CN111859626A - BOE design method and laser processing device based on BOE - Google Patents
BOE design method and laser processing device based on BOE Download PDFInfo
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Abstract
The embodiment of the invention discloses a design method of BOE and a laser processing device based on the BOE; the apparatus may include: an ultrafast laser, a laser processing head, and a BOE; wherein the ultrafast laser generates an ultrafast laser beam; the BOE is arranged on a guide path of the ultrafast laser beam and at a beam waist position of an x axis under a set Cartesian coordinate system, and is used for correcting a divergence angle of the ultrafast laser beam and a y axis under the Cartesian coordinate system, so that an elliptical light spot of the ultrafast laser beam is changed into a circular light spot to eliminate astigmatism, and the BOE is obtained by the design method of the BOE; the laser processing head is used for processing a target workpiece by using the corrected ultrafast laser beam transmitted through the guide path.
Description
Technical Field
The embodiment of the invention relates to the technical field of laser processing, in particular to a design method of a Binary Optical Element (BOE) and a BOE-based laser processing device.
Background
In the field of laser processing technology, astigmatism seriously affects the quality of laser beams output by a laser, and further deteriorates the processing effect of a laser processing device. In a conventional scheme, in order to eliminate astigmatism of a laser, a currently related technical scheme corrects divergence angles of a meridian plane and a sagittal plane by using a cylindrical mirror, so that the divergence angles are kept consistent, and astigmatism is eliminated. For the above-mentioned related art solution, astigmatism of the laser can be corrected to about 50um and a divergence angle can be corrected to 0.1 mrad. However, for the ultrafast laser, since the astigmatism is less than 0.2mm and the divergence angle is less than 0.1mrad, the related art solution cannot be applied to the ultrafast laser due to its low precision. Therefore, a solution for eliminating astigmatism for the ultra-fast laser astigmatism is needed.
Disclosure of Invention
In view of this, embodiments of the present invention are intended to provide a BOE design method and a laser processing apparatus based on the BOE; the requirements of the ultrafast laser on the precision of the optical element for astigmatism elimination can be met, and the astigmatism of the ultrafast laser beam can be effectively reduced, so that the astigmatism reaches the micron level.
The technical scheme of the embodiment of the invention is realized as follows:
in a first aspect, an embodiment of the present invention provides a method for designing a binary optical element BOE, where the method includes:
designing a target phase distribution function of the BOE by utilizing a mixed alternative iterative algorithm combining a local optimization algorithm and a group optimization algorithm based on an actual incident light field amplitude distribution function on an input plane and an ideal target output light amplitude distribution function on an output plane;
and fitting the target phase distribution function of the BOE by adopting a multi-order relief structure.
In a second aspect, an embodiment of the present invention provides a laser processing apparatus based on a binary optical element BOE, where the apparatus includes an ultrafast laser, a laser processing head, and a BOE; wherein the ultrafast laser generates an ultrafast laser beam; the BOE is disposed on a guiding path of the ultrafast laser beam and at a beam waist position of an x-axis in a set cartesian coordinate system, and is configured to correct a divergence angle between the ultrafast laser beam and a y-axis in the cartesian coordinate system, so that an elliptical spot of the ultrafast laser beam is changed into a circular spot to eliminate astigmatism, and the BOE is designed and obtained by the design method of the BOE of the first aspect; the laser processing head is used for processing a target workpiece by using the corrected ultrafast laser beam transmitted through the guide path.
The embodiment of the invention provides a design method of BOE and a laser processing device based on the BOE; designing a target phase distribution function of the BOE by utilizing a mixed alternative iterative algorithm combining a local optimization algorithm and a group optimization algorithm based on an actual incident light field amplitude distribution function on an input plane and an ideal target output light amplitude distribution function on an output plane; and fitting the target phase distribution function of the BOE by adopting a multi-order relief structure. The requirements of the ultrafast laser on the precision of the optical element for astigmatism elimination can be met, and the astigmatism of the ultrafast laser beam can be effectively reduced, so that the astigmatism reaches the micron level.
Drawings
Fig. 1 is a schematic composition diagram of a related art laser processing apparatus according to an embodiment of the present invention;
fig. 2 is a schematic diagram illustrating a laser processing apparatus according to an embodiment of the present invention;
FIG. 3 is a schematic flow chart of a target phase distribution function for designing a BOE according to an embodiment of the present invention;
FIG. 4 is a schematic flow chart of another objective phase distribution function for designing a BOE according to an embodiment of the present invention;
fig. 5 is a schematic flowchart of a GS iterative algorithm according to an embodiment of the present invention;
FIG. 6 is a schematic flow chart of a genetic algorithm provided by an embodiment of the present invention;
FIG. 7 is a schematic flow chart of a simulated annealing algorithm according to an embodiment of the present invention;
fig. 8 is a schematic diagram of phase distribution of a BOE according to an embodiment of the present invention.
