CN110059846A - The technological parameter higher-dimension Multipurpose Optimal Method of polyester fiber polymerization esterification process - Google Patents
The technological parameter higher-dimension Multipurpose Optimal Method of polyester fiber polymerization esterification process Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 122
- 230000008569 process Effects 0.000 title claims abstract description 82
- 230000032050 esterification Effects 0.000 title claims abstract description 74
- 238000005886 esterification reaction Methods 0.000 title claims abstract description 74
- 238000006116 polymerization reaction Methods 0.000 title claims abstract description 62
- 229920000728 polyester Polymers 0.000 title claims abstract description 55
- 239000000835 fiber Substances 0.000 title claims abstract description 53
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- 238000006243 chemical reaction Methods 0.000 claims description 42
- MTHSVFCYNBDYFN-UHFFFAOYSA-N diethylene glycol Chemical compound OCCOCCO MTHSVFCYNBDYFN-UHFFFAOYSA-N 0.000 claims description 35
- 230000007246 mechanism Effects 0.000 claims description 11
- 230000008859 change Effects 0.000 claims description 10
- 239000000463 material Substances 0.000 claims description 10
- 230000035484 reaction time Effects 0.000 claims description 7
- 239000007788 liquid Substances 0.000 claims description 4
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- 238000005303 weighing Methods 0.000 claims 1
- 238000004519 manufacturing process Methods 0.000 abstract description 8
- 229920000642 polymer Polymers 0.000 abstract description 4
- 238000005457 optimization Methods 0.000 description 30
- KKEYFWRCBNTPAC-UHFFFAOYSA-N Terephthalic acid Chemical compound OC(=O)C1=CC=C(C(O)=O)C=C1 KKEYFWRCBNTPAC-UHFFFAOYSA-N 0.000 description 23
- LYCAIKOWRPUZTN-UHFFFAOYSA-N Ethylene glycol Chemical compound OCCO LYCAIKOWRPUZTN-UHFFFAOYSA-N 0.000 description 18
- 230000000694 effects Effects 0.000 description 7
- 239000012071 phase Substances 0.000 description 6
- 239000002002 slurry Substances 0.000 description 6
- 239000007791 liquid phase Substances 0.000 description 5
- 239000000047 product Substances 0.000 description 5
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 5
- 238000010438 heat treatment Methods 0.000 description 4
- 238000004364 calculation method Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 230000001788 irregular Effects 0.000 description 3
- 241000208340 Araliaceae Species 0.000 description 2
- 235000005035 Panax pseudoginseng ssp. pseudoginseng Nutrition 0.000 description 2
- 235000003140 Panax quinquefolius Nutrition 0.000 description 2
- 230000000052 comparative effect Effects 0.000 description 2
- 230000007812 deficiency Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000009826 distribution Methods 0.000 description 2
- 238000001704 evaporation Methods 0.000 description 2
- 230000008020 evaporation Effects 0.000 description 2
- 235000008434 ginseng Nutrition 0.000 description 2
- 238000013178 mathematical model Methods 0.000 description 2
- -1 poly(ethylene terephthalate) Polymers 0.000 description 2
- 229920000139 polyethylene terephthalate Polymers 0.000 description 2
- 239000005020 polyethylene terephthalate Substances 0.000 description 2
- 238000012216 screening Methods 0.000 description 2
- 239000000126 substance Substances 0.000 description 2
- 241000183024 Populus tremula Species 0.000 description 1
- IKHGUXGNUITLKF-XPULMUKRSA-N acetaldehyde Chemical group [14CH]([14CH3])=O IKHGUXGNUITLKF-XPULMUKRSA-N 0.000 description 1
- 230000003044 adaptive effect Effects 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- QPKOBORKPHRBPS-UHFFFAOYSA-N bis(2-hydroxyethyl) terephthalate Chemical compound OCCOC(=O)C1=CC=C(C(=O)OCCO)C=C1 QPKOBORKPHRBPS-UHFFFAOYSA-N 0.000 description 1
- 239000006227 byproduct Substances 0.000 description 1
- 125000003178 carboxy group Chemical group [H]OC(*)=O 0.000 description 1
- 238000003889 chemical engineering Methods 0.000 description 1
- 238000005094 computer simulation Methods 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 238000005265 energy consumption Methods 0.000 description 1
- 150000002148 esters Chemical class 0.000 description 1
- 235000019256 formaldehyde Nutrition 0.000 description 1
- 230000002068 genetic effect Effects 0.000 description 1
- 125000002887 hydroxy group Chemical group [H]O* 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 239000002245 particle Substances 0.000 description 1
- 238000006068 polycondensation reaction Methods 0.000 description 1
- 239000011541 reaction mixture Substances 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000000630 rising effect Effects 0.000 description 1
- 229920006395 saturated elastomer Polymers 0.000 description 1
- 238000000926 separation method Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 238000010792 warming Methods 0.000 description 1
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Abstract
The present invention relates to a kind of technological parameter higher-dimension Multipurpose Optimal Methods of polyester fiber polymerization esterification process, using one group of process parameter value and its corresponding technic index value as individual, time multiple individuals are selected in multiple individuals using improved RVEA algorithm, again based on user preference after selecting an optimum individual in secondary multiple individuals, by the technological parameter of the process parameter value setting polyester fiber polymerization esterification process of optimum individual, plurality of individual is by after generation multiple groups process parameter value, it is entered into objective function by group, it is obtained by the corresponding technic index value of objective function output each group, projector distance operator is added in angle punishment distance in improved RVEA algorithm, the solution made has preferably convergence and diversity.The present invention punishes the improvement of distance by the angle to RVEA algorithm, can optimize simultaneously to multiple targets, and guarantees the diversity and convergence that understand, realizes differential production high quality polyester fiber polymer.
