JPS63168209A - Method and apparatus for estimating shape of steel plate - Google Patents
Method and apparatus for estimating shape of steel plateInfo
- Publication number
- JPS63168209A JPS63168209A JP61311770A JP31177086A JPS63168209A JP S63168209 A JPS63168209 A JP S63168209A JP 61311770 A JP61311770 A JP 61311770A JP 31177086 A JP31177086 A JP 31177086A JP S63168209 A JPS63168209 A JP S63168209A
- Authority
- JP
- Japan
- Prior art keywords
- steel plate
- temp
- temperature
- temperature distribution
- characteristic values
- 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.)
- Granted
Links
- 229910000831 Steel Inorganic materials 0.000 title claims abstract description 76
- 239000010959 steel Substances 0.000 title claims abstract description 76
- 238000000034 method Methods 0.000 title claims description 25
- 238000001816 cooling Methods 0.000 claims abstract description 37
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 16
- 239000006185 dispersion Substances 0.000 claims abstract description 6
- 238000002347 injection Methods 0.000 claims description 5
- 239000007924 injection Substances 0.000 claims description 5
- 238000009434 installation Methods 0.000 abstract 1
- 238000010586 diagram Methods 0.000 description 6
- 239000000463 material Substances 0.000 description 6
- 230000005484 gravity Effects 0.000 description 4
- 238000005096 rolling process Methods 0.000 description 3
- 239000007921 spray Substances 0.000 description 3
- 230000000694 effects Effects 0.000 description 2
- 238000005098 hot rolling Methods 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 239000013589 supplement Substances 0.000 description 2
- 229910004613 CdTe Inorganic materials 0.000 description 1
- 238000009529 body temperature measurement Methods 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 239000000284 extract Substances 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- PCHJSUWPFVWCPO-UHFFFAOYSA-N gold Chemical compound [Au] PCHJSUWPFVWCPO-UHFFFAOYSA-N 0.000 description 1
- 239000010931 gold Substances 0.000 description 1
- 229910052737 gold Inorganic materials 0.000 description 1
- 230000002747 voluntary effect Effects 0.000 description 1
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B21—MECHANICAL METAL-WORKING WITHOUT ESSENTIALLY REMOVING MATERIAL; PUNCHING METAL
- B21B—ROLLING OF METAL
- B21B37/00—Control devices or methods specially adapted for metal-rolling mills or the work produced thereby
- B21B37/28—Control of flatness or profile during rolling of strip, sheets or plates
- B21B37/44—Control of flatness or profile during rolling of strip, sheets or plates using heating, lubricating or water-spray cooling of the product
-
- 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
- B21B2261/21—Temperature profile
Abstract
Description
【発明の詳細な説明】
〔産業上の利用分野〕
本発明は、冷却制御プロセスにより急速冷却された鋼板
の形状推定方法及び装置に関する。DETAILED DESCRIPTION OF THE INVENTION [Field of Industrial Application] The present invention relates to a method and apparatus for estimating the shape of a steel plate rapidly cooled by a cooling control process.
厚板の熱間圧延工程では、圧延最終段から出てきた鋼板
に注水して所定温度に急速冷却することが行なわれる。In the process of hot rolling thick plates, water is poured into the steel plate coming out of the final stage of rolling to rapidly cool it to a predetermined temperature.
この制御冷却（ＣＬ Ｃ）工程を経た例えば圧延長６〜
４０ｍ１圧延幅１〜４．５ｍのｗｉ坂はその後条切りさ
れ、例えば幅４０（！ｌの帯状体にされ、次工程へ渡さ
れる。For example, after passing through this controlled cooling (CLC) process,
The 40 m1 rolling width 1 to 4.5 m width is then cut into strips, for example, 40 (!l) wide, and passed on to the next process.
