CN108804746A - A kind of Design Method of Propeller based on genetic algorithm - Google Patents
A kind of Design Method of Propeller based on genetic algorithm Download PDFInfo
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Abstract
The invention discloses a kind of Design Method of Propeller based on genetic algorithm, include the following steps：First preset initial speed of a ship or plane V0；Determine the value range of propeller initial parameter；Structural gene group population；Vacuole is carried out to genome population and checks the undesirable set of genome of rejecting recombination；Calculate the propeller efficiency of genome；Genome population is evolved and eliminated, until reaching default evolution number；It exports and chooses the highest Design of Propeller parameter of efficiency and calculate the corresponding speed of a ship or plane；It is last to judge whether to continue to optimize according to the speed of a ship or plane.The present invention uses Genetic Algorithm optimized design, and it is to obtain best propeller efficiency in the prior art to overcome, and needs to consider the limitation for influencing each other and constantly adjusting when change between each parameter, improves the design efficiency of propeller；For comparing because only obtaining one group of optimized parameter with Atlas Design mode, the finally obtained majorization of solutions parametric scheme more than one group of the present invention easily facilitates selection and determines optimal Design of Propeller scheme.
Description
Technical field
The present invention relates to Design of Propeller technical fields, more specifically, are related to a kind of propeller based on genetic algorithm
Design method.
Background technology
Genetic algorithm (Genetic Algorithm) is to simulate natural selection and the science of heredity machine of Darwinian evolutionism
The computation model of the biological evolution process of reason is a kind of method by simulating natural evolution process searches optimal solution.Heredity is calculated
Method is may be a population (population) of potential disaggregation since the problem that represents, and a population is then by passing through base
Because of individual (individual) composition of the certain amount of (gene) coding.Each individual is actually chromosome
(chromosome) entity of feature is carried.Therefore, needing to realize that the mapping from phenotype to genotype encodes at the beginning
Work.Due to copying the work of gene code very complicated, generally simplified in practical application, is such as reduced to binary system volume
Code.After primary population generates, according to the principle of the survival of the fittest and the survival of the fittest, produced more by generation (generation) evolution
Carry out better approximate solution, in every generation, (selection) is selected according to fitness (fitness) size individual in Problem Areas
Individual, and by means of the genetic operator of natural genetics (genetic operators) be combined intersection (crossover) and
It makes a variation (mutation), produces the population for representing new disaggregation.After this process will cause kind of images of a group of characters natural evolution the same
Raw to be adaptive to environment than former generation for population, the optimum individual in last reign of a dynasty population, can conduct by decoding (decoding)
Problem approximate optimal solution.
Design of Propeller is an important component of entire Ship Design.After the completion of Ship Hull Lines Preliminary design,
Pass through net horse power estimation or ship model resistance test, with obtaining the ship net horse power curve.On this basis, it is desirable that design one
A propeller best with efficiency, makes it to reach：When given main engine power, the attainable maximum speed of ship institute；Or
It is minimum main engine power necessary to keeping the required speed of a ship or plane.During Design of Propeller, when the type parameter for determining ship
Afterwards, the design of the initial parameter of airscrew diameter D, screw pitch ratio P/D, disk ratio AE/A0, number of blade Z and speed of a ship or plane V can be obtained
Range；But in order to save vessel motion expense, it is thus necessary to determine that best propeller efficiency, that is, to determine the target speed of a ship or plane
V0And target speed of a ship or plane V0Corresponding airscrew diameter D, screw pitch ratio P/D, disk ratio AE/A0, number of blade Z and the target speed of a ship or plane
V0Concrete numerical value.
It is existing using in Atlas Design method, best propeller efficiency in order to obtain, sometimes designer use collection of illustrative plates
Design method, according to airscrew diameter D, screw pitch ratio P/D, disk ratio AE/A0, number of blade Z and target speed of a ship or plane V0Initial ginseng
Several scopes of design inquires from Holland collection of illustrative plates table and obtains most similar concrete numerical value.But this Atlas Design
Mode has the following defects：On the one hand, computationally intensive, it needs to expend designer's a large amount of operating time；On the other hand, sometimes
Because condition limits, and can not be inquired from Holland collection of illustrative plates table and obtain the corresponding airscrew diameters of optimum speed V
D, screw pitch ratio P/D, disk ratio AE/A0, number of blade Z and target speed of a ship or plane V0Concrete numerical value, be unable to get best propeller
Efficiency；Also, unique solution can only be inquired from Holland collection of illustrative plates table, for not only limiting rotating speed but also limiting propeller
Diameter, and the airscrew diameter not situation in optimum diameter range, are unable to get best propeller efficiency, big with limitation.
Invention content
In view of this, the present invention provides a kind of Design Method of Propeller based on genetic algorithm, solve in the prior art
Because designing propeller when that parameter limits is more with Atlas Design mode, and propeller because parameter limitation cause cannot be in collection of illustrative plates
Optimum efficiency region value and leading to not obtains best propeller efficiency and the big defect of collection of illustrative plates value error.
A kind of Design Method of Propeller based on genetic algorithm, includes the following steps：
S1, an estimated ship speed of a ship or plane V0(speed of a ship or plane that expected design reaches)；
S2, the scope of design for inputting propeller initial parameter：According to the requirement of design, airscrew diameter D, spiral shell is determined in advance
Away from than P/D, disk ratio AE/A0, number of blade Z, genome population scale and revolution speed of propeller Np(due to host, gear-box are determining
For certain value) initial parameter scope of design；
S3, structural gene group population：To airscrew diameter D, screw pitch ratio P/D, disk ratio AE/A0And tetra- ginsengs of number of blade Z
Number random value in setting range, and value is subjected to zero dimension conversion, splice this four binary codings and forms binary system something lost
Pass code set set；
S4, vacuole are checked；Zero dimension data convert is carried out respectively to each genome encoding information of genome population, with
Speed of a ship or plane V0, airscrew diameter D, screw pitch ratio P/D, disk ratio AE/A0, number of blade Z, blade center to water surface distance hs, host thrust
PDEquivalence carries out vacuole check.It is qualified Design of Propeller parameter by the parameter that vacuole is checked, corresponding genome is to close
The genome of lattice；
S5, propeller efficiency is calculated：Each new gene group coding information difference to the new gene group for meeting vacuole requirement
Zero dimension data convert is carried out, the corresponding propeller efficiency of this genome population is calculated；It is repeatedly performed the base of quantification
Because of group, generation gene families are formed, are sorted in descending order to the propeller efficiency of this generation gene families；
The evolution of S6, gene families：Default gene crisscross inheritance rule, immigrant's heredity rule, aberration rate and mortality,
Generate next-generation gene families.A new gene group is often completed, invocation step S4 rejects the genome for being unsatisfactory for vacuole requirement.