Description
Technical field
The invention belongs to technical field of production process of chemical fibers, are related to a kind of technological parameter of polyester fiber polymerization esterification process
Higher-dimension Multipurpose Optimal Method.
Background technique
Polymerization process is that polyester fiber produces full-range research primary link.The process includes esterification, precondensation and end
Polycondensation three phases.And esterification process is the leading link of entire polymerization process, technical process is first by terephthalic acid (TPA)
It is mixed with certain proportion in slurry tank with ethylene glycol, then by prepared slurry with being pumped into surge tank and continuous metering is sent
Enter esterifying kettle.
Multi-objective optimization question of the target dimension more than or equal to 4 is known as higher-dimension multi-objective optimization question.Currently, higher-dimension is more
The correlative study that objective optimization algorithm is applied to polyester fiber polymerization esterification production process is few, most of according to experimental result tune
It is whole or polyester fiber polymerization esterification process is optimized using mixed Gauss model and traditional low-dimensional multi-objective optimization algorithm.Example
As document 1 (esterification process optimization [D] the East China University of Science based on multi-objective genetic algorithm, 2003.) proposes to be based on NSGA-
II multi-objective optimization algorithm optimizes the technological parameter of polyester fiber polymerization esterification process, and solution is one 2 dimension work
The optimization problem of skill index, the algorithm cannot keep the convergence and diversity of disaggregation to higher-dimension multi-objective optimization question.With this
Meanwhile document 2 (Hu Yaohui Mathematical Model for Direct Esterification Process of PET [D] Beijing University of Chemical Technology, 2003.), 3 (A of document
mathematical model for computer simulation of a direct continuous
esterification process between terephthalic acid and ethylene glycol[J]
.Polymer Engineering&Science, 2010,25 (12): 788-795.) and 4 (Multiobjective of document
optimization of an industrial wiped film poly(ethylene terephthalate)reactor:
some further insights[J].Computers&Chemical Engineering,2001,25(2):391-407.)
Have studied the mechanism model of polyester fiber polymerization esterification process, document 5 (large polyester production process intelligent modeling, control with it is excellent
Change and studies [D] East China University of Science, 2010.) on the basis of above-mentioned model, using Aspen Plus software to polymerization process
Intelligent modeling not only proposes a kind of hybrid intelligent for combining Estimation of Distribution Algorithm with Cauchy's Distribution Algorithm and particle swarm algorithm
Optimization algorithm and polymerization esterification process model is established with the intelligent algorithm proposed and is certainly with reaction temperature and residence time
Plan variable is optimized with the minimum single optimization aim of energy consumption, has certain directive function to actual production.But
It is polyester fiber polymerization esterification process is a complicated industrial process, performance indicator runs far deeper than three, carry out 1 to it~
The optimization of 2 targets can not make polyester fiber polymerization esterification process global optimization, therefore, to polyester fiber polymerization esterification process
The optimization for carrying out higher-dimension multiple target is very important.
In recent years with the development for decomposing evolution thought, higher-dimension multi-objective problem has obtained solution to a certain extent,
In, the algorithm decomposed based on reference vector to object space achieves good effect on higher-dimension multiple target test set,
And in numerous intelligent algorithms for higher-dimension multiple-objection optimization, RVEA (A Reference Vector Guided
Evolutionary Algorithm) there is disaggregation to be uniformly distributed, the advantages such as multiple target equilibrium consideration and calculating speed are very fast, then
In addition RVEA diagonally punishes the use of distance, so that population can not only rapidly converge to optimal leading surface, and it is able to maintain solution
It is uniformly distributed.But as target dimension increases, the efficiency for solving higher-dimension multi-objective optimization question can sharply decline, wherein main former
Because being exactly increasing with target dimension, the number for optimizing solution is exponentially increased, and traditional multi-objective optimization algorithm use is non-
It dominating selection strategy and selects insufficient pressure on higher-dimension multi-objective problem, population can not converge to global optimum, so that its
Effect of optimization when optimizing to multiple targets is poor.
It would therefore be highly desirable to which it is poly- to need to study a kind of polyester fiber that effect of optimization when optimizing to multiple process goals is good
Close the technological parameter higher-dimension Multipurpose Optimal Method of esterification process.