この条切りされた鋼板にキャンバ−が発生し、また耳波
、中伸びが発生することがある。これは鋼板の温度分布
が原因である。即ちＣＬＣ工程では鋼板両縁上に遮蔽板
（エツジマスク）を配置し・これを鋼帯中心線側へ突出
させまた端縁側へ退去させて鋼板幅方向温度分布を関節
する（フラットであるのが良好）が、これが適切に行な
われないと第８図Ａ−Ｄ等の温度分布になる。Ａは両縁
の温度が低いケース、Ｂは逆に高いケースで、前者は耳
波を発生させ、後者は中波（中伸び）を発生させる。Ｃ
のように中央部より両端縁が高く、少し中へ入ると逆に
低くなるケースもあり、これも耳波を発生させる。Ｄは
フラットなケースで、この場合耳波も中伸びも発生しな
い。ケースＡは水冷による両縁の冷却が著しい場合で、
エツジマスク（Ｅ／Ｍ）制御は不良（過小）である、Ｂ
のケースは水冷による両縁の冷却が過小、Ｅ／Ｍ制御は
過大、である。Camber may occur in the cut steel sheet, and ear waves and elongation may occur. This is caused by the temperature distribution of the steel plate. That is, in the CLC process, shielding plates (edge masks) are placed on both edges of the steel plate, and these are made to protrude toward the center line of the steel strip and retreat toward the edges to adjust the temperature distribution in the width direction of the steel plate (flat is better. ), but if this is not done properly, a temperature distribution such as that shown in FIG. 8A to D will result. A is a case where the temperature at both edges is low, and B is a case where the temperature is high.The former generates ear waves, and the latter generates medium waves (medium extension). C
There are also cases where the edges are higher than the center, and conversely become lower as you move a little further in, which also causes ear waves. D is a flat case, in which neither ear waves nor mid-length extension occur. Case A is a case where both edges are significantly cooled by water cooling.
Edge mask (E/M) control is poor (too small), B
In the case of , the cooling of both edges by water cooling is too little, and the E/M control is too much.
キャンバ−は、やはり幅方向温度分布がフラットでない
と発生する。第５図で説明すると、（ａ）はＣＬＣ設備
を出た直後の鋼板を条切りされた状態で示し、この鋼板
１０ａの一方の端縁Ｓａの温度は高＜（Ｈ）、他方の端
縁ｓｂの温度は低い（Ｌ）とすると、冷却後は（ｂｌに
示すようにｓｂ側が伸びてキャンバ−のついた鋼板１０
ｂになる。金鋼板１０の温度プロフィールが第８図Ａの
如くであり、これを第５図（Ｃ１の如く条切りしたとす
ると、冷却後は第５図（ｄ＋の如くキャンバ−が付く。Camber also occurs when the temperature distribution in the width direction is not flat. To explain this with reference to FIG. 5, (a) shows a steel plate immediately after leaving the CLC equipment in a cut state, and the temperature at one edge Sa of this steel plate 10a is high < (H), and the temperature at the other edge Sa is Assuming that the temperature of sb is low (L), after cooling, the steel plate 10 is stretched on the sb side and has a camber as shown in bl.
It becomes b. If the temperature profile of the gold steel plate 10 is as shown in FIG. 8A, and it is cut into strips as shown in FIG. 5 (C1), after cooling it will have a camber as shown in FIG. 5 (d+).
また該鋼板の温度プロフィールが第８図Ｂの如くである
と、冷却後は第５図（ｅ）の如くキャンバ−が付く。Further, if the temperature profile of the steel plate is as shown in FIG. 8B, camber will be formed after cooling as shown in FIG. 5(e).
第５図＋ａ）の鋼帯１０ａの端縁Ｓａ、Ｓｂに温度差が
あると、冷却後どの程度のキャンバ−かつ（かを実測し
た結果を第４図に示す。この鋼帯１０ａの長さは１８ｍ
１幅は４００ｍで、温度分布は全長に亘ってＡプロフィ
ール又はＢプロフィールである。このグラフから温度差
ΔＴが大になる程キャンバー量は大になり、両者はほり
比例すると見做せる。If there is a temperature difference between the edges Sa and Sb of the steel strip 10a in FIG. 5+a), the results of actual measurements of how much camber and () will occur after cooling are shown in FIG. 4.The length of this steel strip 10a is 18m
1 width is 400 m, and the temperature distribution is A profile or B profile over the entire length. From this graph, it can be seen that the larger the temperature difference ΔT, the larger the amount of camber, and that the two are roughly proportional.
