JPS6236543A - Purity measurement for steel plate surface - Google Patents

Purity measurement for steel plate surface

Info

Publication number
JPS6236543A
JPS6236543A JP17724485A JP17724485A JPS6236543A JP S6236543 A JPS6236543 A JP S6236543A JP 17724485 A JP17724485 A JP 17724485A JP 17724485 A JP17724485 A JP 17724485A JP S6236543 A JPS6236543 A JP S6236543A
Authority
JP
Japan
Prior art keywords
steel plate
color difference
values
cleanliness
white
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.)
Pending
Application number
JP17724485A
Other languages
Japanese (ja)
Inventor
Akira Torao
彰 虎尾
Noboru Tsuruta
弦田 登
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
JFE Steel Corp
Original Assignee
Kawasaki Steel Corp
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Kawasaki Steel Corp filed Critical Kawasaki Steel Corp
Priority to JP17724485A priority Critical patent/JPS6236543A/en
Publication of JPS6236543A publication Critical patent/JPS6236543A/en
Pending legal-status Critical Current

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  • Investigating Or Analysing Materials By Optical Means (AREA)

Abstract

PURPOSE:To enable the discrimination of discoloring from underpickling while determining the overlap thereof continuously in the detection, by detecting the surface purity of a steel plate using values of white or color difference and yellow. CONSTITUTION:A running steel plate 10 is irradiated with a white light source 14 and the reflected light thereof is spectroscopically analyzed with a diffraction grating 20 and detected simultaneously with a parallel type photodetection element train 22 in the visible wavelength range. Values of white W or color difference DELTAEh and yellow (b) are calculated with an arithmetic processor 24 from three stimulant values X, Y and Z from the detection signals thus obtained; the resulting values are converted into information of surface purity indicating discoloring, under pickling and the like. The white W is determined by the formula I, the color difference DELTAEh by the formula II and the yellow (b) by the formula III, wherein the subscript (s) represents the value of the reference steel plate.

Description

【発明の詳細な説明】[Detailed description of the invention] 【産業上の利用分野】[Industrial application field]

本発明は、鋼板表面の色彩異常状況を検出するための鋼
板表面の清浄度測定方法に係り、特に、鉄rI4業の酸
洗工程において走行する鋼板の酸洗状況を連続的に検出
し、その結果を基に操業の安定化や品質の保証を行う際
に用いるのに好適な、鋼板表面の清浄度測定方法に関す
る。
The present invention relates to a method for measuring the cleanliness of a steel plate surface for detecting color abnormalities on the surface of a steel plate, and in particular, it continuously detects the pickling status of a running steel plate in the pickling process of the iron rI4 industry. This invention relates to a method for measuring the cleanliness of a steel plate surface, which is suitable for use in stabilizing operations and guaranteeing quality based on the results.

【従来の技術】[Conventional technology]

