CN114955586B - System for predicting quality of coal blending coke of silo - Google Patents
System for predicting quality of coal blending coke of silo Download PDFInfo
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- CN114955586B CN114955586B CN202210829314.7A CN202210829314A CN114955586B CN 114955586 B CN114955586 B CN 114955586B CN 202210829314 A CN202210829314 A CN 202210829314A CN 114955586 B CN114955586 B CN 114955586B
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- 239000003245 coal Substances 0.000 title claims abstract description 227
- 238000002156 mixing Methods 0.000 title claims abstract description 121
- 239000000571 coke Substances 0.000 title claims abstract description 64
- 238000004939 coking Methods 0.000 claims abstract description 108
- 239000004615 ingredient Substances 0.000 claims abstract description 25
- 238000009826 distribution Methods 0.000 claims abstract description 22
- 239000000463 material Substances 0.000 claims abstract description 15
- 238000004458 analytical method Methods 0.000 claims abstract description 10
- 238000003860 storage Methods 0.000 claims description 18
- 238000001514 detection method Methods 0.000 claims description 11
- 238000004519 manufacturing process Methods 0.000 claims description 8
- 238000004364 calculation method Methods 0.000 claims description 7
- 238000006243 chemical reaction Methods 0.000 claims description 6
- 238000007599 discharging Methods 0.000 claims description 5
- 238000000034 method Methods 0.000 claims description 5
- NINIDFKCEFEMDL-UHFFFAOYSA-N Sulfur Chemical compound [S] NINIDFKCEFEMDL-UHFFFAOYSA-N 0.000 claims description 4
- 229910052717 sulfur Inorganic materials 0.000 claims description 4
- 239000011593 sulfur Substances 0.000 claims description 4
- 238000012360 testing method Methods 0.000 claims description 4
- 239000011335 coal coke Substances 0.000 claims 2
- 241000273930 Brevoortia tyrannus Species 0.000 description 6
- 238000010586 diagram Methods 0.000 description 5
- 238000005070 sampling Methods 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 239000000203 mixture Substances 0.000 description 2
- 238000002360 preparation method Methods 0.000 description 2
- 238000010791 quenching Methods 0.000 description 2
- 230000000171 quenching effect Effects 0.000 description 2
- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000003763 carbonization Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000009897 systematic effect Effects 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
- B65G65/00—Loading or unloading
- B65G65/30—Methods or devices for filling or emptying bunkers, hoppers, tanks, or like containers, of interest apart from their use in particular chemical or physical processes or their application in particular machines, e.g. not covered by a single other subclass
- B65G65/32—Filling devices
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
- B65G43/00—Control devices, e.g. for safety, warning or fault-correcting
- B65G43/08—Control devices operated by article or material being fed, conveyed or discharged
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
- B65G2201/00—Indexing codes relating to handling devices, e.g. conveyors, characterised by the type of product or load being conveyed or handled
- B65G2201/04—Bulk
- B65G2201/045—Sand, soil and mineral ore
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
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- Coke Industry (AREA)
Abstract
The invention relates to a silo coal blending coke quality prediction system, which belongs to the coking field and comprises the following components: the silo receiving and storing module is used for carrying out silo receiving and storing inquiry and management; the coal blending actual score inquiry module is used for carrying out comparison analysis on the planned proportioning and the actual proportioning of the ingredients; the in-silo material dynamic tracking module is used for dynamically tracking the total stock, variety and weight distribution condition of coking coal in the silo; the coking coal quality module is used for correlating the actual coal blending performance with the quality of the coking coal used in shift or daily blending and is used as basic data for coke quality prediction; and the coke quality prediction module is used for predicting the coke quality based on the coal blending performance and coking coal quality module to obtain the coke prediction quality and comparing the coke prediction quality with the actual coke quality.
Description
Technical Field
The invention belongs to the field of coking, and relates to a silo coal blending coke quality prediction system.
Background
The storage capacity of the silos is large, but the number of the silos is limited. The same silo can store different varieties of coking coals, and the quality fluctuation of the coking coals is easily caused by the quality difference of the coking coals. After coking coals of different varieties and batches enter the same silo, the position of the coking coals in the silo cannot be determined, the quality of the coking coals matched with the current coal silo cannot be calculated, and meanwhile, the actual coal blending ratio and the theoretical coal blending ratio are affected by factors such as coal silo hanging, so that the coke quality is difficult to predict.
