CN109551673B - Engineering plastic crushing device and control method thereof - Google Patents

Engineering plastic crushing device and control method thereof Download PDF

Info

Publication number
CN109551673B
CN109551673B CN201910069798.8A CN201910069798A CN109551673B CN 109551673 B CN109551673 B CN 109551673B CN 201910069798 A CN201910069798 A CN 201910069798A CN 109551673 B CN109551673 B CN 109551673B
Authority
CN
China
Prior art keywords
crushing
crushing shaft
shaft
discharging
weight
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201910069798.8A
Other languages
Chinese (zh)
Other versions
CN109551673A (en
Inventor
刘莎
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Jiangsu Pufeier Plastic Technology Co ltd
Original Assignee
Jiangyin Hongfeng Plastic Industry Co ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Jiangyin Hongfeng Plastic Industry Co ltd filed Critical Jiangyin Hongfeng Plastic Industry Co ltd
Priority to CN201910069798.8A priority Critical patent/CN109551673B/en
Publication of CN109551673A publication Critical patent/CN109551673A/en
Application granted granted Critical
Publication of CN109551673B publication Critical patent/CN109551673B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
    • B29B—PREPARATION OR PRETREATMENT OF THE MATERIAL TO BE SHAPED; MAKING GRANULES OR PREFORMS; RECOVERY OF PLASTICS OR OTHER CONSTITUENTS OF WASTE MATERIAL CONTAINING PLASTICS
    • B29B17/00—Recovery of plastics or other constituents of waste material containing plastics
    • B29B17/04—Disintegrating plastics, e.g. by milling
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B02—CRUSHING, PULVERISING, OR DISINTEGRATING; PREPARATORY TREATMENT OF GRAIN FOR MILLING
    • B02C—CRUSHING, PULVERISING, OR DISINTEGRATING IN GENERAL; MILLING GRAIN
    • B02C19/00—Other disintegrating devices or methods
    • B02C19/22—Crushing mills with screw-shaped crushing means
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B02—CRUSHING, PULVERISING, OR DISINTEGRATING; PREPARATORY TREATMENT OF GRAIN FOR MILLING
    • B02C—CRUSHING, PULVERISING, OR DISINTEGRATING IN GENERAL; MILLING GRAIN
    • B02C25/00—Control arrangements specially adapted for crushing or disintegrating
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
    • B29B—PREPARATION OR PRETREATMENT OF THE MATERIAL TO BE SHAPED; MAKING GRANULES OR PREFORMS; RECOVERY OF PLASTICS OR OTHER CONSTITUENTS OF WASTE MATERIAL CONTAINING PLASTICS
    • B29B17/00—Recovery of plastics or other constituents of waste material containing plastics
    • B29B17/04—Disintegrating plastics, e.g. by milling
    • B29B2017/0424—Specific disintegrating techniques; devices therefor
    • B29B2017/0472—Balls or rollers in a container
    • 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
    • Y02W—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO WASTEWATER TREATMENT OR WASTE MANAGEMENT
    • Y02W30/00—Technologies for solid waste management
    • Y02W30/50—Reuse, recycling or recovery technologies
    • Y02W30/52—Mechanical processing of waste for the recovery of materials, e.g. crushing, shredding, separation or disassembly
    • 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
    • Y02W—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO WASTEWATER TREATMENT OR WASTE MANAGEMENT
    • Y02W30/00—Technologies for solid waste management
    • Y02W30/50—Reuse, recycling or recovery technologies
    • Y02W30/62—Plastics recycling; Rubber recycling

Abstract

The invention discloses an engineering plastic crushing device, which comprises: the crushing bin 100, the first crushing cavity, the second crushing cavity, the third crushing cavity, the first motor 211, the second motor 212, the third motor 213 and the controller 200; wherein the crushing bin 100 has a feed inlet 110 and a discharge outlet, and a discharge gate 170 is provided at the discharge outlet; the invention discloses a control method of an engineering plastic crushing device.

