CN100465294C - Intelligent control method for bottom-blowing argon in refining furnace - Google Patents
Intelligent control method for bottom-blowing argon in refining furnace Download PDFInfo
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- CN100465294C CN100465294C CNB2006101021335A CN200610102133A CN100465294C CN 100465294 C CN100465294 C CN 100465294C CN B2006101021335 A CNB2006101021335 A CN B2006101021335A CN 200610102133 A CN200610102133 A CN 200610102133A CN 100465294 C CN100465294 C CN 100465294C
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- XKRFYHLGVUSROY-UHFFFAOYSA-N Argon Chemical compound [Ar] XKRFYHLGVUSROY-UHFFFAOYSA-N 0.000 title claims abstract description 84
- 229910052786 argon Inorganic materials 0.000 title claims abstract description 42
- 238000000034 method Methods 0.000 title claims abstract description 35
- 238000007664 blowing Methods 0.000 title claims abstract description 24
- 238000007670 refining Methods 0.000 title claims abstract description 17
- 230000008859 change Effects 0.000 claims abstract description 19
- 230000008569 process Effects 0.000 claims abstract description 11
- 239000002436 steel type Substances 0.000 claims description 8
- 230000003044 adaptive effect Effects 0.000 claims description 7
- 239000007789 gas Substances 0.000 claims description 7
- 229910000831 Steel Inorganic materials 0.000 claims description 5
- 230000007246 mechanism Effects 0.000 claims description 5
- 239000010959 steel Substances 0.000 claims description 5
- 230000033228 biological regulation Effects 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 claims description 3
- 230000001276 controlling effect Effects 0.000 claims description 3
- 230000001105 regulatory effect Effects 0.000 claims description 3
- 238000004519 manufacturing process Methods 0.000 abstract description 3
- 101100129500 Caenorhabditis elegans max-2 gene Proteins 0.000 description 4
- 238000010586 diagram Methods 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 230000000694 effects Effects 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 229910045601 alloy Inorganic materials 0.000 description 2
- 239000000956 alloy Substances 0.000 description 2
- 239000011159 matrix material Substances 0.000 description 2
- 238000009628 steelmaking Methods 0.000 description 2
- VYZAMTAEIAYCRO-UHFFFAOYSA-N Chromium Chemical compound [Cr] VYZAMTAEIAYCRO-UHFFFAOYSA-N 0.000 description 1
- 238000003723 Smelting Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000011449 brick Substances 0.000 description 1
- 229910052804 chromium Inorganic materials 0.000 description 1
- 239000011651 chromium Substances 0.000 description 1
- 238000005262 decarbonization Methods 0.000 description 1
- 230000003009 desulfurizing effect Effects 0.000 description 1
- 238000005265 energy consumption Methods 0.000 description 1
- 238000000265 homogenisation Methods 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 230000014759 maintenance of location Effects 0.000 description 1
- 239000010935 stainless steel Substances 0.000 description 1
- 229910001220 stainless steel Inorganic materials 0.000 description 1
- 238000003756 stirring Methods 0.000 description 1
- 230000001131 transforming effect Effects 0.000 description 1
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P10/00—Technologies related to metal processing
- Y02P10/25—Process efficiency
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Abstract
The invention relates to an intelligent control method of blowing argon at the bottom of the refining furnace, basing on the vague self-adaptation algorithm containing grading structure. The whole control system is divided into 3 level: (1) basal vague controlling level adopting fuzzy logic control modes to meets the real time requirement of the system, (2) self-adaptation adjusting level adopting self-adaptive control to adapts the time change conditions of the system to adjust the parameter of the fuzzy controller, (3) process state judge level. Process state judge is adopted as auxiliary input to improve the robustness of the controlling system. Relevant parameter of the fuzzy controller is adopted according to the state of the system. The invention improves the control precision of the control system, thus the production efficiency and steeling quality is improved. Besides the control system is simple and costs low.
Description
Technical Field
The invention relates to an intelligent control method for blowing argon at the bottom of a refining furnace, in particular to a control method for blowing argon at the bottom of a refining furnace based on a fuzzy self-adaptive control algorithm with a hierarchical structure.
Background
The bottom argon blowing steelmaking technology of the refining furnace has the advantages of low cost, convenient operation and good stirring effect, and thus, a series of extremely beneficial metallurgical effects are produced. It can obviously shorten smelting time, reduce energy consumption, raise desulfurizing and dephosphorizing capacity and promote alloy homogenization. When the stainless steel is smelted, the decarbonization and chromium retention can be promoted, the alloy yield is increased, and the labor intensity of workers can be greatly reduced.