It repeats to evolve and be checked with vacuole, the genome quantity until meeting vacuole condition reaches setting quantity, completes a gene evolution
Process obtains the genome population of a new generation.Invocation step S5 obtains the efficiency value of each genome, is arranged with efficiency value descending
Sequence；
S7, judge whether evolution number reaches preset value：Default evolution frequency n, and after execution step S6, evolution times N
=N+1 executes step S6 again if N is not more than n；If N is more than n, in next step；
S8, the optimal propeller efficiency set of design parameters of output, the speed of a ship or plane determine：Obtain speed of a ship or plane V0Corresponding one group of gene
Group, each each gene code of genome convert to obtain corresponding：Airscrew diameter D, screw pitch ratio P/D, disk ratio AE/A0, number of blade
Z and propeller efficiency value.The selected first each parameter of gene of being ordered as is calculated separately respectively by preset speed of a ship or plane V value ranges
A corresponding thrust T and resistance F (V) of speed of a ship or plane V calculate thrust T and are equal to the corresponding target speed of a ship or plane V of resistance F (V)S；
S9, parameter optimization result judge；Compare V0With VSDifference then return to step S1 if deviation is more than judgment value and carry out again
Optimization, by V0=VS, re-start optimization and calculate；Until V0With VSDifference be less than judgment value, export optimum results, optimization complete.
As the priority scheme of the present invention, step S3 is specially:S31, setting genetic coding rule, according to the spiral shell of input
Revolve the scope of design of paddle diameter D, the setting of remaining parameter system：Screw pitch ratio P/D systems setting 0<P/D<1, disk ratio AE/A0 systems
Setting 0<AE/A0<1,3≤Z of number of blade<< 7, to every group of airscrew diameter D, screw pitch ratio P/D, disk ratio AE/A0 and blade
Number Z carries out random value；S32, zero dimension conversion：Convert this four real numbers that this is obtained at random to regulation number of bits
Binary numeral, formed four binary radixs such as airscrew diameter D, screw pitch ratio P/D, disk ratio AE/A0 and number of blade Z because；
S33, initial gene generate：By the binary radix of airscrew diameter D, screw pitch ratio P/D, disk ratio AE/A0 and number of blade Z because into
Row splicing, to form an initial genome；Step S31-S33 is executed by repeatedly recycling, to be formed containing default
The genome population of number of genes group.
As the priority scheme of the present invention, step S4 is specially：S41, the base for obtaining each gene in genome population
Because of group coding information (D, P/D, an AE/A0,Z)；S42, zero dimension data convert is carried out to the coding information of each genome, obtained
The corresponding airscrew diameter D of each genome encoding information, screw pitch ratio P/D, disk ratio AE/A0And the specific number of number of blade Z
Value；S43, according to airscrew diameter D, screw pitch ratio P/D, disk ratio AE/A0And the concrete numerical value of number of blade Z, utilize thrust loading
Coefficient formula and actual thrust load coefficient formula carry out vacuole check；S44, meet the genomic data that vacuole checks requirement,
It is determined as qualified genetic entities.
As the priority scheme of the present invention, step S5 is specially：S51, according to the new gene group population in step S4, obtain
Take new gene group coding information；S52, zero dimension data convert is carried out to each new gene group coding information, obtains each new base
Because of the corresponding airscrew diameter D of group coding information, screw pitch ratio P/D, disk ratio AE/A0And the concrete numerical value of number of blade Z；
S53, according to the corresponding airscrew diameter D of each new gene group coding information, screw pitch ratio P/D, disk ratio AE/A0And blade
The concrete numerical value of number Z, calculates advance coefficient J using advance coefficient formula, thrust coefficient is calculated using thrust coefficient formula
KT, moment coefficient K is calculated using moment coefficient formulaQ；S54, according to the corresponding advance coefficient J of each new gene group, thrust
COEFFICIENT KTAnd moment coefficient KQ, calculate separately out the corresponding propeller of each new gene group using propeller efficiency formula and imitate
Rate.
As the priority scheme of the present invention, step S6 is specially：S61, default gene crisscross inheritance rule, immigrant's heredity
Rule, aberration rate and mortality；S62, judge whether to meet immigrant's rule；It is equal to immigrant's operation according to iterations N to generate
When immigrant's rules of default iterations execute step S63 if meeting immigrant's rule；If being unsatisfactory for immigrant's rule, execute
Step S64；S63, foundation mortality, eliminate the low genome of propeller efficiency successively from low to high；Superseded genome uses
Migrate gene substitution；Immigrant's gene is obtained using the highest gene of efficiency in previous generation genes and worst gene crisscross inheritance；
S64, it is arranged using the descending of propeller efficiency, it is general to obtain the high gene crisscross inheritance of select probability according to propeller efficiency height
Rate carries out crisscross inheritance to each genome of the genome population obtained in step S5；S65, foundation aberration rate, to step
The genome population obtained in S64 randomly selects genome, carries out mutation operation, " 1 " to some gene in genome at random
Become " 0 " or " 0 " to become " 1 "；S66, vacuole check is carried out to new gene group, calls S4；S67, the genome for generating a new generation
Population.
As the priority scheme of the present invention, step S7 is specially：S71, specified iterations n is preset；S72, step is executed
After rapid S6, practical iterations Ni=Ni-1+1；S73, judge practical iterations NiWhether specified iterations n is more than；If real
Border iterations NiNo more than specified iterations n, S74 is thened follow the steps；If practical iterations NiMore than specified iterations
N thens follow the steps S75；S74, step S6 is repeated；S75, step S8 is executed.
As the priority scheme of the present invention, step S8 is specially：S81, default resistance curve F (V)；S82, selecting step
Peak efficiency is worth corresponding propeller parameter in S7 results, is calculated under the different speed of a ship or plane by each speed of a ship or plane V within the scope of the preset speed of a ship or plane
Thrust magnitude T.S83, the speed of a ship or plane is calculated；The intersection point of resistance curve F (V) and thrust curve T (V), intersection point are calculated with Approximation Method
Corresponding speed VS, to select propeller parameter in corresponding determining host, the speed of a ship or plane of gear-box, hull resistance.
