CN111994650A - Full-automatic feeding method for rapid quantitative loading station - Google Patents

Full-automatic feeding method for rapid quantitative loading station Download PDF

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Publication number
CN111994650A
CN111994650A CN202010823478.XA CN202010823478A CN111994650A CN 111994650 A CN111994650 A CN 111994650A CN 202010823478 A CN202010823478 A CN 202010823478A CN 111994650 A CN111994650 A CN 111994650A
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fuzzy
stock
bin
buffer bin
change
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武徽
肖雅静
张新
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Tiandi Science and Technology Co Ltd
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Tiandi Science and Technology Co Ltd
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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
    • 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

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  • Mechanical Engineering (AREA)
  • Control Of Conveyors (AREA)

Abstract

The invention relates to a full-automatic feeding method for a rapid quantitative loading station, which comprises the following steps: establishing a fuzzy set of deviation of the material stock of the buffer bin; establishing a buffer bin material stock change fuzzy set; establishing a control quantity fuzzy set; making a fuzzy rule; setting boundary conditions of fuzzy decision; and controlling and setting the fuzzy control residual difference. According to the invention, a fuzzy control principle is slowly utilized, the control and regulation process of the material conveying process is fully automated by establishing the selection deviation and the fuzzy set, the starting and stopping of the feeding machine and the variable-frequency speed regulation of the belt conveyor can be controlled according to the stock and the reduced speed of the material in the buffer bin without manual intervention, the full automation of the feeding is realized, the operation process of the feeding is more scientific and accurate, the manpower and material resources are saved, and the working efficiency is improved.

