Calcium fluoride crystal defect detection system and method

Abstract

The invention provides a calcium fluoride crystal defect detection system and method, and relates to the technical field of detection, and the method comprises the following steps: preprocessing a crystal to determine a reference position and environmental parameters, and then respectively carrying out optical uniformity detection and stress birefringence detection to obtain an interference fringe pattern and polarization state change data; and optical path difference data and stress field data are generated. And through spatial registration and data association analysis, extracting areas with both refractive index anomaly and stress anomaly as candidate defect areas, quantifying defect strength and stress influence range, and finally outputting a quality judgment result of the crystal defect. The method improves the defect detection precision and reliability, and is especially suitable for high-precision calcium fluoride crystal quality control.

Description

Technical Field

[0001] The present application relates to the field of detection technology, and in particular to a calcium fluoride crystal defect detection system and method. Background Art

[0002] Calcium fluoride (CaF2) crystal is a key optical crystal material widely used in optical lenses, window materials, and high-energy laser optical components. It exhibits high transmittance, low refractive index dispersion, and excellent laser tolerance, demonstrating excellent optical performance in the ultraviolet, visible, and infrared bands. In recent years, with the increasing performance requirements for optical components in fields such as semiconductor lithography, extreme ultraviolet optics, and high-energy laser systems, the accuracy and reliability of internal defect detection in calcium fluoride crystals has become a major technical bottleneck restricting the manufacture of high-performance optical components.

[0003] During actual production and testing, calcium fluoride crystals are prone to microscopic defects such as microcracks, lattice defects, stress concentration areas, or impurity agglomerations. These defects not only reduce the optical uniformity and mechanical stability of the crystals, but can also cause performance degradation or even damage to optical components under high-power laser irradiation. Therefore, accurate and comprehensive detection and evaluation of the location and intensity of defects within the crystals, as well as the resulting optical and stress field anomalies, are crucial to ensuring the quality of calcium fluoride crystals.

[0004] Existing technologies currently lack the ability to accurately, stably, and comprehensively detect defects in calcium fluoride crystals, making it difficult to meet the stringent crystal quality requirements of high-performance optical applications. Therefore, there is an urgent need for a more accurate and robust calcium fluoride crystal defect detection method to improve crystal defect detection sensitivity, location accuracy, and evaluation reliability. Summary of the Invention

[0005] In response to the deficiencies in the prior art, the present application provides a calcium fluoride crystal defect detection system and method.

[0006] In a first aspect, the present application provides a method for detecting defects in calcium fluoride crystals, comprising:

[0007] Obtaining a calcium fluoride crystal to be tested, performing preprocessing, and obtaining first state information; wherein the first state information is used to record a reference position and environmental parameters of the calcium fluoride crystal during the testing process;

[0008] performing optical uniformity testing on the calcium fluoride crystal to obtain an interference fringe pattern of the calcium fluoride crystal; performing image processing on the interference fringe pattern and obtaining first optical path difference data for characterizing a refractive index distribution based on the first state information;

[0009] Performing stress birefringence testing on the calcium fluoride crystal to obtain polarization state change data of the calcium fluoride crystal; performing a solution process on the polarization state change data and obtaining first stress field data for characterizing stress distribution based on the first state information;

[0010] Correlating and analyzing the first optical path difference data with the first stress field data to generate defect location information; wherein the defect location information includes: defect location, defect intensity, and stress influence range of the suspected defect;

[0011] A quantitative evaluation is performed on the defect area of ​​the calcium fluoride crystal according to the defect location information to generate a quality determination result, and a test report is output based on the quality determination result.

[0012] As an optional implementation manner, obtaining the first state information includes:

[0013] Calibrate the coordinate position of the calcium fluoride crystal in the detection station to determine the relative reference between the calcium fluoride crystal and the detection light path to obtain a reference position;

[0014] Obtain the temperature, humidity and light source stability parameters in the current detection environment to obtain environmental parameters.

[0015] As an optional implementation manner, performing image processing on the interference fringe pattern and obtaining first optical path difference data for characterizing the refractive index distribution based on the first state information includes:

[0016] Based on the reference position, establishing a registration model between pixel coordinates and physical coordinates of the calcium fluoride crystal, and performing coordinate transformation processing on the interference fringe pattern after noise reduction processing to obtain a registered interference fringe pattern;

[0017] executing a phase unwrapping algorithm on the registered interference fringe pattern to obtain phase information characterizing the refractive index distribution of the calcium fluoride crystal;

[0018] Based on the environmental parameters, compensation calculation is performed on the phase information to obtain first optical path difference data.

[0019] As an optional implementation manner, performing a phase unwrapping algorithm on the registered interference fringe pattern to obtain phase information characterizing the refractive index distribution of the calcium fluoride crystal includes:

[0020] Performing a two-dimensional phase transformation on the registered interference fringe pattern to obtain an initial wrapped phase pattern;

[0021] Based on a preset phase gradient threshold, identifying a phase jump region in the initial wrapped phase image, and establishing a shear line along the phase gradient in the phase jump region;

[0022] performing dewrapping processing on the phase data on both sides of the shear line in sequence to generate a local unwrapped phase map;

[0023] Perform stitching and fusion on each local unwrapped phase image to obtain a complete global unwrapped phase image;

[0024] A noise reduction process is performed on the global unwrapped phase image to obtain phase information that ultimately characterizes the refractive index distribution of the calcium fluoride crystal.

[0025] As an optional implementation manner, the phase unwrapping algorithm further includes:

[0026] While identifying the phase jump region, extracting pixel coordinates of the stress concentration region from the first stress field data, and setting an adaptive phase gradient threshold for the corresponding phase jump region;

[0027] performing multiple iterative unwrapping processes on the phase data on both sides of the shear line in the stress concentration region to generate a local unwrapped phase map;

[0028] During the global splicing and fusion process, a local phase offset correction is performed on the unwrapped phase according to the stress distribution in the stress concentration area;

[0029] The local unwrapped phase image corrected for the local phase offset is spliced ​​and fused with the unwrapped phase images of other regions to obtain the final global phase information that characterizes the refractive index distribution of the calcium fluoride crystal.

[0030] As an optional implementation manner, performing local phase offset correction on the unwrapped phase according to the stress distribution in the stress concentration area includes:

[0031] Calculating a phase offset based on the first stress field data for the stress amplitude of each pixel in the stress concentration area;

[0032] The phase offset is superimposed on the corresponding pixel of the local unwrapped phase image to generate a corrected local unwrapped phase image.

[0033] As an optional implementation, performing multiple iterative dewrapping processes on the phase data on both sides of the shear line in the stress concentration region to generate a local unwrapped phase map includes:

[0034] Set the iterative initial value for the initial phase distribution in the stress concentration region and define the phase continuity boundary condition at the shear line;

[0035] Based on phase continuity and stress amplitude, an iterative error evaluation function is constructed to quantify the phase difference between adjacent pixels of the current dewrapping result.

[0036] During each iteration, the phase data is adjusted in sequence along both sides of the shear line so as to gradually reduce the error evaluation function;

[0037] When the number of iterations reaches a preset upper limit or the error evaluation function is lower than a threshold, a local unwrapped phase map of the stress concentration area is output.

[0038] As an optional implementation, performing multiple iterative dewrapping processes on the phase data on both sides of the shear line in the stress concentration region to generate a local unwrapped phase map further includes:

[0039] Before each iteration begins, based on the environmental parameters in the first state information, searching and loading the threshold correction rule and iteration step correction rule corresponding to the current environmental conditions, and updating the phase gradient threshold and iteration step;

[0040] The updated phase gradient threshold and iteration step size are used to perform iterative de-wrapping operations on the phase data on both sides of the shear line.

[0041] After each iteration, incrementally updating the registration model of the local unwrapped phase and the physical coordinates of the calcium fluoride crystal using the reference position in the first state information, and recording the updated registration model;

[0042] When the number of iterations reaches a preset upper limit, or the phase difference variation during the iteration process is lower than a preset threshold, a local unwrapped phase map corresponding to the stress concentration region is output.

[0043] As an optional implementation manner, the correlating analysis of the first optical path difference data and the first stress field data to generate defect location information includes:

[0044] Based on the reference position recorded in the first state information, performing spatial registration on the first optical path difference data and the first stress field data so that the two are aligned in the same coordinate system;

[0045] In the aligned data, the optical path difference gradient and stress gradient are calculated respectively, and the abnormal optical path difference gradient area and stress gradient abnormal area are identified;

[0046] Perform overlapping analysis on the optical path difference gradient abnormal area and the stress gradient abnormal area to extract candidate defect areas where both the optical path difference and stress abnormality exist in the same area;

[0047] For each candidate defect area, the average optical path difference amplitude of the candidate defect area is calculated as the defect intensity, and the stress gradient distribution range corresponding to the candidate defect area is statistically analyzed to obtain the stress influence range of the suspected defect;

[0048] The candidate defect area is marked as a defect position in the same coordinate system, and the defect location information is generated based on the defect intensity and stress influence range.