Summary of the invention
In view of the deficiencies of the prior art, it is an object of the present invention to provide it is a kind of multiple targets are optimized when optimization effect
The technological parameter higher-dimension Multipurpose Optimal Method of the good polyester fiber polymerization esterification process of fruit.The present invention passes through to RVEA algorithm
Angle punishment the distance calculating of (APD) and the improvement of screening process propose that one kind can be to multiple targets (4 and process above ginseng
Number) the technological parameter higher-dimension Multipurpose Optimal Method of polyester fiber polymerization esterification process that optimizes.
In order to achieve the above object, the present invention adopts the following technical scheme that:
The technological parameter higher-dimension Multipurpose Optimal Method of polyester fiber polymerization esterification process, with one group of process parameter value and its
Corresponding technic index value selects time multiple individuals, then base in multiple individuals as individual, using improved RVEA algorithm
It is fine by the process parameter value setting polyester of optimum individual in user preference after selecting an optimum individual in secondary multiple individuals
Tie up the technological parameter of polymerization esterification process；
Process parameter value is the value of technological parameter, and technological parameter is reaction temperature T, reaction pressure P, reaction time
The wet end furnish r of τ and EG/PTA, unit is respectively as follows: DEG C, mmHg, min and 1；
Technic index value is the value of technic index, and technic index is esterification yield Es, average degree of polymerization Pn, average molecular weight
MnWith diethylene glycol (DEG) mol percent content Wt, unit is respectively as follows: %, 1,1 and %；
Multiple individuals are by being entered into objective function by group, by target letter after generation multiple groups process parameter value
The corresponding technic index value of number output each group obtains, and the expression formula of objective function is as follows:
Improved RVEA algorithm thes improvement is that angle punishes that distance, improved angle punishment distance are denoted as dt,i,j, table
It is as follows up to formula:
In formula, M is target number, and t is evolutionary generation, tmaxFor maximum evolutionary generation, α dt,i,jRate of change, i table
Object vector after showing i-th of individual conversion, j indicate j-th of reference vector, θt,i,jIt indicates when i-th of individual conversion in former generation
The angle of object vector and reference vector j afterwards,What is indicated is the minimum angle worked as in former generation between all reference vectors,
ft,iFor t generation obtained target function value,The minimum value in all target function values obtained for t generation, | | f 't,i||
For the Euclidean distance between the objective function and origin after conversion；
Optimum individual be by according to user preference from Es、Pn、MnAnd WtAfter middle selection one is as technic index is referred to,
It is selected from secondary multiple individuals and is worth what maximum individual obtained with reference to technic index.
As a preferred technical scheme:
The technological parameter higher-dimension Multipurpose Optimal Method of polyester fiber polymerization esterification process as described above, the target letter
Mechanism model of several foundation based on polyester fiber polymerization esterification process.
The technological parameter higher-dimension Multipurpose Optimal Method of polyester fiber polymerization esterification process as described above, the polyester are fine
The mechanism model of polymerization esterification process is tieed up by vapor liquid equilibrium equation, reaction rate equation, material balance equation and conservation of mass side
Cheng Lianli is obtained；
Wherein, vapor liquid equilibrium equation is as follows:
Material balance equation and mass-conservation equation are as follows:
R1=-k1 × c1 × c2+k2 × c3 × c5-k3 × c1 × c3+k4 × c4 × c5-k1 × c1 × c8
+k2×c5×c7+k10×c3
R2=-k1 × c1 × c2+k2 × c3 × c5+k5 × c3^2-k6 × c2 × c4
-k8×c2×c3-2×k9×c2^2
R3=k1 × c1 × c2-k2 × c3 × c5-2 × k5 × c3^2-k3 × c1 × c3+k4 × c4 × c5
+k6×c4×c2-2×k7×c3^2-k8×c2×c3-k10×c3-k5×c10×c3
R4=k3 × c1 × c3-k4 × c4 × c5+k5 × c3^2-k6 × c4 × c2
R5=k1 × c1 × c2-k2 × c3 × c5+k3 × c1 × c3-k4 × c4 × c5+k7 × c3^2
+k8×c2×c3+k9×c2^2+k1×c1×c8-k2×c5×c7
R6=k7 × c3^2
R7=k8 × c2 × c3+k1 × c1 × c8-k2 × c5 × c7
R8=k9 × c2^2-k1 × c1 × c8+k2 × c5 × c7
R9=k10 × c3
Esterification yield calculation formula is as follows:
Diethylene glycol content percentage calculation formula is as follows:
It is as follows that average molecular weight calculates formula:
Average degree of polymerization calculation formula is as follows:
W=F0× τ, c20=c10 × r；
In formula, MnFor average molecular weight, PnFor average degree of polymerization, EsFor esterification yield, WtContain for diethylene glycol (DEG) mol percent
Amount, unit is respectively as follows: 1,1, % and %, T be reaction temperature, unit is DEG C that P is reaction pressure, and unit mmHg, τ are reaction
Residence time, unit min, r are the wet end furnish of EG/PTA, and unit 1, W is reactor reaction mixture gross mass, single
