Calcium fluoride crystal defect detection system and method

Abstract

The application provides a calcium fluoride crystal defect detection system and method, relates to the technical field of detection, and the method comprises the following steps: pretreating the crystal to determine a reference position and environmental parameters, then respectively carrying out optical uniformity detection and stress birefringence detection, obtaining interference fringe patterns and polarization state change data, and generating optical path difference data and stress field data. Through spatial registration and data correlation analysis, the area where the refractive index anomaly and the stress anomaly exist at the same time is extracted as a candidate defect area, the defect intensity and the stress influence range are quantified, and finally the quality judgment result of the crystal defect is output. The application improves the defect detection precision and reliability, and is especially suitable for high-precision calcium fluoride crystal quality control.

Description

Technical Field

[0001] This application relates to the field of detection technology, and more specifically, to a system and method for detecting defects in calcium fluoride crystals. Background Technology

[0002] Calcium fluoride (CaF2) crystal is an important optical crystal material widely used in optical lenses, window materials, and high-energy laser optical components. It features high transmittance, low refractive index dispersion, and excellent laser tolerance, exhibiting good optical performance in the ultraviolet, visible, and infrared bands. In recent years, with the increasing demands on the performance of optical components from 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 one of the major technical bottlenecks restricting the manufacturing of high-performance optical components.

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

[0004] Current technologies fall short in accurately, stably, and comprehensively detecting 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 to provide a more accurate and robust method for detecting defects in calcium fluoride crystals to improve the detection sensitivity, location accuracy, and evaluation reliability. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this application provides a system and method for detecting defects in calcium fluoride crystals.

[0006] Firstly, this application provides a method for detecting defects in calcium fluoride crystals, including:

[0007] The calcium fluoride crystal to be tested is obtained, pre-processed, and first state information is obtained; wherein, the first state information is used to record the reference position and environmental parameters of the calcium fluoride crystal during the testing process;

[0008] Optical uniformity detection is performed on the calcium fluoride crystal to obtain an interference fringe pattern of the calcium fluoride crystal; image processing is performed on the interference fringe pattern and, based on the first state information, first optical path difference data for characterizing the refractive index distribution is obtained;

[0009] Stress birefringence detection is performed on the calcium fluoride crystal to obtain polarization state change data of the calcium fluoride crystal; the polarization state change data is processed and, based on the first state information, first stress field data for characterizing stress distribution is obtained;

[0010] The first optical path difference data and the first stress field data are correlated and analyzed to generate defect location information; wherein, the defect location information includes: defect location, defect strength, and stress influence range of suspected defects;

[0011] Based on the defect location information, the defect area of ​​the calcium fluoride crystal is quantitatively evaluated, a quality judgment result is generated, and a test report is output based on the quality judgment result.

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

[0013] The coordinate position of the calcium fluoride crystal in the detection station is calibrated to determine the relative reference between the calcium fluoride crystal and the detection optical path, thereby obtaining the reference position;

[0014] The environmental parameters are obtained by acquiring the temperature, humidity, and light source stability parameters in the current detection environment.

[0015] As an optional implementation, 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, a registration model between pixel coordinates and calcium fluoride crystal physical coordinates is established, and coordinate transformation processing is performed on the noise-reduced interference fringe pattern to obtain the registered interference fringe pattern.

[0017] A phase unwrapping algorithm is performed 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, the phase information is compensated and calculated to obtain the first optical path difference data.

[0019] As an optional implementation, the step of 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] A two-dimensional phase transformation is performed on the registered interference fringe pattern to obtain an initial encapsulated phase pattern;

[0021] Based on a preset phase gradient threshold, the phase jump regions existing in the initial wrapped phase map are identified, and shear lines are established along the phase gradient in the phase jump regions;

[0022] The phase data on both sides of the shear line are sequentially dewound to generate a locally unwound phase map;

[0023] The local unwrapped phase maps are stitched and fused together to obtain the complete global unwrapped phase map;

[0024] The global unwrapped phase map is subjected to noise reduction processing to obtain the final phase information characterizing the refractive index distribution of the calcium fluoride crystal.

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

[0026] While identifying the phase transition region, the pixel coordinates of the stress concentration region are extracted from the first stress field data, and an adaptive phase gradient threshold is set for the corresponding phase transition region.