[0049] In a second aspect, the present application provides a calcium fluoride crystal defect detection system, comprising:

[0050] an acquisition module, configured to acquire the calcium fluoride crystal to be detected, perform preprocessing, and obtain first state information; wherein the first state information is used to record the reference position and environmental parameters of the calcium fluoride crystal during the detection process;

[0051] a first processing module, configured to perform optical uniformity detection on the calcium fluoride crystal to obtain an interference fringe pattern of the calcium fluoride crystal; perform image processing on the interference fringe pattern and obtain first optical path difference data for characterizing a refractive index distribution based on the first state information;

[0052] a second processing module, configured to perform stress birefringence detection on the calcium fluoride crystal to obtain polarization state change data of the calcium fluoride crystal; perform a solution process on the polarization state change data and obtain first stress field data for characterizing stress distribution based on the first state information;

[0053] a positioning module, configured to correlate and analyze the first optical path difference data with the first stress field data to generate defect positioning information; wherein the defect positioning information includes: defect position, defect intensity, and stress influence range of the suspected defect;

[0054] A determination module is configured to perform a quantitative assessment of the defect area of ​​the calcium fluoride crystal according to the defect location information, generate a quality determination result, and output a test report based on the quality determination result.

[0055] Compared with existing technologies, the present invention combines the advantages of optical uniformity testing and stress birefringence testing of calcium fluoride crystals, overcoming the limitation of a single detection method that cannot simultaneously capture refractive index anomalies and stress concentration problems. By deeply correlating the interference fringe pattern with stress distribution data, the accuracy and reliability of defect detection are effectively improved. In addition, by recording the crystal's reference position and real-time environmental parameters before testing and continuously applying this information for coordinate alignment and environmental compensation during data analysis, the present invention significantly reduces measurement errors caused by position drift, temperature and humidity changes, or light source fluctuations. At the same time, the present invention also proposes an improved phase unwrapping algorithm, especially setting an adaptive gradient threshold and multiple iteration strategies for high stress concentration areas, effectively avoiding the phase unwrapping failure or insufficient accuracy of traditional methods in complex areas. Therefore, the present invention can achieve higher-precision and higher-stability localization and evaluation of internal crystal defects, which is suitable for the refined detection needs of high-performance calcium fluoride crystals and has important engineering value and practical application significance for improving crystal quality control and the reliability of high-power optical components. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 A flow chart of the calcium fluoride crystal defect detection method provided in this application;

[0057] Figure 2 A flowchart of a method for obtaining first optical path difference data for characterizing a refractive index distribution provided in this application;

[0058] Figure 3 A flowchart of a method for obtaining phase information characterizing the refractive index distribution of calcium fluoride crystals provided in this application;

[0059] Figure 4 Schematic diagram of the calcium fluoride crystal defect detection system provided in this application. DETAILED DESCRIPTION

[0060] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments.

[0061] This application first obtains a calcium fluoride crystal to be tested, performs necessary operations such as cleaning, surface preparation, and temperature balancing, and then places the crystal at the testing station. At this point, the crystal's reference position and parameters related to the testing environment are recorded to form first state information, which is used to calibrate and compensate for the relative position of the crystal and the testing optical path, as well as environmental influences, during the testing process. An interferometer is used to perform optical uniformity testing on the pre-treated crystal. A collimated light source or parallel light beam passes through the crystal and obtains interference fringes on the optical testing surface. The obtained fringe pattern is image processed and, combined with the reference position and environmental parameters contained in the first state information, corrected, noise filtered, and phase unwrapped to obtain first optical path difference data that characterizes the crystal's refractive index distribution. Subsequently, a polarization stress meter is used to test the stress birefringence characteristics of the same crystal. Linearly polarized or circularly polarized light is incident on the crystal, and polarization state change data is obtained using an analyzer or polarization measurement device. By performing phase delay calculation or photoelastic analysis on this polarization state change data, and combining it with the first state information for coordinate alignment or environmental compensation, first stress field data reflecting the internal stress distribution of the crystal can be obtained. Based on the two types of test results, the first optical path difference data and the first stress field data are placed in the same coordinate system for correlation analysis to determine the degree of abnormality in the optical path difference and stress distribution of different regions, and to generate defect location information. This defect location information includes not only the specific location of the suspected defect area in the crystal, but also quantifies the intensity of the defect and the impact range defined by the stress gradient or stress concentration area. Finally, by comparing the defect intensity with the set quality index or process threshold, a further quantitative evaluation of the crystal defect area is performed to obtain a quality judgment result for the overall performance, and finally generate a test report for device screening, quality certification or process optimization in subsequent processes.

[0062] In this way, the two properties of optical uniformity and stress birefringence are effectively combined, which can comprehensively and accurately locate and evaluate the internal defects of calcium fluoride crystals, providing reliable quality assurance for high-precision optical devices and high-energy laser applications.

[0063] See also Figure 1 FIG. 1 is a flow chart of a calcium fluoride crystal defect detection method provided by the present application, wherein the method includes steps S101 to S105, wherein:

[0064] S101: Acquire a calcium fluoride crystal to be detected, perform preprocessing, and obtain first state information; wherein the first state information is used to record the reference position and environmental parameters of the calcium fluoride crystal during the detection process;

[0065] S102: performing optical uniformity testing on the calcium fluoride crystal to obtain an interference fringe pattern of the calcium fluoride crystal; performing image processing on the interference fringe pattern and obtaining first optical path difference data for characterizing a refractive index distribution based on the first state information;

[0066] S103: performing stress birefringence testing on the calcium fluoride crystal to obtain polarization state change data of the calcium fluoride crystal; performing a solution process on the polarization state change data and obtaining first stress field data for characterizing stress distribution based on the first state information;

[0067] S104: Correlation analysis is performed on the first optical path difference data and the first stress field data to generate defect location information; wherein the defect location information includes: defect position, defect intensity, and stress influence range of the suspected defect;

[0068] S105: performing a quantitative assessment on the defect area of ​​the calcium fluoride crystal according to the defect location information, generating a quality determination result, and outputting a test report based on the quality determination result.

[0069] Regarding S101 above:

[0070] In practice, the calcium fluoride crystal to be inspected is placed on a dedicated inspection station. Prior to placement, the crystal surface is cleaned, for example, using a dust-free cloth or ultrasonic cleaning to remove surface particles and grease. The treated calcium fluoride crystal is then secured in a precision fixture or holder, and a displacement platform or alignment mechanism is used to fine-tune the crystal's flatness and orientation, maintaining a defined angle and distance from the pre-set inspection optical path. This alignment process can be accomplished using a laser alignment device, a reflector positioner, or a CCD vision alignment system, ensuring that the spatial relationship between the crystal and the optical system meets the designed accuracy range.

[0071] After alignment is completed, the reference position data of the crystal in the detection coordinate system is obtained through the measuring device, and this data is recorded in the system control module to form a reference position record. At the same time, environmental parameters are collected using temperature, humidity, and light source stability sensors deployed at the detection station or laboratory. The temperature sensor can be a high-precision platinum resistance thermometer or a digital thermometer, and the humidity sensor can be a capacitive or impedance humidity probe. The light source stability can be obtained by real-time monitoring of light power or light intensity fluctuations. During this process, if necessary, preliminary light source preheating or stabilization operations can be performed to ensure that the light source is in an optimal output state.

[0072] The crystal reference position data and environmental parameters are written to a database or corresponding memory via the control system and are collectively referred to as first state information. This first state information is used to compensate for or correct positional offsets and environmental disturbances during subsequent optical uniformity and stress birefringence testing steps, allowing testing to be performed within the same coordinate reference and controlled environment. This approach enables preprocessing and basic data collection for the calcium fluoride crystal, ensuring uniform accuracy and environmental consistency for subsequent measurement steps.

[0073] Furthermore, without accurate, real-time acquisition and recording of the reference position and environmental parameters of the calcium fluoride crystal during the overall inspection process of the present invention, unstable measurement results can occur during optical uniformity and stress birefringence testing due to interference factors such as crystal position shift, temperature drift, or light source power fluctuations. Especially when dealing with large, high-precision calcium fluoride crystals, even slight changes in spatial orientation or temperature fluctuations can cause inconsistent fringe patterns or stress measurement errors, making it difficult to obtain accurate and reliable defect detection results.

[0074] Therefore, when obtaining the first state information, the coordinate position of the crystal in the detection station can be additionally calibrated, and key parameters such as the temperature, humidity, and light source stability of the current detection environment can be collected. The principle is:

[0075] Mechanical or optical calibration establishes a clear relative reference between the crystal and the detection optical path, enabling subsequent registration analysis of interference patterns and polarization patterns to be spatially overlapped within the same coordinate reference system. Real-time recording of parameters such as ambient temperature, humidity, and light source output fluctuations allows for appropriate compensation or correction in optical path difference and stress calculations, minimizing measurement deviations caused by thermal expansion, temperature coefficient of refractive index, or unstable light source energy.