In 1998, Bao steel introduces a bottom-blown argon control technology from Japan and is built and put into operation, thereby obtaining better effect. At present, most domestic refining technologies adopt a ladle bottom argon blowing method, but most domestic manufacturers basically adopt a manual direct operation control method because imported equipment is expensive, the maintenance cost is high, and the requirement on operators is high.
Disclosure of Invention
The invention aims to solve the technical problem of providing the intelligent control method for blowing argon at the bottom of the refining furnace, which has simple system structure, low cost and high control precision.
The technical scheme adopted by the invention for solving the technical problems is as follows:
the technical core of the invention is to adopt a fuzzy self-adaptive control method with a hierarchical structure, wherein the hierarchical structure divides the whole control system into three-level control structures: (1) basic fuzzy control stage. In order to meet the real-time control requirement of the system, a fuzzy logic control mode is adopted in the basic fuzzy control stage. (2) And (4) self-adaptive adjustment of the stage. In order to adapt to the time-varying condition of the parameters of the controlled system, a self-adaptive control mode is adopted, and the parameters of the fuzzy controller are adjusted on line at regular time. (3) The process state decision level. In order to overcome the influence of process state change (or different actual working conditions), improve the robust performance of the control system, judge the process state as the auxiliary input quantity, and adopt the corresponding fuzzy controller parameter set according to the process state of the system.
The method comprises the following specific steps:
firstly, an input step:
the following parameters were entered into the industrial computer: the ladle number and the steel type number of the refining furnace, argon blowing flow set values corresponding to the ladle number and the steel type number at each stage, a fuzzy rule base adopted by selection and the range of a fuzzy variable discourse domain;
II, data acquisition:
real-time values of the following sensors are collected by the industrial computer in real time: the device comprises a flow sensor for measuring the flow of argon gas, a pressure sensor for measuring the pressure of the argon gas and a temperature sensor for measuring the ambient temperature of an argon supply branch;
thirdly, calculating:
the following calculation steps are accomplished by an industrial computer equipped with a fuzzy adaptive algorithm with a hierarchical structure:
(1) basic fuzzy control stage:
a. calculating the error e and the error change rate delta e of the system;
b. the error e and the error change rate delta e of the system are transformed into respective discourse domain ranges through scales;
c. carrying out fuzzy processing on the input quantity converted into the discourse domain range to change the original accurate input quantity into a fuzzy quantity;
d. calculating a fuzzy value of the control quantity u through fuzzy reasoning;
e. determination of the control amount u:
firstly, the value z of the controlled variable u in the theory domain is obtained by a weighted average method0(ii) a Then z is transformed by scaling0Becomes the actual control amount uoutput;
(2) self-adaptive regulation stage:
when the output of the control quantity u does not meet the control requirement, adopting a membership degree output value adjusting method to carry out self-adaptive adjustment, then entering the item d in the step (1), and finally correcting the output value of the control quantity u;
(3) process state determination stage:
when the system working condition is changed greatly, such as the steel type and the steel ladle change, the change is judged by the industrial computer, and a fuzzy control rule base is automatically selected to adapt to the change;
fourthly, executing the steps:
the control quantity u is used for controlling argon blowing through an actuating mechanism.
The actuating mechanism is a regulating valve arranged on a normal branch of the argon supply system.
The flow sensor is arranged on the pipeline of the normal branch.
The pressure sensor is arranged on the pipeline of the normal branch.
The temperature sensor is arranged on the pipe wall of the pipeline of the normal branch or around the pipeline of the normal branch.
The invention has the advantages that the fuzzy self-adaptive control method with the hierarchical structure is adopted, so the control precision of the control system is greatly improved, the production efficiency and the steelmaking quality are improved, in addition, the control system has simple structure and lower cost.
Drawings
FIG. 1 is a schematic diagram of the system of the present invention.
Fig. 2 is a schematic diagram of a fuzzy adaptive control with a hierarchical structure.
FIG. 3 is a software flow diagram of the present invention.
Detailed Description
The system structure diagram of the embodiment is shown in fig. 1, and the system is composed of an argon tank 16, a pressure buffer tank 14, a normal branch, an accident branch, three sensors, a flow totalizer 12, an industrial computer 10, a regulating valve 7, a pressure reducing valve 1, a check valve 8, a safety valve 15, an electromagnetic valve 2 and the like (detailed in fig. 1); the pressure buffer tank 14, the flow sensor 3 and the pressure sensor 4 are arranged on the pipeline of the normal branch, and the temperature sensor 5 is arranged on the pipe wall of the pipeline of the normal branch or around the pipeline of the normal branch. An adjusting valve 7 (actuator) and the solenoid valve 2 are also installed on the normal branch, and the opening degree of the adjusting valve 7 is controlled by the output (control amount u) of the industrial computer 10.