Description

Full-automatic feeding method for rapid quantitative loading station
Technical Field
The invention relates to a full-automatic feeding method for a quick quantitative loading station, which is an automatic process method of a transport machine and is a batching method for the automatic quantitative loading process of bulk goods.
Background
The traditional system for supplying materials to the buffer bin by the rapid quantitative loading station generally comprises an upper station belt, one end of which is arranged at the top of the buffer bin, the other end of which is connected with a conveying belt of the storage bin, and the storage bin is generally provided with a plurality of feeders. The traditional operation is that a plurality of feeders are continuously started or stopped by observing the material amount in the buffer bin to form the change of the material amount, so that the material in the buffer bin can meet the requirement of loading. In the buffer bin, sensors capable of detecting the stock of materials in the buffer bin are arranged, so that an operator can increase or decrease the input quantity of the materials without depending on experience, and meanwhile, due to the improvement of the belt conveyor, the variable frequency speed regulation is increased, and the conveying of the material quantity of the buffer bin is easier to adjust. Despite these improvements, the operation of adjusting the amount of material delivered is largely influenced by the experience of personnel and human judgment, and fully automated feeding is a problem to be solved.
Disclosure of Invention
In order to overcome the problems in the prior art, the invention provides a full-automatic feeding method for a rapid quantitative loading station. The method utilizes a fuzzy control principle, and fully automates the control and regulation process of the material conveying process by establishing a fuzzy set, thereby realizing the full automation of the feeding.
The purpose of the invention is realized as follows: a full-automatic feeding method for a rapid quantitative loading station comprises the following steps: the method comprises the following steps that an upper station belt conveyor with one end arranged at the top end of a buffering bin of a loading station and the other end connected with a storage bin belt conveyor is arranged, the buffering bin is provided with a material storage amount monitoring sensor, at least two feeders are arranged above the storage bin belt conveyor, and the method comprises the following steps:
step 1, establishing a fuzzy set of material stock deviation of a buffer bin: setting stock deviation E of a buffer bin, dividing the deviation into 5 material deviation stock fuzzy sets according to the difference value between the target stock level and the current stock level of the material stock in the buffer bin as an observed quantity, wherein the empty bin, the low bin, the moderate bin, the high bin and the full bin are empty bins, and the positive and negative of E are that the current stock level is higher than or lower than the target stock level;
step 2, establishing a buffer bin material stock change fuzzy set: setting the stock change rate Ec of the buffer bin, and dividing 5 fuzzy sets of stock change rates according to the stock increase and decrease rate conditions: fast decrease, slow decrease, balance, full increase, fast increase;
step 3, establishing a control quantity fuzzy set: the start and stop of the feeders are used as the controlled variable u, the domains of the four feeders are discrete {0,1,2,3,4}, and a fuzzy set of the controlled variable is obtained correspondingly: 0,1,2,3 and 4;
step 4, formulating a fuzzy rule: formulating a fuzzy rule according to the field condition, and obtaining a fuzzy relation set R through fuzzy set operation according to the formulated fuzzy rule;
step 5, setting the boundary conditions of fuzzy decision: the loading period of the station is T0After the response time T is calculated, the current loading period T cannot be guaranteed0After the completion, the materials in the buffer bin meet the loading of the next vehicle, even under the fuzzy control, the timely feeding can not be realized, and the system of the loading station is required to stop and wait for the materials;
and 6, controlling and setting a fuzzy control residual difference: the feeding machines are opened in different combinations for adjustment, or the feeding amount of the feeding machines is compensated and controlled.
Further, the observation mode of the material increase and decrease rate condition is a weighing judgment method: the change of the materials in the buffer bin is periodically measured through the weighing sensor, whether the time delay occurs in the batching process or not is observed at the current periodic time node, so that the change of the increase and decrease rate of the materials in the buffer bin is judged, the material change in several periods is measured, and the average value of the material change in the several periods is obtained.
Further, the observation mode of the material increase and decrease rate condition is a vehicle speed judgment method: the speed of the train is judged through the sensor, and the improvement and the slowing of the loading speed are judged according to the speed of the train, so that the change of the increase and decrease rate of the materials of the buffer bin is corresponded.
The invention has the advantages and beneficial effects that: according to the invention, a fuzzy control principle is slowly utilized, the control and regulation process of the material conveying process is fully automated by establishing the selection deviation and the fuzzy set, the starting and stopping of the feeding machine and the variable-frequency speed regulation of the belt conveyor can be controlled according to the stock and the reduced speed of the material in the buffer bin without manual intervention, the full automation of the feeding is realized, the operation process of the feeding is more scientific and accurate, the manpower and material resources are saved, and the working efficiency is improved.
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The invention is further illustrated by the following figures and examples.
FIG. 1 is a schematic diagram of a system architecture used in the method according to one embodiment of the present invention;
FIG. 2 is a flowchart of a method according to an embodiment of the present invention.
Detailed Description
The first embodiment is as follows:
the embodiment is a full-automatic feeding method for a rapid quantitative loading station. The feeding system used in the method is shown in figure 1. The feeding system includes: the loading device comprises a conventional loading station provided with a buffer bin, a quantitative bin and a chute, and a long-length belt conveyor for loading. One end of the upper station belt conveyor is arranged at the top end of a buffer bin 101 of the loading station 1, the other end of the upper station belt conveyor 3 is connected with a storage bin belt conveyor 2, the buffer bin is provided with a material storage amount monitoring sensor 4, at least two feeders 5 are arranged above the storage bin belt conveyor, and the feeders convey materials from a material pile 6 to the storage bin belt conveyor. A vehicle speed sensor 8 may be provided near the loading train 7 as necessary. The material storage monitoring sensor can be a video monitor and a material pile height scale, the stacking height of the material pile is detected by manual visual inspection, or the material height is automatically monitored by an image analysis mode. The material storage quantity monitoring sensor can also be a strain sensor arranged on the bearing steel structure frame, and the storage quantity change rate of the materials in the buffer bin are calculated through the deformation of the steel structure frame.
The method of this embodiment includes the following specific steps, and the flow of the method is shown in fig. 2:
step 1, establishing a fuzzy set of material stock deviation of a buffer bin: setting stock deviation E of a buffer bin, dividing the deviation into 5 material deviation stock fuzzy sets according to the difference value between the target stock level and the current stock level of the material stock in the buffer bin as an observed quantity, wherein the empty bin, the low bin, the moderate bin, the high bin and the full bin are empty bins, and the positive and negative of E are that the current stock level is higher than or lower than the target stock level;
in the loading process, the material in the buffer bin is generally controlled to be maintained at the middle upper position of the bin level to be the best, stock deviation E, namely the difference value between the target bin level and the current bin level is selected as an observed quantity, the deviation is divided into 5 material deviation stock fuzzy sets, an empty bin (NB), a low bin (NS), a medium bin (0), a high bin (PS) and a full bin (PB), wherein the E is negative and indicates that the current bin level is lower than the target bin level, and the E is positive and indicates that the current water level is higher than the target bin level.
