Beam shaping quality detection and optimization system and method

Abstract

The invention relates to a light beam shaping quality detection and optimization system, which comprises a light spot preprocessing unit, a light spot fitting unit, a light beam quality evaluation unit and a shaping optimization unit, and is characterized in that the light spot preprocessing unit is used for preprocessing acquired light spots into net light spots; the light spot fitting unit is used for extracting the size of a net light spot and performing energy distribution fitting on a net light spot image and a standard Gaussian light spot image; the light beam quality evaluation unit is used for reconstructing two-dimensional light field distribution according to the energy fitting curve, comparing a deviation curve between a fitting result and a theoretical Gaussian curve, and evaluating the light beam quality of a light beam output light spot in combination with the deviation curve; and the shaping optimization unit is used for modeling the light beam shaping target and correcting a light beam phase surface in combination with the established model so as to perform directional shaping optimization on the light field. The invention further provides a beam shaping quality detection method. By constructing a multi-dimensional parameter detection mechanism of laser spots, high-precision reconstruction and analysis of key parameters such as amplitude, phase and polarization distribution of laser output can be realized.

Description

Technical Field

[0001] This invention relates to the field of optical communication technology, specifically to a beam shaping quality detection and optimization system and method. Background Technology

[0002] Ultrafast lasers, with their extremely high peak power and extremely short pulse width, play a key role in the manufacturing of silicon-based cells in the field of solar photovoltaics, and are widely used in high-precision processes such as cell thinning, etching, grooving, and doping.

[0003] To meet the demands of large-area, high-precision, and highly uniform processing, DOEs (diffractive optical elements) are typically used to shape and homogenize the laser beam, transforming the original Gaussian beam into a flat-topped spot with uniform energy distribution and sharp edges, thereby improving processing quality and stability. Especially during laser thinning and etching processes, the uniformity of the spot energy density directly determines the thickness uniformity of the thinned silicon wafer and the edge quality of the etched pattern.

[0004] However, current domestically produced ultrafast lasers still face problems such as low processing yield and significant inconsistencies in DOE-assisted beam shaping systems. Although their basic parameters such as power, repetition rate, and pulse width have met factory standards, the lack of wavefront detection and beam quality assessment methods results in significant gaps in wavefront distribution and mode stability, making it difficult to achieve effective closed-loop control of the processing. Users generally report that when using DOE systems, domestically produced lasers often exhibit problems such as spot distortion and energy unevenness, leading to low yield, edge ablation, and poor processing repeatability.

[0005] In contrast, foreign laser manufacturers such as Coherent (HyperRapid) and Trumpf (TruMicro) have widely adopted Shack-Hartmann wavefront analyzers, which can monitor and correct wavefront distortion of the laser in real time during transmission, thereby ensuring the quality of the shaped laser spot and maintaining a stable processing yield of over 80%. Domestic lasers currently lack supporting testing and optimization systems in this area, hindering their further promotion in high-end manufacturing. Summary of the Invention

[0006] The purpose of this invention is to provide a beam shaping quality detection and optimization system and method, which can at least solve some of the defects in the prior art.

[0007] To achieve the above objectives, embodiments of the present invention provide the following technical solution: a beam shaping quality detection and optimization system, comprising a beam preprocessing unit, a beam fitting unit, a beam quality evaluation unit, and a beam shaping optimization unit.

[0008] The light spot preprocessing unit is used to preprocess the acquired light spot into a clean light spot.

[0009] The spot fitting unit is used to extract the size of the net spot and fit the energy distribution of the net spot image with the standard fundamental mode Gaussian spot image.

[0010] The beam quality assessment unit is used to reconstruct the two-dimensional optical field distribution based on the energy fitting curve, compare the deviation curve between the reconstruction result and the theoretical fundamental mode Gaussian curve, and evaluate the beam quality of the output beam spot in conjunction with the deviation curve.

[0011] The shaping and optimization unit is used to model the beam shaping target and modify the beam phase surface in combination with the model to optimize the directional shaping of the light field.

[0012] Furthermore, the light spot preprocessing unit includes a light spot acquisition device and a noise processing module.

[0013] The light spot acquisition device acquires two-dimensional image data of the light spot and reads the light spot matrix image.

[0014] The noise processing module converts the read spot matrix image into units based on pixel size, and performs Gaussian filtering and smooths local noise.