[0027] Multiple iterative unwrapping processes are performed on the phase data on both sides of the shear line within the stress concentration region to generate a locally unwrapped phase map;

[0028] During the global stitching and fusion process, local phase shift correction is performed on the unwrapped phase based on the stress distribution in the stress concentration area.

[0029] The local unwrapped phase map, which has undergone local phase shift correction, is stitched and fused with the unwrapped phase maps of other regions to obtain the final global phase information characterizing the refractive index distribution of calcium fluoride crystals.

[0030] As an optional implementation, performing local phase shift correction on the unwrapping phase based on the stress distribution in the stress concentration region includes:

[0031] Based on the first stress field data, the phase offset is calculated for the stress amplitude of each pixel in the stress concentration region;

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

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

[0034] Initial values ​​for the initial phase distribution within the stress concentration region are set for iteration, and phase continuity boundary conditions are defined 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 in the current unwrapping result.

[0036] During each iteration, the phase data is adjusted sequentially along both sides of the shear line so that the error evaluation function gradually decreases.

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

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

[0039] Before each iteration begins, based on the environmental parameters in the first state information, the threshold correction rule and iteration step size correction rule corresponding to the current environmental conditions are searched and loaded, and the phase gradient threshold and iteration step size are updated.

[0040] Using the updated phase gradient threshold and iteration step size, the phase data on both sides of the shear line are subjected to iterative unwinding operation round by round;

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

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

[0043] As an optional implementation, the step of performing correlation analysis between 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, spatial registration is performed on the first optical path difference data and the first stress field data to align them in the same coordinate system.

[0045] In the aligned data, the optical path difference gradient and stress gradient are calculated separately, and the optical path difference gradient anomaly region and stress gradient anomaly region are identified.

[0046] Overlap analysis is performed on the optical path difference gradient anomaly region and the stress gradient anomaly region to extract candidate defect regions that simultaneously exhibit optical path difference anomalies and stress anomalies within the same region.

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

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

[0049] Secondly, this application provides a calcium fluoride crystal defect detection system, including:

[0050] The acquisition module is used 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] The first processing module is used to perform optical uniformity detection on the calcium fluoride crystal, obtain the 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 the refractive index distribution based on the first state information.

[0052] The second processing module is used to perform stress birefringence detection on the calcium fluoride crystal to obtain polarization state change data of the calcium fluoride crystal; perform calculation processing on the polarization state change data and obtain first stress field data for characterizing stress distribution based on the first state information;

[0053] The positioning module is used to perform correlation analysis between the first optical path difference data and the first stress field data to generate defect positioning information; wherein, the defect positioning information includes: defect location, defect strength, and stress influence range of the suspected defect;

[0054] The judgment module is used to quantitatively evaluate the defect area of ​​the calcium fluoride crystal based on the defect location information, generate a quality judgment result, and output a test report based on the quality judgment result.

[0055] Compared with existing technologies, this application integrates the advantages of optical uniformity detection and stress birefringence detection of calcium fluoride crystals, overcoming the limitation of single detection methods that cannot simultaneously capture refractive index anomalies and stress concentration problems. By performing in-depth correlation analysis between interference fringe patterns and stress distribution data, the accuracy and reliability of defect detection are effectively improved. In addition, this application records the crystal's reference position and real-time environmental parameters before detection, and continuously applies this information for coordinate registration and environmental compensation during data analysis, thereby significantly reducing measurement errors caused by position drift, temperature and humidity changes, or light source fluctuations. At the same time, this application also proposes an improved phase unwrapping algorithm, especially for high stress concentration regions, by setting an adaptive gradient threshold and a multi-iteration strategy, effectively avoiding the problems of phase unwrapping failure or insufficient accuracy in complex regions of traditional methods. Therefore, this application can achieve higher accuracy and higher stability in locating and evaluating internal defects in crystals, which is suitable for the fine 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. Attached Figure Description

[0056] Figure 1 A flowchart 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 refractive index distribution is provided in this application;

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

[0059] Figure 4 This is a schematic diagram of the calcium fluoride crystal defect detection system provided in this application. Detailed Implementation