Position is kg, F0For into flow, unit mol/min, F are away flow, unit mol/min,WithFor H2O and EG
Saturated vapour pressure, unit mmHg, rEGWithFor EG and H2The activity coefficient of O, k1-k10 are chemical reaction rate constant,
It is kg/ (molh) that unit, which is respectively as follows: k1-k9, and k10 unit is 1/h, and c1-c9 respectively represents the concentration of each component in liquid phase, is had
Body are as follows: c1 is carboxyl end group (terephthalic acid (TPA)), and c2 is ethylene glycol, and c3 is terminal hydroxy group (bishydroxyethyl terephthalate), and c4 is ester
Base (pet polymer), c5 are water, c6, c7, c8, are various forms of diethylene glycol (DEG)s, and c9 is acetaldehyde, unit mol/kg, c10~
C90 respectively corresponds as the initial concentration of c1-c9 each component, unit mol/kg, and R1-R9 respectively corresponds as c1-c9 each component
Reaction rate equation, unit are kg/ (molh), QEG,Respectively indicate EG and H2The ethylene glycol that O is transmitted from liquid phase to gas phase
Amount, that is, reactor in EG evaporation capacity and evaporation capacity from liquid phase from water to the amount, that is, reactor for the water that gas phase is transmitted, unit be
kg/h,ηEG,Respectively indicate EG and H2The equilibrium concentration of O, unit mol/kg, Q'EGIt indicates to flow back to reactor from knockout tower
EG flow, unit kg/h, k λ indicate chemical reaction rate constant, λ=1,2,3...10, k λ respectively correspond the change of k1-k10
Learn reaction rate constant, AλFor frequency factor, unit 1, EλFor reaction activity, unit cal/mol, R are gas constants,
Unit is cal/ (mol*K), TλFor absolute temperature, unit K；KEGα,The mass tranfer coefficient of EG and water is respectively represented, it is single
Position is kg/ (hkPa),And cPTARespectively represent the concentration in the initial concentration and reaction process of terephthalic acid (TPA), unit
For mol/kg, cDEGAnd WDEGThe concentration of diethylene glycol (DEG) and the relative molecular mass of diethylene glycol (DEG) are respectively represented, unit is respectively mol/kg
And kg,WithRespectively EG and H2The reactor inner vapor pressure of O, yEGWithIndicate EG and H2The gas phase mole fraction of O,
xEGWithIndicate EG and H2The liquid phase mole fraction of O, P are stagnation pressure in reactor, unit mmHg.
The technological parameter higher-dimension Multipurpose Optimal Method of polyester fiber polymerization esterification process as described above, the target letter
Number is to export E by model by the way that the numerical value of T, P, τ and r to be input in polyester fiber polymerization esterification process mechanism models、Pn、
MnAnd WtNumerical value after converted.
The technological parameter higher-dimension Multipurpose Optimal Method of polyester fiber polymerization esterification process as described above, optimum individual
It is specific to determine that steps are as follows:
(1) according to the constraint condition of technological parameter, process parameter value is carried out using Latin Hypercube Sampling method initial
Change, generates N group technological parameter, while generating equally distributed M group reference vector using simplex lattice method, enable the number of iterations Pt=
1；
(2) N group process parameter value is inputted into objective function, N group technic index value is exported by it, with each group process parameter value
And its corresponding target function value is as individual；
(3) binary intersection is carried out to all individuals and multinomial makes a variation；
(4) individual after the prechiasmal individual that will make a variation intersects with variation merges as one containing 2N individual
Population, with season Pt=Pt+1；
(5) individual in population is selected using improved RVEA algorithm, the individual selected forms new population；
(6) floor operation is carried out to the product for setting maximum algebra and fr, if obtained number is G, judges PtDivided by G remainder
It whether is zero, if it is, updating reference vector, more new formula are as follows:In formula, V is updated
Reference vector, V0For initial reference vector,For maximum value in current solution,For minimum value in current solution, enter step
(7)；Conversely, N is then enabled to be equal to the individual number that step (5) are selected, return step (3)；
(7) judge PtWhether it is less than and sets maximum algebra, if it is, N is enabled to be equal to individual that step (5) are selected
Number, return step (3)；Conversely, then stopping iteration, into next step；
(8) optimum individual is selected based on user preference.
The technological parameter higher-dimension Multipurpose Optimal Method of polyester fiber polymerization esterification process as described above, the technique ginseng
Several constraint condition is as follows:
The constraint condition of above four technological parameters is mainly by the knowhow gained of worker, and the present invention passes through multiple target
Aforementioned four technological parameter is combined by optimization algorithm, and Product Process index is made to have reached enterprise's desirable, so that in work
In the constraint condition of skill parameter, the more effective technological parameter combined goes that enterprise is instructed to produce.