このように、ＣＬＣ工程を出た直後の鋼板温度分布を知
ると、条切り後かつ冷却後の鋼帯の耳波、中伸び、キャ
ンバ一つまり形状を推定することが可能である０本発明
はか＼る点に着目するものであり、鋼板温度分布を計測
して形状を推定しようとするものである。In this way, by knowing the temperature distribution of the steel strip immediately after exiting the CLC process, it is possible to estimate the ear wave, mid-elongation, camber, or shape of the steel strip after strip cutting and cooling. This method focuses on these points, and attempts to estimate the shape by measuring the temperature distribution of the steel sheet.
形状を知ってＣＬＣ工程の冷却制御、次工程の修正制御
等を行なうには形状を定量的に把握する必要がある。形
状を定量的に、正確に把握するには精密な鋼板温度分布
の計測が必要であり、本発明はまたこの精密な鋼板温度
分布の測定法を提案するものである。In order to know the shape and perform cooling control in the CLC process, correction control in the next process, etc., it is necessary to understand the shape quantitatively. In order to quantitatively and accurately grasp the shape, it is necessary to precisely measure the temperature distribution of the steel plate, and the present invention also proposes a method for measuring this precise temperature distribution of the steel plate.
本発明は、熱間圧延された鋼板の注水冷却制御工程の直
後で温度センサにより鋼板表面の板幅方向および板長平
方向の二次元温度分布を測定し、咳板幅方向温度分布よ
り、少なくとも板中央部と両端縁部の高、低温度差を示
す特徴値（ａ、ｅ。The present invention measures the two-dimensional temperature distribution of the steel sheet surface in the sheet width direction and the sheet longitudinal direction using a temperature sensor immediately after the water injection cooling control process of a hot rolled steel sheet, and from the temperature distribution in the sheet width direction, at least Characteristic values (a, e) indicating high and low temperature differences between the center and both edges.
ｂ、ｒ）を求め、また該鋼板を板長平方向で複数区分に
分割したその各、領域における前記二次元温度分布より
鋼板表面温度の分散を示す特徴値を求め、これらの特徴
値より、鋼板冷却後かつ条切り後の板形状を推定するこ
とを特徴とするものである。b, r), and the characteristic values indicating the dispersion of the steel plate surface temperature are determined from the two-dimensional temperature distribution in each region of the steel plate divided into a plurality of sections in the horizontal direction of the plate length. From these characteristic values, the steel plate This method is characterized by estimating the shape of the plate after cooling and cutting.
この発明によれば、ＣＬＣ材の冷却後の形状を推定して
散水冷却の制御、次工程への修正データの提供、ディス
プレイに表示してオペレータによる制御、調整に寄与す
ることができ甚だ有効である。According to this invention, the shape of the CLC material after cooling can be estimated to control water spray cooling, provide correction data to the next process, and display it on a display to contribute to operator control and adjustment, which is extremely effective. be.
第１図に本発明の実施例を示す、ＦＭは厚板熱間圧延の
最終圧延段、ＣＬＣは前述の散水による冷却制御設備で
ある。１２は温度センサで、光電変換素子としてＨｇ
Ｃｄ Ｔｅを用い、測温レンジは一５０℃〜２０００℃
、測定精度は±３．５℃（１２０〜８００℃）である。An embodiment of the present invention is shown in FIG. 1, where FM is the final rolling stage for hot rolling of thick plates, and CLC is the cooling control equipment using the water spray described above. 12 is a temperature sensor, which uses Hg as a photoelectric conversion element.
Using CdTe, the temperature measuring range is -50℃ to 2000℃
, the measurement accuracy is ±3.5°C (120-800°C).