一般に、熱間圧延工程により圧延されて製造される熱間
圧延鋼板の表面には、黒皮と呼ばれる鉄の酸化物が付着
しているため、冷間圧延等に際しては、まず酸洗工程を
通すことにより、それらを除去する必要がある。この酸
洗工程における黒皮の剥離は、物理的、化学的作用を利
用して行われ、均一な清8度の鋼板表面を得るようにし
ているが、F1々の原因により鋼板の表面状況が異なる
場合が生じることがある。 その原因としては、例えば、酸洗速度の増減がある。即
ち、酸洗速度が速過ぎるために、黒皮の除去が完全では
なく、アンダービックリングと呼ばれる黒皮残りが生じ
る場合や、ライン停止や酸洗速度が遅過ぎるために、変
色と呼ばれる赤錆が生じる場合がある。 前者は酸洗以後の工程で鋼板の品質に悪い影響を及ぼし
、又、後者は酸洗工程後に直接製品とされる場合には、
表面品質上不良とされ、製品になり得ない。 このように、アンダービックリング、赤錆共に品質上問
題になるため、従来は、酸洗鋼板表面の変色やアンダー
ビックリング等の異常を表わすに際して、良好、変色小
、変色大、アンダービック小等のように感覚的な判別基
準を用いて、作業員の目視により酸洗状況を管理してい
た。しかしながら、これでは個人差や周囲の明暗等環境
条件にも左右されるので、正確な把握は困難である。 一方、ライン速度の高速化、品質管理の厳しさが増すの
に従って、自動検査の要求は強くなりつつある。 そのため、従来から、冷間圧延鋼板の表面疵検査に広く
使用されている表面疵検査装置を酸洗工程に導入し、表
面清浄の測定に応用しようとする試みがなされている。 このような目的で、表面疵のような突発的に発生するも
のを検出する方式を用いることも考えられるが、この方
式は、アンダービックリングや変色等の欠陥が徐々に進
行することや、広い面積に亘ること等から、表面清浄度
をうまく測定することができない。 又、別の方法として、テレビカメラで鋼板表面を1li
l像し、モニタ上に画像処理することも考えられるが、
鋼板の表面性状を定量化して測定することが難しい。 一方、このような試みの一つとして、発明者は、変色や
アンダービックリングの度合を定量化するために、測色
パラメータの導入を検討した。これは表面性状の良好な
酸洗鋼板が銀白色なのに対して変色が進むにつれて赤茶
色の度合が進み、又、アンダービックリングが進むにつ
れて黒褐色の度合が進むことが分かり、変色やアンダー
ビックリングと邑とは密接な関係があると推定されたか
らである。従って、適当な色彩パラメータを選択すれば
変色とアンダービックリングを判別可能で、しかもそれ
らの重度を定量化可能であると予想された。 しかしながら、色彩パラメータには各種あるため、どの
パラメータが変色やアンダービックリングとよく対応す
るかを調べる必要がある。そこで発明者は変色の度合と
各種色彩パラメータの関係を調べた結果、白色1tW(
BG)がよく対応することが分り、変色の度合を白色r
!IW(BG)から推定可能であることを見出して、特
願昭59−257091で既に提案している。 この方法を実際の酸洗ラインに適用して採取したデータ
を第6図に示す。これより変色の度合が白色度W (B
G)の値から推定可能であることが分る。一方、アンダ
ービックリングのサンプルを同様に測定すると、その重
度と白色度W(BG)の値とが、第7図に示す如く、変
色の場合と同様によく対応することが分った。 これらの結果より、白色度W (BG)の値は、変色や
アンダービックリングの重度を定量的に評価する場合に
有効であることが分る。
In general, iron oxides called black scale are attached to the surface of hot-rolled steel sheets that are manufactured by rolling in the hot-rolling process. Therefore, it is necessary to remove them. The peeling of black scale in this pickling process is carried out using physical and chemical effects to obtain a uniform steel plate surface of 8 degrees of cleanliness, but the surface condition of the steel plate is Different cases may arise. The reason for this is, for example, an increase or decrease in the pickling speed. In other words, if the pickling speed is too fast, the black scales may not be removed completely and a black scale remains called under bicking, or if the line is stopped or the pickling speed is too slow, red rust called discoloration may occur. may occur. The former has a negative effect on the quality of the steel sheet in the process after pickling, and the latter has a negative effect on the quality of the steel sheet in the process after pickling, and the latter has a negative effect on the quality of the steel plate when it is made into a product directly after the pickling process.
It is considered defective due to its surface quality and cannot be used as a product. In this way, both under-bickling and red rust pose quality problems, so conventionally, when indicating abnormalities such as discoloration or under-bickling on the surface of a pickled steel sheet, it has been classified as good, small discoloration, large discoloration, small under-bickling, etc. The pickling situation was managed visually by workers using intuitive criteria. However, this is difficult to accurately grasp because it depends on individual differences and environmental conditions such as surrounding brightness and darkness. On the other hand, as line speeds increase and quality control becomes more stringent, the demand for automatic inspection is becoming stronger. Therefore, attempts have been made to introduce a surface flaw inspection device, which has been widely used for surface flaw inspection of cold-rolled steel plates, into the pickling process and apply it to the measurement of surface cleanliness. For this purpose, it is conceivable to use a method that detects sudden occurrences such as surface flaws, but this method is difficult to detect because defects such as under-bickling and discoloration progress gradually, and Because the surface area is covered, surface cleanliness cannot be measured well. Another method is to measure the surface of the steel plate with a television camera.
It is also possible to image the image and process it on a monitor, but
It is difficult to quantify and measure the surface properties of steel sheets. On the other hand, as one such attempt, the inventor considered introducing a colorimetric parameter in order to quantify the degree of discoloration and underbickling. This is because pickled steel sheets with good surface properties are silvery white, but as the discoloration progresses, the degree of reddish-brown increases, and as under-bickling progresses, the degree of black-brown increases. This is because it was assumed that there was a close relationship with the village. Therefore, it was expected that by selecting appropriate color parameters, it would be possible to distinguish between discoloration and underbickling, and also to quantify their severity. However, since there are various color parameters, it is necessary to investigate which parameters correspond well to discoloration and under-bicking. Therefore, the inventor investigated the relationship between the degree of discoloration and various color parameters, and found that white 1tW (
BG) was found to correspond well, and the degree of discoloration was determined by white r
! It was discovered that it could be estimated from IW(BG), and it was already proposed in Japanese Patent Application No. 59-257091. Figure 6 shows data collected by applying this method to an actual pickling line. From this, the degree of discoloration is the whiteness W (B
It can be seen that it can be estimated from the value of G). On the other hand, when samples with under-bickling were similarly measured, it was found that the severity of the under-bickling and the value of whiteness W (BG) corresponded well, as in the case of discoloration, as shown in FIG. These results show that the whiteness W (BG) value is effective in quantitatively evaluating the severity of discoloration and under-bickling.

【発明が解決しようとする問題点】[Problems to be solved by the invention]

しかしながら、白色度W (BG)の値だけでは、第6
図及び第7図から明らかな如く、変色とアンダービック
リングとを判別することができないという問題点を有し
ていた。これは、色差ΔEのみを用いた場合も、良好な
銅板と変色やアンダービックリングのある鋼板の区別は
可能であるが、変色とアンダービックリングを判別でき
ないという問題がある点で同様である。
However, only the value of whiteness W (BG)
As is clear from the figures and FIG. 7, there was a problem in that it was not possible to distinguish between discoloration and under-bickling. This is similar in that even when only the color difference ΔE is used, it is possible to distinguish between a good copper plate and a steel plate with discoloration or under-bickling, but there is a problem in that discoloration and under-bickling cannot be distinguished.

【発明の目的】[Purpose of the invention]

本発明は、前記従来の問題点を解消するべくなされたも
ので、作業員が介入することなく、変色とアンダービッ
クリングの選別を行い、しかもその重度を連続的に定m
化して検出することができる鋼板表面の清浄度測定方法
を提供することを目的とする。
The present invention has been made to solve the above-mentioned conventional problems, and it is possible to sort out discoloration and under-bickling without operator intervention, and to continuously determine the severity of the discoloration and under-bickling.
The purpose of the present invention is to provide a method for measuring the cleanliness of a steel plate surface, which can detect the cleanliness of a steel plate surface.

【問題点を解決するための手段】[Means to solve the problem]

本発明は、鋼板表面の色彩異常状況を検出するための鋼
板表面の清浄度測定方法において、第1図にその要旨を
示す如く、鋼板表面に白色光を照射し、その反射光を分
光解析して三刺激値X、Y、Zの値を求め、該三刺!1
t(iffX、Y、Zの値から所定の変換式によって白
色度W又は色差ΔEと、黄色r!IYeの値とを求め、
該白色度W又は色差ΔEと、黄色度Yeの値とによって
鋼板の表面清浄度を検出するようにして、前記目的を達
成したものである。 又、本発明の実施態様は、前記白色r!1.Wを、三刺
激@X、Y、Zの値から、次の変換式1式%(1) により求められる白色mW(BG)としたものである。 又、本発明の他の実施態様は、前記色差ΔEを、三刺激
値X、Y、Zの値から、次の変換式1式%) (ここで、Lslas、bSは、それぞれ基準となる鋼
板のl、a、b値)により求められる色差ΔEhとした
ものである。 又、本発明の実施態様は、前記黄色度’(eを、三刺激
値X1Y1Zの値から次の変換式1式% により求められる黄色度すとしたものである。
The present invention is a method for measuring the cleanliness of a steel plate surface to detect color abnormalities on the steel plate surface, as shown in FIG. Find the tristimulus values X, Y, and Z, and find the three stimuli! 1
Determine the whiteness W or color difference ΔE and the value of yellow r!IYe from the values of t(if
The above object is achieved by detecting the surface cleanliness of the steel plate based on the whiteness W or color difference ΔE and the value of the yellowness Ye. Further, an embodiment of the present invention provides the white r! 1. W is the white mW (BG) obtained from the values of the three stimuli @X, Y, and Z using the following conversion formula 1 (%(1)). Further, in another embodiment of the present invention, the color difference ΔE is converted from the tristimulus values X, Y, and Z using the following conversion formula 1 (%) (where Lslas and bS are respectively the reference steel plate The color difference ΔEh is determined by the l, a, b values). Further, in an embodiment of the present invention, the yellowness degree '(e) is the yellowness degree obtained from the tristimulus value X1Y1Z by the following conversion formula 1.

【作用】[Effect]

本発明は、鋼板表面の色彩異常状況を検出するに際して
、白色度W又は色差ΔEだけでなく、黄色度Yeの値を
求め、前記白色度W又は色差ΔEと黄色度Yeの値によ
って、鋼板の表面清浄度を検出するようにしている。従
って、作業員が介入することなく、変色とアンダービッ
クリングの選別を行ない、しかも、その重度を連続的に
室間化して検出することができる。 即ち、発明者が種々の色彩パラメータの値を変色やアン
ダーピックリング試料について実験測定した結果、測色
計ではよく用いられる黄色Ib値を導入すれば、両者を
完全に判別可能であることを見出した。−例として試料
鋼板をオフラインで測定した場合の、白色度W (BG
)値と黄色度す値の測定結果を第2図に、同じく、色差
ΔE値と黄色度す値の測定結果を第3図に示す。図から
明らかなように、変色やアンダービックリングの度合が
進むにつれて色差ΔEが大きくなるため、酸洗良好な鋼
板と区別が可能である。一方、黄色度す値については、
変色鋼板が変色度合が進むにつれて増加するのに対して
、アンダービックリング鋼板においては、変化が小さい
かむしろ減少の傾向にある。 従って、色差ΔEと黄色度Ye  (例えばb値)を同
時に測定することにより、酸洗良好な鋼板との区別や不
良重度の判定ができ、表面清浄度のオンライン測定が可
能となって、安定した製品品質を達成することができる
When detecting color abnormality on the surface of a steel plate, the present invention calculates not only the whiteness W or color difference ΔE but also the yellowness Ye, and uses the whiteness W or color difference ΔE and the yellowness Ye to determine the value of the steel plate. The surface cleanliness is detected. Therefore, discoloration and under-bickling can be sorted out without operator intervention, and the severity of the discoloration and under-bickling can be detected continuously. That is, as a result of experimentally measuring the values of various color parameters on discolored and underpickling samples, the inventor found that by introducing the yellow Ib value, which is often used in colorimeter, it is possible to completely distinguish between the two. Ta. - As an example, the whiteness W (BG
) and the yellowness value are shown in FIG. 2, and similarly, the measurement results of the color difference ΔE value and the yellowness value are shown in FIG. As is clear from the figure, the color difference ΔE increases as the degree of discoloration and under-bicking progresses, so that it can be distinguished from a steel plate that has been well pickled. On the other hand, regarding the yellowness value,
While the degree of discoloration of a discolored steel plate increases as the degree of discoloration progresses, in an under-bicking steel plate, the change is small or rather tends to decrease. Therefore, by simultaneously measuring the color difference ΔE and the yellowness Ye (e.g. b value), it is possible to distinguish steel sheets from well-pickled steel sheets and determine the severity of defects, making online measurement of surface cleanliness possible, and ensuring stable Product quality can be achieved.

【実施・例】【Example】

以下図面を参照して、本発明が採用された、走行する酸
洗鋼板の表面清浄度測定装置の実施例を詳細に説明する
。 本発明の第1実施例では、第4図に示す如く、走行鋼板
10の表面反射特性を分光解析して三刺激値x、y、z
を得るために、白色光を照射する2つの白色光源14と
、測定視野を規定するスリット16と、測定対象である
鋼板10からの反射光をスリット16上に結像したり、
スリット通過後の反射光を平行にするレンズ系18と、
平行光にされた反射光を分光する反射型回折格子20′
8の分光素子と、可視波長領域での分光光を同時検出す
るための並列型光検出素子列22と、該光検出素子列2
2から得られる信号の増幅、変換、演算や、演算結果の
出力等を行うアナログ・デジタル演算処理装置24とを
有する高分解能の分光測色装置12を用いている。 即ち、この第1実施例においては、走行鋼板10を2つ
の白色光+1Pi14で照射して、その反射光をレンズ
18やスリット16を通した後に反射型回折格子20で
分光し、その分光光を並列型光検出素子列22において
可視波長領域で同時検出する。検出された信号は、アナ
ログ・デジタル演算処理装置24で、三刺激値X、Y、
Zの値をもとにして、白色度W又は色差ΔEと、黄色度
すの値とがn出され、それらの値が、変色やアンダービ
ックリング等の表面清浄度の情報に変換される。 前記アナログ・デジタル演算装置24には、CR7表示
画面やプリンタ等も内蔵されているので、データの保存
や出力も可能である。 従って作業員は、清浄度の出力結果を元に変色やアンダ
ーピックリングの発生状況を知り、それらの発生を極力
防止することにより、操業の安定化、品質の管理を図る
ことができる。又、作業員が介在せずに、清浄度の測定
結果を直接用いて、酸洗鋼板製造ラインの′ylA度を
制御することも可能である。 次に本発明の第2実施例を詳細に説明する。 この第2実施例においては、三刺激値X、Y。 Zを厳密な分光を行うことなく得られるものとして、第
5図に示す如く、第6図に示すような三刺激値分布曲線
の刺激値分布曲線x、y、zに各々対応した3個の干渉
フィルタ30A、30B、30Cを装着した回転セクタ
32を高速回転させて、フィルタ透過後の光量を単一の
光検出素子34で検出する三刺激値直読型の測色計28
を用いている。他の点については前記第1実施例と同様
であるので説明は省略する。 なお前記実施例においては、いずれも本発明が走行する
酸洗鋼板の清浄度測定に適用されていたが、本発明の適
用範囲はこれに限定されず、停止している一般の鋼板の
清浄度測定にも同様に適用できることは明らかである。
DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of a surface cleanliness measuring device for a traveling pickled steel plate to which the present invention is applied will be described in detail below with reference to the drawings. In the first embodiment of the present invention, as shown in FIG. 4, the surface reflection characteristics of the running steel plate 10 are spectroscopically analyzed to determine the tristimulus values
In order to obtain this, two white light sources 14 that emit white light, a slit 16 that defines the measurement field of view, and the reflected light from the steel plate 10 to be measured are imaged on the slit 16,
a lens system 18 that parallelizes the reflected light after passing through the slit;
Reflection type diffraction grating 20' that separates the reflected light that has been made into parallel light.
8 spectroscopic elements, a parallel photodetection element array 22 for simultaneously detecting spectral light in the visible wavelength region, and the photodetection element array 2
A high-resolution spectrophotometric device 12 is used, which includes an analog/digital processing device 24 that amplifies, converts, and calculates signals obtained from 2 and outputs the results of calculations. That is, in this first embodiment, the traveling steel plate 10 is irradiated with two white lights + 1 Pi 14, the reflected light is passed through the lens 18 and the slit 16, and then separated into spectra by the reflection type diffraction grating 20. Simultaneous detection is performed in the visible wavelength region in the parallel photodetecting element array 22. The detected signal is converted into tristimulus values X, Y,
Based on the value of Z, the whiteness W or color difference ΔE and the yellowness value are calculated, and these values are converted into information on surface cleanliness such as discoloration and under-bickling. The analog/digital arithmetic unit 24 also has a built-in CR7 display screen, printer, etc., so it is also possible to save and output data. Therefore, workers can learn about the occurrence of discoloration and underpickling based on the cleanliness output results, and by preventing these occurrences as much as possible, they can stabilize operations and control quality. It is also possible to control the 'ylA degree of the pickled steel plate manufacturing line directly using the cleanliness measurement results without operator intervention. Next, a second embodiment of the present invention will be described in detail. In this second embodiment, the tristimulus values X, Y. Assuming that Z can be obtained without conducting strict spectroscopy, as shown in Fig. 5, three points corresponding to the stimulus value distribution curves x, y, and z of the tristimulus value distribution curve as shown in Fig. 6 are calculated. A tristimulus value direct reading type colorimeter 28 that rotates a rotating sector 32 equipped with interference filters 30A, 30B, and 30C at high speed and detects the amount of light after passing through the filter with a single light detection element 34.
is used. The other points are the same as those of the first embodiment, so the explanation will be omitted. In each of the above embodiments, the present invention was applied to measuring the cleanliness of a running pickled steel plate, but the scope of application of the present invention is not limited to this, and the cleanliness of a general steel plate that is not running is applied. It is clear that the same applies to measurements as well.

【発明の効果】【Effect of the invention】

以上説明した通り、本発明によれば、変色とアンダーピ
ックリングの選別を行って、鋼板表面の清浄度を、作業
員が介入することなく、連続的に定量化して検出するこ
とが可能となる。従って、例えば連続酸洗工程において
安定した自動清浄度管理が行え、不良品の早期発見、操
業の安定化、ユーザに対する品質保証等が可能となる。 更に、目視検査をなくすことができるので、作業負荷を
減らすことができ、自動速度制御への発展も可能である
。又、表面疵検査装置と組合せることにより、表面品質
管理体制を築くこともできる等の優れた効果を有する。
As explained above, according to the present invention, it is possible to screen for discoloration and underpickling, and continuously quantify and detect the cleanliness of the steel plate surface without operator intervention. . Therefore, stable automatic cleanliness control can be performed, for example, in a continuous pickling process, making it possible to detect defective products early, stabilize operations, and guarantee quality to users. Furthermore, since visual inspection can be eliminated, the workload can be reduced and development to automatic speed control is also possible. In addition, by combining it with a surface flaw inspection device, it has excellent effects such as being able to establish a surface quality control system.

【図面の簡単な説明】[Brief explanation of the drawing]

第1図は、本発明に係る鋼板表面の清浄度測定方法の要
旨を示す流れ図、第2図は、本発明の詳細な説明するた
めの、変色及びアンダービックリング鋼板の白色度W<
BG)値及び黄色度す値の例を示す線図、第3図は、同
じく、色差ΔE値及び黄色度す値の例を示す線図、第4
図は、本発明が採用された、走行する酸洗綱板の表面清
浄度測定装置の第1実施例の構成を示す、一部ブロック
線図を含む断面図、第5図は、同じく第2実施例の構成
を示す断面図、第6図は、前記第2実施例で用いられて
いる干渉フィルタの特性を説明するための、三刺激値分
布曲線を示す縮図、第7図は、発明者が提案したPA連
技術で利用されている、目視変色度と白色度W (8G
)の対応関係の例を示す絵図、第8図は、目視アンダー
ビックリング重度と白色度W (BG)の対応関係の例
を示す線図である。 10・・・走行鋼板、 12・・・分光測色装置、 14・・・白色光源、 20・・・反射型回折格子、 22・・・並列型光検出素子列、 24・・・アナログ・デジタル演算処理装置、28・・
・測色計、 30A、30B130G・・・干渉フィルタ、32・・
・回転セック、 34・・・光検出素子。
FIG. 1 is a flowchart showing the gist of the method for measuring the cleanliness of a steel sheet surface according to the present invention, and FIG. 2 is a flow chart showing the details of the present invention, showing the whiteness W< of discoloration and under-bickling steel sheets.
Figure 3 is a diagram showing examples of color difference ΔE values and yellowness values, and Figure 4 is a diagram showing examples of color difference ΔE values and yellowness values.
The figure is a sectional view including a partial block diagram showing the configuration of a first embodiment of a surface cleanliness measuring device for a running pickled steel plate to which the present invention is adopted; FIG. 6 is a cross-sectional view showing the configuration of the embodiment; FIG. 6 is a miniature diagram showing a tristimulus value distribution curve for explaining the characteristics of the interference filter used in the second embodiment; FIG. Visual discoloration and whiteness W (8G
) is a diagram showing an example of the correspondence between the degree of visual under-bickling and the degree of whiteness W (BG). DESCRIPTION OF SYMBOLS 10... Traveling steel plate, 12... Spectrophotometer, 14... White light source, 20... Reflection type diffraction grating, 22... Parallel type photodetection element row, 24... Analog/digital Arithmetic processing unit, 28...
・Colorimeter, 30A, 30B130G...Interference filter, 32...
・Rotating SEC, 34...Photodetection element.

Claims (4)

【特許請求の範囲】[Claims] (1)鋼板表面の色彩異常状況を検出するための鋼板表
面の清浄度測定方法において、 鋼板表面に白色光を照射し、 その反射光を分光解析して三刺激値X、Y、Zの値を求
め、 該三刺激値X、Y、Zの値から所定の変換式によって白
色度W又は色差ΔEと、黄色度Yeの値とを求め、 該白色度W又は色差ΔEと、黄色度Yeの値とによって
鋼板の表面清浄度を検出することを特徴とする鋼板表面
の清浄度測定方法。
(1) In the method of measuring the cleanliness of a steel plate surface to detect color abnormalities on the steel plate surface, the steel plate surface is irradiated with white light, and the reflected light is spectrally analyzed to determine the tristimulus values X, Y, and Z. From the tristimulus values X, Y, and Z, use a predetermined conversion formula to determine the whiteness W or color difference ΔE and the yellowness Ye, and calculate the whiteness W or color difference ΔE and the yellowness Ye. A method for measuring the cleanliness of a surface of a steel plate, characterized by detecting the surface cleanliness of the steel plate based on the value.
(2)前記白色度Wを、三刺激値X、Y、Zの値から、
次の変換式 W(BG)=3.388×Z−3×Y により求められる白色度W(BG)とした特許請求の範
囲第1項記載の鋼板表面の清浄度測定方法。
(2) The whiteness W is determined from the tristimulus values X, Y, and Z,
The method for measuring the cleanliness of a steel plate surface according to claim 1, wherein the whiteness W (BG) is determined by the following conversion formula W (BG) = 3.388 x Z - 3 x Y.
(3)前記色差ΔEを、三刺激値X、Y、Zの値から、
次の変換式 L=10√Y a=17.5×(1.02×X−Y)/√Yb=7×(
Y−0.847×Z)/√Y ΔEh=√[(L−L_s)^2+(a−a_s)^2
+(b−b_s)^2] (ここで、L_s、a_s、b_sは、それぞれ基準と
なる鋼板のL、a、b値)により求められる色差ΔEh
とした特許請求の範囲第1項記載の鋼板表面の清浄度測
定方法。
(3) The color difference ΔE is calculated from the tristimulus values X, Y, and Z,
The following conversion formula L=10√Y a=17.5×(1.02×X-Y)/√Yb=7×(
Y-0.847×Z)/√Y ΔEh=√[(LL_s)^2+(a-a_s)^2
+(b-b_s)^2] (Here, L_s, a_s, and b_s are the L, a, and b values of the reference steel plate, respectively) Color difference ΔEh
A method for measuring the cleanliness of a steel plate surface according to claim 1.
(4)前記黄色度Yeを、三刺激値X、Y、Zの値から
、次の変換式 b=7×(Y−0.847×Z)/√Y により求められる黄色度bとした特許請求の範囲第1項
記載の綱板表面の清浄度測定方法。
(4) A patent in which the yellowness Ye is determined from the tristimulus values X, Y, and Z by the following conversion formula b=7×(Y-0.847×Z)/√Y A method for measuring the cleanliness of a steel plate surface according to claim 1.
JP17724485A 1985-08-12 1985-08-12 Purity measurement for steel plate surface Pending JPS6236543A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
JP17724485A JPS6236543A (en) 1985-08-12 1985-08-12 Purity measurement for steel plate surface

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
JP17724485A JPS6236543A (en) 1985-08-12 1985-08-12 Purity measurement for steel plate surface

Publications (1)

Publication Number Publication Date
JPS6236543A true JPS6236543A (en) 1987-02-17

Family

ID=16027672

Family Applications (1)

Application Number Title Priority Date Filing Date
JP17724485A Pending JPS6236543A (en) 1985-08-12 1985-08-12 Purity measurement for steel plate surface

Country Status (1)

Country Link
JP (1) JPS6236543A (en)

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR100765654B1 (en) 2006-05-15 2007-10-10 현대자동차주식회사 Analytical method of discolorized edge surface on baf annealed cold rolled coil
CN105486808A (en) * 2015-08-25 2016-04-13 武汉钢铁(集团)公司 Portable strip steel surface cleaning on-line detection device and use method thereof
JP2018049009A (en) * 2016-09-19 2018-03-29 レッド・ブル・ゲゼルシャフト・ミット・ベシュレンクテル・ハフツングRed Bull Gmbh Method and device for processing and monitoring object
JP2019190957A (en) * 2018-04-24 2019-10-31 トヨタ自動車株式会社 Inspection method of nickel film irradiated with laser
JP2020148471A (en) * 2019-03-11 2020-09-17 株式会社神戸製鋼所 Surface state determination method and surface state determination device

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPS5081582A (en) * 1973-11-21 1975-07-02
JPS57125833A (en) * 1981-01-30 1982-08-05 Nippon Kokan Kk <Nkk> Measuring method for degree of rust removal
JPS5930028A (en) * 1982-08-12 1984-02-17 Sumitomo Chem Co Ltd Method for measuring color difference of dye

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPS5081582A (en) * 1973-11-21 1975-07-02
JPS57125833A (en) * 1981-01-30 1982-08-05 Nippon Kokan Kk <Nkk> Measuring method for degree of rust removal
JPS5930028A (en) * 1982-08-12 1984-02-17 Sumitomo Chem Co Ltd Method for measuring color difference of dye

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR100765654B1 (en) 2006-05-15 2007-10-10 현대자동차주식회사 Analytical method of discolorized edge surface on baf annealed cold rolled coil
CN105486808A (en) * 2015-08-25 2016-04-13 武汉钢铁(集团)公司 Portable strip steel surface cleaning on-line detection device and use method thereof
JP2018049009A (en) * 2016-09-19 2018-03-29 レッド・ブル・ゲゼルシャフト・ミット・ベシュレンクテル・ハフツングRed Bull Gmbh Method and device for processing and monitoring object
JP2019190957A (en) * 2018-04-24 2019-10-31 トヨタ自動車株式会社 Inspection method of nickel film irradiated with laser
JP2020148471A (en) * 2019-03-11 2020-09-17 株式会社神戸製鋼所 Surface state determination method and surface state determination device

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