Detailed Description
The technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.
Generally, a laser processing apparatus is used as a part of a laser processing apparatus (e.g., a laser processing machine) for performing laser processing on a specific workpiece. Referring to fig. 1, the composition of a laser processing apparatus 1 is exemplarily illustrated; it is to be understood that, for reasons of simplicity and clarity, fig. 1 only shows exemplary components and details relevant to the technical solution, and does not show other possible components and details of the laser machining device 1. As shown in fig. 1, the laser processing apparatus 1 may include a laser 11 and a laser processing head 12; specifically, laser 11 is capable of generating a laser beam 22; the laser beam 22 is transmitted to the laser processing head 12 based on the guiding path, and is emitted to the workpiece 33 through the laser processing head 12 to implement processing on the workpiece 33, such as cutting, welding, surface treatment, punching, micromachining and the like. In addition, for reasons of simplicity and clarity, the guiding path of the laser beam 22 shown in fig. 1 is a straight path, so that the laser beam 22 propagates linearly, and it can be understood that, in the embodiment of the present invention, it is not excluded that a plurality of lenses for refraction or reflection are disposed on the guiding path, so as to enable the laser beam 22 to propagate non-linearly, for example, a broken line, and details of the embodiment of the present invention are not repeated.
For conventional laser processing devices, the laser 1 shown in fig. 1 may typically employ a carbon dioxide CO2 gas laser or a solid state laser to generate the laser beam 22. However, with the development of the technology, the ultra-fast laser has the characteristics of ultra-short duration, ultra-strong peak power and the like, so that the existence and influence of the thermal diffusion phenomenon can be avoided, the cold processing of the element is realized, and the ultra-fast laser is more and more widely applied to the field of industrial processing. In view of this, the laser 11 may also be preferably an ultrafast laser in some examples.
For any of the above-described exemplary lasers (including ultrafast lasers), the laser beam propagates in two perpendicular planes (meridian plane and sagittal plane) with different focal points resulting in the focal spot being dispersed, so that the laser beam 22 output by the conventional laser 1 forms an elliptical spot rather than a circular spot on the arrival plane wavefront, which is generally referred to as astigmatism. The occurrence of the astigmatism phenomenon seriously affects the quality of the laser beam 22 output by the laser 1, and further deteriorates the processing effect of the laser processing device 1; therefore, an astigmatism eliminating device is generally disposed on the guiding path of the laser beam 22 in the laser processing apparatus 1, so as to eliminate astigmatism and ensure that the laser beam 22 forms a circular spot on the arrival plane wavefront.
In some conventional examples, cylindrical mirrors are used to correct the divergence angles of the meridian plane and the sagittal plane to be the same, so as to change the elliptical spot to a circular spot to achieve the effect of eliminating astigmatism. But for the ultrafast laser, the astigmatism is less than 0.2mm, and the divergence angle is less than 0.1 mrad; in the conventional correction process by adopting the cylindrical mirror, the requirements on the precision of the curvature and the surface shape of the cylindrical mirror are high, astigmatism can be corrected to about 50um only by the conventional cylindrical mirror, and the divergence angle is corrected to 0.1 mrad; therefore, the conventional cylindrical mirror is difficult to eliminate astigmatism with high precision, and thus cannot be applied to an ultrafast laser. In order to improve the precision of astigmatism elimination so as to be suitable for the ultrafast laser, other modes are required; for example, the binary optical element BOE may be disposed in the laser processing apparatus 1, even on the guiding path of the laser beam in the laser processing apparatus 1, to eliminate the astigmatism of the ultrafast laser. The binary optical element is a phase-only diffraction element, and compensates for the optical path difference to correct the wave surface, thereby achieving the effect of eliminating astigmatism.
Based on the above description and the laser processing apparatus 1 shown in fig. 1, referring to fig. 2, a composition of a laser processing apparatus 20 capable of implementing the technical solution of the embodiment of the present invention is shown, and may include: an ultrafast laser 201, a laser processing head 202, and a BOE 203; wherein, the ultrafast laser 201 generates an ultrafast laser beam; the BOE 203 is arranged on a guide path of the ultrafast laser beam and at a beam waist position of an x axis under a set Cartesian coordinate system, and is used for correcting a divergence angle of the ultrafast laser beam and a y axis under the Cartesian coordinate system, so that an elliptical light spot is changed into a circular light spot to eliminate astigmatism, and the quality of the ultrafast laser beam is improved; the laser processing head is used for processing a target workpiece by using the corrected ultrafast laser beam transmitted through the guide path.