Disclosure of Invention
In view of the above, the invention provides a coke quality prediction system based on the actual coal blending ratio of coking coal, the memory quantity distribution, the quality distribution and the like of the coking coal in a silo, and aims to realize accurate prediction of the coke quality of the coking coal blending in the silo and realize the comparison analysis of the coke prediction quality and the actual quality.
In order to achieve the above purpose, the present invention provides the following technical solutions:
a silo coal blending coke quality prediction system, comprising:
the silo receiving and storing module is used for carrying out silo receiving and storing inquiry and management;
the coal blending actual score inquiry module is used for carrying out comparison analysis on the planned proportioning and the actual proportioning of the ingredients;
the in-silo material dynamic tracking module is used for dynamically tracking the total stock, variety and weight distribution condition of coking coal in the silo;
the coking coal quality module is used for correlating the actual coal blending performance with the quality of the coking coal used in shift or daily blending and is used as basic data for coke quality prediction;
and the coke quality prediction module is used for predicting the coke quality based on the coal blending performance and coking coal quality module to obtain the coke prediction quality and comparing the coke prediction quality with the actual coke quality.
Further, the silo receiving and storing module is specifically configured to:
1) When a coking coal acquisition and purchase factory enters a silo, recording the silo entering time, the silo entering variety, the silo entering weight and the silo entering group batch number information in a silo receiving and storing module;
2) After each material mixing of the silo is finished, the silo receiving and storing module displays the silo discharging time and discharging weight information;
3) The silo receiving and dispatching storage module displays silo storage quantity, and the silo storage quantity is obtained by calculation according to silo storage, silo entering weight and silo distributing weight;
4) The silo receiving and storing module is also used for manually adjusting when the actual weight of the silo is greatly different from the number of the silo systems after the silo inventory is developed;
5) In the silo receiving and storing module, the blending time and the weight are correspondingly blended into the number of the coal tower, so that the association between coking coal blending and the coal tower is realized.
Further, the coal blending actual result inquiring module respectively calculates and inquires the planned proportioning and actual proportioning conditions of each silo proportioning or accumulated proportioning according to the shift, day or coal tower number; and comparing the planned coal blending ratio with the actual coal blending ratio, and carrying out statistical query analysis according to the silo number or the coking coal variety.
Further, the coal blending actual score query module tracks the coal blending actual score, and includes:
single silo batching actual results: inquiring actual record of the ingredients according to inquiry conditions of date, shift and tower number, inquiring weight of each ingredient, actual score coal blending ratio, planned proportion and difference between actual score proportion and planned proportion under corresponding conditions, and reminding when the difference between actual score proportion and planned proportion reaches a certain range;
accumulating silo batching actual results: inquiring accumulated ingredients under the selected conditions according to the date, shift and coal tower number inquiring conditions; inquiring the planned proportion, the accumulated coal blending quantity and the accumulated actual score proportion under the selected condition; if the batching plan numbers of the planned proportioning under the inquiry condition are consistent, correspondingly displaying the planned coal blending ratio, and if a plurality of batching plan numbers exist, displaying the planned coal blending ratio for each batching plan number respectively;
single variety (manufacturing code) batching actual results: inquiring actual results of single-variety ingredients under the selected conditions according to date, shift and tower number inquiring conditions, inquiring weight of each ingredient under the corresponding conditions, actual result coal blending ratio, planned proportion, actual result proportion and planned proportion difference, and reminding when the actual result proportion and the planned proportion difference reach a certain range;
accumulating single variety (manufacturing code) batching actual results: inquiring accumulated ingredients under the selected conditions according to date, shift and tower number inquiring conditions, and inquiring the planned proportioning, accumulated coal blending amount and accumulated actual result proportioning under the selected conditions; and if the batching plan numbers of the planned proportioning under the inquiry condition are consistent, correspondingly displaying the planned coal blending ratio, and if a plurality of batching plan numbers exist, displaying the planned coal blending ratio for each batching plan number respectively.
Further, the in-bin material dynamic tracking module calculates the distribution condition of the coking coal in the bin according to the total stock of the bin and the sequence of the varieties and the weights of the coking coals; and meanwhile, when the coking coal distribution situation is displayed, according to the coking coal quality associated with the batch numbers, if the coking coal quality exceeds the limit standard requirement, displaying index items and numerical values of the over-limit index in a coking coal distribution picture in the silo, and carrying out early warning and forecasting.
