CN105631231A - Method for correcting temperature measured value for hot rolling process - Google Patents

Method for correcting temperature measured value for hot rolling process Download PDF

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Publication number
CN105631231A
CN105631231A CN201610058645.XA CN201610058645A CN105631231A CN 105631231 A CN105631231 A CN 105631231A CN 201610058645 A CN201610058645 A CN 201610058645A CN 105631231 A CN105631231 A CN 105631231A
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rolled piece
measured value
temperature measured
temperature
current
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CN105631231B (en
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宋勇
孙树萌
董伟琦
何安瑞
赵海山
石俊龙
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University of Science and Technology Beijing USTB
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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
    • B21B38/006—Methods or devices for measuring, detecting or monitoring specially adapted for metal-rolling mills, e.g. position detection, inspection of the product for measuring temperature
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16Z—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS, NOT OTHERWISE PROVIDED FOR
    • G16Z99/00—Subject matter not provided for in other main groups of this subclass

Abstract

The invention belongs to the technical field of hot rolling automatic control, and in particular to a method for correcting a temperature measured value for a hot rolling process. The method comprises the steps of firstly collecting production data of historical rolled pieces in the hot rolling process; performing cluster analysis on the production data of the historical rolled pieces to obtain a classic working condition of the historical rolled pieces; performing working condition matching on a current rolled piece and the historical rolled pieces according to the production data of the historical rolled pieces and the current rolled piece; then performing data fusion to correct a temperature measured value of the current rolled piece so as to obtain a corrected temperature measured value of the current rolled piece. By the hot rolling process temperature measured data processing method, in a hot rolling method, disclosed by the invention, the influence of site environment causal factors on the accuracy of the temperature measured value can be eliminated, and an accurate corrected temperature measured value is obtained.

Description

A kind of method that course of hot rolling temperature measured value is modified
Technical field
The present invention principally falls into hot rolling automatic control technology field, is specifically related to a kind of method that course of hot rolling temperature measured value is modified.
Background technology
In operation of rolling control system, rolled piece temperature is a vital parameter, and wherein, the accuracy of measured temperature is particularly important. Accurately temperature value for instruct hot continuous rolling produce there is extremely important effect, its certainty of measurement directly determines rolling procedure setting accuracy and rolled piece temperature control effect, thus affecting dimensional accuracy and the mechanical property of product.
In process of production, rolled piece temperature survey is generally adopted by contactless infrared pyrometer, and the factor such as the steam of the operation of rolling, smog and rolled piece surface quality is likely under certain conditions its measured value be interfered.
At present, in producing at the scene, for ensureing that the main method of rolled piece measured temperature reliability is to adopt hardware redundancy, namely two or more infrared pyrometer is set on the important same position measuring point of rolling line. If certain pyrometer occurs abnormal, its measured value not in the reasonable scope, then can adopt the measurement data of standby pyrometer to produce without impact. But, if the measurement data that multiple pyrometer transmission comes up is all within zone of reasonableness, the final measurement data adopted can only be select one by artificial experience or average. Therefore, hardware redundancy method can only solve the problem that measured temperature is abnormal, and cannot successfully manage the impact that measured value precision is caused by site environment accidentalia.
For in prior art, be difficult to solve site environment accidentalia measured temperature precision is caused affect this problem, need badly exploitation a kind of method that course of hot rolling temperature measured value is modified to get rid of the impact that measured value precision is caused by site environment accidentalia.
Summary of the invention
For the problems referred to above, the invention discloses a kind of method that course of hot rolling temperature measured value is modified, the temperature measured value of the rolled piece by pyrometer is recorded is modified, obtain measured temperature after revising, it is possible to get rid of the impact that measured value precision is caused by site environment accidentalia preferably.
The present invention is achieved by the following technical solutions:
A kind of method that course of hot rolling temperature measured value is modified, first described method collects the creation data of the history rolled piece in course of hot rolling, the typical condition that history rolled piece produces is obtained by the creation data of described history rolled piece being carried out cluster analysis, by the creation data of history rolled piece and current rolled piece, current rolled piece and history rolled piece are carried out Conditions Matching, then data fusion is carried out to revise the temperature measured value of current rolled piece, it is thus achieved that measured temperature after current rolled piece correction.
