CN111581822A - Blast furnace burden distribution numerical simulation method based on intelligent algorithm - Google Patents
Blast furnace burden distribution numerical simulation method based on intelligent algorithm Download PDFInfo
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- 230000008571 general function Effects 0.000 abstract 1
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- G06F30/20—Design optimisation, verification or simulation
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- C—CHEMISTRY; METALLURGY
- C21—METALLURGY OF IRON
- C21B—MANUFACTURE OF IRON OR STEEL
- C21B5/00—Making pig-iron in the blast furnace
- C21B5/006—Automatically controlling the process
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- C—CHEMISTRY; METALLURGY
- C21—METALLURGY OF IRON
- C21B—MANUFACTURE OF IRON OR STEEL
- C21B5/00—Making pig-iron in the blast furnace
- C21B5/008—Composition or distribution of the charge
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- C—CHEMISTRY; METALLURGY
- C21—METALLURGY OF IRON
- C21B—MANUFACTURE OF IRON OR STEEL
- C21B2300/00—Process aspects
- C21B2300/04—Modeling of the process, e.g. for control purposes; CII
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Abstract
The invention discloses a numerical simulation method of blast furnace burden distribution based on an intelligent algorithm, which comprises the following steps of ①, reading furnace body parameters, and dividing a burden surface curve into a first straight line y between a furnace body central line and a furnace wall in sequence1＝kx1+b1Arc-shaped section (x)2‑x0/a)2+(y2‑y0/b)21 and a second straight line segment y3＝‑kx3+b3② selecting historical furnace charge parameters, reading the historical charge level curves at various time points, fitting the curves, ③, reselecting the furnace charge parameters and determining C1、C2、C3、C4、C5④, outputting a charge level curve, and obtaining the charge level curve by simplified fitting of the charge level curveIs used as a general function of (1). The method comprises the steps of obtaining a time-varying relation of a charge level curve by using a measured historical charge level curve, applying the function-varying relation to the time-varying charge level curve to be measured, determining specific parameters of the time-varying charge level curve to be measured by an undetermined coefficient method, outputting the time-varying relation of the charge level curve to be measured, fully utilizing existing data and greatly reducing the test quantity.
Description
[ technical field ] A method for producing a semiconductor device
The invention relates to a numerical simulation method of blast furnace burden distribution based on an intelligent algorithm, and belongs to the field of metallurgical control.
[ background of the invention ]
Although the change of a burden surface curve along with time can be measured in the process of blast furnace burden distribution, once the burden parameters change, the burden parameters need to be measured again, the measurement workload is very large, time and labor are consumed, and a very large error exists, so that the actual burden distribution process design is very complicated.
[ summary of the invention ]
The invention aims to overcome the defects of the prior art and provide a numerical simulation method for blast furnace burden distribution based on an intelligent algorithm, which can quickly predict burden surface curves.
The technical scheme adopted by the invention is as follows:
a numerical simulation method of blast furnace burden distribution based on an intelligent algorithm comprises the following steps:
①, reading furnace body parameters, and dividing the charge level curve into a first straight line y between the furnace body central line and the furnace wall1＝kx1+b1Arc-shaped section (x)2-x0/a)2+(y2-y0/b)21 and a second straight line segment y3＝-kx3+b3；
②, selecting the historical furnace charge parameters, reading the historical charge level curves at each time point, and respectively obtaining the y-th charge level curve through fitting the curves1＝k(t)x1+b1(t)、(x2-x0(t)/a(t))2+(y2-y0(t)/b(t))21 and y3＝-k(t)x3+b3(t)；
③ selecting the furnace charge parameters again, the charge level curve becomes y after the furnace charge parameters are changed1＝C1k(t)x1+C2b1(t)、(x2-C3x0(t)/C6a(t))2+(y2-C4y0(t)/C7b(t))21 and y3＝-C1k(t)x3+C5b3(t), where t is t1And t2Separately measuring the charge level curve to determine C1、C2、C3、C4、C5；
Step ④, according to y1＝C1k(t)x1+C2b1(t)、(x2-C3x0(t)/C6a(t))2+(y2-C4y0(t)/C7b(t))21 and y3＝-C1k(t)x3+C5b3(t) outputting a time-varying image of the charge level curve.
The invention has the beneficial effects that:
and obtaining a universal function of the charge level curve by simplified fitting of the charge level curve. The method comprises the steps of obtaining a time-varying relation of a charge level curve by utilizing a measured historical charge level curve, applying the time-varying relation of the function to the time-varying charge level curve to be measured, determining specific parameters of the time-varying charge level curve to be measured by an undetermined coefficient method, outputting the time-varying relation of the charge level curve to be measured, fully utilizing existing data, greatly reducing the test quantity, and having strong guiding significance on the distribution of the blast furnace.
In the invention, in the same charge level curve, the first straight line section and the second straight line section are both tangent to the arc section.