Description

Engineering plastic crushing device and control method thereof
Technical Field
The invention relates to the field of polymer material preparation, in particular to an engineering plastic crushing device and a control method thereof.
Background
The engineering plastic can be used as engineering material and can replace metal to manufacture machine parts and other plastics, has excellent comprehensive performance, high rigidity, small creep, high mechanical strength, high heat resistance and high electric insulating property, can be used in harsh chemical and physical environments for a long time, can replace metal to be used as engineering structural material, but has high price and low yield.
Compared with general plastics, the engineering plastics can meet higher requirements in the aspects of mechanical property, durability, corrosion resistance, heat resistance and the like, are more convenient to process and can replace metal materials, the engineering plastics are widely applied to the industries of electronics, electrics, automobiles, buildings, office equipment, machinery, aerospace and the like, the replacement of steel by plastics and the replacement of wood by plastics become international popular trends, the engineering plastics become the fields with the fastest growth speed in the plastic industry in the world at present, the development of the engineering plastics not only plays a supporting role in the national pillar industry and modern high and new technology industry, but also promotes the transformation of the traditional industry and the adjustment of the product structure.
At present, because the industries such as automobiles, electronics, buildings and the like in China develop rapidly, China has become the country with the fastest increase of the global engineering plastic demand; according to analysis, with the continuous development of domestic economy, the demand of engineering plastics will be further increased, and the development prospect of the engineering plastics industry in China is very wide, so in order to improve the utilization efficiency of plastics, defective goods and waste products need to be recycled for many times, and the recycling needs to crush the plastics, and the problems of high working strength and poor crushing effect exist in the prior art, and the crushing device needs to be further improved to better improve the utilization efficiency of the plastics.
Disclosure of Invention
The invention designs and develops an engineering plastic crushing device, and aims to fully crush crushed materials by arranging three layers of crushing cavities in a crushing bin.
The invention designs and develops a control method of an engineering plastic crushing device, and aims to respectively control a discharging stop door and a discharging stop door in a BP neural network mode so as to fully crush crushed materials in a crushing cavity.
The invention also aims to set the preset rotating speed of the crushing shaft so as to set the initial rotating speed, so that the rotating speed of the crushing shaft can be better controlled to fully crush the crushed materials.
The technical scheme provided by the invention is as follows:
an engineering plastic crushing device comprises:
the crushing bin is provided with a feeding hole and a discharging hole, and a discharging baffle door is arranged at the discharging hole;
the first crushing cavity is communicated with the feeding hole and is also provided with a first discharging hole;
the first crushing shaft transversely penetrates through the first crushing cavity, one end of the first crushing shaft is rotatably supported on the first crushing cavity and penetrates out of the first crushing cavity, and double-helix stirring blades are arranged on the first crushing shaft;
a first motor, an output shaft of which is connected with the first crushing shaft;
the second crushing cavity is communicated with the first discharge hole and is also provided with a second discharge hole;
the second crushing shaft transversely penetrates through the second crushing cavity, one end of the second crushing shaft is rotatably supported on the second crushing cavity and penetrates out of the second crushing cavity, and double-helix stirring blades are arranged on the second crushing shaft;
a second motor, an output shaft of which is connected with the second crushing shaft;
the third crushing cavity is communicated with the second discharge hole and is also provided with a third discharge hole;
the third crushing shaft transversely penetrates through the third crushing cavity, one end of the third crushing shaft is rotatably supported on the third crushing cavity and penetrates out of the third crushing cavity, and double-helix stirring blades are arranged on the third crushing shaft;
and the output shaft of the third motor is connected with the third crushing shaft.
Preferably, the method further comprises the following steps:
the first discharging stop gate is arranged at the first discharging opening;
the second discharging stop gate is arranged at the second discharging opening; and
and the third discharging stop door is arranged at the third discharging opening.
Preferably, the method further comprises the following steps:
a first rotation speed sensor connected with the first crushing shaft for monitoring the rotation speed of the first crushing shaft;
a second rotation speed sensor connected with the second crushing shaft and used for monitoring the rotation speed of the second crushing shaft;
a third rotation speed sensor connected with the third crushing shaft and used for monitoring the rotation speed of the third crushing shaft;
the first weight sensor is arranged at the bottom of the first discharging stop door and used for monitoring the weight of the crushed materials in the first crushing cavity;
the second weight sensor is arranged at the bottom of the second discharging stop door and is used for monitoring the weight of the crushed materials in the second crushing cavity;
the third weight sensor is arranged at the bottom of the third discharging stop door and used for monitoring the weight of the crushed materials in the third crushing cavity; and
a controller electrically coupled to the speed sensor, the weight sensor, and the door simultaneously.
Preferably, a plurality of vibrators are arranged at the bottom of the crushing bin.
A control method of an engineering plastic crushing device is controlled based on a BP neural network and comprises the following steps:
step one, measuring a first weight M of the crushed material in the first crushing cavity through a weight sensor according to a sampling periodaA second weight M of the crushed material in the second crushing chamberbThird, aA third weight M of the material to be crushed in the crushing chambercMeasuring the rotational speed omega of the first comminution shaft by means of a rotational speed sensoraSecond crushing shaft rotational speed ωbThird crushing shaft rotational speed ωc；
Step two, normalizing the parameters in sequence, and determining an input layer vector x ═ x of the three-layer BP neural network1,x2,x3,x4,x5,x6}; wherein x is1Is a first weight coefficient, x2Is a second weight coefficient, x3Is the third weight coefficient, x4Is the coefficient of rotation, x, of the first crushing shaft5Is the second crushing shaft speed coefficient x6Is the rotation speed coefficient of the third crushing shaft;
step three, the input layer vector is mapped to a middle layer, and the middle layer vector y is { y ═ y1,y2,…,ym}; m is the number of intermediate layer nodes;
step four, obtaining an output layer vector o ═ o1,o2,o3,o4}；o1For the first discharge door aperture regulating coefficient, o2For the second discharge door aperture regulating coefficient o3The opening degree adjustment coefficient and the opening degree of the third discharging stop door are adjusted4The state is a discharging stop door;
fifthly, controlling the opening degree of the first discharging stop door, the second discharging stop door and the third discharging stop door to ensure that
Figure BDA0001956902280000051
Figure BDA0001956902280000052
Figure BDA0001956902280000053
Wherein the content of the first and second substances,
Figure BDA0001956902280000054
respectively outputting the first three parameters of the layer vector, delta, for the ith sampling perioda_max、δb_max、δc_maxThe maximum opening degree, delta, set for the first discharge stop door, the second discharge stop door and the third discharge stop door respectivelya(i+1)、δb(i+1)、δc(i+1)The set opening degrees of the first discharging stop door, the second discharging stop door and the third discharging stop door in the (i + 1) th sampling period are respectively set;
sixthly, judging the running state of the discharging stop door in the (i + 1) th cycle according to the rotating speed and weight sampling signals in the ith cycle, and outputting signals
Figure BDA0001956902280000055
When the discharging shutter is closed, the signal is output
Figure BDA0001956902280000056
When the material is discharged, the material discharge stop door is closed.
Preferably, the number m of the intermediate layer nodes satisfies:
Figure BDA0001956902280000057
wherein n is the number of nodes of the input layer, and p is the number of nodes of the output layer.
Preferably, in the second step, the first weight M is addedaSecond weight MbA third weight McFirst crushing shaft rotation speed omegaaSecond crushing shaft rotation speed omegabThird crushing shaft rotation speed omegacThe formula for normalization is:
Figure BDA0001956902280000058
wherein x isjFor parameters in the input layer vector, XjRespectively being a measurement parameter Ma、Mb、Mc、ωa、ωb、ωc，j＝1,2,3,4,5,6；XjmaxAnd XjminRespectively, a maximum value and a minimum value in the corresponding measured parameter.
Preferably, in the third step, the rotation speeds of the first crushing shaft, the second crushing shaft and the third crushing shaft in the initial motion state satisfy an empirical value:
ωa0＝0.85ωa_pre
ωb0＝0.93ωb_pre
ωc0＝0.88ωc_pre
wherein, ω isa0、ωb0、ωc0Initial rotation speeds, ω, of the first crushing shaft, the second crushing shaft and the third crushing shaft, respectivelya_pre、ωb_pre、ωc_preThe preset rotating speeds of the first crushing shaft, the second crushing shaft and the third crushing shaft are respectively.
Preferably, the preset rotation speed ω of the first pulverizing shafta_preIs composed of
Figure BDA0001956902280000061
The preset rotating speed omega of the second crushing shaftb_preIs composed of
Figure BDA0001956902280000062
A preset rotation speed omega of the third crushing shaftc_preIs composed of
Figure BDA0001956902280000071
In the formula, ζaIs a first correction coefficient; zetabIs a second correction coefficient; zetacIs a third correction coefficient; lambda [ alpha ]aThe number of the first crushing shaft blades; lambda [ alpha ]bThe number of the second crushing shaft blades; lambda [ alpha ]cThe number of the third crushing shaft blades; omegaa_maxThe maximum rotating speed of the first crushing shaft; omegaa_minThe minimum rotation speed of the first crushing shaft; omegab_maxThe maximum rotating speed of the second crushing shaft; omegab_minThe minimum rotation speed of the second crushing shaft; omegac_maxThe maximum rotating speed of the third crushing shaft; omegac_minThe minimum rotating speed of the third crushing shaft; d is the length of the blade on the crushing shaft; l is the length of the crushing shaft; deltaaThe first experimental coefficient is 0.29-0.67; deltabThe value of the second empirical coefficient is 0.31-0.55; deltacThe third empirical coefficient is 0.33-0.71; vaIs the volume of the first crushing chamber; vbIs the volume of the second crushing chamber; vcIs the volume of the third crushing cavity; a is a first empirical constant; b is a second empirical constant; c is a third empirical constant; e is the base number of the natural logarithm; pi is 3.14.
Preferably, the first empirical coefficient δaThe value is 0.33; second empirical coefficient deltabThe value is 0.41; third empirical coefficient deltacThe value is 0.55; the first empirical constant A is 0.119; the second empirical constant B is 0.113; the third empirical constant C is 0.108.
Compared with the prior art, the invention has the following beneficial effects:
1. according to the invention, the three layers of crushing shafts are arranged in the crushing bin, and when the crushed materials in the crushing bin need to be crushed or discharged, the crushing degree and discharge of the crushed materials in the crushing bin can be effectively controlled by controlling the rotating direction of the crushing shafts;
2. the opening degree of a first discharging stop door, the opening degree of a second discharging stop door, the opening degree of a third discharging stop door and the state of a discharging stop door are controlled based on BP neural network adjustment, so that the crushing degree of crushed materials in a crushing bin is controlled;