[0060] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0061] This application first acquires the calcium fluoride crystal to be tested, and after necessary operations such as cleaning, surface preparation, or temperature equilibration, places the crystal at the testing station. At this time, the reference position of the crystal 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. On the pre-processed crystal, an interferometer is used to perform optical uniformity testing, allowing a collimated light source or parallel beam to pass through the crystal and acquire interference fringes on the optical testing surface. The acquired fringe pattern is image-processed, and combined with the reference position and environmental parameters contained in the first state information, operations such as correction, noise filtering, and phase unwrapping are performed on the fringe pattern to obtain first optical path difference data characterizing the crystal's refractive index distribution. Subsequently, the stress birefringence characteristics of the same crystal are detected using a polarimeter. Linearly polarized or circularly polarized light is incident on the crystal, and polarization state change data is acquired through 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 registration or environmental compensation, first stress field data reflecting the internal stress distribution of the crystal can be obtained. Based on the two types of detection results, the first optical path difference data and the first stress field data are correlated and analyzed in the same coordinate system to determine the degree of anomaly in optical path difference and stress distribution in different regions, and to generate defect location information. This defect location information includes the specific location of the suspected defect area within the crystal, as well as the quantified intensity of the defect and the influence range defined by the stress gradient or stress concentration area. Finally, by comparing the defect intensity with the set quality indicators or process thresholds, the crystal defect area is further quantitatively evaluated, thereby obtaining a quality judgment result for the overall performance. A detection report is then generated for subsequent device screening, quality certification, or process optimization.

[0062] This effectively combines the characteristics of optical homogeneity and stress birefringence, enabling comprehensive and precise location and evaluation of internal defects in calcium fluoride crystals, providing reliable quality assurance for high-precision optical devices and high-energy laser applications.

[0063] See Figure 1 The diagram shows a flowchart of the calcium fluoride crystal defect detection method provided in this application. The method includes steps S101 to S105, wherein:

[0064] S101: Obtain the calcium fluoride crystal to be tested, 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 testing process;

[0065] S102: Perform optical uniformity detection on the calcium fluoride crystal to obtain the 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 the refractive index distribution based on the first state information;

[0066] S103: Perform stress birefringence detection on the calcium fluoride crystal to obtain polarization state change data of the calcium fluoride crystal; perform calculation processing on the polarization state change data and obtain first stress field data for characterizing stress distribution based on the first state information;

[0067] S104: Correlate 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 strength, and stress influence range of the suspected defect;

[0068] S105: Based on the defect location information, quantitatively evaluate the defect area of ​​the calcium fluoride crystal, generate a quality judgment result, and output a test report based on the quality judgment result.

[0069] Regarding the above S101:

[0070] In practice, the calcium fluoride crystal to be tested can be placed on a dedicated testing station. Before placement, the crystal surface is cleaned, for example, by using a lint-free cloth or ultrasonic cleaning to remove surface particles and grease. The treated calcium fluoride crystal is then fixed in a precision fixture or cassette, and the flatness and orientation of the crystal are finely adjusted using a displacement platform or alignment mechanism to maintain a set angle and distance with the preset detection optical path. This alignment process can be accomplished using a laser alignment device, a reflector locator, or a CCD vision alignment system, ensuring that the spatial relationship between the crystal and the optical system reaches the designed accuracy range.

[0071] After alignment, the reference position data of the crystal in the detection coordinate system is acquired by a measuring device, and this data is recorded in the system control module to form a reference position record. Simultaneously, 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; the humidity sensor can be a capacitive or impedance humidity probe; and the light source stability can be obtained by real-time monitoring of light power or intensity fluctuations. If necessary, preliminary light source preheating or stabilization operations can be performed during this process to ensure the light source is in optimal output condition.

[0072] The aforementioned crystal reference position data and environmental parameters are written into a database or corresponding memory through the control system, collectively referred to as the first state information. This first state information is used to compensate for or correct positional offsets and environmental disturbances in subsequent steps of optical uniformity testing and stress birefringence testing, thereby enabling testing tasks to be carried out under the same coordinate reference and controllable environment. This method achieves preprocessing and basic data acquisition of the calcium fluoride crystal, providing a guarantee of uniform accuracy and environmental consistency for subsequent measurement steps.

[0073] Furthermore, in the overall detection process of this invention, if the reference position and environmental parameters of the calcium fluoride crystal are not accurately and in real-time acquired and recorded, the measurement results will be unstable due to interference factors such as crystal position shift, temperature drift, or fluctuations in light source power during optical uniformity detection and stress birefringence detection. Especially when dealing with large-sized, high-precision calcium fluoride crystals, even slight changes in spatial orientation or temperature fluctuations can cause inconsistencies in the fringe pattern or stress measurement errors, making it difficult to obtain accurate and reliable defect detection results.

