number of crucial mistake
N number of parameter in range control parameter curve is judged, and provides specific judgement grade, and default judgment rule is to utilize
The rule that historical data was verified, so when being judged using this judgment rule, it is possible to increase the accuracy rate of judgement.
Brief description of the drawings
Fig. 1 is a kind of flow chart of the decision method of hot-strip in the embodiment of the present invention；
Fig. 2 is the composition schematic diagram of the online quality judging system of hot rolling in the embodiment of the present invention.
Embodiment
In order that the application the technical staff in the technical field is more clearly understood that the application, below in conjunction with the accompanying drawings,
Technical scheme is described in detail by specific embodiment.
Judge the problem of accuracy rate of hot-strip is not high, this hair to solve the online quality judging system of current hot rolling
It is bright to provide a kind of decision method of hot-strip, for the complete or at least part of judgement hot-strip solved at present
The problem of accuracy rate is not high, the accuracy rate to improve hot-strip judgement.
Fig. 1 is refer to below, is the implementation process figure of the decision method of the hot-strip of the present invention, and this method includes：
Step 11, N number of critical process control parameter curve of the hot-strip is obtained.
Wherein, N is positive integer.
Critical process control parameter curve can have very multiple parameters, in the present invention, and N number of critical process control parameter is bent
Line at least includes：Width, thickness, convexity, glacing flatness, wedge shape, finishing temperature, coiling temperature, the hot rolling surface quality testing
The defect information of system.Defect major class is selected to scab, stick up skin, foreign matter, hole, side are split, iron scale, roll marks and scratch several major classes
Judged.
Selected 8 critical process control parameter curve conducts of the influence with steel dimensions, template, performance and surface of the present invention
The parameter foundation judged online.Wherein, size class process parameter is width, thickness, and version type class process parameter is convexity, glacing flatness
And wedge shape, performance class process parameter is finishing temperature, coiling temperature, and surface class process parameter is hot rolling surface quality detecting system
Defect information.
It is of the invention then devise corresponding judgment rule for several parameters above, and the online quality judging system of hot rolling
System is then judged hot-strip using this judgment rule.
Step 12, based on default judgment rule in the online quality judging system of the hot rolling to N number of critical process
N number of parameter in control parameter curve is judged, and provides specific judgement grade, wherein, the default judgment rule
It is the rule verified using historical data.Historical data method of calibration is as follows：Rolled by the quality engineer of hot rolling from early stage
The quality information data of volume 1000 is chosen in historical data, and gives quality judging result.These data include off quality
Data account for 40%, and up-to-standard data account for 40%, and 20% is accounted between up-to-standard and unqualified edge data.Using current
Decision rule judged, think the decision rule without asking when applicating history data judging rate of accuracy reached is to more than 98%
Topic, is applied to actual production process and is judged.
In specific implementation process, the present invention first introduces the judgment rule：
When N number of critical process control parameter curve includes width, thickness, the default decision rule is：
Setting is not involved in judging end to end apart from A meters；
Setting control bound；
Width is according to segmentation decision method, and head B meters of setting allows super upper limit C millimeters of the not super D% of point, and center section surpasses
The not super E% of point of the upper limit；
Wherein, A values are 3-10, and B values are 10-30, C values 3-8, D value 0-50, E value 0-10.
When N number of critical process control parameter curve includes convexity, wedge shape, glacing flatness, the default judgement rule
It is then：
Setting is not involved in judging end to end apart from A meters；
Wedge shape judges that B meters of wedge-shaped differences are not more than C microns end to end for setting according to segmentation decision method using differential technique, in
Between the wedge-shaped difference in part be not more than D microns；
Flatness control interval E, Crown control interval F are set, is less than G meters beyond control interval or is less than beyond ratio
H%；
Wherein, A values are 5-10, and B values are 10-30, and C values 45-80, D value 30-60, E are that [- 150,150] are interval
Subset, F is [0,100] interval subset, and G values are 0-50, and F values are 0-30.
