CN118195144A - Method and system for predicting, regulating and controlling zinc load of long-flow steel mill blast furnace - Google Patents
Method and system for predicting, regulating and controlling zinc load of long-flow steel mill blast furnace Download PDFInfo
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- 239000011701 zinc Substances 0.000 title claims abstract description 151
- HCHKCACWOHOZIP-UHFFFAOYSA-N Zinc Chemical compound [Zn] HCHKCACWOHOZIP-UHFFFAOYSA-N 0.000 title claims abstract description 139
- 229910052725 zinc Inorganic materials 0.000 title claims abstract description 139
- 238000000034 method Methods 0.000 title claims abstract description 52
- 229910000831 Steel Inorganic materials 0.000 title claims abstract description 41
- 239000010959 steel Substances 0.000 title claims abstract description 41
- 230000001105 regulatory effect Effects 0.000 title claims description 6
- 230000001276 controlling effect Effects 0.000 title description 4
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 claims abstract description 144
- 229910052742 iron Inorganic materials 0.000 claims abstract description 72
- 239000000463 material Substances 0.000 claims abstract description 50
- 239000000446 fuel Substances 0.000 claims abstract description 27
- KFZAUHNPPZCSCR-UHFFFAOYSA-N iron zinc Chemical compound [Fe].[Zn] KFZAUHNPPZCSCR-UHFFFAOYSA-N 0.000 claims abstract description 21
- 238000012360 testing method Methods 0.000 claims abstract description 14
- 238000011156 evaluation Methods 0.000 claims abstract description 13
- 238000009826 distribution Methods 0.000 claims abstract description 11
- 238000005303 weighing Methods 0.000 claims abstract description 7
- 238000009960 carding Methods 0.000 claims abstract description 4
- 238000004064 recycling Methods 0.000 claims description 37
- 239000000428 dust Substances 0.000 claims description 27
- 238000009628 steelmaking Methods 0.000 claims description 24
- 238000004364 calculation method Methods 0.000 claims description 19
- 239000002994 raw material Substances 0.000 claims description 9
- 239000000571 coke Substances 0.000 claims description 8
- 238000004519 manufacturing process Methods 0.000 claims description 8
- 238000010586 diagram Methods 0.000 claims description 7
- 238000007689 inspection Methods 0.000 claims description 7
- 230000008569 process Effects 0.000 claims description 7
- 238000003032 molecular docking Methods 0.000 claims description 6
- 238000011084 recovery Methods 0.000 claims description 5
- 238000012545 processing Methods 0.000 claims description 4
- 239000003245 coal Substances 0.000 claims description 3
- 125000004122 cyclic group Chemical group 0.000 claims description 3
- 238000002372 labelling Methods 0.000 claims description 3
- 239000000843 powder Substances 0.000 claims description 3
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 5
- 230000008901 benefit Effects 0.000 description 5
- 239000011449 brick Substances 0.000 description 5
- 229910052799 carbon Inorganic materials 0.000 description 5
- 230000006378 damage Effects 0.000 description 5
- 239000002817 coal dust Substances 0.000 description 3
- 238000013461 design Methods 0.000 description 3
- 230000008859 change Effects 0.000 description 2
- 230000007797 corrosion Effects 0.000 description 2
- 238000005260 corrosion Methods 0.000 description 2
- 238000010943 off-gassing Methods 0.000 description 2
- 239000011148 porous material Substances 0.000 description 2
- 239000011819 refractory material Substances 0.000 description 2
- 238000003860 storage Methods 0.000 description 2
- 238000003723 Smelting Methods 0.000 description 1
- 230000001174 ascending effect Effects 0.000 description 1
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- 238000012946 outsourcing Methods 0.000 description 1
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Abstract
The invention relates to a long-process steel mill blast furnace zinc load prediction regulation method, which belongs to the field of blast furnace zinc load prediction and comprises the following steps: s1: uniformly naming and coding iron-containing reclaimed material data of the whole factory, and constructing an electronic tag; s2: carding and classifying each iron-containing reclaimed material according to different utilization modes; s3: collecting each batch of test data and wagon balance weighing data of iron ores, fuels, scrap steel and recycled iron materials in a factory, and automatically transmitting and synchronously recording the data; s4: receiving data, and uniformly converting the zinc content into ton iron-zinc load data; calculating and evaluating zinc load, and giving a regulation suggestion according to an evaluation result; s5: and (3) establishing a whole-plant map model, marking a whole-plant iron-containing reclaimed material generation source, a middle-change warehouse and a tail end destination, and presenting a whole-flow distribution list chart, a data graph report and message pushing in real time.