Further, the material dynamic tracking module in the silo uses the total stock of the silo as a reference, the material dynamic tracking module performs backward pushing according to the sequence of the silo, the amount of each silo is a coal seam, backward pushing calculation is performed from the last silo feeding, the last silo feeding amount is subtracted, and the last silo feeding amount is not less than the silo stock.
Further, key parameters in the prediction process of the coke quality prediction module comprise ash conversion coefficients and sulfur conversion coefficients of coking coal and coke, and the corresponding relation between the coal blending time and the detection time of different indexes of the coke; after the coal blending is finished, the coal blending is stored in a coal tower, carbonized into coke in a coke oven, dry quenched, sampled and tested, and the test period time is used for making a corresponding relation between the end of the coal blending and the coke detection quality time, and then the corresponding relation is compared according to the corresponding time difference.
The invention has the beneficial effects that: according to the invention, accurate prediction of the quality of the coal blending coke of the silo is realized according to the actual coal blending ratio, which is beneficial to monitoring the quality of the coke and guiding the production of the 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 block diagram of a system for predicting the quality of coal blending coke of a silo according to the invention;
FIG. 2 is a dynamic distribution model diagram of coking coal in a No. 3 silo;
fig. 3 is a mass dynamic distribution model diagram of the 3# silo.
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, the invention provides a coke quality prediction system for silo coal blending, which aims to solve the problems that after coking coals of different varieties and batches enter the same silo, the internal position of the coking coals cannot be determined, the quality of the coking coals blended by the current coal silo cannot be calculated, and meanwhile, the coke quality prediction is difficult because the actual coal blending ratio is influenced by factors such as coal silo hanging and the like and has a certain difference from the theoretical coal blending ratio.
The solution is as follows: 1. and (5) establishing silo coking coal receiving and storing. 1) When the coking coal is purchased and enters a silo, relevant information such as the time of entering the silo, the weight of entering the silo, the batch number of entering the silo group and the like is carried. 2) After each material mixing of the silo is finished, the silo receives and stores the related information such as the silo blanking time, the silo blanking weight and the like. 3) The silo receives and transmits the storage quantity of the silo, the storage quantity is obtained by calculation according to the silo stock, the silo entering weight and the silo dispensing weight, and meanwhile an adjusting button is arranged. And after the silo inventory is developed, manually adjusting the actual weight of the silo and the number of the silo systems if the actual weight of the silo and the number of the silo systems are greatly different. The adjustment quantity is stored in a silo for receiving and storing. 2. And (5) establishing the comparison query analysis of the actual coal blending ratio and the planned coal blending of the coking coal. 3. And carrying out tracking statistics on the basis of the shift or day to calculate the consumption of the coking coal in the shift or day to obtain the actual shift proportion or the actual day proportion. 4. And (5) pushing the feeding time and the batch number of the feeding group of the coking coal consumed on duty or the day according to the stock quantity and the consumption quantity. 5. And automatically extracting the batch inspection and test results according to the batch number system to obtain the quality information of the coking coal consumed on the duty or the day. 6. And (3) carrying out systematic calculation according to the actual proportioning of each silo and the mass information of each consumed coking coal on the same day or on the same day, and predicting the coke mass.
The system comprises:
1. the silo receives and stores the module. The module is mainly used for receiving and sending the storage inquiry and management of the silo.
Feeding silo: when the coking coal is purchased in a factory and unloaded into a silo, the silo receives and stores the coking coal, and records the entering time, variety, batch number and weight of the coking coal. When the in-factory transfer is carried into the silo, information such as the silo feeding time, the silo feeding variety, the batch number, the weight and the like is displayed. If the feed varieties are mixed coals collected by a stock yard and the like, the batch number cannot be determined, and the batch number can be empty.
And (3) discharging the silo: after each material proportioning is finished, the blanking time and the blanking weight of each silo are displayed, and meanwhile, the system automatically calculates the storage quantity of the silo.
Silo stock adjustment: and obtaining the stock quantity of the coal bin according to the inventory weight, comparing the inventory weight with the system stock quantity, and adjusting the system internal stock quantity through a system stock quantity adjusting button to ensure that the system stock quantity is consistent with the actual stock quantity.
1) Assuming that the coking coal A is purchased into a factory on 1 st 4 th 2022, the shipments reach 3871 tons, the coking coal A is unloaded into a 3# silo on 12:20 th 4 th month, the batch number ZP20220402003 of the sampling group is obtained, the receiving and dispatching record of the coking coal A group on the 3# silo can be inquired to 3871 tons of the warehouse entering quantity of the batch number ZP20220402003 of the coking coal A on the 2 nd 2022 th month 4 th month, and the warehouse entering quantity is correspondingly increased by 3871 tons.