[0076] Exemplarily, a high-precision mechanical displacement platform and a laser calibrator are set at the detection station. After the calcium fluoride crystal is placed in the holder, the laser calibrator is turned on first, and the light beam reflected from the center of the crystal returns to the CCD sensor through the reflector locator; according to the position of the reflected light spot obtained by the CCD, the XYZ and inclination of the displacement platform are automatically or manually adjusted to keep the light spot within a deviation range of no more than 0.01mm at the center of the target. At this time, this position is recorded as the reference position. In addition, a set of temperature and humidity sensors are installed on the detection station, and an optical power monitor is arranged at the light source end. The obtained temperature, humidity and light source power stability values ​​are regularly written into the storage module of the control system, and together with the "reference position" constitute the first state information.

[0077] During subsequent interferometry testing, if the temperature sensor reading indicates that the ambient temperature has risen by 0.5°C compared to the initial record, the system will use this temperature change to apply a coefficient correction to the optical path difference data. If the light source stability drops below the set warning level, the system will prompt the operator to preheat the light source or replace the filter. Furthermore, when the polarimeter and interferometer stations are not on the same platform, by re-positioning the crystal on the same reference surface, reading the initial "reference position" coordinates, and comparing the differences in platform coordinates, the crystal can be guaranteed to have a comparable coordinate basis within both measurement systems, avoiding unnecessary accumulation of spatial errors.

[0078] In this way, the measurement deviation problems caused by inaccurate positioning in the detection space and interference from the detection environment are solved, making the calculation of optical path difference and stress distribution more stable; due to the monitoring of light source stability and real-time compensation combined with temperature and humidity information, the interference fringe pattern and polarization pattern achieve better consistency, which can significantly improve the accuracy and reliability of defect detection; when crystals are inspected at different workstations, data visualization and subsequent defect evaluation in the same coordinate system can also be achieved based on the recording of the "reference position", which is especially suitable for large-size or high-precision crystals.

[0079] Regarding S102 above:

[0080] When performing optical uniformity detection, an interferometer can be configured at the detection station to obtain an interference fringe pattern corresponding to the refractive index distribution inside the calcium fluoride crystal. The specific form of the interferometer can be a laser interferometer (such as Twyman-Green, Fizeau or Mach-Zehnder structure, etc.) or a white light interferometer, depending on the required detection wavelength and sensitivity requirements. During detection, a collimated light beam is passed through the calcium fluoride crystal along a preset optical path, and the interference fringes are recorded on a detector or imaging system (such as a CCD, CMOS camera). According to the size of the calcium fluoride crystal and the field of view of the interference system, the light source divergence angle, beam diameter or cavity length of the interferometer can be appropriately adjusted to ensure that the resolution and contrast of the fringe pattern meet the measurement accuracy requirements of the present invention.

[0081] After obtaining the fringe pattern, image processing is performed on it, including basic operations such as background light subtraction, noise filtering, and fringe distortion correction. The clarity of the fringe can be enhanced by digital filtering algorithms (such as Gaussian filtering, morphological filtering, etc.). If multi-frame shooting is involved, the multi-frame fringe pattern can be superimposed and averaged or time-series filtered to improve the signal-to-noise ratio. After processing, the fringe phase information is obtained through the phase unwrapping algorithm or the interferometric phase extraction algorithm, and the possible phase jump area is corrected in sections or branch-cut. In order to ensure that the processing results match the crystal space coordinates, the reference position data in the first state information is called, and the fringe pattern or phase distribution is aligned and the coordinates are transformed to ensure that the subsequent analysis links can be integrated with the stress data under the same coordinate reference.

[0082] During the compensation process, the unwrapped phase can be corrected for temperature and humidity based on the environmental parameters in the first state information. For example, the optical path difference (OPD) can be adjusted accordingly based on the temperature coefficient to reduce measurement errors caused by environmental interference. Ultimately, the unwrapped phase is converted into an OPD value, yielding first OPD data representing the refractive index distribution. This data can be recorded in the main control module or measurement database and serve as the basis for subsequent correlation analysis with stress distribution. This operation enables quantitative detection of the optical uniformity of calcium fluoride crystals, significantly improving the accuracy of identifying and locating microscopic refractive index anomalies.

[0083] Regarding S103 above:

[0084] In this step, a polarized stress detection device is used to measure stress birefringence in the calcium fluoride crystal. Typically, a transmission or reflection polarized stress meter is used, specifically configured with a polarized light source (such as linearly polarized light or circularly polarized light), a polarization analyzer (such as an analyzer or a half-wave plate plus analyzer combination), and a high-resolution sensor. By placing the calcium fluoride crystal under test in the polarized light path, the polarization state changes of the transmitted or reflected light are recorded and collected, resulting in an original image or light intensity distribution reflecting the local stress state of the crystal.

[0085] To implement the present invention, a polarization stress meter can be deployed at the inspection station or a nearby station for use in conjunction with an interferometer. During testing, a calcium fluoride crystal is aligned with the polarization stress meter optical path according to a predetermined reference position. If the crystal position or posture requires fine-tuning, the reference coordinates in the first state information can be used to perform coordinate transformation or optical path compensation to maintain consistency with the coordinate reference used in the previous optical uniformity test. Polarized light can be monochromatic light of a specific wavelength or broadband polarized light. For applications requiring high power or high sensitivity, a laser polarization light source can be used in conjunction with an attenuator or aperture to avoid oversaturation or instrument damage.

[0086] In transmission-type polarized stress testing, the polarizer and analyzer are typically positioned orthogonally. When stress birefringence is present in a crystal, the transmitted light will experience additional phase delay or amplitude variation. The light intensity distribution after passing through the analyzer can be captured by a CCD / CMOS camera to form a digital image. If a rotating polarized light source or phase-shifting polarization measurement method is used, multiple frames can be captured at different angles or phase steps to obtain more complete stress birefringence information. When performing relative intensity analysis or phase delay calculation on the resulting polarized image, it is necessary to call upon environmental parameters (such as temperature and humidity) in the first state information to compensate for temperature coefficient or refractive index drift in the measurement data, thereby improving the accuracy of the quantitative stress distribution results.

[0087] In order to restore the obtained polarization state change data to the stress distribution inside the crystal, the solution can be performed based on the photoelastic principle or the phase delay calculation model. Specifically, the transmitted light intensity or phase delay value at the same pixel position can be compared with the pre-established calibration curve or reference model to infer the magnitude and direction of the local stress inside the crystal. If there are multiple frames of phase-shifted images, the least squares method, Fourier transform method or multi-angle fitting algorithm can be used to jointly solve the light intensity data of each frame. After the solution is completed, the calculated stress value is mapped in a two-dimensional or three-dimensional coordinate system to form a stress distribution image, and then the reference position in the first state information is called to align or correct the stress distribution with the physical coordinates of the crystal so that the stress distribution result is consistent with the coordinate system of the aforementioned optical uniformity detection.

[0088] Finally, the stress distribution data obtained after the above solution and registration is recorded as the first stress field data. This data can quantify the stress magnitude and distribution at different pixel locations or regions within the crystal, providing accurate stress information support for subsequent defect correlation analysis. Through the above steps, the stress birefringence characteristics of the crystal can be effectively and stably detected, helping to identify stress concentration areas and potential microcracks or structural defects.

[0089] Regarding S104 above:

[0090] In this step, the first optical path difference data and the first stress field data are aligned and analyzed in parallel within the same coordinate system to identify potential defect areas within the crystal that exhibit both optical inhomogeneity and stress anomalies. First, based on the reference position recorded in the first state information or the established alignment model, the optical path difference data and the stress field data are mapped to unified spatial coordinates or pixel coordinates to ensure that the correspondence between the refractive index anomaly and the stress intensity can be extracted from the two types of data at each point (or each pixel). If there are differences in resolution or different data point step sizes, interpolation algorithms, resampling, or fusion strategies can be used for alignment.

[0091] On this basis, gradient analysis or anomaly identification is performed on the optical path difference data to identify areas where the local refractive index changes significantly or experiences sharp jumps. Simultaneously, the stress concentration or stress gradient in the stress field data is calculated to screen for areas where stress concentration or stress mutation may occur. Pre-set thresholds, statistical judgment, or image segmentation methods can be used to identify areas with normal optical path difference and abnormal stress. High-probability defect areas are detected by overlapping the two in coordinate space. If both normal optical path difference and abnormal stress are detected in a given area, it can be considered to be at greater risk of defects or to harbor potential microcracks, impurity accumulation, or crystal structure damage.

[0092] For the above-mentioned overlapping areas, the optical path difference and stress field data are comprehensively analyzed to quantify the defect intensity and stress influence range. The defect intensity can be calculated based on the optical path difference amplitude or optical inhomogeneity, or it can be characterized by specifying the degree to which the optical path difference exceeds the background mean by a certain number of standard deviations depending on actual needs. The stress influence range can be defined by methods such as statistical stress gradient distribution or radius threshold. For example, if the stress still exceeds the set threshold within the search radius around the local stress peak, the area within this radius can be regarded as the "stress influence range of the suspected defect." Based on this result, the coordinates of each defect area are calibrated and written into the defect location information, recording the core parameters of the area such as the defect location, defect intensity, and stress influence range.