[0074] Therefore, when acquiring the first state information, additional calibration of the crystal's coordinate position in the testing station can be performed, and key parameters such as the current testing environment's temperature, humidity, and light source stability can be collected. The principle is as follows:

[0075] By establishing a clear relative reference between the crystal and the detection optical path through mechanical or optical calibration, subsequent registration and analysis of interferograms and polarization diagrams can be performed spatially based on the same coordinate reference system. By recording parameters such as ambient temperature, humidity, and light source output fluctuations in real time, corresponding compensations or corrections can be made in optical path difference calculation and stress calculation to reduce measurement deviations caused by thermal expansion, refractive index temperature coefficient, or instability of light source energy.

[0076] For example, a high-precision mechanical displacement platform and laser calibrator are set up at the detection station. After the calcium fluoride crystal is placed in the holder, the laser calibrator is turned on first. The beam reflected from the center of the crystal returns to the CCD sensor through the reflector positioner. Based on the position of the reflected light spot obtained by the CCD, the XYZ and tilt angle of the displacement platform are automatically or manually adjusted to keep the light spot within a deviation range of no more than 0.01mm from the center of the target. This position is then recorded as the reference position. In addition, a set of temperature and humidity sensors are installed at the detection station, and a light power monitor is placed at the light source end. The acquired temperature, humidity, and light source power stability values ​​are periodically written into the storage module of the control system, forming the first state information together with the "reference position".

[0077] In subsequent interferometric testing, if the temperature sensor reading shows that the ambient temperature has risen by 0.5℃ compared to the initial record, the system will use this temperature change value to correct the optical path difference data. If the light source stability drops below the set warning line, the system will prompt the operator to preheat the light source or replace the filter. Furthermore, when the polarizer and interferometer stations are not on the same platform, by placing the crystal back on the same reference plane, reading the initial "reference position" coordinates, and comparing the platform coordinate differences, it can be ensured that the crystal has a comparable coordinate basis in both measurement systems, avoiding unnecessary accumulation of spatial errors.

[0078] This solves the measurement deviation problems caused by inaccurate spatial positioning and environmental interference, making the calculation of optical path difference and stress distribution more stable. By monitoring the stability of the light source and combining it with temperature and humidity information for real-time compensation, the interference fringe pattern and polarization pattern achieve better consistency, which can significantly improve the accuracy and reliability of defect detection. When the crystal is inspected at different workstations, data visualization and subsequent defect assessment can also be achieved in the same coordinate system based on the record of the "reference position", which is especially suitable for large-size or high-precision crystals.

[0079] Regarding S102 above:

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

[0081] After obtaining the fringe pattern, image processing is performed, including basic operations such as background light subtraction, noise filtering, and fringe distortion correction. Digital filtering algorithms (such as Gaussian filtering and morphological filtering) can be used to enhance fringe clarity. If multiple frames are involved, to improve the signal-to-noise ratio, multiple frames of fringe patterns can be superimposed and averaged or subjected to temporal filtering. After processing, fringe phase information is obtained using phase unwrapping algorithms or interferometric phase extraction algorithms, and segmented correction or branch-cut processing is performed on possible phase transition regions. To ensure that the processing results match the crystal space coordinates, the reference position data from the first state information is used to register and transform the fringe pattern or phase distribution, ensuring that subsequent analysis steps can be fused 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 can be adjusted accordingly based on the temperature coefficient to reduce measurement errors caused by environmental interference. Finally, the unwrapped phase is converted into an optical path difference value, obtaining the first optical path difference data characterizing the refractive index distribution. This data can be recorded in the main control module or measurement database and serves as the basis for subsequent steps and stress distribution correlation analysis. Through the above operations, quantitative detection of the optical homogeneity of calcium fluoride crystals can be achieved, significantly improving the accuracy of identifying and locating microscopic refractive index anomalies.

[0083] Regarding the above S103:

[0084] In this step, a polarized stress detection device is used to measure the birefringence of stress in the calcium fluoride crystal. A transmission-type or reflection-type polarized stress meter is typically used, and its configuration includes a polarization source (such as linearly polarized or circularly polarized light), a polarization analyzer (such as an analyzer or a combination of a half-wave plate and analyzer), 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 acquired to obtain the original image or light intensity distribution reflecting the local stress state of the crystal.

