CN108170176B - SiO in finished ball2Content control method - Google Patents
SiO in finished ball2Content control method Download PDFInfo
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- CN108170176B CN108170176B CN201711392868.0A CN201711392868A CN108170176B CN 108170176 B CN108170176 B CN 108170176B CN 201711392868 A CN201711392868 A CN 201711392868A CN 108170176 B CN108170176 B CN 108170176B
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- 238000000034 method Methods 0.000 title claims abstract description 21
- 239000000203 mixture Substances 0.000 claims abstract description 33
- 238000003556 assay Methods 0.000 claims abstract description 4
- 239000000463 material Substances 0.000 claims description 30
- VYPSYNLAJGMNEJ-UHFFFAOYSA-N silicon dioxide Inorganic materials O=[Si]=O VYPSYNLAJGMNEJ-UHFFFAOYSA-N 0.000 claims description 25
- 229910052681 coesite Inorganic materials 0.000 claims description 14
- 229910052906 cristobalite Inorganic materials 0.000 claims description 14
- 239000000377 silicon dioxide Substances 0.000 claims description 14
- 229910052682 stishovite Inorganic materials 0.000 claims description 14
- 229910052905 tridymite Inorganic materials 0.000 claims description 14
- 238000013329 compounding Methods 0.000 claims 1
- 239000008188 pellet Substances 0.000 abstract description 5
- 239000002245 particle Substances 0.000 abstract description 4
- 206010063385 Intellectualisation Diseases 0.000 abstract description 2
- 238000003908 quality control method Methods 0.000 abstract description 2
- 239000000843 powder Substances 0.000 description 16
- 235000012239 silicon dioxide Nutrition 0.000 description 11
- 238000004519 manufacturing process Methods 0.000 description 4
- 239000011159 matrix material Substances 0.000 description 2
- 229910004298 SiO 2 Inorganic materials 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000003111 delayed effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000007599 discharging Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D11/00—Control of flow ratio
- G05D11/02—Controlling ratio of two or more flows of fluid or fluent material
- G05D11/13—Controlling ratio of two or more flows of fluid or fluent material characterised by the use of electric means
- G05D11/139—Controlling ratio of two or more flows of fluid or fluent material characterised by the use of electric means by measuring a value related to the quantity of the individual components and sensing at least one property of the mixture
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
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- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- General Physics & Mathematics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Medical Informatics (AREA)
- Software Systems (AREA)
- Evolutionary Computation (AREA)
- Health & Medical Sciences (AREA)
- Artificial Intelligence (AREA)
- Feedback Control In General (AREA)
- Control Of Conveyors (AREA)
- Apparatuses For Bulk Treatment Of Fruits And Vegetables And Apparatuses For Preparing Feeds (AREA)
Abstract
SiO in finished ball2A content control method belongs to the technical field of closed-loop automatic control of pellet quality. The invention provides a novel fuzzy control method for overcoming feedforward disturbance. The invention comprises the following steps: 1) finding out the mixture components corresponding to the current assay components through the process flow and the dynamic storage calculation; 2) finding out various species components and actual blanking proportion of a certain batch according to particle tracking; 3) comparing the mixture component obtained in step 2) with a target mixture component to obtain an effective difference value; 4) effective difference and influence factor calculated by 3) and SiO in the finished ball2Calculating a fuzzy deviation value according to the deviation of the content and the target value and the influence factor; 5) and converting the fuzzy deviation value into a species ratio change value to be adjusted according to manual adjustment experience. The invention realizes the SiO in the finished ball2The accurate closed-loop control of the content improves the automation and intellectualization level of the quality control of finished balls.
Description
Technical Field
The invention belongs to the technical field of closed-loop automatic control of pellet quality, and particularly provides a novel fuzzy control method for overcoming feedforward disturbance.
Background
The stability of the content of SiO2 in the finished ball is used as an assessment index of a pellet production enterprise, due to the particularity of the production process, N hours are needed from pre-batching to finished ball production, a typical large hysteresis link is adopted, and the existing control means completely depends onThe artificial experience is high in randomness, and the control effect needs to be improved. Influence on SiO in finished ball2The factors of content change are many and are classified into two types, namely the component factors of the first material, whether the component assay is accurate or not and whether the application is in time or not; and whether the blanking amount of the second type of blanking equipment is accurate or not. How to quickly and accurately control the content of SiO2 in the finished ball is not seen in practical application, the invention provides a novel fuzzy control method for overcoming feedforward disturbance, and the method is applied in practice, so that the content of SiO2 in the finished ball is effectively stabilized.