As the priority scheme of the present invention, step S9 is specially：S91, compare V0With VSDifference；S92, such as deviation are big
In judgment value, then returns to step S1 and carry out re-optimization, by V0=VS, re-start optimization and calculate；S93, such as deviation, which are less than, to be judged
Value, exports optimum results, and optimization is completed.
As the priority scheme of the present invention, the advance coefficient formula is specifically as shown in Equation 1：
The thrust coefficient formula is specifically as shown in Equation 2：
The moment coefficient formula is specifically as shown in Equation 3：
Wherein, J is progress coefficient, VAFor propeller advance (m/s), n is propeller revolution (r/s), and D is airscrew diameter
D (m), P/D are screw pitch ratio, AE/A0For disk ratio, Z is blade number, △ KT、△KQFor Reynolds correction factor, Cs、t、u、vTo return
Coefficient, s, t, u, v are to return index.
As the priority scheme of the present invention, the propeller efficiency formula is specifically as shown in Equation 4：
Wherein, η0For propeller efficiency, π is pi, value 3.1415926.
As the priority scheme of the present invention, the thrust load coefficient formula is specifically as shown in Equation 5：
The actual thrust load coefficient formula is specifically as shown in Equation 6：
Wherein, η0.7RFor the vaporization cavitation number of section at propeller 0.7R, τC0For thrust load coefficient, τCFor actual thrust
Load coefficient, T are airscrew thrust, ApFor projected blade area, ρ is water density, V0.7R 2For section and water at propeller 0.7R
Square of the relative velocity of stream.
It can be seen from the above technical scheme that beneficial effects of the present invention are：
1, the present invention is based on genetic algorithm, the propeller designed based on regression formula is quickly found out using pre-set programs most
Good design scheme avoids heavy calculation amount, accelerates desin speed, shortens the operating time of staff, improves work
The design efficiency of personnel.
2, the present invention calculates final determining speed of a ship or plane V0Afterwards, using V0Calculating can be optimized, a series of optimal solutions are obtained,
The leeway of selection is increased, suitable genome can be chosen according to propeller tail portion resonance and be designed as optimal propeller efficiency and join
Number, effectively avoids the resonance of propeller tail portion from influencing；Further, it is possible to not only to limit rotating speed but also limiting airscrew diameter, and spiral
Situation of the paddle diameter not in optimum diameter range provides multiple solutions, expands design scheme operation strategies.It overcomes
Lead to not obtain best propeller efficiency and with limitation because designing propeller with Atlas Design mode in the prior art
Big defect so that the present invention, which can be used in rotating speed, airscrew diameter and airscrew diameter, to be existed on the place of limitation, is increased
The big scope of application of the present invention.
3, the embodiment of the present invention prevents from causing to calculate inaccuracy because of genome precocity, specially to improve design accuracy
Immigrant's rule is introduced, according to immigrant's rule, there are most excellent genes and worst gene to carry out crisscross inheritance previous generation, formed
New body introduces this generation population, replaces this generation worst individual, the variability of next-generation individual evolution gene is improved, to improve meter
Calculate the coverage area of result.
Description of the drawings
Fig. 1 is a kind of step flow chart of the Design Method of Propeller based on genetic algorithm provided in an embodiment of the present invention.
Fig. 2 is the particular flow sheet of step S3.
Fig. 3 is the particular flow sheet of step S4.
Fig. 4 is the particular flow sheet of step S5.
Fig. 5 is the particular flow sheet of step S6.
Fig. 6 is the particular flow sheet of step S7.
Fig. 7 is the particular flow sheet of step S8, S9.
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is the attached drawing described in technology description to be briefly described, it is therefore apparent that the attached drawing in description below is only the present invention's
Some embodiments for those of ordinary skill in the art, can also basis under the premise of being not required to make the creative labor
These attached drawings obtain other attached drawings.
Specific implementation mode
Below in conjunction with attached drawing, the present invention is further illustrated.
As shown in figs. 1-7, an embodiment of the present invention provides a kind of Design Method of Propeller based on genetic algorithm, including with
Lower step：
S1, first setting inputs corresponding speed of a ship or plane V0, in this step S1, due to ship type and host model it has been determined that because
This, speed of a ship or plane V can be obtained according to the requirement of design in staff0Initial parameter.
S2, the scope of design for inputting initial parameter：According to the requirement of design, airscrew diameter D, screw pitch ratio P/ is determined in advance
D, disk ratio AE/A0, number of blade Z, genome population scale and speed of a ship or plane V initial parameter scope of design.In this step S2
In, due to ship type and host model it has been determined that therefore, airscrew diameter D, spiral shell can be obtained according to the requirement of design in staff
Away from than P/D, disk ratio AE/A0, number of blade Z and genome population scale initial parameter scope of design, and will initially join
Several scopes of design are as initial operational parameter.
S3, structural gene group population.Step S3 is specially:S31, according to binary system genetic coding rule, in range
Airscrew diameter D, screw pitch ratio P/D, disk ratio AE/A0And the value of number of blade Z carries out random value；S32, by what is obtained
Value carry out binary coding conversion, formed four binary radixs because；S33, splicing airscrew diameter D, screw pitch ratio P/D, disk ratio
AE/A0And number of blade Z binary radixs because.In this step S3, binary system genetic coding rule is as follows：
In each genome：1~8 encoded radio for airscrew diameter D, binary value is 0~11111111, corresponding
Decimal value be 0~255.9~15 are screw pitch ratio P/D encoded radios, and binary value is 0~1111111, the corresponding decimal system
Value is 0~127.16~24 are disk ratio AE/A0 encoded radios, and binary value is 0~111111, and corresponding decimal value is 0
~63.23~24 are propeller number of sheets Z encoded radios, and binary value is 0~11, and corresponding decimal value is 0~3.Propeller
Rotating speed n is not incorporated into gene, is to want select host when because calculating, and gearbox speed reduction ratio generally selects 2,2.5,3,3.5,4 systems
Row.Therefore in calculating process, n is inputted as a variable, is used as definite value to participate in optimization in the calculation and is calculated.According to speed of a ship or plane V0
Concrete numerical value and population scale select determining speed of a ship or plane V at random from code set set0It is corresponding containing default population invariable number
Genome population a, that is to say, that speed of a ship or plane V0Concrete numerical value corresponds to one group of genome population for containing default population invariable number.