The furnace body parameters of the invention comprise chute inclination angle, chute length and chute rotating speed, and the chute inclination angle, the chute length and the chute rotating speed are fixed values.
In the same charge level curve of the invention, x1Has a value length of x3More than twice the length of the value.
Under the condition that the furnace charge parameters are fixed and unchanged, x in a charge level curve is increased along with the increase of t2The value range of (a) is gradually reduced.
Other features and advantages of the present invention will be disclosed in more detail in the following detailed description of the invention and the accompanying drawings.
[ description of the drawings ]
The invention is further described below with reference to the accompanying drawings:
fig. 1 is a flowchart of a numerical simulation method for blast furnace burden distribution based on an intelligent algorithm according to an embodiment of the present invention.
[ detailed description ] embodiments
The technical solutions of the embodiments of the present invention are explained and illustrated below with reference to the drawings of the embodiments of the present invention, but the following embodiments are only preferred embodiments of the present invention, and not all embodiments. Based on the embodiments in the implementation, other embodiments obtained by those skilled in the art without any creative effort belong to the protection scope of the present invention.
In the following description, the appearances of the indicating orientation or positional relationship such as the terms "inner", "outer", "upper", "lower", "left", "right", etc. are only for convenience in describing the embodiments and for simplicity in description, and do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and are not to be construed as limiting the present invention.
Example (b):
referring to fig. 1, the present embodiment provides a numerical simulation method for blast furnace burden distribution based on an intelligent algorithm, including the following steps:
①, reading furnace body parameters, and dividing the charge level curve into a first straight line y between the furnace body central line and the furnace wall1＝kx1+b1Arc-shaped section (x)2-x0/a)2+(y2-y0/b)21 and a second straight line segment y3＝-kx3+b3；
In the method, the curve of the actual arc-shaped section after material throwing is fitted into an elliptic line in the embodiment because the arc-shaped section is regarded as a parabola in the existing numerical simulation method, but the assumption is that the interaction between the material throwing and the charge level is not considered;
step two: randomly selecting a group of furnace charge parameters from the historical furnace charge parameters, reading historical charge level curves of each time point under the condition of the group of furnace charge parameters, wherein furnace body parameters required by all the read historical charge level curves are consistent with or similar to the furnace body parameters in the first step;
the corresponding first straight line fitting function is y1＝k(t)x1+b1(t) the arc segment fitting equation is (x)2-x0(t)/a(t))2+(y2-y0(t)/b(t))21, the second straight line segment fitting function is y3＝-k(t)x3+b3(t); fitting the charge level curves at different time points under the fixed furnace body parameters and the furnace charge parameters by combining the characteristics of the continuity of the charge level curves to obtain k (t), b1(t)、x0(t)、a(t)、y0(t), b (t) and b3(t) functional equations;
③, maintaining the parameters of furnace body unchanged, and reselecting the parameters of furnace charge, k (t), b1(t)、x0(t)、a(t)、y0(t), b (t) and b3(t) can still be applied to the change of the charge level curve with time after the charge parameters are changed, and the fitting function of the first straight line segment is y in consideration of the change of the charge parameters1＝C1k(t)x1+C2b1(t) the fitting equation for the arc segment is (x)2-C3x0(t)/C6a(t))2+(y2-C4y0(t)/C7b(t))2The fitting function for the second straight line segment is y ═ 13＝-C1k(t)x3+C5b3(t) after the change of the charge material parameters, respectively at t ═ t1And t ═ t2Time-tested charge level curve due to k (t)1)、b1(t1)、x0(t1)、a(t1)、y0(t1)、b(t1) And b3(t1) It is known that when t is t ═ t1C after the charge level curve is fitted1、C2、C3、C4、C5、C6、C7It is also possible to make a determination that k (t) is used to ensure accuracy, taking into account test errors2)、b1(t2)、x0(t2)、a(t2)、y0(t2)、b(t2) And b3(t2) Can also be determined by using t as t2Fitting the charge level curve obtained by time measurement to determine t as t2C of (1)1、C2、C3、C4、C5、C6、C7Specific numerical values are obtained by changing t to t1C of (1)1、C2、C3、C4、C5、C6、C7And t ═ t2C of (1)1、C2、C3、C4、C5、C6、C7Taking an average to determine the final C1、C2、C3、C4、C5、C6、C7A numerical value;
step ④, according to y1＝C1k(t)x1+C2b1(t)、(x2-C3x0(t)/C6a(t))2+(y2-C4y0(t)/C7b(t))21 and y3＝-C1k(t)x3+C5b3(t) outputting a time-varying image of the charge level curve.
The whole numerical simulation method uses the existing charge level curve group data for conjecturing and evolving the time-varying relation of the charge level curve to be tested. The change of the charge level curve at the next time can be predicted only by testing the charge level curve to be tested at the specific time for 1-2 times according to the change relation of the charge level curve to be tested with time, and the test program is greatly saved without real-time test.