Description
Technical Field
The invention belongs to the field of prediction of zinc load of a blast furnace, and relates to a method and a system for predicting and regulating zinc load of a blast furnace in a long-flow steel mill.
Background
In long-process steelworks, the blast furnace is the core production unit responsible for providing qualified molten iron, and the high efficiency, high quality, low consumption, long service life and environment-friendly operation are directly related to the cost competitiveness of enterprises. In order to ensure the stable and smooth operation of the blast furnace, the content of harmful impurities in raw fuel fed into the furnace is controlled, and zinc is an element with the greatest harm, so that the control value of the load of zinc fed into the furnace is definitely required to be not more than 0.15kg per ton of iron in the design specification of blast furnace ironmaking engineering GB 50427-2015.
The zinc is gradually reduced and gasified along with the descending of furnace burden after entering a blast furnace, gaseous zinc rapidly permeates into the pores of refractory materials of a furnace body, volume expansion occurs after deposition and oxidation to damage the refractory materials, meanwhile, the zinc also invades into the pores of coke to damage the reactivity and thermal strength of the coke, so that the fuel ratio of the blast furnace is increased, or the zinc adheres to gaps between a lining and a material column along with the ascending of the furnace burden, the problems of nodulation and suspension are caused, the air permeability of the material column and the uniformity of gas flow distribution are deteriorated, and even serious accidents are caused by the damping down and the reduction of the yield of the blast furnace, and the economic loss is huge. The serious corrosion of hearth refractory is one of the important reasons for accidents, the zinc content permeated into the micro gaps of the carbon bricks is super-standard, and the volume of the metal zinc expands after being oxidized in a high-temperature environment, so that the carbon brick masonry generates larger internal stress in the vertical and horizontal directions, the carbon brick tissue is damaged, the carbon brick is pulverized and fluffy, a carbon brick ring crack loose layer is formed, the corrosion process is further aggravated by high-temperature melt and gas scouring, and the tragic drama is finally produced.
In the past, because the blast furnace has smaller furnace capacity and too pursue short-term benefits, the damage to zinc damage is paid attention to inadequacy. In recent years, as the blast furnace is increasingly enlarged, the requirements for the concentrate are becoming more stringent, but the high cost of the raw fuel is still causing the raw fuel to be in a deteriorated state, which makes enterprises have to pay high attention to the management of zinc load. However, the long-process steel mill lacks system management due to long production process, more and miscellaneous smelting raw materials, particularly the iron-containing reclaimed materials produced by the inside of enterprises are in a simple rough management state for a long time, and lack of overall process integrity assessment prediction and regulation, so that the zinc load management of the blast furnace is easily distorted, and the regulation is invalid until the production instability is caused.
Disclosure of Invention
In view of the above, the invention aims to provide a method and a system for predicting and controlling zinc load of a long-process steel mill blast furnace.
In order to achieve the above purpose, the present invention provides the following technical solutions:
on one hand, the invention provides a long-process steel mill blast furnace zinc load prediction regulation method, which comprises the following steps:
s1: uniformly naming and coding iron-containing reclaimed material data of the whole factory, constructing an electronic tag, and realizing automatic identification and recording of various iron-containing reclaimed material category names and batch information;
S2: according to different utilization modes, carding and classifying each iron-containing reclaimed material into a self-recycling part R and a non-recycling part O of the blast furnace;
S3: collecting each batch of test data and wagon balance weighing data of iron ores, fuels, scrap steel and recycled iron materials in a factory, and automatically transmitting and synchronously recording the data;
s4: receiving the name, the going classification and the inspection and weighing data of corresponding batches of summarized raw fuel, scrap steel and each iron-containing reclaimed material, and uniformly converting the zinc content of the raw fuel, scrap steel and each iron-containing reclaimed material into ton iron-zinc load data by taking the batch as a basic unit; then calculating and evaluating the zinc load, and giving out regulation and control suggestions according to an evaluation result;
s5: and (3) establishing a whole-plant map model, marking a whole-plant iron-containing reclaimed material generation source, a middle-change warehouse and a tail end destination, and presenting a whole-flow distribution list chart, a data graph report and message pushing in real time.
