CN104751288B - A kind of coil of strip segmentation online quality judging system and method for multidimensional - Google Patents
A kind of coil of strip segmentation online quality judging system and method for multidimensional Download PDFInfo
- Publication number
- CN104751288B CN104751288B CN201510146138.7A CN201510146138A CN104751288B CN 104751288 B CN104751288 B CN 104751288B CN 201510146138 A CN201510146138 A CN 201510146138A CN 104751288 B CN104751288 B CN 104751288B
- Authority
- CN
- China
- Prior art keywords
- defect
- quality
- coil
- strip
- grade
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
Landscapes
- Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
- General Factory Administration (AREA)
- Investigating Or Analyzing Materials By The Use Of Magnetic Means (AREA)
Abstract
A kind of coil of strip segmentation online quality judging system and method for multidimensional, belong to metallurgy industry manufacture and informationization technology field.The production process data when present invention is judged by data-interface acquisition quality and Surface testing data, coil of strip is divided into several sections along volume length when coil of strip is offline, read the data of acquisition, judge the quality results of each section of internal procedure and surface defect respectively according to business rule and target level of product quality, finally determines each section of integrated level and the credit rating of coil of strip.A Secondary process parameter and table inspection instrument defect information are acquired, the integrated of production process data is farthest realized；Quality of service standard and control plan control operating instruction are realized into quantization and systematization processing, and the judgement of segmentation fractional dimension is just carried out when product is just offline, coil of strip is realized to check comprehensively, the labour for collecting data is liberated, quality inspection personnel is contributed to find quality problems in time, subsequent processing is made, it is final to improve product quality and Business Economic Benefit.
Description
Technical field
The invention belongs to metallurgy industry manufacture and informationization technology fields, online more particularly to a kind of coil of strip segmentation multidimensional
Quality judging system and method.
Background technology
Quality management is the core of metallurgic product production management, has effects that leading one starts whole body.Traditional artificial pair
Finished products carry out sampling observation mode can not adapt to production and the quality requirement of product completely.In recent years, steel industry is existing
Information system development at different levels are swift and violent, include mainly the production operations systems such as ERP system, MES system, Basic automation control system
System, these systems provide a large amount of, complete basic data for managers at different levels.But quality is carried out by production system
" after death autopsy " type of being generally, i.e. output is examined to examine.These methods of inspection wait for drawback and place to be modified there are many：
1. can not carry out volume volume to each product to examine, quality inspection is not comprehensive.
2. can not be prevented and be controlled in process of production, belong to non-value-added activity, is low-quality cost.
3. also resting on hardware check to the grading of defect when Surface testing to add in the conventional method of artificial experience, without section
The detection method of quantization.
4. sentencing in waste has much only in certain section of existing defects, but cutting position can not define, and the most of the time is whole
Volume is discarded or artificial uncoiling, and economic loss and manpower is caused to waste.
For above-mentioned quality judging business the problem of, the present invention propose a kind of to carry out segmentation various dimensions to coil of strip
The method of online quality judging, solves problem above.
Invention content
The purpose of the present invention is to provide one kind being segmented the online quality judging system and method for multidimensional for coil of strip.Pass through number
Production process data when judging according to interface acquisition quality and Surface testing data, when coil of strip is offline by coil of strip along volume length point
It is several sections, reads the data of acquisition, each section of internal procedure and surface is judged according to business rule and target level of product quality respectively
The quality results of defect finally determine each section of integrated level and the credit rating of coil of strip.
One kind includes mass parameter acquisition module, business rule conversion for the coil of strip segmentation online quality judging system of multidimensional
Module, comprehensive judgement hierarchical management module, segmentation quality judging module.Business rule conversion module includes surface defect business rule
Then conversion module and procedure parameter business rule conversion module.The segmentation quality judging module is acquired with mass parameter respectively
Module, comprehensive judgement hierarchical management module, surface defect business rule conversion module and procedure parameter business rule conversion module
It is connected；Comprehensive judgement hierarchical management module and surface defect business rule conversion module and procedure parameter business rule modulus of conversion
Block is connected.