Further, described creation data include rolled piece temperature measured value and with the operation of rolling parameter value of rolled piece temperature correlation, described operation of rolling parameter value includes finished product target thickness, slab time inside furnace, roughing rolling time, extreme trace time roll-force, roughing exit thickness and the whole or arbitrarily several combination in the delay table time.
Further, described method specifically includes following steps:
(1) creation data of history rolled piece is collected: collect the temperature measured value rolling every piece of history rolled piece in complete process from coming out of the stove to and the operation of rolling parameter value with rolled piece temperature correlation;
(2) cluster analysis obtains the typical condition that history rolled piece produces: by the described temperature measured value of every piece of history rolled piece in step (1) and described operation of rolling parameter value composition sample object, and the sample object of the N block history rolled piece produced recently is formed sample set D, wherein N is more than 1000;
Described sample set D is carried out the cluster analysis based on distance, the sample object of each cluster centre is set to the typical condition of this cluster classification, be designated as sample Dk *, wherein, k is cluster classification number, calculates its cluster radius Rk, and calculate the meansigma methods of the described temperature measured value of all sample object in this cluster classificationAnd confidence level Zk (M), described temperature measured value is recorded by the pyrometer at M;
(3) Conditions Matching
Obtain the current rolled piece j that pyrometer at M place records temperature measured value and with the operation of rolling parameter value of rolled piece temperature correlation, form sample object, calculate the typical condition sample D of each cluster in the sample object of current rolled piece j and step (2)k *Distance djk; The sample object of current rolled piece j is minimum with the distance of the cluster that cluster classification number is k, then the cluster classification number of current rolled piece j is also k;
(4) measured temperature step after the current rolled piece correction of data fusion acquisition: after step (3) Conditions Matching, the cluster classification number obtaining current rolled piece j is k,For current rolled piece j measured temperature after the correction of the pyrometer at M place, its computing formula is as follows:
T ^ j ( M ) = ( 1 - α ) · T j ( M ) + α · T ‾ k ( M ) - - - ( 1 )
Wherein, �� is fusion coefficients, Tj (M)For the temperature measured value that the current rolled piece j pyrometer at M place records.
Further, the computing formula of step (4) described fusion coefficients �� is:
α = λ · ( 1 - Z k ( M ) ) ( 1 - G ) · ( 1 - d j k R k ) - - - ( 2 )
Wherein, �� is adjustment factor, and the span of �� is 0.8��1.0; G is the confidence level of the temperature measured value that the current rolled piece j pyrometer at M place records.
Further, whenTime, ��=0.
Further, described M place is any one place in roughing porch, roughing exit, finish rolling porch, finish rolling exit, section cooling porch and laminar flow exit.
The Advantageous Effects of the present invention:
(1) method that course of hot rolling temperature measured value is modified disclosed by the invention, the temperature measured value of the rolled piece that pyrometer is recorded is modified, utilize the creation data of substantial amounts of history rolled piece in producing, typical condition is obtained by cluster analysis, obtain measured temperature after revising, it is possible to get rid of the impact that measured value precision is caused by site environment accidentalia preferably.
(2) creation data of history rolled piece is carried out the cluster analysis based on distance by the present invention, and the typical condition obtained can provide reference value for the rolled piece temperature survey under current similar working condition.
(3) can be seen that from fusion coefficients formula, the value of fusion coefficients can adjust automatically according to factors such as the matching degrees of the confidence level of the temperature measured value of current rolled piece and current rolled piece operating mode and history rolled piece typical condition, and fusion treatment therefore can be made to be attained by good effect in varied situations.
Accompanying drawing explanation
Fig. 1 be heretofore described course of hot rolling temperature measuring data processing method in data anastomosing algorithm schematic diagram;
The location drawing of pyrometer when Fig. 2 is adopt hardware redundancy to ensure rolled piece measured temperature reliability in conventional art;
Fig. 3 be course of hot rolling temperature measuring data of the present invention processing method in data anastomosing algorithm block diagram.
Detailed description of the invention
In order to make the purpose of the present invention, technical scheme and advantage clearly understand, below in conjunction with drawings and Examples, the present invention is explained in further detail. Should be appreciated that specific embodiment described herein is used only for explaining the present invention, be not intended to limit the present invention.
