CN108265157A - Intelligent arc furnace steelmaking system - Google Patents
Intelligent arc furnace steelmaking system Download PDFInfo
- Publication number
- CN108265157A CN108265157A CN201810075943.9A CN201810075943A CN108265157A CN 108265157 A CN108265157 A CN 108265157A CN 201810075943 A CN201810075943 A CN 201810075943A CN 108265157 A CN108265157 A CN 108265157A
- Authority
- CN
- China
- Prior art keywords
- intelligent
- electrode
- control system
- electric arc
- plc
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- C—CHEMISTRY; METALLURGY
- C21—METALLURGY OF IRON
- C21C—PROCESSING OF PIG-IRON, e.g. REFINING, MANUFACTURE OF WROUGHT-IRON OR STEEL; TREATMENT IN MOLTEN STATE OF FERROUS ALLOYS
- C21C5/00—Manufacture of carbon-steel, e.g. plain mild steel, medium carbon steel or cast steel or stainless steel
- C21C5/52—Manufacture of steel in electric furnaces
-
- C—CHEMISTRY; METALLURGY
- C21—METALLURGY OF IRON
- C21C—PROCESSING OF PIG-IRON, e.g. REFINING, MANUFACTURE OF WROUGHT-IRON OR STEEL; TREATMENT IN MOLTEN STATE OF FERROUS ALLOYS
- C21C5/00—Manufacture of carbon-steel, e.g. plain mild steel, medium carbon steel or cast steel or stainless steel
- C21C5/52—Manufacture of steel in electric furnaces
- C21C2005/5288—Measuring or sampling devices
-
- C—CHEMISTRY; METALLURGY
- C21—METALLURGY OF IRON
- C21C—PROCESSING OF PIG-IRON, e.g. REFINING, MANUFACTURE OF WROUGHT-IRON OR STEEL; TREATMENT IN MOLTEN STATE OF FERROUS ALLOYS
- C21C2300/00—Process aspects
- C21C2300/06—Modeling of the process, e.g. for control purposes; CII
-
- 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
- Y02P10/20—Recycling
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Chemical & Material Sciences (AREA)
- Manufacturing & Machinery (AREA)
- Materials Engineering (AREA)
- Metallurgy (AREA)
- Organic Chemistry (AREA)
- Waste-Gas Treatment And Other Accessory Devices For Furnaces (AREA)
- Vertical, Hearth, Or Arc Furnaces (AREA)
- Furnace Details (AREA)
Abstract
The present invention relates to intelligent arc furnace steelmaking systems, it is made of furnace control system, oxygen rifle control system, dedusting control system and intelligent electrode control system, using the SIMATIC STEP7 of Siemens Company as exploitation software, the PLC software control procedures that electric arc furnaces intelligent electrode is adjusted are designed, build intelligent electrode adjuster；The intelligent electrode adjuster includes conventional electrode controller, the neural network electric arc furnaces prediction model of Fast Convergent and predictive compensation program, make electric arc furnaces intelligence steel-making precisely controllable at this stage by the combination of artificial intelligence and automated system, reduce energy consumption, steel-making amount is promoted to greatest extent, is greatly increased the production efficiency.
Description
Technical field
The invention belongs to electric furnace steel making field, more particularly to intelligent arc furnace steelmaking system.
Background technology
Steel making operation technology experienced for four generations, and the first generation is the steel-making behaviour that few detection means relies primarily on operator's experience
Make method, the second generation is by being equipped with more detection instrument and automatic control system with the operating method of artificial judgment
Three generations is to possess more detection instrument and automatic control system by what is introduced, and equipped with mathematical model and direct surveillance and
The method of certain judgements, forth generation are the operating methods of artificial intelligence, finally or operator to be replaced to judge are automatically achieved ripe
The operation for practicing operator is horizontal, and makes steelmaking process unmanned or only Control Centre is equipped with operator on duty.