For the laser machining apparatus 20 shown in fig. 2, in some examples, the BOE 203 is a multi-phase order relief structure, i.e., a phase distribution function of the BOE 203 is fitted by a multi-step relief structure. This makes it possible to visually ascertain: the greater the number of steps in a period, the closer to the desired phase profile and thus the higher the diffraction efficiency. Specifically, the relationship between diffraction efficiency and the number of steps within a period is:
in the above formula, N is the quantization order. When N is 2, 4, 8 and 16, respectively, the diffraction efficiencies η are 41%, 81%, 95% and 99%, respectively. Based on the relationship between the diffraction efficiency and the number of steps within the period, in the present example, the BOE 203 is preferably an 8-step BOE.
In addition, the relationship between the sawtooth depth d of the BOE 203 and the operating wavelength λ and the refractive index n is: d ═ λ/(n-1). Whereas for the ultrafast laser 201, the operating wavelength λ is typically 1030nm, and the ultrafast laser processing industry uses optical glass, typically fused silica, with a refractive index n of typically 1.458, from which it can be seen that in this example, the BOE 203 preferably has a depth d of 2.28um of serrations.
Based on the preferred number of steps and the depth of the saw teeth for the BOE 203, it can be known that, in the embodiment of the present invention, the thickness of each step of the BOE 203 is 2.28 um/8. In a specific practical implementation scenario, the process machining precision of the BOE 203 is less than 0.2um, the line width in the y direction of the set cartesian coordinate system can reach 0.7um, the precision requirement of the ultrafast laser 201 on the optical element for astigmatism elimination is met, and then the astigmatism of the ultrafast laser beam can be effectively reduced, so that the astigmatism reaches the micrometer level.
The above examples and preferred embodiments specifically describe the structure of the multi-step relief of the BOE 203, but for the BOE 203, before designing the relief structure with multiple phase orders, the phase distribution function of the BOE 203 needs to be designed to be able to fit with the above-described multi-step relief structure. For the laser processing apparatus 20 shown in fig. 2, in some examples, the target phase distribution function of the BOE 203 may be designed using a hybrid alternating iterative algorithm combining a local optimization algorithm and a group optimization algorithm based on the actual light field amplitude distribution F (x, y) on the input plane and the ideal light field amplitude distribution I (u, v) on the output plane. In the embodiment of the present invention, the actual optical field amplitude distribution F (x, y) on the input plane may also be referred to as the incident optical field amplitude distribution function of the BOE 203; the ideal optical field amplitude distribution I (u, v) on the output plane may also be referred to as the target output light amplitude distribution function of BOE 203; and will not be described in detail later. For this example, in some possible implementations, the local optimization algorithm is preferably a Gaster Begge-Saxton (GS) iterative algorithm or a modified GS iterative algorithm; and the population optimization algorithm is preferably a genetic algorithm or a simulated annealing algorithm.
For the above example, the target phase distribution function of the BOE203 is designed based on the actual light field amplitude distribution F (x, y) in the input plane and the ideal light field amplitude distribution I (u, v) in the output plane by using a hybrid alternating iterative algorithm of a local optimization algorithm and a group optimization algorithm, and the design method may include the following steps as shown in fig. 3:
s301: during each hybrid alternating iteration, based on an incident light field amplitude distribution function of the BOE203, a target output light amplitude distribution function of the BOE203 and an initial phase distribution function, acquiring an intermediate result of the phase distribution function by using a set local optimization strategy;
s302: during each hybrid alternating iteration, acquiring a final phase distribution function result by using a set group optimization strategy according to the intermediate result of the phase distribution function and the amplitude distribution of the incident light field of the BOE 203;
and, S303: and when the set mixed alternative iteration stop judgment condition is met, determining the final result of the phase distribution function obtained by the final mixed alternative iteration as the target phase distribution function of the BOE 203.
For the design method, the target phase distribution function of the BOE203 is obtained by adopting a hybrid iteration strategy of combining a local optimization algorithm and a group optimization algorithm, so that the method has the advantages of flexibility and less initial condition limitation, effectively avoids the defect that the design method falls into a local extreme point, and has global optimal searching performance.