When N number of critical process control parameter curve includes：Finish to gauge, coiling temperature；The default decision rule is：
Setting is not involved in judging end to end apart from A meters；
Design temperature control interval is positive and negative 30 degree on the basis of desired value, is less than B meters beyond control interval or exceeds
Ratio is less than C%；
Wherein, A values are 10-20, and B values are 30-100, and C values are 10-30.
When N number of critical process control parameter curve includes the defect information of the hot rolling surface quality detecting system,
Then the default decision rule is：
Be not involved in judging that distance is set as 2-10 meter end to end, according to the size of defect, area, density, apart from end to end and side
The distance in portion is judged.
Above-mentioned decision rule contrasts advantage with traditional decision rule：Traditional decision rule is general only according to figure-of-merit curve
Average value is judged, does not consider that figure-of-merit curve integrally fluctuates situation, the demand of client can not be fully converted to quality judging rule
Then, therefore, even judging that up-to-standard product can not fully meet the demand of client, cause quality objection more.And
Decision rule provided by the present invention can also be realized and fluctuated according to curve total length in addition to it can carry out curve average judgement
Situation formulates personalized decision rule, does not such as judge that a meter number, curve allow the percentage transfinited, curve to allow the rice that transfinites end to end
Number, a range of extreme value of curve etc., can so be fully converted to customer personalized demand quality judging rule, both
Meet customer need, strip quality is realized again and is accurately judged.
In the following embodiments, after judgment rule is formulated, classification storage can also be carried out to judgment rule, so
When realizing the judgement of different hot-strips, the online quality judging system of hot rolling can directly invoke the judgement under correspondence classification
Rule is judged.
For example, according to individual demand of the client to strip quality, the rule group that quality judging is carried out to steel grade is divided, root
Different decision rules are customized according to different customer demands.Steel grade is such as divided into cold rolling material, general carbon, pipe line steel, diamond plate, silicon
The rule group such as steel.Then corresponding regular partition is arrived under corresponding regular group for different regular group, certain different rule
Then in group between there may be identical judgment rule.For example in the two regular group of cold rolling material, general carbon all have and width, thickness
Spend related judgment rule.Such design, is to judge different types of heat for the ease of the online quality judging system of hot rolling
Corresponding rule can be easily called quickly to be judged when rolling strip.
Certainly, in addition to above-mentioned regular group, other regular groups can also be divided into, the present invention is herein without limit
System.
And after judgment rule formulation, in order to ensure the determination rate of accuracy of judgment rule, the present invention goes back applicating history number
According to line discipline verification is entered, check whether decision rule is formulated problematic.Then the rule that this judges automatically is applied in fact again
Quality judging is carried out in the production process of border.
And in specific checking procedure, verified by historical data, specifically implementation process is as follows：History
Data verification method is as follows：The quality information number of volume 1000 is chosen from early stage rolling historical data by the quality engineer of hot rolling
According to, and given quality judging result.These data account for 40% including data off quality, and up-to-standard data account for 40%,
20% is accounted between up-to-standard and unqualified edge data.Judged using current decision rule, when applicating history number
The decision rule no problem is thought when reaching more than 98% according to determination rate of accuracy, is applied to actual production process and is sentenced
It is fixed.
In one embodiment, by the rule settings summary of parameters.An such as following table of emphasis kind：
Table 1
The rule of the online quality judging system of high-strength cold rolling material hot rolling is formulated and optimized according to upper table.
By width, thickness, glacing flatness, wedge shape, convexity, finishing temperature, coiling temperature, 8 critical process controls of surface quality
Parameter curve processed is used as the foundation judged online；
High-strength cold rolling material is divided into cold rolling gauge then group；
Rulemaking：
Size class：
Setting is not involved in judging 3 meters of distance end to end；
Thickness calibration：Control bound is formulated according to national standard, width is according to 0-20 controls；
Width allows the point of super 8 millimeters of the upper limit not surpass 50%, center section according to segmentation decision method, 30 meters of head of setting
The point of the super upper limit does not surpass 10%；
It is unsatisfactory for requiring then judging that " block " receives manual review.