The technological parameter higher-dimension Multipurpose Optimal Method of polyester fiber polymerization esterification process as described above, the value model of N
Enclosing for the value range of 130~150, M is 90~100, sets maximum algebra as 100 generations, fr 0.1.Invention mechanism:
The reference vector of the algorithm (RVEA) of higher-dimension multiple-objection optimization based on reference vector guidance asks multiple-objection optimization
Topic is converted into a series of single-object problems, can be gone according to user preference effectively close to true leading surface, and the algorithm
An angle punishment distance (Angle-penalized distance) is proposed, the root in higher-dimension object space is enabled the algorithm to
Reference vector is generated according to objective function dynamic self-adapting, the expression formula of RVEA adaptive angle punishment distance (APD) is as follows:
In formula, M is target number, and t is evolutionary generation, tmaxFor maximum evolutionary generation, α dt,i,jRate of change, i table
Object vector after showing i-th of individual conversion, j indicate j-th of reference vector, θt,i,jIt indicates when i-th of individual conversion in former generation
The angle of object vector and reference vector j afterwards,What is indicated is the minimum angle worked as in former generation between all reference vectors,
ft,iFor t generation obtained target function value,The minimum value in all target function values obtained for t generation, | | f 't,i||
For the Euclidean distance between the objective function and origin after conversion；
As can be seen from the above equation, when t is much smaller than tmaxWhen, dt,i,j≈||f′t,i||；When t is close to tmaxWhen,Since possible solution can also continue to converge to ideal point, this kind of algorithm makes population repeatedly
Withhold to hold back and be more concerned with convergence early period, in the iteration later period, be more concerned with diversity, this cause the iteration later period solve convergence not
It is good.
One population diversity detective operators of addition can overcome above-mentioned to a certain extent in above-mentioned RVEA algorithm
For RVEA algorithm in the problem of iteration later period convergence deficiency, improved angle, which is punished, is denoted as dt,i,j, expression formula is as follows:
So distance APD such as following formula is punished at improved angle:
dt,i,j=(1+P (θi,i,j))·||f′t,i||；
In formula, M is target number, and t is evolutionary generation, tmaxFor maximum evolutionary generation, α tmaxRate of change, α indicate
Dt,i,jThe object vector of individual, i indicate i-th of reference vector, j indicate in the former generation object vector of j-th of individual with
Reference vector θt,i,jAngle, what i was indicated is the minimum angle in the former generation between all reference vectors, and j is when former generation refers to
Empty reference vector number in vector set, nt-1For the empty reference vector number concentrated when the previous generation reference vector of former generation,
For threshold value.
It is that a population diversity detective operators are added on the basis of existing technology that the algorithm, which mainly improves thought, is saved
One fixed reference vector set finds an associated reference according to the angle of individual to reference vector for each individual in population
Vector, if being less than threshold value for the difference of associated reference vector up and down, then it is assumed that population diversity is kept preferably, and Evolutionary direction is to restrain
Property based on, on the contrary then think that population diversity is insufficient at this time, Evolutionary direction is based on diversity.But the above thought of improving has one
Fixed limitation judges the diversity of solution using the number of the blank vector of reference vector, the number of blank vector is than certain threshold
Value is big, it is meant that the diversity of solution is bad, need to consider the diversity for increasing solution, but (irregular i.e. true for irregular problem
Real leading surface is uniformly distributed in object space, and each reference vector has an associated individual, and it is irregular on the contrary, leading surface simultaneously
It is not covered with entire object space, perhaps the only sub-fraction in object space, so many dereferenced reference vectors are had, but
Do not mean that the diversity of solution is bad at this time), the number of associated reference vector is seldom, considers diversity by force at this time, also simultaneously
It not will increase the number effectively solved.
The present invention improves the angle punishment distance of RVEA algorithm, and improved angle punishment distance is denoted as dt,i,j, table
It is as follows up to formula:
In formula, M is target number, and t is evolutionary generation, tmaxFor maximum evolutionary generation, α dt,i,jRate of change, i table
Object vector after showing i-th of individual conversion, j indicate j-th of reference vector, θt,i,jIt indicates when i-th of individual conversion in former generation
The angle of object vector and reference vector j afterwards,What is indicated is the minimum angle worked as in former generation between all reference vectors,
ft,iFor t generation obtained target function value,The minimum value in all target function values obtained for t generation, | | f 't,i||
For the Euclidean distance between the objective function and origin after conversion.
Above-mentioned improved main thought is: projector distance operator is added (i.e.),
Projector distance is not considered early period in iteration convergence, the diversity of solution is not only considered in the iteration later period, it is also contemplated that Xie Can
The projector distance on vector is examined, this solution made has preferably convergence and diversity.This is because for not improving
Angle punishment distance for, as t < < tmaxWhen, dt,i,j≈||f′t,i| |, i.e. the angle of object vector and reference vector is small, no
It can represent that target point is close apart from ideal point, so the present invention is by being added projector distance of the object vector in reference vector,
While guaranteeing that object vector and reference vector angle are small, also the solution in object space can be made closer apart from ideal point, in turn
The optimization solution closer to true leading surface is obtained, at the same time, is worked simultaneously in iteration later period algorithm diversity with convergence.
Specific as illustrated in fig. 1 and 2, dotted line represents object vector in figure, and solid line represents reference vector, and d1 is between objective function and origin
Euclidean distance, projector distance of the d2 between objective function and origin, f1 and f1 are objective function, and θ is reference vector and mesh
The angle of vector is marked, is a solution in object space, although reference vector and the angle theta of object vector are smaller in Fig. 1, not
It can illustrate that target function value is closer apart from ideal point, and projector distance is added, as shown in Fig. 2, can then guarantee that not only angle is small,
And it is closer apart from ideal point.