Modern steelmaking process automation and computer application mainly carry out basic automatization, process automation and management
Automation is all PLC, DCS or the scene used using microcomputer as core including detection instrument and control, power transmission system control
Bus apparatus is performed, and connects network, formation EIC (i.e. Electric Drive, instrument and control, computer control and management, I
State's steel circle is referred to as three electric systems) system and Multipole effect machine automated system.In order to obtained Control platform, with meet
The complex process of steel-making, further reduces energy consumption, reduces cost and production high value added product, automation are not used only
Conventional control (automatically controlling for pid algorithm), and using advanced control method, Control platform is made to reach higher level and obtain
Higher economic benefit.It is also greatly developed in terms of detection technique and instrument, not merely with new detection method, telemetering skill
Art, digitizing technique and artificial intelligence technology are handled, and using soft-measuring technique, the letter that steelmaking process is made to obtain in the past
Breath is addressed or solution to a certain degree, so as to greatly facilitate production normalization and create prerequisite for Dynamic matrix control.
It also reaches its maturity in terms of man-machine interface, picture are shown, such as visualization technique.In short, it is formed with state-of-the-art technology efficient, excellent
Matter, the automated system of low cost are the development trends of steel-making automation.
Dynamics is eliminated as country increases steel-making ironmaking backward production facilities and to reduce exploitation of mineral resources and improving society
The ratio for improving electric steel is advocated in the utilization of Resource recovery, constantly has the steel mill new on the basis of eliminating the backward production facilities in recent years
Electric furnace arrangement for producing steel equipment is built, the cost is relatively high since process for making causes electric-arc furnace steelmaking, for over ten years arc furnace equipment number
Amount is constantly reduced, so the automated control technology of electric-arc furnace steelmaking coordinative composition of equipments lies substantially in dead state.But with electricity
The required primary raw material of stove arc process for making --- scrap resources increase, price reduction, hold the cost of electric-arc furnace steelmaking
It is continuous to decline.It may predict and have the production of electric-arc furnace steelmaking equipment investment in the future, and mating more advanced intelligent arc furnace steel-making system
System becomes urgent demand.
Invention content
Electric-arc furnace steelmaking has a highly developed process for making, and with the fast development of computer technology in recent years,
Steel-making course of the electric arc furnace also have highly developed control algolithm (as expected from being calculated in smelting process with technological parameter molten steel into
Part, liquid steel temperature produce additions of auxiliary materials such as the required lime of qualified molten steel, alloy etc.).But since electric-arc furnace steelmaking is set
Standby smelting process high temperature, dusty, strong noise, the adverse circumstances of high vibration cause the Partial key detection instrument at scene not
Energy normal use possesses complete detection instrument and automated system including what is introduced a few years ago, since part detection instrument cannot
Expected effect is not achieved in normal use.
Main control means are exactly experienced worker in the first generation, second generation operating technology, due to steelmaking process work
The complexity of skill operating process, experienced experienced operator's culture generally require to put into a large amount of energy and time, and different
People for the difference of the controls such as dynamic electric arc BF's inner state, equipment operation, process data in real time in steelmaking process, can also make
Into the final duration of heat, smelt consumption, steel quality difference, this point puts into several classes operation difference teams and groups for 24 hours from steelshop
Yield, consumption, the level of quality it is uneven with regard to that can embody.And the advantage of manual operation maximum is really skilled and has
The experienced operator of experience can constantly correct oneself operation according to the difference of result, be allowed to more they tend to
The variation of situation adjusts the parameters such as power supply, oxygen supply, spray carbon dust in time, reaches the target that electric-arc furnace steelmaking is more efficient, more energy efficient.But
The disadvantage of manual operation maximum is that people is unable to the operation skill that machine can be optimized repeatedly every time like that due to various reasons
Ingeniously.