In step S1, the iron-containing recovery material data of the whole plant is supplemented and perfected on the basis of the main raw fuel data of the existing iron ores, fuels, scrap steel and the like.
In step S1, electronic labeling information collection is implemented by using a barcode, a two-dimensional code or an RFID method.
Further, the step S4 specifically includes the following steps:
(8) According to the test and metering data of iron ore, coke and coal powder, uniformly converting the zinc content into ton iron-zinc load, and recording as C1;
(9) According to the test and metering data of the scrap steel, uniformly converting the zinc content into iron-zinc load of ton, and recording as C2;
(10) According to the utilization mode of the iron-containing reclaimed materials in the whole factory, uniformly converting the zinc content in the iron-containing reclaimed materials of the recycled blast furnace ironmaking system into ton iron-zinc load, and marking the ton iron-zinc load as R; wherein, the zinc load directly recycled by the blast furnace ironmaking system is recorded as RI, and the corresponding recycling coefficient is recorded as alpha; the zinc load recycled by the steelmaking system is denoted as RS, and the corresponding recycling coefficient is denoted as beta;
(11) According to the utilization mode of the iron-containing reclaimed materials in the whole factory, uniformly converting the zinc content in the non-recycled iron-containing reclaimed materials into ton iron-zinc load, and marking as O Real world ;
(12) The zinc load of the blast furnace is recorded as Z, and Z=C1+RI+RS;
(13) The number of loop iterations is denoted i, i=1, 2, … …, n, the loop iteration process has the following relationship:
RIn＝C1+α×Zn (Ⅰ)
RSn＝β×C2 (Ⅱ)
Zn+1＝RIn+RSn＝C1+α×Zn+β×C2 (Ⅲ)
The method comprises the following steps of (III) carrying out iterative treatment:
When n.fwdarw.infinity, α n.fwdarw.0, there are:
At this time, the output zinc O is:
On+1≈Zn+1×(1-α)+C2×(1-β)＝C1+C2 (Ⅵ)
from formulas (V) and (VI), it can be seen that the following rule is obeyed when the equilibrium state is finally achieved through cyclic iteration:
c) The zinc load of the blast furnace is approximately:
d) The output zinc amount discharged to the outside of the plant is equal to the input zinc amount brought in by the raw fuel and the scrap steel outside the plant, namely, O Management device = C1+C2;
(14) According to the calculation result, the risk degree of the zinc load state of the blast furnace is estimated and predicted, and is divided into 5 grades, namely, serious, dangerous, attention, healthy and good, and the estimation result is as follows:
when Z > is allowed, if O Real world ≥O Management device , then evaluate as "dangerous"; if O Real world <O Management device , then it is evaluated as "severe";
When Z is less than or equal to the allowable value, if O Real world >O Management device is judged to be 'good'; if O Real world ＝O Management device , then evaluate to "healthy"; if O Real world <O Management device , then the evaluation is "attention".
Further, the regulation and control guidance is carried out on the subsequent production according to the evaluation result:
d) When in a good or healthy state, the observation is mainly performed, and no adjustment is performed;
e) When the method is in a 'attention' state, the reuse coefficients alpha and beta are dynamically adjusted by combining the trend of the discharged zinc, and when the measured discharged zinc is lower than a theoretical calculation value and the gap has a trend of increasing, the reuse amount of the blast furnace dust and the steelmaking dust is reduced, or the dezincification treatment amount of the blast furnace dust and the steelmaking dust is increased;
f) When the dust collector is in a dangerous state or a serious state, the recycling coefficients alpha and beta are firstly adjusted, namely the recycling amount of the blast furnace dust and the steelmaking dust is reduced, or the dezincification treatment amount of the blast furnace dust and the steelmaking dust is increased; and secondly, adjusting the input zinc amounts C1 and C2 of the main raw fuel, namely reducing the adding amount of the iron ore and the scrap steel with high zinc content.