3. the invention can set the initial rotating speed of the crushing shaft, and then control the crushing shaft based on the BP neural network, and improve the crushing degree of the crushed material in the crushing cavity again.
Drawings
Fig. 1 is a schematic structural diagram of the present invention.
Detailed Description
The present invention is further described in detail below with reference to the attached drawings so that those skilled in the art can implement the invention by referring to the description text.
As shown in fig. 1, the present invention provides an engineering plastic pulverizing apparatus, the main structure of which comprises a pulverizing bin 100, a first pulverizing chamber, a second pulverizing chamber, a third pulverizing chamber, a first motor 211, a second motor 212, a third motor 213 and a controller 200; wherein the crushing bin 100 has a feed inlet 110 and a discharge outlet, and a discharge gate 170 is provided at the discharge outlet;
the first crushing cavity is communicated with the feed inlet 110, and is also provided with a first discharge hole, a first discharging baffle door 151 is arranged at the first discharging opening, a first weight sensor 141 is arranged at the bottom of the first discharging baffle door 151 and used for monitoring the weight of the crushed materials in the first crushing cavity, a first crushing shaft 121 transversely penetrates through the inside of the first crushing cavity, one end of the first crushing shaft is rotatably supported on the first crushing cavity and penetrates out of the first crushing cavity, the first pulverizing shaft 121 is provided with a double spiral agitating blade, and when the first pulverizing shaft 121 rotates clockwise, for stirring the crushed materials introduced into the first crushing chamber from the feed opening 110, when the first crushing shaft 121 is rotated counterclockwise, the bottom plate 131 of the first crushing cavity is arc-shaped, so that the crushed materials can be smoothly discharged from the first crushing cavity, and residues in the first crushing cavity are prevented;
the second crushing cavity is communicated with the first discharge hole, the second crushing cavity is also provided with a second discharge hole, a second discharge stop door 152 is arranged at the second discharge hole, a second weight sensor 142 is arranged at the bottom of the second discharge stop door 152 and used for monitoring the weight of the crushed materials in the second crushing cavity, a second crushing shaft 122 transversely penetrates through the second crushing cavity, one end of the second crushing shaft is rotatably supported on the second crushing cavity and penetrates out of the second crushing cavity, a double-helix stirring blade is arranged on the second crushing shaft 122, the crushed materials entering the second crushing cavity from the first discharge hole are stirred when the second crushing shaft 122 rotates clockwise, the crushed materials in the second crushing cavity are discharged from the second discharge hole when the second crushing shaft 122 rotates anticlockwise, the bottom plate 132 of the second crushing cavity is arc-shaped, and the crushed materials are conveniently and smoothly discharged from the second crushing cavity, preventing residue in the second crushing cavity;
the third crushing cavity is communicated with the second discharge hole, the third crushing cavity is also provided with a third discharge hole, a third discharge stop door 153 is arranged at the third discharge hole, a third weight sensor 143 is arranged at the bottom of the third discharge stop door 153 and used for monitoring the weight of the crushed materials in the third crushing cavity, a third crushing shaft 123 transversely penetrates through the third crushing cavity, one end of the third crushing shaft is rotatably supported on the third crushing cavity and penetrates out of the third crushing cavity, a double-helix stirring blade is arranged on the third crushing shaft 123, when the third crushing shaft 123 rotates clockwise, the third crushing shaft is used for stirring the crushed materials entering the third crushing cavity from the second discharge hole, when the third crushing shaft 123 rotates anticlockwise, the crushed materials in the third crushing cavity are discharged from the third discharge hole, the bottom plate 133 of the third crushing cavity is arc-shaped, the crushed materials can be conveniently and smoothly discharged from the third crushing cavity, preventing residue in the third crushing cavity;
an output shaft of the first motor 211 is connected to the first pulverizing shaft 121, and an acceleration motor 221 is provided between the first motor 211 and the first pulverizing shaft 121, an output shaft of the second motor 212 is connected to the second pulverizing shaft 122, and an acceleration motor 222 is provided between the second motor 212 and the second pulverizing shaft 122, an output shaft of the third motor 213 is connected to the third pulverizing shaft 123, and an acceleration motor 223 is provided between the third motor 213 and the third pulverizing shaft 123,
in another embodiment, the method further comprises: a first rotational speed sensor 231, a second rotational speed sensor 232, and a third rotational speed sensor 233; wherein, a first rotation speed sensor 231 is arranged outside the crushing bin 100 and connected with the first crushing shaft 121 for monitoring the rotation speed of the first crushing shaft 121, a second rotation speed sensor 232 is arranged outside the crushing bin 100 and connected with the second crushing shaft 122 for monitoring the rotation speed of the second crushing shaft 122, and a third rotation speed sensor 233 is arranged outside the crushing bin 100 and connected with the third crushing shaft 123 for monitoring the rotation speed of the third crushing shaft 123.
In another embodiment, the bottom of the pulverizing bin 100 is provided with a plurality of vibrators 160, when the vibrators 160 are turned on, the pulverized material in the pulverizing bin 100 can be shaken off completely, and finally the pulverized material is discharged from the outlet 180.
In another embodiment, controller 200 is electrically coupled to first rotational speed sensor 231, second rotational speed sensor 232, third rotational speed sensor 233, first output shutter 151, second output shutter 152, third output shutter 153, first weight sensor 141, second weight sensor 142, third weight sensor 143, and shutter dump 170 at the same time.
The invention also discloses a control method of the engineering plastic crushing device, which is based on BP neural network control and comprises the following steps:
step one, establishing a BP neural network model.
The BP network system structure adopted by the invention is composed of three layers, wherein the first layer is an input layer, n nodes are provided in total, n detection signals representing the working state of the equipment are correspondingly provided, and the signal parameters are provided by a data preprocessing module. The second layer is a hidden layer, and has m nodes, and is determined by the training process of the network in a self-adaptive mode. The third layer is an output layer, p nodes are provided in total, and the output is determined by the response actually needed by the system.
The mathematical model of the network is:
inputting a vector: x ═ x1,x2,...,xn)T
Intermediate layer vector: y ═ y1,y2,...,ym)T
Outputting a vector: o ═ O1,o2,...,op)T
In the invention, the number of nodes of the input layer is n-6, and the number of nodes of the output layer is p-4. The number m of hidden layer nodes is estimated by the following formula:
Figure BDA0001956902280000111
the input signal has 6 parameters expressed as: x is the number of1Is a first weight coefficient, x2Is a second weight coefficient, x3Is the third weight coefficient, x4Is the coefficient of rotation, x, of the first crushing shaft5Is the second crushing shaft speed coefficient x6The rotation speed coefficient of the third pulverizing shaft.
The data acquired by the sensors belong to different physical quantities, and the dimensions of the data are different. Therefore, the data needs to be normalized to a number between 0-1 before it is input into the artificial neural network.
Specifically, for a first weight M measured using a first weight sensoraNormalized to obtain a first weight coefficient x1：
Figure BDA0001956902280000121
Wherein M isa_minAnd Ma_maxRespectively the minimum and maximum weight of the crushed material in the first crushing chamber.
Likewise, a second weight M measured using a second weight sensorbNormalized to obtain a second weight coefficient x2：
Figure BDA0001956902280000122
Wherein M isb_minAnd Mb_maxRespectively the minimum weight and the maximum weight of the crushing amount in the second crushing cavity.
Third weight M measured using third weight sensorcNormalized to obtain a third weight coefficient x3：
Figure BDA0001956902280000123
Wherein M isc_minAnd Mc_maxRespectively the minimum weight and the maximum weight of the crushed material in the third crushing chamber.
Measuring the rotation speed omega of the first crushing shaft by using a first rotation speed sensoraNormalized to obtain a first pulverizing shaft speed coefficient x4：
Figure BDA0001956902280000124
Wherein, ω isa_minAnd ωa_maxRespectively, the maximum value and the minimum value of the rotation speed of the first pulverizing shaft.
The rotation speed omega of the second crushing shaft is measured by using a second rotation speed sensorbNormalized to obtain a second pulverizing shaft speed coefficient x5：
Figure BDA0001956902280000131
Wherein, ω isb_minAnd ωb_maxRespectively the maximum value and the minimum value of the rotation speed of the second crushing shaft.
Measuring the rotation speed omega of the third crushing shaft by using a third rotation speed sensorcNormalized to obtain a third pulverizing shaft speed coefficient x6：
Figure BDA0001956902280000132
Wherein, ω isc_minAnd ωc_maxRespectively, the maximum value and the minimum value of the rotation speed of the third pulverizing shaft.
The 4 parameters of the output signal are respectively expressed as: o1Is the first discharge stop opening degree regulating coefficient o2For the second discharge shutter opening degree adjustment coefficient, o3Is the aperture regulating coefficient of the third discharging stop door o4The state is the material discharging shutter.
First discharge stop opening degree regulating coefficient o1Expressed as the ratio of the opening of the first discharging stop gate in the next sampling period to the set maximum opening of the first discharging stop gate in the current sampling period, namely, in the ith sampling period, the collected opening of the first discharging stop gate is deltaaiOutputting a first discharging stop door opening degree regulating coefficient of the ith sampling period through a BP neural network
Figure BDA0001956902280000135
Then, the opening degree of the first discharging stop door in the (i + 1) th sampling period is controlled to be deltaa(i+1)To make it satisfy
Figure BDA0001956902280000133
Opening degree regulating coefficient o of second discharging stop door2Expressed as the ratio of the opening of the second discharging baffle in the next sampling period to the set maximum opening of the second discharging baffle in the current sampling period, namely, in the ith sampling period, the collected opening of the second discharging baffle is deltabiOutputting a second discharging stop door opening degree regulating coefficient of the ith sampling period through a BP neural network
Figure BDA0001956902280000134
Then, the opening degree of a second discharging stop door in the (i + 1) th sampling period is controlled to be deltab(i+1)To make it satisfy
Figure BDA0001956902280000141
Regulating coefficient o of opening degree of third discharging stop door3Expressed as the ratio of the opening of the third discharging stop gate in the next sampling period to the set maximum opening of the third discharging stop gate in the current sampling period, namely, in the ith sampling period, the collected opening of the third discharging stop gate is deltaciOutputting a third discharging stop door opening degree regulating coefficient of the ith sampling period through a BP neural network
Figure BDA0001956902280000142
Then, the opening degree of a third discharging stop door in the (i + 1) th sampling period is controlled to be deltac(i+1)To make it satisfy
Figure BDA0001956902280000143
Discharge door stop state signal o4Is indicated as currentWhen the output value is 0, the current discharging stop door is in a closed state; when the output value is 1, the current discharging stop door is in an open state.
And step two, training the BP neural network.
After the BP neural network node model is established, the training of the BP neural network can be carried out. Obtaining a training sample according to historical experience data of the product, and giving a connection weight w between an input node i and a hidden layer node jijConnection weight w between hidden layer node j and output layer node kjkThreshold value theta of hidden layer node jjThreshold value theta of output layer node kk、wij、wjk、θj、θkAre all random numbers between-1 and 1.