Fig. 4 illustrates an exemplary implementation method of the design method illustrated in fig. 3, which may include:
s401: setting an initial phase distribution function of the input surface of the BOE203 corresponding to the ith mixed alternating iteration;
in some examples, the initial phase distribution function may specifically be a final estimate of the phase distribution function obtained in the previous i-1 st hybrid alternating iteration. For the first mixing alternation iteration, the initial value may be a specific starting value, which may be arbitrarily selected or may be determined based on other available information. In this example, the initial phase distribution function corresponding to the first hybrid alternating iteration may preferably be
Where sign () denotes a sign function, f denotes a focal length, K denotes a light wave number and K is 2 pi/λ, α denotes an angle formed by the optical axis and the light beam focusing direction, and x and y denote coordinate values of sampling points of the initial phase distribution function on the x (lateral) axis and the y (longitudinal) axis of the light field, respectively.
S402: acquiring an intermediate result of the phase distribution function corresponding to the ith hybrid alternating iteration by using a set local optimization strategy according to the initial phase distribution function, the incident light field amplitude distribution function of the BOE203 and the target output light amplitude distribution function of the BOE 203;
For example, the local optimization strategy may preferably be a GS iterative algorithm or a modified GS iterative algorithm, which is also an iterative algorithm. In this example, the iteration number of the GS iterative algorithm or the improved GS iterative algorithm may be a set value n, that is, in the process of performing calculation using the GS iterative algorithm or the improved GS iterative algorithm, when the iteration number reaches the specified maximum iteration number n, the GS iterative algorithm or the improved GS iterative algorithm is stopped; or setting a preset error control threshold, and stopping the GS iterative algorithm or the improved GS iterative algorithm when the error control quantity is smaller than the error control threshold in the calculation process by using the GS iterative algorithm or the improved GS iterative algorithm. It can be understood that the result obtained when the GS iterative algorithm or the improved GS iterative algorithm is stopped is the intermediate result of the phase distribution function corresponding to the ith hybrid alternating iteration.
S403: obtaining a final phase distribution function result corresponding to the ith hybrid alternating iteration by using a set group optimization strategy according to the intermediate result of the phase distribution function corresponding to the ith hybrid alternating iteration and the amplitude distribution of the incident light field of the BOE 203;
For example, the cluster optimization strategy may preferably be a genetic algorithm or a simulated annealing algorithm, which is itself an iterative algorithm. In this example, the iteration number of the genetic algorithm or the simulated annealing algorithm may be a set value k, that is, in the calculation process using the genetic algorithm or the simulated annealing algorithm, when the iteration number reaches the specified maximum iteration number k, the genetic algorithm or the simulated annealing algorithm is stopped, and at this time, the obtained result is the final result of the phase distribution function corresponding to the ith hybrid alternating iteration.
S404: determining whether to continue the (i + 1) th mixed alternative iteration based on a set mixed alternative iteration stop criterion;
for example, the present implementation method may stop the mixing alternation iteration when the error control amount is smaller than the preset error threshold. That is, if the criterion of stopping the hybrid alternating iteration is satisfied, it is stated that the final result of the phase distribution function corresponding to the ith hybrid alternating iteration is very close to the target phase distribution function, and it can be considered that the target phase distribution function has been obtained, and at this time, S405 may be executed: and determining the final result of the phase distribution function corresponding to the ith mixed alternating iteration as a target phase distribution function. If the criterion for stopping the hybrid alternating iteration is not satisfied, that is, the final result of the phase distribution function corresponding to the ith hybrid alternating iteration is not close to the target phase distribution function, it may be considered that the subsequent (i + 1) th hybrid alternating iteration process is performed, and at this time, S406 may be executed: and generating an initial phase distribution function of the input surface of the BOE 203 corresponding to the (i + 1) th mixed alternating iteration based on the final phase distribution function result corresponding to the ith mixed alternating iteration, and returning to S402 to repeatedly execute S402 to S404.
Specifically, the error control amount E is preferably the final result a according to the phase distribution functionk(x, y) is related to the target phase distribution function A (x, y)
Calculating to obtain e as a set threshold; when E is<And e, the mixed alternative iteration stop criterion is met, otherwise, the mixed alternative iteration stop criterion is not met. In addition, in S406, the initial phase distribution function of the BOE203 input surface corresponding to the i +1 th hybrid-alternate iteration is generated based on the final phase distribution function result corresponding to the i-th hybrid-alternate iteration, and the BOE203 input corresponding to the i +1 th hybrid-alternate iteration may be preferably obtained according to the following formulaInitial phase distribution function of the face:
where k denotes the number of iterations of the set group optimization strategy and m denotes the number of times such phase replacement is performed.