Because hot-strip has certain camber defect end to end, therefore the appropriate width control system for widening 30 meters end to end will
Ask, help to make up due to the cold rolling unilateral very few problem of trimming amount caused by band end to end camber, reduce cold rolling stifled extension side phenomenon.
Template class：
Setting is not involved in judging 10 meters of distance end to end；
Wedge shape judges that 30 meters of wedge-shaped differences are not more than 60 microns end to end for setting according to segmentation decision method using differential technique,
Center section wedge shape difference is not more than 45 microns；
Flatness control interval ± 100I is set, Crown control interval [10,80] is less than 30% beyond control ratio；
It is unsatisfactory for requiring then judging that " block " receives manual review.
By tracking convexity less than 10, easily occur protuberance defect, and be unfavorable for the Strip Shape Control of high-strength steel, more than 80
Convexity is too big, and destabilizing factor is also increased during cold rolling.It is easy to cause down by the wedge shape mutation of tracking end to end
The sideslip and broken belt defect at visitor family, therefore wedge shape mutation requires strict compared with middle part end to end.
Performance class：
Batch and finishing temperature：In positive and negative 30 degree of target temperature fluctuation, surpass 50 meters, judge block.By track finish to gauge and
Positive and negative 30 degree of coiling temperature change will not produce influence to performance substantially, therefore, and control bound is used as according to positive and negative 30 degree.
Surface quality：Distance according to the size of defect, area, density, distance end to end with edge is judged.Hole and
Occur blocking while splitting defect, it is to block to scratch defect number to be more than 100, and iron sheet defect number is more than 30 and blocked, and roll marks is scarce
Fall into area and be more than 300mm2Block.
The regular applicating history data are tested, check whether Rulemaking is problematic, through checking, the decision rule
Judge accurate.
By the rule use in actual production, 8 critical process control parameter curves of hot-strip are obtained.Using default
Judgment rule 8 critical process control parameter curves are judged.
Decision rule is constantly optimized according to customer demand change, the demand of End-Customer is met.
By above method, the online determination rate of accuracy of high-strength cold rolling material reaches 98%, meets the quality of downstream client
Demand.
Based on unified inventive concept, referring to Fig. 2, the invention discloses a kind of online quality judging system of hot rolling, including：
Acquisition module 21, N number of critical process control parameter curve for obtaining the hot-strip, wherein, N is just whole
Number；N number of critical process control parameter curve at least includes：
Width, thickness, convexity, glacing flatness, wedge shape, finishing temperature, coiling temperature, the hot rolling surface quality detecting system
Defect information.
Determination module 22, for based on default judgment rule in the online quality judging system of the hot rolling to described N number of
N number of parameter in critical process control parameter curve is judged, and provides specific judgement grade.
As a kind of optional embodiment, when N number of critical process control parameter curve includes width, thickness,
The default decision rule is：
Setting is not involved in judging end to end apart from A meters；
Setting control bound；
Width is according to segmentation decision method, and head B meters of setting allows super upper limit C millimeters of the not super D% of point, and center section surpasses
The not super E% of point of the upper limit；
Wherein, A values are 3-10, and B values are 10-30, C values 3-8, D value 0-50, E value 0-10.
As a kind of optional embodiment, include convexity when N number of critical process control parameter curve, wedge shape, straight
When spending,
The default decision rule is：
Setting is not involved in judging end to end apart from A meters；
Wedge shape judges that B meters of wedge-shaped differences are not more than C microns end to end for setting according to segmentation decision method using differential technique, in
Between the wedge-shaped difference in part be not more than D microns；
Flatness control interval E, Crown control interval F are set, is less than G meters beyond control interval or is less than beyond ratio
H%；
Wherein, A values are 5-10, and B values are 10-30, and C values 45-80, D value 30-60, E are that [- 150,150] are interval
Subset, F is [0,100] interval subset, and G values are 0-50, and F values are 0-30.