The feedforward vector effectively overcomes the deviation caused by the fluctuation of components and material quantity, and the feedback vector effectively overcomes the system deviation, and the difficult points are the determination of the feedforward quantity and the time sequence, the determination of the influence factors of the feedforward quantity and the feedback quantity, and the determination of the fuzzy control matrix. The method mainly comprises the following steps: 1) particle tracking model: finding out the mixture components corresponding to the current assay components through the process flow and the dynamic storage calculation; 2) and (3) calculating the components of the mixture: finding out various species components and actual blanking proportion of a certain batch according to particle tracking; 3) determination of feed forward amount: comparing the mixture component obtained in step 2) with a target mixture component to obtain an effective difference value; 4) calculating a fuzzy difference value: effective difference and influence factor calculated by 3) and SiO in the finished ball2Calculating a fuzzy deviation value according to the deviation of the content and the target value and the influence factor; 5) fuzzy control matrix and proportioning adjustment: and converting the fuzzy deviation value into a species ratio change value to be adjusted according to manual adjustment experience. The invention realizes the SiO in the finished ball2The accurate closed-loop control of the content improves the automation and intellectualization level of the quality control of finished balls.
Disclosure of Invention
The invention aims to provide SiO in a finished ball2A content control method belongs to the technical field of closed-loop automatic control of pellet quality, and particularly relates to a novel fuzzy control method for overcoming feedforward disturbance.
SiO in the finished ball2The content control method comprises the following operation steps:
the method comprises the following steps: calculating the actual mixture ratio: calculating the actual weight of each material (2-4 types) in the charging period by tracking the charging starting time of the mixing bin (No. 9-11), and calculating the actual proportion;
step two: dynamically tracking the change of storage and calculating the time when new materials come out from a mixing bin according to the blanking amount and the blanking starting time of the No. 9-11 bins;
step three: calculating the SiO of the mixture according to the starting time of the new material (if the time is N hours and M minutes), the actual mixture ratio and the material components2Content (c);
step four: calculating the lingering time through the process flow and the running speed of each part, and finally calculating the time when the mixture becomes a finished ball, wherein if the lingering time is N + N hours, M + M minutes;
step five: the test result from the finished ball to the finished ball needs to be delayed for n1 hours and m1 minutes; calculating feed forward amount, obtaining test result of finished ball in N + N + N1 hours and M + M + M1 minutes, and comparing the SiO of the mixture at the moment2The deviation of the content from N hours and M minutes and the influence factor obtain the deviation E of the feedforward quantity1。
Step six: obtaining the feedback quantity deviation E through the finished product spheroidization test components, the target components and the influence factors2。
Step seven: by E1、E2A blur deviation E and a variation DE are formed.
Blur deviation E ═ k × E1+(1-k)*E2Wherein k is a proportionality coefficient between 0 and 1, i.e. a weight.
DE＝EAt present-ELast timeIn the formula EAt presentRepresenting the deviation of this time, ELast timeRepresenting the last deviation.
Step eight: determining the maximum amount P0 of allowable variation of material ratio, and dividing P0 into L grades, then P { -P0, - (L-1)/L × P0, - (L-2)/L × P0, …, 0, …, (L-2)/L × P0, (L-1)/L × P0, P0}, setting the maximum deviation E0, the maximum variation DE0, E { -E0, - (L-1)/L × E0, - (L-2)/L × E0, …, 0, …, (L-2)/L × E0, (L-1)/L × E0, E0 }, DE { -DE 0, - (L-1)/L × DE0, - (L-2)/L × DE0, …, 0, …, (L-2)/L DE0, (L-1)/L DE0, DE 0}, and a plurality of sections are divided according to the E, DE set, and the sections are normalized to be e { -1, - (L-1)/L, - (L-2)/L, …, 0, …, (L-2)/L1, (L-1)/L1, 1}, DE { -1, - (L-1)/L, - (L-2)/L, …, 0, …, (L-2)/L1, (L-1)/L1, 1}, and P ═ P0 ═ e + DE), wherein r is-0.5. The concrete results are as follows
Fuzzification processing, namely selecting the value of the set P closest to the value P as the ratio variation.
The invention has the beneficial effects that: can realize the SiO of the finished ball2The automatic closed-loop control of the content improves the automation and intelligence level of the pellet production.
Drawings
Fig. 1 is a flow chart of actual mixture ratio calculation according to the present invention.
FIG. 2 is a flow chart of the calculation of the time for changing the mixture into finished balls.
FIG. 3 is a logic diagram for implementing the system of the present invention.