In some examples, when the set local optimization strategy is preferably a GS iterative algorithm, referring to fig. 5, which shows a process of obtaining an intermediate result of a phase distribution function corresponding to an ith hybrid alternating iteration by using the GS iterative algorithm during the ith hybrid alternating iteration, with reference to fig. 3 and fig. 4, it can be understood that the process may be implemented as a specific implementation of step S302 in fig. 3 or step S402 in fig. 4, and the process may include:
S501: combining the initial phase distribution function with an incident light field amplitude distribution function of the BOE203 to obtain an incident light field complex amplitude distribution function during a kth GS iteration;
s502: performing Fourier transform on the incident light field complex amplitude distribution function during a kth GS iteration, and acquiring a phase function of the incident light field complex amplitude distribution function based on the Fourier transform;
s503: combining the phase function of the incident light field complex amplitude distribution function with the target output light amplitude distribution function of the BOE203 to obtain a complex amplitude function to be determined during the kth GS iteration;
s504: during the kth GS iteration, performing inverse Fourier transform on the complex amplitude function to be judged, and acquiring a phase function to be judged based on the inverse Fourier transform;
s505: judging whether to stop the GS iteration algorithm based on the phase function to be judged and a set GS iteration stop criterion: if the GS iterative algorithm is determined to be stopped, S506 is executed: determining the phase function to be judged acquired during the kth GS iteration as an intermediate result of the phase distribution function corresponding to the ith hybrid alternating iteration; otherwise, executing S507: taking the phase function to be determined obtained during the kth GS iteration as an initial phase distribution function used by the (k + 1) th GS iteration; and returns to S501 to perform the (k + 1) th GS iteration.
In the present example, preferably, when i-1 and k-1, the initial phase distribution function is
When i is>When 1 and k is 1, the initial phase distribution function is the final result of the phase distribution function corresponding to the i-1 st hybrid alternating iteration; when i is>1 and k>1, the initial phase distribution function is the phase function to be determined acquired during the k-1 th GS iteration.
In this example, the set GS iteration stop criterion may be specifically the set GS iteration number n, or an error control amount obtained by performing error analysis by using the phase function to be determined may be smaller than the set error control threshold e. For example, the actual output light amplitude distribution function I corresponding to the kth GS iteration is obtained according to the phase function to be determinedk(x, y), and then the actual output light amplitude distribution function Ik(x, y) and the target output light amplitude distribution function I (x, y) obtain an error control quantity E corresponding to the kth iteration GS according to the following formula:
finally, comparing the error control quantity E corresponding to the kth GS iteration with a set error control threshold value E; if E < E, meeting GS iteration stop criterion; otherwise, the GS iteration stop criterion is not satisfied.
In some examples, when the set group optimization strategy is preferably a genetic algorithm, referring to fig. 6, which shows a process of obtaining a final result of a phase distribution function corresponding to an ith hybrid-alternating iteration by using a genetic algorithm during the ith hybrid-alternating iteration, with reference to fig. 3 and fig. 4, it can be understood that the process may be implemented as a specific implementation of step S303 in fig. 3 or step S403 in fig. 4, and the process may include:
S601: a setting stage: setting the number of sampling points of an input light field and an output light field to be M multiplied by N, wherein a sampling matrix of a phase distribution function of the BOE is an M multiplied by N matrix;
s602: in the initial breeding stage: n phase distributions randomly selected according to the intermediate result of the phase distribution function corresponding to the ith hybrid alternating iteration
Forming an initialization group X (0), wherein each individual in the initialization group is an M multiplied by N matrix;
that is, n phases to be randomly selected are distributed
Composing an initialization population
S603: a replication stage: evaluation of fitness value Q (X) for each individuali) And adopting roulette selection and adopting a guarantee strategy to directly enter the individuals with the optimal fitness currently into the next generation.
In S603, the fitness of the individual is set to Q (X)i) 1/cost, wherein t represents a certain individual in the current population, t is more than or equal to 0 and less than or equal to 2 pi, and the individuals with higher fitness have higher replication probability;
s604: and (3) a cross stage: converting each individual into a 1 x MN column vector from a matrix, adopting a double-point crossing strategy to select two individuals optionally, and generating two random numbers between 1 and MN, wherein the two random numbers represent a starting point and an end point of the exchange of chromosomes of the two individuals;
It should be noted that each individual is converted from a matrix to a column vector to facilitate the crossover and mutation operations. Thus, each individual is converted into a 1 × MN column vector.
S605: and (3) a mutation stage: a random number is generated between 1 and MN as a mutation position.
For example, if the phase is quantized by 8 steps, which means that there are 8 values of the phase, a number between 0 and 7 is randomly generated to represent the phase value. If 5 is randomly generated, the phase variation of the chromosome can be expressed as:
s606: an iteration stage: and carrying out Fourier transform iterative operation on each individual in the population.