Based on above 2 points, that is, detect the unreliability of instrument, it is manually-operated uncertain and cannot repeatability, exploitation
The urgent meaning of reality is provided with advanced, reliable intelligent arc furnace steelmaking system.The solution of the present invention is as follows：
The present invention intelligent arc furnace steelmaking system, by furnace control system, oxygen rifle control system, dedusting control system and
Intelligent electrode control system form, which is characterized in that the intelligent electrode control system include host computer and slave computer, it is described on
Position machine uses the HMI system of form control centre Wincc, realizes the operational process monitoring of electric arc furnaces intelligent electrode control system,
Arc current, voltage waveform and its data show that the setting of three-phase current and voltage emulation data, production smelting process data are protected
Deposit filing and with the functions such as the communication of slave computer；The slave computer uses the PLC of Siemens S7-1500 series, described upper
Machine is connected by communicating network interface card with the communication module of slave computer；The PLC of the Siemens S7-1500 series includes communication mould
Block, analogue collection module, current transducer, Signal-regulated kinase and signal acquisition module.Using Siemens Company
The PLC software control procedures that SIMATICSTEP7 is adjusted as exploitation software, design electric arc furnaces intelligent electrode, build intelligent electrode
Adjuster；The intelligent electrode adjuster includes conventional electrode controller, the neural network electric arc furnaces of Fast Convergent estimates mould
Type and predictive compensation program；The intelligent electrode conditioner operation step is as follows：
1), the parameter using data collecting system acquisition electric arc furnaces during smelting, using these parameters in offline mode
The lower neural network predicting model for carrying out Fast Convergent is established；
2), the neural network predicting model of the Fast Convergent of foundation is put into online, and constantly carries out online adaptive tune
Whole, making prediction model, predictive compensation program utilizes estimation results to practical electric arc furnaces object Step wise approximation, to conventional control electricity
The output of pole adjuster optimizes compensation, for controlling in real time, to obtain desired control effect.
Further, the Dedusting of EAF control system according to the stage of smelting, adds in steel scrap weight, blowing oxygen quantity, dust
The discharge capacity of the parameter predictions flue dust such as concentration, auxiliary material weight controls the rotating speed of wind turbine and volume damper aperture by PLC, real
Existing dust removal process is intelligent.
Further, the alarm completes alarm and oil temperature alarm for voltage and current alarm, operation；The group of the host computer
Part includes host, address card, display, Windows7 systems, programming software and the man-machine friendship for realizing PLC system programming and debugging
Mutual monitoring software.
Further, the electric arc furnaces prediction model of the neural network of the Fast Convergent, using three-layer neural network, including
Input layer, middle layer (hidden layer), output layer, the neural network algorithm of the Fast Convergent draw on the basis of traditional neural network
Enter generalized error function, to improve convergence rate and precision, the generalized error function is：
In formulaIt respectively refers in p-th training mode lower network i-th of output neuron of output layer
Desired output and reality output；P refers to training mode sum；NL refers to network output layer neuron number；λ is variable factor, in training
Period is decremented to 0 from 1；ε is the positive number of very little, and value range is 0.0001~0.01, for expected response di to be prevented to be equal to 0,
Cause by zero except the phenomenon that occur.
Intelligent arc furnace steelmaking system of the present invention, electric arc furnaces intelligence cannot effectively be met by being fully solved detection instrument at present
Change the demand of steel-making, electric arc furnaces intelligence steel-making is made precisely may be used at this stage by the combination of artificial intelligence and automated system
Control improves convergence rate and precision so that intelligent steelmaking process intelligent control, essence using the neural network algorithm of Fast Convergent
It is small to spend high deviation, reduces energy consumption, promotes steel-making amount to greatest extent, greatly increases the production efficiency.
Description of the drawings
Fig. 1 is intelligent arc furnace steelmaking system block diagram.
Fig. 2 is electric arc furnaces intelligent electrode Control system architecture block diagram.
Fig. 3 is the neural network algorithm flow chart of Fast Convergent.
Specific embodiment
For those skilled in the art is made to be best understood from the present invention, with reference to attached drawing 1-3, the present invention will be described, it should be appreciated that
Specific embodiment is intended to illustrate invention, the present invention is not restricted, and all supplements made in the thinking of the present invention change
Into all belonging to the scope of the present invention.
