CN108875155B - Energy consumption optimization method of ceramic polishing machine based on improved genetic algorithm - Google Patents

Energy consumption optimization method of ceramic polishing machine based on improved genetic algorithm Download PDF

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CN108875155B
CN108875155B CN201810531088.8A CN201810531088A CN108875155B CN 108875155 B CN108875155 B CN 108875155B CN 201810531088 A CN201810531088 A CN 201810531088A CN 108875155 B CN108875155 B CN 108875155B
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energy consumption
polishing machine
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ceramic polishing
grinding head
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CN108875155A (en
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杨海东
刘汉勇
印四华
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Guangdong University of Technology
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
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    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
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    • G06N3/00—Computing arrangements based on biological models
    • G06N3/12—Computing arrangements based on biological models using genetic models
    • G06N3/126—Evolutionary algorithms, e.g. genetic algorithms or genetic programming
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2111/00—Details relating to CAD techniques
    • G06F2111/06—Multi-objective optimisation, e.g. Pareto optimisation using simulated annealing [SA], ant colony algorithms or genetic algorithms [GA]
    • 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
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    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
    • 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
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Abstract

A method for optimizing the energy consumption of a ceramic polishing machine based on an improved genetic algorithm comprises the following steps: step A: constructing and solving an energy consumption model of the ceramic polishing machine, and obtaining parameters influencing the energy consumption of the ceramic polishing machine according to the solving result of the energy consumption model of the ceramic polishing machine; the energy consumption model of the ceramic polishing machine comprises cutting formation energy consumption, polishing grinding head energy consumption, transmission roller energy consumption, beam swing energy consumption and auxiliary system energy consumption; and B: and improving the adaptive genetic algorithm, and calculating the optimal parameters influencing the energy consumption of the ceramic polishing machine by utilizing the improved adaptive genetic algorithm. The invention provides an energy consumption optimization method of a ceramic polishing machine based on an improved genetic algorithm, which can accurately obtain technological parameters influencing the energy consumption of the ceramic polishing machine, thereby performing targeted technological parameter optimization and ensuring that the ceramic polishing machine reaches the minimum energy consumption during operation.

Description

Ceramic polishing machine energy consumption optimization method based on improved genetic algorithm
Technical Field
The invention relates to the technical field of energy consumption of polishing equipment, in particular to an energy consumption optimization method of a ceramic polishing machine based on an improved genetic algorithm.
Background
The polishing of the ceramic tile is an important process in the preparation of the ceramic tile, and the surface of the ceramic tile after polishing has the characteristics of flatness, brightness and the like. However, tile polishing consumes more than one-third of the total power for tile preparation. With the increase of energy costs and the pressure of resource environments, the improvement of polishing energy efficiency has been the focus of attention of ceramic enterprises. However, few researches on energy consumption process parameters of polishing equipment are available at present, the process parameter setting is generally limited to the problems of ceramic tile surface glossiness, polishing efficiency and the like, and energy consumption is neglected, so that the energy consumption is high, and the energy utilization rate is low.
The genetic algorithm is an intelligent optimization algorithm which is inspired by Darwinian evolutionary theory by Holland professor and simulates the mechanisms of biological selection and inheritance. The adaptive genetic algorithm is greatly improved in the aspect of parameter control of the algorithm on the basis of a standard genetic algorithm, and adopts a self-adaptive cross probability and a self-adaptive variation probability. The cross probability and the mutation probability of the traditional genetic algorithm are fixed and invariable, the cross probability and the mutation probability of the self-adaptive genetic algorithm change along with the difference of individual fitness values in a group, and individuals with different fitness have different cross probability and mutation probability.
Parameters influencing the energy consumption of the ceramic polishing machine can be accurately obtained by using the self-adaptive genetic algorithm, so that parameter optimization is made in a targeted manner, and the ceramic polishing machine achieves the minimum energy consumption during operation.
Disclosure of Invention
The invention aims to provide an energy consumption optimization method of a ceramic polishing machine based on an improved genetic algorithm, which can accurately obtain technological parameters influencing the energy consumption of the ceramic polishing machine, so that the technological parameters are optimized in a targeted manner, and the ceramic polishing machine can reach the minimum energy consumption during operation.
In order to achieve the purpose, the invention adopts the following technical scheme:
an energy consumption optimization method of a ceramic polishing machine based on an improved genetic algorithm comprises the following steps:
step A: constructing and solving an energy consumption model of the ceramic polishing machine, and obtaining parameters influencing the energy consumption of the ceramic polishing machine according to the solving result of the energy consumption model of the ceramic polishing machine; the energy consumption model of the ceramic polishing machine comprises cutting formation energy consumption, polishing grinding head energy consumption, transmission roller energy consumption, beam swing energy consumption and auxiliary system energy consumption;
and B: and improving the adaptive genetic algorithm, and calculating the optimal parameters influencing the energy consumption of the ceramic polishing machine by utilizing the improved adaptive genetic algorithm.