2) Assuming that 778 tons are allocated from the No. 3 coal bunker of 16:50 on 2 month 4 of 2022 and enter the No. B coal bunker, and the amount of the allocated bunker is reduced by 778 tons.
3) Assuming that the inventory is taken on 3 days of 4 months of 2022, the inventory of the 3# silo is 4587 tons, but the transceiving inventory of the 3# silo is 5087 tons, the inventory of the silo is adjusted through an adjusting function, the adjustment is the inventory minus the transceiving inventory, and the transceiving inventory after adjustment is the inventory, as shown in table 1:
TABLE 1
| Date of day | Feed time | Coal type | Group lot number | Quantity to be stored | Amount of the mixture | Stock quantity | Adjustment amount | Coal tower number |
| 20220402 | 12:20 | Coking coal A | ZP20220402003 | 3871 | 6516 | |||
| 20220402 | 16:50 | 778 | 5738 | B | ||||
| 20220403 | 9:30 | 651 | 5087 | C | ||||
| 20220403 | 12:10 | 4587 | -500 | |||||
| 20220403 | 13:45 | 475 | 4112 | A | ||||
| 20220403 | 15:20 | Coking coal A | ZP20220403004 | 1719 | 5831 | |||
| 20220403 | 20:30 | Coking coal B | ZP20220403009 | 867 | 6698 | |||
| 20220403 | 22:25 | 502 | 6196 | A | ||||
| 20220404 | 1:10 | Coking coal C | ZP20220404001 | 2270 | 8466 | |||
| 20220404 | 2:36 | 546 | 7920 | C | ||||
| 20220404 | 8:30 | 740 | 7180 | B | ||||
| 20220404 | 12:05 | 7480 | 300 | |||||
| 20220404 | 15:12 | Coking coal A | ZP20220404010 | 1885 | 9365 | |||
| 20220404 | 17:45 | 539 | 8826 | A |
2. And a coal blending actual result query module. The module is mainly used for comparing and analyzing the planned proportion and the actual proportion of the ingredients, and can respectively count and inquire the planned proportion and the actual proportion of each ingredient or accumulated ingredients of each silo according to the shift, the day and the coal tower number. The comparison analysis of the planned coal blending ratio and the actual coal blending ratio of the module can be used for carrying out statistical query analysis according to the silo number and also can be used for carrying out statistical query analysis according to the coking coal variety (manufacturing code).
1) Single silo batching actual results. Inquiring the actual record of the ingredients according to inquiry conditions such as date, shift, tower number and the like, wherein the actual record of the ingredients inquires the weight of each ingredient, the actual score coal blending ratio, the planned proportion and the difference between the actual score proportion and the planned proportion under the corresponding conditions, and the color-developing reminding can be performed when the difference between the actual score proportion and the planned proportion reaches a certain range. The plan proportion is provided with a batching plan number.
2) And accumulating the actual results of the silo ingredients. The accumulated ingredients under the selected conditions can be inquired according to inquiry conditions such as date, shift, coal tower number and the like. The method can inquire the planned proportion, the accumulated coal blending quantity and the accumulated actual result proportion under the selected condition. And if the batching plan numbers of the planned proportioning under the query condition are consistent, namely only one batching plan number corresponds to the planned coal blending ratio, and if a plurality of batching plan numbers exist, each batching plan number displays the planned coal blending ratio respectively.
3) Single variety batching actual results. The single variety refers to a single manufacturing code, namely the corresponding variety in the planned coal blending ratio. According to the inquiry conditions of date, shift, coal tower number and the like, inquiring actual results of single-variety ingredients under the selected conditions, inquiring weight of each ingredient under the corresponding conditions, actual result coal blending ratio, planned ratio, and difference between actual result ratio and planned ratio, and developing and reminding if the difference between actual result ratio and planned ratio is within a certain range. The plan proportion is provided with a batching plan number.
4) Accumulating the actual results of single-variety ingredients. The accumulated ingredients under the selected conditions can be inquired according to inquiry conditions such as date, shift, coal tower number and the like. The method can inquire the planned proportion, the accumulated coal blending quantity and the accumulated actual result proportion under the selected condition. And if the batching plan numbers of the planned proportioning under the query condition are consistent, namely only one batching plan number corresponds to the planned coal blending ratio, and if a plurality of batching plan numbers exist, each batching plan number displays the planned coal blending ratio respectively.