On the other hand, the invention provides a long-process steel mill blast furnace zinc load prediction regulation system, which comprises: the system comprises a data docking module, a whole-plant iron-containing reclaimed material list module, a zinc load prediction module and a zinc load regulation module;
The data docking module is used for receiving data of a logistics system, an inspection and test system, a blast furnace raw material system and a steelmaking raw material system and uniformly converting zinc content into ton iron-zinc load data;
the whole plant iron-containing reclaimed material list diagram module is used for displaying a whole plant map model and presenting a whole flow distribution list diagram, a data graph report and message pushing in real time;
The zinc load prediction module is used for selecting and sorting data, setting limit values and periods, and performing prediction evaluation calculation on zinc load;
The zinc load regulation and control module is used for setting distribution coefficients, carrying out regulation and control calculation according to zinc load evaluation results and giving out regulation and control scheme suggestions.
The invention has the beneficial effects that: the invention provides a method and a system for predicting and regulating the zinc load of a long-process steel mill blast furnace, which can be used for predicting and regulating the zinc load of the long-process steel mill blast furnace, and assisting the high-efficiency stable and smooth production of the long-process steel mill blast furnace.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention. The objects and other advantages of the invention may be realized and obtained by means of the instrumentalities and combinations particularly pointed out in the specification.
Drawings
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in the following preferred detail with reference to the accompanying drawings, in which:
FIG. 1 is a schematic diagram of the zinc balance distribution of the present invention;
FIG. 2 is a system workflow diagram of the present invention;
Fig. 3 is a system architecture diagram of the present invention.
Detailed Description
Other advantages and effects of the present invention will become apparent to those skilled in the art from the following disclosure, which describes the embodiments of the present invention with reference to specific examples. The invention may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present invention. It should be noted that the illustrations provided in the following embodiments merely illustrate the basic idea of the present invention by way of illustration, and the following embodiments and features in the embodiments may be combined with each other without conflict.
Wherein the drawings are for illustrative purposes only and are shown in schematic, non-physical, and not intended to limit the invention; for the purpose of better illustrating embodiments of the invention, certain elements of the drawings may be omitted, enlarged or reduced and do not represent the size of the actual product; it will be appreciated by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted.
The same or similar reference numbers in the drawings of embodiments of the invention correspond to the same or similar components; in the description of the present invention, it should be understood that, if there are terms such as "upper", "lower", "left", "right", "front", "rear", etc., that indicate an azimuth or a positional relationship based on the azimuth or the positional relationship shown in the drawings, it is only for convenience of describing the present invention and simplifying the description, but not for indicating or suggesting that the referred device or element must have a specific azimuth, be constructed and operated in a specific azimuth, so that the terms describing the positional relationship in the drawings are merely for exemplary illustration and should not be construed as limiting the present invention, and that the specific meaning of the above terms may be understood by those of ordinary skill in the art according to the specific circumstances.
Referring to fig. 1 to 3, the method for predicting and controlling the zinc load of a long-process steel mill blast furnace, disclosed by the invention, comprises the following steps of:
1) On the basis of the existing main raw fuel data of iron ores, fuels, scrap steel and the like, the iron-containing reclaimed material data of the whole factory is supplemented and perfected, unified naming and coding are carried out on the iron-containing reclaimed material data, electronic tag transformation is completed, and automatic identification and recording of the type names and batch information of various iron-containing reclaimed materials are realized. The electronic labeling information acquisition can be realized by using bar codes, two-dimensional codes, RFID and other modes, and acquired data are transmitted by using wired networks, 5G, wiFi, NFC and other modes.