Detailed Description
In order to make the aforementioned and other features and advantages of the invention more comprehensible, the invention provides the following detailed description taken in conjunction with the accompanying drawings and specific examples:
step 1: calculating the actual mixture ratio: the change of the materials in the bin is dynamically tracked through a particle tracking model, and the basic principle is that the change of the bin is dynamically calculated according to the bin position, the blanking amount, the loading time and other data and the difference of the materials entering and exiting through data acquisition (a little knowledge is supplemented, the loading process is discontinuous, and the blanking process is continuous). Taking the bin No. 9 as an example, when a discharge valve (plough) on the bin is opened, the bin position (for example, 120) of the bin is recorded, the blanking flow, the loading time (if the loading time is 2017/8/101:10), the loading type (processed powder 99, Peru powder 102) and the type components are calculated, when the accumulated value of the blanking amount is larger than the original bin position value through the period (1 minute), the use of a new material is indicated, the actual blanking amount of the processed powder and the Peru powder at the moment is calculated, the actual proportioning is calculated through the actual blanking amount, as shown in the table I, when 2017/8/101: 28, the accumulated blanking amount 119 is calculated, and the processed powder in the loading amount is 21.3 and 178.5; when 2017/8/101: 29 is calculated, the blanking amount 126 is accumulated, the processing powder in the feeding amount is 22.8, 189, so 2017/8/101: 29 is the starting time of the blanking amount, and the actual mixture ratio of the processing powder to the Peru powder is as follows: 10.76: 89.24.
table-9 storehouse feeding recording information table
| Serial number | Time of day | Status of state | Position of a warehouse | Amount of feed | Processing powder | Peru powder |
| 1 | 2017/8/10 1:10 | Start of loading | 120.0 | 33578.0 | 1170.0 | 10530.0 |
| 2 | 2017/8/101:11 | Feeding material | 124.6 | 33585.0 | 1171.2 | 10540.5 |
| 3 | 2017/8/10 1:12 | Feeding material | 129.3 | 33592.0 | 1172.3 | 10551.0 |
| 4 | 2017/8/10 1:13 | Feeding material | 133.9 | 33599.0 | 1173.5 | 10561.5 |
| … | Feeding material | |||||
| 18 | 2017/8/10 1:27 | Feeding material | 194.6 | 33690.0 | 1190.0 | 10698.0 |
| 19 | 2017/8/10 1:28 | Feeding material | 199.2 | 33697.0 | 1191.3 | 10708.5 |
| 20 | 2017/8/10 1:29 | Feeding material | 203.9 | 33704.0 | 1192.8 | 10719.0 |
| 21 | 2017/8/10 1:30 | Feeding material | 208.5 | 33711.0 | 1194.0 | 10729.5 |
Step 2: calculating the new material discharging time:
according to the information in Step1, firstly, a feeding start mark is found, an initial bin position, an initial feeding amount, initial processing powder and initial Peru powder are recorded, then, the calculation is carried out once per cycle, and when the calculated accumulated feeding amount is larger than the initial bin position value, the current time is recorded as the new material starting time.
The accumulated blanking amount is the current accumulated blanking amount-initial blanking amount;
step 3: mixture SiO2And (3) calculating the content:
according to the actual mixture ratio obtained in Step1 and the new material starting time obtained in Step2, inquiring a corresponding database to find out the components corresponding to the corresponding materials (the processed powder and the Peru powder), such as:
table two 9 bin mix information
The calculation formula is as follows:
mixture SiO2The content is actual ratio of SiO2 content of the processed powder and SiO2 content of Peru powder;
step 4: calculating the moment when the mixture becomes finished balls:
a flow chart for calculating the time for changing the mixture into finished balls (figure 2);
t1 and T3 can be respectively calculated according to the warehousing and blanking speeds, T2, T5, T7 and T8 can be respectively calculated according to the belt speed and the trolley speed, and T3, T6 and the whole delay time T can be estimated according to the process experience;
T＝t1+t2+t3+t4+t5+t6+t7+t8；
step 5: calculation of feedforward amount E1:
the SiO2 content of the mixture corresponding to the current finished ball is obtained through steps 1-4, and then the deviation E1 of the SiO2 content of the mixture is calculated according to the SiO2 content and the influence factors of the current mixture, wherein the calculation formula is as follows:
e1 ═ SiO2 content of current mix-SiO 2 content of mix before time T ═ impact factor;
step 6: calculation of feedback E2:
calculating the deviation E2 according to the test value, the target value and the influence factor of the finished ball, wherein the calculation formula is as follows:
e2 (target value of finished ball SiO2 content-test value of finished ball SiO2 content) × influence factor;
step 7: a fuzzy deviation E and a variable DE;
the blur deviation E and the variation DE are obtained at steps 6 and 7.
Step 8: the coefficient (weight) in the fuzzy deviation formula is the core of the invention, the meanings of the coefficients from 0 to 1 are different, the feedback control in the traditional sense is adopted when the coefficient is 0, the feedforward control is adopted when the coefficient is 1, the mixed deviation fuzzy control is adopted when the coefficient is a number between (0 and 1), and each factory can properly select the coefficient according to the actual condition.