3. And a dynamic tracking module for materials in the cylinder bin. The module is mainly used for dynamically tracking the total stock, variety and weight distribution of coking coal in the silo. According to the total stock of the coal bins, the variety of the entering coking coal and the sequence of the weight, each silo forms a dynamic tracking model for the distribution of the coking coal in the silo, and dynamically tracks the distribution condition of the coking coal in the coal bins. And meanwhile, when the coking coal distribution condition is displayed, the coking coal quality is related according to the batch numbers, and if the coking coal quality exceeds the limit standard requirement, index items and numerical values of the over-limit indexes are displayed on a coking coal distribution picture in the silo so as to achieve the effect of early warning and forecasting.
The main principle of tracking the coking coal dynamic distribution model in the silo is as follows: and (3) taking the total storage quantity of the silo as a reference, carrying out backward pushing according to the sequence of silo feeding, wherein each silo feeding quantity is a coal seam, and carrying out backward pushing calculation (subtracting the last silo feeding quantity) from the last silo feeding until the final silo feeding quantity is more than or equal to the silo storage quantity. Such as:
the total amount of 18:00 coal bunkers is 8826 tons at 4 months of 2022, the last time the bunkers are taken in is 20220404, 15:12, and the total amount of 8826 tons minus 1885 tons is 6941 tons.
The last feeding is 20220404 1:10, the feeding amount is 2270 tons, which is smaller than 6941 tons, and the total stock is 6941-2270=4671 tons.
When the last feeding is 20220403 to 20:30 and the feeding amount is 867 tons which is smaller than 4671 tons, the total stock amount is 4671-867=3804 tons.
When the last feeding is 20220403:20 and the feeding amount is 1719 tons which is smaller than 3804 tons, the total stock amount is 3804-1719=2085 tons.
When the last feeding is 20220402 12:20 and the feeding amount is 3871 tons which is larger than 2085 tons, the batch of coking coal in the silo stores 2085 tons. Assuming that ZP20220403009 ash is 11.25% above the limit requirement and ZP20220403004G value 50 is below the limit requirement, the coking coal distribution in the # 3 silo is shown in fig. 2.
4. And a coal blending performance and coking coal quality module. The module is mainly used for correlating the actual results of shift or daily blending with the quality of the coking coal used, and is used as basic data for coke quality prediction.
The module is mainly used for correlating the actual results of shift or daily blending with the quality of the coking coal used, and is used as basic data for coke quality prediction. The module comprises: silo number, actual proportioning, quality information for each coal silo, etc., as shown in table 2:
TABLE 2
Because the inner diameter of the silo is generally larger, coking coal enters the silo instead of entering the silo according to a plane, namely, the coking coal in the silo is artificially managed in a layering manner, but the coking coal in the actual silo is uneven, so that in order to ensure accurate coke quality prediction, in a quality selection stage, a certain amount of layers at the joint of coking coals in different batches are taken as mixing quality, and 500 tons are taken as an example for illustration. The coking coal A, group batch numbers ZP20220403004 and G50, the upper part (group batch number ZP 20220403009) and the lower part (group batch number ZP 20220402003) of the coking coal A are in cross contact with 500 tons, the mass of the coking coal A and the coking coal B are the average value, and the mass corresponding to the group batch number is arranged outside the coking coal A.
Illustrating: group lot No. ZP20220403004, total 1719 tons, 500 tons each for the contact portion with the lower group lot No. ZP20220402003, and 500 tons each for the contact portion with the upper group lot No. ZP 20220403009.
When 300 tons of coking coal are matched with the class 3 silo, and all the coking coal are in the position of 'ZP 20220402003 1585 tons', the mass of the coking coal is equal to that of ZP 20220402003.
When 300 tons of coking coal are matched with the class 3 silo, and all the coking coal is in the position of 'ZP 20220403004 500 tons plus ZP20220402003 500 tons', the mass of the coking coal is the average value of the mass of ZP20220403004 and the mass of ZP 20220402003. If one or two batches of ZP20220403004 and ZP20220402003 have a certain quality not detected, selecting the detection result of the previous batch according to the corresponding purchase code of the batch.
When 300 tons of coking coal are matched with a 3# silo in shift, at the intersection of 'ZP 20220402003 1585 tons' and 'ZP 20220403004 500 tons+ZP 20220402003 500 tons', 300 is used for more coal at which interface, and the quality of which layer is used first. If 200 tons of the 300 tons are "ZP20220402003 1585 tons" and 100 tons are "ZP20220403004 500 tons+zp 20220402003 500 tons", the 300 tons mass is the mass of "ZP20220402003 1585 tons". The mass distribution diagram of a specific coal bunker is shown in fig. 3.
