CN100546791C - Asphalt mixture stirring equipment cold aggregate feeding control method - Google Patents
Asphalt mixture stirring equipment cold aggregate feeding control method Download PDFInfo
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- CN100546791C CN100546791C CNB2007100209445A CN200710020944A CN100546791C CN 100546791 C CN100546791 C CN 100546791C CN B2007100209445 A CNB2007100209445 A CN B2007100209445A CN 200710020944 A CN200710020944 A CN 200710020944A CN 100546791 C CN100546791 C CN 100546791C
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Abstract
The invention discloses a kind of asphalt mixture stirring equipment cold aggregate feeding control method.This method is that the stone particle specification in each cold aggregate bin of asphalt mixing plant is descending, stone enters main belt conveyor by different feeding belts with different speed, carry out heat drying by main belt conveyor input drying, after arriving suitable temperature, deliver into high building through lifting; At the high building top screening system is arranged, hot aggregate according to prescription metering and a certain proportion of pitch mixing stirring in proportion, obtains asphalt again through obtaining the hot aggregate of six kinds of corresponding different sizes after sieving.The present invention can learn to discern the relation of cold aggregate bin delivery rate and hot aggregate proportioning automatically when asphalt mixing plant moves; Guarantee that the material phenomenon can not appear waiting in hot aggregate storage bin; The temperature accuracy of hot aggregate is reached≤± 4 ℃.
Description
Technical field
The invention belongs to the asphalt mixing plant control technology, particularly a kind of asphalt mixture stirring equipment cold aggregate feeding control method.
Background technology
Asphalt mixing plant all has higher required precision to hot aggregate weight and temperature, in traditional asphalt mixing plant, because how much stone content to all size in the cold aggregate bin does not all have the function of detection automatically, the stone specification that only relying on the stone field provides is carried out feed control as foundation, like this can be because contain the different size stone that quantity does not wait in a kind of stone of specification, when system moves, the feed of cold aggregate is that in accordance with regulations control program carries out, so just may cause occurring the so-called hot aggregate storage bin phenomenon that " waits material ": promptly since cold aggregate bin make a mistake at when filling with substance, perhaps cold aggregate mixes when stacking mutually, cause the stone specification of cold aggregate bin not conform to the data that the stone field provides, according to certain feed control program feed the time, the stone of a certain specification of hot aggregate storage bin can not in time be supplied with, the hot aggregate of this specification just can't measure like this, thereby cause equipment not can normally continuously work, material such as appearance.On the other hand and since do not know in the cold aggregate bin stone specification content what, when causing cold aggregate to enter drying carrying out heat drying, can only use a kind of heating-up temperature to come dried material.Because the actual cold specification of aggregate content that enters drier is in continuous variation, thereby makes the temperature of hot aggregate bigger fluctuation can occur, thereby cause the temperature accuracy of hot aggregate lower, be generally≤± 8 ℃.
Summary of the invention
Goal of the invention of the present invention is to provide a kind of asphalt mixture stirring equipment cold aggregate feeding control method, it is the relation by cold aggregate bin delivery rate of on-line study and hot aggregate proportioning, predict the delivery rate of cold aggregate then, and then improve the hot aggregate temperature precision of asphalt mixing plant, and the hot aggregate storage bin that the solves asphalt mixing plant phenomenon that " waits material ".