ミラー走査により鋼板１０の幅方向温度分布を測定し、
鋼板１０の移動につれてこれを繰り返すので第７図に示
すように鋼板幅方向で１、＋＝２０ｍ、鋼板長さ方向で
Ｌ２＝５５ｆｉの小区域毎の温度を測定することができ
る。この小区域を画素と呼び、鋼板全体では３２万点な
どの多数になる。温度センサ１２の出力は計装マイコン
１４に一旦取込まれ、それよりＣＬＣ材温度分布パター
ン判定装置１６へ高速転送され、こ＼で温度データの収
集、加工が行なわれ、その収集、加工データＤは冷却制
御プロコン１８へ送られる。Measuring the temperature distribution in the width direction of the steel plate 10 by mirror scanning,
Since this process is repeated as the steel plate 10 moves, it is possible to measure the temperature in each small area of 1.+=20 m in the width direction of the steel plate and L2=55 fi in the length direction of the steel plate, as shown in FIG. These small areas are called pixels, and there are a large number of pixels, such as 320,000 points, on the entire steel plate. The output of the temperature sensor 12 is once taken into the instrumentation microcomputer 14, and then transferred at high speed to the CLC material temperature distribution pattern determination device 16, where temperature data is collected and processed, and the collected and processed data D is sent to the cooling control processor 18.
また鋼板各部の温度レベルを色で表現し、この多色画像
をディスプレイ２０に表示し、また所要ブータラフロッ
ピーディスク２２に格納する。Furthermore, the temperature level of each part of the steel plate is expressed in color, and this multicolor image is displayed on the display 20 and stored in the required booter floppy disk 22.
判定装置１６の処理内容を第２図に示す。温度センサ１
２の温度計測データ（鋼板表面を幅方向に主走査、長さ
方向に副走査して得られた２次元データで、イメージデ
ータともいう）を、計装マイコン１４を通してイメージ
データファイル１６ａへ取込み、該イメージデータを前
処理して特徴量計算対象データを得、該データにより平
均濃度等を算出し、これらを特徴量ファイル１６ｂへ格
納したのち前記冷却制御プロコン１８へ伝送する。The processing contents of the determination device 16 are shown in FIG. Temperature sensor 1
2 temperature measurement data (two-dimensional data obtained by main scanning the steel plate surface in the width direction and sub-scanning in the length direction, also referred to as image data) is taken into the image data file 16a through the instrumentation microcomputer 14, The image data is pre-processed to obtain feature calculation target data, average density, etc. are calculated from the data, and after being stored in the feature file 16b, it is transmitted to the cooling control processor 18.
第３図はこの部分のハードウェアを示す。１６ｄはイメ
ージデータの処理プロセッサ、１６ｅは判定装置１６全
体のプロセッサである。FIG. 3 shows the hardware of this part. 16d is an image data processing processor, and 16e is a processor for the entire determination device 16.
また当該鋼板の板幅、板厚、全長、材質などの数値デー
タを受信し、これをファイル１６ｃへ格納したのち、フ
ァイル１６ａ、１６ｂのイメージデータおよび特徴量と
共にディスプレイ２０に表示する。It also receives numerical data such as the width, thickness, overall length, material, etc. of the steel plate, stores it in the file 16c, and then displays it on the display 20 together with the image data and feature quantities of the files 16a and 16b.
温度センサー２の幅方向１走査分の出力は例えば第７回
申）に示す如くである。か＼る温度分布における図示温
度差ａ ｗ ｄを求め、右側部分についても同様にする
。この温度差（特徴１ｉ）ａ−ｈは第８図Ａ−Ｄの定量
的表現になる。The output of the temperature sensor 2 for one scan in the width direction is, for example, as shown in the seventh report. Find the indicated temperature difference a w d in the temperature distribution, and do the same for the right side. This temperature difference (characteristic 1i) a-h becomes the quantitative expression of FIG. 8A-D.
また特徴量として平均濃度（平均温度） ＭＥＡＧ、濃
淡分散ＶＡＲＧ、面積率８１重心ｇ、 ＲＭＩＮ、 Ｒ
ＭＡＸ比。In addition, the feature values are average density (average temperature) MEAG, gray scale variance VARG, area ratio 81 center of gravity g, RMIN, R
MAX ratio.
