CN110276141A - A kind of optimization method in solenoid coil magnetic field - Google Patents
A kind of optimization method in solenoid coil magnetic field Download PDFInfo
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- CN110276141A CN110276141A CN201910559030.9A CN201910559030A CN110276141A CN 110276141 A CN110276141 A CN 110276141A CN 201910559030 A CN201910559030 A CN 201910559030A CN 110276141 A CN110276141 A CN 110276141A
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Abstract
The invention discloses a kind of optimization methods in solenoid coil magnetic field, belong to the optimisation technique field in solenoid coil magnetic field, a kind of optimization method in solenoid coil magnetic field, the following steps are included: S1: optimization algorithm, using genetic algorithm as optimization algorithm, it is calculated using the gatool in the tool box Matlab, it is optimized according to operation process of the genetic algorithm in Matlab, S2: mathematical model optimizing parameter is utilized, in the case where considering solenoidal thickness and height, reach optimization aim, S3: optimization calculated result, according to optimum results, central magnetic field is calculated away from the magnetic induction intensity at central point 50mm, it is translated into the number of plies of solenoid coil and the number of turns of length direction.Optimization method of the invention is optimized solenoid structure parameter using genetic algorithm, improves excitation field intensity of the solenoid inside barrel, increases internal magnetic induction intensity.
Description
Technical field
The present invention relates to the optimisation technique fields in solenoid coil magnetic field, more specifically to a kind of solenoid coil
The optimization method in magnetic field.
Background technique
Genetic algorithm is a kind of stochastic search methods based on natural selection principle and natural genetic mechanism.It can be simulated
The life concern mechanism of " survival of the fittest is selected the superior and eliminated the inferior " in nature, to realize that there is specific objective in manual system
Optimization.Each feasible solution is equal to biological subject by genetic algorithm, and system is at random by initial kind of individual composition before optimizing
Then group artificially determines fitness function, system is then ranked up individual according to fitness height, and will wherein high fitness
Individual carry out genetic manipulation (selection, intersect and variation), the individual of low fitness is carried out superseded.The process is repeated,
Until the best individual of final fitness is screened out, as globally optimal solution.Genetic algorithm has mature, convergence speed
Degree is fast, is not easy to the advantages that falling into locally optimal solution.
It is that magnetic field strength is 0.5T as a reference value using at axis when constructing electromagnetic induction characteristic optimizing and designing a model,
Magnetic field strength and uniform section length are smaller at its axis, and volume is larger, influence excitation field of the solenoid inside barrel
Intensity, to influence its internal magnetic induction intensity.
For this purpose, proposing a kind of optimization method in solenoid coil magnetic field.
Summary of the invention
1. technical problems to be solved
Aiming at the problems existing in the prior art, the purpose of the present invention is to provide a kind of optimizations in solenoid coil magnetic field
Method, it is using solenoid coil parameter and barrel parameter as design variable, to electromagnetic induction characteristic in coaxial solenoid coil metal cylinder
It optimizes, solenoid structure parameter is optimized using genetic algorithm, further increase solenoid swashing inside barrel
Excitation field intensity increases internal magnetic induction intensity.
2. technical solution
To solve the above problems, the present invention adopts the following technical scheme that.
A kind of optimization method in solenoid coil magnetic field, comprising the following steps:
S1: optimization algorithm is counted using genetic algorithm as optimization algorithm using gatool in the tool box Matlab
It calculates, is optimized according to operation process of the genetic algorithm in Matlab, be divided into five steps；
S2: utilizing mathematical model optimizing parameter, optimizes its related spiral shell in the case where considering solenoidal thickness to height
Spool coil parameter, reaches optimization aim, using matlab GAs Toolbox, writes the M file of objective function；
S3: optimization calculated result determines internal coil diameter, coil thickness and current density, obtains center according to optimum results
Magnetic field converts above-mentioned optimal value to the number of plies and length direction of solenoid coil away from the magnetic induction intensity at central point 50mm
The number of turns.
Further, five steps are respectively to generate initial population to carry out assignment to operating parameter, calculate initial kind in the S1
Group fitness value and objective function, according to fitness value choose for breeding individual, according to certain probability and method into
Row intersects and variation generates new population and calculates fitness and objective function with to the new population of generation, and judges whether to meet excellent
Change standard.
Further, the operating parameter includes population scale, variable number, crossover probability, mutation probability and termination
The number of iterations of evolution.
