CN106835200B - Aluminum electrolysis cell region control system - Google Patents
Aluminum electrolysis cell region control system Download PDFInfo
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- CN106835200B CN106835200B CN201510872653.3A CN201510872653A CN106835200B CN 106835200 B CN106835200 B CN 106835200B CN 201510872653 A CN201510872653 A CN 201510872653A CN 106835200 B CN106835200 B CN 106835200B
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Abstract
The invention discloses a kind of aluminum electrolysis cell region control systems, including electrolytic cell and slot control machine, wherein the control system further includes sensor group, data acquisition module and computer control, the sensor group is arranged in the electrolytic cell, for detecting the slot condition parameter of the electrolytic cell;The data acquisition module is connected between the sensor group and the computer control, is supplied to the computer control for acquiring the slot condition parameter detected by the sensor group, and by slot condition parameter;Fuzzy algoritic module of birdsing of the same feather flock together is provided in the computer control, the computer control receiving slit condition parameter carries out analytical calculation to slot condition parameter by the fuzzy algoritic module of birdsing of the same feather flock together, forms control instruction and be input to the slot control machine;The slot control machine controls the electrolytic cell according to the control instruction, optimizes the slot condition parameter of electrolytic cell.The control system may be implemented automation control electrolytic cell and achieve the purpose that energy consumption minimum and energy balance.
Description
Technical field
The present invention relates to technical field of aluminum electrolysis, more particularly to a kind of aluminum electrolysis cell region control system.
Background technique
With the automation of aluminum electrolysis industry, information-based development, aluminum electrolysis enterprise acquires a large amount of anti-
The creation data for reflecting electrolytic cell operation conditions, in actual production management process, production management personnel to the management of electrolytic cell also
It rests in artificial experience, cannot sufficiently find and using the useful information and rule being hidden in these data, causes to give birth to
It produces decision and lacks scientific basis.How the data of these magnanimity are effectively analyzed, finds out and be hidden in behind these data
Objective law currently exist the software of some this respects to obtain the slot condition and its development trend of electrolytic cell.Such as matter
The methods of buret reason, automatic control, Six Sigma, expert system have an application in terms of aluminium electrolysis cell condition analysis, but due to
The reasons such as the time is short, experience is insufficient, it is desired nonetheless to technologist by scene for many years working experience it is artificial go to analyze and determine
Slot condition is found out disease slot and is handled, while making a policy to the production of electrolytic cell.At this time the working experience of policymaker plays
Critically important effect, therefore this method is not smart enough.
Summary of the invention
In view of the shortcomings of the prior art, the present invention provides a kind of aluminum electrolysis cell region control systems, by fuzzy
Algorithm of birdsing of the same feather flock together carries out analytical calculation to the slot condition parameter of electrolytic cell, and the corresponding control of electrolytic bath condition parameter for obtaining optimization refers to
It enables, then electrolytic cell is controlled according to control instruction by slot control machine, to realize that automation control electrolytic cell reaches energy consumption minimum and energy
The purpose of balance.
To achieve the goals above, present invention employs the following technical solutions:
A kind of aluminum electrolysis cell region control system, including electrolytic cell and slot control machine, wherein the control system further includes sensing
Device group, data acquisition module and computer control, the sensor group is arranged in the electrolytic cell, for detecting the electricity
Solve the slot condition parameter of slot;The data acquisition module is connected between the sensor group and the computer control, is used for
The slot condition parameter detected by the sensor group is acquired, and slot condition parameter is supplied to the computer control;The meter
It calculates and is provided with fuzzy algoritic module of birdsing of the same feather flock together, the computer control receiving slit condition parameter, by the fuzzy class in machine controller
Poly- algoritic module carries out analytical calculation to slot condition parameter, forms control instruction and is input to the slot control machine;The slot control machine according to
The control instruction controls the electrolytic cell, optimizes the slot condition parameter of electrolytic cell.
Wherein, the slot condition parameter includes that electrolytic cell aluminum water is flat, electrolyte level, electrolysis temperature, molecular proportion, pole span, sun
Polar effect coefficient, anode drop and electrolyte pressure drop.
Wherein, the sensor group includes multiple sensors, is put down for detecting the electrolytic cell aluminum water respectively, electrolyte water
Flat, electrolysis temperature, molecular proportion, pole span, anode effect coefficient, anode drop and the parameter of electrolyte pressure drop.
Wherein, the sensor group detects to obtain the slot condition parameter of real-time change, and the data collecting module collected obtains
The slot condition parameter of discrete values point.
Wherein, the computer control birdss of the same feather flock together algoritic module to slot by described obscure according to the slot condition parameter received
Condition parameter is analyzed, and obtains slot condition parameter and electrolytic cell energy consumption and energy balance by the method for Multiple Non-linear Regression Analysis
Dynamic response relationship obtain the electrolytic bath condition parameter of optimization using energy consumption minimum and energy balance as target, form control and refer to
It enables.