S4, vacuole are checked.Step S4 is specially：S41, each genome encoding information (D, the P/ for obtaining gene families
D、AE/A0,Z)；S42, zero dimension data convert is carried out to the coding information of each genome, obtains each genome encoding information
Corresponding airscrew diameter D, screw pitch ratio P/D, disk ratio AE/A0And the concrete numerical value of number of blade Z；S43, according to propeller
Diameter D, screw pitch ratio P/D, disk ratio AE/A0And the concrete numerical value of number of blade Z, it is calculated and is pushed away using thrust load coefficient formula
Power load coefficient τc0, actual thrust load coefficient τ is calculated using actual thrust load coefficient formulac；S44, judge that thrust is negative
Lotus coefficient τc0With actual thrust load coefficient τcSize, if τc0No more than τc, then follow the steps S45；If τc0More than τc, then hold
Row step S46；S45, τ is found outc0No more than τcGenome, then the genome is adjusted, increases spiral shell in a random basis
Revolve paddle diameter D, disk ratio AE/A0And the numerical value of number of blade Z, the numerical value of screw pitch ratio P/D is reduced, recycling executes step S41-
S44, until the genome meets τc0More than τcRequirement；The new genome population of S46, output：Meet the τ of vacuole checkc0Greatly
In τC'sIt is required that genomic data, be determined as qualified genome, to form the genome population for meeting vacuole requirement；Its
In, population quantity is the preset genome population scale of software systems.The thrust load coefficient formula is specifically as shown in Equation 5：
The actual thrust load coefficient formula is specifically as shown in Equation 6：
Wherein, η0.7RFor the vaporization cavitation number of section at propeller 0.7R, τC0For thrust load coefficient, τCFor actual thrust
Load coefficient, T are airscrew thrust, ApFor projected blade area, ρ is water density, V0.7R 2For section and water at propeller 0.7R
Square of the relative velocity of stream.
In formula：P0=Pa+ γ hs, unit kgf/cm3；γ --- water weight density, fresh water
1000kgf/cm3, seawater 1025kgf/cm3；hs--- propeller submersible depth (paddle shaft centre-to-centre spacing water surface elevation)；Pa--- it is big
Atmospheric pressure, 10330kgf/m2；
Unit is m2/s2, represent the relative velocity of section and flow at 0.7R
Square；
Pv--- the pressure for vaporization of water, numerical value 1700Pa；
ρ --- water density；Wherein, fresh water 100kgfs2/m4, seawater 104.6kgfs2/m4；
T --- airscrew thrust.(power unit：Horsepower hp)；
VA--- propeller advance (m/s)
AP--- blade projected area (m2), AP≈AE(1.067-0.229P/D)
AE--- propeller expended area.The summation of developed area.
A0--- disc area.The area A of blade tip circle0=π * D2/4。
AP--- projected area.Each blade the area of vertical paddle shaft plane projection summation.
PE--- net horse power.
PD--- propeller receives horsepower.PD=P12h·ηH·ηR·ηG·ηS·C；P12hFor 12 hours lasting work(of host
Rate is known definite value；ηHFor hull efficiency, 1.01 fixed value calculations are generally taken；ηRFor hull relative rotative efficiency, 1 definite value is generally taken
It calculates；ηGFor host gear-box efficiency, 0.95 fixed value calculation is generally taken；ηSFor depletion efficiency, 0.98 fixed value calculation is generally taken；C is
Propeller Reynolds number is chosen, fixed value calculation by Reynolds table.Wherein：hs、P12h(12 hours continuous powers of host) is initial ginseng
Number.When selected propeller parameter meets vacuole requirement, then a qualified propeller, so that propeller is wanted meeting vacuole
There is maximum efficiency under conditions of asking, be one of the final goal that we design.
S5, propeller efficiency is calculated：Each new gene group coding information to the new gene group population for meeting vacuole requirement
Zero dimension data convert is carried out respectively, calculates separately out the corresponding propeller efficiency of each genome of new gene group population.
Step S5 is specially：S51, according to the new gene group population in step S4, obtain new gene group coding information：Obtain each base
Because of the airscrew diameter D of group, screw pitch ratio P/D, disk ratio AE/A0And the binary coding of number of blade Z；S52, to each new base
Because group coding information carries out zero dimension data convert, the corresponding airscrew diameter D of each new gene group coding information, spiral shell are obtained
Away from than P/D, disk ratio AE/A0And the concrete numerical value of number of blade Z；It is S53, corresponding according to each new gene group coding information
Airscrew diameter D, screw pitch ratio P/D, disk ratio AE/A0And the concrete numerical value of number of blade Z, it is calculated using advance coefficient formula
Advance coefficient J calculates thrust coefficient K using thrust coefficient formulaT, moment coefficient K is calculated using moment coefficient formulaQ；
S54, according to the corresponding advance coefficient J of each new gene group, thrust coefficient KTAnd moment coefficient KQ, utilize propeller efficiency
Formula calculates separately out each corresponding propeller efficiency of new gene group.Wherein, to each new gene group in genome population
Corresponding propeller efficiency from high to low, carries out descending arrangement to each new gene group successively according to propeller efficiency；By spiral shell
Rotation paddle efficiency illustrates the adaptation of the genome as the fitness foundation for evaluating each new gene group if propeller efficiency is high
Degree is high.The advance coefficient formula is specifically as shown in Equation 1：
The thrust coefficient formula is specifically as shown in Equation 2：
The moment coefficient formula is specifically as shown in Equation 3：
The propeller efficiency formula is specifically as shown in Equation 4：
Wherein, η0For propeller efficiency, π is pi, value 3.1415926；J is progress coefficient, VAFor propeller into
Journey (m/s) definite value, n are propeller revolution (r/s), and D is airscrew diameter D (m), and P/D is screw pitch ratio, AE/A0For disk ratio, Z is
Blade number, △ KT、△KQFor Reynolds correction factor, Cs、t、u、vFor regression coefficient, s, t, u, v are to return index.△KT、△KQ、
Cs、t、u、vAnd s, t, u, v can choose definite value as calculation basis according to regression parameter table.