1. mass parameter acquisition module：Acquire steel roll temperature, width, coil of strip number, steel grade, thickness, above and below width desired value
The data such as limit value, defect type, position, area, number, severity；Such as temperature, width coil of strip can be continuous when passing through milling train
The data of variation；Secondary server acquisition production process data is connected, coil of strip order in interface acquisition MES system is established and believes
Breath, such as coil of strip number, steel grade, thickness, width desired value upper lower limit value；Number in field instrument equipment (calibrator, template instrument)
Surface defect data according to this and in surface detecting system, such as defect type, position, area, number, severity.
Surface defect business rule conversion module：Define surface defect decision rule, can according to different clients, steel grade come
Surface defect control range is defined, the defect classification of each steel clock, defect rank, defect class weight are corresponded, table is formed
The face decision rule grade table of comparisons, the defect weight table of comparisons and defect level and the quality results table of comparisons, convert surface defect to
It can quantify measurable judgment basis.Specific practice is as follows：
Defect classification sum is r, and (classification includes hole to defect classification Ar, sticks up skin, scabs and foreign matter, iron scale, side
Split, scale mark, roll marks etc.), (grade distinguishes G=1,2 ..., n to each defective grade G of defect classification, and production is represented from 1 to n
For product surface quality by good to time, the definition of grade has different judgements to advise according to product material and purposes, user's particular/special requirement etc.
Then, the decision rule grade table of comparisons is formed), defect class weight Kr (K1, K2 ..., Kr (1 >=K1 .Kr >=0 K2 ..., and K1+K2
+ ... Kr=1)), defect class weight is corresponding with defect classification Ar.Defect class weight is also by different users and steel grade
To specify.For example, phosphorous high-strength steel requires strictly iron scale, the weight coefficient that iron scale accounts for is just high；And for IF steel
Or Automobile Plate, it sticks up skin, scab and foreign matter is to need the defect paid close attention to, then sticking up skin, scabbing and the weight of foreign matter is just high.
Surface quality results are S1, S2 ... Si (general setting i is bigger, quality not in proper sequence or order), are finally formulated according to company standard
Cum rights defect level and the quality results table of comparisons realize conversion of the defect rank to quality results.The table can be into according to business variation
Row adjustment.
2. procedure parameter business rule is converted：
(1) the quality results of definition procedure class parameter.The Pt (t >=1) that is defined as P1, P2 ..., P1 to Pt indicate procedure quality by
Well to poor.
(2) all kinds of procedure parameter rule lists are formulated according to different users and steel grade, realize the fluctuation of procedure parameter to process
The conversion of quality results；The fluctuation of the procedure parameter to procedure quality result conversion opsition dependent to procedure parameter into professional etiquette
It then constrains, coil of strip is divided into certain length range and middle section end to end, the defect situation of certain length end to end is not examined
Consider or the defect situation of certain length end to end is improved into a grade in normal defect rank and is configured.
Opsition dependent carries out rule constraint to procedure parameter, due to the special nature of coil of strip production, quality entirety deviation end to end,
The part will be different from middle section and carry out definition rule.5-10 meters and middle section end to end can be divided into.For 5-10 meters end to end
Defect situation is not considered or 5-10 meters end to end of defect situation is improved a grade in normal defect rank and sets
It sets.Such as：For width, the point of super upper limit 8mm is allowed to be more than 50% to be determined as P3, the point of the super upper limit in middle section for 5 meters end to end
It is determined as P3 more than 10%.
(3) above-mentioned rule, forming process parameter rule table can be refined by different users and steel grade.
3. comprehensive judgement hierarchical management module：Pass through the judgement etc. for business rule modulus of conversion process in the block and surface
Grade corresponds, and configures final comprehensive judgement as a result, forming comprehensive judgement grade allocation list.
4. being segmented quality judging module：Coil of strip is divided into several sections, the grade of every section of difference decision process and surface,
The grade that the process and surface of every section of coil of strip are obtained according to priority obtains every section comprehensive further according to grade allocation list information contrast
Close the comprehensive judgement result of judgement result and entire coil of strip.
The offline coil of strip not being determined of automatic checking, once it finds to carry out quality judging immediately, it is assumed that coil of strip length
It it is X meters, it is that least unit is segmented that definition (refers to the experience of coil of strip speed, general Y >=1) per Y meters, then shares X/Y+1 sections, judgement
Surface grade on each section and procedure parameter grade.