And in actual applications, the judgment rule in system of the invention, by subsequently track the quality requirement of client after
Continuous Optimal improvements rule, meets the demand of End-Customer.
By one or more embodiment of the present invention, the invention has the advantages that or advantage：
The invention discloses the decision method and the online quality judging system of hot rolling that the present invention discloses a kind of hot-strip of class,
N number of critical process control parameter curve of the hot-strip is obtained first, is then based on the online quality judging system of the hot rolling
Default judgment rule is judged N number of parameter in N number of critical process control parameter curve in system, and provides specific
Judgement grade, and default judgment rule is the rule verified using historical data, so enter using this judgment rule
When row judges, it is possible to increase the accuracy rate of judgement.
Although having been described for the preferred embodiment of the application, one of ordinary skilled in the art once knows substantially
Creative concept, then can make other change and modification to these embodiments.So, appended claims are intended to be construed to bag
Include preferred embodiment and fall into having altered and changing for the application scope.
Obviously, those skilled in the art can carry out the essence of various changes and modification without departing from the application to the application
God and scope.So, if these modifications and variations of the application belong to the scope of the application claim and its equivalent technologies
Within, then the application is also intended to comprising including these changes and modification.
Claims (10)
1. a kind of decision method of hot-strip, it is characterised in that methods described includes：
N number of critical process control parameter curve of the hot-strip is obtained, wherein, N is positive integer；
Based on default judgment rule in the online quality judging system of hot rolling in N number of critical process control parameter curve
N number of parameter is judged, and provides specific judgement grade, wherein, the default judgment rule is to utilize historical data school
The rule tested.
2. the method as described in claim 1, it is characterised in that N number of critical process control parameter curve at least includes：
Width, thickness, convexity, glacing flatness, wedge shape, finishing temperature, coiling temperature, the hot rolling surface quality detecting system lack
Fall into information.
3. method as claimed in claim 2, it is characterised in that
When N number of critical process control parameter curve includes width, thickness,
The default decision rule is：
Setting is not involved in judging end to end apart from A meters；
Setting control bound；
Width allows super upper limit C millimeters of the not super D% of point, the super upper limit in center section according to segmentation decision method, head B meters of setting
The not super E% of point；
Wherein, A values are 3-10, and B values are 10-30, C values 3-8, D value 0-50, E value 0-10.
4. method as claimed in claim 2, it is characterised in that when N number of critical process control parameter curve include convexity,
When wedge shape, glacing flatness,
The default decision rule is：
Setting is not involved in judging end to end apart from A meters；
Wedge shape judges that B meters of wedge-shaped differences are not more than C microns, pars intermedia end to end for setting according to segmentation decision method using differential technique
Wedge-shaped difference is divided to be not more than D microns；
Flatness control interval E, Crown control interval F are set, is less than G meters beyond control interval or is less than H% beyond ratio；
Wherein, A values are 5-10, and B values are 10-30, and C values 45-80, D value 30-60, E are [- 150,150] interval son
Collection, F is [0,100] interval subset, and G values are 0-50, and F values are 0-30.
5. method as claimed in claim 2, it is characterised in that when N number of critical process control parameter curve includes：Eventually
Roll, coiling temperature；
The default decision rule is：
Setting is not involved in judging end to end apart from A meters；
Design temperature control interval is positive and negative 30 degree on the basis of desired value, is less than B meters or beyond ratio beyond control interval
Less than C%；
Wherein, A values are 10-20, and B values are 30-100, and C values are 10-30.
6. method as claimed in claim 2, it is characterised in that
When N number of critical process control parameter curve includes the defect information of the hot rolling surface quality detecting system, then institute
Stating default decision rule is：
Be not involved in end to end judge distance be set as 2-10 meter, according to the size of defect, area, density, apart from end to end with edge
Distance is judged.
7. a kind of online quality judging system of hot rolling, it is characterised in that including：
Acquisition module, N number of critical process control parameter curve for obtaining the hot-strip, wherein, N is positive integer；
Determination module, for based on default judgment rule in the online quality judging system of the hot rolling to N number of crucial mistake
N number of parameter in range control parameter curve is judged, and provides specific judgement grade.