S607: and (3) evaluation stage: obtaining an optimal phase based on the Fourier transform iterative operation, and evaluating whether the whole genetic iteration meets an end criterion according to the optimal phase: if so, the genetic algorithm ends, otherwise, the replication stage returns to S603 until the fitness for the best phase in the population is less than or equal to the preset fitness.
In particular, in this example, the end criterion may be that the best phase occurs in the population
Whether the fitting degree of (2) satisfies a preset fitting degree or not, and in the specific implementation process, the optimal phase can be judged 
Degree of fitting of
Whether or not the value is equal to or less than a set determination threshold e. If less than or equal to the decision threshold e, the end criterion is met and the genetic algorithm process described in this example ends, otherwise steps S603 to S606 are repeated until the fitness of the best phase in a group of populations is less than or equal to the pre-given fitness.
In some examples, when the set group optimization strategy is preferably a simulated annealing algorithm, referring to fig. 7, which shows a process of obtaining a final result of a phase distribution function corresponding to an ith hybrid-alternating iteration by using the simulated annealing algorithm during the ith hybrid-alternating iteration, with reference to fig. 3 and fig. 4, it can be understood that the process may be implemented as a specific implementation of step S303 in fig. 3 or step S403 in fig. 4, and the process may include:
s701: setting an initial temperature T0Target temperature TendAnd cooling rate dTTempering temperature rise threshold temperature TlowAnd initial phase solution
It should be noted that, for the simulated annealing algorithm, the initial phase solution of the first initialization
Can be the current phase solution of the subsequent algorithm during the first simulated annealing iteration
S702: solving the current phase during the current temperature T 
Making neighborhood perturbation to obtain new phase solution
Wherein S (x, y) is a neighborhood perturbation factor, and when T is>TlowWhen S (x, y) is exponentially decreased by a factor Se(x, y) rand (-a, a) exp (-b · k), where k is the number of iterations and a, b are self-setting coefficients; when T is less than or equal to TlowWhen S (x, y) is a temperature dependent Cauchy decreasing factor
And rand () denotes a random number generation function.
S703: according to the phase new solution
And BOE203, and performing Fourier transform on the combination of the incident light field amplitude distribution functions F (x, y) to obtain the complex amplitude distribution of the output surface
S704: modulus | A from complex amplitude distribution of output surface2(u, v) | calculation evaluation function SSEnewAnd evaluating the change amount Δ of the functionSSE；
S705: change of value Δ according to evaluation functionSSEJudging whether the set internal circulation condition is met, if so, executing S706; otherwise, executing S707;
specifically, the set internal circulation condition may preferably be ΔSSE<0 or exp (-delta)SSE/T)>rand(1)。
S706: with output light amplitude distribution function and phase of complex amplitude distribution of output face
Performing inverse Fourier transform to obtain
And will be
Set to the current phase solution at the next iteration temperature
Will SSEnewIs set to SSEbest。
S707: ending the cycle and maintaining
And SSEbestWithout change, S702 to S705 are repeatedly executed until the internal cycle condition at the current temperature is satisfied.
S708: according to the cooling rate dTFor the currentThe temperature is reduced, and the iteration process at the next temperature is carried out until the temperature is reduced to the target temperature Tend。
By the above example, the specific implementation processes of the GS iterative algorithm, the genetic algorithm, and the simulated annealing algorithm in the embodiment of the present invention are explained, and the phase distribution function of the binary optical element BOE203 is calculated by mixing the GS iterative algorithm and the genetic algorithm, and the GS iterative algorithm and the simulated annealing algorithm in an alternating iterative manner, so that the method is flexible to use, less limited by initial conditions, effectively avoids the algorithm from falling into local extreme points, and has global optimal search performance. Referring to fig. 8, a schematic diagram of the phase distribution of the binary optical element BOE obtained by the design method of the BOE203 is shown, and as can be seen from fig. 8, the size of the binary optical element BOE is close to or larger than the size of the laser emergent spot, so that the light beam can be ensured to be incident into the effective range of the binary optical element, and the binary optical element can modulate the wavefront phase distribution of the light beam.
It should be noted that the design method for the BOE203 may be implemented in a form of hardware, or may be implemented in a form of a software functional module. If the design method is implemented in the form of a software functional module and is not sold or used as a standalone product, the design method for the BOE203 may be stored in a computer readable storage medium, and based on the understanding, a part of the design method per se or contributing to the prior art, or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium, and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) to execute all or part of the steps of the method according to this embodiment. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Therefore, the present embodiment provides a computer storage medium, where a design program of a binary optical element BOE is stored, and when the design program of the binary optical element BOE is executed by at least one processor, the steps of the design method of the binary optical element BOE in the above technical solution are implemented.