In the second step and the third step, in the same charge level curve, the first straight line section and the second straight line section are tangent to the arc section, the result most conforms to the existing test result, and meanwhile, under the constraint condition, the widths of the first straight line section, the arc section and the second straight line section in the x-axis direction can be adjusted, so that the actual charge level curve is more conformed.
Based on the above-mentioned constraint condition, the method,under the condition that the furnace body parameters and the furnace burden parameters are fixed and unchanged, x in the charge level curve is increased along with the increase of t2Gradually decreases, i.e. the width of the arc segment gradually decreases with time.
Along with the increase of time, the width of the first straight line section in the charge level curve is gradually reduced, the width of the second straight line section is gradually increased, but the width of the arc section is gradually reduced, when t is increased to a certain value, the width of the arc section is approximately 0, and the fitting distortion is caused, so that the upper limit value of t needs to be ensured in the same charge level curve, x and x are in the same charge level curve1The length of the value of (a) needs to be x3The length is more than twice of the value to ensure the fitting accuracy.
Furnace body parameter includes chute inclination, chute length and chute rotational speed in this embodiment, and chute inclination, chute length and chute rotational speed are the definite value to guarantee that the historical charge level curve group data that have surveyed can be used for simulating the charge level curve relation of change with time that awaits measuring.
While the invention has been described with reference to specific embodiments thereof, it will be understood by those skilled in the art that the invention is not limited thereto, and may be embodied in many different forms without departing from the spirit and scope of the invention as set forth in the following claims. Any modification which does not depart from the functional and structural principles of the present invention is intended to be included within the scope of the claims.
Claims (5)
1. A numerical simulation method of blast furnace burden distribution based on an intelligent algorithm is characterized by comprising the following steps:
①, reading furnace body parameters, and dividing the charge level curve into a first straight line y between the furnace body central line and the furnace wall1＝kx1+b1Arc-shaped section (x)2-x0/a)2+(y2-y0/b)21 and a second straight line segment y3＝-kx3+b3；
②, selecting the historical furnace charge parameters, reading the historical charge level curves at each time point, and respectively obtaining the y-th charge level curve through fitting the curves1＝k(t)x1+b1(t)、(x2-x0(t)/a(t))2+(y2-y0(t)/b(t))21 and y3＝-k(t)x3+b3(t)；
③ selecting the furnace charge parameters again, the charge level curve becomes y after the furnace charge parameters are changed1＝C1k(t)x1+C2b1(t)、(x2-C3x0(t)/C6a(t))2+(y2-C4y0(t)/C7b(t))21 and y3＝-C1k(t)x3+C5b3(t), where t is t1And t2Separately measuring the charge level curve to determine C1、C2、C3、C4、C5；
Step ④, according to y1＝C1k(t)x1+C2b1(t)、(x2-C3x0(t)/C6a(t))2+(y2-C4y0(t)/C7b(t))21 and y3＝-C1k(t)x3+C5b3(t) outputting a time-varying image of the charge level curve.
2. The intelligent algorithm-based numerical simulation method for blast furnace burden distribution as defined in claim 1, wherein the first straight line segment and the second straight line segment are tangent to the arc segment in the same burden surface curve.
3. The intelligent algorithm-based numerical simulation method for blast furnace burden distribution according to claim 1, wherein the furnace body parameters comprise a chute inclination angle, a chute length and a chute rotation speed, and the chute inclination angle, the chute length and the chute rotation speed are constant values.
4. The numerical simulation method for blast furnace burden distribution based on intelligent algorithm of claim 3, wherein x is in the same burden surface curve1Has a value length of x3More than twice the length of the value.
5. The intelligent algorithm-based numerical simulation method for blast furnace burden distribution as claimed in claim 4, wherein x in the burden surface curve increases with t under the condition that the burden material parameters are fixed and unchanged2The value range of (a) is gradually reduced.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102629286A (en) * | 2012-02-24 | 2012-08-08 | 北京首钢自动化信息技术有限公司 | Blast furnace burden distribution value simulation method based on intelligent algorithm |
| CN107656900A (en) * | 2017-09-01 | 2018-02-02 | 武汉钢铁有限公司 | A kind of method at different stockline compensation angles during determination blast furnace material distribution |
| US20200173457A1 (en) * | 2017-04-17 | 2020-06-04 | Ihi Corporation | Method of designing blade of axial flow fluid machine and blade |
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- 2020-05-08 CN CN202010383692.8A patent/CN111581822A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102629286A (en) * | 2012-02-24 | 2012-08-08 | 北京首钢自动化信息技术有限公司 | Blast furnace burden distribution value simulation method based on intelligent algorithm |
| US20200173457A1 (en) * | 2017-04-17 | 2020-06-04 | Ihi Corporation | Method of designing blade of axial flow fluid machine and blade |
| CN107656900A (en) * | 2017-09-01 | 2018-02-02 | 武汉钢铁有限公司 | A kind of method at different stockline compensation angles during determination blast furnace material distribution |
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Application publication date: 20200825 |