On the contrary, the present invention contains any replacement made in the spirit and scope of the present invention, amendment, equivalent method and scheme being defined by the claims. Further, in order to make the public that the present invention to be had a better understanding, in below the details of the present invention being described, detailed describe some specific detail sections. The description not having these detail sections for a person skilled in the art can also understand the present invention completely.
Embodiment 1
A kind of method that course of hot rolling temperature measured value is modified, first described method collects the creation data of the history rolled piece in course of hot rolling, the typical condition that history rolled piece produces is obtained by the creation data of described history rolled piece being carried out cluster analysis, by the creation data of history rolled piece and current rolled piece, current rolled piece and history rolled piece are carried out Conditions Matching, then data fusion is carried out to revise the temperature measured value of current rolled piece, it is thus achieved that measured temperature after current rolled piece correction.
Described creation data include in course of hot rolling the rolled piece on production line measured by pyrometer temperature measured value and with the operation of rolling parameter value of rolled piece temperature correlation, described operation of rolling parameter value includes finished product target thickness, slab time inside furnace, roughing rolling time, extreme trace time roll-force, roughing exit thickness and the whole or arbitrarily several combination in the delay table time.
In the technological parameter that Hot Strip Rolling is many, temperature is it is critical that a parameter, and its forecast precision is to ensure that the key of the quality index hit rates such as the plate shape of product, thickness, width, is also the important foundation being effectively improved end product quality level. The factor affecting temperature in hot continuous rolling is a lot, and each factor is many to intercouple again, if adopting artificial analysis method completely, workload and difficulty are all very big. The present invention adopts course of hot rolling temperature measuring data treatment method accurately to revise temperature measured value, utilize the creation data of substantial amounts of history rolled piece in producing, typical condition is obtained by cluster analysis, obtain measured temperature after revising, it is possible to get rid of the impact that measured value precision is caused by site environment accidentalia preferably.
The finished product target thickness that the present embodiment rolls with certain steel mill is for 2.95mm, and steel grade is the creation data of Q235B is example, and the temperature measured value of the rolled piece that the pyrometer of finish rolling porch (taking finish rolling porch is M place) is recorded is modified.
As shown in Figures 1 and 3, the method temperature measured value of finish rolling porch being modified specifically includes following steps:
(1) collect the creation data of history rolled piece: collect from rolling complete process of coming out of the stove every piece of history rolled piece the temperature measured value of finish rolling porch (M) and with the operation of rolling parameter value of rolled piece temperature correlation;
The described operation of rolling parameter value with rolled piece temperature correlation includes finished product target thickness, slab time inside furnace, roughing rolling time, extreme trace time roll-force, roughing exit thickness and whole in the delay table time. Because the temperature measured value of finish rolling entrance is had impact by roughing outlet temperature measured value, so when collecting the creation data of history rolled piece, also the roughing outlet temperature measured value of history rolled piece is collected.
(2) cluster analysis obtains the typical condition that history rolled piece produces:
By the described temperature measured value in finish rolling porch of the every piece of history rolled piece in step (1) and described operation of rolling parameter value composition sample object, and the sample object composition sample set D of N block history rolled piece that will produce recently, wherein N is 1261;
Described sample set D is carried out the cluster analysis based on distance, obtains 9 cluster classifications, be respectively labeled as cluster classification 1, cluster classification 2 ... cluster classification 9. The sample object at the center of each cluster is set to the typical condition of this cluster classification, is designated as sample Dk *, wherein, k is the cluster classification number after cluster analysis, k=1,2 ... 9, each typical condition sample Dk *Corresponding numerical result is as shown in table 1.
Table 1 typical condition sample Dk *List
Calculate and record the number of samples of each cluster classification, calculate and record the cluster radius R of each cluster classification according to Euclidean distance formula successivelyk, and the meansigma methods of the entry temperature at finishing measured value calculated in this cluster classification in all sample object (namely the pyrometer at M place records)And confidence level Zk (M); 9 meansigma methodss clustering the number of samples of classification, entry temperature at finishing measured valueConfidence level Zk (M), result is as shown in table 2.