S6, gene families are evolved：Default gene crossover rule, immigrant's rule, aberration rate and mortality, utilize propeller
The descending of efficiency arranges, and iteration update is optimized to each genome of genome population, to obtain the gene of a new generation
Group population.Step S6 is specially：S61, default gene crisscross inheritance rule, immigrant's heredity rule, aberration rate and mortality；
S62, judge whether to meet immigrant's rule；It is equal to the immigrant of default iterations when immigrant's operation generates according to iterations N
Rule executes step S63 if meeting immigrant's rule；If being unsatisfactory for immigrant's rule, S64 is thened follow the steps；S63, immigrant's base is generated
Because of group, worst genome is replaced：According to mortality, the low genome of propeller efficiency is eliminated successively from low to high, then by upper
The worst genome crisscross inheritance of the optimal genome of propeller efficiency and propeller efficiency of one iteration genome generates new immigrant
Genome, to replace superseded genome；S64, roulette rule, 2 individual progress crisscross inheritances of selection are used：Utilize spiral shell
The descending arrangement for revolving paddle efficiency obtains the roulette rule of the high gene crisscross inheritance probability of select probability according to propeller efficiency height
Then, crisscross inheritance is carried out to each genome of the genome population obtained in step S5；S65, foundation aberration rate, to step
The genome population obtained in S64 randomly selects genome, carries out mutation operation, " 1 " to some gene in genome at random
Become " 0 " or " 0 " and become " 1 ", to obtain new genome population；S66, vacuole are checked：The new base that step S65 is obtained
Because the genome in group population carries out vacuole check processing respectively, vacuole checks process as described in step S4, if genome is not
Meet vacuole check, then follow the steps S64-S66, until the genome in the new genome population that step S65 is obtained is whole
Meet vacuole and checks requirement, S67, output genome population of new generation.
In this step S6, which specifically uses roulette algorithm, and genome is selected to carry out crisscross inheritance,
By the way that roulette algorithm is arranged, the high gene of fitness, that is, excellent genes group will obtain high select probability, pass through two genes
The cross exchanged of group, such as preceding 8 genetic fragments of preceding 8 genetic fragments of A genomes and 1 B gene group are exchanged so that A bases
Because preceding 8 genetic fragments of group will become belonging to originally preceding 8 genetic fragments in 1 B gene group, and preceding 8 genes of 1 B gene group
Segment will become belonging to preceding 8 genetic fragments in A genomes originally, to generate two different genomes, that is, new one
The genome in generation, here it is the processes of crisscross inheritance, and carry out the genome of gene crossover operation then by gene crossover rule
Roulette algorithm determine.Immigrant's rule is precocious to prevent from evolving, and one group of immigrant's gene is introduced every certain genetic algebra
Group；Immigrant's genome is carried out crisscross inheritance by the optimal genome of previous generation genomes and worst genome and is obtained, this program
Immigrant's quantity takes superseded quantity, will migrate genome and replace the worst group of evaluation, i.e., first preset the iteration something lost that immigrant's operation occurs
Passage number (is generally set every several generations), when iterations are first to preset the iteration genetic algebra of immigrant's operation generation, then to base
Because population carries out immigrant's operation.Aberration rate and mortality can be according to actual conditions, directly default concrete numerical value.This step
The purpose of S6 be to the genome of genome population carry out it is excellent in select excellent, by preset iterations, obtain speed of a ship or plane V0Phase
The optimal genome population of corresponding propeller efficiency.
S7, judge whether iterations are best：Default iterations n, and after execution step S6, iterations N=N+1,
If N is not more than n, step S6 is executed again；If N is more than n, step S8 is executed again；Step S7 is specially：S71, it presets
Specified iterations n；After S72, execution step S6, practical iterations Ni=Ni-1+1；S73, judge practical iterations NiIt is
It is no to be more than specified iterations n；If practical iterations NiNo more than specified iterations n, S74 is thened follow the steps；If practical
Iterations NiMore than specified iterations n, S75 is thened follow the steps；S74, step S6 is repeated；S75, step S8 is executed.
S8, output propeller parameter group, determine speed of a ship or plane VS：S81, default resistance curve F (V)；Due to ship type and host
It determines, therefore, resistance curve F (V) is known curve；S82, thrust curve T (V) is calculated；N times iteration can be obtained after step S7
The genome population of evolution number, then invocation step S5 acquire each base in the genome population through n times iterative evolution number
Because organizing corresponding propeller efficiency, and the sequence according to propeller efficiency from high to low, genome is ranked up, is then selected
The highest genome of propeller efficiency is taken, and the data of the genome are subjected to zero dimension reduction treatment and obtain airscrew diameter
D, screw pitch ratio P/D, disk ratio AE/A0And the concrete numerical value of number of blade Z, the preliminary design scheme of propeller is obtained, to basis
FormulaThe different speed of a ship or plane (i.e. preset spirals are calculated by each speed of a ship or plane V within the scope of the preset speed of a ship or plane
Paddle process VA) under thrust magnitude T, to obtain thrust curve T (V)；S82, speed of a ship or plane V is calculatedS：It is calculated and is hindered with Approximation Method
The intersection point of force curve F (V) and thrust curve T (V), the corresponding speed V of intersection pointS, to select propeller parameter in corresponding determination
The speed of a ship or plane of host, gear-box, hull resistance finally executes step S9.
S9, judge V0With VSWhether meet the requirements.Detailed process is：S91, according to the speed V acquired in step S8SAnd step
Preset speed V in rapid S10, compare V0With VSDifference then return to step S1 if deviation is more than judgment value and carry out re-optimization, by V0
=VS, re-start optimization and calculate；Until V0With VSDeviation be not more than judgment value, export optimum results, optimization complete, output
The parameter arranged by efficiency value descending.
The technical solution of embodiment in order to further illustrate the present invention, illustrates below in conjunction with specific experiment：
250t freighters are steel single machine single screw double rudder, indulge packschnee sled type, tail portion sets the big hatch goods in inland river of the shallow tunnel of enclosed
Ship, main navigation is in Liuzhou --- Guangdong course line.Due to the limitation of fairway depth, the size of propeller is absorbed water and ship
The limitation of body line style, propeller maximum paddle diameter<=1.2m.Choice of main machine 6135Aca diesel engines, 12h power 143Hp, rotating speed are
1500rpm, using 135 gear-boxes, deceleration speed ratio is 1：3.