(1) table inspection segmentation judgement
The quality results of each section of coil of strip are calculated, computation rule is as follows：
In detection process, by the quantity statistics I of each defect rank in each defect classificationArG；Steel plate divides j sections, every section of defect
Measure Zj=∑s Kr × G × IArG；The quality results of every section of steel plate are obtained according to defect level and the quality results table of comparisons.
Note：Since the quality of coil of strip generally end to end can be poor, can remove end to end after 5-10 meters, the quality results of entire volume by
Each section of quality is worst after removal end to end determines.
(2) procedure parameter segmentation judgement
All procedure parameter rule lists are traversed, judge the grade of every section of procedure parameter, final process grade is by wherein each
Quality is worst in section grade determines.
(3) comprehensive judgement
Every section of comprehensive judgement grade is obtained according to comprehensive judgement grade allocation list.
One kind being segmented the online quality judging method of multidimensional for coil of strip, is as follows：
Step 1: determine that surface defect can quantify, defect classification sum is r, defect classification Ar (classification include hole,
Stick up skin, scab and foreign matter, iron scale, side split, scale mark, roll marks etc.), each defective grade G (grades of defect classification
G=1,2 ..., n respectively, from 1 to n representative products surface quality by good to secondary, different grades of definition is according to product material and use
On the way, user's particular/special requirement etc. has different decision rules, forms the decision rule grade table of comparisons), defect class weight Kr (K1,
K2 ..., Kr (1 >=K1 .Kr >=0 K2 ..., and K1+K2+ ... Kr=1)), defect class weight is corresponding with defect classification Ar.It lacks
Sunken class weight is also to be specified by different users and steel grade.For example, phosphorous high-strength steel requires iron scale stringent, oxidation
The weight coefficient that iron sheet accounts for is just high；And for IF steel or Automobile Plate, it sticks up skin, scab and foreign matter is to need the defect paid close attention to,
It so sticks up skin, scab and the weight of foreign matter is just high.
Quality results are S1, S2 ... Si (general setting i is bigger, quality not in proper sequence or order), finally formulate cum rights according to company standard
Defect level and the quality results table of comparisons realize conversion of the defect rank to quality results.The table can be adjusted according to business variation
It is whole.
Step 2: the quality results of definition procedure class parameter.The Pt that process class parametric results is defined as P1, P2 ... (t >=
1), P1 to Pt indicates procedure quality by good to poor.Conversion of the procedure parameter fluctuation to procedure quality result is realized by position of steel coil
Opsition dependent carries out rule constraint, forming process parameter rule table to procedure parameter.Opsition dependent carries out rule constraint to procedure parameter,
Due to the special nature of coil of strip production, quality entirety deviation, the part will be different from middle section and carry out definition rule end to end.It can divide
For 5-10 meters end to end and middle section.5 meters end to end of defect situation is not considered or by 5-10 meters end to end of defect feelings
Condition improves a grade in normal defect rank and is configured.Such as：For width, 5 meters of points for allowing super upper limit 8mm end to end
It is determined as P3 more than 50%, the point of the super upper limit in middle section is more than 10% to be determined as P3.It can come by different users and steel grade thin
Change above-mentioned rule, forming process parameter rule table.
It is described realize procedure parameter fluctuation to procedure quality result conversion opsition dependent to procedure parameter into line discipline about
Coil of strip is divided into certain length range and middle section end to end by beam, the defect situation of certain length end to end is not considered or
The defect situation of certain length end to end is improved a grade in normal defect rank and is configured by person.
Step 3: being corresponded by process and the judgement grade on surface, final comprehensive judgement is configured as a result, being formed
Comprehensive judgement grade allocation list.
Step 4: the offline coil of strip not being determined of automatic checking, once it finds to carry out quality judging immediately, it is assumed that steel
It is X meters to roll up length, and it is that least unit is segmented that definition (refers to the experience of coil of strip speed, general Y >=1) per Y meters, then shares X/Y+1
Section judges the surface grade on each section and procedure parameter grade.