The technical solution that realizes the object of the invention is: a kind of asphalt mixture stirring equipment cold aggregate feeding control method may further comprise the steps:
At first, asphalt mixing plant is equipped with a kind of stone of specification size at two or plural cold aggregate bin, the stone of different size enters main belt conveyor by frequency control with different speed by different feeding belts, promptly adopt the BP model on-line prediction self-learning method of human nerve's network, set up the self-identifying scheme that the material quantitative changeization of hot aggregate storage bin is associated with the delivery rate of each cold aggregate bin, the relation of the material quantitative change percentage of online knowledge study hot aggregate storage bin and the delivery rate of cold aggregate bin, predict the feed control of cold aggregate then, the control step of this cold aggregate feeding is:
The first step is set up the self-identifying scheme that the material quantitative changeization of hot aggregate storage bin is associated with the delivery rate of two or more cold aggregate bins, and the controlling level of promptly supposing hot aggregate storage bin is h, and then the weight of hot aggregate is expressed as:
G=ah+bh
2+ ch
3, a wherein, b, c are constant, calculate according to the hot aggregate storage bin structure;
Second step, write down the delivery rate of cold aggregate, cold aggregate is through heating, promote and screening, the hot aggregate of final formation, because what record is the controlling level of hot aggregate, weight formula according to the above-mentioned hot aggregate of controlling level process calculates hot aggregate quality, hot aggregate promptly obtains containing in the cold aggregate actual percentage of this hot aggregate in the recruitment of unit interval divided by the feeding coal of cold aggregate unit interval, so just formed a learning sample, the actual percentage of instant heating aggregate and the delivery rate of cold aggregate, acquisition time equals the final time that forms hot aggregate of cold aggregate, i.e. unit interval at interval; The actual percentage of hot aggregate as input, the delivery rate of cold aggregate is as output, enter the training of learning phase, training method is: by the hot aggregate controlling level of real-time measurement and the feeding coal of cold aggregate, obtain the actual percentage of real-time hot aggregate, when the actual percentage of hot aggregate changed, system can change the connection weights between input layer and the output layer automatically.
Secondly, carry out heat drying by main belt conveyor input drying, after arriving suitable temperature, deliver into high building through lifting, screening system classification at this high building top, hot aggregate is loaded into corresponding hot aggregate storage bin respectively through the hot aggregate that obtains corresponding different size after sieving, and forms new learning sample for the on-line study of human nerve's network;
At last, require the hot aggregate of different size measured in proportion with a certain proportion of pitch according to the asphalt prescription and mix, obtain the asphalt product.
The connection weights size of asphalt mixture stirring equipment cold aggregate feeding control method of the present invention is relevant with the delivery rate of cold aggregate bin by the material quantitative change percentage of hot aggregate storage bin, when the material quantitative change percentage delivery rate big, cold aggregate bin of hot aggregate storage bin is big, it is big then to connect weights; The material quantitative change percentage of hot aggregate storage bin delivery rate little, cold aggregate bin is little, and it is little then to connect weights; Small one and large one then gets intermediate value.It is minimum can making output error like this.
The present invention compared with prior art, its remarkable advantage: (1) has proposed the self study technology of cold aggregate bin aggregate feeding speed in the blending process of asphalt mixing plant, can learn to discern the relation of cold aggregate bin delivery rate and hot aggregate proportioning automatically when asphalt mixing plant moves; (2) relation of equipment when operation on-line study cold aggregate feeding control rate and the controlling level of hot aggregate storage bin is finally controlled the variable-frequency governor of feeding belt, expects phenomenon to guarantee that waiting can not appear in hot aggregate storage bin; (3) according to the heating-up temperature of the aggregate content FEEDFORWARD CONTROL drier of cold aggregate feeding speed and cold aggregate bin, like this temperature accuracy of hot aggregate is reached≤± 4 ℃, improve the efficient of asphalt mixing plant and the quality of product.
Below in conjunction with accompanying drawing the present invention is described in further detail.
Description of drawings
Fig. 1 is the fundamental diagram of asphalt mixing plant of the present invention.
Fig. 2 is the structural representation of the cold aggregate on-line prediction self study of asphalt mixture stirring equipment cold aggregate feeding control method of the present invention.