The utility model has the advantages that
(1) present invention proposes a kind of technological parameter higher-dimension Multipurpose Optimal Method of polyester fiber polymerization esterification process, right
The calculating and screening of distance are punished at the angle of the algorithm of higher dimensional space adaptable search optimal solution based on reference vector guidance population
It is improved, so that population is not only guaranteed the diversity understood during evolution, while also ensuring the convergence of solution；
(2) the technological parameter higher-dimension Multipurpose Optimal Method of a kind of polyester fiber polymerization esterification process of the invention, really
Actual production theoretically is instructed, by process optimization, obtains one group of optimal solution set, enterprise can select according to user demand
More suitably solution and technological parameter can reach the requirement of differential production high quality polyester fiber polymer.
Detailed description of the invention
Fig. 1 is that APD criterion restrains operator figure in RVEA algorithm；
Fig. 2 is the increased convergence operator figure of APD criterion in improved RVEA algorithm of the invention；
Fig. 3 is polyester fiber polymerization esterification process schematic；
Fig. 4 is the flow chart of the technological parameter higher-dimension Multipurpose Optimal Method of polyester fiber polymerization esterification process；
Fig. 5 is the schematic diagram of the technological parameter collection after the Pareto disaggregation obtained using the method for the present invention and optimization；
Fig. 6 is the schematic diagram of the technological parameter collection after the Pareto disaggregation and optimization obtained using the method for the prior art；
Wherein, 1- heater, 2- esterifying kettle, 3- knockout tower, 4- oligomer delivery pump.
Specific embodiment
The invention will be further elucidated with reference to specific embodiments.It should be understood that these embodiments are merely to illustrate this hair
It is bright rather than limit the scope of the invention.In addition, it should also be understood that, after reading the content taught by the present invention, art technology
Personnel can make various changes or modifications the present invention, and such equivalent forms equally fall within the application the appended claims and limited
Fixed range.
The process route of polyester fiber polymerization esterification process are as follows: the terephthalic acid (TPA) and ethylene glycol of room temperature are existed with certain proportion
It is entered in esterifying kettle after being mixed in feeder channel, then material reacted under the conditions of heating medium for heating and in esterifying kettle
Mixing, is finally warming up to 250-290 DEG C of progress esterification, specific as shown in figure 3, the EG/PTA slurry sent from slurry supply tank
Material injects esterification system by the lower end pipeline of heater, under the heating effect of rising liter of heater 1, the material that is newly added with
Old material forms one by U-tube to heater again to the circulation of esterifying kettle 2 in esterification system together, is being circulated throughout
Cheng Zhong, esterification constantly carry out, and heat needed for esterification and the heating of new material is constantly supplemented by heater, reach
The oligomer required to esterification, which is constantly sent by oligomer delivery pump 4 to prepolymerization reaction kettle from the tube bottom of U-tube, carries out preshrunk
It is poly-.In the process, the common work of most liquid phase material motive force caused by the pressure difference of double-chamber structure and density contrast
Enter heater through U-tube with lower, is mixed again with slurry, the water and excessive ethylene glycol that esterification generates, in esterifying kettle
Stopped at the biggish gas-phase space of mistress, separate oligomer, to avoid more entrainment, then by gas phase pipe into
Enter knockout tower 3 and carry out rectifying separation, completes polymerization esterification.
The technological parameter higher-dimension Multipurpose Optimal Method of polyester fiber polymerization esterification process, flow chart is as shown in figure 4, tool
Steps are as follows for body:
(1) according to the constraint condition of technological parameter, process parameter value is carried out using Latin Hypercube Sampling method initial
Change, generates N group technological parameter, while generating equally distributed M group reference vector using simplex lattice method, enable the number of iterations Pt=
1, the value range that wherein value range of N is 130~150, M is 90~100, and the constraint condition of technological parameter is as follows:
Wherein, T is reaction temperature, and P is reaction pressure, and τ is reaction time, and r is the wet end furnish of EG/PTA, unit
It is respectively as follows: DEG C, mmHg, min and 1；
(2) N group process parameter value is inputted into objective function, N group technic index value is exported by it, with each group process parameter value
And its corresponding target function value, as individual, the expression formula of objective function is as follows:
In formula, MnFor average molecular weight, PnFor average degree of polymerization, EsFor esterification yield, WtContain for diethylene glycol (DEG) mol percent
Amount, unit is respectively as follows: 1,1, % and %, T be reaction temperature, P is reaction pressure, and τ is reaction time, and r is EG/PTA's
Wet end furnish, unit is respectively as follows: DEG C, mmHg, min and 1；
Mechanism model of the foundation of objective function based on polyester fiber polymerization esterification process, polyester fiber polymerization esterification process
Mechanism model obtained by reaction rate equation, vapor liquid equilibrium equation, material balance equation and mass-conservation equation simultaneous, target
Function is to export E by model by the way that the numerical value of T, P, τ and r to be input in polyester fiber polymerization esterification process mechanism models、