8. system as claimed in claim 7, it is characterised in that N number of critical process control parameter curve at least includes：
Width, thickness, convexity, glacing flatness, wedge shape, finishing temperature, coiling temperature, the hot rolling surface quality detecting system lack
Fall into information.
9. system as claimed in claim 8, it is characterised in that when N number of critical process control parameter curve include width,
During thickness,
The default decision rule is：
Setting is not involved in judging end to end apart from A meters；
Setting control bound；
Width allows super upper limit C millimeters of the not super D% of point, the super upper limit in center section according to segmentation decision method, head B meters of setting
The not super E% of point；
Wherein, A values are 3-10, and B values are 10-30, C values 3-8, D value 0-50, E value 0-10.
10. system as claimed in claim 8, it is characterised in that when N number of critical process control parameter curve is including convex
When degree, wedge shape, glacing flatness,
The default decision rule is：
Setting is not involved in judging end to end apart from A meters；
Wedge shape judges that B meters of wedge-shaped differences are not more than C microns, pars intermedia end to end for setting according to segmentation decision method using differential technique
Wedge-shaped difference is divided to be not more than D microns；
Flatness control interval E, Crown control interval F are set, is less than G meters beyond control interval or is less than H% beyond ratio；
Wherein, A values are 5-10, and B values are 10-30, and C values 45-80, D value 30-60, E are [- 150,150] interval son
Collection, F is [0,100] interval subset, and G values are 0-50, and F values are 0-30.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710495184.7A CN107321801B (en) | 2017-06-26 | 2017-06-26 | Hot-rolled strip steel judgment method and hot-rolled online quality judgment system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710495184.7A CN107321801B (en) | 2017-06-26 | 2017-06-26 | Hot-rolled strip steel judgment method and hot-rolled online quality judgment system |
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| Publication Number | Publication Date |
|---|---|
| CN107321801A true CN107321801A (en) | 2017-11-07 |
| CN107321801B CN107321801B (en) | 2020-02-04 |
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| Application Number | Title | Priority Date | Filing Date |
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| CN201710495184.7A Active CN107321801B (en) | 2017-06-26 | 2017-06-26 | Hot-rolled strip steel judgment method and hot-rolled online quality judgment system |
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| CN108152292A (en) * | 2017-12-07 | 2018-06-12 | 北京首钢股份有限公司 | A kind of detection method of hot rolling surface quality detecting system edge interference |
| CN108280169A (en) * | 2018-01-19 | 2018-07-13 | 山东钢铁集团日照有限公司 | A kind of hot-rolled product figure-of-merit curve Reaction Fast Query Software and querying method |
| CN110202010A (en) * | 2019-05-22 | 2019-09-06 | 山西太钢不锈钢股份有限公司 | Stainless steel cold rolling coil board width determination method and system based on RAP line MES |
| CN110404977A (en) * | 2019-07-26 | 2019-11-05 | 东北大学 | A kind of online quality judging method of plate strip rolling process |
| CN110728059A (en) * | 2019-10-16 | 2020-01-24 | 北京首钢股份有限公司 | Intelligent plate roll head and tail slitting method based on industrial big data platform and industrial big data platform |
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| CN112547807A (en) * | 2020-10-30 | 2021-03-26 | 北京科技大学 | Decision tree algorithm-based hot rolled strip quality accurate judgment method |