Preferably, solving the cutting formation energy consumption, the polishing grinding head energy consumption, the transmission roller energy consumption, the beam swing energy consumption and the auxiliary system energy consumption in the ceramic polishing machine energy consumption model;
the method comprises the following steps:
step A1: the energy consumption generated by the removal effect of the abrasive particles on the surface material of the ceramic tile is the energy consumption generated by the cutting formation of the ceramic polishing machine,
constructing an energy consumption model of the ceramic polishing machine, and solving the cutting formation energy consumption of the ceramic polishing machine comprises the following steps:
determining a cut forming energy consumption objective function E of a ceramic polishing machinechipAn objective function EchipThe formula (1.1) of (a) is as follows:
Figure BDA0001677202520000021
cutting to form an objective function E of energy consumptionchipThe parametric variables of- - (1.1) are:
Ωadenotes the total area of all abrasive grains in mm2；
t represents the time taken to polish the tile, in units of s;
phi denotes the density per unit abrasive grain, unit g/cm3；
h represents the height of a unit abrasive grain, in mm;
μ represents a friction coefficient between the abrasive grains and the tile;
d Ω represents the area of unit abrasive grain, unit mm2；
a represents the acceleration of the unit abrasive grain in mm/s2；
v represents the velocity per abrasive particle, in mm/s;
p represents the pressure of the grinding head;
step A2: constructing an energy consumption model of the ceramic polishing machine, and solving the energy consumption of a polishing grinding head of the ceramic polishing machine comprises the following steps:
determining polishing grinding head energy consumption objective function EheadPolishing head energy consumption objective function EheadEquation (2.1) below:
Figure BDA0001677202520000031
polishing head energy consumption objective function Ehead- - (2.1) ginsengThe number variables are:
omega represents the angular speed of the grinding head in rad/s;
m1representing the mass of the grinding head, unit kg:
d represents the diameter of the grinding head in m;
step A3: constructing an energy consumption model of the ceramic polishing machine, and solving the energy consumption of a transmission drum of the ceramic polishing machine comprises the following steps:
determining a drive drum energy consumption objective function ErollerTarget function of energy consumption of driving drum ErollerEquation (3.1) below:
Figure BDA0001677202520000032
target function E of energy consumption of transmission rollerrollerThe parametric variables of- - (3.1) are:
μ1representing the friction coefficient between the grinding block and the ceramic tile;
μ2representing the coefficient of friction between the conveyor belt and the rollers;
μ3representing the coefficient of friction between the polishing brick and the conveyor belt;
v0the speed of the driving roller, i.e. the feeding speed of the tiles, is expressed in mm/s;
m1represents the weight of the grinding head in kg;
m2represents the mass of the polished tile in kg;
m3represents the mass of the conveyor belt in kg;
Figure BDA0001677202520000041
showing abrasive grains in
Figure BDA0001677202520000042
Acceleration in a direction;
g represents the acceleration of gravity, and is usually 9.8N/kg;
step A4: constructing an energy consumption model of the ceramic polishing machine, and solving the beam swing energy consumption of the ceramic polishing machine comprises the following steps:
determining a beam swing energy consumption objective function EtransomTarget function E of beam swing energy consumptiontransomEquation (4.1) below:
Figure BDA0001677202520000043
target function E of energy consumption of beam swingtransomThe parametric variables of- - (4.1) are:
l1represents the crank length, in mm:
a represents the amplitude of the beam in mm;
f represents the frequency of the beam oscillation in mm;
ω1representing the angular velocity of the crank, in rad/s;
ω2represents the angular velocity of the connecting rod, in rad/s;
φ1the size of an included angle between the crank and the X axis is in unit rad;
φ2the size of an included angle between the connecting rod and an X axis is unit rad;
m1represents the mass of the crank in kg;
m2represents the mass of the connecting rod in kg;
m3represents the mass of the slider in kg;
step A5: the energy consumption of the auxiliary system of the ceramic polishing machine comprises the energy consumption of a cooling system in the ceramic tile polishing process and the energy consumption of an air pressure system in the ceramic tile polishing process, an energy consumption model of the ceramic polishing machine is built, and the solving of the energy consumption of the auxiliary system of the ceramic polishing machine comprises the following steps:
determining an auxiliary system energy consumption objective function E2Auxiliary system energy consumption objective function E2Equation (5.1) below:
E2＝Ew+Eg--(5.1)；
in formula (5.1), EwRepresenting the energy consumption of the cooling system in the ceramic tile polishing process;
Egto representEnergy consumption of the pneumatic system in the ceramic tile polishing process;
energy consumption E of pneumatic system in ceramic tile polishing processgEquation (5.2) below:
Figure BDA0001677202520000051
the parametric variables for equation (5.2) are:
m1represents the weight of the grinding head in kg;
g represents the acceleration of gravity, usually 9.8N/kg;
q represents the gas flow rate, unit L/min;
a represents the area of the piston in mm2；
Energy consumption E of cooling system in ceramic tile polishing processwThe following formula (5.3) should be satisfied:
Ew＝cρ|tin-tout|q----(5.3)；
the parametric variables for equation (5.3) are:
EWabsolute represents the power loss value, in units J;
c represents the specific heat capacity of the cooling water, and is usually 4.2 × 103J(kg.℃)；
ρ represents the density of the cooling water, and is usually 1.0 × 103kg/m3；
tinRepresents the initial temperature of the cooling water in units;
toutthe temperature of the cooling water after passing through the cooling system is expressed in unit ℃;
q represents the flow rate of the consumed cooling water in units of L.