Continuously correcting w in the training processijAnd wjkUntil the system error is less than or equal to the expected error, the training process of the neural network is completed.
As shown in table 1, a set of training samples is given, along with the values of the nodes in the training process.
TABLE 1 training Process node values
Figure BDA0001956902280000144
Figure BDA0001956902280000151
And step three, the controller collects operation parameters and inputs the operation parameters into the neural network to obtain an opening coefficient and a discharging stop signal.
The trained artificial neural network is solidified in a chip, so that a hardware circuit has the functions of prediction and intelligent decision making, and intelligent hardware is formed; after the intelligent hardware is powered on and started, the first crushing shaft, the second crushing shaft and the third crushing shaft are started at a preset rotating speed, and then the initial rotating speed is adjusted, namely the initial rotating speed of the first crushing shaft is omegaa0＝0.85ωa_preThe initial rotation speed of the second crushing shaft is omegab0＝0.93ωb_preThe initial rotation speed of the third crushing shaft is omegac0＝0.88ωc_pre。
While measuring a first weight M using a weight sensora0Second weight Mb0A third weight Mc0(ii) a Normalizing the parameters to obtain an initial input vector of the BP neural network
Figure BDA0001956902280000161
Obtaining an initial output vector through operation of a BP neural network
Figure BDA0001956902280000162
And step four, controlling the opening degrees of the first discharging stop door, the second discharging stop door and the third discharging stop door.
Obtaining an initial output vector
Figure BDA0001956902280000163
After, can carry out the regulation and control of aperture, adjust first ejection of compact stop gate, second ejection of compact stop gate, third ejection of compact stop gate, make the aperture of first ejection of compact stop gate, second ejection of compact stop gate, third ejection of compact stop gate in next sampling period do respectively:
Figure BDA0001956902280000164
Figure BDA0001956902280000165
Figure BDA0001956902280000166
obtaining a first weight M of an ith sampling period through a sensoraSecond weight MbA third weight McFirst crushing shaft rotation speed omegaaSecond crushing shaft rotation speed omegabThird crushing shaftSpeed of rotation omegacObtaining the input vector of the ith sampling period by formatting
Figure BDA0001956902280000167
Obtaining an output vector to the ith sampling period through the operation of a BP neural network
Figure BDA0001956902280000168
Then the aperture of the first ejection of compact stop door, the second ejection of compact stop door, the third ejection of compact stop door is adjusted in control, makes the aperture of first ejection of compact stop door, the second ejection of compact stop door, the third ejection of compact stop door be respectively when the (i + 1) th sampling cycle:
Figure BDA0001956902280000169
Figure BDA00019569022800001610
Figure BDA00019569022800001611
and step five, monitoring the state of the discharge outlet.
Judging the running state of the discharging stop gate in the (i + 1) th cycle according to the rotating speed and weight sampling signals in the (i) th cycle, and outputting a signal
Figure BDA0001956902280000171
When the discharging shutter is closed, the signal is output
Figure BDA0001956902280000172
When the material is discharged, the material stop door is opened.
Through the arrangement, the running state of the crushing shaft is detected in real time through the sensor, and the discharge stop door is regulated and controlled by adopting a BP neural network algorithm, so that the crushing device reaches the nearest running state, and the crushing quality is improved.
In another embodiment, the preset rotation speed ω of the first crushing shafta_preIs composed of
Figure BDA0001956902280000173
；
Preset rotation speed omega of second crushing shaftb_preIs composed of
Figure BDA0001956902280000174
；
Preset rotation speed omega of third crushing shaftc_preIs composed of
Figure BDA0001956902280000175
Figure BDA0001956902280000181
In the formula, ζaIs a first correction coefficient; zetabIs a second correction coefficient; zetacIs a third correction coefficient; lambda [ alpha ]aThe number of the first crushing shaft blades; lambda [ alpha ]bThe number of the second crushing shaft blades; lambda [ alpha ]cThe number of the third crushing shaft blades; omegaa_maxThe maximum rotating speed of the first crushing shaft is in rad/min; omegaa_minThe minimum rotating speed of the first crushing shaft is in rad/min; omegab_maxThe maximum rotating speed of the second crushing shaft is in rad/min; omegab_minThe minimum rotation speed of the second crushing shaft is in rad/min; omegac_maxThe maximum rotating speed of the third crushing shaft is in rad/min; omegac_minThe minimum rotating speed of the third crushing shaft is in rad/min; d is the length of the blades on the crushing shaft and the unit is m; l is the length of the crushing shaft and is m; deltaaThe first experimental coefficient is 0.29-0.67; deltabThe value of the second empirical coefficient is 0.31-0.55; deltacThe third empirical coefficient is 0.33-0.71; vaIs the volume of the first crushing chamber and has the unit of m3；VbIs a second crushing cavityVolume of (d) in m3；VcIs the volume of the third crushing cavity and has the unit of m3(ii) a A is a first empirical constant; b is a second empirical constant; c is a third empirical constant; e is the base number of the natural logarithm; pi is 3.14.
In another embodiment, the first empirical factor δaThe value is 0.33; second empirical coefficient deltabThe value is 0.41; third empirical coefficient deltacThe value is 0.55; the first empirical constant A is 0.119; the second empirical constant B is 0.113; the third empirical constant C is 0.108.
While embodiments of the invention have been described above, it is not limited to the applications set forth in the description and the embodiments, which are fully applicable in various fields of endeavor to which the invention pertains, and further modifications may readily be made by those skilled in the art, it being understood that the invention is not limited to the details shown and described herein without departing from the general concept defined by the appended claims and their equivalents.

