JPH0994646A - Method for controlling cut-off of cast slab in continuous casting - Google Patents

Abstract

PROBLEM TO BE SOLVED: To minimize a waste by selecting an optimum order size and to quicken a cut-off operation, at the time of cutting off a continuously cast slab. SOLUTION: At the time of cutting off the continuously cast slab, an evalution function weighing to casting condition of a specific length, secondary cut-off times, cut-off remained waste, number in the specified length, etc., to a non-cut-off cast slab length and a factor related to kind of steel, are prepared. As the optimizing means for obtaining the cast slab length, in which this evaluation function becomes the max., a genetic algorithm containing the specific length and some length cases, in which the orders are assumed after that, as a gene information, is used to control the cut-off of the continuously cast slab.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for automatically controlling slab cutting in continuous casting in a steelmaking process.

[0002]

2. Description of the Related Art As a method of cutting a slab in continuous casting, there is a method described in Japanese Patent Laid-Open No. 3-27853. This is because when a quality abnormality part is found on a slab that has been poured from a tundish into a mold and cooled, the cutting control device that receives the signal from the process control device calculates the good piece length L, and the lower limit value of the planned cutting length. It is determined whether the total lower limit value added is equal to or more than the lower limit value added a, and when L ≧ a, the ingots are collected as planned, and when L <a, one is subtracted from the planned number. Controlling the control device so as to collect the number of pipes, at this time calculating the difference value ΔL between the total value of the reference length of each slab and the length L of the good piece, and allocating this difference value ΔL to each slab Is. As a result, generation of a surplus material slab can be prevented, and the collection rate of the slab can be improved. A flowchart of this method is shown in FIG.

Further, in Japanese Unexamined Patent Publication No. 58-159953, the dimensions and the order of the pieces are determined for each of the strands A and B, and the pieces are cut in the designated size and order, and an abnormality occurs during casting. If it is, the first condition is to satisfy the production condition,
A cutting method for a continuously cast slab is disclosed in which the measurement plan is re-edited for cutting an uncut slab, with the second condition being that the yield loss is minimized. FIG. 6 shows a flowchart of this method.

[0004]

However, in these methods, the slab collection rate or the minimum yield loss is evaluated by adjusting the length of the slab within the allowable range, and only this is done. Then there are insufficient evaluation items.

An object to be solved by the present invention is to provide a slab cutting control method capable of easily coping with changes in steel type and operating conditions such as yield priority and orthogonality priority.

[0006]

In order to solve the above-mentioned problems, a method for controlling cutting of a slab in continuous casting according to the present invention comprises:
When cutting continuously cast slabs, an evaluation function that weighs factors related to casting conditions such as specified length, number of secondary cuttings, cutting debris, and specified length, and steel type, relative to the length of uncut slabs As an optimization method for obtaining the slab length that maximizes this evaluation function, a genetic algorithm that uses the specified length and some cases of the length that is not the specified length but is expected to be ordered from now on as genetic information. Is used.

[0007]

In the present invention, a new evaluation function is created, the weighting factor can be adjusted arbitrarily, and the structure is such that the evaluation can be easily added, the general optimization method is applied, and the slab is We verified that the genetic algorithm is most suitable for calculating the optimal length of. The evaluation function is set as follows as an optimized calculation method of the slab cutting length. Evaluation function = a
× Designated length deviation + b × Secondary cutting count + c × Cutting debris + d ×
Specified length number + e x hot water shortage + f x hot water surplus + g x casting speed balance

A genetic algorithm is used as the optimum control method. A genetic algorithm is an artificial model that simulates the mechanism of organism evolution, and its outline is the repeated action of organisms as they evolve. Natural selection: Only individuals that adapt to the environment survive. Dominant inheritance: Breeding between individuals allows inheritance of superior traits between generations. Mutation: A mutation that is completely different in nature.

In applying this genetic algorithm to the optimization of the cutting length of a slab, the specified length and some cases of the length which is not the specified length but is expected to be ordered from now on are used as genetic information, The slab length that maximizes the evaluation is calculated for the total length of the slab. In addition, the casting speed balance is the speed ratio of each of multiple castings from a tundish through a plurality of molds.
It is possible to minimize the specified length deviation of the slab by changing the speed ratio of the above and changing the casting length of the predetermined strand.

[0010]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, the present invention will be specifically described with reference to embodiments shown in the drawings. FIG. 1 is a flowchart showing an embodiment of a slab cutting control method according to the present invention. In the figure, in step 100, calculation conditions are fetched. The calculation conditions include casting length, designated slab length, equipment constraint length, designated tolerance range, quality abnormal position, random scale tolerance range (the length of products that are out of the specifications but ordered in the past), etc. . In step 110, the weighting factors ai, bi, ci, of the evaluation function are
Set d ... Based on priority. Step 12
At 0, the evaluation function f is set.

[Equation 2] In step 130, the optimum length is calculated by the genetic algorithm.