Further, solenoid coil parameter includes coil inside radius, coil thickness, running current in the S2.
Further, solenoid coil volume that optimization aim is center magnetic induction intensity in the S2 when being 0.5T is minimum,
And the uniformity is no more than 5% within the scope of Φ 30mm × 100mm.
Further, using in the S2 the step of matlab GAs Toolbox is the M text for first writing objective function
Then part sets the correlation values of population scale, the number of iterations, crossover probability, mutation probability and convergence threshold values.
Further, the objective function of nonlinear Debye potential condition is carried out individually writing one
M file.
Further, optimize in the S3 calculated current density it is larger when, superconductor can be used and make production conducting wire.
3. beneficial effect
Compared with the prior art, the present invention has the advantages that
This programme is using solenoid coil parameter and barrel parameter as design variable, to electromagnetism sense in coaxial solenoid coil metal cylinder
Characteristic is answered to optimize, wherein solenoid coil parameter includes coil inside radius, coil thickness, running current, in building electromagnetism
When response characteristic mathematical optimization models, magnetic field strength is 0.5T as a reference value using at axis, is mentioned by optimization design variable
Magnetic field strength and uniform section length at high axis, while keeping volume minimum, solenoid structure parameter is carried out using genetic algorithm
Optimization, further increases excitation field intensity of the solenoid inside barrel, increases internal magnetic induction intensity.
Detailed description of the invention
Fig. 1 is overall flow schematic diagram of the invention；
Fig. 2 is genetic algorithm iterative process of the invention；
Fig. 3 is solenoid coil structural parameters schematic diagram of the invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description；Obviously, described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments, is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
Embodiment 1:
Please refer to Fig. 1-3, a kind of optimization method in solenoid coil magnetic field, comprising the following steps:
S1: optimization algorithm is counted using genetic algorithm as optimization algorithm using gatool in the tool box Matlab
It calculates, is divided into five steps, searching process is as shown in Figure 2:
The first step generates initial population P (t) and carries out assignment, including population scale, variable number, intersection to operating parameter
Probability, mutation probability and the number of iterations for terminating evolution；
Second step calculates the fitness value and objective function of initial population P (t)；
Third step chooses the individual for breeding according to fitness value, and the selected probability of the big individual of fitness value is high,
The small individual of fitness value may then be eliminated；
4th step, is intersected and is made a variation according to certain probability and method and generate new population P (t+1)；
5th step calculates fitness and objective function to the new population P (t+1) of generation, and judges whether to meet optimization mark
Standard, if the conditions are met, then algorithm terminates, and otherwise enables P (t)=P (t+1), is then transferred to third step and continues optimizing；
S2: utilizing mathematical model optimizing parameter, produces inside solenoid since winding the number of turns and the number of plies of coil directly affect
Magnetisation field, therefore solenoidal thickness and height are considered in optimization process, as shown in figure 3, solenoid radius is a, with a thickness of
B, long L are 200mm, if the average current density of coil is J, sectional area of wire is that S takes 6mm2, then table of the solenoid on Z axis
Up to formula are as follows:
In formulaSolenoidal dimensional units are mm, and the unit of J is A/m2.Conducting wire
Critical current are as follows:
Ic=-129.4 × Bm+1239.6
BmFor the maximum value of B, BmThe unit for taking 1, B is T, IcUnit is A, the running current I on conducting wireo=J × S, to magnetic
Field parameters carry out entity coding, with internal coil diameter a, coil thickness b, running current I0And turn number N is design variable, optimization
Target is minimum to obtain solenoid coil volume when center magnetic induction intensity is 0.5T, and within the scope of Φ 30mm × 100mm
Evenness is no more than 5%, if L1=100mm, B1Indicate L1Magnetic induction intensity value in range, by design variable a, b, IoIt is set as x1、
x2、x3, mathematical model is as follows,
Objective function:
MinV=π l [(a+b)2-a2]
Constraint condition:
Realization of the genetic algorithm on matlab writes the M of objective function using matlab GAs Toolbox first
File individually writes a M file for nonlinear Debye potential condition, and function [c ceq]=
Nonlcon (x), nonlinear inequalities expression formula be written as c (1)=| 0.5-B1|-0.05B0, c (2)=I0-0.3Ic；It is non-linear
Equations expression is written as ceq=B (0,0) -1；Population scale is set as 50, the number of iterations is set as 50 times, crossover probability and variation
Probability is respectively 0.65,0.04, and convergence threshold values is 0.01；
S3: optimization calculated result,
Design variable optimum results
According to optimum results, determine that internal coil diameter is 32mm, coil thickness 90mm, current density 9.5A/mm2, thus
Central magnetic field B (0,0)=0.507T is obtained away from magnetic induction density B (0,50)=0.533T at central point 50mm, it is known that uneven
Evenness is 5.1%, converts above-mentioned optimal value to the number of plies of solenoid coil and the number of turns of length direction, result n=66, N
=144, it is larger to optimize calculated current density, can make production conducting wire using superconductor, by optimization design variable come
Improve magnetic field strength and uniform section length at axis, while keeping volume minimum, using genetic algorithm to solenoid structure parameter into
Row optimization, further increases excitation field intensity of the solenoid inside barrel, increases internal magnetic induction intensity.