2) And carding and classifying the iron-containing reclaimed materials into two main types according to different utilization modes such as self-recycling, vending or outsourcing disposal, namely a self-recycling part R and a non-recycling part O of the blast furnace.
3) And accessing a whole factory inspection and test system and a logistics system, collecting each batch inspection and test data (chemical component mass percent) and wagon balance weighing data (batch mass) of iron ore, fuel, scrap steel and recycled iron materials in the factory, and automatically transmitting and synchronously recording the data.
4) The system comprises a data docking module, a control module and a process principle, wherein the data docking module of the system receives the name and the going classification of summarized raw fuel, scrap steel and each iron-containing reclaimed material and the inspection, test and weighing data of corresponding batches, takes the batches as basic units, uniformly converts the zinc content into ton iron and zinc load data, and the unit g/t, and then the prediction module of the system calculates and evaluates according to the flow method shown in the figures 1-2, and then the control module provides strategy advice according to the evaluation result, wherein the process principle is as follows:
according to the test and metering data of iron ore, coke and coal powder, the zinc content is uniformly converted into ton iron-zinc load, and the ton iron-zinc load is recorded as C1 in g/t.
According to the test and metering data of the scrap steel, the zinc content is uniformly converted into a ton of iron-zinc load, and the ton of iron-zinc load is recorded as C2 in g/t.
According to the utilization mode of the iron-containing reclaimed materials in the whole factory, the zinc content in the iron-containing reclaimed materials of a recycled blast furnace ironmaking system (including direct recycling and recycling after dezincification treatment) is uniformly converted into ton iron-zinc load, and is recorded as R in g/t. Wherein, the zinc load directly recycled by the blast furnace ironmaking system is recorded as RI, and the corresponding recycling coefficient is recorded as alpha (alpha is more than or equal to 0 and less than or equal to 1); the zinc load recycled by the steelmaking system is denoted as RS, and the corresponding recycling coefficient is denoted as beta (beta is more than or equal to 0 and less than or equal to 1).
According to the utilization mode of the iron-containing reclaimed materials in the whole factory, the zinc content in the non-recycled (i.e. discharged) iron-containing reclaimed materials is uniformly converted into ton iron-zinc load which is recorded as O Real world and is expressed in g/t.
The zinc load of the blast furnace is denoted as Z, and the unit g/t is Z=C1+RI+RS.
The large amount of raw materials such as ores, fuels, scrap steel and the like are purchased regularly, the property is stable, and the balance of zinc in production is achieved again through sintering-blast furnace circulation iteration very rapidly, and the period of raw material purchasing change is generally smaller than that of raw material purchasing change. Therefore, in the iteration period, the raw materials can be approximately considered to be brought into zinc loads C1 and C2, and the zinc recycling coefficients alpha and beta returned by the iron and steel making system through recycling the iron materials are constant.
The number of loop iterations is denoted i (i=1, 2, … …, n), and the loop iteration process has the following relationship:
RIn＝C1+α×Zn (Ⅰ)
RSn＝β×C2 (Ⅱ)
Zn+1＝RIn+RSn＝C1+α×Zn+β×C2 (Ⅲ)
The method comprises the following steps of (III) carrying out iterative treatment:
further, when n→infinity, α n →0, there are:
At this time, the output zinc O is:
On+1≈Zn+1×(1-α)+C2×(1-β)＝C1+C2 (Ⅵ)
from formulas (V) and (VI), it can be seen that the following rule is obeyed when the equilibrium state is finally achieved through cyclic iteration:
The zinc load of the blast furnace is mainly related to zinc carried in raw fuel and scrap steel and the recycling coefficient of the zinc returned by the blast furnace and steelmaking processes, the current zinc load of the blast furnace only has influence on short-term results, but has little influence on final balance values, and can be approximately considered as follows:
The output zinc amount discharged to the outside of the plant is equal to the input zinc amount brought in by the raw fuel and the scrap steel outside the plant, that is, O Management device =c1+c2.
Based on the calculation results, the risk level of the zinc load state of the blast furnace was estimated and predicted, and the zinc load state of the blast furnace was classified into 5 grades, namely, "serious (NB)", "dangerous (NM)", "attention (NS)", "healthy (Z)", and "good (G)", and the results are summarized in table 1.