The specific embodiment
In conjunction with Fig. 1, asphalt mixture stirring equipment cold aggregate feeding control method of the present invention may further comprise the steps:
At first, asphalt mixing plant is at two or plural cold aggregate bin 1,2,3,4,5,6 are equipped with a kind of stone of specification size, the stone of different size enters main belt conveyor 8 by frequency control with different speed by different feeding belt 7, promptly adopt the BP model on-line prediction self-learning method of human nerve's network, set up the self-identifying scheme that the material quantitative changeization of hot aggregate storage bin is associated with the delivery rate of each cold aggregate bin, the relation of the material quantitative change percentage of online knowledge study hot aggregate storage bin and the delivery rate of cold aggregate bin is predicted the feed control of cold aggregate then;
Secondly, carry out heat drying by main belt conveyor input drying 9, after arriving suitable temperature, deliver into high building 11 through lifting, screening system 14 classifications at this high building top, hot aggregate is loaded into corresponding hot aggregate storage bin 13 respectively through the hot aggregate that obtains corresponding different size after sieving, and forms new learning sample for the on-line study of human nerve's network;
At last, according to the asphalt prescription require the hot aggregate of different size measure in proportion 12 and a certain proportion of pitch mix 10, obtain the asphalt product.
Asphalt mixing plant generally has 6 cold aggregate bins, stone particle specification in this each cold aggregate bin is descending, stone enters main belt conveyor 8 by different feeding belt 7 with different speed, carry out heat drying by main belt conveyor 8 input dryings 9, after arriving suitable temperature, deliver into high building through lifting.At the high building top screening system 14 is arranged, hot aggregate according to prescription metering and a certain proportion of pitch mixing stirring in proportion, obtains asphalt again through obtaining the hot aggregate of six kinds of corresponding different sizes after sieving.
The feed control scheme of cold aggregate of the present invention is as follows: at first be the online self study prediction algorithm of BP (BackPropagation) model that adopts human nerve's network, set up the material quantitative changeization and the self-identifying scheme that the delivery rate of six cold aggregate bins is associated of hot aggregate storage bin, the multilayer feedforward neural network model that promptly utilizes error backpropagation algorithm to find the solution.The essence of BP algorithm is to find the solution the minimum problems of error function, because it adopts the gradient descent method (Gradient Descent) in the Non-Linear Programming, press the negative gradient adjustment in direction weights of error function, its main thought is if obtain the target function error of training network:
The BP algorithm is that correspondence is imported each time and all proofreaied and correct weights one time among the present invention, promptly error function is asked partial derivative, can calculate error all are connected the partial derivative of weights, connects weights thereby can utilize the gradient descent method to revise each.
The on-line prediction self-learning algorithm at first needs to carry out the i.e. process of study of obtaining of knowledge.The data of gathering are used for training network as learning sample, compose respectively to network input, output node, by Learning Algorithm sample is learnt, constantly revised weights through the network internal adaptive algorithm, till reaching desired study precision.After training sample training finished, can predict.Because the corresponding content that produces each hot aggregate of each cold aggregate is not fixed, so must online study adjustment constantly connect weights.
The controlling level of supposing hot aggregate storage bin is h, and then the weight of hot aggregate can be expressed as: G=ah+bh
2+ ch
3, a wherein, b, c are constant, can calculate according to the hot aggregate storage bin structure.The self study process: cold aggregate finally forms hot aggregate through heating, lifting and screening.Write down the delivery rate of cold aggregate, and the feeding coal of each cold aggregate is determined, because what record is the controlling level of hot aggregate, can calculate hot aggregate quality according to controlling level through following formula, hot aggregate can obtain containing in the cold aggregate actual percentage of this hot aggregate in the recruitment of unit interval divided by the feeding coal of cold aggregate unit interval.So just formed a learning sample (actual percentage of hot aggregate, the delivery rate of cold aggregate), noticed that their acquisition time equals the final time that forms hot aggregate of cold aggregate, i.e. unit interval at interval.The actual percentage of hot aggregate as input, the delivery rate of cold aggregate is as output, enter the training of the learning phase of Fig. 2 b, training method is: by the hot aggregate controlling level of real-time measurement and the feeding coal of cold aggregate, obtain the actual percentage of real-time hot aggregate, when the actual percentage of hot aggregate changes, system can change the connection weights between input layer and the output layer automatically, and it is relevant with the delivery rate of cold aggregate bin by the material quantitative change percentage of hot aggregate storage bin to connect the weights size.When the material quantitative change percentage delivery rate big, cold aggregate bin of hot aggregate storage bin is big, it is big then to connect weights; The material quantitative change percentage of hot aggregate storage bin delivery rate little, cold aggregate bin is little, and it is little then to connect weights; Small one and large one then gets intermediate value.It is minimum can making output error like this.This process is online continuously.