[0015] Furthermore, the light spot preprocessing unit also includes a net light spot extraction module.

[0016] The net spot extraction module calculates the average background light intensity in the four corner regions of the spot matrix image and subtracts the background noise value to extract the net spot.

[0017] Furthermore, the light spot fitting unit includes a light intensity extraction module and a light spot calculation module.

[0018] The light intensity extraction module extracts the two-dimensional light intensity energy distribution in the horizontal, vertical, and positive and negative diagonal directions of the light spot center.

[0019] The light spot calculation module calculates the light intensity energy distribution in each direction based on 1 / e 2 The light spot radius under the threshold is calculated, and the average light spot size and ellipticity are also calculated.

[0020] Furthermore, the spot fitting unit also includes a fitting module.

[0021] The fitting module integrates the light intensity distribution in polar coordinates, normalizes the cropped image of the light spot region, and then fits the cropped image with the energy distribution of a standard two-dimensional Gaussian light spot image of the target light field. The standard two-dimensional Gaussian light spot image corresponds to a fundamental mode with a preset fixed radius. A Gaussian beam is used as the reference source field input to ensure spatial scale consistency during the fitting and phase holographic calculation processes.

[0022] Furthermore, the beam quality assessment unit includes a one-dimensional Gaussian expansion module and a fitting error analysis module.

[0023] The one-dimensional Gaussian expansion module constructs a standard fundamental Gaussian function basis with different radii, and reconstructs the measured beam profiles along the transverse, longitudinal, and positive and negative diagonal directions of the beam center. Then, it performs normalized interpolation and resampling based on the measured light intensity of the measured beam profiles to reconstruct the one-dimensional Gaussian envelope coefficients in the corresponding directions.

[0024] The fitting error analysis module compares the deviation curve between the reconstruction result of the one-dimensional Gaussian expansion module and the theoretical fundamental mode Gaussian curve, and outputs a directional deviation index. The deviation index parameters of all fittings are weighted to form a comprehensive evaluation index, which is used to evaluate the beam quality of the output beam spot as a whole.

[0025] This invention provides another technical solution: a method for detecting beam shaping quality, comprising the following steps:

[0026] S1, preprocess the acquired light spot into a clean light spot;

[0027] S2, extract the size of the net spot and fit the energy distribution of the net spot image with the standard fundamental mode Gaussian spot image;

[0028] S3. Reconstruct the two-dimensional light field distribution based on the energy fitting curve, compare the deviation curve between the reconstruction result and the theoretical fundamental mode Gaussian curve, and evaluate the beam quality of the output beam spot in combination with the deviation curve.

[0029] S4. Model the beam shaping target and modify the beam phase surface based on the model to optimize the optical field orientation shaping.

[0030] Furthermore, step S1 specifically includes:

[0031] Two-dimensional image data of the light spot is acquired using a CCD camera or a laser spot measurement device, and the spot matrix is ​​read from the data;

[0032] The read spot matrix image is converted to pixel size, and Gaussian filtering and local noise smoothing are performed.

[0033] The background light intensity in the four corner regions of the light spot matrix image is averaged and the background noise value is subtracted to extract the net light spot.

[0034] An image center extraction algorithm is used to align the center of the light spot with the center of the image.

[0035] Furthermore, step S2 specifically includes:

[0036] Extract the two-dimensional light intensity energy distribution along the horizontal, vertical, and positive and negative diagonal directions of the light spot center;

[0037] Based on the energy distribution of light intensity in each direction, it is calculated that at 1 / e 2 The spot radius under the threshold is calculated, and the average spot size and ellipticity are also calculated.

[0038] The light intensity distribution is integrated in polar coordinates, and the image of the light spot region is normalized. Then, the energy distribution of the cropped image is fitted to the standard two-dimensional Gaussian light spot image of the target light field.

[0039] The consistency between the light spot and the ideal Gaussian light spot is quantified by calculating information entropy and deviation function evaluation indicators.

[0040] Furthermore, step S3 specifically includes:

[0041] Construct a standard fundamental Gaussian function basis with different radii, and reconstruct the measured spot profiles in the transverse, longitudinal, and positive and negative diagonal directions of the spot center;

[0042] Normalized interpolation resampling is performed based on the measured light intensity of the measured light spot profile to fit the one-dimensional Gaussian envelope coefficients in the corresponding direction;

[0043] Compare the deviation curve between the fitting result of the one-dimensional Gaussian expansion module and the theoretical fundamental Gaussian curve, and output the directional deviation index;

[0044] By weighting all the above-mentioned fitting deviation parameters, a comprehensive evaluation index is formed, which is used to evaluate the overall beam quality of the output beam spot.