Claims (3)

1. An engineering plastic reducing mechanism, comprising: the crushing bin is provided with a feeding hole and a discharging hole, and a discharging baffle door is arranged at the discharging hole; the first crushing cavity is communicated with the feeding hole and is also provided with a first discharging hole; the first crushing shaft transversely penetrates through the first crushing cavity, one end of the first crushing shaft is rotatably supported on the first crushing cavity and penetrates out of the first crushing cavity, and double-helix stirring blades are arranged on the first crushing shaft; a first motor, an output shaft of which is connected with the first crushing shaft; the second crushing cavity is communicated with the first discharge hole and is also provided with a second discharge hole; the second crushing shaft transversely penetrates through the second crushing cavity, one end of the second crushing shaft is rotatably supported on the second crushing cavity and penetrates out of the second crushing cavity, and double-helix stirring blades are arranged on the second crushing shaft; a second motor, an output shaft of which is connected with the second crushing shaft; the third crushing cavity is communicated with the second discharge hole and is also provided with a third discharge hole; the third crushing shaft transversely penetrates through the third crushing cavity, one end of the third crushing shaft is rotatably supported on the third crushing cavity and penetrates out of the third crushing cavity, and double-helix stirring blades are arranged on the third crushing shaft; a third motor, an output shaft of which is connected with the third crushing shaft;
further comprising: the first discharging stop gate is arranged at the first discharging opening; the second discharging stop gate is arranged at the second discharging opening; the third discharging stop door is arranged at the third discharging opening;
further comprising: a first rotation speed sensor connected with the first crushing shaft for monitoring the rotation speed of the first crushing shaft; a second rotation speed sensor connected with the second crushing shaft and used for monitoring the rotation speed of the second crushing shaft; a third rotation speed sensor connected with the third crushing shaft and used for monitoring the rotation speed of the third crushing shaft; the first weight sensor is arranged at the bottom of the first discharging stop door and used for monitoring the weight of the crushed materials in the first crushing cavity; the second weight sensor is arranged at the bottom of the second discharging stop door and is used for monitoring the weight of the crushed materials in the second crushing cavity; the third weight sensor is arranged at the bottom of the third discharging stop door and used for monitoring the weight of the crushed materials in the third crushing cavity; and a controller electrically coupled to the speed sensor, the weight sensor, and the door at the same time;
the control method of the engineering plastic crushing device is controlled based on a BP neural network, and comprises the following steps: step one, measuring a first weight M of the crushed material in the first crushing cavity through a weight sensor according to a sampling periodaA second weight M of the crushed material in the second crushing chamberbThird weight M of the pulverized material in the third pulverizing chambercMeasuring the rotational speed omega of the first comminution shaft by means of a rotational speed sensoraSecond crushing shaft rotational speed ωbThird crushing shaft rotational speed ωc(ii) a Step two, normalizing the parameters in sequence, and determining an input layer vector x ═ x of the three-layer BP neural network1，x2，x3，x4，x5，x6}; wherein x is1Is a first weight coefficient, x2Is a second weight coefficient, x3Is the third weight coefficient, x4Is the coefficient of rotation, x, of the first crushing shaft5Is the second crushing shaft speed coefficient x6Is the rotation speed coefficient of the third crushing shaft; step three, the input layer vector is mapped to a middle layer, and the middle layer vector y is { y ═ y1，y2，...，ym}; m is the number of intermediate layer nodes; step four, obtaining an output layer vector o ═ o1，o2，o3，o4}；o1For the first discharge door aperture regulating coefficient, o2For the second discharge door aperture regulating coefficient o3The opening degree adjustment coefficient and the opening degree of the third discharging stop door are adjusted4The state is a discharging stop door; fifthly, controlling the opening degree of the first discharging stop door, the second discharging stop door and the third discharging stop door to ensure that
Figure FDA0003042327830000021
Figure FDA0003042327830000022
Figure FDA0003042327830000023
Wherein the content of the first and second substances,
Figure FDA0003042327830000024
respectively outputting the first three parameters of the layer vector, delta, for the ith sampling perioda_max、δb_max、δc_maxThe maximum opening degree, delta, set for the first discharge stop door, the second discharge stop door and the third discharge stop door respectivelya(i+1)、δb(i+1)、δc(i+1)The first discharging baffle door and the second discharging baffle door are respectively at the (i + 1) th sampling periodThe set opening degrees of the door and the third discharging stop door; sixthly, judging the running state of the discharging stop door in the (i + 1) th cycle according to the rotating speed and weight sampling signals in the ith cycle, and outputting signals
Figure FDA0003042327830000025
When the discharging shutter is closed, the signal is output
Figure FDA0003042327830000026
When the material is discharged, the material discharging stop door is closed;
the number m of the intermediate layer nodes meets the following requirements:
Figure FDA0003042327830000027
wherein n is the number of nodes of an input layer, and p is the number of nodes of an output layer;
in the second step, the first weight M is addedaSecond weight MbA third weight McFirst crushing shaft rotation speed omegaaSecond crushing shaft rotation speed omegabThird crushing shaft rotation speed omegacThe formula for normalization is:
Figure FDA0003042327830000031
wherein x isjFor parameters in the input layer vector, XjRespectively being a measurement parameter Ma、Mb、Mc、ωa、ωb、ωc，j＝1，2，3，4，5，6；XjmaxAnd XjminRespectively the maximum value and the minimum value in the corresponding measurement parameters;
in the third step, in the initial motion state, the rotating speeds of the first crushing shaft, the second crushing shaft and the third crushing shaft meet the empirical value: omegaa0＝0.85ωa_preωb0＝0.93ωb_preωc0＝0.88ωc_preWherein, ω isa0、ωb0、ωc0Initial rotation speeds, ω, of the first crushing shaft, the second crushing shaft and the third crushing shaft, respectivelya_pre、ωb_pre、ωc_preThe preset rotating speeds of the first crushing shaft, the second crushing shaft and the third crushing shaft are respectively set;
the preset rotating speed omega of the first crushing shafta_preIs composed of
Figure FDA0003042327830000032
The preset rotating speed omega of the second crushing shaftb_preIs composed of
Figure FDA0003042327830000033
A preset rotation speed omega of the third crushing shaftc_preIs composed of
Figure FDA0003042327830000041
In the formula, ζaIs a first correction coefficient; zetabIs a second correction coefficient; zetacIs a third correction coefficient; lambda [ alpha ]aThe number of the first crushing shaft blades; lambda [ alpha ]bThe number of the second crushing shaft blades; lambda [ alpha ]cThe number of the third crushing shaft blades; omegaa_maxThe maximum rotating speed of the first crushing shaft; omegaa_minThe minimum rotation speed of the first crushing shaft; omegab_maxThe maximum rotating speed of the second crushing shaft; omegab_minThe minimum rotation speed of the second crushing shaft; omegac_maxThe maximum rotating speed of the third crushing shaft; omegac_minThe minimum rotating speed of the third crushing shaft; d is the length of the blade on the crushing shaft; l is the length of the crushing shaft; deltaaThe first experimental coefficient is 0.29-0.67; deltabThe value of the second empirical coefficient is 0.31-0.55; deltacThe third empirical coefficient is 0.33-0.71; vaIs the volume of the first crushing chamber; vbIs the volume of the second crushing chamber; vcIs the volume of the third crushing cavity; a is a first empirical constant; b is a second empirical constant; c is a third empirical constant; e is a natural pairThe base of the number; pi is 3.14.
2. The engineering plastic crushing device as claimed in claim 1, wherein a plurality of vibrators are provided at the bottom of the crushing bin.
3. The apparatus for pulverizing engineering plastics according to claim 2, wherein the first empirical factor δaThe value is 0.33; second empirical coefficient deltabA third empirical coefficient delta of 0.41cThe first empirical constant A is 0.55, the second empirical constant B is 0.113; the third empirical constant C is 0.108.
CN201910069798.8A 2019-01-24 2019-01-24 Engineering plastic crushing device and control method thereof Active CN109551673B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201910069798.8A CN109551673B (en) 2019-01-24 2019-01-24 Engineering plastic crushing device and control method thereof