Due to being known axes power PS, propeller revolution u, into fast VA, it is desirable that it calculates and selectes optimum diameter D, therefore, preset
Airscrew diameter D values are 1.1-1.2, screw pitch ratio P/D values are 0.4-0.6, disk ratio AE/A0Value is 0.5-0.7, blade
Number Z values are 3-5, propeller revolution u values are 1500, genome population scale value is 200, and genetic iteration number n is 100,
Aberration rate is 2%, and mortality 1% and speed of a ship or plane V values are 8-13, preset initial speed of a ship or plane V0It is 8.
Then it is 1.1-1.2 according to airscrew diameter D values, screw pitch ratio P/D values are 0.4-0.6, disk ratio AE/A0It takes
Value is 0.5-0.7, number of blade Z values be 3-5 constitute population scale be 200 genome population.
Then the genome being directed in genome population carries out vacuole check, rejects the genome for being unsatisfactory for vacuole requirement,
Then increase D, AE/A0, Z according to random again, reduce the mode of the concrete numerical value of P/D, constitute new genome, so that often
Each genome of the corresponding genome population of a speed of a ship or plane V is satisfied by vacuole requirement.
Then the propeller effect of each genome for meeting vacuole requirement of genome population is found out with operational formula 1-6
Rate, and the height to each genome according to propeller efficiency carries out descending arrangement.
Then judge whether to need to migrate.Immigrant's rule is that precocious phenomenon occurs for genome population in order to prevent.In this reality
In testing, immigrant's rule is：When iterations N is 5 multiple, then the optimal genome of previous generation genomes and worst gene
Group carries out crisscross inheritance and generates immigrant's genome, and immigrant's genome quantity, which is equal to, eliminates genome quantity, and immigrant's genome is replaced
It changes propeller efficiency and evaluates worst genome.Therefore, as N=5, then according to 1% mortality, rejecting imitated according to propeller
Rate descending is arranged in rearmost 2 genomes of genome population, and then by N=4, i.e. the gene in the 4th generation are organized in population
According to propeller efficiency descending be arranged in genome population foremost 2 genomes and rearmost 2 genomes respectively into
Row gene crisscross inheritance generates immigrant's gene, and genome population is arranged according to propeller efficiency descending for replacing in the 5th generation
Rearmost 2 genomes；Then gene crisscross inheritance processing is carried out to immigrant's gene again.Whenever iterations N is not 5 times
When number, then gene crisscross inheritance processing is directly carried out to genome population.
Descending according to propeller efficiency arranges, and according to propeller efficiency height, then the high gene crisscross inheritance of select probability is advised
Then, gene crisscross inheritance processing is carried out to each genome；For example, the propeller efficiency of A genomes is 47.55%, 1 B gene group
Propeller efficiency is that the propeller efficiency of 46.88%, C genomes is for the propeller efficiency of 44.33%, D genomes
43.33%, then A genomes and 1 B gene group will very maximum probability can producer crisscross inheritance processing, by preceding 8 bases of A genomes
Because preceding 8 genetic fragments of segment and 1 B gene group are exchanged so that preceding 8 genetic fragments of A genomes will become belonging to originally in B
Preceding 8 genetic fragments of genome, and preceding 8 genetic fragments of 1 B gene group will become belonging to preceding 8 bases in A genomes originally
Because of segment, to generate two different genomes, that is, the genome of a new generation, here it is the process of crisscross inheritance, this
It is exactly the operating process of gene crisscross inheritance rule.
After carrying out gene crisscross inheritance to genome, then the aberration rate of foundation 2%, randomly selects 4 genomes and carries out bases
Because of mutation, for example, selection genome E, genome N, genome Q and genome K carry out gene mutation, to genome E, gene
Random genetic fragment in group N, genome Q and genome K becomes 0 by 1 or becomes 1 by 0, such as gene into row variation processing
Group E script gene orders are 11,111,111 1,111,111 111,111 11, and the gene order after variation is specially 11111111
1111111 111101 11；Genome N script gene orders are 11,101,111 1,111,111 111,111 11, the base after variation
Because sequence is specially 11,111,111 1,111,111 111,111 11；Genome Q script gene orders are 11,111,111 0111111
111111 11, the gene order after variation is specially 11,111,111 1,111,111 111,111 11；Genome K script gene sequences
11,111,111 1,111,111 111,111 11 are classified as, the gene order after variation is specially 11,111,111 1,011,111 111111
11；To generate 4 new genomes respectively to replacement gene group E, genome N, genome Q and genome K；Then again
Vacuole check is carried out to the genome population after variation, if genome is unsatisfactory for vacuole check, rejects and corresponding is unsatisfactory for sky
The genome checked is steeped, gene crisscross inheritance is reused and generates new genome, until the genome in genome population is whole
Meet vacuole check；By to genome population iteration with eliminate, to generate a new generation genome population, iterations
Become 6 from 5.Since iterations are not more than 100, then the vacuole that genome is constantly carried out to genome population is checked and gene
The iteration update of group, until iterations N is more than default evolutionary generation 100.
Then resistance curve F (V) is preset；Due to ship type and host it has been determined that therefore, resistance curve F (V) is known song
Line；Thrust curve T (V) is calculated again；The genome population of n times iterative evolution number can be obtained after step S7, then call step
Rapid S5 acquires each corresponding propeller efficiency of genome in the genome population through n times iterative evolution number, and according to spiral shell
The sequence of paddle efficiency from high to low is revolved, genome is ranked up, then chooses the highest genome of propeller efficiency, and should
The data of genome carry out zero dimension reduction treatment and obtain airscrew diameter D, screw pitch ratio P/D, disk ratio AE/A0And blade
The concrete numerical value of number Z, obtains the preliminary design scheme of propeller, to according to formulaIt presses
Each speed of a ship or plane V calculates the different speed of a ship or plane (i.e. preset propeller advance V within the scope of the preset speed of a ship or planeA) under thrust magnitude T, to obtain
Thrust curve T (V)；The intersection point of resistance curve F (V) and thrust curve T (V) are finally calculated with Approximation Method, intersection point corresponds to
Speed VS, to select propeller parameter in corresponding determining host, the speed of a ship or plane of gear-box, hull resistance.
Finally according to the speed V acquired in previous stepSWith preset speed V in step S10, judge speed VSWhether etc.