The present invention intelligent arc furnace steelmaking system, by furnace control system, oxygen rifle control system, dedusting control system and
Intelligent electrode control system form, which is characterized in that the intelligent electrode control system include host computer and slave computer, it is described on
Position machine uses the HMI system of form control centre Wincc, realizes the operational process monitoring of electric arc furnaces intelligent electrode control system,
Arc current, voltage waveform and its data show that the setting of three-phase current and voltage emulation data, production smelting process data are protected
Deposit filing and with the functions such as the communication of slave computer；The slave computer uses the PLC of Siemens S7-1500 series, described upper
Machine is connected by communicating network interface card with the communication module of slave computer；The PLC of the Siemens S7-1500 series includes communication mould
Block, analogue collection module, current transducer, Signal-regulated kinase and signal acquisition module.Using Siemens Company
The PLC software control procedures that SIMATICSTEP7 is adjusted as exploitation software, design electric arc furnaces intelligent electrode, build intelligent electrode
Adjuster；The intelligent electrode adjuster includes conventional electrode controller, the neural network electric arc furnaces of Fast Convergent estimates mould
Type and predictive compensation program；The intelligent electrode conditioner operation step is as follows：
1), the parameter using data collecting system acquisition electric arc furnaces during smelting, using these parameters in offline mode
The lower neural network predicting model for carrying out Fast Convergent is established；
2), the neural network predicting model of the Fast Convergent of foundation is put into online, and constantly carries out online adaptive tune
Whole, making prediction model, predictive compensation program utilizes estimation results to practical electric arc furnaces object Step wise approximation, to conventional control electricity
The output of pole adjuster optimizes compensation, for controlling in real time, to obtain desired control effect.
Specific embodiment is as follows：
Intelligent arc furnace steelmaking system structure chart is as shown in Figure 1, this system (can using host computer (industrial personal computer) and slave computer
Programmable controller PLC), monitoring host computer it is main its coordinate upper and lower and between relationship effect, monitor the phase of smelting process
It closes parameter, preserve smelting process data, establish good human-computer interaction interface.The effect of slave computer is that live number is smelted in acquisition
According to after the data of acquisition are made corresponding pretreatment, elevating control being carried out to electrode, while smelting field data is transmitted to upper
On industrial personal computer, the control command that upper industrial personal computer is assigned at the same time is received, and relevant operation can be performed according to order.It is upper
Machine and slave computer use fieldbus Network Communication.
Electric arc furnaces intelligent electrode control system is as shown in Fig. 2, electric arc furnaces intelligent electrode control system host computer uses configuration
Software Wincc (Windows Control Center) is responsible for the monitoring of field control picture and the report of intelligent electrode control system
The operation of electric arc furnaces intelligent electrode control system is realized in the setting and optimization of alert, PLC communication modules and data disaply moudle parameter
Process monitoring and arc current, voltage waveform and its data show, the setting of three-phase current and voltage emulation data；Production is smelted
Process data preserves filing and with the communication of slave computer and electric arc furnaces simulation model etc..Wherein alarm indication is voltage and current
Alarm and oil temperature alarm are completed in alarm, operation.Host computer component Configuration includes host, address card, display, Windows7 systems
System, the programming software for realizing PLC system programming and debugging, the monitoring software for realizing monitoring, real-time display, human-computer interaction.It is described
Monitoring software is WINCCV7.4.Above-mentioned host computer is connected with the ancillary equipments such as printer.
Slave computer use Siemens S7-1500 series PLC products, hardware system including power module, communication module,
CPU module and signaling module.Power module provides stable 24V DC power supplies for PLC system；CPU module is responsible for the fortune of program
The storage and processing of row, data, the transmission of communication and data with host computer；Communication module is used to connect SIMATICS7-1500
It is connected to Industrial Ethernet.Slave computer is responsible for three-phase current in entire smelting process, the acquisition of voltage and electrode control signals and place
Reason, and perform Electrode control.It also has the operation signal and Communication for Configuration Software that will collect controller, can also receive
Signal instruction from configuration software.