It should be noted that: the technical schemes described in the embodiments of the present invention can be combined arbitrarily without conflict.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (10)
1. A method for designing a binary optical element BOE, the method comprising:
designing a target phase distribution function of the BOE by utilizing a mixed alternative iterative algorithm combining a local optimization algorithm and a group optimization algorithm based on an actual incident light field amplitude distribution function on an input plane and an ideal target output light amplitude distribution function on an output plane;
And fitting the target phase distribution function of the BOE by adopting a multi-order relief structure.
2. The method of claim 1, wherein the designing the target phase distribution function of the BOE using a hybrid alternating iterative algorithm of a local optimization algorithm combined with a group optimization algorithm based on an actual incident light field amplitude distribution function at an input plane and an ideal target output light amplitude distribution function at an output plane comprises:
during each hybrid alternating iteration, acquiring an intermediate result of a phase distribution function by using a set local optimization strategy based on an incident light field amplitude distribution function of the BOE, a target output light amplitude distribution function of the BOE and an initial phase distribution function;
during each hybrid alternating iteration, acquiring a final phase distribution function result by using a set group optimization strategy according to the intermediate result of the phase distribution function and the amplitude distribution of the incident light field of the BOE;
and when the set mixed alternative iteration stop judgment condition is met, determining the final result of the phase distribution function obtained by the final mixed alternative iteration as the target phase distribution function of the BOE.
3. The method of claim 1, wherein the designing the target phase distribution function of the BOE using a hybrid alternating iterative algorithm of a local optimization algorithm combined with a group optimization algorithm based on an actual incident light field amplitude distribution function at an input plane and an ideal target output light amplitude distribution function at an output plane comprises:
Setting an initial phase distribution function of the BOE input surface corresponding to the ith mixed alternative iteration;
acquiring an intermediate result of the phase distribution function corresponding to the ith hybrid alternating iteration by using a set local optimization strategy according to the initial phase distribution function, the incident light field amplitude distribution function of the BOE and the target output light amplitude distribution function of the BOE;
obtaining a final phase distribution function result corresponding to the ith hybrid alternating iteration by using a set group optimization strategy according to the intermediate result of the phase distribution function corresponding to the ith hybrid alternating iteration and the incident light field amplitude distribution of the BOE;
determining whether to continue the (i + 1) th mixed alternative iteration based on a set mixed alternative iteration stop criterion;
correspondingly, determining the final result of the phase distribution function corresponding to the ith hybrid alternating iteration as a target phase distribution function according to the condition that the hybrid alternating iteration stop criterion is met;
and correspondingly not meeting the stop criterion of the mixed alternating iteration, generating an initial phase distribution function of the BOE input surface corresponding to the (i + 1) th mixed alternating iteration based on a final phase distribution function result corresponding to the ith mixed alternating iteration, and executing the (i + 1) th mixed alternating iteration process.
4. The method according to claim 2 or 3, wherein the local optimization strategy comprises a Gaster Baker-saxoston GS iterative algorithm or a modified GS iterative algorithm; the population optimization algorithm comprises a genetic algorithm or a simulated annealing algorithm.
5. The method according to claim 4, wherein the obtaining an intermediate result of the phase distribution function corresponding to the ith hybrid alternating iteration by using the set local optimization strategy according to the initial phase distribution function, the incident light field amplitude distribution function of the BOE and the target output light amplitude distribution function of the BOE, corresponding to the local optimization strategy being a GS iterative algorithm, comprises:
during the ith mixing alternating iteration, the following steps are performed:
combining the initial phase distribution function with an incident light field amplitude distribution function of the BOE to obtain an incident light field complex amplitude distribution function during a kth GS iteration;
performing Fourier transform on the incident light field complex amplitude distribution function during a kth GS iteration, and acquiring a phase function of the incident light field complex amplitude distribution function based on the Fourier transform;
combining the phase function of the incident light field complex amplitude distribution function with the target output light amplitude distribution function of the BOE to obtain a complex amplitude function to be determined during the kth GS iteration;
During the kth GS iteration, performing inverse Fourier transform on the complex amplitude function to be judged, and acquiring a phase function to be judged based on the inverse Fourier transform;
judging whether to stop the GS iteration algorithm or not based on the phase function to be judged and a set GS iteration stop criterion;
if judging that the GS iteration algorithm is stopped, determining the phase function to be judged acquired during the kth GS iteration as an intermediate result of the phase distribution function corresponding to the ith mixed alternating iteration; otherwise, the phase function to be determined acquired during the kth GS iteration is used as an initial phase distribution function used by the (k + 1) th GS iteration.