In speed V0；If unequal, V is enabled0=VS, above-mentioned steps are repeated, until V0=VS, optimum results are finally exported, have been optimized
At the parameter that output is arranged by efficiency value descending.
In this experiment, which is 47.6127%, optimum speed V0It is for 11.45km/h, thrust T
63.99hp, airscrew diameter D are 1.100392, and screw pitch ratio P/D values are 0.5, disk ratio AE/A0Value is 0.5857143, paddle
Number of sheets Z values are 3,.
In conclusion in the present invention, 1, the present invention is based on genetic algorithms, the initial parameter design of propeller is input to
In corresponding computer program, appliance computer carries out sequencing calculating, it is no longer necessary to manually calculate one by one and be fabricated to collection of illustrative plates
In the specific value of each corresponding parameter of propeller efficiency, avoid heavy calculation amount, accelerate desin speed, shorten work
The operating time for making personnel improves the design efficiency of staff.2, the present invention can calculate that each speed of a ship or plane V is corresponding to be pushed away
Power T and resistance F (V) selects thrust T and is equal to the corresponding target speed of a ship or plane V of resistance F (V)0, i.e. optimum speed V0, then basis
Target speed of a ship or plane V0The highest genome of the corresponding propeller efficiencies of target speed of a ship or plane V is found out, airscrew diameter D, screw pitch ratio are obtained
P/D, disk ratio AE/A0, number of blade Z and target speed of a ship or plane V0Optimal propeller efficiency design parameter value, overcome existing skill
It is unable to get best propeller parameter in art under the restrictive condition of part, and the defect for causing propeller efficiency not high, it enhances and obtains
The ability for obtaining optimal Design of Propeller parameter, improves the design efficiency of propeller.3, the target speed of a ship or plane V that the present invention is calculated
There are multigroup corresponding highest genome of propeller efficiency, optimum results have more solutions, increase the leeway of selection.As can root
Suitable genome is chosen as optimal propeller efficiency design parameter according to propeller tail portion resonance, effectively avoids propeller tail portion
Resonance influence；Further, it is possible to not only to limit rotating speed but also limiting airscrew diameter, and airscrew diameter is not in optimum diameter model
Situation when enclosing provides a variety of design schemes, expands design scheme operation strategies, overcomes under multiple restrictive conditions, existing
When in technology because with Atlas Design mode or Fertilizer Test of Regression Design mode, designs propeller and lead to not obtain best propeller effect
Rate and the defect for using limitation big so that the present invention can be used in rotating speed, airscrew diameter and airscrew diameter and there is limit
On the place of system, the scope of application of the present invention is increased.4, the embodiment of the present invention is in order to obtain optimal design as a result, preventing Yin Ji
It is not optimal solution to cause to calculate due to group precocity, and except implementing, genetic mutation operation is outer, and it is regular to be also intentionally introduced into immigrant, according to
Immigrant's rule, targetedly carries out gene emigration operation to genome population.Migrate gene combination genetic mutation operation, be
Gene families introduce Mutation Mechanism, avoid population precocity, the optimal value covering surface of result of calculation are improved, to improve
Design the performance of propeller.
The present invention implements the first value range according to Design of Propeller parameter, constructs a corresponding genome population,
For a specific speed of a ship or plane V0, vacuole check then is carried out to the genome population, obtains the gene kind for meeting vacuole condition
Group carries out gene evolution according to the law of heredity of genetic design, and the gene each evolved carries out vacuole check, meets vacuole condition
Gene formed a new generation population.Evolutionary process is repeated, until evolution number, which meets, presets evolution number, acquisition is a series of most
Excellent solution.Then the parameter of selected peak efficiency calculates the thrust curve T (V) of the parameter, with resistance as propeller calculating parameter
Force curve F (V) intersects, and obtains speed of a ship or plane VS.Compare V0With VSDifference, if deviation is more than judgment value, then return to step S1 carry out it is excellent again
Change, by V0=VS, re-start optimization and calculate；Until V0With VSDeviation be not more than judgment value, export optimum results, optimized
At.After the completion of optimization, last genome population is optimal genome population, and propeller efficiency is highest in the genome population
Genome is optimal genome, VSFor design speed.
Each embodiment is described by the way of progressive in this specification, the highlights of each of the examples are with other
The difference of embodiment, identical similar portion cross-reference between each embodiment.
The foregoing description of the disclosed embodiments enables professional and technical personnel in the field to realize the present invention.To these
A variety of modifications of embodiment will be apparent to those skilled in the art, general original as defined herein
Reason can be realized in other embodiments without departing from the spirit or scope of the present invention.Therefore, the present invention will not
Be intended to be limited to the embodiments shown herein, and be to fit to it is consistent with the principles and novel features disclosed in this article most
Wide range.
Claims (10)
1. a kind of Design Method of Propeller based on genetic algorithm, which is characterized in that include the following steps：
S1, default speed of a ship or plane V0；
S2, the scope of design for inputting propeller initial parameter：According to the requirement of design, determine airscrew diameter D, screw pitch ratio P/D,
Disk ratio AE/A0, number of blade Z, genome population scale and revolution speed of propeller NpInitial parameter design value range；
S3, structural gene group population；
S4, vacuole check is carried out to genome population；
S5, the propeller efficiency for calculating genome；
The evolution of S6, genome population：Immigrant or crisscross inheritance are carried out by genome to handle with variation, are picked out full after evolving
The genome population that sufficient vacuole is checked；
S7, judge whether evolution number reaches preset value：Default evolution frequency n, and after execution step S6, evolution times N=N+
1, if N is not more than n, step S6 is executed again；If N is more than n, S8 is thened follow the steps；
S8, the optimal propeller efficiency set of design parameters of output, determine target speed of a ship or plane VS；
S9, parameter optimization result judge；Compare V0With VSDifference, if deviation is more than judgment value, return to step S1 carry out it is excellent again
Change, enables V0=VS, step S1-S9 is executed again；Until V0With VSDeviation be not more than judgment value, export optimum results, optimized
At.