5. And a coke quality prediction module. The coke quality prediction is carried out by the module based on the actual coal blending performance and coking coal quality module, so that the coke prediction quality is obtained and is compared with the actual coke quality.
The module predicts coke quality based on coal blending performance and coking coal quality tracking, and maintains relevant key parameters in the prediction process, such as ash conversion coefficient and sulfur conversion coefficient of coking coal and coke, and the corresponding relation between coal blending time and different index detection time of coke. After the blending is finished, the blending coal is subjected to cycle time of coal tower storage, coke formation by carbonization in a coke oven, dry quenching, sampling, sample preparation, test and the like to make a corresponding relation between the blending end and coke detection quality time, and the corresponding relation is compared according to a corresponding time difference. If the early 4 th year 2022 is finished, the detection result time of the ash content, sulfur content, grain fraction, M40, M10 and the like of the coke is 2022, 4 th year, 6 th day, early work and the detection result time of the thermal strength of the coke is 2022, 4 th month, 7 th day, early work after the period use time of coal tower storage, coking, dry quenching, sampling, sample preparation, detection and the like. The comparison of the predicted quality of the coke and the actual detection quality can be obtained by aiming at the time difference.
The present embodiment provides the following examples for illustration:
1. the silo receives and transmits the storage inquiry. Inquiring the 3# silo receiving and storing report form of 2022, 4 months and 4 days, and obtaining the 3# silo receiving and storing report form, as shown in table 3:
TABLE 3 Table 3
| Date of day | Feed time | Coal type | Group lot number | Quantity to be stored | Amount of the mixture | Stock quantity | Adjustment amount | Coal tower number |
| 20220402 | 12:20 | Coking coal A | ZP20220402003 | 3871 | 6516 | |||
| 20220402 | 16:50 | 778 | 5738 | B | ||||
| 20220403 | 9:30 | 651 | 5087 | C | ||||
| 20220403 | 12:10 | 4587 | -500 | |||||
| 20220403 | 13:45 | 475 | 4112 | A | ||||
| 20220403 | 15:20 | Coking coal A | ZP20220403004 | 1719 | 5831 | |||
| 20220403 | 20:30 | Coking coal B | ZP20220403009 | 867 | 6698 | |||
| 20220403 | 22:25 | 502 | 6196 | A | ||||
| 20220404 | 1:10 | Coking coal C | ZP20220404001 | 2270 | 8466 | |||
| 20220404 | 2:36 | 546 | 7920 | C | ||||
| 20220404 | 8:30 | 740 | 7180 | B | ||||
| 20220404 | 12:05 | 7480 | 300 | |||||
| 20220404 | 15:12 | Coking coal A | ZP20220404010 | 1885 | 9365 | |||
| 20220404 | 17:45 | 539 | 8826 | A |
2. And dynamically inquiring the materials in the cylinder bin. The distribution condition of coking coal in the 3# silo can be known by inquiring a dynamic model diagram of the material in the 3# silo in 2022, 4 and 4 days shown in fig. 2.
3. Inquiring the actual results of coal blending. The actual coal blending ratio condition can be inquired, and the actual coal blending ratio is different from the theoretical coal blending ratio. Table 4 shows the actual proportioning performance screen under the condition of inquiring the manufacturing code and date, and table 5 shows the actual proportioning execution condition of the coal tower number C in table 4.
TABLE 4 Table 4
| Coal tower number | Batching plan number | Time of effectiveness | Stockline | Start-up time | Stop time |
| A | LJ2021010431 | 2021-01-18 21:34 | H101/H103 | 2021-01-19 04:54 | 2021-01-19 07:52 |
| B | LJ2021010429 | 2021-01-18 21:34 | H102/H104 | 2021-01-19 07:18 | 2021-01-19 08:35 |
| C | LJ2021010430 | 2021-01-18 21:34 | H102/H104 | 2021-01-19 02:14 | 2021-01-19 04:21 |
| B | LJ2021010429 | 2021-01-18 21:34 | H101/H103 | 2021-01-18 21:50 | 2021-01-18 22:46 |
| A | LJ2021010431 | 2021-01-18 21:34 | H102/H104 | 2021-01-19 21:45 | 2021-01-19 23:25 |
| A | LJ2021010421 | 2021-01-14 22:36 | H101/H103 | 2021-01-18 14:20 | 2021-01-18 15:50 |
TABLE 5
Note that: 1) -1% or more and 1% or less of the ratio difference, and displaying normally; 2) The proportion difference is more than or equal to 1 percent and less than or equal to 2 percent, the proportion difference is more than or equal to-2 percent and less than or equal to-1 percent, and the yellow color is displayed; 3) The proportion difference is more than 2 percent, the proportion difference is less than-2 percent, and the red color is displayed.