[0093] Finally, the analysis results are stored or output as defect location information, which is used in the next step for quantitative evaluation and quality determination. This comprehensive correlation analysis effectively integrates refractive index anomalies with stress concentrations, screening out crystal defect areas with higher risks or more significant impacts, thereby improving detection sensitivity and determination accuracy.

[0094] For example, a calcium fluoride crystal sample with a diameter of approximately 50 mm and a thickness of approximately 10 mm was selected and placed in a testing station. The aforementioned steps were followed to obtain first optical path difference data for characterizing the refractive index distribution and first stress field data for characterizing the stress distribution. The resolution of the detection device ensured that each sampling pixel corresponded to a physical area of ​​approximately 0.1 mm × 0.1 mm on the crystal surface. By reading the reference coordinates in the first state information, this embodiment employed bilinear interpolation during coordinate system alignment to resample the optical path difference and stress field data into a uniform 512 × 512 pixel matrix.

[0095] During the data fusion phase, a gradient calculation is first performed on the optical path difference data and a threshold value T1 is set to identify areas with a large local optical path difference change rate. In this embodiment, T1 is set to (mean + 3 times the standard deviation) based on background statistical information. Pixel positions where the optical path difference gradient exceeds T1 are marked as "normal optical path difference areas," accounting for approximately 5% of the crystal surface area. On the other hand, local stress gradient analysis is performed on the stress field data, and the stress gradient judgment standard is set with a threshold value T2. In this embodiment, T2 is set to (mean + 2 times the standard deviation). When the stress gradient exceeds T2, the pixel is considered an "abnormal stress area," accounting for approximately 8% of the crystal surface area.

[0096] After performing a logical AND operation on these two abnormal areas in a unified coordinate system, it is obtained that the overlapping area with both optical path difference and stress anomaly accounts for about 1.5%. This overlapping area can be regarded as a high-risk defect candidate area. In order to quantify the defect intensity, the optical path difference pixel values ​​of each candidate area are weighted averaged to obtain the average amplitude of the refractive index anomaly in the area; for example, in this embodiment, there are 3 independent high-risk candidate areas, and their average optical path difference amplitudes are (mean + 4.2 times the standard deviation), (mean + 5.1 times the standard deviation) and (mean + 3.9 times the standard deviation), respectively. Subsequently, in order to determine the stress influence range, the stress peak point is selected as the center in the stress anomaly area, and the stress gradient is checked pixel by pixel to see if it is still higher than T2 until the stress gradient drops below T2. This radius is defined as the stress influence radius. The stress influence radii of the three candidate areas were measured to be 3.2mm, 4.8mm and 2.7mm, respectively.

[0097] Finally, to facilitate subsequent determination and output, the center coordinates of the candidate area (provided by the registration model) are recorded as the defect location, the corresponding refractive index anomaly amplitude is considered the defect intensity, and the influence radius obtained based on stress gradient analysis is considered the stress influence range of the suspected defect, and each is stored in the defect location information. During this process, the physical coordinates of the crystal surface corresponding to each defect area are also associated in the database to facilitate downstream process identification and further processing or screening. Through this specific embodiment, it can be clearly seen how multiple steps such as data registration, gradient determination, and regional analysis are combined with the first state information to obtain more precise and accurate positioning and quantification results for calcium fluoride crystal defects.

[0098] For example, during the inspection process, since optical uniformity testing and stress birefringence testing may be performed using different optical paths, different viewing angles, or imaging systems with different resolutions, a registration model is required to accurately map the first optical path difference data and the first stress field data to a unified coordinate system. This registration model typically consists of a set of coordinate transformation relationships or transformation matrices that describe the correspondence between pixel coordinates and actual crystal surface coordinates, as well as between different inspection data sources.

[0099] In a specific example, assume that an interferometric imaging system with a resolution of 512×512 pixels is used to obtain optical path difference data, while a polarized stress camera with a resolution of 720×540 pixels is used to obtain stress distribution data. Since the resolution and field of view of the two detectors are different, the coordinates of the latter need to be transformed to align with the former. First, by placing several visible marking points (such as cross targets or tiny dots) on the inspection station or using the geometric features of the outer edge of the crystal, the pixel coordinates of these marking points under the two imaging systems are obtained; secondly, the least squares fitting or affine transformation solution method is used to calculate a 2D transformation matrix M, which converts the stress camera coordinates (u, v) to the interferometric camera coordinates (x, y), forming the following relationship:

[0100]

[0101] When the number and distribution of markers are sufficient to cover the primary detection range, further distortion correction terms can be established. For example, polynomial corrections can be added to affine or perspective transformations to compensate for nonlinear distortion caused by optical lenses or light source angle differences. Once calculated, the transformation matrix is ​​recorded in the system control module and serves as the registration model used in the present invention to unify the two types of data in the subsequent correlation analysis step.

[0102] In an embodiment, it is assumed that each pixel point (u, v) in the stress camera coordinate system is sequentially applied with the above-mentioned transformation matrix M to obtain the corresponding interference camera coordinates (x, y). If (x, y) is a non-integer pixel, the fusion value of the optical path difference data and the stress data at the same point can be obtained by bilinear interpolation, B-spline interpolation or other interpolation methods. In conjunction with the reference position, environmental parameters and other information in the first state information, the position or phase correction of the pixels with potential errors or temperature effects can be performed to ensure the accuracy and stability of the data registration. Through this registration model, the first optical path difference data and the first stress field data can be effectively aligned in a unified coordinate system, and then the refractive index anomaly and stress anomaly can be simultaneously evaluated for each pixel or coordinate point in the detection area.

[0103] Regarding S105 above:

[0104] In this step, based on the defect location information obtained from the previous correlation analysis, a quantitative assessment operation is further performed for each defect area. First, the defect location information (including the defect position, defect intensity, and the stress influence range of the suspected defect) can be imported into the quality evaluation unit or algorithm model. The model numerically scores or grades the defect parameters according to the performance requirements of the crystal in different application scenarios. For example, if calcium fluoride crystals are used in high-energy laser optical components, multiple indicators such as the optical path difference threshold and the stress gradient threshold can be set; when the optical path difference amplitude or stress concentration of the defect area exceeds a certain warning line, the system will assign a higher risk score.

[0105] During the graded assessment, it can be carried out in the following manner:

[0106] First, read the amplitude information of the defect intensity, such as how many times the optical path difference exceeds the global mean standard deviation or absolute threshold;

[0107] Second, refer to the stress influence range to determine whether the stress distribution radius or local peak stress corresponding to the defect area exceeds the established safety limit;

[0108] Third, through weighted functions or rule tables, the defect intensity and stress influence range are combined into a single score, or a comprehensive score is given based on multiple indicators.

[0109] If specific process requirements or application scenarios need to be considered (such as bands, power thresholds, etc.), additional factors can be superimposed during scoring or grading to achieve customized quality judgment.

[0110] After completing the above quantitative assessment, the system will generate a quality judgment result based on the scoring or grading results, such as labels such as "excellent", "qualified", "to be observed", and "unqualified", or reflect the overall quality risk of the crystal in the form of a numerical score. Subsequently, the quality judgment result and the specific defect parameters are output together in a test report. The report is usually presented in an electronic file or visual form, including: a defect location diagram showing the coordinate position and distribution form of each defect area; defect intensity and stress parameters, listing key values ​​such as optical path difference amplitude and stress gradient; recommended treatment plans or screening results, such as additional testing of high-risk defect areas, re-grinding and polishing, or directly excluding the crystal.

[0111] In this way, operators can intuitively understand the key defect information within the calcium fluoride crystal and make production or usage decisions based on the numerical indicators in the report, thereby significantly improving crystal quality control and the reliability of subsequent device processing or use.

[0112] As an optional implementation, the quality evaluation unit or algorithm model can be implemented by a hardware logic circuit, an embedded system or a software module (such as running on a host computer or a server), which is used to receive the optical path difference amplitude, stress parameters, spatial coordinates and other characteristics of each area in the "defect location information" and output a judgment result on the defect severity or quality grade of the calcium fluoride crystal.

[0113] For example, it may be a rule-based quality evaluation model, which is centered on pre-set evaluation rules or decision tables and can be implemented without the need for large-scale data training.

[0114] In practice, a series of grading thresholds are set, such as optical path difference amplitude thresholds D1 and D2, and stress concentration thresholds S1 and S2. If the optical path difference amplitude in a defect area exceeds D2 and the stress concentration exceeds S2, it is judged as a "high-risk defect" and the quality level is "unqualified," requiring further annealing or polishing. If only a certain threshold is exceeded, it may be classified as "acceptable" or "needs observation." Within this rule system, thresholds can be set based on different application scenarios. For example, high-energy laser applications typically have stricter upper limits for the optical path difference amplitude threshold D and stress concentration threshold S, while infrared optics may have more stringent upper limits. This rule model can quickly determine defect risk and is easy to maintain and expand. It is suitable for scenarios with limited defect data samples and clear engineering thresholds for quality indicators.