[0085] To implement this invention, a polarizing stress meter can be configured at or near the testing station and used in conjunction with an interferometer. During testing, the calcium fluoride crystal is aligned with the optical path of the polarizing stress meter according to a predetermined reference position. If the crystal position or orientation needs fine-tuning, the reference coordinates in the first state information can be used for coordinate transformation or optical path compensation to maintain consistency with the coordinate reference of the preceding optical uniformity testing process. The polarized light can be monochromatic light of a certain wavelength or broadband polarized light; for applications requiring high power or high sensitivity, a laser polarized light source can be used, supplemented by an attenuator or aperture, to avoid oversaturation or instrument damage.

[0086] In transmission-type polarized stress detection, the polarizer and analyzer are typically placed orthogonally. When stress birefringence exists in the crystal, the transmitted light will produce additional phase delay or amplitude change. The intensity distribution of the light after passing through the analyzer can be captured by a CCD / CMOS camera to form a digital image. If a rotating polarization 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 obtained polarization images, it is necessary to call the 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 results of stress distribution.

[0087] To reconstruct the stress distribution within the crystal from the obtained polarization state change data, calculations can be performed based on photoelasticity principles or phase retardation calculation models. Specifically, for the transmitted light intensity or phase retardation value at the same pixel location, it can be compared with a pre-established calibration curve or reference model to infer the magnitude and direction of local stress within the crystal. If multiple phase-shifted images exist, algorithms such as least squares, Fourier transform, or multi-angle fitting can be used to jointly solve the light intensity data from each frame. After the calculation is completed, the calculated stress values ​​are mapped in a two-dimensional or three-dimensional coordinate system to form a stress distribution image. Then, the reference position in the first state information is called to register or correct the stress distribution with the crystal's physical coordinates, ensuring that the stress distribution result is consistent with the coordinate system used for the aforementioned optical uniformity detection.

[0088] Finally, the stress distribution data obtained after the above calculation and registration is recorded as the first stress field data. This data can quantify the stress magnitude and distribution pattern 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, which helps to identify stress concentration areas and potential microcracks or structural defects.

[0089] Regarding S104 above:

[0090] In this step, by registering and parallel analyzing the first optical path difference data and the first stress field data in the same coordinate system, potential defect regions within the crystal that simultaneously possess optical inhomogeneities and stress anomalies are identified. First, based on the reference position recorded in the first state information or the established registration model, the optical path difference data and stress field data are mapped to unified spatial coordinates or pixel coordinates, ensuring that the correspondence between refractive index anomalies and stress intensity can be extracted from both types of data at each point (or each pixel). If there are resolution differences or different data point spacings, interpolation algorithms, resampling, or fusion strategies can be used for alignment.

[0091] Based on this, gradient analysis or anomaly identification is performed on the optical path difference data to identify areas with significant local refractive index changes or abrupt jumps. Simultaneously, stress concentration or stress gradients in the stress field data are calculated to screen for segments potentially exhibiting stress concentration or abrupt stress changes. Pre-set thresholds, statistical judgments, or image segmentation methods can be used to identify optical path difference anomalous areas and stress anomaly areas, and high-probability defect regions are detected by their overlap in coordinate space. If both optical path difference anomalousness and stress anomaly are detected simultaneously in a certain area, it can be considered that this location has a higher risk of defects or potential microcracks, impurity aggregation, or crystal structure damage.

[0092] For the aforementioned overlapping areas, optical path difference and stress field data are comprehensively analyzed to quantify defect intensity and stress influence range. 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 standard deviation, depending on actual needs. The stress influence range can be defined using methods such as statistical stress gradient distribution or radius thresholds. For example, within a search radius around a local stress peak, if the stress still exceeds a set threshold, the area within that radius can be considered the "stress influence range of a 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 such as the defect location, defect intensity, and stress influence range of that area.

[0093] Finally, the above analysis results are stored or output in a unified manner to form defect location information, which is used for quantitative assessment and quality judgment in the next step. Through this comprehensive correlation analysis, refractive index anomalies and stress concentration can be effectively integrated to screen out crystal defect regions with higher risk or more significant impact, thereby improving detection sensitivity and judgment 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, placed at the testing station, and the first optical path difference data for characterizing the refractive index distribution and the first stress field data for characterizing the stress distribution were obtained according to the aforementioned steps. The resolution of the testing device is such that each sampling pixel corresponds 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 uses bilinear interpolation during coordinate system registration to resample the optical path difference data and stress field data into a uniform 512 × 512 pixel matrix.