It is soft as developing using SIMATICSTEP7 for electric arc furnace smelting technology characteristics, on-site supervision and optimization requirement
Part, the PLC software control procedures that design arc furnace electrode is adjusted.The exploitation software provides a variety of PLC programming languages and mentions easily
The functions such as program debugging, system testing, fault diagnosis, user software exploitation are finished, are downloaded in the CPU module of PLC, during operation
PLC is only depended on, is totally independent of development environment.PLC softwares exist in the form of engineering, and a complete engineering is mainly by hard
Three parts such as part configuration, network structure, user program are formed, and correspondingly, STEP7 provides hardware configuration function, and network is matched
Put function and detail programming function.In its Program on-line debugging, system can read operation in detail and fault diagnosis letter from PLC
Breath, when run-time error occurs for program, the reason of can analyzing error according to these information, and corrected.For the ease of program
Logic testing, provide data enforcement functionalities in software, I/O states and program parameter numerical value can be forced, such nothing
Need the variation of external signal just can test logic result.These functions that software environment provides are provided for the exploitation of application program
It is convenient.
Electrode regulating PLC program designs, about being briefly described as follows for power function included in electrode regulating PLC.
FC32:The manual control function of electrode, the function control manually for electrode, when operation console has electrode to grasp manually
Start the function when ordering, control has automatically controlled priority to electrode relative to electrode manually.
FC36:Electrode jaw control function, the function are for coordination electrode clamper, the clamping of electrode and are loosened
It by PC control, is not controlled on operation console, can measure to the greatest extent prevents maloperation in this way.
FC65:Active electrical degree cumulative calculation function is calculated active needed for every stove steel by active electrical degree counting pulse
Electric degree, so that business accounting cost is used.
FC67:Range conversion function, the function are to be displayable by range conversion collected analogue transformation
Quantities, so that host computer is shown.
FC59:Indicator light display function completes the display function of some state parameters.
FC100:Data exchanging function, what which completed is the data friendship between electrode regulating PLC and furnace body action PLC
Function is changed, the data exchange between two PLC is realized by sending module SFC5 and receiving module SFC6.Each scan period ties
A data are exchanged during beam.
SFC5:Sending module, the module are system function modules, and the data of electrode regulating PLC are sent to furnace body action
PLC。
SFC6:Receiving module, the module are system function modules, and the data come from furnace body action PLC are received electrode
PLC is adjusted, source code is invisible.
FC66:Sampling functions, the function are analog acquisition functions, it control system need analog acquisition into
Come, and be filtered.
FC61,FC62,FC63:A, B, C three-phase electrode automatic lifting control function, using system pid function block FB91 and
The control algolithm of the application carries out automatically controlling electrode.
FB91:PID regulator function, the function are PID regulator function, can provide control according to the parameters of input
Output valve, source code are invisible.
The realization of the Software for Design of electrode regulating control automatic function (FC61, FC62, FC63)：
Arc furnace electrode adjusting control function is realized by the analog input/output template and CPU element of PLC
's.First, three-phase arc current and three-phase arc voltage are acquired, after measuring measuring loop rectifying and wave-filtering, becomes 4-20mA
Direct current signal input PLC analog modules；Then, it is sent into the PLC of Siemens after crossing A/D conversions, the control algolithm taken
Selection realized in S7-1500；Finally, the servo valve of electric-liquid drive system is output to by the D/A results converted, to control
Rise fall of electrodes processed adjusts the input power of electric arc furnaces, it is ensured that three-phase arc current and voltage maintain defined range of set value
Within.
Electrode regulating control principle：Arc stream, the arc voltage signal of refining furnace are rectified, after filtering, enterprising in counter-jib resistance
Row compares, and difference is sent into servo valve coil.When working under rated condition, difference zero, servo valve is failure to actuate；When arc length is inclined
During from set-point, arc current is more than set-point at this time, then the electric signal for being sent into servo valve electromagnetic coil is that valve rod is transported upwards
It is dynamic, rise fall of electrodes hydraulic cylinder is flowed into so as to carry energy liquid, electrode is made to increase, speed depends on valve opening openings of sizes.Work as electric current
When reaching set-point again, electric signal disappears, electrode stopping action；On the contrary, when if arc length is more than set-point, i.e. electric arc in stove
When electric current is less than set-point, then valve rod moves down, and the liquid in hydraulic cylinder just under the action of electrode lifting device dead weight, flows
Reservoir is returned, electrode declines until reaching given arc length again.