TABLE 1
And carrying out regulation and control guidance on subsequent production according to the evaluation result:
when in a good or healthy state, the observation is mainly performed, and no adjustment is performed;
When the method is in a 'attention' state, the reuse coefficients alpha and beta are dynamically adjusted by combining the trend of the discharged zinc, and when the measured discharged zinc is lower than a theoretical calculation value and the gap has a trend of increasing, the reuse amount of the blast furnace dust and the steelmaking dust (or the dezincification treatment amount of the blast furnace dust and the steelmaking dust) is reduced;
When the high-zinc-content iron ore and steel-making dust is in a dangerous state or a serious state, the recycling coefficients alpha and beta are firstly adjusted, namely the recycling amount of the blast furnace dust and the steel-making dust is reduced (or the dezincification treatment amount of the blast furnace dust and the steel-making dust is increased), and then the input zinc amount C1 and C2 of the main raw fuel are adjusted, namely the adding amount of the high-zinc-content iron ore and the steel scraps is reduced.
5) The system is configured with a display system, a whole plant map model is established, a whole plant iron-containing reclaimed material generation source, a middle-change warehouse and tail end destination are marked, a whole flow distribution list chart, a data graph report and a real-time presentation of message pushing are formed, and meanwhile, the system is responsible for man-machine interaction display of all functional modules of the system.
Example 1:
(1) Iron ore, coke, coal dust zinc loading c1=20 g/t.
(2) Zinc loading of scrap c2=100 g/t.
(3) In the iron-containing reclaimed materials recycled by the blast furnace ironmaking system (including direct recycling and recycling after processing treatment), the recycling coefficient alpha=0.3 of the zinc load directly recycled by the blast furnace ironmaking system and the recycling coefficient beta=0.7 of the zinc load recycled by the steelmaking system.
(4) Zinc loading in non-recycled (i.e., off-stream) iron-containing recovery O Real world = 168g/t.
(5) The calculation of the zinc load of the blast furnace is obtained:
Z= (20+0.7X120)/(1-0.3) =148.5 g/t, meeting the requirement of GB 50427-2015 'design Specification for blast furnace ironmaking engineering' on the load of zinc entering the furnace not exceeding 150 g/t.
(6) The theoretical zinc discharge load calculation can be obtained:
And O Management device = 20+120 = 140g/t, less than the measured zinc out-gassing load O Real world .
(7) According to the calculation results of (5) and (6), the current state is judged to be in a good state, and the zinc discharging capacity is rich, so that adjustment is not needed.
Example 2:
(1) Iron ore, coke, coal dust zinc loading c1=20 g/t.
(2) Zinc loading of scrap c2=100 g/t.
(3) In the iron-containing reclaimed materials recycled by the blast furnace ironmaking system (including direct recycling and recycling after processing treatment), the recycling coefficient alpha=0.5 of the zinc load directly recycled by the blast furnace ironmaking system and the recycling coefficient beta=0.5 of the zinc load recycled by the steelmaking system.
(4) Zinc loading in non-recycled (i.e., off-stream) iron-containing recovery O Real world = 125g/t.
(5) The calculation of the zinc load of the blast furnace is obtained:
z= (20+0.5X100)/(1-0.5) =150g/t, which is equal to the requirement that the load of zinc in the furnace does not exceed 150g/t in GB 50427-2015.
(6) The theoretical zinc discharge load calculation can be obtained:
O Management device = 20+100 = 120g/t, substantially flush with the measured zinc out-take load O Real world .
(7) And (3) judging that the current state is in an 'attention' state according to the calculation results of (5) and (6), wherein the theoretical zinc discharge capacity is enough, and the theoretical zinc discharge capacity can be temporarily adjusted and can be kept for observation.
Example 3:
(1) Iron ore, coke, coal dust zinc loading c1=20 g/t.
(2) Zinc loading of scrap c2=300 g/t.