Pn、MnAnd WtNumerical value after converted；
(3) binary intersection is carried out to all individuals and multinomial makes a variation；
(4) by variation intersect top n individual and variation intersect after individual merge become one it is individual containing 2N
Population, with season Pt=Pt+1；
(5) individual in population being selected using improved RVEA algorithm, the individual selected forms new population,
Improved RVEA algorithm thes improvement is that distance, improved angle punishment distance note are punished in angle compared to general RVEA algorithm
For dt,i,j, expression formula is as follows:
In formula, M is target number, and t is evolutionary generation, tmaxFor maximum evolutionary generation, α dt,i,jRate of change, i table
Object vector after showing i-th of individual conversion, j indicate j-th of reference vector, θt,i,jIt indicates when i-th of individual conversion in former generation
The angle of object vector and reference vector j afterwards,What is indicated is the minimum angle worked as in former generation between all reference vectors,
ft,iFor t generation obtained target function value,The minimum value in all target function values obtained for t generation, | | f 't,i||
For the Euclidean distance between the objective function and origin after conversion；
(6) floor operation is carried out to the product for setting maximum algebra (100 generation) and fr (0.1), if obtained number is G, sentenced
Disconnected PtIt whether is zero divided by G remainder, if it is, updating reference vector, more new formula are as follows:Formula
In, V is updated reference vector, V0For initial reference vector,For maximum value in current solution,For in current solution most
Small value enters step (7)；Conversely, N is then enabled to be equal to the individual number that step (5) are selected, return step (3)；
(7) judge PtWhether it is less than and sets maximum algebra, if it is, N is enabled to be equal to individual that step (5) are selected
Number, return step (3)；Conversely, then stopping iteration, into next step；
(8) user preference is based on from Es、Pn、MnAnd WtAfter middle selection one is as technic index is referred to, from secondary multiple individuals
In select with reference to the maximum individual of technic index value as optimum individual；
(9) by the technological parameter of the process parameter value setting polyester fiber polymerization esterification process of optimum individual.
Embodiment 1
A kind of technological parameter higher-dimension Multipurpose Optimal Method of polyester fiber polymerization esterification process, what setting was intended to be esterified
The technic index of product: esterification yield 92%, the degree of polymerization 3, average molecular mass 600, diethylene glycol content percentage are
0.4%, it is intended to be esterified to obtain according to the technological parameter higher-dimension Multipurpose Optimal Method solution of polyester fiber polymerization esterification process as above
Product technological parameter, wherein setup parameter α=0.2, fr=0.1, hereditary crossing-over rate be 1.0, aberration rate 0.1, N
Value be 145, by 100 generation evolutionary computations, finally obtained Pareto disaggregation and optimization after technological parameter collection such as Fig. 5 institute
Show, abscissa represents dimension in figure, and ordinate represents target function value, the technological parameter obtained after initialization are as follows: temperature is 270
Between~290 degrees Celsius, reaction time is between 30~70 minutes, and wet end furnish is between 1.1~1.5, reaction pressure
Between 3400~3500mmHg, finally obtained technological parameter are as follows: temperature is between 280~300 degrees Celsius, when reaction stops
Between between 30~55 minutes, wet end furnish is between 1.3~1.5, and reaction pressure is between 3450~3500mmHg.
Comparative example 1
A kind of technological parameter higher-dimension Multipurpose Optimal Method of polyester fiber polymerization esterification process, by with patent
The improved RVEA algorithm of the ARVEA algorithm alternate embodiment 1 of CN108197738A obtains, finally obtained Pareto disaggregation and
Technological parameter collection after optimization is as shown in fig. 6, abscissa represents dimension in figure, and ordinate represents target function value, after initialization
Obtained technological parameter are as follows: temperature is between 270~290 degrees Celsius, and reaction time between 30~70 minutes, match by slurry
Than between 1.1~1.5, reaction pressure is between 3400~3500mmHg, finally obtained technological parameter are as follows: temperature is 275
Between~300 degrees Celsius, reaction time is between 30~60 minutes, and wet end furnish is between 1.3~1.5, reaction pressure
Between 3450~3500mmHg.
Fig. 5 and Fig. 6 are compared as can be seen that target function value is concentrated mainly in Fig. 5 for average molecular weight
0.7, and Fig. 6 is unevenly distributed, and is concentrated mainly on 0.7-0.8；For average degree of polymerization, comparative example 1 and the main collection of embodiment 1
In between 0.85-0.93, and the solution that Fig. 5 is obtained tends to 0.85；For esterification yield, Fig. 5 is concentrated mainly on 0.05-0.3
Between, and it is 0.08-0.4 that Fig. 6, which solves distributed area, and the number solved is less；For diethylene glycol content percentage, Fig. 5 target
Functional value is concentrated mainly on 0.21-0.7, and Fig. 6 is concentrated mainly on 0.21-0.6, and the number solved is less, using the method for the present invention,
Esterification yield value increases more (target function value is smaller, and it is higher to represent esterification yield), by-product diethylene glycol (DEG) mol percent content
It reduces, and the range shorter of technological parameter, therefore, for the solution obtained using inventive algorithm closer to ideal point, i.e. convergence is good,
The number of solution is more, i.e., diversity is good, and carrying out higher-dimension optimization to multiple technological parameters of polyester fiber polymerization esterification process has
Certain practical significance.