Intelligent electrode adjuster of the application based on neural network includes the electrode regulating controller (constant-impedance of (1) routine
Control strategy, pid control algorithm)；The neural network electric arc furnaces prediction model of (2) Fast Convergents；(3) predictive compensation journey
Sequence.The intelligent electrode conditioner operation step is as follows：1st, the parameter using data collecting system acquisition electric arc furnaces during smelting,
The neural network predicting model for being carried out Fast Convergent under offline mode using these parameters is established；2nd, by the Fast Convergent of foundation
Neural network predicting model put into online, and constantly carry out online adaptive adjustment, make prediction model to practical electric arc furnaces
Object Step wise approximation, predictive compensation program utilize estimation results, compensation are optimized to the output of conventional control electrode regulator,
For controlling in real time, to obtain desired control effect.
The neural network algorithm flow chart of Fast Convergent is as shown in figure 3, the electric arc furnaces of the neural network of Fast Convergent is estimated
Model is：Using three-layer neural network, including input layer, middle layer (hidden layer), output layer, in order to enable neural network is quickly received
It holds back, introduces generalized error function：
In formulaIt respectively refers in p-th training mode lower network i-th of output neuron of output layer
Desired output and reality output；P refers to training mode sum；NL refers to network output layer neuron number；λ is variable factor, in training
Period is decremented to 0 from 1；ε is the positive number of very little, and value range is 0.0001~0.01, for expected response di to be prevented to be equal to 0,
Cause by zero except the phenomenon that occur.
The generalized error Function Synthesis considers the convergence rate of back propagation algorithm and study precision, is absolute error and opposite
A kind of target function that error combines, and general index function can improve convergence speed of the algorithm, relative error can improve calculation
Method precision.It has been proved by practice that convergence rate greatly improves after introducing generalized error function, learn precision higher.
Predictive compensation program is to calculate compensation, meter according to the current value of neural network predicting and the deviation of stove desired value
Calculating formula is：
Cout=Co+Cb
Wherein：
CoutThe output controlled quentity controlled variable calculated for compensation program；
CoThe controlled quentity controlled variable sent out for proportional controller calculating；
CbFor the compensation rate calculated；
IgThe electric current for the subsequent time that neural network predicting model for Fast Convergent calculates；
IeTo give constant current；
IoFor current electric current.
By intelligent arc furnace steelmaking system of the present invention, electric arc furnaces intelligence cannot effectively be met by being fully solved detection instrument at present
The demand of energyization steel-making, artificial intelligence is combined with automated system makes electric arc furnaces intelligence steel-making precisely controllable, using quick
Convergent neural network algorithm improves convergence rate and precision so that and intelligent steelmaking process intelligent control, the high deviation of precision is small,
Energy consumption is reduced, steel-making amount is promoted to greatest extent, greatly increases the production efficiency.
The above content is a further detailed description of the present invention in conjunction with specific preferred embodiments, it is impossible to assert
The specific implementation of the present invention is confined to these explanations.For those of ordinary skill in the art to which the present invention belongs, exist
Under the premise of not departing from present inventive concept, several simple deduction or replace can also be made, should all be considered as belonging to the present invention's
Protection domain.