およびＸ、Ｙ軸投影幅を求める。第６図でこれらを説明
すると、平均濃度は、鋼板温度がＴＩ、Ｔ２゜Ｔ３で第
６図（ａ）の分布を有するとし、この鋼板の全温度画素
数をＧ ［１、温度ＴＩ、Ｔ２．Ｔ３部分の画素数をＧ
皇、Ｇ２．Ｇ３とすれば
であり、一般化すれば
である。濃淡分散は
で表わされ、ＶＡＲＧ＝ ０のとき均一冷却である。ま
た面積率は第６回申）に示すように特定の温度Ｔ２の領
域の全領域に対する比を言い、
Ｓ＝ （ａ＋＋ａ２＞／ｌｔ＋Ｉ１２
で表わされる。重心ｇは温度分布が第６図（Ｃ）の如（
であるとして、この分布の重心ｇをそのＸ、 Ｙ座標で
求める。ＲＭＩＮ、 ＲＭＡＸ比は第６図（ｄ）に示す
ように特定分布領域の重心ｇから最小距離と最大距離と
比（ＲＲＡＴ）を言い、
ＲＲＡＴ＝ ＲＭＩＮ２／ ＲＭＡＸ２＝ａ ｇ２／
ｂ ｇ２で表わされる。またＸ、Ｙ軸投影幅は第６図（
ｄ）のＡ、Ｂをいう。この特徴ｉ１ＭＥＡＧ、・・・・
・・は鋼板を長手方向で分割し、その所定の各領域に対
して求める。メモリ上で言えばこれは５１２Ｘ ５１２
画素のディジタルデータであり、各画素の温度は８ビツ
トで表わされる。特徴量抽出に当ってはノイズ除去（原
画像に対して３×３の重み付き空間フィルタリングをＮ
回繰り返す）、マスクパターン作成（鋼板部、背景部の
各温度のヒストグラムを作り、これによりスライスレベ
ルを得、原画像を２値化し、マスクパターンを作成）、
計算対象部の抽出などを行なう。And calculate the X and Y axis projected width. To explain these using FIG. 6, the average density has the distribution shown in FIG. 6(a) when the steel plate temperature is TI, T2°T3, and the total number of temperature pixels of this steel plate is G [1, temperature TI, T2. The number of pixels in the T3 part is G
Emperor, G2. If you call it G3, then yes, if you generalize it. The density dispersion is expressed as: When VARG=0, uniform cooling is achieved. In addition, as shown in the 6th report, the area ratio refers to the ratio of the area of a specific temperature T2 to the whole area, and is expressed as S = (a++a2>/lt+I12).The center of gravity g is the temperature distribution as shown in Figure 6 (C). Like (
, find the center of gravity g of this distribution using its X and Y coordinates. The RMIN, RMAX ratio is the ratio of the minimum distance to the maximum distance (RRAT) from the center of gravity g of a specific distribution area, as shown in Figure 6 (d), and RRAT = RMIN2/ RMAX2 = a g2/
b It is expressed as g2. Also, the X and Y axis projected widths are shown in Figure 6 (
d) A and B. This feature i1MEAG...
... is calculated for each predetermined area of the steel plate divided in the longitudinal direction. In terms of memory, this is 512X 512
This is digital data of pixels, and the temperature of each pixel is represented by 8 bits. When extracting features, noise is removed (3×3 weighted spatial filtering is applied to the original image with N
(repeat twice), mask pattern creation (create a histogram of each temperature of the steel plate part and background part, obtain the slice level from this, binarize the original image, create a mask pattern),
Extracts the part to be calculated.
以上説明したように、本発明によればＣＬＣ材の冷却後
の形状を推定して散水冷却の制御、次工程への修正デー
タの提供、ディスプレイに表示してオペレータによる制
御、調整に寄与することができ甚だ有効である。As explained above, according to the present invention, the shape of the CLC material after cooling can be estimated to control water spray cooling, provide correction data to the next process, and display it on a display to contribute to operator control and adjustment. It is very effective.