2. a kind of Design Method of Propeller based on genetic algorithm as described in claim 1, which is characterized in that the step S3
Specially:
S31, setting genetic coding rule：According to the scope of design of the airscrew diameter D of input, the setting of remaining parameter system：Spiral shell
Away from than P/D system setting 0<P/D<1, disk ratio AE/A0 systems setting 0<AE/A0<1,3≤Z of number of blade<< 7, to every group of spiral
Paddle diameter D, screw pitch ratio P/D, disk ratio AE/A0 and number of blade Z carry out random value；
S32, zero dimension conversion：Convert this four real numbers that this is obtained at random to the binary numeral of regulation number of bits,
Formed four binary radixs such as airscrew diameter D, screw pitch ratio P/D, disk ratio AE/A0 and number of blade Z because；
S33, initial gene generate：By the binary radix of airscrew diameter D, screw pitch ratio P/D, disk ratio AE/A0 and number of blade Z
Because being spliced, genome is formed.
3. a kind of Design Method of Propeller based on genetic algorithm as described in claim 1, which is characterized in that the step S4
Specially：
S41, the genome encoding information for obtaining each gene；
S42, zero dimension data convert is carried out to the coding information of each genome, it is corresponding obtains each genome encoding information
Airscrew diameter D, screw pitch ratio P/D, disk ratio AE/A0And the concrete numerical value of number of blade Z；
S43, according to airscrew diameter D, screw pitch ratio P/D, disk ratio AE/A0And the concrete numerical value of number of blade Z, it is negative using thrust
Lotus coefficient formula and actual thrust load coefficient formula carry out vacuole check；Carry out vacuole check；
S44, meet the genome population that vacuole checks requirement, be determined as qualified genome population.
4. a kind of Design Method of Propeller based on genetic algorithm as described in claim 1, which is characterized in that the step S5
Specially：
S51, according to the new gene group population in step S4, obtain new gene group coding information；
S52, zero dimension data convert is carried out to each new gene group coding information, it is opposite obtains each new gene group coding information
Airscrew diameter D, screw pitch ratio P/D, the disk ratio A answeredE/A0And the concrete numerical value of number of blade Z；
S53, according to the corresponding airscrew diameter D of each new gene group coding information, screw pitch ratio P/D, disk ratio AE/A0And
The concrete numerical value of number of blade Z, advance coefficient J is calculated using advance coefficient formula, and thrust is calculated using thrust coefficient formula
COEFFICIENT KT, moment coefficient K is calculated using moment coefficient formulaQ；
S54, according to the corresponding advance coefficient J of each new gene group, thrust coefficient KTAnd moment coefficient KQ, utilize propeller
Effectiveness formula calculates separately out each corresponding propeller efficiency of new gene group.
5. a kind of Design Method of Propeller based on genetic algorithm as described in claim 1, which is characterized in that the step S6
Specially：
S61, default gene crisscross inheritance rule, immigrant's heredity rule, aberration rate and mortality；
S62, judge whether to meet immigrant's rule；It is equal to default iterations when immigrant's operation generates according to iterations N
Immigrant's rule executes step S63 if meeting immigrant's rule；If being unsatisfactory for immigrant's rule, S64 is thened follow the steps；
S63, foundation mortality, eliminate the low genome of propeller efficiency successively from low to high；
S64, it is arranged using the descending of propeller efficiency, the high gene crisscross inheritance of select probability is obtained according to propeller efficiency height
Probability carries out crisscross inheritance to each genome of the genome population obtained in step S5；
S65, foundation aberration rate, randomly select genome, at random in genome to the genome population obtained in step S64
Some gene carries out mutation operation；
S66, vacuole check is carried out to new gene group, calls S4；
S67, the genome population for generating a new generation.
6. a kind of Design Method of Propeller based on genetic algorithm as described in claim 1, which is characterized in that the step S7
Specially：
S71, specified iterations n is preset；
After S72, execution step S6, practical iterations Ni=Ni-1+1；
S73, judge practical iterations NiWhether specified iterations n is more than；If practical iterations NiNo more than specified iteration
Frequency n thens follow the steps S74；If practical iterations NiMore than specified iterations n, S75 is thened follow the steps；
S74, step S6 is repeated；
S75, step S8 is executed.
7. a kind of Design Method of Propeller based on genetic algorithm as described in claim 1, which is characterized in that the step S8
Specially：
S81, default resistance curve F (V)；
Peak efficiency is worth corresponding propeller parameter in S82, selecting step S7 results, by each speed of a ship or plane V within the scope of the preset speed of a ship or plane
Calculate the thrust magnitude T under the different speed of a ship or plane；
S83, the speed of a ship or plane is calculated；The intersection point of resistance curve F (V) and thrust curve T (V) are calculated with Approximation Method, intersection point corresponds to
Speed VS。
8. a kind of Design Method of Propeller based on genetic algorithm as described in claim 1, which is characterized in that the step S9
Specially：
S91, compare V0With VSDifference；
If S92, V0With VSDeviation be more than judgment value, then return to step S1 and carry out re-optimization, by V0=VS, re-start optimization meter
It calculates；
If S93, V0With VSDeviation be not more than judgment value, then export optimum results, optimization is completed.
9. a kind of Design Method of Propeller based on genetic algorithm as claimed in claim 4, which is characterized in that in step S5
In, the advance coefficient formula is specifically as shown in Equation 1：
The thrust coefficient formula is specifically as shown in Equation 2：
The moment coefficient formula is specifically as shown in Equation 3：
The propeller efficiency formula is specifically as shown in Equation 4：
Wherein, η0For propeller efficiency, π is pi, and value 3.1415926, J is progress coefficient, VAFor propeller advance
(m/s), n is propeller revolution (r/s), and D is airscrew diameter D (m), and P/D is screw pitch ratio, AE/A0For disk ratio, Z is number of blade
Mesh, △ KT、△KQFor Reynolds correction factor, Cs、t、u、vFor regression coefficient, s, t, u, v are to return index.
10. a kind of Design Method of Propeller based on genetic algorithm as claimed in claim 3, which is characterized in that in step S4
In, the thrust load coefficient formula is specifically as shown in Equation 5：
τC0=0.189 σ0.7R+ 0.25-0.165 formulas 5
The actual thrust load coefficient formula is specifically as shown in Equation 6：
Wherein, η0.7RFor the vaporization cavitation number of section at propeller 0.7R, τC0For thrust load coefficient, τCFor actual thrust load
Coefficient, T are airscrew thrust, ApFor projected blade area, ρ is water density, V0.7R 2For section at propeller 0.7R and flow
Square of relative velocity.
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Application publication date: 20181113 |