6. The method according to claim 4, wherein the obtaining a final result of the phase distribution function corresponding to the ith hybrid alternating iteration by using the set group optimization strategy according to the intermediate result of the phase distribution function corresponding to the ith hybrid alternating iteration and the incident light field amplitude distribution of the BOE, in response to the group optimization strategy being a genetic algorithm, comprises:
during the ith mixing alternating iteration, the following steps are performed:
a setting stage: setting the number of sampling points of an input light field and an output light field to be M multiplied by N, wherein a sampling matrix of a phase distribution function of the BOE is an M multiplied by N matrix;
In the initial breeding stage: n phase distributions randomly selected according to the intermediate result of the phase distribution function corresponding to the ith hybrid alternating iteration
Forming an initialization group X (0), wherein each individual in the initialization group is an M multiplied by N matrix;
a replication stage: evaluation of fitness value Q (X) for each individuali) Adopting a roulette selection and adopting a guarantee strategy to directly enter the individuals with the optimal fitness into the next generation;
and (3) a cross stage: converting each individual into a 1 x MN column vector from a matrix, adopting a double-point crossing strategy to select two individuals optionally, and generating two random numbers between 1 and MN, wherein the two random numbers represent a starting point and an end point of the exchange of chromosomes of the two individuals;
and (3) a mutation stage: generating a random number between 1 and MN as a variation position;
an iteration stage: performing Fourier transform iterative operation on each individual in the population;
and (3) evaluation stage: obtaining an optimal phase based on the Fourier transform iterative operation, and evaluating whether the whole genetic iteration meets an end criterion according to the optimal phase: if so, the genetic algorithm ends, otherwise, the replication stage is returned until the fitness of the best phase appearing in the population is less than or equal to the preset fitness.
7. The method of claim 4, wherein the obtaining a final result of the phase distribution function corresponding to the ith hybrid-alternating iteration by using a set group optimization strategy according to the intermediate result of the phase distribution function corresponding to the ith hybrid-alternating iteration and the incident light field amplitude distribution of the BOE, corresponding to the group optimization strategy being a genetic simulated annealing algorithm, comprises:
during the ith mixing alternating iteration, the following steps are performed:
s71: setting an initial temperature T0Target temperature TendAnd cooling rate dTTempering temperature rise threshold temperature TlowAnd initial phase solution
S72: solving the current phase during the current temperature T
Making neighborhood perturbation to obtain new phase solution
Wherein S (x, y) is a neighborhood perturbation factor, and when T is>TlowWhen S (x, y) is exponentially decreased by a factor Se(x, y) rand (-a, a) exp (-b · k), where k is the number of iterations and a, b are self-setting coefficients; when T is less than or equal to TlowWhen S (x, y) is a temperature dependent Cauchy decreasing factor
tan () represents a random number generation function;
s73: according to the phase new solution
Fourier transform is carried out by combining the input light field amplitude distribution function F (x, y) of the BOE 203 to obtain the complex amplitude distribution of the output surface 
S74: modulus | A from complex amplitude distribution of output surface2(u, v) | calculation evaluation function SSEnewAnd evaluating the change amount Δ of the functionSSE；
S75: change of value Δ according to evaluation functionSSEJudging whether the set internal circulation condition is met, and if so, executing S76; otherwise, go to S77;
s76: with output light amplitude distribution function and phase of complex amplitude distribution of output face
Performing inverse Fourier transform to obtain
And will be
Set to the current phase solution at the next iteration temperature
Will SSEnewIs set to SSEbest；
S77: ending the cycle and maintaining
And SSEbestUnchanged, S72-S75 are repeatedly executed until the current condition is satisfiedInternal circulation conditions at temperature;
s78: according to the cooling rate dTCooling the current temperature, and performing the iteration process at the next temperature until the temperature is reduced to the target temperature Tend。
8. A laser processing device based on a binary optical element BOE is characterized by comprising an ultrafast laser, a laser processing head and the BOE; wherein the ultrafast laser generates an ultrafast laser beam; the BOE is arranged on a guide path of the ultrafast laser beam and at a beam waist position of an x axis under a set Cartesian coordinate system, and is used for correcting a divergence angle of the ultrafast laser beam and a y axis under the Cartesian coordinate system, so that an elliptical light spot of the ultrafast laser beam is changed into a circular light spot to eliminate astigmatism, and the BOE is obtained by the design method of the BOE according to any one of claims 1 to 7; the laser processing head is used for processing a target workpiece by using the corrected ultrafast laser beam transmitted through the guide path.
9. The apparatus of claim 8, wherein the BOE is fit to a phase distribution function of the BOE by a structure of multi-order reliefs.
10. The apparatus of claim 8, wherein the BOE is an 8-step BOE, and the depth d of the serrations of the BOE is 2.28 um.
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