第１図は本発明の詳細な説明図、
第２図および第３図は第１図の制御系のブロック図、
第４図は温度差とキャンバ−の関係図、第５図はキャン
バ−発生の説明図、
第６図は特徴量の説明図、
第７図は温度センサの出力の説明図、
第８図は温度プロフィールと形状の関係図である。
図面で１０は鋼板、１２は温度センサ、１６は温度分布
パターン判定装置、１０ａは条切りされた鋼帯である。
出 願 人 新日本製鐵株式会社
代理人弁理士 青 柳 稔
制得系のブ０・ソクロ
第３図
→２ｌ−ＷＳ
Ｌ２
（ｔｌ）
；態度ｔ７すの出Ｖの説明３
第７図
；Ｌ度プロフィールヒ形状関係囮
！￥８図
手続補正書（自発）
１、事件の表示
昭和６１年特許願第３１）７７０号
明の名称
鋼板の形状推定方法および装置
３、補正をする者
事件との関係 特許出願人
住所 東京都千代田区大手町二丁目６番３号名称 （６
６５）新日本製鐵株式会社
代表者 武 １） 豊
埋入 〒１０１
住 所 東京都千代田区岩本町３丁目４番５号第−東
ビル１０氏 名 （７０１７）弁理士 青 柳
稔１ジ正命令の日付 な し
王によシ増加する発明の数 な し
７、補
８、補
８、補正の内容
（１）明細書の特許請求の範囲を次の様に補正する。
「（１）熱間圧延された鋼板の注水冷却制御工程の直後
で温度センサにより鋼板表面の板幅方向および坂長手方
向の二次元温度分布を測定し、該板幅方向温度分布より
、少なくとも板中央部と両端縁部の高、低温度差を示す
特徴値（ａｔｅ、ｂ、ｆ）を求め、また該鋼板を板長平
方向で複数区分に分割したその各領域における前記二次
元温度分布より鋼板表面温度の分散を示す特徴値を求め
、
これらの特徴値より、鋼板冷却後かつ条切り後の板形状
を推定することを特徴とする鋼板の形状推定方法。
（２）熱間圧延された鋼板（１０）の注水冷却制御工程
の直後に配置され、鋼板表面の板幅方向および板長平方
向の二次元温度分布を測定する温度センサ（１２）と、
該板幅方向温度分布より少なくとも扱中央部と両端縁部
の高、低温度差を示す特徴値（ａ。
ｅ、ｂ、ｆ）を求め、また該鋼板を坂長手方向で複数区
分に分割したその各領域における前記二次元温度分布よ
り鋼板表面温度分散（ＶＡＲＧ）を示す特徴値を計算す
る温度分布パターン判定装置（１６）と、
これらの特徴値より鋼板冷却後かつ条切り後、の板形状
を推定する手段（１８）を有することを特徴とする鋼板
の形状推定装置。」
（２）同第２頁１５行の「厚板」を「鋼板」に補正する
。
（３）同第２頁１７行のｒ （ＣＬＣ）Ｊを削除する。
（４）同第３頁３行、第４頁１行、第５頁６行の［ＣＬ
ＣＪを「冷却制御」に補正する。
（５）同第３頁４行の「（エツジマスク）」を削除する
。
（６）同第３頁１５行〜１８行の「場合で、〜である」
を次の様に補正する。
「場合である。Ｂのケースは水冷による両縁の冷却が少
ない場合である。」
（７）同第４頁２０行のｒＣＬＣ工程」を「冷却制御設
備」に補正する。
（８）同第６頁５行のｒＣＬＣ材」を「鋼板」に補正す
る。
（９）同第６頁１）行の「厚板」を削除する。
α０同第６頁１２行のｒＣＬＣＪをｒＲｓＪに補正する
。
（１）１同第７頁３行、第１０頁７行のｒＣＬＣ材」を
「冷却鋼板」に補正する。
０２図面第１図、第８図を別紙のとおりに補正する。Figure 1 is a detailed explanatory diagram of the present invention, Figures 2 and 3 are block diagrams of the control system in Figure 1, Figure 4 is a diagram of the relationship between temperature difference and camber, and Figure 5 is camber generation. FIG. 6 is an explanatory diagram of the feature quantity, FIG. 7 is an explanatory diagram of the output of the temperature sensor, and FIG. 8 is a diagram of the relationship between temperature profile and shape. In the drawing, 10 is a steel plate, 12 is a temperature sensor, 16 is a temperature distribution pattern determination device, and 10a is a cut steel strip. Applicant Minoru Aoyagi, patent attorney representing Nippon Steel Corporation Degree profile H shape relationship decoy! ￥8 Figure procedural amendment (voluntary) 1. Indication of the case Name of Patent Application No. 31) 770 of 1985 Method and device for estimating the shape of steel plate 3. Person making the amendment Relationship with the case Patent applicant address Tokyo 2-6-3 Otemachi, Chiyoda-ku Name (6
65) Takeshi, Representative of Nippon Steel Corporation 1) Toyozuke 101 Address No. 10, Higashi Building, 3-4-5 Iwamoto-cho, Chiyoda-ku, Tokyo Name (7017) Patent Attorney Aoyagi
Date of Minoru 1st Order: None Number of Inventions Increased by the King: None 7, Supplement 8, Supplement 8, Contents of Amendment (1) The scope of claims in the specification is amended as follows. (1) Immediately after the water injection cooling control process of the hot-rolled steel plate, the two-dimensional temperature distribution of the steel plate surface in the width direction and slope longitudinal direction is measured using a temperature sensor, and from the temperature distribution in the width direction, at least The characteristic values (ate, b, f) indicating the high and low temperature differences between the center and both edges are determined, and the steel plate is divided into a plurality of sections in the