Preferably, the minimum energy consumption objective function E of the ceramic polishing machine is determined according to the cutting formation energy consumption, the polishing grinding head energy consumption, the transmission roller energy consumption, the beam swing energy consumption and the auxiliary system energy consumption solved in the steps A1-A5chm(x) Obtaining parameters influencing the minimum energy consumption of the ceramic polishing machine;
minimum energy consumption objective function E of ceramic polishing machinechm(x) Should satisfyEquation (6.1):
Figure BDA0001677202520000061
wherein formula (6.1) should satisfy formula (6.2) and formula (6.3):
Figure BDA0001677202520000062
Figure BDA0001677202520000071
in the formula (6.1), η represents the energy consumption conversion coefficient of the ceramic polishing machine;
in the formula (6.3), the metal oxide,
v represents the tile feed speed in mm/s;
omega represents the angular speed of the grinding head in rad/s;
p represents the grinding head air pressure in unit MPa;
f represents the swing frequency of the beam;
preferably, the formula (7.1) and the formula (7.2) of the improved adaptive genetic algorithm are used for obtaining parameter values influencing the minimum energy consumption of the ceramic polishing machine;
Figure BDA0001677202520000072
Figure BDA0001677202520000073
Pm，max(t) and Pm，min(t) represents the upper and lower limits of the crossover probability in the population of the t-th generation;
favgrepresenting the average value of individual fitness in the population;
f' represents the more adaptive of the individuals to be crossed;
f "indicates the more adaptive of the individuals to be mutated.
Drawings
FIG. 1 is a graph illustrating the movement trace of abrasive particles according to the present invention;
FIG. 2 is a force analysis diagram of the grinding head of the present invention;
FIG. 3 is a force analysis diagram of the drive roller of the present invention;
FIG. 4 is a structural view of a beam swing mechanism of the present invention.
Detailed Description
The technical scheme of the invention is further explained by the specific implementation mode in combination with the attached drawings. The embodiment is based on a novel swing type ceramic polishing machine.
The method for optimizing the energy consumption of the ceramic polishing machine based on the improved genetic algorithm comprises the following steps:
step A: constructing and solving an energy consumption model of the ceramic polishing machine, and obtaining parameters influencing the energy consumption of the ceramic polishing machine according to the solving result of the energy consumption model of the ceramic polishing machine; the energy consumption model of the ceramic polishing machine comprises cutting formation energy consumption, polishing grinding head energy consumption, transmission roller energy consumption, beam swing energy consumption and auxiliary system energy consumption;
and B: and improving the adaptive genetic algorithm, and calculating the optimal parameters influencing the energy consumption of the ceramic polishing machine by utilizing the improved adaptive genetic algorithm.