Compared with the prior art, the aluminum electrolysis cell region control system provided in the embodiment of the present invention is birdsed of the same feather flock together by fuzzy
Algorithm carries out analytical calculation to the slot condition parameter of electrolytic cell, obtains the corresponding control instruction of electrolytic bath condition parameter of optimization, then
Electrolytic cell is controlled according to control instruction by slot control machine, to realize that automation control electrolytic cell reaches energy consumption minimum and energy balance
Purpose.
Detailed description of the invention
Fig. 1 is the structural block diagram of aluminum electrolysis cell region control system provided in an embodiment of the present invention;
Fig. 2 is the process diagram of aluminium cell control method provided in an embodiment of the present invention.
Specific embodiment
To make the object, technical solutions and advantages of the present invention clearer, with reference to the accompanying drawing to specific reality of the invention
The mode of applying is described in detail.The example of these preferred embodiments is illustrated in the accompanying drawings.Shown in attached drawing and according to
The embodiments of the present invention of attached drawing description are only exemplary, and the present invention is not limited to these embodiments.
Here, it should also be noted that, in order to avoid having obscured the present invention because of unnecessary details, in the accompanying drawings only
Show with closely related structure and/or processing step according to the solution of the present invention, and be omitted little with relationship of the present invention
Other details.
The embodiment of the invention provides a kind of aluminum electrolysis cell region control systems, as shown in Figure 1, the aluminium cell region is controlled
System processed includes electrolytic cell 100 and slot control machine 200, sensor group 300, data acquisition module 400 and computer control 500,
Wherein, fuzzy algoritic module 501 of birdsing of the same feather flock together is provided in computer control 500.
Wherein, the sensor group 300 is arranged in the electrolytic cell 100, for detecting the slot condition of the electrolytic cell 100
Parameter;The data acquisition module 400 is connected between the sensor group 300 and the computer control 500, for adopting
Collect the slot condition parameter detected by the sensor group 300, and slot condition parameter is supplied to the computer control 500;Institute
500 receiving slit condition parameter of computer control is stated, analysis meter is carried out to slot condition parameter by the fuzzy algoritic module 501 of birdsing of the same feather flock together
It calculates, forms control instruction and be input to the slot control machine 200;The slot control machine 200 controls the electrolysis according to the control instruction
Slot 100 optimizes the slot condition parameter of electrolytic cell 100.
As shown in Fig. 2, the control method of aluminum electrolysis cell region control system as provided above specifically includes:
S1, the slot condition parameter that electrolytic cell 100 is detected by sensor group 300.
S2, the slot condition parameter detected by sensor group 300 is acquired by data acquisition module 400, is supplied to computer control
Device 500 processed.
S3, fuzzy algorithm of birdsing of the same feather flock together is based on to slot condition parameter progress analytical calculation by computer control 500, forms control and refers to
It enables.Wherein, algorithm of birdsing of the same feather flock together: fuzzy c-means algorithm, abbreviation FCMA or FCM is obscured.
S4, electrolytic cell 100 is controlled according to control instruction by slot control machine 200.
Wherein, the slot condition parameter includes that electrolytic cell aluminum water is flat, electrolyte level, electrolysis temperature, molecular proportion, pole span, sun
Polar effect coefficient, anode drop and electrolyte pressure drop.
Wherein, the sensor group 300 includes multiple sensors (merely exemplary in Fig. 1 to show two sensors), is used
In detecting respectively, the electrolytic cell aluminum water is flat, electrolyte level, electrolysis temperature, molecular proportion, pole span, anode effect coefficient, anode
The parameter of pressure drop and electrolyte pressure drop.
Wherein, the detection of sensor group 300 obtains the slot condition parameter of real-time change, and the data acquisition module 400 is adopted
Collection obtains the slot condition parameter of discrete values point.
Wherein, the computer control 500 is according to the slot condition parameter received, by the fuzzy algoritic module of birdsing of the same feather flock together
501 pairs of slot condition parameters are analyzed, by the method for Multiple Non-linear Regression Analysis obtain slot condition parameter and electrolytic cell energy consumption and
The dynamic response relationship of energy balance obtains the electrolytic bath condition parameter of optimization, shape using energy consumption minimum and energy balance as target
At control instruction.