Claims (3)
1. intelligent arc furnace steelmaking system, by furnace control system, oxygen rifle control system, dedusting control system and intelligent electrode control
System composition processed, which is characterized in that
The intelligent electrode control system includes host computer and slave computer, and the host computer is using form control centre Wincc's
HMI system, realize electric arc furnaces intelligent electrode control system operational process monitoring and alarm, arc current, voltage waveform and its
Data show, the setting of three-phase current and voltage emulation data, production smelting process data preserve filing and with slave computer
The functions such as communication；
The slave computer uses the PLC of Siemens S7-1500 series, and the host computer is by communicating the communication of network interface card and slave computer
Module is connected；The PLC of the Siemens S7-1500 series include communication module, analogue collection module, current transducer,
Signal-regulated kinase and signal acquisition module；
The PLC softwares adjusted using the SIMATIC STEP7 of Siemens Company as exploitation software, design electric arc furnaces intelligent electrode
Program is controlled, builds intelligent electrode adjuster；The intelligent electrode adjuster includes conventional electrode controller, Fast Convergent
Neural network electric arc furnaces prediction model and predictive compensation program；
The intelligent electrode conditioner operation step is as follows：
1), using parameter of the data collecting system acquisition electric arc furnaces during smelting, using these parameters under offline mode into
The neural network predicting model of row Fast Convergent is established；
2) neural network predicting model of the Fast Convergent of foundation is put into online, and constantly carries out online adaptive adjustment, made
Prediction model is to practical electric arc furnaces object Step wise approximation, and predictive compensation program utilizes estimation results, to conventional control electrode tune
The output of section device optimizes compensation, for controlling in real time, to obtain desired control effect.
2. intelligent arc furnace steelmaking system as described in claim 1, which is characterized in that the Dedusting of EAF control system,
According to the discharge capacity of the parameter predictions flue dust such as the stage of smelting, addition steel scrap weight, blowing oxygen quantity, dust concentration, auxiliary material weight, pass through
PLC controls the rotating speed of wind turbine and volume damper aperture, realizes that dust removal process is intelligent.
3. intelligent arc furnace steelmaking system as described in claim 1, which is characterized in that it is described alarm for voltage and current alarm,
Alarm and oil temperature alarm are completed in operation；The component of the host computer includes host, address card, display, Windows7 systems, reality
Existing PLC system programming and the programming software of debugging and the monitoring software of human-computer interaction.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810075943.9A CN108265157A (en) | 2018-01-26 | 2018-01-26 | Intelligent arc furnace steelmaking system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810075943.9A CN108265157A (en) | 2018-01-26 | 2018-01-26 | Intelligent arc furnace steelmaking system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108265157A true CN108265157A (en) | 2018-07-10 |
Family
ID=62776899
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810075943.9A Pending CN108265157A (en) | 2018-01-26 | 2018-01-26 | Intelligent arc furnace steelmaking system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108265157A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110825053A (en) * | 2019-11-19 | 2020-02-21 | 王希宏 | Full-flow intelligent control system for electric arc furnace steelmaking |
| CN112036101A (en) * | 2020-11-03 | 2020-12-04 | 北京科技大学 | Electric arc furnace steelmaking molten pool simulation device, simulation system and method for simulating and measuring temperature of melt in molten pool by using simulation system |
| CN113324402A (en) * | 2021-05-28 | 2021-08-31 | 牡丹江师范学院 | Automatic control system of three-phase electric arc smelting electric furnace |
| CN115619101A (en) * | 2022-11-09 | 2023-01-17 | 北京科技大学 | Electric arc furnace steelmaking energy efficiency evaluation method |
| CN116334349A (en) * | 2023-04-13 | 2023-06-27 | 无锡东雄重型电炉有限公司 | Heating data acquisition and adjustment module of steelmaking electric furnace |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101715257A (en) * | 2009-11-20 | 2010-05-26 | 东北大学 | Intelligent controller of electric furnace electrode |