Preferably, the energy consumption generated by the removal of the abrasive particles on the block to the surface material of the tile is formed by cutting of the ceramic polishing machine, a kinematic model of any point P on the block is constructed, as shown in fig. 1, a planar rectangular coordinate system is first established with the left lower side of the tile as an origin, and a planar rectangular coordinate system is defined
Figure BDA0001677202520000081
The shaft is the same as the feeding direction of the polishing brick;
Figure BDA0001677202520000082
the axis represents the swinging direction of the grinding head along with the beam and is connected with
Figure BDA0001677202520000083
With vertical axis, then movement of point PThe motion trajectory may be perpendicular to the vector, and then the motion trajectory of point P may be determined by the vector
Figure BDA0001677202520000084
Indicating movement of tile feed
Figure BDA0001677202520000085
Self-rotation movement of grinding head
Figure BDA0001677202520000086
And lateral movement of the grinding head
Figure BDA0001677202520000087
Figure BDA0001677202520000088
And:
Figure BDA0001677202520000091
Figure BDA0001677202520000092
Figure BDA0001677202520000093
thus, the kinematic equation for the abrasive particle is:
Figure BDA0001677202520000094
in the case of the formula 1.15,
v represents the belt feed speed in mm/s;
t represents the abrasive grain polishing time, and is determined by the transmission speed V of the transmission belt, and the unit is s;
r represents the distance of the abrasive particles from the center of the grinding head in mm;
k represents a rotation direction coefficient and is used for judging the forward rotation or the reverse rotation of the grinding disc, and k is 1 when the grinding head rotates forwards, or k is-1;
omega represents the angular velocity of rotation of the abrasive particles, unit rad/s;
a, the swing amplitude of the beam is in unit mm;
f represents the frequency of the grinding head swinging along with the transverse beam.
In the formula 1.15, the first derivative and the second derivative are respectively obtained for the time t, and the velocity equation and the acceleration equation of the abrasive particles are obtained as follows:
Figure BDA0001677202520000095
Figure BDA0001677202520000096
therefore, the cutting energy dE per abrasive grainchipCan be expressed as:
dEchip＝dEresultant+dEredsstan- - (formula 1.18);
in formula 1.18:
dEresultantrepresenting the resultant force work per abrasive grain, unit J;
dErestiasnrepresents the resistance work of unit abrasive grain, unit J;
resultant force of unit abrasive grains
Figure BDA0001677202520000101
Mass m is phi hd omega, displacement
Figure BDA0001677202520000102
Then resultant work dEresdltantCan be expressed as:
Figure BDA0001677202520000103
m represents the mass per abrasive grain, in g;
a represents the acceleration of the unit abrasive grain in mm/s2；
Figure BDA0001677202520000104
Represents the instantaneous displacement in units of abrasive grain, in mm;
phi denotes the density per unit abrasive grain, unit g/cm3；
h represents the height of a unit abrasive grain, in mm;
d Ω represents the area of unit abrasive grain, unit mm2；
Friction accounts for a large portion of the total work as compared to the resultant force. Mu is the coefficient of friction, P is the pressure of the grinding head, the friction force FfrictionCan be expressed as:
|Ffrictionμ Pd Ω - (formula 1.19);
thus, the frictional force does work dEresistanceCan be expressed as:
Figure BDA0001677202520000105
Figure BDA0001677202520000106
which represents the frictional force per unit area of abrasive grain.
As can be seen from fig. 1, there are two cases of the positions of the abrasive particles: the abrasive particles are not on the ceramic tile, the abrasive particles are not in contact with the ceramic tile at the moment, and the friction coefficient mu is 0; when the abrasive grains are on the tile, the coefficient of friction is a constant value, i.e. mu-mu0·. Therefore, the friction coefficient μ can be rewritten as:
Figure BDA0001677202520000111
therefore, the cutting energy dE per abrasive grainchipComprises the following steps:
Figure BDA0001677202520000112
integration can give:
Figure BDA0001677202520000113
Ωadenotes the total area of all abrasive grains in mm2；
t represents the time taken to polish the tile in units of s.
Preferably, constructing an energy consumption model of the ceramic polishing machine, and solving the energy consumption of a polishing grinding head of the ceramic polishing machine;
as shown in fig. 2, the polishing head was subjected to the following analysis:
the grinding head is acted by 4 forces in total, namely the shape and the friction force F of the grinding headfForce F of hydraulic system on polishing grinding head1' grinding head self-weight mlg and supporting force F of ceramic tile surface to polishing grinding head1' and the torque transmitted by the main shaft to the polishing grinding head is T.
The following tests show that: the rotational inertia expression of the grinding head is as follows:
Figure BDA0001677202520000114
in the formula: m is1The weight of the abrasive head is indicated. Unit kg;
d represents the wheelhead diameter in m.
σ represents the mass per unit area of the grinding head.
If the rotating speed of the grinding head is n, the corresponding angular speed omega is as follows:
ω ═ 2 pi n- - (formula 2.12);
the grinding head torque T is then:
Figure BDA0001677202520000121
when the grinding head polishes the ceramic tile, the rotating speed of the grinding head is kept unchanged all the time, and the energy consumption E of the polishing grinding headheadCan be expressed as:
Figure BDA0001677202520000122
polishing head energy consumption objective function EheadThe parametric variables of- - (2.1) are:
omega represents the angular speed of the grinding head in rad/s;
m1representing the mass of the grinding head in kg;
d represents the diameter of the grinding head in m;
as can be seen from the formula 2.1, the larger the rotational angular velocity of the grinding head is, the larger the grinding head is, the more the polishing head is
The more energy is consumed. This is because the spindle motor needs to provide a larger torque as the grinding stone rotational angular velocity is larger. However, when the rotation angular velocity of the grinding head is too small, the number of times that the abrasive grains stay on the surface of the polished tile is too small, so that the grinding amount cannot meet the requirement of the polishing procedure, and the polishing quality cannot meet the actual production requirement.