Table inspection segmentation judgement：The quality results of each section of coil of strip are calculated, computation rule is as follows：In detection process, lacked by each
Fall into the quantity statistics I of each defect rank in classificationArG；Steel plate divides j sections, every section of defect level Zj=∑s Kr × G × IArG；According to scarce
It falls into amount and obtains the quality results of every section of steel plate with the quality results table of comparisons.
Note：Since the quality of coil of strip generally end to end can be poor, can remove end to end after 5-10 meters, the quality results of entire volume by
Each section of quality is worst after removal end to end determines.
Procedure parameter segmentation judgement：All procedure parameter rule lists are traversed, judge the quality results of every section of procedure parameter,
Entire volume processes result is determined by quality in wherein each section of grade is worst.
Comprehensive judgement：Every section of comprehensive judgement grade is obtained according to comprehensive judgement grade allocation list.The comprehensive judgement of entire volume
Grade is obtained by surface quality results and procedure quality result the control integrated level allocation list of entire volume.
Beneficial effects of the present invention：
The present invention acquires a Secondary process parameter and table inspection instrument defect information, farthest realizes production process number
According to it is integrated；Quality of service standard and control plan control operating instruction are realized into quantization and systematization processing, and in product
The judgement of segmentation fractional dimension has just been carried out when just offline, coil of strip has been realized and checks comprehensively, has been liberated the labour for collecting data, has been helped
In finding quality problems in time, subsequent processing is made, product quality is finally improved.By using invention achieves following effects
Fruit：
1. complete quality inspection covering surface, it is ensured that product quality.Artificial quality inspection is sampling inspection, and online quality judging is
Block block check improves the probability of product defects discovery, quality problems or abnormal conditions can be found more in time, to hereafter coil of strip
Technique be adjusted, avoid same quality problems, it is ensured that product quality.
2. the monitoring of pair procedural information.The increase of procedure parameter can not only complete the judgement to end product quality, together
When can play supervisory role to the stability of process device parameter, it is ensured that procedure quality.
3. saving the labour for collecting data and time.Data source in multiple systems (including：One level two, MES three-levels
System, table check system, LIMS systems), it is related to that data area is wide, and data pick-up is timely.Quality inspection staff finishes " to run quickly everywhere
The operating mode of wave ", greatly improves work efficiency.
4. reducing rejection number.The quality condition that can be seen that every section of coil of strip according to the result of segmentation judgement, so as to
According to cutting opinion in detail is provided the case where every section, determine the specific location of excision, coil of strip after cutting can according to weight and
Credit rating situation is assigned to new order, avoids the entire coil of strip caused by portion defect from sentencing useless, greatly reduces useless
Product amount, brings economic benefit.
5. establishing enterprise's judgement knowledge base.The mode of science is provided to count the judgement on surface and process as a result, utilizing
Artificial experience is effectively fused in determination method by the mode of weighted calculation.Surface decision rule grade, defect classification power
Weight, procedure parameter rule list and comprehensive judgement grade are adjusted and add at any time according to business variation and different product,
Enterprise is helped to establish and improve judgement knowledge base.
Description of the drawings
Fig. 1 flow charts of the present invention.
The decision rule grade table of comparisons in surface in Fig. 2 present invention.
The defect weight table of comparisons in Fig. 3 present invention.
Defect level and the quality results table of comparisons in Fig. 4 present invention.
Procedure parameter rule list in Fig. 5 present invention.
Comprehensive judgement grade allocation list in Fig. 6 present invention.
Specific implementation mode
The present invention proposes that a kind of coil of strip is segmented the online quality judging system and method for multidimensional, in conjunction with Fig. 1,2,3,4,5 and in fact
Detailed description are as follows for example：
1. mass parameter acquires：The data-interface with a two level, MES, LIMS and table check system is established, by triggering in real time
Mode will be in data integration to online quality judging system.
2. table examines criterion conversion
(1) judgement grade in surface is divided into：G1、G2、G3、G4.Surface quality results are divided into S1, S2, S3, S4.
(2) the number and area by company standard according to defect carry out it defect rank quantization, form the grade table of comparisons,
By taking hole as an example：There is primary then grade and is determined as G4 in hole.See Fig. 2, can according to actual needs quantify all defect.
(3) the weight shared by each defect is specified by different users and steel grade.See Fig. 3, defect kind, number in figure
It actually can at any time be adjusted according to business with weight.