It as a specific example, is tested in aluminium electroloysis enterprise: using aluminum cell current for 240kA,
The amount of electrolytic cell Inner electrolysis matter is 10 tons, and addition doses is 3.2kg, and electrolytic cell has 8 blanking devices.In computer control system
In, alumina concentration control is set as 2% in target value, alumina feeding interval 120s.By anode effect waiting time, sun
Polar effect time span, the vibration of electrolyzer electric pressing, the exact automatic control of voltage swing, double dead zone function ranges, guarantee electricity
The application of power-saving technology and the even running of production process during solution aluminium reduce technical parameter and swing degree.Based on the present invention
The aluminum electrolysis cell region control system and control method that embodiment provides, the electricity flat to electrolytic cell aluminum water using fuzzy algorithm of birdsing of the same feather flock together
Solve the control of the technical parameters such as matter level, electrolysis temperature, molecular proportion, pole span, anode effect coefficient, anode drop, electrolyte pressure drop
Value processed is assessed, and carries out the optimization of technical parameter, to improve the process control of every technical measures during electrolytic aluminium
Ability keeps the energy saving and stability of electrolytic cell operation.Electrolytic cell average voltage can be made to be reduced to 3.950-4.000V, primary aluminum
Ton aluminium ac consumption declines 400kWh or more on the original basis.For enterprise realize " four low one is high " (that is: low alumina concentration,
Low electrolysis temperature, lower molecular ratio, low effect coefficient, high pole span) technology and control lays a good foundation.
In conclusion the aluminum electrolysis cell region control system provided in the embodiment of the present invention, passes through fuzzy algorithm pair of birdsing of the same feather flock together
The slot condition parameter of electrolytic cell carries out analytical calculation, obtains the corresponding control instruction of electrolytic bath condition parameter of optimization, then by slot control
Machine controls electrolytic cell according to control instruction, to realize that automation control electrolytic cell achievees the purpose that energy consumption minimum and energy balance.
It should be noted that, in this document, relational terms such as first and second and the like are used merely to a reality
Body or operation are distinguished with another entity or operation, are deposited without necessarily requiring or implying between these entities or operation
In any actual relationship or order or sequence.Moreover, the terms "include", "comprise" or its any other variant are intended to
Non-exclusive inclusion, so that the process, method, article or equipment including a series of elements is not only wanted including those
Element, but also including other elements that are not explicitly listed, or further include for this process, method, article or equipment
Intrinsic element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that
There is also other identical elements in process, method, article or equipment including the element.
The above is only the specific embodiment of the application, it is noted that for the ordinary skill people of the art
For member, under the premise of not departing from the application principle, several improvements and modifications can also be made, these improvements and modifications are also answered
It is considered as the protection scope of the application.
Claims (1)
1. a kind of aluminum electrolysis cell region control system, including electrolytic cell and slot control machine, which is characterized in that the control system further includes
Sensor group, data acquisition module and computer control, the sensor group is arranged in the electrolytic cell, for detecting
State the slot condition parameter of electrolytic cell;The data acquisition module is connected between the sensor group and the computer control,
The computer control is supplied to for acquiring the slot condition parameter detected by the sensor group, and by slot condition parameter;Institute
It states and is provided with fuzzy algoritic module of birdsing of the same feather flock together, the computer control receiving slit condition parameter, by the mould in computer control
Paste birdss of the same feather flock together algoritic module to slot condition parameter progress analytical calculation, forms control instruction and is input to the slot control machine;The slot control machine
The electrolytic cell is controlled according to the control instruction, optimizes the slot condition parameter of electrolytic cell;
Wherein, the sensor group includes multiple sensors, for detecting the following slot condition parameter of the electrolytic cell: aluminum water respectively
Flat, electrolyte level, electrolysis temperature, molecular proportion, pole span, anode effect coefficient, anode drop and the parameter of electrolyte pressure drop;
Wherein, the sensor group detects to obtain the slot condition parameter of real-time change, and the data collecting module collected obtains discrete
The slot condition parameter of numerical point;
Wherein, the computer control joins slot condition by the fuzzy algoritic module of birdsing of the same feather flock together according to the slot condition parameter received
Number is analyzed, and obtains the dynamic of slot condition parameter and electrolytic cell energy consumption and energy balance by the method for Multiple Non-linear Regression Analysis
State response relation obtains the electrolytic bath condition parameter of optimization using energy consumption minimum and energy balance as target, forms control instruction.
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CN109100598B (en) * | 2018-10-23 | 2021-01-26 | 攀钢集团攀枝花钢铁研究院有限公司 | Method for judging single-cell running state of assembly line type magnesium electrolytic cell |
CN110592617B (en) * | 2019-08-29 | 2021-06-15 | 青海物产工业投资有限公司 | Secondary starting method for full-series power failure of aluminum electrolysis cell |
CN110751379A (en) * | 2019-09-29 | 2020-02-04 | 山西中铝华润有限公司 | Method for judging technical indexes of aluminum electrolysis cell |
CN111996558B (en) * | 2020-08-24 | 2021-06-25 | 常州机电职业技术学院 | Method for setting technological parameters of aluminum electrolysis production |
CN115323440B (en) * | 2022-09-30 | 2023-04-07 | 湖南力得尔智能科技股份有限公司 | Aluminum electrolysis holographic closed-loop control system based on AI neural network deep self-learning |
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