Preferably, constructing an energy consumption model of the ceramic polishing machine, and solving the energy consumption of a transmission drum of the ceramic polishing machine;
the stress of the transmission roller is mainly friction force and cutting force generated when the grinding head rotates. When the ceramic tile grinding machine works, the friction force f1 generated between the conveyor belt and the roller is generated, a ceramic tile is placed on the conveyor belt, the friction force between the ceramic tile and the conveyor belt is f2, the friction resistance generated between the ceramic tile and the grinding block is Ff, the pressure Fp of the grinding head on the ceramic tile, the supporting force Fn of the ceramic tile on the grinding head, and the gravity (m) of the grinding head and the ceramic tile1+m2) g, the tiles are fed horizontally at a speed v0, as shown in figure 3. The required circumferential driving force FA on the driving drum is the sum of these running resistances, i.e.:
FA＝f1+f2+Ff- - (formula 3.11);
the friction force Ff of the grinding head to the tile is:
Figure BDA0001677202520000131
μ1the representation represents the coefficient of friction between the abrasive head and the tile.
The friction force f1 between the conveyor belt and the roller is:
f1＝μ2(m1+m2+m3) g- - (formula 3.13);
m2 is the mass of the polished tile, m3 is the mass of the conveyor belt,. mu.2G is the gravitational acceleration, which is the coefficient of friction between the conveyor belt and the rollers.
The friction force f2 between the tile and the conveyor belt is:
f2＝μ3(m1+m2) g- - (formula 3.14);
μ3is the coefficient of friction between the polished tile and the conveyor belt.
The circumferential driving force FA on the driving roller is therefore:
Figure BDA0001677202520000132
therefore, the energy consumption of the transmission roller is as follows:
Figure BDA0001677202520000133
μ1representing the friction coefficient between the grinding block and the ceramic tile;
μ2representing the coefficient of friction between the conveyor belt and the rollers;
μ3representing the coefficient of friction between the polishing brick and the conveyor belt;
v0the speed of the driving roller, i.e. the feeding speed of the tiles, is expressed in mm/s;
m1represents the weight of the grinding head in kg;
m2represents the mass of the polished tile in kg;
m3represents the mass of the conveyor belt in kg;
Figure BDA0001677202520000141
showing abrasive grains in
Figure BDA0001677202520000142
Acceleration in direction
g represents the acceleration of gravity, and is usually 9.8N/kg.
Therefore, it can be seen that the higher the tile feeding speed, the more energy is consumed by the driving roller. This is because the torque of the transmission roller will also increase when the tile feeding speed is greater. The torque of the corresponding drum motor will also increase, and the energy consumption of the corresponding drum motor will also increase. However, when the tile feeding speed is too low, the yield of polished tiles is low, the polishing efficiency is low, and the cost per square meter of polished tiles is high. Therefore, it is not the case that the lower the tile feeding speed, the better.
Preferably, constructing an energy consumption model of the ceramic polishing machine, and solving the swing energy consumption of a cross beam of the ceramic polishing machine;
when the ceramic polishing machine grinds large-sized polished bricks, the side length of the polished bricks is larger than the diameter of the grinding head, and in order to ensure the polishing quality, the grinding head must do reciprocating swing under the action of the cross beam to cover the grinding surface. When the specification of the ceramic tile is larger than the diameter of the grinding head and the feeding speed of the ceramic tile is high, the phenomenon of 'missing throwing' can occur on the surface of the ceramic tile, and the swinging linear speed of the cross beam must be increased for times.