The outputs of the flow sensor 3, the pressure sensor 4 and the temperature sensor 5 are respectively connected with the input end of the industrial computer 10 through a flow totalizer 12. The flow totalizer 12 and the industrial computer 10 are installed in the control room 11.
The system can realize two functions of manual control and computer automatic control. On one hand, when the bottom argon blowing system works normally, controlled argon is blown into the refining furnace through the normal branch, so that the argon blowing process is realized; when argon blowing work is started, higher pressure can be provided to blow the blocked air brick open so as to ensure the normal start of the argon blowing work. On the other hand, in order to increase the reliability of the system, the control system can be switched to the accident branch in time for manual operation after the control system fails in the argon blowing process, and the normal operation of production is ensured.
The flow totalizer 12 adopts a vortex-connected flow meter; the check valve 8 is a device for preventing high-pressure gas of an accident branch from entering a normal branch and damaging the normal branch.
In fig. 1 and 2, 6, 9 and 13 are valves, 15 is a safety valve, 16 is an argon tank, r (k) is a set value, e (k) is a system error, u (k) is a control quantity, and y (k) is an actual argon flow value.
The present embodiment includes the following four steps:
firstly, an input step is carried out,
the following parameters were entered into the industrial computer: the ladle number and the steel type number of the refining furnace, argon blowing flow set values corresponding to the ladle number and the steel type number at each stage, an adopted fuzzy rule base and the range of a fuzzy variable universe are selected;
II, data acquisition:
real-time values of the following sensors are collected by the industrial computer in real time: the device comprises a flow sensor for measuring the flow of argon gas, a pressure sensor for measuring the pressure of the argon gas and a temperature sensor for measuring the ambient temperature of an argon supply branch;
thirdly, calculating:
the following calculation steps are accomplished by an industrial computer equipped with a fuzzy adaptive algorithm with a hierarchical structure:
(1) basic fuzzy control stage:
a. calculating the error e and the error change rate delta e of the system:
e＝r-y
△e＝de/dt＝e(i)-e(i-1)/T
wherein T is the control period of the system, r is the argon flow set value, y is the actual argon flow value, e (i) is the error of the ith moment, and e (i-1) is the error of the ith-1 moment.
b. And (3) converting the error e and the error change rate delta e of the system into respective discourse domain ranges through scales, wherein the general formula is as follows:
wherein k islCalled scale factor
[xmin，xmax]Is the domain of discourse required;
c. the input quantity converted into the discourse domain range is subjected to fuzzy processing, so that the original accurate input quantity is changed into fuzzy quantity, and the following bell-shaped membership function is adopted:
wherein x0Is the central value, σ, of the membership function2Is the variance;
d. calculating a fuzzy value of the control quantity u through fuzzy reasoning, wherein the fuzzy reasoning adopts the following formula:
wherein,
for values of language variables representing error e
For fuzzy implication relationships obtained from a control rule base
B' is a linguistic variable value representing the controlled variable u;
e. determination of the control amount u:
obtaining the value z of the control quantity u in the theory domain by a weighted average method0：
By transforming z by scale0Becomes the actual control amount uoutput:
wherein k isOCalled the output scale factor
[zmin，zmax]Is z0Scope of discourse of
[umin，umax]Is the variation range of the output quantity;
(2) self-adaptive regulation stage:
when the output of the control quantity u does not meet the control requirement, adopting a membership degree output value adjusting method to carry out self-adaptive adjustment, then entering the item d in the step (1), and finally correcting the output value of the control quantity u;
the adaptive adjustment of the membership output value adjusting method is adopted, and belongs to direct fuzzy adaptive control:
u＝uc(x|θ)+uD
wherein u isc(x | θ) is
WhereinFor state x in the l ruleiFor fuzzy subsets
Degree of membership, n is the number of states, M is the number of rules, ylThe output value corresponding to the conclusion membership degree of 1 in the first rule; will ylAs tunable parameters, the above equation can be written as:
wherein θ ═ y1，…，yM)TIs a parameter vector, xi (x) ═ xi (xi)1(x)，…，ξM(x))TIs the regression vector, and xi1(x) Referred to as fuzzy basis functions; u. ofD＝kdsgn(eTPbc) For D control, kd≥0，bc＝[0，0，…，b]TIf e isTPbc>0, then uD＝kdIf e isTPbc<0, then uD＝-kd；
The adaptive law for the parameter vector θ is:
wherein P isr[*]Is defined as:
Pnis the last column of P, | theta | < Mθ<∞，MθIs a finite upper bound of the θ vector;
p is a positive definite matrix and satisfies the Lyapunov equation ΛTP + Λ ═ Q, where Q is an arbitrary positive definite matrix of n × n;
(3) process state determination stage:
when the system working condition is changed greatly, such as the steel type and the steel ladle change, the change is judged by the industrial computer, and a fuzzy control rule base is automatically selected to adapt to the change;
fourthly, executing the steps:
the control quantity u is used for controlling argon blowing through an actuating mechanism.