[0115] For example, a quality assessment model based on machine learning can also be used. For applications that require more flexible or multi-dimensional evaluation, supervised learning models such as multilayer perceptrons (MLPs) or decision tree ensembles (such as XGBoost and RandomForest) can be used. In this embodiment, a batch of calcium fluoride crystal samples with known quality grades or defect distribution labels can be collected, and their optical path difference data, stress distribution data, final device performance or test results (such as laser damage threshold, imaging distortion degree, etc.) can be recorded. These samples are divided into training sets and validation sets, and several feature dimensions (such as defect location coordinates, defect intensity, stress influence range, local optical path difference distribution curve, average stress gradient, etc.) are extracted as input to the machine learning model; the quality grade or defect severity is used as a label for supervised training. After training is completed, the model can predict or evaluate any newly detected crystal defect information and output a corresponding risk score or quality grade. For example, if the model output score exceeds a certain threshold, the crystal can be judged as "unqualified" and a note indicating that it needs to be replaced or reprocessed is indicated in the test report; if the score is lower, it is classified as "qualified" or "excellent". If there is enough test data and the real usage scenarios are constantly updated, feedback results can be collected continuously and the model can be updated through online learning or regular offline retraining to maintain high accuracy under a wider range of conditions.

[0116] In the above two types of examples, whether the rule-based or machine learning-based approach is adopted, the input of the model revolves around "defect location information", including optical path difference measurement, stress distribution characteristics, crystal physical coordinates, environmental information, etc., and is therefore closely related to the aforementioned steps of the present invention (especially S104). The output of the model is generally a graded label or risk score, and it can also integrate the production line requirements to formulate a multi-level screening strategy and automatically generate a test report for subsequent decision-making. Through this quality evaluation unit or algorithm model, the present invention can convert multi-dimensional defect information into intuitive quantitative evaluation results, greatly improving the efficiency and accuracy of detection.

[0117] As an optional implementation, see Figure 2 , is a flow chart of a method for obtaining first optical path difference data for characterizing a refractive index distribution provided by the present application, comprising steps S201 to S203, wherein:

[0118] S201: establishing a registration model between pixel coordinates and physical coordinates of the calcium fluoride crystal based on the reference position, and performing coordinate transformation processing on the interference fringe pattern after noise reduction processing to obtain a registered interference fringe pattern;

[0119] S202: performing a phase unwrapping algorithm on the registered interference fringe pattern to obtain phase information representing the refractive index distribution of the calcium fluoride crystal;

[0120] S203: Perform compensation calculation on the phase information based on the environmental parameters to obtain first optical path difference data.

[0121] In existing optical detection schemes, interference fringe patterns often only reflect the light and dark distribution under pixel coordinates, making it difficult to accurately map the physical coordinates of the crystal. Once the crystal size is large or the resolution of the imaging system does not match the field of view, it will cause inaccurate alignment of the refractive index distribution position. In addition, if the interference fringe unwrapping process ignores the effects of ambient temperature, humidity, etc., it may also lead to cumulative errors in phase calculations, making it impossible to truly reflect the microscopic refractive index changes inside the calcium fluoride crystal. In response to these problems, the present application further proposes to establish a registration model between pixel coordinates and physical coordinates, and cooperate with the phase compensation strategy of environmental parameters to convert the interference fringe pattern into accurate optical path difference data through three steps of coordinate transformation, phase unwrapping, and numerical correction.

[0122] In practice, a registration model can be constructed by first using the acquired reference positions to establish a mapping relationship between the interferometric imaging system and the outer edge of the crystal or several marker points. After several visible marker points or crystal edge features are determined, a coordinate transformation matrix is ​​solved using methods such as least squares fitting or perspective transformation to map each pixel to the actual position on the crystal surface. Subsequently, a coordinate transformation is performed on the interference fringe pattern that has undergone preliminary noise reduction to obtain a "registered interference fringe pattern" so that the spatial distribution of the fringe phase is consistent with the physical coordinates of the crystal.

[0123] On the basis of the registered image, the periodic winding phenomenon of the fringe phase is removed by the phase unwrapping algorithm. Common methods include branch-cut, region growing or least squares method. After the phase unwrapping is completed, targeted compensation calculations can be performed based on the records of environmental parameters (such as temperature, humidity or light source stability). For example, if the temperature rises by 1°C compared to the initial detection, the phase data can be corrected accordingly according to the refractive index temperature coefficient, or if the light source power is offset by a certain proportion compared to the initial value, the overall phase amplitude of the fringe pattern can be corrected. This process incorporates various environmental interference factors into a unified phase calculation framework and reduces phase deviation through numerical compensation. Finally, the compensated phase distribution is converted into an optical path difference value to form the first optical path difference data for characterizing the refractive index distribution of calcium fluoride crystals.

[0124] In a specific embodiment, a 512×512 pixel interferometric imaging camera can be used to capture the fringe pattern, and the interferometer performs full coverage imaging of the crystal surface field of view. By setting four visible alignment markers on the periphery of the crystal and identifying their pixel coordinates in the camera, the transformation matrix is ​​solved using affine transformation, and the pixel coordinates are mapped to the physical coordinate system of the crystal with a size of 50mm×50mm. After performing this transformation on the fringe pattern after noise reduction, Goldstein's branch-cut unwrapping algorithm is executed to obtain a preliminary phase distribution. Then, the record of the ambient temperature being approximately 0.8°C higher than that during calibration is read, and the phase value of each pixel is corrected by 0.3% according to the estimated temperature coefficient, and the optical path difference result is finally output.

[0125] This registration model, phase unwrapping, and environmental compensation method significantly resolves the difficulty in aligning interferometric imaging with the crystal's physical coordinates, as well as phase deviations caused by environmental fluctuations, resulting in a more accurate refractive index distribution. Consequently, subsequent stress testing or defect determination of calcium fluoride crystals can be perfectly aligned with stress field data from the same coordinate reference, significantly improving the reliability of defect location and quantitative assessment. This has significant engineering value for high-precision optical components and high-energy laser applications.

[0126] As an alternative implementation, see Figure 3 , is a flow chart of a method for obtaining phase information characterizing the refractive index distribution of calcium fluoride crystal provided by the present application, comprising steps S301 to S305, wherein:

[0127] S301: performing a two-dimensional phase transformation on the registered interference fringe pattern to obtain an initial wrapped phase pattern;

[0128] S302: Based on a preset phase gradient threshold, identifying a phase jump region in the initial wrapped phase image, and establishing a shear line along the phase gradient in the phase jump region;

[0129] S303: performing dewrapping processing on the phase data on both sides of the cutting line in sequence to generate a local unwrapped phase map;

[0130] S304: performing splicing and fusion on each local unwrapped phase image to obtain a complete global unwrapped phase image;

[0131] S305: performing noise reduction processing on the global unwrapped phase image to obtain phase information that ultimately characterizes the refractive index distribution of the calcium fluoride crystal.

[0132] In existing phase unwrapping algorithms, if only global least squares or simple region growing methods are relied upon, unwrapping failure or phase distortion may easily occur where the phase jump of the interference fringes is drastic. This is especially true when the calcium fluoride crystal size is large and the fringe distribution is complex. Such methods often cannot achieve both high precision and high efficiency.

[0133] Therefore, this application combines the initial phase conversion, the shear line method and the local unwrapping process, and finally performs denoising on the global unwrapped phase map to obtain a more stable and reliable refractive index distribution.

[0134] Specifically, the registered interference fringe pattern can first be subjected to a two-dimensional phase transformation, mapping the fringe brightness and darkness information into wrapped phase data. During this process, a preliminary phase estimate can be made based on the optical path geometry or fringe period. To identify phase jump regions, a phase gradient threshold can be set. The gradient levels of adjacent pixels in the initial wrapped phase image are scanned. Regions exceeding the threshold are identified as phase abrupt bands or high-gradient jump regions. Cut lines are then established around these regions to isolate the phase jump points from normal areas. Subsequently, the phase image, divided by the cut lines, undergoes local block or region-growing dewrapping. Each block is unfolded according to the principle of phase continuity, gradually transitioning the phase from the jump point to the surrounding area, generating a local unwrapped phase image. Multiple local unwrapping results can be spliced ​​and fused in coordinate space. Phase differences between adjacent regions are corrected at the splicing boundaries to form a complete global unwrapped phase image. To reduce high-frequency noise or local residual errors, a further denoising or filtering operation can be applied after the global unwrapping process, such as wavelet denoising, frequency domain filtering, or adaptive smoothing, to suppress residual fringe noise and speckle. The final phase distribution can completely preserve the low-frequency and high-frequency information of the fringes without being excessively destroyed by phase jumps.

[0135] For example, after the initial phase conversion of the registered interference fringe pattern with a size of 512×512 pixels, a phase gradient threshold T can be set to determine the local phase mutation. When it is detected that the local gradient is greater than T, a branch-cut shear line is immediately established at the outer edge of the area to separate the area from other areas to prevent invalid phase transfer. For each block after segmentation, dewrapping processing is performed step by step. When the phase difference between adjacent pixels is less than a certain acceptable threshold, the original phase extension is retained; if the threshold is exceeded, phase compensation or additional statistical judgment is performed. When splicing, the relative consistency of the block phase is guaranteed by setting a common reference pixel at the edge of the adjacent block. After obtaining the complete unwrapped phase, if it is found that high-frequency noise still exists locally, frequency domain filtering can be used to remove the strong noise frequency component, or bilateral filtering can be used to reduce spike interference, and finally the unwrapped phase image is smoothed into a global continuous phase distribution.