The motion form of the cross beam can be understood as that the swing motor rotates to drive the cross beam to swing left and right. In the present embodiment, the crank-link mechanism is used for the test, and the structure is simplified as shown in fig. 4;
the crank length is assumed to be l1The length of the connecting rod is assumed to be l2(ii) a Angular velocity of crank omega1Angular velocity of the connecting rod is omega2(ii) a The included angle between the crank and the X axis is phi1The connecting rod and the X-axis direction form an included angle phi2(ii) a The mass of the crank, the connecting rod and the sliding block is m respectively1，m2，m3(ii) a The velocity of the slider is assumed to be v3(ii) a The moment applied to the crank by the motor is tau; the displacement of the slide block is s; the friction force on the sliding block is F3。
Connecting rod1Power P of1Comprises the following steps:
Figure BDA0001677202520000151
crank l2Power P of2Comprises the following steps:
Figure BDA0001677202520000152
power P of the slider3Comprises the following steps:
P3＝m3v3＝m3l1(ω1+ω2)·|sinφ1|；
energy consumption of beam swing EtransomComprises the following steps:
Etranson＝P1+P2+P3；
therefore, the energy consumption of the beam swing is as follows:
Figure BDA0001677202520000153
l1represents the crank length, in mm:
a represents the amplitude of the beam in mm;
f represents the frequency of the beam oscillation in mm;
ω1representing the angular velocity of the crank, in rad/s;
ω2represents the angular velocity of the connecting rod, in rad/s;
φ1the size of an included angle between the crank and the X axis is unit rad;
φ2the size of an included angle between the connecting rod and an X axis is unit rad;
m1represents the mass of the crank in kg;
m2represents the mass of the connecting rod in kg;
m3represents the mass of the slider in kg.
From the equation 4.1, it can be known that the larger the swing frequency of the beam is, the more energy is consumed by the swing of the beam. When the swing frequency of the cross beam is too low, the phenomenon of 'missing polishing' can occur, and the polishing quality can not be ensured. When the swing frequency of the cross beam is too large, the swing linear speed of the cross beam is too fast, the reciprocating times are multiple, and the abrasion and damage frequency of the swing mechanism are increased.
For the energy consumption of the whole polishing system in the tile polishing process, the energy consumption of the auxiliary component is not negligible, and the cooling system and the air pressure system are the main energy consumption components in the auxiliary component, so the energy consumption of the auxiliary system can be expressed as:
E2＝Ew+Eg；
in the formula: ewRepresenting the energy consumption of the cooling system in the ceramic tile polishing process
EgRepresenting the energy consumption of a pneumatic system in the ceramic tile polishing process;
the experiment shows that:
Figure BDA0001677202520000171
the parametric variables for equation (5.2) are:
m1represents the weight of the grinding head in kg;
g represents the acceleration of gravity, usually 9.8N/kg;
q represents the gas flow rate, unit L/min;
a represents the area of the piston in mm2；
The most of the heat dissipated by the cooling system is converted into heat energy, and the heat energy taken away by the cooling water cannot be less than the corresponding heat energy loss under the condition of not causing the high temperature of the grinding head. According to the law of conservation of energy, the cooling flow rate should satisfy the following formula:
Ew＝cρ|tin-tout| q- -formula 5.3;
in the formula: eWAbsolute represents the power loss value, in units J;
c represents the specific heat capacity of the cooling water, and is usually 4.2 × 103J(kg.℃)；
ρ represents the density of the cooling water, and is usually 1.0 × 103kg/m3；
tinRepresents the initial temperature of the cooling water in units;
toutthe temperature of the cooling water after passing through the cooling system is expressed in unit ℃;
q represents the flow rate of the cooling water consumed in units of L; .
Preferably, as can be known from modeling, the parameters influencing the energy consumption of the polishing machine mainly include: the ceramic tile feeding speed V, the grinding head angular speed omega, the grinding head pressure P and the beam swing frequency f.
After the ceramic polishing energy consumption model is established, the polishing energy consumption value can be obtained at any time for the value of any polishing process parameter. However, the values of a specific set of polishing process parameters cannot be determined to satisfy the minimum polishing energy consumption. Therefore, it is necessary to optimize the polishing process parameters while satisfying the processing requirements.
It is necessary to determine the minimum energy consumption objective function E of the ceramic polisherchm(x)；
Minimum energy consumption objective function E of ceramic polishing machinechm(x) The following formula should be satisfied:
Echm(x)＝Echip+Ehead+Eroller+Etransom+Ew+Eg；
Figure BDA0001677202520000181
as can be seen from the formula 6.11, the energy consumption of the ceramic polishing machine relates to a plurality of parameters. However, many parameters are fixed and unadjustable when the machine leaves the factory, so the corresponding parameter values are also fixed values. For the sake of the following calculations, considering only the variables associated with the constraints, and other temporary considerations as constants instead of parameters, we can obtain:
Figure BDA0001677202520000182
wherein formula (6.1) should satisfy formula (6.2) and formula (6.3):
Figure BDA0001677202520000183
Figure BDA0001677202520000191
in the formula (6.1), η represents the energy consumption conversion coefficient of the ceramic polishing machine;
in the formula (6.3), the metal oxide,
v represents the tile feed speed in mm/s;
omega represents the angular speed of the grinding head in rad/s;
p represents the grinding head air pressure in unit MPa;
f represents the swing frequency of the beam;
preferably, the formula (7.1) and the formula (7.2) of the improved adaptive genetic algorithm are used for obtaining parameter values influencing the minimum energy consumption of the ceramic polishing machine;
Figure BDA0001677202520000192
Figure BDA0001677202520000193
Pm，max(t) and Pm，min(t) represents the upper and lower limits of the crossover probability in the population of the t-th generation;
favgrepresenting the average value of individual fitness in the population;
f' represents the more adaptive of the individuals to be crossed;
f "indicates the more adaptive of the individuals to be mutated.