3. procedure parameter traffic criteria is converted
(1) process grade name and priority can be configured by User Defined.Such as it can be divided into：P1、P2、P3.P1
The product process quality represented to P3 is by good to time, and priority is from low to high.
(2) press company standard and grade quantizing carried out to procedure parameter, see Fig. 4, for example, to hot rolling finishing temperature, coiling temperature,
Width and thickness carries out grade quantizing, and standard can also be formulated in the ratio of the overproof normal line of curve.
4. configuring comprehensive judgement grade
By taking Fig. 5 as an example, surface and process grade can one by one be compareed with self-defined title, formed matrix by judgement grade
Mode configures comprehensive judgement grade.It can be divided into：Qualified, reinspection and closing.Qualification volume is let pass, and is reviewed volume and is needed manually to be done
In advance, closing volume is sentenced useless.
5. segmentation judgement
The offline coil of strip not being determined of automatic checking, once it finds to carry out quality judging immediately, it is assumed that production
The each rice of cold-rolled low carbon steel is judged.50th meter is judged, hole quantity 1 in the section, scab and foreign matter >=
70mm*70mm has 2, (5*5mm2≤defect area<40*40mm2) there are 2.The point of the super upper limit 8mm of width of this section is
13%, finishing temperature is 830 DEG C
(1) table inspection segmentation judgement
Face decision rule grade table of comparisons table of tabling look-up learns that hole is G4, scabs and foreign matter is respectively G4 and G2, obtain hole
Hole defect amount is 1*4=4, scabs and foreign matter defect level is 2*4+1*2=10；It looks into Fig. 3 defect weight tables of comparisons and learns hole
The weight in hole is 80%, scabs and the weight of foreign matter is 10%, then the cum rights defect level of this section is 4*80%+10*10%=
4.2, look into Fig. 4 defect levels and the quality results table of comparisons, quality results S2.
(2) procedure parameter segmentation judgement
5 procedure parameter rule list of traversing graph, width are determined as that P3, finishing temperature are determined as P1.According to priority principle, P3
Priority be more than P1, so this section of procedure quality result is P3.
(3) comprehensive judgement
Show that the comprehensive judgement result of this section is to review according to allocation list.
Claims (7)
1. a kind of coil of strip is segmented the online quality judging system of multidimensional, it is characterised in that：System includes mass parameter acquisition module, industry
The regular conversion module of business, comprehensive judgement hierarchical management module, segmentation quality judging module；Business rule conversion module includes surface
Defect business rule conversion module and procedure parameter business rule conversion module；The segmentation quality judging module respectively with matter
Measure parameter collection module, comprehensive judgement hierarchical management module, surface defect business rule conversion module and procedure parameter business rule
Then conversion module is connected；Comprehensive judgement hierarchical management module and surface defect business rule conversion module and procedure parameter business
Regular conversion module is connected；
The mass parameter acquisition module obtains coil of strip and passes through the data changed when milling train, obtains coil of strip order information, obtains
Surface defect data in data and surface detecting system in field instrument equipment；
The surface defect business rule conversion module defines the decision rule on surface, is defined according to different clients, steel grade
The defect classification of each steel clock, defect rank, defect class weight are corresponded, make surface by surface defect control range
The decision rule grade table of comparisons and the defect weight table of comparisons；Surface quality results are S1, S2 ... Si, formulate and lack according to company standard
Class weight and the quality results table of comparisons are fallen into, realizes conversion of the defect rank to quality results；
Quality results P1, P2 ... the Pt of the procedure parameter business rule conversion module definition procedure class parameter, wherein t >=1,
P1 to Pt indicates procedure quality by good to poor；
All kinds of procedure parameter rule lists are formulated according to different users and steel grade, realize the fluctuation of procedure parameter to procedure quality knot
The conversion of fruit；
The comprehensive judgement hierarchical management module：Pass through the judgement etc. for business rule modulus of conversion process in the block and surface
Grade corresponds, and configures final comprehensive judgement as a result, forming comprehensive judgement grade allocation list；
Coil of strip is divided into several sections by the segmentation quality judging module, the grade of every section of difference decision process and surface,
According to priority obtain every section of coil of strip process and surface as a result, being obtained further according to comprehensive judgement grade allocation list information contrast
Every section of comprehensive judgement result and the comprehensive judgement result of entire coil of strip；
The surface defect allocation list is that determining defect classification sum is r, and defect classification Ar, each defect classification has scarce
Fall into grade G, defect class weight Kr, wherein 1 >=K1 .Kr >=0 K2 ..., and K1+K2+ ... Kr=1, defect class weight Kr with
Defect classification Ar is corresponding；
The conversion opsition dependent of the fluctuation of the procedure parameter to procedure quality result carries out rule constraint to procedure parameter, by steel
Volume is divided into certain length range and middle section end to end, the defect situation of certain length end to end is not considered or will end to end
The defect situation of certain length improves a grade in normal defect rank and is configured.