[0136] This method offers more stable unwrapping capabilities for complex scenarios such as multiple fringes, high-gradient jumps, and localized noise. Compared to traditional global least squares or simple region growing algorithms, it reduces the probability of large-scale fringing unwrapping failure and localized phase misalignment, significantly improving the accuracy of refractive index distribution restoration. This shear-line-based local unwrapping, followed by splicing and fusion, and noise reduction effectively addresses challenges such as localized phase distortion caused by large-scale jumps or defects in the initial wrapped phase image, thereby ensuring high-precision coupled analysis of subsequent optical path difference and stress field data.

[0137] As an optional implementation manner, the phase unwrapping algorithm further includes:

[0138] While identifying the phase jump region, extracting pixel coordinates of the stress concentration region from the first stress field data, and setting an adaptive phase gradient threshold for the corresponding phase jump region;

[0139] performing multiple iterative unwrapping processes on the phase data on both sides of the shear line in the stress concentration region to generate a local unwrapped phase map;

[0140] During the global splicing and fusion process, a local phase offset correction is performed on the unwrapped phase according to the stress distribution in the stress concentration area;

[0141] The local unwrapped phase image corrected for the local phase offset is spliced ​​and fused with the unwrapped phase images of other regions to obtain the final global phase information that characterizes the refractive index distribution of the calcium fluoride crystal.

[0142] In existing phase unwrapping processes, if a region of the crystal is particularly susceptible to stress concentration and severe fringe distortion, the typical uniform phase gradient threshold or single iteration often cannot reliably unwrap these extreme regions. To address this issue, this solution leverages the high-stress concentration region information provided by the first stress field data during phase unwrapping of the registered interference fringe pattern. Adaptive threshold adjustment and multiple iterative unwrapping are performed on this region. Furthermore, local phase offset correction is performed based on the stress distribution during global stitching to ensure a smooth transition between the high-stress region and surrounding areas.

[0143] In practice, the central extreme value of the stress field data is used as a reference point for the stress concentration region. A specific range covering this region is calculated based on the stress amplitude. For example, all pixels with a stress amplitude greater than the global mean plus two standard deviations are labeled as "high-stress regions." A higher initial threshold, G0, is assigned during phase jump detection to tolerate larger phase gradient jumps. A separate shear line is established for this high-stress region, and a branch-cut method is used to close the phase jump edge to prevent large jumps from affecting the surrounding stable areas.

[0144] After the shear lines are generated, the phase unwinding process for the high stress area can adopt a five-iteration strategy:

[0145] At the beginning of each iteration, the local phase gradient threshold G is updated in the neighborhood of the stress peak. i =G0×f(σi), where σ i represents the average stress amplitude or stress gradient calculated for the stress block during the current iteration. f(·) can be a linear or exponential function, used to dynamically adjust the phase gradient tolerance. Subsequently, the phase difference between each pixel and its neighbors is compared one by one. Pixels exceeding the updated threshold are temporarily marked as "pending verification pixels." Region growing or least squares methods are then used to detect significant phase jumps in their local neighborhood. Phase compensation is then performed or the original value is retained, as appropriate. After each iteration, the relative relationship between the stress amplitude and phase data is re-examined to determine whether the threshold should be maintained, raised, or lowered for the next iteration, until all iterations are exhausted or the rate of change of the phase difference converges to a very low level.

[0146] After completing the unwrapping of the high-stress block, a local unwrapping phase map is obtained, but there may still be phase zero drift or discontinuity bands when splicing the edges. To this end, in the global splicing and fusion stage, the directional distribution of the high-stress block in the stress field data can be referred to, and a local phase offset correction can be applied to the boundary pixels. For example, if the average phase difference detected at the edge transition exceeds a certain threshold, the offset can be calculated based on the stress peak and the surrounding stress gradient difference, so that the edge phase does not abruptly connect to the external unwrapping area. By performing similar local corrections at the junction of each high-stress block and the external stable area, the damage to the entire phase map caused by large gradient jumps can be significantly reduced.

[0147] As an optional implementation manner, performing local phase offset correction on the unwrapped phase according to the stress distribution in the stress concentration area includes:

[0148] Calculating a phase offset based on the first stress field data for the stress amplitude of each pixel in the stress concentration area;

[0149] The phase offset is superimposed on the corresponding pixel of the local unwrapped phase image to generate a corrected local unwrapped phase image.

[0150] In existing interference fringe unwrapping processes, when significant stress concentration areas exist within calcium fluoride crystals, the unwrapped phase corresponding to these areas often exhibits significant local offset or distortion, particularly at the junction with relatively stable surrounding areas, where phase abrupt shifts or misalignments can occur. This local phase discontinuity severely impacts the accuracy of subsequent refractive index distribution analysis and reduces the reliability of locating microscopic defects within the crystal. To effectively address this technical issue, in this embodiment, after performing phase unwrapping in the stress concentration area, the obtained first stress field data is further used to perform precise offset correction on the unwrapped local phase.

[0151] Specifically, based on the first stress field data obtained in the aforementioned steps, the stress amplitude of each pixel in the stress concentration area can be analyzed to calculate the corresponding local phase offset. During the specific calculation, the linear or nonlinear relationship between the stress amplitude and the refractive index is first determined based on the photoelastic effect of the crystal material and the parameters of the optical measurement system. Then, the stress field data at each pixel position is transformed to obtain a functional relationship with stress as input and phase offset as output, thereby obtaining the corresponding pixel-by-pixel phase offset. After completing the above calculation, the pixel-by-pixel phase offset is directly superimposed on the phase map that has been previously processed by local unwrapping, and the original unwrapped phase data is finely corrected in a pixel-by-pixel manner to generate a locally corrected phase distribution.

[0152] In one specific embodiment, the above correction process can be performed on an unwrapped phase image of a calcium fluoride crystal measuring 512×512 pixels. Assume that a region approximately 20 mm×20 mm in the middle of the crystal exhibits significant stress concentration and has been identified as a high-stress area with a high stress amplitude (e.g., 2.5 times the full-field average stress value). First, a quantitative model is established between stress amplitude and phase offset based on the photoelastic coefficient and crystal thickness parameters to calculate the specific phase offset for each pixel in this region. For example, the phase offset of the pixel with the highest stress amplitude at the center of the region can reach 0.45 radians, while the phase offset of pixels moving away from the center gradually decreases to zero. The calculated phase offset is then superimposed pixel by pixel on the unwrapped phase image at the corresponding location, significantly improving the existing local distortion or discontinuity and effectively eliminating the phase difference between adjacent regions.

[0153] This refined local phase offset correction significantly improves the accuracy and local continuity of the unwrapped phase in areas of high stress concentration, successfully resolving the problem of overall unwrapping failure caused by local phase distortion or faults. Furthermore, the corrected local phase map blends more naturally with the surrounding area during splicing, ultimately yielding more accurate and physically realistic crystal refractive index distribution data. This provides high-quality data support for the precise location and reliable assessment of subsequent crystal defects, demonstrating significant technological advancement and practical application value.

[0154] As an optional implementation, performing multiple iterative dewrapping processes on the phase data on both sides of the shear line in the stress concentration region to generate a local unwrapped phase map includes:

[0155] Set the iterative initial value for the initial phase distribution in the stress concentration region and define the phase continuity boundary condition at the shear line;

[0156] Based on phase continuity and stress amplitude, an iterative error evaluation function is constructed to quantify the phase difference between adjacent pixels of the current dewrapping result.

[0157] During each iteration, the phase data is adjusted in sequence along both sides of the shear line so as to gradually reduce the error evaluation function;

[0158] When the number of iterations reaches a preset upper limit or the error evaluation function is lower than a threshold, a local unwrapped phase map of the stress concentration area is output.

[0159] In conventional local unwrapping, if there is a large phase jump in the stress concentration area, a simple one-time iteration often fails to continuously unwrap the phase at the jump, and is prone to forming "faults" or "loops" on both sides of the shear line. To address this phenomenon, this application introduces multiple rounds of iterative fine-tuning in the phase image after the shear line segmentation, ensuring that each iteration can preferentially eliminate large gradient jumps along the direction of stress focus, ultimately obtaining a smooth and continuous local unwrapping phase image.

[0160] Specifically, the wrapped phase after registration and environmental compensation is first taken as the initial iteration field, and the phase continuity is locked at the shear line boundary: that is, the phase value of each pixel on the shear line remains unchanged in all iterations, thus providing a stable reference for the internal phase unwrapping. Subsequently, an error evaluation function E is constructed that takes into account both phase difference and stress intensity, and its form can be:

[0161]

[0162] Among them, i and j are the horizontal and vertical coordinate indexes of the pixels to be processed in the stress concentration area in the two-dimensional coordinate system (or pixel matrix), φ i,j is the current phase value of the pixel to be iterated, is the phase average of its four neighboring pixels, σ i,j is the stress amplitude at the pixel, α is the constant that balances the phase difference and stress weight, and Ω is the set of pixels within the stress concentration area. This design allows high-stress pixels to receive a larger phase adjustment weight during iteration.