Table 2 clusters classification parameter table
(3) Conditions Matching
Obtain the entry temperature at finishing measured value of current rolled piece j and all operation of rolling parameter values (as shown in table 3) with rolled piece temperature correlation, composition sample object, calculates sample object and the typical condition sample D of each cluster in step (3) of current rolled piece jk *Euclidean distance djk, result is as shown in table 4,
The current rolled piece sample object table of table 3 part
The each current rolled piece of table 4 is to the distance values table of each cluster centre
If the sample object of current rolled piece j and the Euclidean distance d clustering the cluster that classification number is kjkMinimum, then the cluster classification number of current rolled piece j is also k; According to table 4, obtain the cluster classification number k (namely clustering classification number) belonging to each current rolled piece, as shown in table 5.
The current cluster belonging to rolled piece of table 5
(4) measured temperature step after the current rolled piece correction of data fusion acquisition:
To above-mentioned current rolled piece sample, calculate according to following equation (2) and obtain fusion coefficients ��.
α = λ · ( 1 - Z k ( M ) ) ( 1 - G ) · ( 1 - d j k R k ) - - - ( 2 )
Wherein, �� is adjustment factor, and different working conditions takes different adjustment factors, and the span of number �� is [0.8��1.0]; G is the current rolled piece j confidence level at finish rolling entrance M place temperature measured value (namely recording at the pyrometer at M place); Zk (M)When cluster number for obtaining according to step (1) calculating is k, the confidence level of the described temperature measured value of all sample object in this cluster classification; djkThe sample object of current rolled piece j and the typical condition sample D of each cluster in step (3)k *Distance; RkWhen being k for cluster number, the radius of this cluster; Work as djk��RkTime, ��=0.
Wherein, the current rolled piece j of determination Main Basis of adjustment factor �� is to its Euclidean distance of cluster that cluster classification number is k mated, i.e. djkSize. Assume a kind of limiting case,Level off to 0 time, i.e. djkLevel off to 0, then the mean temperature now clustering classification k accounts for the great ratio of correction temperature during fusion treatment, now takes adjustment factor ��=1; IfLevel off to 1, then prove the observed temperature of current rolled piece j and cluster classification k the mean temperature similarity of cluster be not as high. Then now clustering the ratio revising temperature when the mean temperature of classification k accounts for fusion treatment relatively low, now taking adjustment factor is ��=0.8. In sum, according toSpan, in conjunction with practical condition, select the value of adjustment factor ��.
Each parameter values in fusion coefficients �� and formula (2) is as shown in table 6 below.
The fusion parameters of the current rolled piece sample of table 6 part and relevant parameter numerical tabular
Calculating current rolled piece j measured temperature after the correction of the temperature measured value (pyrometer at M place records) of finish rolling porch according to formula (1) is
T ^ j ( M ) = ( 1 - α ) · T j ( M ) + α · T ‾ k ( M ) - - - ( 1 )
Wherein, �� is above-mentioned formula (2) calculated fusion coefficients, for the proportion shared in data fusion process with the average temperature value of the current rolled piece j cluster classification mated; The proportion that the observed temperature value that (1-��) is current rolled piece j rolled piece is shared in data fusion process; Tj (M)For the temperature measured value that the current rolled piece j pyrometer at finish rolling entrance M place records;When cluster number for obtaining according to step (1) calculating is k, the meansigma methods of the described temperature measured value of all sample object in this cluster classification. Shown in result table 7 below, can be seen that, current rolled piece is obtained for correction in various degree at finish rolling inlet temperature measured value (namely the pyrometer at M place records), particularly the entry temperature at finishing measured value 988.53 DEG C of current rolled piece sample 6 is significantly lower than the meansigma methods 1021.41 DEG C of the temperature measured value of the history rolled piece in its affiliated cluster classification (cluster classification number is 5), and this is likely due to entry temperature at finishing meter and receives the impact of water vapour or iron scale and cause measured value on the low side.
Table 7 entry temperature at finishing Measurement fusion result of calculation table
For ensureing that the main method of rolled piece measured temperature reliability is to adopt hardware redundancy (such as Fig. 2) in conventional art, the important same position measuring point of rolling line arranges two or more infrared pyrometer. But, if the measurement data that multiple pyrometer transmission comes up is all within zone of reasonableness, the final measurement data adopted can only be select one by artificial experience or average. Visible hardware redundancy method can only solve the problem that measured temperature is abnormal, and cannot successfully manage the impact that measured value precision is caused by site environment accidentalia. Compared with conventional art, in the present invention, the processing method of course of hot rolling temperature measuring data can eliminate the interference to measured temperature of this environment accidentalia to a certain extent.