| CN101782321A (en) * | 2010-01-27 | 2010-07-21 | 上海金自天正信息技术有限公司 | Automatic regulating device of DC electric arc furnace electrode and control method thereof |
| CN102605139A (en) * | 2011-10-31 | 2012-07-25 | 中冶赛迪工程技术股份有限公司 | Digital electric arc furnace electrode control method and system based on network transmission |
-
2018
- 2018-01-26 CN CN201810075943.9A patent/CN108265157A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101715257A (en) * | 2009-11-20 | 2010-05-26 | 东北大学 | Intelligent controller of electric furnace electrode |
| CN101782321A (en) * | 2010-01-27 | 2010-07-21 | 上海金自天正信息技术有限公司 | Automatic regulating device of DC electric arc furnace electrode and control method thereof |
| CN102605139A (en) * | 2011-10-31 | 2012-07-25 | 中冶赛迪工程技术股份有限公司 | Digital electric arc furnace electrode control method and system based on network transmission |
Non-Patent Citations (2)
| Title |
|---|
| 李艳伟: "智能控制技术在电弧炉电极调节中的应用", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
| 王科俊等: "快速收敛全局最优的多层前向神经网络综合反向传播算法", 《哈尔滨工程大学学报》 * |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110825053A (en) * | 2019-11-19 | 2020-02-21 | 王希宏 | Full-flow intelligent control system for electric arc furnace steelmaking |
| CN112036101A (en) * | 2020-11-03 | 2020-12-04 | 北京科技大学 | Electric arc furnace steelmaking molten pool simulation device, simulation system and method for simulating and measuring temperature of melt in molten pool by using simulation system |
| CN113324402A (en) * | 2021-05-28 | 2021-08-31 | 牡丹江师范学院 | Automatic control system of three-phase electric arc smelting electric furnace |
| CN115619101A (en) * | 2022-11-09 | 2023-01-17 | 北京科技大学 | Electric arc furnace steelmaking energy efficiency evaluation method |
| CN116334349A (en) * | 2023-04-13 | 2023-06-27 | 无锡东雄重型电炉有限公司 | Heating data acquisition and adjustment module of steelmaking electric furnace |
| CN116334349B (en) * | 2023-04-13 | 2023-08-29 | 无锡东雄重型电炉有限公司 | Heating data acquisition and adjustment module of steelmaking electric furnace |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108265157A (en) | Intelligent arc furnace steelmaking system | |
| CN108763550B (en) | Blast furnace big data application system | |
| CN101592964B (en) | Method for controlling forecast of molten steel temperature of double-station LF furnace | |
| CN106249724B (en) | A kind of polynary molten steel quality forecast Control Algorithm of blast furnace and system | |
| CN111650903B (en) | Intelligent control system for bottom argon blowing of steel ladle based on visual identification | |
| CN110263494B (en) | Alumina production operation optimization system and method based on cloud edge cooperation | |
| CN103426035A (en) | Self-balanced byproduct blast furnace gas dispatching system in iron and steel industry and method for predicting yield and consumption | |
| Lin et al. | Consideration of green intelligent steel processes and narrow window stability control technology on steel quality | |
| CN101765258A (en) | Three-phase electrode positioning device in smelting process of electro-fused magnesia furnace and control method thereof | |
| Backman et al. | Methods and tools of improving steel manufacturing processes: Current state and future methods | |
| CN116822380B (en) | Collaborative optimization method for tail gas recycling in copper smelting process based on digital twin | |
| CN103024959B (en) | Intelligent electrode regulator and intelligent electrode control method | |
| CN109581988A (en) | A kind of intelligent steelmaking system based on converter gas analytical technology | |
| CN104267600B (en) | Ladle refining furnace Electrode Computer Control System and control method thereof | |
| Spirin et al. | Complex of model systems for supporting decisions made in managing blast-furnace smelting technology | |
| CN210765379U (en) | Device for intelligent tapping of converter | |
| CN107164597A (en) | It is a kind of to detect the one-touch automatic method for making steel of converter without furnace gas without sublance | |
| CN111290267A (en) | Thermal power model identification device and identification method based on LabVIEW | |
| CN105271398A (en) | Hydrolysis integrated system and working method thereof | |
| CN105242545B (en) | A kind of Forecasting Methodology of the coverter pig oxygen flow based on process batch model | |
| CN113778035B (en) | Intelligent crude tin smelting system | |
| CN109870986A (en) | A kind of stirred autoclave On-Line Control Method based on neural network and data-driven | |
| CN116705211B (en) | Digital twin-based online prediction method and system for copper loss rate of oxygen-enriched copper molten pool | |
| CN116127345B (en) | Converter steelmaking process mode design method based on deep clustering generation countermeasure network | |
| CN215975982U (en) | Intelligent crude tin smelting system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20180710 |