[0163] During each iteration, each pixel to be processed within the stress concentration region is scanned sequentially, and the change in E before and after the current iteration, ΔE, is calculated. If ΔE < 0, the fitting effect has improved, and a step-by-step gradient descent strategy is used to shift the pixel phase by a small step size δφ toward the neighborhood average. If ΔE ≥ 0, the pixel is skipped, retaining its original phase. After a complete scan, the error function value is reevaluated, and the step size δφ for the next iteration is adjusted accordingly. If the iteration converges slowly, the step size is appropriately increased; otherwise, it is maintained or reduced to accelerate convergence.

[0164] When the number of iterations reaches the preset maximum number (e.g. 8 to 12 rounds) or the net error decreases ΔE for three consecutive rounds total are all below the micro threshold (e.g. 10 -4 ), the local optimal unwrapping is considered complete, and the local unwrapped phase map of this region is output. Throughout the entire process, because the boundary pixels are locked, the gradual unwrapping of the internal pixels always revolves around the shear line, avoiding phase confusion caused by improper handling of a single large jump.

[0165] Through multiple iterative de-entanglement strategies, not only can the phase be finely unfolded in the stress concentration area, but the residual error caused by large gradient jumps can also be effectively suppressed, providing a more reliable local basis for subsequent global phase splicing and refractive index distribution reconstruction.

[0166] As an optional implementation, performing multiple iterative dewrapping processes on the phase data on both sides of the shear line in the stress concentration region to generate a local unwrapped phase map further includes:

[0167] Before each iteration begins, based on the environmental parameters in the first state information, searching and loading the threshold correction rule and iteration step correction rule corresponding to the current environmental conditions, and updating the phase gradient threshold and iteration step;

[0168] The updated phase gradient threshold and iteration step size are used to perform iterative de-wrapping operations on the phase data on both sides of the shear line.

[0169] After each iteration, incrementally updating the registration model of the local unwrapped phase and the physical coordinates of the calcium fluoride crystal using the reference position in the first state information, and recording the updated registration model;

[0170] When the number of iterations reaches a preset upper limit, or the phase difference variation during the iteration process is lower than a preset threshold, a local unwrapped phase map corresponding to the stress concentration region is output.

[0171] In conventional multiple-iteration dewrapping, if the dynamic changes in environmental conditions are ignored, once the temperature, humidity or light source power shifts, the iteration may fall into local convergence or jump amplification, resulting in difficulty in convergence or decreased accuracy of the dewrapping. To this end, before each iteration begins, this embodiment first reads the environmental parameters in the first state information, such as the current temperature, relative humidity and light source output stability, and dynamically updates the phase gradient threshold and iteration step size based on the threshold correction rules and iteration step size correction rules pre-set in the experiment. For example, when the temperature at the detection site is 0.5°C higher than the calibration temperature, the original phase gradient threshold can be multiplied by 1.1 and the initial iteration step size can be increased by 10%; if the light source stability is less than 90%, the phase gradient threshold is lowered by 5% and the step size is reduced to avoid overshoot caused by light intensity fluctuations.

[0172] During the iteration process, the phase gradient threshold and iteration step size used are the updated parameters described above. Each iteration de-wrapped the phase data on both sides of the shear line according to the latest rules, and the degree of reduction in the iteration error evaluation function was calculated in real time. After a round of iteration is completed, the system uses the reference position in the first state information to incrementally correct the currently generated local phase map and the registration model of the physical coordinates of the calcium fluoride crystal. This involves fine-tuning the affine or distortion coefficients in the model to correct for registration drift caused by iterative steps and environmental influences. The updated model is then written to storage to ensure spatial alignment during the next iteration or subsequent splicing.

[0173] The entire iterative cycle ends only when the preset stop condition is met. When the number of iterations reaches the upper limit or the phase difference change is lower than the pre-set convergence threshold (for example, the average phase change per pixel is less than 0.001 radians), the iteration is stopped and the local unwrapped phase map at this time is output. This can take into account the real-time correction caused by environmental disturbances, and can also maintain high-precision matching between the local phase and the crystal physical coordinates through incremental updates of the registration model, greatly improving the stability and accuracy of phase unwrapping in the details of high-stress areas, and providing a more stable and reliable data foundation for subsequent global stitching and defect positioning.

[0174] As an optional implementation manner, the correlating analysis of the first optical path difference data and the first stress field data to generate defect location information includes:

[0175] Based on the reference position recorded in the first state information, performing spatial registration on the first optical path difference data and the first stress field data so that the two are aligned in the same coordinate system;

[0176] In the aligned data, the optical path difference gradient and stress gradient are calculated respectively, and the abnormal optical path difference gradient area and stress gradient abnormal area are identified;

[0177] Perform overlapping analysis on the optical path difference gradient abnormal area and the stress gradient abnormal area to extract candidate defect areas where both the optical path difference and stress abnormality exist in the same area;

[0178] For each candidate defect area, the average optical path difference amplitude of the candidate defect area is calculated as the defect intensity, and the stress gradient distribution range corresponding to the candidate defect area is statistically analyzed to obtain the stress influence range of the suspected defect;

[0179] The candidate defect area is marked as a defect position in the same coordinate system, and the defect location information is generated based on the defect intensity and stress influence range.

[0180] In practical applications, since the optical path difference data and stress field data often come from different imaging systems, and are each affected by measurement noise and sampling differences, if they are directly compared pixel by pixel, false positive or false negative defect marks are likely to occur. In order to solve the problems of registration and anomaly identification in such data fusion, this application first uses the reference position in the recorded first state information to perform spatial registration on the two sets of data. Specifically, the optical path difference matrix and the stress field matrix are respectively mapped to a unified crystal physical coordinate system. In the process, the previously obtained coordinate transformation matrix is ​​used for affine or perspective transformation, and then bilinear interpolation or cubic convolution interpolation is used to fill the holes to ensure that the two images are seamlessly aligned at the same resolution and field of view.

[0181] After alignment, gradient operators, such as Sobel or central difference operators, are applied to the optical path difference map and stress field map, respectively, to calculate the gradient amplitude at each pixel, thereby obtaining the "optical path difference gradient map" and "stress gradient map." Based on statistical methods, the global average value of the gradient map plus three times the standard deviation is used as the threshold to identify abnormal optical path difference gradient areas and abnormal stress gradient areas. Next, a logical AND operation is performed on these two binary areas in the same coordinate system to extract a set of candidate defect areas with both refractive index mutations and stress concentration. Morphological dilation and erosion are used to remove sporadic noise points, and connected domain analysis or region labeling algorithms are used to obtain multiple unconnected defect candidate areas.

[0182] For each candidate defect area, the system calculates the average optical path difference value of all pixels in the area from the optical path difference matrix based on the wavelength of the light source used and the conversion relationship between the phase and optical path difference, and converts it into an absolute optical path difference amplitude as the defect intensity of the area. At the same time, in the stress gradient map, the pixels in the corresponding area perform a minimum enclosing circle or distance transformation to calculate the maximum distance from the farthest pixel where the stress gradient is still above the threshold to the center of the area, which is used as the stress influence radius of the suspected defect. Using the aligned physical coordinate system, the center of mass position of each connected area is mapped to the defect position coordinates on the crystal, and the above-mentioned defect intensity and stress influence radius are packaged together into "defect location information."

[0183] In one specific embodiment, after aligning an optical path difference map (512×512 pixels with a pixel pitch of 0.1mm) with a stress field map, an average optical path difference threshold of 0.8μm and a stress gradient threshold of 5MPa / mm were calculated. A logical AND operation resulted in two candidate regions, each with 150 and 220 connected pixels, corresponding to average optical path differences of 1.15μm and 1.02μm, and stress influence radii of 3.2mm and 2.7mm, respectively. The region centroid coordinates were calibrated to (23.6mm, 18.4mm) and (12.8mm, 34.1mm), generating two defect location records. These coordinates and intensity parameters can then be directly used in subsequent comparisons and screening to guide reprocessing or screening decisions.

[0184] Through the above-mentioned multi-step refinement processing such as alignment, gradient calculation and overlap analysis, this application significantly improves the reliability of the coordinated detection of refractive index anomalies and stress anomalies, avoids misjudgment caused by a single feature, and achieves high-precision positioning and quantitative evaluation of tiny defects inside calcium fluoride crystals.

[0185] Based on the same inventive concept, the embodiments of the present application also provide a calcium fluoride crystal defect detection system corresponding to the calcium fluoride crystal defect detection method. Since the principle of solving the problem by the system in the embodiments of the present application is similar to that of the calcium fluoride crystal defect detection method in the embodiments of the present application, the implementation of the system can refer to the implementation of the method, and the repeated parts will not be repeated.