(3) In the iron-containing reclaimed materials recycled by the blast furnace ironmaking system (including direct recycling and recycling after processing treatment), the recycling coefficient alpha=0.3 of the zinc load directly recycled by the blast furnace ironmaking system and the recycling coefficient beta=0.7 of the zinc load recycled by the steelmaking system.
(4) Zinc loading in non-recycled (i.e., off-stream) iron-containing recovery O Real world = 216g/t.
(5) The calculation of the zinc load of the blast furnace is obtained:
Z= (20+0.7x300)/(1-0.3) =328.6 g/t, exceeding the requirement of GB 50427-2015 'blast furnace ironmaking engineering design Specification' that the load of zinc into the furnace does not exceed 150 g/t.
(6) The theoretical zinc discharge load calculation can be obtained:
o Management device = 20+300 = 320g/t, greater than the measured zinc out-gassing load O Real world .
(7) And (3) judging that the current state is in a serious state according to the calculation results of (5) and (6), and the zinc discharge capacity is insufficient, and adjusting as soon as possible.
(8) The distribution coefficient is calculated reversely according to the control upper limit of 150 g/t:
And if alpha, C1 and C2 are unchanged temporarily, beta= (150× (1-0.3) -20)/(300=0.28), namely, the zinc load recycling coefficient beta recycled by the steelmaking system is reduced to 0.28, so that the zinc load of the blast furnace can meet the control requirement again.
Those of ordinary skill in the art will appreciate that all or some of the steps in the methods of the above embodiments may be implemented by a program to instruct related hardware, where the program may be stored in a computer readable storage medium, where the program may be executed to implement the steps of the method, where the storage medium includes: ROM/RAM, magnetic disks, optical disks, etc.
Finally, it is noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made thereto without departing from the spirit and scope of the present invention, which is intended to be covered by the claims of the present invention.
Claims (6)
1. A method for predicting and regulating zinc load of a long-process steel mill blast furnace is characterized by comprising the following steps of: the method comprises the following steps:
s1: uniformly naming and coding iron-containing reclaimed material data of the whole factory, constructing an electronic tag, and realizing automatic identification and recording of various iron-containing reclaimed material category names and batch information;
S2: according to different utilization modes, carding and classifying each iron-containing reclaimed material into a self-recycling part R and a non-recycling part O of the blast furnace;
S3: collecting each batch of test data and wagon balance weighing data of iron ores, fuels, scrap steel and recycled iron materials in a factory, and automatically transmitting and synchronously recording the data;
s4: receiving the name, the going classification and the inspection and weighing data of corresponding batches of summarized raw fuel, scrap steel and each iron-containing reclaimed material, and uniformly converting the zinc content of the raw fuel, scrap steel and each iron-containing reclaimed material into ton iron-zinc load data by taking the batch as a basic unit; then calculating and evaluating the zinc load, and giving out regulation and control suggestions according to an evaluation result;
s5: and (3) establishing a whole-plant map model, marking a whole-plant iron-containing reclaimed material generation source, a middle-change warehouse and a tail end destination, and presenting a whole-flow distribution list chart, a data graph report and message pushing in real time.
2. The long-process steel mill blast furnace zinc load prediction regulation method according to claim 1, wherein the method comprises the following steps: in the step S1, firstly, the iron-containing recovery material data of the whole factory is supplemented and perfected on the basis of the main raw fuel data of the existing iron ores, fuels, scrap steel and the like.
3. The long-process steel mill blast furnace zinc load prediction regulation method according to claim 2, wherein the method is characterized in that: in step S1, electronic labeling information collection is implemented by using a bar code, a two-dimensional code or an RFID method.