Step 9: the specific process of proportioning dynamic adjustment, including selecting material species and other parameters, is determined according to the actual conditions of various plants.
Step 10: for a simple and practical fuzzy controller, each plant can put L to a number of 3, 4, 5 or more according to its actual situation.
Claims (1)
1. SiO in finished ball2The content control method is characterized by comprising the following steps:
step one, calculating the actual mixture ratio of the mixture: calculating the actual weight of each material in the charging period by tracking the charging starting time of the compounding bin, and calculating the actual proportion;
step two, dynamically tracking the change of storage and predicting the moment when new materials come out of the mixing bin according to the blanking amount of the mixing bin and the blanking starting time;
step three, calculating the SiO of the mixture according to the starting time of the new material, the actual mixture ratio and the material components2Content (c);
step four, calculating the lingering time through the process flow and the running speed of each part, and finally calculating the moment when the mixture becomes a finished ball;
step five, comparing the mixture SiO at the moment of the test result of the finished ball2The deviation of the content from the start of the new material and the influence factor are used to obtain the deviation E of the feedforward quantity1；E1Not ═ SiO of current mix2SiO mixed material before content-T moment2Content) influencing factor;
step six, obtaining the feedback quantity deviation E through the finished product spheroidization test components, the target components and the influence factors2；E2(finished ball SiO)2Content target value-finished ball SiO2Assay value) influence factor;
step seven, passing through E1、E2Forming a fuzzy deviation E and a variable DE; blur deviation E ═ k × E1+(1-k)*E2Wherein k is a proportionality coefficient between 0 and 1; DE ═ EAt present-ELast timeIn the formula EAt presentRepresenting the deviation of this time, ELast timeRepresents the last deviation;
step eight, determining the maximum amount P of allowable change of material ratio0A 1 is to P0Splitting into L range, then P { -P {0，-(L-1)/L*P0，-(L-2)/L*P0，…，0，…，(L-2)/L*P0，(L-1)/L*P0，P0}, setting the maximum deviation E0Maximum change amount DE0，E＝{-E0，-(L-1)/L*E 0，-(L-2)/L*E 0，…，0，…，(L-2)/L*E 0，(L-1)/L*E 0，E 0}，DE＝{-DE 0，-(L-1)/L*DE 0，-(L-2)/L*DE 0，…，0，…，(L-2)/L*DE 0，(L-1)/L*DE 0，DE 0Dividing the intervals according to E, DE sets, and normalizing the intervals into e { -1, - (L-1)/L, - (L-2)/L, …, 0, …, (L-2)/L1, (L-1)/L1, 1}, de { -1, - (L-1)/L, - (L-2)/L, …, 0, …, (L-2)/L1, (L-1)/L1, 1}, P ═ r { -P0(e + de), wherein r ═ -0.5;
fuzzification processing, namely selecting the set P value closest to the P value as the ratio variation.
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Citations (4)
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|---|---|---|---|---|
| JPH1017946A (en) * | 1996-06-27 | 1998-01-20 | Nkk Corp | Method for controlling moisture in sintering raw material |
| JPH11236629A (en) * | 1998-02-23 | 1999-08-31 | Nippon Steel Corp | Method for controlling blasting quantity of cooler for sintered ore |
| CN101949652A (en) * | 2010-09-28 | 2011-01-19 | 中南大学 | Hot air temperature and sintering trough point temperature coordinated control method based on satisfactory optimization |
| CN103397171A (en) * | 2013-08-20 | 2013-11-20 | 中冶赛迪工程技术股份有限公司 | Method for determining furnace-temperature set value of billet heating furnace |
-
2017
- 2017-12-21 CN CN201711392868.0A patent/CN108170176B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH1017946A (en) * | 1996-06-27 | 1998-01-20 | Nkk Corp | Method for controlling moisture in sintering raw material |
| JPH11236629A (en) * | 1998-02-23 | 1999-08-31 | Nippon Steel Corp | Method for controlling blasting quantity of cooler for sintered ore |
| CN101949652A (en) * | 2010-09-28 | 2011-01-19 | 中南大学 | Hot air temperature and sintering trough point temperature coordinated control method based on satisfactory optimization |
| CN103397171A (en) * | 2013-08-20 | 2013-11-20 | 中冶赛迪工程技术股份有限公司 | Method for determining furnace-temperature set value of billet heating furnace |
Non-Patent Citations (4)
| Title |
|---|
| BTP prediction of sintering process by using multiple models;Jialin Wang等;《The 26th Chinese Control and Decision Conference》;20140714;全文 * |
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