[0045] Compared with the prior art, the beneficial effects of the present invention are:

[0046] 1. This system replaces imported detection equipment such as traditional Shack-Hartmann wavefront analyzers by constructing a multi-dimensional parameter detection mechanism for laser spots, such as spot preprocessing, spot fitting, beam quality assessment, and shaping optimization. It can achieve high-precision reconstruction and analysis of key parameters such as amplitude, phase, and polarization distribution of laser output.

[0047] 2. By introducing computational holography and light field inversion algorithms, the laser mode can be rapidly decomposed and identified. Combined with the DOE beam shaping characteristics, the system can be adapted to improve the consistency of the laser spot and the uniformity of energy distribution during laser processing. This system has the advantages of compact structure, fast response, and suitability for automated production lines. It can be widely used for factory testing of domestic ultrafast lasers and real-time monitoring of on-site processing by industrial users.

[0048] 3. It can significantly improve the processing yield and mode stability of domestic lasers based on DOE shaping systems, reduce dependence on imported high-end testing equipment, and promote the large-scale application of domestic ultrafast lasers in high-end manufacturing fields such as new energy photovoltaics and laser micro-nano processing. It has good industrialization prospects and promotion value.

[0049] 4. The ability to conduct laser wavefront mode analysis and shaping prediction modeling research is a key technological path to improve the consistency and processing yield of domestically produced ultrafast lasers. This will not only help build an independent and controllable beam quality evaluation system and promote the establishment of domestic group standards related to laser processing, but will also provide solid support for domestic substitution in fields such as new energy batteries and semiconductor micromachining, and accelerate the localization process of my country's high-end laser equipment. Attached Figure Description

[0050] Figure 1 A two-dimensional distribution map of the original beam spot after filtering and denoising, provided by a beam shaping quality detection and optimization system in an embodiment of the present invention;

[0051] Figure 2 A three-dimensional optical field distribution diagram of a beam shaping quality detection and optimization system provided in an embodiment of the present invention;

[0052] Figure 3 An X-axis one-dimensional Gaussian fitting diagram of a beam shaping quality detection and optimization system provided in an embodiment of the present invention;

[0053] Figure 4 A one-dimensional Gaussian fitting image in the Y direction of a beam shaping quality detection and optimization system provided in an embodiment of the present invention;

[0054] Figure 5 A one-dimensional Gaussian fitting diagram along the main diagonal direction of a beam shaping quality detection and optimization system provided in an embodiment of the present invention;

[0055] Figure 6 A one-dimensional Gaussian fitting plot of the sub-diagonal direction of a beam shaping quality detection and optimization system provided in an embodiment of the present invention;

[0056] Figure 7 This is a diagram showing the predicted beam shaping effect after collimation and DOE of an actual measured beam in a beam shaping quality detection and optimization system provided in an embodiment of the present invention.

[0057] Figure 8 This invention provides a phase distribution map of a beam shaping quality detection and optimization system required to achieve a target optical field.

[0058] Figure 9A two-dimensional image of an optimized, ideal Gaussian beam after passing through a doe (doe) is provided for an embodiment of the present invention.

[0059] Figure 10 A two-dimensional optical field offset analysis diagram along the main diagonal direction of a beam shaping quality detection and optimization system provided in an embodiment of the present invention;

[0060] Figure 11 A two-dimensional optical field offset analysis diagram in the X direction of a beam shaping quality detection and optimization system provided in an embodiment of the present invention;

[0061] Figure 12 A two-dimensional optical field offset analysis diagram in the Y direction of a beam shaping quality detection and optimization system provided in an embodiment of the present invention;

[0062] Figure 13 This is a two-dimensional optical field offset analysis diagram in the diagonal direction of a beam shaping quality detection and optimization system provided in an embodiment of the present invention. Detailed Implementation

[0063] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0064] Example 1:

[0065] Please see Figures 1 to 9This invention provides a beam shaping quality detection and optimization system, including a beam preprocessing unit, a beam fitting unit, a beam quality evaluation unit, and a beam shaping optimization unit. The beam preprocessing unit preprocesses the acquired beam spot into a net beam spot. The beam fitting unit extracts the size of the net beam spot and fits the net beam spot image to a standard fundamental mode Gaussian beam spot image for energy distribution. The beam quality evaluation unit reconstructs a two-dimensional light field distribution based on the energy fitting curve, compares the deviation curve between the reconstructed result and the theoretical fundamental mode Gaussian curve, and evaluates the beam quality of the output beam spot based on the deviation curve. The beam shaping optimization unit models the beam shaping target and corrects the beam phase plane based on the constructed model to optimize the directional shaping of the light field. In this embodiment, the system is particularly suitable for beam quality diagnosis, beam shaping prediction, and phase optimization design of domestically produced ultrafast lasers in DOE (diffractive optical element)-assisted micro / nano fabrication. This system combines measured beam spot data, wavefront reconstruction algorithms, and DOE optimization modeling techniques to establish a complete beam analysis and shaping method. It features non-contact operation, high resolution, and feedback-based optimization capabilities, and can be widely applied in laser production line quality control and laser micro / nano fabrication system design. This system is suitable for beam spot quality control in precision laser processing such as laser etching of solar cells.

[0066] Please see Figures 1 to 9 The spot preprocessing unit includes a spot acquisition device and a noise processing module. The spot acquisition device acquires two-dimensional image data of the spot and reads the spot matrix image; the noise processing module converts the read spot matrix image to pixel size, performs Gaussian filtering, and smooths local noise. The spot preprocessing unit also includes a net spot extraction module, which averages the background light intensity in the four corner regions of the spot matrix image and subtracts the background noise value to extract the net spot. In this embodiment, two-dimensional image data of the spot is acquired using a high-resolution CCD or a domestic laser spot measurement device, and a spot matrix in .bgData or .beamData format is read. Then, the read image is converted to pixel size, and Gaussian filtering is performed to smooth local noise. Next, the background light intensity in the four corner regions is averaged and the background noise value is subtracted to extract the net spot. Finally, an image center extraction algorithm is used to align the spot center with the image center to ensure the accuracy of subsequent analysis.

[0067] Please see Figures 1 to 9 The light spot fitting unit includes a light intensity extraction module and a light spot calculation module. The light intensity extraction module extracts the two-dimensional light intensity energy distribution in the horizontal, vertical, and positive and negative diagonal directions of the light spot center. The light spot calculation module calculates the light intensity energy distribution in 1 / e based on the light intensity energy distribution in each direction. 2The light spot radius under the threshold is calculated, and the average light spot size and ellipticity are calculated. The light spot fitting unit also includes a fitting module, which integrates the light intensity distribution in polar coordinates, normalizes the image of the cropped light spot region, and then fits the cropped image with the energy distribution of a standard two-dimensional Gaussian light spot image of the target light field, wherein the standard two-dimensional Gaussian light spot image corresponds to a fundamental mode with a preset fixed radius. A Gaussian beam is used as the reference source field input to ensure spatial scale consistency during fitting and phase holographic calculations. In this embodiment, intensity profiles are extracted from the center of the beam in the transverse (X), longitudinal (Y), and positive and negative diagonal directions, and then the intensity profiles in each direction at 1 / e are calculated. 2 The light spot radius under the threshold is determined, and the average light spot size and ellipticity are estimated. Then, the light intensity distribution is integrated in polar coordinates to determine the equivalent Gaussian envelope radius containing 86.5% of the total energy. The cropped area image is then normalized and its energy distribution is fitted with that of a standard two-dimensional Gaussian light spot. The consistency between the light spot and the ideal Gaussian is quantified by calculating evaluation indicators such as information entropy and deviation function.