4. And (5) tracking and inquiring the actual coal blending performance and the quality of coking coal. The actual coal blending ratio and the blending quality information of each silo can be inquired.
As shown in Table 6
TABLE 6
5. Coke quality prediction and comparison query. The predicted daily coal blending coke quality value can be known by inquiring the page and is compared with the actual quality.
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 (3)
1. A silo coal blending coke quality prediction system is characterized in that: comprising the following steps:
the silo receiving and storing module is used for carrying out silo receiving and storing inquiry and management;
the coal blending actual score inquiry module is used for carrying out comparison analysis on the planned coal blending ratio and the actual coal blending ratio of the ingredients;
the in-silo material dynamic tracking module is used for dynamically tracking the total stock, variety and weight distribution condition of coking coal in the silo;
the coking coal quality module is used for correlating the actual coal blending performance with the quality of the coking coal used in shift or daily blending and is used as basic data for coke quality prediction;
the coke quality prediction module is used for predicting the coke quality based on the coal blending performance and the coking coal quality module to obtain coke prediction quality and comparing the coke prediction quality with the actual coke quality; the coal blending actual score inquiring module respectively calculates and inquires the planned coal blending ratio and the actual coal blending ratio of each silo for each blending or accumulated blending according to the shift, day or coal tower number; the planned coal blending ratio is compared with the actual coal blending ratio, and statistical query analysis is carried out according to the silo number or according to the coking coal variety;
the coal blending actual score inquiry module tracks the coal blending actual score and comprises:
single silo batching actual results: inquiring actual blending histories according to date, shift and tower number inquiring conditions, inquiring the weight of each blending under corresponding conditions, actual score blending ratio, planned blending ratio and difference between actual score blending ratio and planned blending ratio, and reminding when the difference between actual score blending ratio and planned blending ratio reaches a certain range;
accumulating silo batching actual results: inquiring accumulated ingredients under the selected conditions according to the date, shift and coal tower number inquiring conditions; inquiring the planned coal blending ratio, the accumulated coal blending amount and the accumulated actual result ratio under the selected condition; if the batching plan numbers of the planned coal blending ratios under the inquiry condition are consistent, the planned coal blending ratios are correspondingly displayed, and if a plurality of batching plan numbers exist, each batching plan number displays the planned coal blending ratio respectively;
single variety (manufacturing code) batching actual results: inquiring actual results of single-variety ingredients under the selected conditions according to date, shift and tower number inquiring conditions, inquiring weight of each ingredient under the corresponding conditions, actual result coal blending ratio, planned coal blending ratio, and difference between actual result ratio and planned coal blending ratio, and reminding when the difference between actual result ratio and planned coal blending ratio reaches a certain range;
accumulating single variety (manufacturing code) batching actual results: inquiring accumulated ingredients under the selected conditions according to the date, shift and tower number inquiring conditions, and inquiring the planned coal blending ratio, the accumulated coal blending amount and the accumulated actual score ratio under the selected conditions; if the batching plan numbers of the planned coal blending ratios under the inquiry condition are consistent, the planned coal blending ratios are correspondingly displayed, and if a plurality of batching plan numbers exist, each batching plan number displays the planned coal blending ratio respectively;
the material dynamic tracking module in the silo calculates the distribution condition of coking coal in the silo according to the total stock of the coal silo and the sequence of the varieties and the weights of the coking coal entering the silo; meanwhile, when the coking coal distribution situation is displayed, according to the coking coal quality associated with the batch numbers, if the coking coal quality exceeds the limit standard requirement, displaying index items and numerical values of the exceeding limit indexes in a coking coal distribution picture in the silo, and carrying out early warning and forecasting;
and the material dynamic tracking module in the silo performs backward pushing according to the sequence of the silo with the total stock of the silo as a reference, the amount of each time of the silo is one coal seam, backward pushing calculation is performed from the last silo feeding, the last silo feeding amount is subtracted, and the last silo feeding amount is not less than the silo stock.