The present invention is using solenoid coil parameter and barrel parameter as design variable, to electromagnetism sense in coaxial solenoid coil metal cylinder
Characteristic is answered to optimize, wherein solenoid coil parameter includes coil inside radius, coil thickness, running current, in building electromagnetism
When response characteristic mathematical optimization models, magnetic field strength is 0.5T as a reference value using at axis, is mentioned by optimization design variable
Magnetic field strength and uniform section length at high axis, while keeping volume minimum, solenoid structure parameter is carried out using genetic algorithm
Optimization, further increases excitation field intensity of the solenoid inside barrel, increases internal magnetic induction intensity.
It although an embodiment of the present invention has been shown and described, for the ordinary skill in the art, can be with
A variety of variations, modification, replacement can be carried out to these embodiments without departing from the principles and spirit of the present invention by understanding
And modification, the scope of the present invention is defined by the appended.
Claims (8)
1. a kind of optimization method in solenoid coil magnetic field, which comprises the following steps:
S1: optimization algorithm is calculated using genetic algorithm as optimization algorithm using the gatool in the tool box Matlab,
It is optimized according to operation process of the genetic algorithm in Matlab, is divided into five steps；
S2: utilizing mathematical model optimizing parameter, optimizes its related solenoid in the case where considering solenoidal thickness and height
Coil parameter reaches optimization aim, using matlab GAs Toolbox, writes the M file of objective function；
S3: optimization calculated result determines internal coil diameter, coil thickness and current density, obtains central magnetic field according to optimum results
Away from the magnetic induction intensity at central point 50mm, it converts above-mentioned optimal value to the number of plies of solenoid coil and the circle of length direction
Number.
2. a kind of optimization method in solenoid coil magnetic field according to claim 1, it is characterised in that: five steps in the S1
It respectively generates initial population and assignment, the fitness value for calculating initial population and objective function is carried out to operating parameter, according to suitable
Answer angle value to choose the individual for breeding, intersected according to certain probability and method and make a variation generate new population with to production
Raw new population calculates fitness and objective function, and judges whether to meet optimisation criteria.
3. a kind of optimization method in solenoid coil magnetic field according to claim 2, it is characterised in that: the operating parameter
Including population scale, variable number, crossover probability, mutation probability and terminate the number of iterations evolved.
4. a kind of optimization method in solenoid coil magnetic field according to claim 1, it is characterised in that: helical in the S2
Pipe coil parameter includes coil inside radius, coil thickness, running current.
5. a kind of optimization method in solenoid coil magnetic field according to claim 1, it is characterised in that: optimize in the S2
Solenoid coil volume that target is center magnetic induction intensity when being 0.5T is minimum, and the uniformity within the scope of Φ 30mm × 100mm
No more than 5%.
6. a kind of optimization method in solenoid coil magnetic field according to claim 1, it is characterised in that: used in the S2
The step of matlab GAs Toolbox is the M file for first writing objective function, then set population scale, the number of iterations,
The correlation values of crossover probability, mutation probability and convergence threshold values.
7. a kind of optimization method in solenoid coil magnetic field according to claim 6, it is characterised in that: for non-linear etc.
The objective function of formula and inequality constraints condition carries out individually writing a M file.
8. a kind of optimization method in solenoid coil magnetic field according to claim 1, it is characterised in that: optimize in the S3
When calculated current density is larger, superconductor can be used and make production conducting wire.
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