[0068] Please see Figures 1 to 9The beam quality assessment unit includes a one-dimensional Gaussian expansion module and a fitting error analysis module. The one-dimensional Gaussian expansion module constructs a standard fundamental mode Gaussian function basis with different radii and reconstructs the measured beam profiles in the transverse, longitudinal, and positive and negative diagonal directions of the beam center. Then, it performs normalized interpolation and resampling based on the measured light intensity of the measured beam profiles to reconstruct the one-dimensional Gaussian envelope coefficients in the corresponding directions. The fitting error analysis module compares the deviation curve between the reconstruction result of the one-dimensional Gaussian expansion module and the theoretical fundamental mode Gaussian curve, and outputs a directional deviation index. The deviation index parameters of all fittings are weighted to form a comprehensive evaluation index, which is used to comprehensively evaluate the beam quality of the output beam spot. In this embodiment, a set of standard fundamental mode Gaussian function bases with different radii are constructed to reconstruct the measured beam profile (X, Y, positive and negative diagonal directions). Then, the measured light intensity is normalized and resampled by interpolation, and the one-dimensional Gaussian envelope coefficients in the corresponding directions are reconstructed by the inverse square error gradient descent method. Next, the deviation curve between the reconstructed result and the theoretical fundamental mode Gaussian curve is compared, and the directional deviation index is output. Then, all fitting index parameters are weighted to form a comprehensive evaluation index, which is used to evaluate the beam quality of the laser output beam as a whole. After this step is completed, DOE beam shaping target modeling and optimization design can be performed. Specifically, the DOE shaping target is set as a rectangular homogenized spot area. An intensity target map is constructed by specifying the imaging size (e.g., 150×150μm). Then, parameters such as laser wavelength, lens focal length, and sampling step size are set. An angular spectrum propagation model or a CZT fast Fourier propagation model is constructed based on diffraction theory. Next, the DOE phase surface is initialized, and the loss function is defined as the weighted difference between the shaped intensity distribution and the target map. Then, the momentum method optimization algorithm is used to iteratively correct the DOE phase surface to minimize the loss function and achieve optical field orientation shaping optimization.

[0069] Please see Figures 1 to 9 This system also includes a simulation evaluation module and an output integration module, both of which are steps following the aforementioned shaping and optimization. Specifically, the simulation evaluation module uses a measured laser spot instead of an ideal Gaussian source as the input light field for the DOE optimization system. It then loads the optimized DOE phase into the system, compares the shaped output diagrams under the measured laser source and ideal Gaussian incident light, and evaluates the shaping adaptability and energy transfer efficiency of the measured light source under the current DOE design, providing a quantitative reference for laser adaptability. The output integration module integrates the above analysis process into the system, supporting the loading of spot files, parameter input, automatic calculation, and result visualization. It then outputs multi-dimensional results including spot parameters, fitting error curves, DOE shaping effect diagrams, shaping matching degree, and predicted processing yield. This system can be used for wavefront testing of domestically produced ultrafast lasers before shipment, light source adaptability evaluation before DOE custom design, and micro / nano fabrication consistency prediction.

[0070] Example 2:

[0071] Please see Figures 1 to 9 This invention provides a beam shaping quality detection method that can be used in the aforementioned system. The method includes the following steps: S1, preprocessing the acquired beam spot into a net beam spot; S2, extracting the size of the net beam spot and fitting the net beam spot image to the energy distribution of a standard fundamental mode Gaussian beam spot image; S3, reconstructing the two-dimensional light field distribution based on the energy fitting curve, comparing the deviation curve between the reconstructed result and the theoretical fundamental mode Gaussian curve, and evaluating the beam quality of the output beam spot based on the deviation curve; S4, modeling the beam shaping target and correcting the beam phase surface based on the constructed model to optimize the directional shaping of the light field. The method in this embodiment effectively solves the practical problems of insufficient wavefront uniformity, unstable shaped beam spot, and low processing yield in current domestically produced ultrafast lasers, and has significant engineering practicality and promotional value. Furthermore, this method offers advantages such as high-resolution reconstruction and analysis of wavefront quality, quantitative evaluation and automatic optimization of laser modes, improved adaptability and yield of DOE beam shaping systems, support for efficient DOE phase design and personalized adaptation, promotion of quality closed-loop and standard setting in the domestic laser industry chain, and reduction of system costs and dependence on imported equipment. This method is non-contact, high-resolution, and allows for feedback optimization, making it widely applicable to laser production line quality control and laser micro / nano fabrication system design. It is also suitable for spot quality control in laser precision processing processes such as laser etching of solar cells.