horizontal direction of the plate, and the two-dimensional temperature distribution in each area is used to calculate the steel plate. A method for estimating the shape of a steel plate, characterized in that characteristic values indicating the dispersion of surface temperature are obtained, and the shape of the steel plate after cooling and strip cutting is estimated from these characteristic values. (2) Hot-rolled steel plate (10) A temperature sensor (12) that is placed immediately after the water injection cooling control step and measures the two-dimensional temperature distribution of the steel sheet surface in the sheet width direction and the sheet longitudinal direction; The characteristic values (a, e, b, f) indicating the high and low temperature differences between the two edges of the steel plate are obtained, and the steel plate is divided into multiple sections in the longitudinal direction of the slope, and from the two-dimensional temperature distribution in each region. The present invention includes a temperature distribution pattern determination device (16) that calculates feature values indicating surface temperature variance (VARG), and means (18) for estimating the shape of the steel plate after cooling and strip cutting from these feature values. Characteristics of a steel plate shape estimating device.'' (2) Correct "thick plate" on page 2, line 15, to "steel plate." (3) Delete r (CLC)J on page 2, line 17. (4) [CL] on page 3, line 3, page 4, line 1, page 5, line 6
Correct CJ to "cooling control". (5) Delete "(edge mask)" on page 3, line 4. (6) "In the case, it is..." on page 3, lines 15 to 18.
Correct as follows. "Case B is a case where cooling of both edges by water cooling is small." (7) Correct "rCLC process" on page 4, line 20 of the same page to "cooling control equipment." (8) Correct “rCLC material” on page 6, line 5 of the same page to “steel plate”. (9) Delete "Thick plate" in line 1) on page 6 of the same page. α0 Correct rCLCJ on page 6, line 12 to rRsJ. (1) 1, page 7, line 3 and page 10, line 7, "rCLC material" is corrected to "cooled steel plate." 02 drawings Figures 1 and 8 will be corrected as shown in the attached sheet.
Claims (2)
温度センサにより鋼板表面の板幅方向および板長手方向
の二次元温度分布を測定し、 該板幅方向温度分布より、少なくとも板中央部と両端縁
部の高、低温度差を示す特徴値（ａ、ｅ、ｂ、ｆ）を求
め、また該鋼板を板長手方向で複数区分に分割したその
各領域における前記二次元温度分布より鋼板表面温度の
分散を示す特徴値を求め、 これらの特徴値より、鋼板冷却後かつ条切り後の板形状
を推定することを特徴とする鋼板の形状推定方法。(1) Immediately after the water injection cooling control process of a hot-rolled steel plate, the two-dimensional temperature distribution in the width direction and longitudinal direction of the steel plate surface is measured using a temperature sensor, and from the temperature distribution in the width direction, at least the center of the plate is measured. The characteristic values (a, e, b, f) indicating the high and low temperature differences between the part and both end edges are determined, and the steel plate is divided into multiple sections in the longitudinal direction of the plate, and from the two-dimensional temperature distribution in each area. A method for estimating the shape of a steel sheet, the method comprising: obtaining characteristic values indicating dispersion of the surface temperature of the steel sheet, and estimating the shape of the sheet after the steel sheet has been cooled and after strip cutting from these characteristic values.