4. The long-process steel mill blast furnace zinc load prediction regulation method according to claim 1, wherein the method comprises the following steps: the step S4 specifically comprises the following steps:
(1) According to the test and metering data of iron ore, coke and coal powder, uniformly converting the zinc content into ton iron-zinc load, and recording as C1;
(2) According to the test and metering data of the scrap steel, uniformly converting the zinc content into iron-zinc load of ton, and recording as C2;
(3) According to the utilization mode of the iron-containing reclaimed materials in the whole factory, uniformly converting the zinc content in the iron-containing reclaimed materials of the recycled blast furnace ironmaking system into ton iron-zinc load, and marking the ton iron-zinc load as R; wherein, the zinc load directly recycled by the blast furnace ironmaking system is recorded as RI, and the corresponding recycling coefficient is recorded as alpha; the zinc load recycled by the steelmaking system is denoted as RS, and the corresponding recycling coefficient is denoted as beta;
(4) According to the utilization mode of the iron-containing reclaimed materials in the whole factory, uniformly converting the zinc content in the non-recycled iron-containing reclaimed materials into ton iron-zinc load, and marking as O Real world ;
(5) The zinc load of the blast furnace is recorded as Z, and Z=C1+RI+RS;
(6) The number of loop iterations is denoted i, i=1, 2, … …, n, the loop iteration process has the following relationship:
RIn＝C1+α×Zn (Ⅰ)
RSn＝β×C2 (II)
Zn+1＝RIn+RSn＝C1+α×Zn+β×C2 (III)
the method can be obtained after the iterative processing of the formula (III):
When n.fwdarw.infinity, α n.fwdarw.0, there are:
At this time, the output zinc O is:
On+1≈Zn+1×(1-α)+C2×(1-β)＝C1+C2 (VI)
from formulas (V) and (VI), the equilibrium state is finally reached through cyclic iteration, and the following rules are obeyed:
a) The zinc load of the blast furnace is approximately:
b) The output zinc amount discharged to the outside of the plant is equal to the input zinc amount brought in by the raw fuel and the scrap steel outside the plant, namely, O Management device = C1+C2;
(7) According to the calculation result, the risk degree of the zinc load state of the blast furnace is estimated and predicted, and is divided into 5 grades, namely, serious, dangerous, attention, healthy and good, and the estimation result is as follows:
when Z > allowable value, if O Real world ≥O Management device , then evaluate as "dangerous"; if O Real world ＜O Management device , then it is evaluated as "severe";
When Z is less than or equal to the allowable value, if O Real world ＞O Management device is judged to be 'good'; if O Real world ＝O Management device , then evaluate to "healthy"; if O Real world ＜O Management device , then the evaluation is "attention".
5. The long-process steel mill blast furnace zinc load prediction regulation method according to claim 4, wherein the method comprises the following steps: and carrying out regulation and control guidance on subsequent production according to the evaluation result:
a) When in a good or healthy state, the observation is mainly performed, and no adjustment is performed;
b) When the method is in a 'attention' state, the reuse coefficients alpha and beta are dynamically adjusted by combining the trend of the discharged zinc, and when the measured discharged zinc is lower than a theoretical calculation value and the gap has a trend of increasing, the reuse amount of the blast furnace dust and the steelmaking dust is reduced, or the dezincification treatment amount of the blast furnace dust and the steelmaking dust is increased;
c) When the dust collector is in a dangerous state or a serious state, the recycling coefficients d and beta are firstly adjusted, namely the recycling amount of the blast furnace dust and the steelmaking dust is reduced, or the dezincification treatment amount of the blast furnace dust and the steelmaking dust is increased; and secondly, adjusting the input zinc amounts C1 and C2 of the main raw fuel, namely reducing the adding amount of the iron ore and the scrap steel with high zinc content.
6. A long-process steel mill blast furnace zinc load prediction regulation and control system is characterized in that: comprising the following steps: the system comprises a data docking module, a whole-plant iron-containing reclaimed material list module, a zinc load prediction module and a zinc load regulation module;
The data docking module is used for receiving data of a logistics system, an inspection and test system, a blast furnace raw material system and a steelmaking raw material system and uniformly converting zinc content into ton iron-zinc load data;
the whole plant iron-containing reclaimed material list diagram module is used for displaying a whole plant map model and presenting a whole flow distribution list diagram, a data graph report and message pushing in real time;
The zinc load prediction module is used for selecting and sorting data, setting limit values and periods, and performing prediction evaluation calculation on zinc load;
The zinc load regulation and control module is used for setting distribution coefficients, carrying out regulation and control calculation according to zinc load evaluation results and giving out regulation and control scheme suggestions.
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