Claims (5)
1. The intelligent control method for blowing argon at the bottom of the refining furnace is characterized by comprising the following steps:
firstly, an input step:
the following parameters were entered into the industrial computer: the method comprises the following steps of (1) selecting a steel ladle number, a steel type number, argon blowing flow set values of all stages corresponding to the steel ladle number and the steel type number of a refining furnace, and selecting a fuzzy rule base and a fuzzy variable domain range;
II, data acquisition:
real-time values of the following sensors are collected by the industrial computer in real time: the device comprises a flow sensor for measuring the flow of argon gas, a pressure sensor for measuring the pressure of the argon gas and a temperature sensor for measuring the ambient temperature of an argon supply branch;
thirdly, calculating:
the following calculation steps are accomplished by an industrial computer equipped with a fuzzy adaptive algorithm with a hierarchical structure:
(1) basic fuzzy control stage:
a. calculating the error e and the error change rate delta e of the system;
b. the error e and the error change rate delta e of the system are converted into respective discourse domain ranges through scales;
c. carrying out fuzzy processing on the input quantity converted into the discourse domain range to change the original accurate input quantity into a fuzzy quantity;
d. calculating a fuzzy value of the control quantity u through fuzzy reasoning;
e. determination of the control amount u:
firstly, the value z of the controlled variable u in the theory domain is obtained by a weighted average method0(ii) a Then z is transformed by scaling0Becomes the actual control amount uoutput;
(2) self-adaptive regulation stage:
when the output of the control quantity u does not meet the control requirement, adopting a membership degree output value adjusting method to carry out self-adaptive adjustment, then entering the item d in the step (1), and finally correcting the output value of the control quantity u;
(3) process state determination stage:
when the system working condition is changed greatly, the industrial computer judges the change and automatically selects the fuzzy control rule base to adapt to the change;
fourthly, executing the steps:
the control quantity u is used for controlling argon blowing through an actuating mechanism.
2. The intelligent control method of argon blowing at the bottom of a refining furnace according to claim 1, characterized in that the actuating mechanism is a regulating valve (7) installed on a normal branch of an argon supply system.
3. A refining furnace bottom argon blowing intelligent control method according to claim 2, characterized in that the flow sensor (3) is installed on the pipeline of the normal branch.
4. An intelligent control method for blowing argon at the bottom of a refining furnace according to claim 3, characterized in that the pressure sensor (4) is installed on the pipeline of the normal branch.
5. A refining furnace bottom argon blowing intelligent control method according to claim 4, characterized in that the temperature sensor (5) is installed on the pipe wall of the normal branch pipe or around the normal branch pipe.
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Families Citing this family (9)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN104249140B (en) * | 2013-06-26 | 2016-08-24 | 宝山钢铁股份有限公司 | A kind of continuous cast mold Argon integrated system |
| CN104073588B (en) * | 2014-07-15 | 2016-03-30 | 中冶南方工程技术有限公司 | A kind of converter steel ladle bottom argon blowing autocontrol method |
| CN104133451A (en) * | 2014-07-31 | 2014-11-05 | 武钢集团昆明钢铁股份有限公司 | Management system and method for steel-making argon blowing ladle |
| CN104091250B (en) * | 2014-07-31 | 2017-07-18 | 武钢集团昆明钢铁股份有限公司 | One kind steel-making refining ladle management system and method |
| CN106148727B (en) * | 2016-08-31 | 2018-10-02 | 浙江大学宁波理工学院 | Compress control method in a kind of refining furnace |
| CN108690901B (en) * | 2017-04-04 | 2021-01-08 | 上海梅山钢铁股份有限公司 | Dynamic automatic control device and control method for ladle bottom argon blowing |
| CN110387454A (en) * | 2018-04-20 | 2019-10-29 | 沈阳人和机械制造有限公司 | The control system and method for steel ladle bottom argon blowing |
| CN115125366B (en) * | 2021-03-25 | 2024-05-10 | 上海梅山钢铁股份有限公司 | Intelligent production control method for argon blowing station |
| CN114646020B (en) * | 2022-03-31 | 2024-05-31 | 华能营口热电有限责任公司 | Power grid steam temperature and pressure reducing device, thermoelectric peak regulating system and pressure reducing and regulating method |
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Application publication date: 20070523 Assignee: Shijiazhuang Jiaxin Electric Co., Ltd. Assignor: Hebei University of Science and Technology Contract record no.: 2013130000049 Denomination of invention: Intelligent control method for bottom-blowing argon in refining furnace Granted publication date: 20090304 License type: Exclusive License Record date: 20130627 |
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