（ＣＬＣ）の直後に配置され、鋼板表面の板幅方向およ
び板長手方向の二次元温度分布を測定する温度センサ（
１２）と、 該板幅方向温度分布より少なくとも板中央部と両端縁部
の高、低温度差を示す特徴値（ａ、ｅ、ｂ、ｆ）を求め
、また該鋼板を板長手方向で複数区分に分割したその各
領域における前記二次元温度分布より鋼板表面温度分散
（ＶＡＲＧ）を示す特徴値を計算する温度分布パターン
判定装置（１６）と、これらの特徴値より鋼板冷却後か
つ条切り後の板形状を推定する手段（１８）を有するこ
とを特徴とする鋼板の形状推定装置。(2) A temperature sensor that is placed immediately after the water injection cooling control process (CLC) of the hot rolled steel plate (10) and measures the two-dimensional temperature distribution on the steel plate surface in the plate width direction and plate longitudinal direction.
12) From the temperature distribution in the sheet width direction, characteristic values (a, e, b, f) indicating the high and low temperature differences at least between the central part of the sheet and both edge portions are determined, and the steel sheet is divided into multiple parts in the longitudinal direction of the sheet. A temperature distribution pattern determination device (16) that calculates characteristic values indicating the steel plate surface temperature variance (VARG) from the two-dimensional temperature distribution in each region divided into sections, and a temperature distribution pattern determination device (16) that calculates characteristic values indicating the steel sheet surface temperature variance (VARG) from the two-dimensional temperature distribution in each region divided into sections; A steel plate shape estimating device comprising means (18) for estimating the shape of a steel plate.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP61311770A JPS63168209A (en) | 1986-12-27 | 1986-12-27 | Method and apparatus for estimating shape of steel plate |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP61311770A JPS63168209A (en) | 1986-12-27 | 1986-12-27 | Method and apparatus for estimating shape of steel plate |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| JPS63168209A true JPS63168209A (en) | 1988-07-12 |
| JPH0516927B2 JPH0516927B2 (en) | 1993-03-05 |
Family
ID=18021267
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP61311770A Granted JPS63168209A (en) | 1986-12-27 | 1986-12-27 | Method and apparatus for estimating shape of steel plate |
Country Status (1)
| Country | Link |
|---|---|
| JP (1) | JPS63168209A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20020051997A (en) * | 2000-12-23 | 2002-07-02 | 이구택 | Method For Predicting Temperature Profile Into Width Direction In A Plate Rolling |
| WO2019224906A1 (en) * | 2018-05-22 | 2019-11-28 | 東芝三菱電機産業システム株式会社 | Industrial plant image analysis device and industrial plant monitoring control system |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS4846554A (en) * | 1971-10-18 | 1973-07-03 | ||
| JPS5926371A (en) * | 1982-08-04 | 1984-02-10 | Nissan Motor Co Ltd | Structure for mounting kicking plate on car body |
-
1986
- 1986-12-27 JP JP61311770A patent/JPS63168209A/en active Granted
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS4846554A (en) * | 1971-10-18 | 1973-07-03 | ||
| JPS5926371A (en) * | 1982-08-04 | 1984-02-10 | Nissan Motor Co Ltd | Structure for mounting kicking plate on car body |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20020051997A (en) * | 2000-12-23 | 2002-07-02 | 이구택 | Method For Predicting Temperature Profile Into Width Direction In A Plate Rolling |
| WO2019224906A1 (en) * | 2018-05-22 | 2019-11-28 | 東芝三菱電機産業システム株式会社 | Industrial plant image analysis device and industrial plant monitoring control system |
| JPWO2019224906A1 (en) * | 2018-05-22 | 2020-12-10 | 東芝三菱電機産業システム株式会社 | Industrial plant monitoring and control system |
Also Published As
| Publication number | Publication date |
|---|---|
| JPH0516927B2 (en) | 1993-03-05 |
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