Step 2, establishing a buffer bin material stock change fuzzy set: setting the stock change rate Ec of the buffer bin, and dividing 5 fuzzy sets of stock change rates according to the stock increase and decrease rate conditions: fast decrease, slow decrease, balance, full increase, fast increase;
because the process principle of the discontinuous accumulation weighing apparatus enables the change of materials unloaded to a vehicle in a loading system to have periodic behavior, the direct measurement of the materials in the silo cannot ensure that the change rate of the materials always reflects the average change condition of the materials in the period. Therefore, the increase and decrease rate of the material is observed by two methods: one method is that whether the time delay occurs in the batching process or not is observed at the current periodic time node, so that the change of the increase and decrease rate of the materials in the buffer bin is judged, and the average value of the material change in several periods is obtained; and the other is that when the train is loaded, the speed of the train is judged through a sensor, and the increase and the decrease of the loading speed are judged according to the speed of the train, so that the loading speed of the train is generally required to be within 1km/h corresponding to the change of the increase and decrease rate of the materials in the buffer bin. It is therefore possible to efficiently provide the fuzzy control range with the boundary value. The train is fast, the corresponding material reduction rate is increased, and the material change rate in the buffer red bin is reduced overall; the train slows down, and the rate of reduction of material diminishes, and the material rate of change in buffering red storehouse increases overall. According to the conversion of the two analysis methods, the two analysis methods must be fuzzified, so that the overall material change rate Ec in the buffer bin can also obtain a fast decrease (NB), a slow decrease (NS), a balance (0), a full increase (PS) and a fast increase (PB). The essence of Ec is the difference between the feed rate into the silo and the discharge rate.
Step 3, establishing a control quantity fuzzy set: the start and stop of the feeders are used as the controlled variable u, the domains of the four feeders are discrete {0,1,2,3,4}, and a fuzzy set of the controlled variable is obtained correspondingly: 0,1,2,3 and 4;
the control u is used in dependence on the feed amount. And selecting the opening degree of a single feeder or the starting number of the total feeders as a control quantity. The opening degree and the feeding amount of the feeding machines are difficult to realize automatic linear control in practical use, so the feeding amount is most commonly controlled by the number of starting and stopping the coal feeder, and the feeding amount does not exceed 4 feeding machines at most under the field use condition as an example. The domain is discrete {0,1,2,3,4}, and the corresponding values are set to obtain 0(NB), 1(NS), 2(0), 3(PS) and 4(PB), and the number of the opened feeders is expressed in a numerical mode.
Step 4, formulating a fuzzy rule: formulating a fuzzy rule according to the field condition, and obtaining a fuzzy relation set R through fuzzy set operation according to the formulated fuzzy rule;
fuzzy rules are formulated according to field experience, the rules are consistent, but the experience is different under different conditions, the corresponding relation is different with the feeding amount and the delay time. The following rule is an example and is not universal:
Figure RE-RE-GDA0002689136320000041
and according to the formulated fuzzy rule, obtaining a fuzzy relation set R through corresponding fuzzy set operation.
U ═ E ≈ Ec) · R. For example, IF (E is 0 and Ec is 0) then u is 0, i.e. 2 feeders are started.
Step 5, setting the boundary conditions of fuzzy decision: the loading period of the station is T0After the response time T is calculated, the current loading period T cannot be guaranteed0After the completion, the materials in the buffer bin meet the loading of the next vehicle, even under the fuzzy control, the timely feeding can not be realized, and the system of the loading station is required to stop and wait for the materials;
the time delay of the feeding system depends on the stationThe speed and length of the belt. And setting the speed of the upper station belt as V and the length as L, and setting the response time of the material after the control change as L/V. The loading period of the station is T0After the response time T is calculated, the current loading period T cannot be guaranteed0After the completion, the materials in the buffer bin meet the loading of the next vehicle, even under the fuzzy control, the timely feeding can not be realized, and the system of the loading station is required to stop and wait for the materials.
Taking the example when Ec has a negative value, the sum of the decrement will affect the total amount of material needed for the subsequent ingredient. Before the material in the buffer bin is consumed, if the Ec cannot be corrected to be a positive value, the future loading process is influenced.
And 6, controlling and setting a fuzzy control residual difference: the feeding machines are opened in different combinations for adjustment, or the feeding amount of the feeding machines is compensated and controlled.
When the difference between the actual equilibrium state and the required equilibrium state exceeds the ideal value, if more feeders are equipped, different combinations can be produced by the feeders to adjust. Through the feeding quantity of recording each batcher at ordinary times, distribute far and near, calculate the most suitable cooperation group and carry out the feed. And secondly, if the feeding machine is an adjustable feeding machine, the feeding machine can be compensated and controlled by properly adjusting the feeding amount.
Example two:
the embodiment is an improvement of the first embodiment, and is a refinement of the observation mode of the material increase and decrease rate condition in the first embodiment, and the observation mode of the material increase and decrease rate condition in the present embodiment is a weighing judgment method: the change of the materials in the buffer bin is periodically measured through the weighing sensor, whether the time delay occurs in the batching process or not is observed at the current periodic time node, so that the change of the increase and decrease rate of the materials in the buffer bin is judged, the material change in several periods is measured, and the average value of the material change in the several periods is obtained.
The weighing sensor can be a strain gauge arranged on the steel structure frame, and the material stock variation in the buffer bin are calculated by sensing the deformation of the steel structure frame when the steel structure frame bears the weight of the material.
The weighing mode of the weighing sensor is periodic, namely weighing is carried out in a selected time period, the change of the materials in the buffer bin is continuous, detection values of a plurality of time periods are required to be obtained for obtaining a continuous change value for average calculation, and then a buffer bin material stock change fuzzy set is formed by utilizing the average change value.
Example three:
the present embodiment is an improvement of the above embodiment, and is a refinement of the observation mode of the material increase and decrease rate condition in the above embodiment, and the observation mode of the material increase and decrease rate condition in the present embodiment is a vehicle speed determination method: the speed of the train is judged through the sensor, and the improvement and the slowing of the loading speed are judged according to the speed of the train, so that the change of the increase and decrease rate of the materials of the buffer bin is corresponded.
The vehicle speed sensor can be a sensor combining laser radar with grating detection, and the detection precision requirement is slightly higher.
The advancing speed of the train during loading means the unloading speed of the quantitative cabin of the loading station to the carriage, the output change condition of the materials can be judged through the vehicle speed change fuzzy set, and then the buffer cabin material stock change fuzzy set is obtained.
Finally, it should be noted that the above only illustrates the technical solution of the present invention, and not by way of limitation, and although the present invention has been described in detail with reference to preferred arrangements, it will be understood by those skilled in the art that modifications or equivalent substitutions can be made to the technical solution of the present invention (such as the form of loading station, the form of storage bin and upper belt conveyor, the sequence of steps, etc.) without departing from the spirit and scope of the technical solution of the present invention.