[0186] Reference Figure 4 FIG. 1 is a schematic diagram of a calcium fluoride crystal defect detection system provided by the present application, the system comprising:

[0187] The acquisition module 10 is used to obtain the calcium fluoride crystal to be detected, perform preprocessing, and obtain first state information; wherein the first state information is used to record the reference position and environmental parameters of the calcium fluoride crystal during the detection process;

[0188] A first processing module 20 is configured to perform optical uniformity detection on the calcium fluoride crystal to obtain an interference fringe pattern of the calcium fluoride crystal; perform image processing on the interference fringe pattern and obtain first optical path difference data for characterizing a refractive index distribution based on the first state information;

[0189] a second processing module 30 configured to perform stress birefringence detection on the calcium fluoride crystal to obtain polarization state change data of the calcium fluoride crystal; perform a solution process on the polarization state change data and obtain first stress field data for characterizing stress distribution based on the first state information;

[0190] A positioning module 40 is configured to perform correlation analysis on the first optical path difference data and the first stress field data to generate defect positioning information; wherein the defect positioning information includes: defect position, defect intensity, and stress influence range of the suspected defect;

[0191] The determination module 50 is configured to perform a quantitative evaluation on the defect area of ​​the calcium fluoride crystal according to the defect location information, generate a quality determination result, and output a test report based on the quality determination result.

[0192] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in this application can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

Claims

1. A method for detecting defects in calcium fluoride crystals, characterized in that: include: Obtaining a calcium fluoride crystal to be tested, performing preprocessing, and obtaining first state information; wherein the first state information is used to record a reference position and environmental parameters of the calcium fluoride crystal during the testing process; performing optical uniformity testing on the calcium fluoride crystal to obtain an interference fringe pattern of the calcium fluoride crystal; performing image processing on the interference fringe pattern and obtaining first optical path difference data for characterizing a refractive index distribution based on the first state information; Performing stress birefringence testing on the calcium fluoride crystal to obtain polarization state change data of the calcium fluoride crystal; performing a solution process on the polarization state change data and obtaining first stress field data for characterizing stress distribution based on the first state information; Correlating and analyzing the first optical path difference data with the first stress field data to generate defect location information; wherein the defect location information includes: defect location, defect intensity, and stress influence range of the suspected defect; A quantitative evaluation is performed on the defect area of ​​the calcium fluoride crystal according to the defect location information to generate a quality determination result, and a test report is output based on the quality determination result.

2. The calcium fluoride crystal defect detection method according to claim 1, characterized in that: Obtaining the first status information includes: Calibrate the coordinate position of the calcium fluoride crystal in the detection station to determine the relative reference between the calcium fluoride crystal and the detection light path to obtain a reference position; Obtain the temperature, humidity and light source stability parameters in the current detection environment to obtain environmental parameters.

3. The calcium fluoride crystal defect detection method according to claim 2, characterized in that: The performing image processing on the interference fringe pattern and obtaining first optical path difference data for characterizing the refractive index distribution based on the first state information includes: Based on the reference position, establishing a registration model between pixel coordinates and physical coordinates of the calcium fluoride crystal, and performing coordinate transformation processing on the interference fringe pattern after noise reduction processing to obtain a registered interference fringe pattern; executing a phase unwrapping algorithm on the registered interference fringe pattern to obtain phase information characterizing the refractive index distribution of the calcium fluoride crystal; Based on the environmental parameters, compensation calculation is performed on the phase information to obtain first optical path difference data.

4. The calcium fluoride crystal defect detection method according to claim 3, characterized in that: The performing of a phase unwrapping algorithm on the registered interference fringe pattern to obtain phase information characterizing the refractive index distribution of the calcium fluoride crystal includes: Performing a two-dimensional phase transformation on the registered interference fringe pattern to obtain an initial wrapped phase pattern; Based on a preset phase gradient threshold, identifying a phase jump region in the initial wrapped phase image, and establishing a shear line along the phase gradient in the phase jump region; performing dewrapping processing on the phase data on both sides of the shear line in sequence to generate a local unwrapped phase map; Perform stitching and fusion on each local unwrapped phase image to obtain a complete global unwrapped phase image; A noise reduction process is performed on the global unwrapped phase image to obtain phase information that ultimately characterizes the refractive index distribution of the calcium fluoride crystal.

5. The calcium fluoride crystal defect detection method according to claim 4, characterized in that: The phase unwrapping algorithm further includes: While identifying the phase jump region, extracting pixel coordinates of the stress concentration region from the first stress field data, and setting an adaptive phase gradient threshold for the corresponding phase jump region; performing multiple iterative unwrapping processes on the phase data on both sides of the shear line in the stress concentration region to generate a local unwrapped phase map; During the global splicing and fusion process, a local phase offset correction is performed on the unwrapped phase according to the stress distribution in the stress concentration area; The local unwrapped phase image corrected for the local phase offset is spliced ​​and fused with the unwrapped phase images of other regions to obtain the final global phase information that characterizes the refractive index distribution of the calcium fluoride crystal.

6. The calcium fluoride crystal defect detection method according to claim 5, characterized in that: The performing local phase offset correction on the unwrapped phase according to the stress distribution in the stress concentration area includes: Calculating a phase offset based on the first stress field data for the stress amplitude of each pixel in the stress concentration area; The phase offset is superimposed on the corresponding pixel of the local unwrapped phase image to generate a corrected local unwrapped phase image.

7. The calcium fluoride crystal defect detection method according to claim 5, characterized in that: The performing multiple iterative dewrapping processes on the phase data on both sides of the shear line in the stress concentration region to generate a local unwrapped phase map includes: Set the iterative initial value for the initial phase distribution in the stress concentration region and define the phase continuity boundary condition at the shear line; Based on phase continuity and stress amplitude, an iterative error evaluation function is constructed to quantify the phase difference between adjacent pixels of the current dewrapping result. During each iteration, the phase data is adjusted in sequence along both sides of the shear line so as to gradually reduce the error evaluation function; When the number of iterations reaches a preset upper limit or the error evaluation function is lower than a threshold, a local unwrapped phase map of the stress concentration area is output.

8. The calcium fluoride crystal defect detection method according to claim 7, characterized in that: The performing multiple iterative dewrapping processes on the phase data on both sides of the shear line in the stress concentration region to generate a local unwrapped phase map further comprises: Before each iteration begins, based on the environmental parameters in the first state information, searching and loading the threshold correction rule and iteration step correction rule corresponding to the current environmental conditions, and updating the phase gradient threshold and iteration step; The updated phase gradient threshold and iteration step size are used to perform iterative de-wrapping operations on the phase data on both sides of the shear line. After each iteration, incrementally updating the registration model of the local unwrapped phase and the physical coordinates of the calcium fluoride crystal using the reference position in the first state information, and recording the updated registration model; When the number of iterations reaches a preset upper limit, or the phase difference variation during the iteration process is lower than a preset threshold, a local unwrapped phase map corresponding to the stress concentration region is output.

9. The calcium fluoride crystal defect detection method according to claim 8, characterized in that: The correlating analysis of the first optical path difference data and the first stress field data to generate defect location information includes: Based on the reference position recorded in the first state information, performing spatial registration on the first optical path difference data and the first stress field data so that the two are aligned in the same coordinate system; In the aligned data, the optical path difference gradient and stress gradient are calculated respectively, and the abnormal optical path difference gradient area and stress gradient abnormal area are identified; Perform overlapping analysis on the optical path difference gradient abnormal area and the stress gradient abnormal area to extract candidate defect areas where both the optical path difference and stress abnormality exist in the same area; For each candidate defect area, the average optical path difference amplitude of the candidate defect area is calculated as the defect intensity, and the stress gradient distribution range corresponding to the candidate defect area is statistically analyzed to obtain the stress influence range of the suspected defect; The candidate defect area is marked as a defect position in the same coordinate system, and the defect location information is generated based on the defect intensity and stress influence range.

10. A calcium fluoride crystal defect detection system, used to implement the calcium fluoride crystal defect detection method according to any one of claims 1 to 9, characterized in that: include: an acquisition module, configured to acquire the calcium fluoride crystal to be detected, perform preprocessing, and obtain first state information; wherein the first state information is used to record the reference position and environmental parameters of the calcium fluoride crystal during the detection process; a first processing module, configured to perform optical uniformity detection on the calcium fluoride crystal to obtain an interference fringe pattern of the calcium fluoride crystal; perform image processing on the interference fringe pattern and obtain first optical path difference data for characterizing a refractive index distribution based on the first state information; a second processing module, configured to perform stress birefringence detection on the calcium fluoride crystal to obtain polarization state change data of the calcium fluoride crystal; perform a solution process on the polarization state change data and obtain first stress field data for characterizing stress distribution based on the first state information; a positioning module, configured to correlate and analyze the first optical path difference data with the first stress field data to generate defect positioning information; wherein the defect positioning information includes: defect position, defect intensity, and stress influence range of the suspected defect; A determination module is configured to perform a quantitative assessment of the defect area of ​​the calcium fluoride crystal according to the defect location information, generate a quality determination result, and output a test report based on the quality determination result.

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