FIG. 2 shows an outline of the calculation in step 130 using the genetic algorithm. First, in step 110, the weight of the evaluation function is set according to the operation needs, and then, in step 115, it is arbitrarily given by a random number within the maximum and minimum range of the cast length that can be manufactured in equipment. Find some combinations. The sum of these combinations corresponds to the sum of the control range casting lengths. For example, if the total casting length is 20 m, the individuals in the set are 5 m, 4 m, 4 m, 4 m, 3 m, or 5 m.
It may be m, 5m, 3m, 3m, 4m. A plurality of such individuals are created to generate one group. Next, at step 120, an evaluation value is calculated for each individual of each combination using the weight given at step 110. Then, in step 130, an arbitrary number is selected from the plurality of individuals, and two individuals among them are spliced to generate two different individuals.

For example, in the above-mentioned example, when the front two are fixed and the rear three are replaced, the arrangement shown in FIG. 4A is obtained. In addition, the mutation is changed at the end by a random number as shown in FIG. 4B. The newly created individuals are evaluated in this way, a new group is generated with the one with a high evaluation value left, and this is repeated.

As for the weighting coefficient of the evaluation function, in the case of the designated length priority, a _i is made larger than other weighting coefficients other than b _i . For example, a _i = 15, b _i = 5000, c _i = 0, and d = 0. In the case of the yield priority, c _i is made larger than the weighting factors other than b _i . For example, a _i = 5, b _i
= 5000, c _i = 15, d = 0.

FIG. 3 shows, as an example, a case where the calculation is performed by a general process control computer having a conventional yield priority function and a case where the above two weights are used by using the algorithm of the present invention. The case of calculation is shown.

In the calculation result by the conventional process control computer on the top, yield-priority calculation is performed, so that three slabs according to the designated length are destroyed (cast slab No. 41).
(Maximum length of ~ 43) absorbs cutting waste. On the other hand, in comparison with the conventional example, in the calculation result of the designated length priority by the second GA (gene algorithm), the number of slabs according to the designated length increased from 3/8 to 4/8 by 4 pieces. . However, on the other hand, the waste generated by cutting is 340 m.
It has deteriorated from m to 435 mm. This is an example in which priority is given to obtaining a slab according to the designated length even if the yield is slightly lowered.

On the other hand, in the third example in which the yield is prioritized, the cutting waste is greatly improved from 435 mm to 340 mm in comparison with the case where the designated length is prioritized, and the yield is improved. On the other hand, the number according to the designated length is 5 from 7/8
/ 8 and 2 are worse.

By applying the genetic algorithm in this way, the slab shavings can be minimized, and the operation time is about several minutes to several tens of minutes when the operation is performed by the usual optimization method (branch limiting method, etc.). On the other hand, it can be calculated within 10 seconds.

[0018]

As described above, according to the present invention, the following effects can be obtained. (1) By creating an evaluation function in which factors relating to casting conditions and steel types are weighted and obtaining a slab length that maximizes this evaluation function, it is possible to minimize slab scrap,
Yield is improved. (2) By using a genetic algorithm as an optimization method, an optimum solution can be calculated in an extremely short time, and efficiency can be improved.

[Brief description of drawings]

FIG. 1 is a flow chart showing an embodiment of the method of the present invention.

FIG. 2 is a flowchart showing an outline of a calculation method using a genetic algorithm.

FIG. 3 is an explanatory diagram showing an example of a slab cutting length according to a calculation result obtained by the present invention.

FIG. 4 is an explanatory diagram showing an example of a genetic algorithm according to the present invention.

FIG. 5 is a flowchart showing an example of a conventional slab cutting length calculation method.

FIG. 6 is a flowchart showing an example of a conventional slab cutting length calculation method.

 ─────────────────────────────────────────────────── ─── Continuation of front page (72) Inventor Tomohiro Furuta 1-1 Tobata-cho, Tobata-ku, Kitakyushu City Shin-Nippon Steel Co., Ltd. Yawata Works (72) Inventor Isao Oshita 1-1 Tobata-cho, Tobata-ku, Kitakyushu City Nippon Steel Co., Ltd. Yawata Works (72) Inventor Toshio Murayama 1-1 Tobata-cho, Tobata-ku, Kitakyushu City Inside Nippon Steel Co., Ltd. Yawata Works

Claims (2)

[Claims] 1. When cutting a continuously cast slab,
For the length of the uncut slab, create an evaluation function that weights factors related to the specified length, the number of secondary cuts, cutting debris, the specified length and other casting conditions and steel types, and this evaluation function is the maximum. As an optimization method for obtaining the slab length, casting in continuous casting characterized by using a genetic algorithm that uses the specified length and some cases where the length is not the specified length but is expected to be ordered from now on, as genetic information. One-side cutting control method. 2. The method for controlling slab cutting in continuous casting according to claim 1, wherein the evaluation function f is represented by the following equation. [Equation 1]