Cold aggregate feeding control: the material quantitative change percentage of setting hot aggregate storage bin according to the controlling level of hot aggregate storage bin, how many delivery rates of predicting cold aggregate bin by the neutral net of Fig. 2 a should be, connection weights in the neutral net of Fig. 2 a equal the learning outcome of Fig. 2 b, predicting that with former learning outcome the specification that is based on cold aggregate has certain continuous hypothesis prerequisite, is more rational.Cause predicting be not very correct if the specification of cold aggregate changes suddenly, but can overcome this disturbance rapidly, so the adjustment of cold aggregate feeding speed has certain adaptivity by on-line study subsequently.Final variable-frequency governor control cold aggregate feeding speed by the control feeding belt.
The control of the temperature of hot aggregate: according to what of the delivery rate of cold aggregate bin and cold aggregate bin specification of aggregate content can feed-forward regulation oven dry bucket temperature, do not regulate again when waiting until variations in temperature like this, improved the temperature control precision of hot aggregate greatly.
When asphalt mixing plant was worked, the cold aggregate feeding device adopted variable frequency regulating speed control, step-less adjustment speed.At first by the percentage of operator in the use of computer input aggregate prescription.When each entire equipment entry into service starts, the cold aggregate feeding device is by predefined order, start respectively one by one, by above-described " the on-line study prediction scheme that the material quantitative changeization of hot aggregate storage bin is associated with the delivery rate of six cold aggregate bins " cold aggregate feeding speed is realized control automatically, specifically: according to the relation of cold aggregate bin delivery rate and hot aggregate proportioning, the variable-frequency governor of final control feeding belt the material phenomenon can not occur waiting to guarantee hot aggregate storage bin.The temperature of hot aggregate control scheme: according to the self-identifying result of the delivery rate of cold aggregate, cold aggregate bin aggregate content obtain various building stones component ratio what, with this temperature of control drier in real time.Temperature according to how many feed-forward regulation oven dry buckets of the delivery rate of cold aggregate bin and cold aggregate bin specification of aggregate content to improve the temperature control precision of hot aggregate, reaches the temperature accuracy of hot aggregate≤± 4 ℃.
Claims (4)
1, a kind of asphalt mixture stirring equipment cold aggregate feeding control method may further comprise the steps:
At first, asphalt mixing plant is equipped with a kind of stone of specification size at two or plural cold aggregate bin, the stone of different size enters main belt conveyor by frequency control with different speed by different feeding belts, promptly adopt the BP model on-line prediction self-learning method of human nerve's network, set up the self-identifying scheme that the material quantitative changeization of hot aggregate storage bin is associated with the delivery rate of each cold aggregate bin, the relation of the material quantitative change percentage of online knowledge study hot aggregate storage bin and the delivery rate of cold aggregate bin, predict the feed control of cold aggregate then, the control step of this cold aggregate feeding is:
The first step is set up the self-identifying scheme that the material quantitative changeization of hot aggregate storage bin is associated with the delivery rate of two or more cold aggregate bins, and the controlling level of promptly supposing hot aggregate storage bin is h, and then the weight of hot aggregate is expressed as: G=ah+bh
2+ ch
3, a wherein, b, c are constant, calculate according to the hot aggregate storage bin structure;
Second step, write down the delivery rate of cold aggregate, cold aggregate is through heating, promote and screening, the hot aggregate of final formation, because what record is the controlling level of hot aggregate, weight formula according to the above-mentioned hot aggregate of controlling level process calculates hot aggregate quality, hot aggregate promptly obtains containing in the cold aggregate actual percentage of this hot aggregate in the recruitment of unit interval divided by the feeding coal of cold aggregate unit interval, so just formed a learning sample, the actual percentage of instant heating aggregate and the delivery rate of cold aggregate, acquisition time equals the final time that forms hot aggregate of cold aggregate, i.e. unit interval at interval; The actual percentage of hot aggregate as input, the delivery rate of cold aggregate is as output, enter the training of learning phase, training method is: by the hot aggregate controlling level of real-time measurement and the feeding coal of cold aggregate, obtain the actual percentage of real-time hot aggregate, when the actual percentage of hot aggregate changed, system can change the connection weights between input layer and the output layer automatically;
Secondly, carry out heat drying by main belt conveyor input drying, after arriving suitable temperature, deliver into high building through lifting, screening system classification at this high building top, hot aggregate is loaded into corresponding hot aggregate storage bin respectively through the hot aggregate that obtains corresponding different size after sieving, and forms new learning sample for the on-line study of human nerve's network;
At last, require the hot aggregate of different size measured in proportion with a certain proportion of pitch according to the asphalt prescription and mix, obtain the asphalt product.