2. The silo-blended coal coke quality prediction system of claim 1, wherein: the silo receiving and storing module is specifically used for:
1) When a coking coal acquisition and purchase factory enters a silo, recording the silo entering time, the silo entering variety, the silo entering weight and the silo entering group batch number information in a silo receiving and storing module;
2) After each material mixing of the silo is finished, the silo receiving and storing module displays the silo discharging time and discharging weight information;
3) The silo receiving and dispatching storage module displays silo storage quantity, and the silo storage quantity is obtained by calculation according to silo storage, silo entering weight and silo distributing weight;
4) The silo receiving and storing module is also used for manually adjusting when the actual weight of the silo is greatly different from the number of the silo systems after the silo inventory is developed;
5) In the silo receiving and storing module, the blending time and the weight are correspondingly blended into the number of the coal tower, so that the association between coking coal blending and the coal tower is realized.
3. The silo-blended coal coke quality prediction system of claim 1, wherein: the key parameters in the prediction process of the coke quality prediction module comprise ash conversion coefficients and sulfur conversion coefficients of coking coal and coke, and the corresponding relation between the coal blending time and the detection time of different indexes of the coke; after the coal blending is finished, the coal blending is stored in a coal tower, carbonized into coke in a coke oven, dry quenched, sampled and tested, and the test period time is used for making a corresponding relation between the end of the coal blending and the coke detection quality time, and then the corresponding relation is compared according to the corresponding time difference.
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2012103600A2 (en) * | 2011-02-01 | 2012-08-09 | Global Ispat Koksna Industrija D.O.O. Lukavac | Coal blend models for determining coke quality |
| CN102756925A (en) * | 2012-07-26 | 2012-10-31 | 中国神华能源股份有限公司 | Silo-based coal blending control system and method |
| CN103454395A (en) * | 2013-08-23 | 2013-12-18 | 安阳钢铁股份有限公司 | Coke quality prediction method in coal silo mode |
| CN103853915A (en) * | 2014-01-14 | 2014-06-11 | 辽宁科技大学 | Method for predicting coke quality through coking coal nonlinear optimization coal blending |
| KR101500180B1 (en) * | 2013-10-29 | 2015-03-06 | 주식회사 포스코 | Silo system |
| CN104773528A (en) * | 2015-01-22 | 2015-07-15 | 浙江华电电站设备有限公司 | Accurate coal blending system of silo and coal blending method of accurate coal blending system |
| CN104951849A (en) * | 2015-06-19 | 2015-09-30 | 武汉钢铁(集团)公司 | Prediction method of coke thermal performance |
| CN105584852A (en) * | 2015-09-10 | 2016-05-18 | 北京金日新事业技术有限公司 | Automatic control system and method for different material layers of stored materials of large-diameter silo |
| CN112027708A (en) * | 2020-08-31 | 2020-12-04 | 山东钢铁集团日照有限公司 | Large-diameter silo uniform blanking and coal blending device and method |
-
2022
- 2022-06-27 CN CN202210829314.7A patent/CN114955586B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2012103600A2 (en) * | 2011-02-01 | 2012-08-09 | Global Ispat Koksna Industrija D.O.O. Lukavac | Coal blend models for determining coke quality |
| CN102756925A (en) * | 2012-07-26 | 2012-10-31 | 中国神华能源股份有限公司 | Silo-based coal blending control system and method |
| CN103454395A (en) * | 2013-08-23 | 2013-12-18 | 安阳钢铁股份有限公司 | Coke quality prediction method in coal silo mode |
| KR101500180B1 (en) * | 2013-10-29 | 2015-03-06 | 주식회사 포스코 | Silo system |
| CN103853915A (en) * | 2014-01-14 | 2014-06-11 | 辽宁科技大学 | Method for predicting coke quality through coking coal nonlinear optimization coal blending |
| CN104773528A (en) * | 2015-01-22 | 2015-07-15 | 浙江华电电站设备有限公司 | Accurate coal blending system of silo and coal blending method of accurate coal blending system |
| CN104951849A (en) * | 2015-06-19 | 2015-09-30 | 武汉钢铁(集团)公司 | Prediction method of coke thermal performance |
| CN105584852A (en) * | 2015-09-10 | 2016-05-18 | 北京金日新事业技术有限公司 | Automatic control system and method for different material layers of stored materials of large-diameter silo |
| CN112027708A (en) * | 2020-08-31 | 2020-12-04 | 山东钢铁集团日照有限公司 | Large-diameter silo uniform blanking and coal blending device and method |
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