Using the above formulas 7.1 and 7.2, experiments have shown that: when the feeding speed V is 99.54, the grinding head angular speed omega is 45.52, the grinding head pressure P is 0.27 and the beam swinging frequency f is 0.86, the ceramic polishing machine is in a minimum energy consumption state.
The technical principle of the present invention is described above in connection with specific embodiments. The description is made for the purpose of illustrating the principles of the invention and should not be construed in any way as limiting the scope of the invention. Based on the explanations herein, those skilled in the art will be able to conceive of other embodiments of the present invention without inventive effort, which would fall within the scope of the present invention.

Claims (3)

1. A ceramic polishing machine energy consumption optimization method based on an improved genetic algorithm is characterized by comprising the following steps: the energy consumption optimization method of the ceramic polishing machine comprises the following steps:
step A: constructing and solving an energy consumption model of the ceramic polishing machine, and obtaining parameters influencing the energy consumption of the ceramic polishing machine according to the solving result of the energy consumption model of the ceramic polishing machine; the energy consumption model of the ceramic polishing machine comprises cutting formation energy consumption, polishing grinding head energy consumption, transmission roller energy consumption, beam swing energy consumption and auxiliary system energy consumption;
and B: improving a self-adaptive genetic algorithm, and calculating optimal parameters influencing the energy consumption of the ceramic polishing machine by utilizing the improved self-adaptive genetic algorithm;
solving cutting formation energy consumption, polishing grinding head energy consumption, transmission roller energy consumption, beam swing energy consumption and auxiliary system energy consumption in the ceramic polishing machine energy consumption model;
the method comprises the following steps:
step A1: the energy consumption generated by the removal effect of the abrasive particles on the surface material of the ceramic tile is the energy consumption generated by the cutting formation of the ceramic polishing machine,
constructing an energy consumption model of the ceramic polishing machine, and solving the cutting formation energy consumption of the ceramic polishing machine comprises the following steps:
determining a cut forming energy consumption objective function E of a ceramic polishing machinechipAn objective function EchipThe formula (1.1) of (a) is as follows:
Figure FDA0003612913870000011
cutting to form an objective function E of energy consumptionchipThe parametric variables of- - (1.1) are:
Ωadenotes the total area of all abrasive grains in mm2；
t represents the time taken to polish the tile, in units of s;
phi denotes the density per unit abrasive grain, unit g/cm3；
h represents the height of a unit abrasive grain, in mm;
μ represents a friction coefficient between the abrasive grains and the tile;
d Ω represents the area of unit abrasive grain, unit mm2；
a represents the acceleration of the unit abrasive grain in mm/s2；
v represents the velocity per abrasive particle, in mm/s;
p represents the pressure of the grinding head;
step A2: constructing an energy consumption model of the ceramic polishing machine, and solving the energy consumption of a polishing grinding head of the ceramic polishing machine comprises the following steps:
determining polishing grinding head energy consumption objective function EheadPolishing head energy consumption objective function EheadEquation (2.1) below:
Figure FDA0003612913870000021
polishing head energy consumption objective function LheadThe parametric variables of- - (2.1) are:
omega represents the angular speed of the grinding head in rad/s;
m1represents the mass of the grinding head in kg;
d represents the diameter of the grinding head in unit;
step A3: constructing an energy consumption model of the ceramic polishing machine, and solving the energy consumption of a transmission drum of the ceramic polishing machine comprises the following steps:
determining a drive rollerTarget function E of cylinder energy consumptionrollerTarget function of energy consumption of driving drum ErollerEquation (3.1) below:
Figure FDA0003612913870000022
target function E of energy consumption of transmission rollerrollrThe parametric variables of- - (3.1) are:
μ1representing the friction coefficient between the grinding block and the ceramic tile;
μ2representing the coefficient of friction between the conveyor belt and the rollers;
μ3representing the coefficient of friction between the polishing brick and the conveyor belt;
v0the speed of the driving roller, i.e. the feeding speed of the tiles, is expressed in mm/s;
m1represents the weight of the grinding head in kg;
m2represents the mass of the polished tile in kg;
m3represents the mass of the conveyor belt in kg;
Figure FDA0003612913870000031
showing abrasive grains in
Figure FDA0003612913870000032