[0072] As an optimized embodiment of the present invention, step S1 specifically involves: acquiring two-dimensional image data of the light spot using a CCD camera or a laser spot measurement device, and reading the light spot matrix in .bgData or .beamData format from the data; converting the read light spot matrix image to pixel size, and performing Gaussian filtering and smoothing local noise; averaging the background light intensity in the four corner regions of the light spot matrix image, subtracting the background noise value to extract the net light spot; and aligning the light spot center with the image center using an image center extraction algorithm. Step S2 specifically involves: extracting the two-dimensional light intensity energy distribution in the horizontal (X), vertical (Y), and positive and negative diagonal directions of the light spot center; calculating the light intensity energy distribution in 1 / e... 2The light spot radius under the threshold is calculated, and the average light spot size and ellipticity are calculated. The light intensity distribution is integrated in polar coordinates to determine the equivalent Gaussian envelope radius containing 86.5% of the total energy. The image of the cropped light spot region is normalized, and then the cropped image is fitted with the standard two-dimensional Gaussian light spot image of the target light field for energy distribution. The consistency between the light spot and the ideal Gaussian light spot is quantified by calculating the information entropy and the deviation function evaluation index. The S3 step specifically involves: constructing a standard fundamental Gaussian function basis with different radii, and reconstructing the measured beam profiles (X, Y, and positive and negative diagonal directions) of the beam center in the transverse, longitudinal, and positive and negative diagonal directions; performing normalized interpolation resampling based on the measured light intensity of the measured beam profiles, and fitting the one-dimensional Gaussian envelope coefficients in the corresponding directions using the inverse squared error gradient descent method; comparing the deviation curve between the fitting result of the one-dimensional Gaussian expansion module and the theoretical fundamental Gaussian curve, and outputting a directional deviation index; weighting all the above-mentioned fitting deviation indexes (such as directional deviation, information entropy, deviation function, etc.) to form a comprehensive evaluation index, which is used to comprehensively evaluate the beam quality of the output beam spot. Step S4 is as follows: Set the DOE shaping target as a rectangular homogenized spot area, construct an intensity target map by specifying the imaging size (e.g., 150×150μm), then set parameters such as laser wavelength, lens focal length, and sampling step size, construct an angular spectrum propagation model or a CZT fast Fourier propagation model based on diffraction theory, then initialize the DOE phase surface, define the loss function as the weighted difference between the shaped intensity distribution and the target map, and then use the momentum method optimization algorithm to iteratively correct the DOE phase surface to minimize the loss function and achieve optical field orientation shaping optimization.

[0073] As an optimized embodiment of the present invention, after the optimization in step S4, step S5 is further included: using a measured light spot instead of an ideal Gaussian source as the input light field of the DOE optimization system; then loading the optimized DOE phase into the system; comparing the shaped output diagrams of the measured laser source and the ideal Gaussian incident light; and then evaluating the shaped adaptability and energy transfer efficiency of the measured light source under the current DOE design, providing a quantitative reference for laser adaptability. Step S6 is also included: integrating the above analysis process into this system, supporting the loading of light spot files, parameter input, automatic calculation, and result visualization; and then outputting multi-dimensional results including light spot parameters, fitting error curves, DOE shaped effect diagrams, shaped matching degree, and processing prediction yield. This system can be used for wavefront testing of domestically produced ultrafast lasers before shipment, light source adaptability evaluation before DOE custom design, and micro / nano fabrication consistency prediction.

[0074] Specifically, this invention employs phase encoding and computational holography technology, eliminating the need for complex optical systems relying on microlens arrays, such as traditional Shack-Hartmann wavefront analyzers, to achieve full parameter measurement of the amplitude, phase, and polarization of the laser beam field. This improves resolution by at least two orders of magnitude, providing technical support for refined beam quality control. By introducing a one-dimensional / two-dimensional Gaussian expansion model and multi-dimensional quantitative indicators such as ellipticity, information entropy, and symmetry, this invention can automatically identify and quantitatively analyze the laser output mode, forming a feedback loop. This provides a basis for proactive optimization of the laser during factory testing or processing, improving product consistency and stability. By inputting the measured beam field into the DOE shaping simulation model, the system can quickly predict the shaped beam quality and processing results of the actual laser under the DOE processing system, avoiding energy distortion and beam unevenness caused by wavefront mismatch, and significantly improving DO beam quality. The system improves the shaping efficiency and micro / nano processing yield of E-spots; it incorporates a built-in DOE inverse design and light field optimization module, combining custom energy distribution targets (such as flat-top, rectangular, or multi-zone spots) and utilizes gradient optimization algorithms to automatically generate a phase structure adapted to the actual laser output. This supports personalized DOE design, enhancing the versatility and robustness of the shaping system. It can be integrated into laser manufacturing lines to achieve rapid detection and recording of the wavefront quality and DOE shaping compatibility of each laser, providing a data foundation for establishing a domestic laser quality control standard system and group standards. This helps enhance the brand competitiveness and international market share of domestic laser products. Complete wavefront detection and shaping analysis functions can be achieved through software algorithms and standard optical components, significantly reducing costs compared to imported equipment and significantly improving the scalability and engineering applicability of system deployment. It is suitable for large-scale promotion in fields such as new energy battery manufacturing and precision laser processing. Thus, it solves key technical problems in current laser processing, such as poor beam consistency, large shaping errors, and yield fluctuations, demonstrating significant engineering application value and economic and social benefits.