2, asphalt mixture stirring equipment cold aggregate feeding control method according to claim 1, it is characterized in that: it is relevant with the delivery rate of cold aggregate bin by the material quantitative change percentage of hot aggregate storage bin to connect the weights size, when the material quantitative change percentage delivery rate big, cold aggregate bin of hot aggregate storage bin is big, it is big then to connect weights; The material quantitative change percentage of hot aggregate storage bin delivery rate little, cold aggregate bin is little, and it is little then to connect weights; Small one and large one then gets intermediate value, and it is minimum can making output error like this.
3, asphalt mixture stirring equipment cold aggregate feeding control method according to claim 1, it is characterized in that: the material quantitative change percentage relation of cold aggregate feeding speed and hot aggregate storage bin, by the variable-frequency governor control cold aggregate feeding speed of control feeding belt.
4, asphalt mixture stirring equipment cold aggregate feeding control method according to claim 1, what it is characterized in that: according to the temperature of feed-forward regulation oven dry bucket of the delivery rate of cold aggregate bin and cold aggregate bin specification of aggregate content, to improve the temperature control precision of hot aggregate.
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| CNB2007100209445A CN100546791C (en) | 2007-04-04 | 2007-04-04 | Asphalt mixture stirring equipment cold aggregate feeding control method |
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| CNB2007100209445A CN100546791C (en) | 2007-04-04 | 2007-04-04 | Asphalt mixture stirring equipment cold aggregate feeding control method |
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| CN102023573B (en) * | 2010-12-10 | 2012-07-25 | 北京化工大学 | Filling control method of semiconductor production lines |
| CN103726429B (en) * | 2014-01-26 | 2015-09-09 | 哈尔滨工业大学 | A kind of method of rapid verification hot mixed asphaltic concrete production grating |
| CN106192676B (en) * | 2016-06-29 | 2023-01-17 | 南阳市辽原筑路机械有限公司 | Intelligent thermal aggregate storage metering system |
| CN106759356B (en) * | 2016-12-09 | 2019-08-09 | 中国人民解放军61489部队 | A kind of vegetation camouflage operation equipment and method |
| CN108277720B (en) * | 2018-01-23 | 2023-12-29 | 华侨大学 | Asphalt mixing station aggregate grading online detection and anti-overflow control method and system |
| CN108951368B (en) * | 2018-09-05 | 2020-09-29 | 三一汽车制造有限公司 | Automatic batching method and system for asphalt mixing plant and asphalt mixing plant |
| CN110258251B (en) * | 2019-07-20 | 2024-04-05 | 江南大学 | Hot aggregate temperature control device and method for asphalt mixture stirring station |
| CN112508253B (en) * | 2020-11-30 | 2023-08-25 | 三一汽车制造有限公司 | Temperature prediction method and device, material mixing system and computer storage medium |
| CN112982175A (en) * | 2021-03-11 | 2021-06-18 | 济南金曰公路工程有限公司 | Pouring type asphalt concrete paving construction process |
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