Acceleration in a direction;
g represents the acceleration of gravity, and is usually taken as 9.8N/kg:
step A4: the method comprises the following steps of constructing a ceramic polishing machine energy consumption model, and solving the cross beam swing energy consumption of the ceramic polishing machine, wherein the steps of:
determining a beam swing energy consumption objective function EtransomTarget function E of beam swing energy consumptiontransomEquation (4.1) below:
Figure FDA0003612913870000033
target function E of energy consumption of beam swingtransomThe parametric variables of- - (4.1) are:
l1represents the crank length, in mm:
a represents the amplitude of the beam in mm;
f represents the frequency of the beam oscillation in mm;
ω1representing the angular velocity of the crank, in rad/s;
ω2represents the angular velocity of the connecting rod, in rad/s;
φ1the size of an included angle between the crank and the X axis is unit rad;
φ2the size of an included angle between the connecting rod and an X axis is in unit rad;
m1represents the mass of the crank in kg;
m2represents the mass of the connecting rod in kg;
m3represents the mass of the slider in kg;
step A5: the auxiliary system energy consumption of the ceramic polishing machine comprises the energy consumption of a cooling system in the ceramic tile polishing process and the energy consumption of an air pressure system in the ceramic tile polishing process, an energy consumption model of the ceramic polishing machine is built, and the solving of the auxiliary system energy consumption of the ceramic polishing machine comprises the following steps:
determining an auxiliary system energy consumption objective function E2Auxiliary system energy consumption objective function E2Equation (5.1) below:
E2＝Ew+Eg--(5.1)；
in formula (5.1), EwRepresenting the energy consumption of the cooling system in the ceramic tile polishing process;
Egrepresenting the energy consumption of a pneumatic system in the ceramic tile polishing process;
energy consumption E of pneumatic system in ceramic tile polishing processgEquation (5.2) below:
Figure FDA0003612913870000041
the parametric variables for equation (5.2) are:
m1represents the weight of the grinding head in kg;
g represents the acceleration of gravity, usually 9.8N/kg;
q represents the gas flow rate, unit L/min;
a represents the area of the piston in mm2；
Energy consumption E of cooling system in ceramic tile polishing processwThe following formula (5.3) should be satisfied:
Ew＝cρ|tin-tout|q----(5.3)；
the parametric variables for equation (5.3) are:
Ewrepresents the power loss to, unit J;
c represents the specific heat capacity of the cooling water, and is usually 4.2 × 103J/(kg.℃)；
ρ represents the density of the cooling water, and is usually 1.0 × 103kg/m3；
tinRepresents the initial temperature of the cooling water in units;
toutthe temperature of the cooling water after passing through the cooling system is expressed in unit ℃;
q represents the flow rate of the consumed cooling water in units of L.
2. The method for optimizing the energy consumption of the ceramic polishing machine based on the improved genetic algorithm is characterized in that:
determining a minimum energy consumption objective function E of the ceramic polishing machine according to the cutting formation energy consumption, the polishing grinding head energy consumption, the transmission roller energy consumption, the beam swing energy consumption and the auxiliary system energy consumption solved in the steps A1-A5chm(x) Obtaining parameters influencing the minimum energy consumption of the ceramic polishing machine;
minimum energy consumption objective function E of ceramic polishing machinechm(x) Equation (6.1) should be satisfied:
Figure FDA0003612913870000051
wherein formula (6.1) should satisfy formula (6.2) and formula (6.3):
Figure FDA0003612913870000052
Figure FDA0003612913870000061
in the formula (6.1), η represents the energy consumption conversion coefficient of the ceramic polishing machine;
in the formula (6.3), the metal oxide,
v represents tile feed speed in mm/s;
omega represents the angular speed of the grinding head in rad/s;
p represents the wheelhead air pressure, unit MPa:
f represents the beam oscillation frequency.
3. The method for optimizing the energy consumption of the ceramic polishing machine based on the improved genetic algorithm is characterized by comprising the following steps of:
obtaining parameter values influencing the minimum energy consumption of the ceramic polishing machine by using a formula (7.1) and a formula (7.2) of an improved adaptive genetic algorithm;
the adaptive genetic algorithm formula (7.1) and formula (7.2) are as follows:
Figure FDA0003612913870000062
Figure FDA0003612913870000063
Pm，max(t) and Pm，min(t) represents the upper and lower limits of the crossover probability in the population of the t-th generation;
favgrepresenting the average value of individual fitness in the population;
f' represents the more adaptive of the individuals to be crossed;
f "indicates the more adaptive of the individuals to be mutated.
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