2. coil of strip as described in claim 1 is segmented the online quality judging system of multidimensional, it is characterised in that：The coil of strip passes through
The data changed when milling train include steel roll temperature, width, thickness；The coil of strip order information includes coil of strip number, steel grade, thickness
Degree, width target upper lower limit value；The field instrument equipment is calibrator and template instrument data；The surface defect data
Including defect type, position, area, number, severity.
3. coil of strip as described in claim 1 is segmented the online quality judging system of multidimensional, it is characterised in that：The defect classification
Including hole, stick up skin, scab and foreign matter, iron scale, side split, scale mark, roll marks.
4. coil of strip as described in claim 1 is segmented the online quality judging system of multidimensional, it is characterised in that：Described is certain end to end
Length is 5-10 meters.
5. a kind of coil of strip is segmented the online quality judging method of multidimensional, it is characterised in that：
Step 1: determining that surface defect can quantify, defect classification sum is r, and defect classification Ar, each defect classification has scarce
Fall into grade G, defect class weight Kr, wherein 1 >=K1 .Kr >=0 K2 ..., and K1+K2+ ... Kr=1, defect class weight with lack
It is corresponding to fall into classification Ar；Defect class weight is determined by different users and steel grade；
Quality results are S1, S2 ... Si, formulate defect class weight and the quality results table of comparisons according to company standard, realize defect
Conversion of the grade to surface quality results；
Step 2: the quality results of definition procedure class parameter, process class parametric results are defined as P1, P2 ... Pt, t >=1；P1 is arrived
Pt indicates procedure quality by good to poor；Realize that procedure parameter fluctuates the conversion opsition dependent pair to procedure quality result by position of steel coil
Procedure parameter carries out rule constraint, forming process parameter rule table；
Step 3: being corresponded by process and the judgement grade on surface, final comprehensive judgement is configured as a result, forming synthesis
Judge grade allocation list；
Step 4: the offline coil of strip not being determined of automatic checking, once finding to carry out quality judging immediately, coil of strip length is
X meters, definition is segmented per Y meters for least unit, then X/Y+1 sections shared, the surface grade in each section of judgement and procedure parameter grade；
Table inspection segmentation judgement：The quality results of each section of coil of strip are calculated, computation rule is as follows：In detection process, by each defect class
The quantity statistics I of each defect rank in notArG；Steel plate divides j sections, every section of defect level Zj=∑ Kr × G × IArG；According to defect level
The quality results of every section of steel plate are obtained with the quality results table of comparisons；Each section of quality of quality results of entire volume is worst to be determined；
Procedure parameter segmentation judgement：All procedure parameter rule lists are traversed, judge the quality results of every section of procedure parameter, entire volume
Processes result is determined by quality in wherein each section of grade is worst；
Comprehensive judgement：Every section of comprehensive judgement grade, the comprehensive judgement grade of entire volume are obtained according to comprehensive judgement grade allocation list
It is obtained by surface quality results and procedure quality result the control integrated level allocation list of entire volume；
The conversion opsition dependent for realizing procedure parameter fluctuation to procedure quality result carries out rule constraint to procedure parameter, will
Coil of strip is divided into certain length range and middle section end to end, the defect situation of certain length end to end is not considered or by head
The defect situation of tail certain length improves a grade in normal defect rank and is configured.