| CN112668133A (en) * | 2019-09-29 | 2021-04-16 | 上海梅山钢铁股份有限公司 | Automatic determination method for cross section of hot-rolled strip steel based on big data analysis |
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| CN108152292B (en) * | 2017-12-07 | 2021-03-09 | 北京首钢股份有限公司 | Detection method for edge interference of hot rolling surface quality detection system |
| CN108152292A (en) * | 2017-12-07 | 2018-06-12 | 北京首钢股份有限公司 | A kind of detection method of hot rolling surface quality detecting system edge interference |
| CN108280169A (en) * | 2018-01-19 | 2018-07-13 | 山东钢铁集团日照有限公司 | A kind of hot-rolled product figure-of-merit curve Reaction Fast Query Software and querying method |
| CN110202010A (en) * | 2019-05-22 | 2019-09-06 | 山西太钢不锈钢股份有限公司 | Stainless steel cold rolling coil board width determination method and system based on RAP line MES |
| CN110404977A (en) * | 2019-07-26 | 2019-11-05 | 东北大学 | A kind of online quality judging method of plate strip rolling process |
| CN110404977B (en) * | 2019-07-26 | 2020-07-28 | 东北大学 | On-line quality judgment method in plate and strip rolling process |
| CN112668133A (en) * | 2019-09-29 | 2021-04-16 | 上海梅山钢铁股份有限公司 | Automatic determination method for cross section of hot-rolled strip steel based on big data analysis |
| CN110728059A (en) * | 2019-10-16 | 2020-01-24 | 北京首钢股份有限公司 | Intelligent plate roll head and tail slitting method based on industrial big data platform and industrial big data platform |
| CN110728059B (en) * | 2019-10-16 | 2023-09-29 | 北京首钢股份有限公司 | Industrial big data platform-based intelligent cutting method for head and tail of plate coil and industrial big data platform |
| CN111080054A (en) * | 2019-11-04 | 2020-04-28 | 北京科技大学 | Automatic evaluation method and system for width quality of hot-rolled strip steel |
| CN112246878A (en) * | 2020-09-28 | 2021-01-22 | 马鞍山钢铁股份有限公司 | Thickness judgment system and judgment method for pickling coil hot rolling process |
| CN112246878B (en) * | 2020-09-28 | 2022-04-26 | 马鞍山钢铁股份有限公司 | Thickness judgment system and judgment method for pickling coil hot rolling process |
| CN112307598A (en) * | 2020-09-30 | 2021-02-02 | 首钢集团有限公司 | Method for evaluating edge plate profile of hot-rolled strip steel |
| CN112547807A (en) * | 2020-10-30 | 2021-03-26 | 北京科技大学 | Decision tree algorithm-based hot rolled strip quality accurate judgment method |
| CN112785115A (en) * | 2020-11-19 | 2021-05-11 | 北京科技大学设计研究院有限公司 | Quality pre-examination method for cold rolling raw material warehouse |
| CN112949970A (en) * | 2020-12-14 | 2021-06-11 | 邯郸钢铁集团有限责任公司 | Method for controlling quality of steel strip product in whole process and automatically judging grade |
| CN113083909A (en) * | 2021-02-24 | 2021-07-09 | 唐山不锈钢有限责任公司 | On-line plate shape quality judgment method for hot-rolled strip steel |
| CN113083909B (en) * | 2021-02-24 | 2022-05-27 | 唐山不锈钢有限责任公司 | On-line plate shape quality judgment method for hot-rolled strip steel |
| CN114101346A (en) * | 2021-10-26 | 2022-03-01 | 中冶南方工程技术有限公司 | Cold-rolled silicon steel thickness defect identification method, device and system |
| 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 |
| CN114397151A (en) * | 2021-12-03 | 2022-04-26 | 首钢集团有限公司 | Plate surface quality control method, device, equipment and storage medium |
| CN114397151B (en) * | 2021-12-03 | 2023-12-12 | 首钢集团有限公司 | Panel surface quality control method, device, equipment and storage medium |
| CN115007662A (en) * | 2022-08-08 | 2022-09-06 | 承德建龙特殊钢有限公司 | Seamless steel tube production control device |
| CN117574215A (en) * | 2024-01-17 | 2024-02-20 | 北京科技大学 | Hot rolled strip steel plate shape prediction control method and device |
| CN117574215B (en) * | 2024-01-17 | 2024-04-02 | 北京科技大学 | Hot rolled strip steel plate shape prediction control method and device |
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