[0075] The following are the specific implementation methods:

[0076] This system includes an ultrafast laser source, a beam-expanding optical system (such as a beam expander), a CCD image acquisition device, and a beam shaping quality detection and optimization system. In practice, the CCD imaging system first acquires three-dimensional distribution data of the expanded laser spot at multiple typical locations in the optical path. The obtained image data is then imported into the system for image preprocessing and parameter analysis. Figure 1 As shown, in the first step of the technical solution, the software filters the original image to obtain a two-dimensional intensity distribution map of the expanded laser spot, which is used to observe the preliminary morphological characteristics of the spot. Figure 2As shown, in the second step, the software reconstructs the three-dimensional light field distribution of the light spot and calculates key parameters including the light spot radius, ellipticity, and energy concentration, establishing a basic index system for evaluating beam quality. Figures 3 to 6 The system demonstrates the one-dimensional intensity distribution curves extracted along the horizontal, vertical, and main and secondary diagonal directions in the third step. By fitting the system to a multi-scale Gaussian function expansion basis, the system obtains Gaussian fitting results for each direction. Combining information entropy, fitting residuals, symmetry, and other indicators, it outputs a comprehensive evaluation criterion to quantitatively measure the consistency between the laser beam and the ideal Gaussian light field. Figure 7 This demonstrates the incident light source after beam expansion and collimation. Figure 8 This is the phase distribution diagram required to shape the Gaussian input light field into the target light field, and it is the core reference for DOE optical structure design. Figure 9 To produce a perfect Gaussian incidence diagram, it is shown that by taking the measured light field as input, through... Figure 8 The output shaping effect diagram obtained after wavefront modulation of the phase surface in the DOE system is used to predict the actual output shaping performance of the laser in the DOE system and to serve as a technical basis for optimizing the laser source adaptability. Figures 10 to 13 The two-dimensional optical field offset analysis diagrams for the main diagonal, X, Y, and sub-diagonal directions respectively all demonstrate the difference between the reconstructed optical field and the ideal Gaussian intensity. This invention not only achieves high-resolution, multi-dimensional measurement and evaluation of laser beams, but also provides a shaping modeling and simulation path driven by measured wavefront data, offering comprehensive and reliable support for laser wavefront tuning and DOE custom design.

[0077] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A beam shaping quality detection and optimization system, characterized in that: It includes a beam preprocessing unit, a beam fitting unit, a beam quality assessment unit, and a beam shaping and optimization unit. The light spot preprocessing unit is used to preprocess the acquired light spot into a clean light spot. The spot fitting unit is used to extract the size of the net spot and fit the energy distribution of the net spot image with the standard fundamental mode Gaussian spot image. The beam quality assessment unit is used to reconstruct the two-dimensional optical field distribution based on the energy fitting curve, compare the deviation curve between the reconstruction result and the theoretical fundamental mode Gaussian curve, and evaluate the beam quality of the output beam spot in conjunction with the deviation curve. The shaping and optimization unit is used to model the beam shaping target and modify the beam phase surface in combination with the model to optimize the directional shaping of the light field.

2. The beam shaping quality detection and optimization system as described in claim 1, characterized in that: The light spot preprocessing unit includes a light spot acquisition device and a noise processing module. The light spot acquisition device acquires two-dimensional image data of the light spot and reads the light spot matrix image. The noise processing module converts the read spot matrix image into units based on pixel size, and performs Gaussian filtering and smooths local noise.

3. The beam shaping quality detection and optimization system as described in claim 2, characterized in that: The light spot preprocessing unit also includes a net light spot extraction module. The net spot extraction module calculates the average background light intensity in the four corner regions of the spot matrix image and subtracts the background noise value to extract the net spot.