6. coil of strip as claimed in claim 5 is segmented the online quality judging method of multidimensional, it is characterised in that：The defect classification
Including hole, stick up skin, scab and foreign matter, iron scale, side split, scale mark, roll marks.
7. coil of strip as claimed in claim 5 is segmented the online quality judging method of multidimensional, it is characterised in that：Described is certain end to end
Length is 5-10 meters.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510146138.7A CN104751288B (en) | 2015-03-30 | 2015-03-30 | A kind of coil of strip segmentation online quality judging system and method for multidimensional |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510146138.7A CN104751288B (en) | 2015-03-30 | 2015-03-30 | A kind of coil of strip segmentation online quality judging system and method for multidimensional |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN104751288A CN104751288A (en) | 2015-07-01 |
| CN104751288B true CN104751288B (en) | 2018-10-09 |
Family
ID=53590930
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510146138.7A Active CN104751288B (en) | 2015-03-30 | 2015-03-30 | A kind of coil of strip segmentation online quality judging system and method for multidimensional |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104751288B (en) |
Families Citing this family (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105486831B (en) * | 2015-11-19 | 2017-09-12 | 武汉钢铁(集团)公司 | A kind of coil of strip quality detecting system |
| CN105277622B (en) * | 2015-12-01 | 2018-03-23 | 西南交通大学 | A kind of Railway wheelset method for detection fault detection and device |
| CN105741052A (en) * | 2016-03-04 | 2016-07-06 | 北京首钢冷轧薄板有限公司 | Strip-shaped steel defect collection method |
| CN107808241B (en) * | 2017-10-16 | 2021-08-06 | 山西太钢不锈钢股份有限公司 | Stainless steel surface detection result comprehensive analysis system |
| CN109754137B (en) * | 2017-11-03 | 2022-03-29 | 钢铁研究总院 | Method and apparatus for determining quality and/or grade of ferrous material product |
| CN108242053B (en) * | 2017-12-29 | 2020-12-01 | 武汉钢铁有限公司 | Defect image classification and collection method based on VAI surface detection system |
| CN109002974A (en) * | 2018-06-29 | 2018-12-14 | 首钢京唐钢铁联合有限责任公司 | A kind of coil of strip surface quality grading determination method and device |
| CN110175274A (en) * | 2019-05-22 | 2019-08-27 | 山西太钢不锈钢股份有限公司 | Defect system method and system based on table inspection instrument |
| CN112122352B (en) * | 2019-06-24 | 2022-03-15 | 上海梅山钢铁股份有限公司 | Control method for improving accurate positioning of defects of pickled products |
| CN110989510A (en) * | 2019-11-12 | 2020-04-10 | 邯郸钢铁集团有限责任公司 | Hot galvanizing product full-process quality control and grade automatic judgment system |
| CN111353694A (en) * | 2020-02-21 | 2020-06-30 | 湖南华菱涟源钢铁有限公司 | Steel coil quality detection method and device, terminal equipment and storage medium |
| CN111366702A (en) * | 2020-03-24 | 2020-07-03 | 包头钢铁（集团）有限责任公司 | Online intelligent accurate slitting system and online intelligent accurate slitting method for non-oriented silicon steel |
| CN111551688B (en) * | 2020-04-16 | 2022-05-20 | 北京首钢自动化信息技术有限公司 | Real-time sampling and judging method for steel manufacturing system |
| CN112785115B (en) * | 2020-11-19 | 2022-11-11 | 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 |
| CN113030422B (en) * | 2021-03-02 | 2022-12-16 | 成都积微物联电子商务有限公司 | Cold-rolled strip steel quality judgment method based on meter detection instrument detection |
| CN113151663B (en) * | 2021-04-01 | 2023-03-03 | 首钢京唐钢铁联合有限责任公司 | Control method and control system for preventing deviation of strip steel in vertical continuous annealing furnace |
| CN113094557B (en) * | 2021-04-02 | 2023-04-21 | 中冶赛迪信息技术(重庆)有限公司 | Rolling mill data association method and system |
| CN114021868A (en) * | 2021-08-16 | 2022-02-08 | 宝山钢铁股份有限公司 | Online performance grading and accurate slitting device and method for oriented silicon steel product |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102658299A (en) * | 2012-05-23 | 2012-09-12 | 河北省首钢迁安钢铁有限责任公司 | System and method for detecting and analyzing transverse thickness difference of electric steel |