Claims (3)

1. A full-automatic feeding method for a rapid quantitative loading station comprises the following steps: the method is characterized in that the method comprises the following steps of:
step 1, establishing a fuzzy set of material stock deviation of a buffer bin: setting stock deviation E of a buffer bin, dividing the deviation into 5 material deviation stock fuzzy sets according to the difference value between the target stock level and the current stock level of the material stock in the buffer bin as an observed quantity, wherein the empty bin, the low bin, the moderate bin, the high bin and the full bin are empty bins, and the positive and negative of E are that the current stock level is higher than or lower than the target stock level;
step 2, establishing a buffer bin material stock change fuzzy set: setting the stock change rate Ec of the buffer bin, and dividing 5 fuzzy sets of stock change rates according to the stock increase and decrease rate conditions: fast decrease, slow decrease, balance, full increase, fast increase;
step 3, establishing a control quantity fuzzy set: the start and stop of the feeders are used as the controlled variable u, the domains of the four feeders are discrete {0,1,2,3,4}, and a fuzzy set of the controlled variable is obtained correspondingly: 0,1,2,3 and 4;
step 4, formulating a fuzzy rule: formulating a fuzzy rule according to the field condition, and obtaining a fuzzy relation set R through fuzzy set operation according to the formulated fuzzy rule;
step 5, setting the boundary conditions of fuzzy decision: the loading period of the station is T0After the response time T is calculated, the current loading period T cannot be guaranteed0After the completion, the materials in the buffer bin meet the loading of the next vehicle, even under the fuzzy control, the timely feeding can not be realized, and the system of the loading station is required to stop and wait for the materials;
and 6, controlling and setting a fuzzy control residual difference: the feeding machines are opened in different combinations for adjustment, or the feeding amount of the feeding machines is compensated and controlled.
2. The method according to claim 1, wherein the observation mode of the material increase and decrease rate condition is a weighing judgment method: the change of the materials in the buffer bin is periodically measured through the weighing sensor, whether the time delay occurs in the batching process or not is observed at the current periodic time node, so that the change of the increase and decrease rate of the materials in the buffer bin is judged, the material change in several periods is measured, and the average value of the material change in the several periods is obtained.
3. The method according to claim 1, wherein the observation mode of the material increase and decrease rate condition is a vehicle speed judgment method: the speed of the train is judged through the sensor, and the improvement and the slowing of the loading speed are judged according to the speed of the train, so that the change of the increase and decrease rate of the materials of the buffer bin is corresponded.
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113879866A (en) * 2021-10-25 2022-01-04 中煤科工智能储装技术有限公司 Coal flow conveying method based on traffic flow

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Publication number Priority date Publication date Assignee Title
CN101012836A (en) * 2006-12-29 2007-08-08 杭州电子科技大学 Variable-frequency speed-adjusting energy-saving water pump fuzzy control method
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Publication number Priority date Publication date Assignee Title
CN101012836A (en) * 2006-12-29 2007-08-08 杭州电子科技大学 Variable-frequency speed-adjusting energy-saving water pump fuzzy control method
CN102556629A (en) * 2010-12-08 2012-07-11 浙江霸王衡器有限公司 Intelligent automatic dosing control system

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CN113879866A (en) * 2021-10-25 2022-01-04 中煤科工智能储装技术有限公司 Coal flow conveying method based on traffic flow

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Application publication date: 20201127