Rough rolling process that a kind of method that course of hot rolling temperature measured value is modified provided by the present invention can apply in course of hot rolling, finishing stands, laminar cooling process, specifically may be used for revising the temperature measured value of the pyrometer used in above three process.

Claims (6)

1. the method that course of hot rolling temperature measured value is modified, it is characterized in that, first described method collects the creation data of the history rolled piece in course of hot rolling, the typical condition that history rolled piece produces is obtained by the creation data of described history rolled piece being carried out cluster analysis, by the creation data of history rolled piece and current rolled piece, current rolled piece and history rolled piece are carried out Conditions Matching, then data fusion is carried out to revise the temperature measured value of current rolled piece, it is thus achieved that measured temperature after current rolled piece correction.
2. a kind of method that course of hot rolling temperature measured value is modified according to claim 1, it is characterized in that, described creation data include rolled piece temperature measured value and with the operation of rolling parameter value of rolled piece temperature correlation, described operation of rolling parameter value includes finished product target thickness, slab time inside furnace, roughing rolling time, extreme trace time roll-force, roughing exit thickness and the whole or arbitrarily several combination in the delay table time.
3. a kind of method that course of hot rolling temperature measured value is modified according to claim 1, it is characterised in that described method specifically includes following steps:
(1) creation data of history rolled piece is collected: collect the temperature measured value rolling every piece of history rolled piece in complete process from coming out of the stove to and the operation of rolling parameter value with rolled piece temperature correlation;
(2) cluster analysis obtains the typical condition that history rolled piece produces: by the described temperature measured value of every piece of history rolled piece in step (1) and described operation of rolling parameter value composition sample object, and the sample object of the N block history rolled piece produced recently is formed sample set D, wherein N is more than 1000;
Described sample set D is carried out the cluster analysis based on distance, the sample object of each cluster centre is set to the typical condition of this cluster classification, be designated as sample Dk *, wherein, k is cluster classification number, calculates its cluster radius Rk, and calculate the meansigma methods of the described temperature measured value of all sample object in this cluster classificationAnd confidence level Zk (M), described temperature measured value is recorded by the pyrometer at M;
(3) Conditions Matching
Obtain the current rolled piece j that pyrometer at M place records temperature measured value and with the operation of rolling parameter value of rolled piece temperature correlation, form sample object, calculate the typical condition sample D of each cluster in the sample object of current rolled piece j and step (2)k *Distance djk; The sample object of current rolled piece j is minimum with the distance of the cluster that cluster classification number is k, then the cluster classification number of current rolled piece j is also k;
(4) measured temperature step after the current rolled piece correction of data fusion acquisition: after step (3) Conditions Matching, the cluster classification number obtaining current rolled piece j is k,For current rolled piece j measured temperature after the correction of the pyrometer at M place, its computing formula is as follows:
T ^ j ( M ) = ( 1 - α ) · T j ( M ) + α · T ‾ k ( M ) - - - ( 1 )
Wherein, �� is fusion coefficients, Tj (M)For the temperature measured value that the current rolled piece j pyrometer at M place records.
4. a kind of method that course of hot rolling temperature measured value is modified according to claim 3, it is characterised in that the computing formula of step (4) described fusion coefficients �� is:
α = λ · ( 1 - Z k ( M ) ) ( 1 - G ) · ( 1 - d j k R k ) - - - ( 2 )
Wherein, �� is adjustment factor, and the span of �� is 0.8��1.0; G is the confidence level of the temperature measured value that the current rolled piece j pyrometer at M place records.
5. a kind of method that course of hot rolling temperature measured value is modified according to claim 5, it is characterised in that work as djk��RkTime, ��=0.
6. a kind of method that course of hot rolling temperature measured value is modified according to claim 3 or 4, it is characterized in that, described M place is any one place in roughing porch, roughing exit, finish rolling porch, finish rolling exit, section cooling porch and laminar flow exit.
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