Claims (7)
1. the technological parameter higher-dimension Multipurpose Optimal Method of polyester fiber polymerization esterification process, it is characterized in that: being joined with one group of technique
Numerical value and its corresponding technic index value select secondary multiple using improved RVEA algorithm as individual in multiple individuals
Body, then set after selecting an optimum individual in secondary multiple individuals by the process parameter value of optimum individual based on user preference
Set the technological parameter of polyester fiber polymerization esterification process；
Process parameter value be technological parameter value, technological parameter be reaction temperature T, reaction pressure P, reaction time τ and
The wet end furnish r of EG/PTA, unit is respectively as follows: DEG C, mmHg, min and 1；
Technic index value is the value of technic index, and technic index is esterification yield Es, average degree of polymerization Pn, average molecular weight MnWith
Diethylene glycol (DEG) mol percent content Wt, unit is respectively as follows: %, 1,1 and %；
Multiple individuals be by generate multiple groups process parameter value after, be entered into objective function by group, it is defeated by objective function
The corresponding technic index value of each group obtains out, and the expression formula of objective function is as follows:
Improved RVEA algorithm thes improvement is that angle punishes that distance, improved angle punishment distance are denoted as dt,i,j, expression formula
It is as follows:
In formula, M is target number, and t is evolutionary generation, tmaxFor maximum evolutionary generation, α dt,i,jRate of change, i indicate i-th
Object vector after individual conversion, j indicate j-th of reference vector, θt,i,jIndicate mesh after i-th of individual conversion in former generation
The angle of vector and reference vector j is marked,What is indicated is as the minimum angle in former generation between all reference vectors, ft,iIt is
The target function value that t generation obtains,The minimum value in all target function values obtained for t generation, | | f 't,i| | after conversion
Objective function and origin between Euclidean distance；
Optimum individual be by according to user preference from Es、Pn、MnAnd WtIt is middle to choose one as with reference to after technic index, from secondary more
It is selected in individual and is worth what maximum individual obtained with reference to technic index.
2. the technological parameter higher-dimension Multipurpose Optimal Method of polyester fiber polymerization esterification process according to claim 1,
It is characterized in that, the foundation of the objective function is based on the mechanism model of polyester fiber polymerization esterification process.
3. the technological parameter higher-dimension Multipurpose Optimal Method of polyester fiber polymerization esterification process according to claim 2,
It is characterized in that, the mechanism model of the polyester fiber polymerization esterification process is put down by reaction rate equation, vapor liquid equilibrium equation, material
Weighing apparatus equation and mass-conservation equation simultaneous obtain.
4. the technological parameter higher-dimension Multipurpose Optimal Method of polyester fiber polymerization esterification process according to claim 3,
It is characterized in that, the objective function is by the way that the numerical value of T, P, τ and r are input to polyester fiber polymerization esterification process mechanism model
In, E is exported by models、Pn、MnAnd WtNumerical value after converted.
5. the technological parameter higher-dimension Multipurpose Optimal Method of polyester fiber polymerization esterification process according to claim 1,
It is characterized in that, the specific of optimum individual determines that steps are as follows:
(1) according to the constraint condition of technological parameter, process parameter value is initialized using Latin Hypercube Sampling method, it is raw
Equally distributed M group reference vector is generated at N group technological parameter, while using simplex lattice method, enables the number of iterations Pt=1；
(2) N group process parameter value is inputted into objective function, N group technic index value is exported by it, with each group process parameter value and its
Corresponding target function value is as individual；
(3) binary intersection is carried out to all individuals and multinomial makes a variation；
(4) merging the individual after make a variation prechiasmal individual and variation intersection becomes the kind containing 2N individual
Group, with season Pt=Pt+1；
(5) individual in population is selected using improved RVEA algorithm, the individual selected forms new population；
(6) floor operation is carried out to the product for setting maximum algebra and fr, if obtained number is G, judges PtDivided by G remainder whether
It is zero, if it is, updating reference vector, more new formula are as follows:In formula, V is updated reference
Vector, V0For initial reference vector,For maximum value in current solution,For minimum value in current solution, (7) are entered step；Instead
It, then enable N be equal to the number for the individual that step (5) are selected, return step (3)；
(7) judge PtWhether it is less than and sets maximum algebra, if it is, N is enabled to be equal to the number for the individual that step (5) are selected, returns
It returns step (3)；Conversely, then stopping iteration, into next step；
(8) optimum individual is selected based on user preference.
6. the technological parameter higher-dimension Multipurpose Optimal Method of polyester fiber polymerization esterification process according to claim 5,
It is characterized in that, the constraint condition of the technological parameter is as follows:
T∈(240,290)
P∈(3400,3500)
τ∈(30,70)
r∈(1.1,1.5)。
7. the technological parameter higher-dimension Multipurpose Optimal Method of polyester fiber polymerization esterification process according to claim 5,
It is characterized in that, the value range that the value range of N is 130~150, M is 90~100, sets maximum algebra as 100 generations, fr is
0.1。
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