4. The beam shaping quality detection and optimization system as described in claim 1, characterized in that: The light spot fitting unit includes a light intensity extraction module and a light spot calculation module. The light intensity extraction module extracts the two-dimensional light intensity energy distribution in the horizontal, vertical, and positive and negative diagonal directions of the light spot center. The light spot calculation module calculates the light intensity energy distribution in each direction based on 1 / e 2 The light spot radius under the threshold is calculated, and the average light spot size and ellipticity are also calculated.

5. The beam shaping quality detection and optimization system as described in claim 4, characterized in that: The spot fitting unit also includes a fitting module. The fitting module integrates the light intensity distribution in polar coordinates, normalizes the cropped image of the light spot region, and then fits the cropped image with the energy distribution of a standard two-dimensional Gaussian light spot image of the target light field. The standard two-dimensional Gaussian light spot image corresponds to a fundamental mode with a preset fixed radius. A Gaussian beam is used as the reference source field input to ensure spatial scale consistency during the fitting and phase holographic calculation processes.

6. The beam shaping quality detection and optimization system as described in claim 1, characterized in that: The beam quality assessment unit includes a one-dimensional Gaussian expansion module and a fitting error analysis module. The one-dimensional Gaussian expansion module constructs a standard fundamental Gaussian function basis with different radii, and reconstructs the measured beam profiles along the transverse, longitudinal, and positive and negative diagonal directions of the beam center. Then, it performs normalized interpolation and resampling based on the measured light intensity of the measured beam profiles to reconstruct the one-dimensional Gaussian envelope coefficients in the corresponding directions. The fitting error analysis module compares the deviation curve between the reconstruction result of the one-dimensional Gaussian expansion module and the theoretical fundamental mode Gaussian curve, and outputs a directional deviation index. The deviation index parameters of all fittings are weighted to form a comprehensive evaluation index, which is used to evaluate the beam quality of the output beam spot as a whole.

7. A method for detecting beam shaping quality, characterized in that, Includes the following steps: S1, preprocess the acquired light spot into a clean light spot; S2, extract the size of the net spot and fit the energy distribution of the net spot image with the standard fundamental mode Gaussian spot image; S3. Reconstruct the two-dimensional light field distribution based on the energy fitting curve, compare the deviation curve between the reconstruction result and the theoretical fundamental mode Gaussian curve, and evaluate the beam quality of the output beam spot in combination with the deviation curve. S4. Model the beam shaping target and modify the beam phase surface based on the model to optimize the optical field orientation shaping.

8. The beam shaping quality detection method as described in claim 7, characterized in that, The specific steps of S1 are as follows: Two-dimensional image data of the light spot is acquired using a CCD camera or a laser spot measurement device, and the spot matrix is ​​read from the data; The read spot matrix image is converted to pixel size, and Gaussian filtering and local noise smoothing are performed. The background light intensity in the four corner regions of the light spot matrix image is averaged and the background noise value is subtracted to extract the net light spot. An image center extraction algorithm is used to align the center of the light spot with the center of the image.

9. The beam shaping quality detection method as described in claim 7, characterized in that, The S2 step is specifically as follows: Extract the two-dimensional light intensity energy distribution along the horizontal, vertical, and positive and negative diagonal directions of the light spot center; Based on the energy distribution of light intensity in each direction, it is calculated that at 1 / e 2 The spot radius under the threshold is calculated, and the average spot size and ellipticity are also calculated. The light intensity distribution is integrated in polar coordinates, and the image of the light spot region is normalized. Then, the energy distribution of the cropped image is fitted to the standard two-dimensional Gaussian light spot image of the target light field. The consistency between the light spot and the ideal Gaussian light spot is quantified by calculating information entropy and deviation function evaluation indicators.

10. The beam shaping quality detection method as described in claim 7, characterized in that, The S3 step is specifically as follows: Construct a standard fundamental Gaussian function basis with different radii, and reconstruct the measured spot profiles in the transverse, longitudinal, and positive and negative diagonal directions of the spot center; Normalized interpolation resampling is performed based on the measured light intensity of the measured light spot profile to fit the one-dimensional Gaussian envelope coefficients in the corresponding direction; Compare the deviation curve between the fitting result of the one-dimensional Gaussian expansion module and the theoretical fundamental Gaussian curve, and output the directional deviation index; By weighting all the above-mentioned fitting deviation parameters, a comprehensive evaluation index is formed, which is used to evaluate the overall beam quality of the output beam spot.

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