| CN104461682A (en) * | 2014-10-31 | 2015-03-25 | 武汉钢铁(集团)公司 | Steel rolling steel plate simulation slitting quality judgment system and method |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE10039016B4 (en) * | 2000-08-10 | 2010-02-25 | Sms Siemag Aktiengesellschaft | Method for producing steel slabs |
| JP5453861B2 (en) * | 2008-03-31 | 2014-03-26 | Ｊｆｅスチール株式会社 | Periodic defect detection apparatus and method |
| CN102319883B (en) * | 2011-10-09 | 2014-01-29 | 北京首钢自动化信息技术有限公司 | Method for controlling on-line prediction of continuous casting blank quality |
| CN102896289B (en) * | 2012-10-19 | 2014-05-28 | 北京首钢股份有限公司 | System and method for realizing real-time tracking of casting blank |
-
2015
- 2015-03-30 CN CN201510146138.7A patent/CN104751288B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102658299A (en) * | 2012-05-23 | 2012-09-12 | 河北省首钢迁安钢铁有限责任公司 | System and method for detecting and analyzing transverse thickness difference of electric steel |
| CN104461682A (en) * | 2014-10-31 | 2015-03-25 | 武汉钢铁(集团)公司 | Steel rolling steel plate simulation slitting quality judgment system and method |
Non-Patent Citations (1)
| Title |
|---|
| 首钢迁钢在线质量判定***综述;李沛根 等;《2014年全国轧钢生产技术会议文集（上）》;20140916;摘要、正文第1-3节 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN104751288A (en) | 2015-07-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104751288B (en) | A kind of coil of strip segmentation online quality judging system and method for multidimensional | |
| CN105486831B (en) | A kind of coil of strip quality detecting system | |
| CN106345823B (en) | The method of online real-time estimate mechanical performance based on coils of hot-rolled steel production procedure | |
| CN107610469A (en) | A kind of day dimension regional traffic index forecasting method for considering multifactor impact | |
| CN110216319A (en) | A kind of cut deal optimizing shear control method based on surface quality online evaluation | |
| CN107179749A (en) | Hot dip zinc product whole process method of quality control | |
| WO2021232856A1 (en) | Big data-based online sales commodity sampling and testing method | |
| CN108256260A (en) | A kind of continuous casting billet quality Forecasting Methodology based on extreme learning machine | |
| CN110110977A (en) | It is a kind of based on improve principal component-step analysis power distribution network appraisal procedure | |
| CN104461682B (en) | A kind of steel rolling steel plate emulation cutting quality judging system and method | |
| CN113887908A (en) | Bridge risk assessment method considering subjective and objective cross fusion weight | |
| CN113159374B (en) | Data-driven urban traffic flow rate mode identification and real-time prediction early warning method | |
| CN109377050A (en) | One kind being based on risk analysis and AI artificial intelligence model risk analysis method | |
| CN112541427B (en) | Identification and material quantity evaluation method for high-quality heavy steel scrap | |
| CN110889092A (en) | Short-time large-scale activity peripheral track station passenger flow volume prediction method based on track transaction data | |
| CN111402236A (en) | Hot-rolled strip steel surface defect grading method based on image gray value | |
| CN110852600A (en) | Method for evaluating dynamic risk of market subject | |
| CN109615185A (en) | A kind of unit mass guarantee ability evaluation method based on Fuzzy AHP | |
| CN110320337A (en) | A kind of automatic evaluating system of strip surface quality and method | |
| CN113538021B (en) | Machine learning method for store duration prediction | |
| CN116109212B (en) | Airport operation efficiency evaluation index design and monitoring method | |
| Ma et al. | Effect of strip profile of hot-rolled silicon steel on transverse thickness difference of cold-rolled strip | |
| CN111459956A (en) | Engineering quality latent defect insurance (IDI) project technology risk management method and system | |
| CN111366702A (en) | Online intelligent accurate slitting system and online intelligent accurate slitting method for non-oriented silicon steel | |
| CN116384807A (en) | Method for evaluating congestion situation of airway network based on fuzzy comprehensive evaluation model |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |