JP2642500B2 - Apparatus for detecting the shape of strip-shaped or plate-shaped metal material - Google Patents

Description

Description: BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a shape detecting device for detecting a shape of a running strip-shaped or plate-shaped metal material in a width direction.

(Prior art)

In general, the shape of a band-shaped or plate-shaped metal material has a difference in a stretched / stretched state described later in the width direction of the material. The stretched portion of the metal material causes wrinkles when wound around a roll, for example, and the stretched portion causes breakage because a large tension is applied.
Further, if the shape related to the elongation / tension of the metal material is asymmetrical in the width direction, the way of applying the tension becomes unbalanced in the width direction, which also causes the metal material to meander. As described above, in the process of handling a band-shaped or plate-shaped metal material, it is very important to measure and grasp the shape state in the width direction in operating the process.

As a shape detection device that detects the shape state in the width direction as described above, at a plurality of points in the width direction of the metal material, an I-UNIT value indicating an elongation percentage is measured, and the process is performed based on the I-UHIT value. Or a graph showing the distribution of the elongation percentage in the width direction is displayed on a screen, for example, to assist an operator who operates the process.

FIG. 19 shows a roll mill 2 for rolling aluminum foil, which is an example of the background of the present invention. In aluminum foil rolling, about 700 to 1700 mm in width and several μm to several hundred μ in thickness wound on the entrance coil 50
m of the raw aluminum foil 51 is rolled by a pair of rolling rolls 52 at a speed of about 300 to 1200 m / min, and the thickness thereof is about 1/2 to 1
Reduced to / 3. The rolled aluminum foil 53 is conveyed in the direction of arrow K by a constant tension generated by the rotation of the drive shaft of the output side coil 64 (FIG. 1).
Wound on 64.

For example, when a raw aluminum foil 51 having a thickness of several hundred μm is finally rolled into an aluminum foil 53 having a thickness of several μm, the rolling process is repeated several times, and the number of rolling is referred to as the number of passes. Can be

In the metal rolling in micron units as described above, as shown in FIG. 20, although the aluminum foil 53 has the same thickness, a portion that “extends” in the foil width direction (arrow L). And "stretched" parts are remarkably present. That is, the extension portion 54 has a peak portion 56 and a valley portion 57 formed along the transport direction of the aluminum foil 53 (arrow K), and the tension portion 55 has a generally flat shape. Therefore, the aluminum foil shown in the figure
Reference numeral 53 denotes a state in which the central portion in the foil width direction (arrow L) is extended and its end is stretched.

The concepts of elongation and tension will be strictly described. It is assumed that the metal foil (or metal plate) shown in FIG. 23 (a) is cut into strips in the transport direction. Let K be the shortest length of the strip in the transport direction. In FIG. 23 (b), it is the length K of the central part.

Assuming that the length of the strip at a position in a certain width direction is K + ΔK, the elongation at that position is defined by (ΔK / K) × 10 ⁵ . The “elongation percentage” on the vertical axis of the graphs in FIGS. 3 and 6 indicates this. The position where the rate of growth is large is called “stretched”, and the position where the rate of growth is small is “stretched”.
That. This is the concept of elongation and tension. Such elongation and tension data is detected by an inspection roll 4 described later. The inspection roll 4 is composed of a number of elements arranged in the width direction of the metal foil (plate) so that the length of the strip can be measured.

The distribution of the degree of elongation and the degree of tension in the foil width direction (arrow L) is hereinafter referred to as the surface shape or actual shape of the aluminum foil 53. The surface shape has a great influence on the quality of the foil product, and in some cases, a large tension is applied to the tension portion 55, which causes the foil to break. Also, the portion 54 causes wrinkles. And, as for the aluminum foil 53 as the final product, it is natural that a flat shape in which the elongation and tension occur uniformly is desired, but it is not necessarily a flat actual shape for each pass, but an intermediate shape. The shape of the aluminum foil 53 in the path is various.

The surface shape of the aluminum foil 53 as described above is
Can be controlled by changing the shape of As shown in FIGS. 19 to 21, the rolling roll 52 bulges called a thermal crown due to heat generation during rolling and its heat conduction characteristics. The example shown in FIG.
Is bulging. Such a bulge, that is, a thermal crown, depends on the appearance location and the degree of bulge.
Change the surface shape of 53. That is, the aluminum foil rolled at a portion where the degree of expansion of the thermal crown of the rolling roll 52 is large.
In the case of 53, the rolling portion is in an elongated state. Therefore, the surface shape of the aluminum foil 53 depends on the temperature or the spray amount of the coolant 58 (FIG. 1) sprayed toward the rolling roll 52 to cool the rolling roll 52 in the width direction of the aluminum foil 53 (arrow L ( No.
20) can be controlled.

Such shape control of the aluminum foil 53 is performed by the roll mill 2.
This is performed by the shape control unit 3 provided next to. That is, the shape control unit 3 is rotatably provided on the exit side of the rolling roll 52, and is configured to rotate the aluminum foil 53 from the inspection roll 4 including 36 elements 4e divided in the foil width direction (arrow L). The actual shape data of elongation and tension is input. Each element 4e has
Each of the piezoelectric elements (not shown) is embedded and functions as a sensor for detecting a pressing force applied to the outer peripheral surface of the element 4e.

Then, the aluminum foil 53 pressed against the element 4e and pulled in the transport direction (arrow K) by a constant tension is
When the extension portion 54 passes over the element 4e, the pressure contact force against the element 4e is small, and when the extension portion 55 passes, it is detected large.

Therefore, as shown in FIG. 21, the actual shape of the aluminum foil 53 is expressed as a distribution (actual shape data) of the elongation rate in the width direction obtained by converting the pressing force data detected from each element 4e. In the case shown in the figure, the quota portion a of the rolling roll 52 is excessively bulged, so that cooling of that portion is promoted,
A target shape is set so that heat is stored in the central portion of 52 and both ends thereof.

The shape control unit 3 performs a comparison operation between the actual shape data and target shape data input in advance, and the actual shape data is injected toward a portion of a rolling roll corresponding to the element 4e having a higher elongation. Increase the amount of coolant 58. The coolant 58 is provided on the entry side of the rolling roll 52, and is sprayed from a spray pipe 59 which is split in the foil width direction (arrow L) and sprayed.

Thereby, the thermal crown of the rolling roll 52 is relieved,
The part of the aluminum foil 53 corresponding to the quarter part a is deformed toward the tension state. If the actual shape data has a lower elongation, the reverse operation is performed. In the target shape data, the elongation percentage obtained from the element 4e corresponding to the quarter portion a is often set to 0 so as to promote cooling of the quarter portion a of the rolling roll 52.

As described above, in foil rolling, rolling (passing) is repeated a plurality of times to obtain a final product. The plan of what pass and what thickness or surface shape to obtain the final product in what pass is called an operation policy. In this operation policy, in order to finish the above-mentioned final product into a flat shape with uniform stretch and tension, a target shape of stretch and tension in a middle pass is set together with a target of thickness.

In an actual operation, the distribution of elongation and tension in the above-described intermediate path is different. This is because the operating conditions such as the deformation (thermal crown) due to the heat of the rolling roll differ for each pass as described above. For this reason, among the actual operating conditions, the operating policy in which the target shape of elongation and tension in each pass is determined in consideration of the operating conditions expected to some extent.

However, in many cases, the target shape of the elongation / tension according to the operation policy described above does not match the actual target shape of the elongation / tension by the shape control unit 3, that is, the target shape data. For example, when a certain material is rolled by a roll rolling mill of a certain path with a target shape based on an operation policy as indicated by a broken line in FIG. 22, target shape data actually set in the shape control unit 3 is represented by a solid line. An example is a case where a setting is made as shown and a good result is obtained.

Further, FIG. 23 shows a continuous annealing facility 70 such as a steel mill as another example of the above process. In such continuous annealing equipment 70, the band-shaped coil material 74 runs between the rolls 73 disposed in the heating furnace 71, and the quality is adjusted by annealing at a predetermined temperature, and the quality is adjusted in the direction of arrow K. It is carried out.

If the shape of the coil material 74 in the heating furnace 71 is not flat, the coil material 74 meanders, or a wrinkle-like squeezing occurs in the extended portion. Therefore, the continuous annealing equipment 70 detects the shape of the running coil material 74, for example, the elongation distribution in the width direction, and adjusts the running conditions such as the speed and tension of the coil material 74 based on the detected value. I have to.

And also in the continuous annealing equipment 70, the coil material 74
The detected elongation distribution (surface shape) in the width direction is shown, for example, in FIGS. 24 (a) and (b). In these cases, the coil material 74 having the surface shape shown in FIG.
Although the maximum elongation rate is larger than that shown in FIG. 5B, the diaphragm is hardly generated due to a smooth change in the width direction as a whole. In the case of ()), although the maximum elongation is small, the drawing tends to occur. The coil member 74 having the surface shape shown in FIG. 25 (a) is in a state where the central portion in the width direction is extended, and the one shown in FIG. 25 (b) is extended in the end portion. State. At this time, the tension must be adjusted because the coil material 74 in the central portion, that is, in the so-called middle stretch state, is generally more likely to contract than the one in the end stretch state.

[Problems to be solved by the invention]

As described above, in processes such as aluminum foil rolling and continuous annealing, not only the size of the actual shape data relating to the elongation rate from each element, but also the pattern of the entire surface shape,
That is, breaking the shape state and the degree thereof has a great significance in controlling the process. However, according to the conventional shape detection method, the judgment of the pattern of the entire surface shape relied on the experience and feeling of the operator, which required skill and was not appropriate.

Therefore, an object of the present invention is to make it possible to appropriately judge the pattern of the entire surface shape in the width direction of a running band-shaped or plate-shaped metal material, and to provide a process for handling the metal material or an operator thereof. An object of the present invention is to provide a device for detecting the shape of a strip-shaped metal material or a plate-shaped metal material capable of giving objective judgment information.

[Means for solving the problem]

In order to achieve the above object, the main means adopted by the present invention is, in its gist, a shape detecting device for detecting a widthwise shape of a running band-shaped or plate-shaped metal material, A sensor for detecting actual shape data during travel of the material, and an actual shape classification item indicating a shape state of the metal material during travel from the actual shape data and an arithmetic unit for calculating the degree thereof. This is a device for detecting the shape of such a band-shaped metal material or a plate-shaped metal material.

Further, as a means of applying this to the field of rolling a strip-shaped metal material, there is a metal material rolled shape detection device that detects the shape in the width direction of a strip-shaped metal material stretched by a roll rolling mill, A sensor for detecting actual shape data during running after rolling, and a metal material rolled shape according to the point comprising: a calculating means for calculating the shape state and the degree of the metal material after rolling from the actual shape data. It is a detection device.

Further, as a means grasped at a more specific level, there is a metal material rolled shape detecting device that detects a surface shape in a width direction of a band-shaped metal material stretched by a roll rolling machine, A sensor for detecting the actual shape data of the elongation / tension during traveling of the vehicle, and arithmetic means for calculating the elongation / tension state and the degree of the metal material after rolling from the actual shape data. This is a metal rolled shape detection device.

Here, the actual shape data may be an output value from a sensor, or may be an elongation / elongation as shown in the following embodiment.
It may be a concept representing the shape of the upholstery.

[Action]

According to the present invention, the sensor detects the actual shape data in the width direction of the band-shaped or plate-shaped metal material during traveling. Then, the calculating means calculates an actual shape state classification item indicating the shape state of the moving metal material from the actual shape data and the degree thereof. Thereby, for example, the process of handling the metal material or an operator operating the process can be provided with objective information on the shape state and the degree of the metal material.

〔Example〕

Subsequently, embodiments embodying the present invention will be described with reference to the accompanying drawings to provide an understanding of the present invention.

Here, FIG. 1 is a schematic diagram showing a system arrangement of an aluminum foil rolling target shape adjusting device including an aluminum foil rolling shape detecting device according to one embodiment of the present invention, and FIG. 2 is an aluminum foil rolling target shape adjusting device. FIG. 3 (a) is a configuration diagram showing a processing flow of the apparatus, FIG. 3 (a) is an explanatory diagram showing main parts of actual shape data represented by an elongation distribution in a foil width direction, and FIG. Explanatory diagram showing actual shape classification items of foil,
FIG. 4 (a) is a flowchart showing a processing procedure for judging a change tendency of the actual shape data, and FIG. 4 (b) shows an action for correcting the number of levels of the actual shape classification items in consideration of the shape change tendency. Illustration, FIG. 5 (a) and FIG. 5 (b)
Is a graph showing the correlation between the number of levels of the two actual shape classification items, FIG. 6 is a three-dimensional graph showing a three-dimensional pattern of the real shape data of the aluminum foil over time, and FIG. 7 is a conceptual view of a neural network. FIG. 8 is an explanatory diagram showing an example of the relationship between a shape change target for an actual shape classification item and an action candidate corresponding to the shape change target, and FIG. 9 is a diagram in which the importance of the shape change target and the actual shape classification item are tight. A graph showing the relationship with certainty factor at a certain time, FIG. 10 is an explanatory diagram showing an example in which a target shape is changed by using a rule used for inference by an action candidate inference unit, and FIG. 11 will be applied. FIG. 12 (a) is an explanatory diagram showing a processing procedure of a routine for checking the validity of the action indicated by a check tree, and FIG. 12 (a) is an explanatory diagram showing target shape adjustment parameters used for changing the target shape. FIG (b) is a ₃ of the parameters
State diagram illustrating a change in circumstances, FIG (c) is a state diagram showing the state central portion of the target shape to be adjusted by a ₄ of the parameters in the order pattern, FIG. (D) of the central portion opposite FIG. 13 is a state diagram showing a pattern situation, FIG. 13 is a schematic explanatory diagram showing an example of inference for changing a target shape, FIG. 14 is a flow sheet showing a processing flow of target shape adjustment, and FIG.
Figure is a display diagram showing an input menu displayed on the screen of the rolling mill side terminal, FIG. 16 is a display diagram showing an example of a target shape displayed on the screen, FIG. 17 is a real shape obtained asymmetrically FIG. 18 is a schematic explanatory view showing a situation in which the asymmetric actual shape is corrected.

In the following description, elements common to those of the roll rolling mill 2 shown in FIGS. 19 to 21 will be denoted by the same reference numerals, and description thereof will be omitted.

Further, the following embodiments are merely examples embodying the present invention, and do not limit the technical scope of the present invention.

Aluminum foil rolled target shape adjustment device 1 comprising an aluminum foil rolling shape detecting apparatus 1 _a according to this embodiment is applied to a process line controls the control know-how of the operator as an expert system systematized. Prior to the detailed description of this system, an outline of the system configuration of the aluminum foil rolling target shape adjusting device 1 will be described with reference to FIG.

As shown in the figure, the aluminum foil rolling target shape adjusting device 1 includes a rolling data collection unit 7, a rolling state analysis unit 8, a control target generation unit 9, an action candidate inference unit 11, a target shape generation unit 12, and an action effect. Rolling condition analysis knowledge base mainly composed of evaluation unit 10 and storing operational knowledge
D ₁ , control goal setting knowledge base D ₂ and action inference knowledge base D ₃ (including knowledge of maintaining rule consistency and action validity) and working memory for temporarily storing various data
M ₁ , M ₂ , M ₃ , M ₄ , M ₅ . The outline of the processing contents in each of the above units will be described below.

In the aluminum foil rolling target shape adjusting device 1, first, an inference process is started by a key input from the terminal device 6 on the aluminum foil rolling mill 2 side, and the operation condition data shape control unit 3 from the aluminum foil rolling mill 2 is activated. Is entered.

Rolling data collection unit rolling data collecting unit 7 receives the operation condition data including the actual shape data from the shape control unit 3 writes into the working memory M _1.

Rolling state analyzing unit The rolling state analyzing unit 8 analyzes the actual shape data and determines the rolling state of the aluminum foil 53. That is, the actual shape data, determines whether the previously several fall into a pattern how each adapted to the actual shape pattern stored in the rolled condition analysis knowledge base D _1.

Control target generation unit The control target generation unit 9 determines the direction in which the actual shape of the aluminum foil 53 is changed based on the analysis result of the actual shape data by the rolling state analysis unit 8 and the input from the terminal 6 by the operator 5. Set the control target.

Action Candidate Inference Unit- (1) Rule Inference The action candidate inference unit 11 is an IF-THEN type action in which the above-mentioned control target and operation conditions and the like are used as a condition part and an action and the like for realizing the above-mentioned control target are used as a conclusion part. the rule inference according to the rules stored in the inference knowledge base D _3, working memory an action is determined to be valid
It is written in the M _5. At the time of this writing, the following processing is executed.

-(2) Resolution of contradiction / redundancy When contradictory action candidates are listed, the action of the control target that is more important is applied.

-(3) Learning of invalid action In the above rule, when a plurality of action candidates exist for a certain control target, priorities are assigned to the action candidates, and only the action having the highest priority is applied. I do. Actions executed to achieve a certain control target and having no effect are not repeatedly applied even if the same control target is set next time.

Target shape generation unit The target shape generation unit 12 generates new target shape data based on the applied action and outputs the data to the shape control unit 3. Based on the target shape data, the shape control unit 3
Controls the aluminum foil rolling mill 2.

Action Effect Evaluation Unit The action effect evaluation unit 10 evaluates whether the control of the aluminum foil rolling mill 2 based on the applied action was effective based on the result of the data analysis and the inquiry to the operator 5. In action evaluated as invalid, working memory M ₄ to be stored, is referred to when the next action candidate Inference action candidate inference section 11.

 Hereinafter, this embodiment will be described in detail.

As shown in FIGS. 1 and 2, the aluminum foil rolling target shape adjusting device 1 controls the shape control unit 3 which controls the injection amount or temperature of the coolant 58 so as to adjust the actual shape of the aluminum foil 53. Target shape data serving as a guide for the control is output, and operation condition data is input from the shape control unit 3.

As a method of adjusting the actual shape of the aluminum foil 53, there is also a method of controlling the push-up force of a push-up roll 60 for urging the lower roll 52 upward toward the upper roll 52, In the present embodiment, only the control of the coolant 58 will be described below.

Collection of Operating Condition Data In the aluminum foil rolling target shape adjusting device 1, the inspection roll 4 is provided with an extension portion 54 of the aluminum foil 53 at the time of rolling.
As a set of elements 4 _e having a sensor for detecting actual shape data indicating the tension portion 55 (FIG. 20), the shape control unit 3 is provided downstream of the rolling roll 52 in the transport direction (arrow K). The actual shape data is transferred to the rolling data collection unit 7
(FIG. 2). The rolling data collection unit 7 writes the operational condition data transferred from the shape control unit 3 at every predetermined time interval (Table 1) in the working memory M ₁ At the same time, the rolling state analysis unit 8 is activated.

Analysis of actual shape data From the actual shape data detected by element 4 _e (sensor), the elongation state and tension state (each actual shape classification item) of aluminum foil 53 during rolling, and the rolling state for calculating their degree analysis knowledge base D _1, as shown in FIG. 3 (b), for example, the actual shape classification items such as "end-clad" - "mumps elongation" is detected from the element 4 _e, the actual shape data indicating the actual shape , And a specific program for each item for specifying the actual shape classification item.

Here, the method of specifying the actual shape classification items will be described first. Actual shape data detected as tension distribution from the element 4 _e, as shown in FIG. 3 (a), obtained in the form of elongation distribution in the foil width. The actual shape data shown in the figure includes an end portion, a quarter portion, a center portion A, and a center portion B from the outside, and the entire center portion is constituted by the center portion A and the center portion B. In this case, the tension portion 55 is located at the central portion B, and the extension portions 54 are located at the quarter portions on both sides.

The actual shape data as described above is classified into any of various actual shape classification items known from experience. If it can be determined which of the actual shape classification items corresponds to this, it is possible to select an appropriate action known from experience to bring the target shape closer to an appropriate one.

That is, the actual shape classification items stored in the rolled condition analysis knowledge base D _1, as shown in FIG. 3 (b), are classified into five main types, as described below.

(1) “Tension”: When the elongation at the end shows a lower value toward the end, it is considered as an end, and whether the value at the end is the minimum value of the whole.

Judgment is made based on the degree of elongation difference between the end and the quarter.

(2) "End elongation": Contrary to the case of end tension, a case where the value of the end is significantly larger than that of other parts. As described above, an actual shape having a somewhat extended end is often preferable, but an excessively extended end is regarded as a problem shape.

(3) “Quarter elongation”: It is determined how much the elongation percentage value of the part that extends most near the part corresponding to the zero point set in the target shape is larger than that of the end part. As described above, the actual shape in the quarter portion is the easiest to stretch, and almost this type appears in the actual actual shape.

(4) "Medium tension": tension in the center (low elongation)
Is compared with the one at the end.

(5) "Medium elongation": The difference between the elongation percentage value of the most elongated part in the center part and that of the most elongated part as a whole (in most cases, the end part or the quarter part) is small. Or if it is negative, it is determined that the medium growth. The middle elongation is classified into two types: general middle elongation with the central part stretched, the area between the quota part and the central part is extended, and the central part is stretched by the mumps.

Other unique actual shape classification items include the following “non-target” and “zero point inappropriate”.

"Asymmetric": Normally, the target shape is symmetrical in the width direction of the foil, and the actual shape is substantially the same as the left-right symmetry, but a shape in which the symmetry is broken is called an asymmetric shape. As a criterion, the difference between the maximum elongation percentage and the minimum elongation percentage at both ends is large.

One end is identified as being stretched, and the other as edge extension.

Are considered asymmetric if any of Of course, both cases may be satisfied.

“Inappropriate zero point” means a case where the zero point portion set in the target shape does not match the portion showing the maximum elongation percentage in the actual shape. Normally, heat easily accumulates in the quarter portion a of the rolling roll 52, and the real-shaped quarter portion corresponding to the quarter portion a is most easily stretched. Therefore, when setting the target shape, a zero point is set at the most extended portion of the quarter portion of the actual shape. If these parts are shifted, it is necessary to make adjustments so as to match.

From the detected actual shape data, it is determined which of the actual shape classification items the current shape state corresponds to in accordance with the method described in the section “specification method” in FIG. 3B. Such techniques are stored as programs in the rolling condition analysis knowledge base D ₁ as described above.

As noted above, one or more solid shape classification items cause actual shape data input from the work memory M ₁ is in the rolled status analyzing unit 8 is calculated by the specific program.

Normally, it is not always the case that only one actual shape classification item for which a certain actual shape is determined to be in that state is selected. Since the actual shape data is obtained as a result of operating conditions that are intricately entangled, it is often determined that there are a plurality of actual shape classification items. In such a case, there are actual shape classification items having a strong causal relationship with the actual shape data and weak classification items. The strength of such a causal relationship, that is, the degree of the shape state is referred to as a certainty factor.

The rolling state analysis unit 8 converts the actual shape data into 1 or 2 at a certain degree of certainty derived by an appropriate function.
Refine the above solid shape classification items, and stores the said actual shape category and confidence to the working memory M _2. For example, within the range of the actual shape data input from the four elements 4 _e from the end on which the aluminum foil 53 is placed, the zero end of the portion having the highest elongation percentage, the elongation difference α _2, and the entire actual shape data When the ratio β ₂ / α ₂ of the difference β ₂ between the maximum value and the minimum value of the elongation exceeds a predetermined value, the actual shape at this time includes the actual shape classification item “end elongation”. And a certainty factor from 0 to 1 is added according to the value of the ratio. The same applies to other actual shape classification items.

In this case, on the basis of the actual shape data within a predetermined past time period from the working memory M _1, the statistical characteristic information of rolling mill 2, for example, the average, the change trend, dispersion, correlation, and calculating the three-dimensional pattern recognition Based on the statistical property information, that is, using the statistical property information as a variable of the certainty factor, the certainty factor for each actual shape classification item may be calculated.

For example, the actual shape at a certain time may be extremely different from the actual shape at a time before or after the actual shape for some reason. Specifically, due to an abnormality in the shape of the raw material plate before rolling, when the actual shape of the "end tension" continues, the state of "edge extension" is detected for a moment, and then the original "edge tension" This is the case where the state continues.

Therefore, if the average value is applied among the statistical characteristic information of the actual shape data at the past several time points up to the certain time point,
The rolling state of the trend can be determined without being affected by the above-mentioned noise factor.

Next, the case where the change tendency of the actual shape data within the past predetermined time is adopted as the statistical characteristic information for use in the calculation of the certainty factor will be described in detail below. The calculation of this tendency is performed, for example, according to the processing procedure of the flowchart shown in FIG. During the rolling operation of the aluminum foil 53, the actual shape data of the aluminum foil 53 obtained from the inspection roll 4 on the roll mill 2 is collected by the rolling data collection unit 7 at predetermined time intervals (S40).

Next, the actual shape data is compared with the actual shape classification item in the rolling condition analysis unit 8 and specified as a certain actual shape classification item, and the degree is represented by the number of levels indicated by natural numbers 0 to 5. That is, the rolling state of the aluminum foil 53 is determined (S41).

For example, 4 from the end where the aluminum foil 53 is pressed.
Within the range of the actual shape data input from the four elements 4 _e , the difference in extension rate α ₂ between the portion and the end having the highest elongation rate and the difference β ₂ between the maximum value and the minimum value of the elongation rate in the entire actual shape data
If the ratio β ₂ / α ₂ exceeds a predetermined set value, the actual shape at this time is determined to include the actual shape classification item “end elongation”, and according to the value of the ratio, The degree of “edge elongation” is represented by the number of levels indicated by natural numbers 0 to 5.

The number of levels shown here is a numerical value corresponding to the aforementioned certainty factor.

 For example, (1) In the case of edge extension, in the case of confidence = 1.0, the level of edge extension = 5 In the case of confidence = 0.8, the level of edge extension = 4 In the case of confidence = 0.6, the level of edge extension = 3 In the case of degree = 0.4, the level of edge elongation = 2 In the case of confidence = 0.2, the level of edge elongation = 1 In the case of credibility = 0, the level of edge elongation = 0 (2) In the case of edge tension, the degree of certainty = 1.0 In the case of, the end elongation level = -5 When the confidence = 0.8, the end elongation level = -4 When the confidence = 0.6, the end elongation level = -3 When the confidence = 0.4, the end elongation level = In the case of -2 confidence = 0.2, the level of edge elongation = -1 In the case of confidence = 0, the level of edge elongation = 0.

Note that various methods can be considered as a method of determining the level of the edge elongation when the certainty factors of the edge elongation and the tension have a value other than 0 simultaneously. This is because which of the end elongation and the tension is considered to be a problem depends on the rolling mill and the material to be controlled.

Examples of the determination method include: (i) a method of always determining the level from the certainty of the edge elongation; (ii) a method of always determining the level from the certainty of the edge elongation; There is a method of determining the level from the larger one, and the like.

Next, the relationship between the certainty factor and the level in the case of another actual shape classification item will be described.

In the case of medium elongation and medium tension, the value of the level of end elongation can be determined from -5 to +5 as in the case of edge elongation and edge tension. However, there is no shape item that means the opposite (tension) for the fortune growth and the quota growth. That is, in the case of these two items, the certainty factor of each of 0 to 1 is only converted to the number of levels of 0 to 5, and the number of levels has no negative value. Furthermore, for inappropriate zeros and asymmetry,
It is not conceivable to calculate the certainty factor using the change tendency of the actual shape data.

Further, in step S42, with respect to the actual shape data at time T, is determined the shape points H _t to +5 points -5 points, stored in the storage unit (not shown) for storing the shape points H _t within a predetermined time period You.

This embodies an empirical handling method when the operator 5 specifies actual shape data to an arbitrary actual shape classification item, and is, for example, so that the operator 5 can easily understand when displayed on the terminal 6. The reliability of the actual shape classification item to which the actual shape data fits and the confidence of the actual shape classification item whose real shape classification item and elongation / tension state contradict each other are defined as both coordinates consisting of positive and negative natural numbers centered on 0. It is converted.

For example, if the actual shape classification item is “edge elongation” and the degree is “level 5”, the number of shape points is +5, and if the level is “1”, the shape point is +1. In addition, level 5 with "edge tension"
In this case, the score is -5 points, and in the case of level 1, the score is -1 point.
If it does not correspond to "edge extension" or "edge tension", it is scored 0 points.

If it is necessary to change and adjust the target shape by the input from the terminal 6 on the side of the rolling mill 2 at the request of the operator 5 or by the input from the rolling condition analysis unit 8 (S43), the process proceeds to step S44. As an example of statistical characteristic information for calculating the degree, a change tendency of the actual shape within a predetermined time up to the present is calculated.

For example, the shape change trend at the time T in the past i pieces of shape points H _{t-i +1,} ..., is calculated from the H _t. Here is the past
Ten shaped score H _t-9, ..., an example which is calculated from the H _t. First, the shape number H _t-9, ..., the maximum and minimum shape score gap shown in the following equation from the value H _d of the H _t is determined.

_{H d = max (H t-} 9, ..., H t) -min (H t-9, ..., H t) at that time, if the shape score gap H _d is 2 or less, the actual shape of the aluminum foil 53 Is in a stable state, and no shape change tendency is recognized.

If _Hd is 3 or more, it is first determined whether the actual shape is in a periodically changing state. For example, the shape points _Ht-9 , ..., _Ht
If that, as shown in the following equation, _- the number of shape points is changed in the direction of increased between the H _+, the number of changes to the decreasing direction _{H | H + -H - | ≦} 3, and 3 ≦ H _d ≦ 4 That is, when the absolute value of the difference between H ₊ and H ₋ is 3 or less and the shape point difference H _d is 3 or more and 4 or less, it is determined that the actual shape has a periodic change tendency. .

When _Hd is 2 or more and other than the above equation, a shape change tendency is recognized, and it is determined what the tendency is. For example, the current number of shape points H _t
Is compared with the shape point number _{Ht-9 at the} tenth point in the past.

That is, as shown in Table 2, _Ht is higher than _Ht-9 . If the value also indicates a large value, it indicates that the end has a tendency to elongate, while if the value indicates a small value, it is determined that the end has a tendency to be taut. Further, when _Ht and _Ht-9 are equal, it is determined that the actual shape is stable, and the process is performed bypassing the level number correction step (S45) of the actual shape classification item described later.

Therefore, for example, if the shape change tendency at time T is “edge extension tendency” and the actual shape classification item at that time is specified as “edge extension” and the number of levels is 3,
As shown in FIG. 4 (b), a correction action is performed to increase the number of levels by 2 with respect to the number of levels of the actual shape classification item at that time (S45). This is because level 3 in the above example is inappropriate when performing the conventional shape control in consideration of the current shape judgment and the shape change tendency. Is considered to be almost equivalent to level 5 (a state in which edge elongation is rapidly progressing).

From the level corrected in consideration of the change tendency, the certainty factor when the change tendency is used is calculated.

For example, if the edge elongation level is 5, the edge elongation confidence is 1.0, if the edge elongation level is 4, the edge elongation certainty is 0.8, and if the edge elongation level is 3, the edge elongation certainty is obtained. 0.6, if the end elongation level is 2, the end elongation confidence is 0.4, if the end elongation level is 1, the end elongation certainty is 0.2, and if the end elongation level is 0, the end elongation certainty To 0.

Also, if the level of the edge extension is negative, the certainty of the edge tension is determined. For example, if the edge elongation level is -5, the confidence of the edge tension is 1.0.
If the level of edge elongation is -4, the confidence of edge tension is 0.8
If the level of edge extension is -3, the confidence of edge tension is 0.6
If the edge elongation level is -2, the confidence of the edge tension is 0.4
If the level of edge extension is -1, the confidence of edge tension is 0.2
If the level of edge extension is 0, the certainty of edge tension is determined to be 0.

In addition, in the case of the happy growth and the quota growth, the certainty factor is calculated from the level corrected in consideration of the change tendency and the change tendency is considered. At that time, if the level becomes a negative value, the certainty factor is set to 0.

Further, it is also possible to recognize the three-dimensional pattern relating to the actual shape data as the statistical characteristic information. The three-dimensional pattern P is shown in FIG. In the figure, an arrow M indicated by a two-dot chain line, elongation at each time t ₀ ~t ₆ indicates the temporal position changes of the element 4 _e which detects the maximum value.
As illustrated, the element 4 _e of the elongation maximum is meandering in width of several foil width direction amino element 4 _e. In such a state, not only the part that is currently maximally extended,
Equally intensively the rolling roll 52 which corresponds to the width of said several elements 4 _e including the site must inject coolant 58. This is because, even if the coolant 58 is injected only to the portion that is currently maximally extended, the extended portion only moves to the adjacent portion. Such 3
The statistical characteristic information represented by the dimensional pattern P, such as “the stretched part of the actual shape is meandering with time” can be determined by the above-described numerical calculation algorithm. A neural network recognition method for pattern recognition of real shape data is effective.

In the neural network 20, as shown in FIG. 7, a plurality of neurons 15 for calculating and outputting input data by threshold processing are conceptually arranged as an input layer, an intermediate layer, and an output layer. Connected via 16. Then, the neural network 20 uses the pattern data of the actual shape data of the aluminum foil 53 as input data, uses the actual shape classification item and the degree thereof as output data, and determines the correspondence between the two to determine the connection weight of the connection unit 16. It is learned by changing. Therefore, when new real shape data is input to the learned neural network 20, the real shape data is specified in any of the real shape classification items together with the degree. Such a neural network 20 may be applied to the rolling situation analysis unit 8.

Here, as a calculation method for determining the actual shape state of the aluminum foil 53, a numerical calculation example by a specific method determined for each actual shape classification item has been mainly described, but the determination by the neural network 20 or such a method is used. It goes without saying that a similar calculation effect can be obtained by a determination based on a rule base (not shown) storing the determination knowledge.

The actual shape data to be subjected to the input operation to the rolling status analyzing unit 8 from the working memory M _1, the value of the type of data at a time in the predetermined time, or several data values at one time Alternatively, it may be one of the values of one type of data at several points in time or the values of several types of data at several points in time, and data necessary for the calculation may be appropriately used.

Thus, the rolling status analyzing unit 8, the current actual shape category and confidence with respect to the actual shape data of the aluminum foil 53 is determined, and written into the working memory M _2.

Generation of Control Target The control target data (shape change target (FIG. 8) and its importance), which is a key in appropriately setting or changing the target shape, is rolled by the operator 5 in the control target generation unit 9. or is input from the rolling mill 2 side of the terminal 6, or on the basis of the working memory M actual shape classification items and the rolling status data of the confidence or the like in ₂ is automatically generated. In this automatic generation, “the operation method (such as“ rolling by extending the end greatly in a predetermined pass ”)” or “if the input by the operator 5 and the automatically generated one conflict, the rule such "give priority to input information of the operator is applied with reference to the control target setting knowledge base D _2.

For example, if the detected actual shape data includes “edge extension” as in the above example and the confidence at that time is 0.8, five shape change targets are set in order to eliminate “edge extension”. Is selected, and the importance corresponding to the certainty factor (0.8) is given to the selected shape change target. Then, the shape change target and its importance are stored in the working memory M _3.

The situation where the importance of the shape change target is calculated in the control target generation unit 9 from the certainty factor of the actual shape classification item specified as described above will be described in detail below.

The importance is a measure of whether the target shape data needs to be changed, and is shown in a graph (FIG. 9) showing the relationship between the actual shape data and, for example, the certainty factor of the actual shape classification item indicating the degree of edge tension. Is shown. In the drawing, an example of “edge tension” in the actual shape classification items is shown.

For each of the actual shape classification items such as edge tension and edge elongation,
An importance calculation function (f (x)) that gives the degree (importance) of the necessity of changing the target shape is defined. For example, a function to calculate the importance of "edge" Is defined as

That is, the end tension degree (confidence) is compared with the first threshold value L _1, as shown in FIG. 9, if it exceeds the first threshold value L _1, for the real shape classification item of target shape change The degree of importance corresponding to the selected degree of certainty is calculated.
On the other hand, if the confidence level is a first threshold value L ₁ or less, the degree of importance 0 is given, the actual shape category never be subjected upon change in the target shape. Wherein for each solid shape classification item, the first threshold value L ₁ is respectively set individually, each of the confidence and said first threshold value L ₁ is the comparison operation, whether to Kyosu the change of the target shape items It is determined every time.

Whether or not it is necessary to change the target shape is determined for each actual shape classification item as described above, and sometimes it is determined whether or not the average of the combined importance of each item exceeds a threshold value. is there.

Subsequently, a method of determining whether or not the target shape needs to be changed based on the combined importance or the average thereof from the actual shape classification item selected to change the target shape will be described in detail.

If the actual shape classification items are S ₁ , S ₂ ,..., S _i , the importance calculation function f for each item defined for them
_{The combination} importance calculation function g () obtained by combining _si () is defined as follows.

The function g () _{is, g≡ (Σf si (x i} )) / i or g≡Σf _si (x _{i) where, 0 ≦ f si (x i} ) ≦ 1, f si (x i) is x, _i is expressed in the form of a sum average or a sum, such as a strong monotone increase.

Here, when f (L ₁ ) is (L ₁ ), the strong monotonic increase means that when L ₁ <L ₂ , f (L ₁ ) <f (L ₂ ).

As described above, the combined importance indicating the degree of necessity of starting the inference processing is calculated from the importance of each item in the action candidate inference unit 11, and the combined importance is determined by the predetermined second threshold L.
When the number exceeds ₃ (not shown), the inference processing is started, and the target shape data is appropriately changed.

The following is a specific example. When the importance for "edge tension" is 0.4, the importance for "quarter elongation" is 0.6, and the importance for other ("edge elongation", "medium elongation", "medium tension") is 0. In the case of the sum, the combined importance is 0.4 + 0.6 + 0 = 1.0. If the second threshold value L ₃ is 0.9 in this case, since the direction of the synthetic importance is high, the inference process is started. As a method of determining the importance as the trigger, the above-described method based on the sum average may be employed.

In this embodiment, as described above, when the confidence of each item exceeds the threshold value given to each, for example, the degree of "end tension" is also inferred when exceeding the threshold value L ₂ shown in FIG. 9 Processing is started.

Further, when the synthetic importance level exceeds the second threshold value L _3, simultaneously outputs a start signal to an alarm device, not shown, may be driving the alarm device.

 Next, the target shape inference processing will be described.

Application of Action-(1) Rule Inference Operating condition data including current target shape data and current actual shape data, rolling condition data including extracted actual shape classification items and their certainty factors, processed as described above. , And the control target data including the shape change target and its importance are transferred from the work memories M ₁ , M ₂ , M ₃ to the action candidate inference unit 11, respectively. In this embodiment, the target shape data is changed based on an empirical value in which a change in the actual shape when the target shape data for the actual shape (data) is changed and given to the shape control unit 3 is stored together with the change in the target shape data. create. Experience as described above, specifically integrated in the action inference knowledgebase D _3, are stored, FIG. 10 and rules Example 1, it is expressed in the form of rules Examples 2-4 of Table 3 to be described later You. Explaining using Rule Example 2, “I want to extend the end” in the main condition part is a change in the actual shape, and “Increase the target value of the end level” in the conclusion part indicates a change in the target shape data. . Action candidate inference unit 11, and the data transferred, collates the condition part of the rule to the action inference knowledgebase D ₃ is stored, the result of the collation, the rule which satisfies the condition part are all true Then, target shape change data (FIG. 8, hereinafter referred to as action) at the conclusion of the rule is selected. As described above, the inference processing for deriving a conclusion (target shape to be adopted) corresponding to the conditions such as the operation condition data, the rolling state data, and the control target data depends on the knowledge (expertise) of the experienced person, as described above. I can't get it. In the present invention, such inference processing is automated. Rules for such automated reasoning is integrated in the action inference knowledgebase D _3, are stored. Such a rule is expressed in the form of "if [condition part], then [conclusion part]", and is expressed by a logical product as shown below.

If [control target data] and [operating condition data, rolling status data], then [designation of target shape adjustment parameter and its change degree (action and its degree)] Here, the target shape adjustment parameter is a table. As shown in -4, it is an element that determines target shape data (a target elongation rate distribution in the path). Not all the parameters shown in Table 4 are described as the target shape adjustment parameters that constitute the conclusion of each rule. In many cases, only a part of the target shape adjustment parameters necessary to satisfy the condition part is described together with the degree of change.

For example, as shown in FIG. 10, in rule example 1,
If the actual shape of the aluminum foil 53 is specified as the quarter extension, and there is no zero below the portion where the extension near the quarter is the largest, then the position of the zero point is set below the portion where the extension near the quarter is the largest. stored in the action inference knowledge base D ₃ is a rule that specifies the action, such as come "have to.

-(2) Resolution of Inconsistency / Redundancy On the other hand, as seen in Rule Example 4 shown in Table 3, there are cases where incidental conditions are added to rules. For example, in an actual shape, when edge tension and quarter elongation occur simultaneously, rule example 2 and rule example 3 may be selected. Since each of them is established at the same time, the action candidate inference unit 11 cannot resolve these inconsistencies, and an error occurs. Therefore, this problem can be solved by providing an additional condition in the condition part of the rule example 2 and setting it to rule example 4. That is, in rule example 4, when the importance of extending the edge and the importance of extending the quota portion are both larger than the first threshold value, but the importance of extending the quota portion is less than 0.4, The target value of the end level (elongation rate at the end in the width direction) is increased. As a method for eliminating such inconsistency or redundancy, the shape change target having the higher importance can be prioritized.

On the other hand, there are cases where two or more types of shape change targets are simultaneously selected for certain actual shape data, and the contents of actions corresponding to the respective shape change targets are the same. For example, the current actual shape classification item (FIG. 3 (b) is simultaneously specified as “edge tension” and “medium extension”, and the difference in the degree of action derived from each actual shape classification item is different. (Fig. 8) is selected at the same time. The rule applied in such a case is the degree of action according to the certainty factor of the specified actual shape classification item. which sets a is stored in the action inference knowledgebase D ₃ in advance.

Therefore, when actions having the same contents having different degrees as described above are selected at the same time, these actions are not executed at the same time. Redundancy is avoided. Here, conversely, only an action with a small degree of action may be executed, or an action corresponding to the average value of the actions may be selected or generated.

-(3) Learning of invalid action Further, as shown in FIG. 8, several types of action candidates with priority added to one shape change target are prepared. Then, when a certain shape change target is selected, the action having the highest priority is executed.

The priority is not fixed and is checked for each inference. For example, if the inference in action candidate inference unit 11 is executed, with respect to which the shape change target, which action it has adopted is stored in the working memory M _5, at action effect evaluation section 10 at the next inference, the last reshaping Whether or not the target has been achieved (evaluation of the effect) is determined by comparing the previous and current importance levels.

As a result, if the current target shape data changed based on the previous shape change target and its importance is determined to be valid in the action effect evaluation unit 10, that is, the importance is set to a value lower than the previous value. If so, the adopted action is considered valid and the action inference knowledge base D ₃
Is raised. Conversely, if it is determined to be invalid, and rules which infers selected last applied in action and the action was not effective it is stored in the working memory M _4.

For example, the shape change target shown in FIG. 8 indicates that the last time “I want to extend the end” is of importance 0 based on the rolling status data from the rolling status analysis unit 8 or the input data from the operator 5.
If it is determined in step 6, the highest priority "increase the level of the edge (priority 1)" among the actions associated with it is selected, and the level of the edge (elongation rate) according to the importance level 0.6. Is output to the shape control unit 3, and the simultaneously applied target shape data, shape change target, its importance (0.6), action, and its priority (1) are stored in the action inference knowledge base D _3. Is stored. Then, when the shape change target “I want to extend the end” is selected with the importance of 0.6 or more at the time of determining the shape change target of the present time, the edge tension state of the actual shape in question is improved. In many cases, the last applied action was invalid. Conversely, if "I want to extend the end" is selected this time with an importance of less than 0.6, it is determined that the previous action was effective.

Therefore, the actions that have been invalidated, the rules deduced the action is written in the working memory M _4. Then, even if the same shape change target is selected at the next inference and the invalid action is selected, the invalid action is not applied, and the next highest priority action determined to be appropriate is applied. Then, it is subjected to the change of the appropriate target shape data this time. As a result, if it is determined that the next action applied to achieve the shape change target is valid, the priority of the action is raised and the priority of the invalid action is lowered. Changed priorities as described above is written in terms of the priority of the action inference knowledgebase D _3.

In this way, even in the case where the target shape obtained by the aluminum foil rolling target shape adjusting device 1 has no effect on the actual shape and the actual shape of the problematic aluminum foil 53 is maintained. In this inference, a different action from the previous action is selected even if the shape change target is the same as that in the previous inference. Thereby, the actual shape is appropriately changed without the invalid rule being repeatedly applied.

Whether action mentioned as candidates is valid in the action candidate inference unit 11, 11 after being checked in detail with check tree shown in FIG., The work each time when it is determined that the appropriate memory M ₅ Registered in. still,
The aforementioned actions inference knowledgebase D _3, rule set comprising a plurality of rules having a condition part as described above same shape change target is set for each of the shape change target, the main area and the for storing the rule set A save area for storing rules removed from the rule set is secured. The rules for which the inference processing has been completed are sequentially removed from the main area to the save area.

In the check tree shown in the figure, first, it is determined whether a rule that matches the currently selected shape change target and the shape change target exists in a rule set to which the rule belongs, that is, a rule corresponding to the above rule set is included in the main area. there are any remaining is checked in case C _1. If Case C ₁ is true,
In Case C ₃ proceeds to check the strings attached according to an operating condition such as the condition part of the rule.

If not corresponding to the case C _3, that is, when all the condition part including incidental condition does not match, the rule is removed to the save area from the rule set of the main area. If satisfied the incidental condition, in case C _4, whether the action of the rule in which the condition part is satisfied all of its effect was not observed when there to have been applied in the past, i.e., the current working memory M ₄ It is checked whether it is registered. Then, if applicable to the case C _4, to remove the rule from the rule set (main area). Case C ₄
If not applicable, the presence of actions conflicting with each other is checked in case C _5. As mentioned above,
The number of shape change targets set is not limited to one, and a plurality of shape change targets may be selected. In this case, it is often the case that actions associated with each shape change target contradict each other.

Therefore, the check result, among the action registered already working memory M ₅ is to be valid, if any action that is inconsistent with the action that is currently checked, among the rules with an action , it is registered in the action working memory M ₅ of the rule if is larger severity shape change target that is currently selected, actions that already the conflicting registered are removed to save area.

Conversely, already left the work registered actions memory M ₅ If is larger importance shaped target with an action of the registered, rules the rule with the action that is checked It is removed from the set (main area) to the save area. If Case C ₅ is not applicable,
That is, when the above each action is consistent, whether the shape change goal of these actions are the same is checked in case C _6. If applicable to the case C _6, check whether there is a difference in the priorities of the respective action (Case C _7), if there is a difference in priority, only the action of the larger priority working memory M ₅ Left in
The smaller action of priority is erased from the working memory M _5. When there is no difference in priority, both actions are left together in the working memory M _5.

As described above, if not applicable to the case C _1, the rules that match the currently selected shape change target is judged not in the rule set proceeds to check the case C _2.

If applicable to the case C _2, i.e. rules of each rule set in has been checked all, if it is determined that the action candidates by checking the case C ₃ -C ₇ becomes all incompatible,
Resets (clears) the historical invalid information in the working memory M _4, Under the current priority since it is not possible to elect an appropriate action candidates, and resets the priority is reset in the priority degree After recovering each rule set consisting of rules with action candidates
Restart the action check inference from the beginning.

On the other hand, if applicable to the case C _2, a result of verification of all the rules in the set each rule, since supposed action candidates considered appropriate is stored in the work memory M ₅ is selected, to the action check The inference ends.

If two or more shape change targets are selected, the validity check of the above action is performed for another set of shape change targets in the same manner as above (C _{1 to} C ₇ ).

Thus, by the check routine, working inconsistency between action candidate memory M ₅ already about to be newly registered as action candidates registered, the priority, the efficacy results and the like are checked, target shape The validity of actions to be applied to data changes and the integrity of rules are maintained.

Generated subsequently registered in the working memory M ₅ action and the degree of the target shape, i.e. "raise the end level, the degree 0.8" target shape changing data such as is transferred to the target shape generator 12.

The target shape generation unit 12 changes the values of the target shape adjustment parameters shown in Table 4 and FIGS. 12 (a) to 12 (d) based on the target shape change data. You. For example, when the above-mentioned action is “raise the end level, the degree is 0.8”, the value of the target shape adjustment parameter a ₁ related to the elongation rate of the end is determined according to the degree of the action. The change is set, and the target shape data changes. Further, the shape control unit 3 controls the coolant 58 of the roll mill 2 based on the input target shape data after the change.

Evaluation of applied action Then, operation condition data including the actual shape data newly obtained this time is input to the rolling data collection unit 7, and the same processing as the previous time is repeated. That is, the shape change target for the current actual shape and its importance are calculated by the control target generation unit 9 and compared with the previous one in the action candidate inference unit 11, respectively.

A specific example of repeating the above inference is shown in FIG. For example, some operating conditions reshaped target E _1, which is calculated from the actual shape data included in the data, when the importance level is "want strung quota" is 0.8, the first inference E ₂ Is executed, and then the action candidate is (A
1) When the width of the zero was widened, (A2) the zero was moved outward. Here high-priority action A1 is applied, it before and after the target shape data are modified by were as shown in the inference result E _3.

However, when evaluating the effect of action A1, E ₁
Was not less than 0.8, and its effect was not observed. Therefore, the rule to derive the above action A1 is stored in the work memory M ₄ as was ineffective.

Then, apply the next highest priority action A2 to 2
Times eyes of inference E ₄ is executed. In this case, the rules including the shape change target E ₁ is continued subsequently applied by rolling process, if operating conditions are not the same as during the first inference, the action A1 and action A2 is obtained as a candidate. As a result of verifying the history of actions effect by inference E ₄ of the second, since the action A1 is stored in the work memory M ₄ as was ineffective last, but this time not applied (in Fig. 11 case C _4), the next highest priority action A2 is applied to the target shape data is changed.

As a result, if it is determined that the quota elongation is improved, the priority of the action A2 can be promoted and stored in the action inference knowledgebase D ₃ than that of the action A1.

As described above, the change of the actual shape (shape change target) when a certain target shape data is given to the actual shape of the aluminum foil 53 and the change of the corresponding target shape data are determined by the action candidate inference unit 11. The target shape data changed each time and the actual shape data obtained as a result, operating condition data used to set the target shape data, rolling state data, or each empirical value such as control target data,
Stored in the action inference knowledgebase D ₃ as inference rules. Then, the action candidate inference unit 11 calculates appropriate target shape data based on the respective empirical values so as to realize an ideal actual shape (operating policy) at that time, and sets the target shape data as a target. Shape generator 12
And automatically outputs the data to the shape control unit 3.

The aluminum foil rolling target shape adjusting device 1 as described above,
As shown in FIG. 14, the operation is started by the operator 5 tapping the key from the rolling mill terminal 6 (step 21). Subsequently, the operator 5 inputs the shape change target information together with the importance according to the input menu (FIG. 15) displayed on the screen of the terminal 6 (step 22).

Accordingly, the aluminum foil rolling target shape adjusting device 1
Analyzes the rolling data transferred from the shape controller 3 (step 23), creates an appropriate target shape by inference (step 24), and displays the target shape before and after the correction (FIG. 16) on the screen. At the same time, the corrected target shape data is output to the roll mill 2 via the shape control unit 3 (step 25). Then, it was evaluated whether the corrected target shape was valid for the problematic actual shape (step 2).
6) Waiting for input by the operator 5.

At this time, the target shape adjusting device 1 also automatically generates a shape change target. If the target is inconsistent with the one input by the operator 5, the target having the higher importance is input by the operator 5. Alternatively, the shape change target may be generated based on a rule that gives priority to any one of the above, or the one based on the shape determination result from the actual shape classification item.

The aluminum foil rolling target shape adjusting device 1 constantly monitors the actual shape of the aluminum foil 53, and when it is determined that the target shape data needs to be changed, the inference is started by the operator 5, Alternatively, the target shape data changing process can be started. For example, a comparison condition between the certainty factor of the actual shape classification item and a certain threshold value α is set in the condition part of the rule. A specific example of the rule will be described below.

If [the actual shape classification item and its certainty] and [working condition], then [designation of the shape change target and its degree] More specifically, if the endurance certainty <α, and If the path is the second pass, we want to extend the end. The importance is expressed as 1.0. That is, when the actual shape changes and the degree of end extension becomes equal to or less than the threshold α, the above rule is applied,
Inference will begin.