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201910069798.8A CN109551673B (en) 2019-01-24 2019-01-24 Engineering plastic crushing device and control method thereof

Publications (2)

Publication Number Publication Date
CN109551673A CN109551673A (en) 2019-04-02
CN109551673B true CN109551673B (en) 2021-09-21

Family

ID=65873628

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201910069798.8A Active CN109551673B (en) 2019-01-24 2019-01-24 Engineering plastic crushing device and control method thereof

Country Status (1)

Country Link
CN (1) CN109551673B (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114536598B (en) * 2022-03-04 2022-10-04 佛山市南海瑞泰机动车报废有限公司 Method for recycling and processing scraped car plastic

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108673816A (en) * 2018-05-16 2018-10-19 合肥海景包装制品有限公司 EPS particulate charges device and its control method

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108673816A (en) * 2018-05-16 2018-10-19 合肥海景包装制品有限公司 EPS particulate charges device and its control method

Also Published As

Publication number Publication date
CN109551673A (en) 2019-04-02

Similar Documents

Publication Publication Date Title
CN109551673B (en) Engineering plastic crushing device and control method thereof
Deng et al. Energy monitoring and quality control of a single screw extruder
CN100546791C (en) Asphalt mixture stirring equipment cold aggregate feeding control method
CN109343351A (en) A kind of switched reluctance machines moment controlling system of advanced PID control
EP3988270A1 (en) Machine learning method, machine learning device, and machine learning program
CN110471285B (en) Trend event driven fuzzy control method for zinc smelting roasting process
CN101285816A (en) Copper matte air refining procedure parameter soft sensing instrument and its soft sensing method
CN110535396A (en) Surface permanent magnetic Synchronous Machine Models forecast Control Algorithm based on BP neural network
CN110518847A (en) Surface permanent magnetic Synchronous Machine Models forecast Control Algorithm based on BP neural network
Bettenhausen et al. Self-organizing structured modelling of a biotechnological fed-batch fermentation by means of genetic programming
CN109925992A (en) It is a kind of based on multimode stage by stage continuously stir on-line monitoring method
CN113885310A (en) Intelligent control system for vacuum dry pump test
Stange Using artificial neural networks for the control of grinding circuits
CN107741695B (en) Machine learning-based control method for direct-falling type material blanking machine
CN108673816B (en) EPS particulate charge device and its control method
CN110518860A (en) Permanent magnet synchronous motor model predictive control method based on BP neural network and switch list
Tang et al. Dual-layer optimized selective information fusion using multi-source multi-component mechanical signals for mill load parameters forecasting
CN105223806B (en) Supersonic motor fuzzy Neural Network Control Method based on basis function network
CN109142167B (en) Method for establishing online robust regular soft measurement model of ore grinding granularity
Takeuchi et al. Variation model abstraction and adaptive control based on element description method toward smart factory
Zhang et al. Reliable multi-objective on-line re-optimisation control of a fed-batch fermentation process using bootstrap aggregated neural networks
CN103472729B (en) The pesticide waste liquid incinerator hazardous emission controls up to par system and method for gunz
CN2339979Y (en) Electronic automatic balance with water-content detection device
Lu et al. Auto-encoder based fault early warning model for primary fan of power plant
CN113289542A (en) Mixing machine control system and method based on optimal mixing energy efficiency ratio

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
TA01 Transfer of patent application right

Effective date of registration: 20210902

Address after: 214400 No. 109, Zhouzhuang East Street, Zhouzhuang Town, Jiangyin City, Wuxi City, Jiangsu Province

Applicant after: JIANGYIN HONGFENG PLASTIC INDUSTRY Co.,Ltd.

Address before: 230000 room 1102, building 20, Arc de Triomphe community, intersection of Qianshan Road and Xingguang East Road, Hefei government district, Anhui Province

Applicant before: ANHUI HANXIN ENVIRONMENTAL PROTECTION TECHNOLOGY Co.,Ltd.

TA01 Transfer of patent application right
GR01 Patent grant
GR01 Patent grant
TR01 Transfer of patent right

Effective date of registration: 20240228

Address after: No. 52, Shenxiang Road, Yunting Industrial Park, Jiangyin City, Wuxi City, Jiangsu Province, 214422

Patentee after: Jiangsu Pufeier Plastic Technology Co.,Ltd.

Country or region after: China

Address before: 214400 No. 109, Zhouzhuang East Street, Zhouzhuang Town, Jiangyin City, Wuxi City, Jiangsu Province

Patentee before: JIANGYIN HONGFENG PLASTIC INDUSTRY Co.,Ltd.

Country or region before: China

TR01 Transfer of patent right