Further, the aluminum foil rolling target shape adjusting device 1 has a function of improving even when the obtained actual shape data is asymmetric in the foil width direction. As shown in FIGS. 17 and 18, when it is determined that the actual shape data is asymmetric (step 31), the target shape, which was previously symmetric with respect to the portion having a low elongation, is determined by the operator. 5 is temporarily set high (step 32). This is a roll 52
This is for temporarily deflecting the distribution of the amount of coolant 58 injected into the roll width direction to uniformize the heat distribution in the rolling roll 52, particularly at the start of operation (during the temperature rise of the roll) or resumption. It is effective at the time (after the roll change). The process in step 32 is repeated until the actual shape data becomes symmetric.

In the present embodiment, the aluminum foil 53 is used as a control target, but the present invention is not limited to this, and copper or another metal may be used, and the thickness is not limited.

As described above, the actual shape data of the aluminum foil 53 divided in the foil width direction and detected from the sensor that detects the tension is:
The aluminum foil rolled shape rendering device 1a performs pattern recognition on _a specific actual shape classification item, and the downstream control target generation unit 9 determines that the shape is a problem shape based on the magnitude of the degree characterized by the actual shape classification item. In this case, an inference process is performed to deal with the actual shape classification items and the degree of the pattern recognition. For this reason, in the aluminum foil rolling, the actual shape of the aluminum foil 53 is constantly monitored, and even when a problem shape occurs, it is possible to quickly cope with the problem. As a result, it is possible to make appropriate shape management, and aluminum foil
It can contribute to 53 quality control and improvement of shape control accuracy.

In the present embodiment, aluminum foils rolled shape detecting device 1 _a
Has been applied to the shape control of the aluminum foil 53, but is not limited to this. An alarm device or a rolling system that issues an alarm according to the specification of the actual shape classification item and the degree thereof is provided. The present invention can also be applied to a stopping device for stopping the whole.

Also, the aluminum foil rolling shape detection device _1a is a sensor for detecting the actual shape data of the elongation and tension at the time of rolling,
Piezoelectric element employing a buried element 4 _e, but a plurality of air-bearing element to the element 4 _e and appearance substantially one substitute as the sensor, the actual shape data based on a change in the air pressure It can also be detected.

Up to this point, the shape of the stretched and stretched shape has been described as the detected actual shape data, but the actual shape data may be data relating to the thickness of the aluminum foil 53 in the foil width direction.

The shape detection device as described above is not limited to the field of aluminum foil rolling, and is applicable to, for example, the continuous annealing equipment 70 and the like described in the related art as long as the process handles a band-shaped or plate-shaped metal material. obtain.

〔The invention's effect〕

What is claimed is: 1. A shape detecting device for detecting a shape of a strip-shaped or plate-shaped metal material in the width direction during traveling, wherein a sensor for detecting actual shape data of the metal material during traveling is provided. Since it is a shape detecting device for a strip-shaped metal material or a plate-shaped metal material, the shape detection device includes an actual shape classification item indicating a shape state of the metal material and an arithmetic unit for calculating the degree thereof. The actual shape classification item indicating the shape in the width direction and its degree, that is, the pattern of the entire surface shape can be appropriately determined. Thereby, objective pattern information of the entire surface shape, which is important in controlling the process of handling the metal material, can be given to the process and the operator.

[Brief description of the drawings]

FIG. 1 is a schematic diagram showing a system layout of an aluminum foil rolling target shape adjusting device having an aluminum foil rolling shape detecting device according to one embodiment of the present invention, and FIG. 2 is a process of the aluminum foil rolling target shape adjusting device. FIG. 3 (a) is an explanatory view showing a main portion of actual shape data represented by an elongation rate distribution in a foil width direction, and FIG. 3 (b) is an actual diagram of an aluminum foil classified by pattern. FIG. 4 (a) is a flowchart showing a processing procedure for judging a change tendency of the actual shape data, and FIG. 4 (b) is a graph showing the shape change tendency of the actual shape classification item. FIG. 5 (a) and FIG. 5 (b) are graphs showing the correlation between the number of levels of two actual shape classification items.
6 is a three-dimensional graph showing a three-dimensional pattern of the actual shape data of the aluminum foil over time, FIG. 7 is a schematic diagram conceptually showing a neural network, and FIG. 8 is a shape change target for an actual shape classification item. FIG. 9 is a graph showing an example of the relationship with the corresponding action candidate, FIG. 9 is a graph showing the relationship between the importance of the shape change target and the certainty factor when the actual shape classification item is tight, and FIG. FIG. 11 is an explanatory diagram showing an example of a rule used for inference by a candidate inference unit and a target shape changed by using the rule. FIG. 11 shows a check tree showing a processing procedure of a routine for checking the validity of an action to be applied. indicated illustration, Figure 12 (a) is an explanatory view showing the target shape adjustment parameter used to change the target shape, FIG. (b) is a state diagram showing the state change of a ₃ of the parameter, Figure (c) is a state diagram showing the state central portion of the target shape to be adjusted by a ₄ of the parameters in the order pattern, FIG. (D) shows a state diagram illustrating the state wherein the central portion is opposite pattern, FIG. 13 is a schematic explanatory view showing an inference execution example for changing a target shape, FIG. 14 is a flow sheet showing a processing flow of target shape adjustment, and FIG. 15 is displayed on a screen of a rolling mill side terminal. FIG. 16 is a display diagram showing an input menu, FIG. 16 is a display diagram showing an example of a target shape displayed on the screen, FIG. 17 is a flow sheet showing a method of correcting an actual shape obtained asymmetrically, and FIG. FIG. 19 is a schematic explanatory view showing a situation in which the asymmetric actual shape is corrected, FIG. 19 is a schematic perspective view showing a roll rolling mill as an example of the background of the present invention, and FIG.
Figure is an external view showing the surface shape of the aluminum foil after rolling, FIG. 21 is an explanatory diagram showing the correlation between the cross-sectional shape of the rolling roll, the actual shape of the aluminum foil, and the target shape for controlling the actual shape,
FIG. 22 is a graph showing simultaneously a target shape in operation of aluminum foil and a target shape set for control, and FIG. 23 is a schematic configuration showing a continuous annealing equipment applied as another example of the background of the present invention. FIGS. 24 (a) and (b) and FIGS. 25 (a) and
(B) is a graph showing the actual shape in the width direction of the coil material traveling in the continuous annealing equipment of FIG. 23. [Explanation of Signs] 1 _a …… Aluminum foil rolling shape detection device 2 …… Roll rolling machine, 3 …… Shape control unit 4 …… Inspection roll 4 _e …… Element (sensor) 8 …… Rolling situation analysis unit (calculation Means) D ₁ …… Rolling situation analysis knowledge base (calculation means) 53 …… Aluminum foil, 54… Elongated part 55 …… Tension part.

Claims (3)

(57) [Claims] 1. A shape detecting device for detecting a shape of a strip-shaped or plate-shaped metal material in a width direction during traveling, a sensor for detecting actual shape data of the metal material during traveling, and the actual shape data. And a calculating means for calculating an actual shape classification item indicating a shape state of the metal material during traveling and a certainty factor indicating the degree thereof. apparatus. 2. A metal material rolled shape detecting device for detecting a shape of a band-shaped metal material stretched by a roll rolling machine in a width direction, wherein actual shape data during running of the metal material after rolling is detected. A metal material roll shape comprising: a sensor; and an actual shape classification item indicating a shape state of the metal material after rolling from the actual shape data and a calculation means for calculating a certainty factor indicating the degree thereof. Detection device. 3. A metal material rolled shape detecting device for detecting a surface shape in a width direction of a band-shaped metal material stretched by a roll rolling mill, wherein the metal material rolled shape detecting device comprises: A sensor for detecting shape data; and a calculating means for calculating an actual shape classification item indicating an elongation / tensile state of the metal material after rolling from the actual shape data and a certainty factor indicating the degree thereof. A rolled metal shape detection device characterized by the following.