[0095] In the data fusion stage, gradient calculation is first performed on the optical path difference data, and a threshold T1 is set to identify areas with large local optical path difference variation rates. In this embodiment, T1 is set as (mean + 3 standard deviations) based on background statistics. Pixel locations that satisfy the optical path difference gradient > T1 are marked as "optical path difference anomalous 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 a stress gradient judgment criterion is set with a threshold T2. In this embodiment, T2 is set as (mean + 2 standard deviations). When the stress gradient exceeds T2, the pixel is considered a "stress anomaly area," accounting for approximately 8% of the crystal surface area.

[0096] After performing a logical AND operation on these two anomaly regions in a unified coordinate system, an overlapping region of approximately 1.5% was obtained, exhibiting both optical path difference anomaly and stress anomaly. This overlapping region can be considered a high-risk defect candidate region. To quantify the defect intensity, a weighted average of the optical path difference pixel values ​​for each candidate region was calculated to obtain the average amplitude of the refractive index anomaly in that region. For example, in this embodiment, there are three independent high-risk candidate regions with average optical path difference amplitudes of (mean + 4.2 standard deviations), (mean + 5.1 standard deviations), and (mean + 3.9 standard deviations), respectively. Subsequently, to determine the stress influence range, the stress peak point within the stress anomaly region was selected as the center, and the stress gradient was checked pixel by pixel outwards to see if it remained higher than T2 until the stress gradient dropped below T2. This radius was defined as the stress influence radius. The stress influence radii of the three candidate regions were measured to be 3.2 mm, 4.8 mm, and 2.7 mm, respectively.

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

[0098] For example, in the detection process, since optical uniformity detection and stress birefringence detection may be performed in imaging systems with different optical paths, different viewing angles, or different resolutions, a registration model needs to be established 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, used to describe the correspondence between pixel coordinates and the actual surface coordinates of the crystal, as well as between different detection data sources.

[0099] In a specific example, assume that an interferometric imaging system with a resolution of 512×512 pixels is used to acquire optical path difference data, while a polarizing stress camera with a resolution of 720×540 pixels is used to acquire stress distribution data. Since the resolutions and fields of view of the two detectors are different, a coordinate transformation is required to align the latter with the former. First, by placing several visible markers (such as crosshairs or tiny dots) at the detection station or utilizing the geometric features of the crystal's outer edge, the pixel coordinates of these markers under both imaging systems are obtained. Second, using least-squares fitting or affine transformation methods, a 2D transformation matrix M is calculated to transform the stress camera coordinates (u,v) to the interferometric camera coordinates (x,y), resulting in the following relationship:

[0100]

[0101] When the number and distribution of markers are sufficient to cover the main detection range, distortion correction terms can be further established, such as adding polynomial correction to affine or perspective transformations to compensate for nonlinear distortion caused by angular differences in optical lenses or light sources. After calculation, the transformation matrix is ​​recorded in the system control module as the registration model of this invention, which is used to unify the two types of data in subsequent correlation analysis steps.

[0102] In this embodiment, it is assumed that each pixel (u,v) in the stress camera coordinate system is sequentially transformed using the aforementioned transformation matrix M to obtain the corresponding interferometric camera coordinates (x,y). If (x,y) is not an integer pixel, the fused value of the optical path difference data and stress data at the same point can be obtained through bilinear interpolation, B-spline interpolation, or other interpolation methods. Combined with the reference position, environmental parameters, and other information in the first state information, position or phase correction can be performed on pixels with potential errors or temperature influences, thereby ensuring the accuracy and stability of data registration. Through this registration model, effective alignment of the first optical path difference data and the first stress field data in a unified coordinate system can be achieved, thereby simultaneously evaluating refractive index anomalies and stress anomalies for each pixel or coordinate point within the detection area.

[0103] Regarding the above S105:

[0104] In this step, based on the defect location information obtained from the preceding correlation analysis, a quantitative assessment is further performed on each defect area. First, the defect location information (including defect location, defect intensity, and the stress influence range of suspected defects) can be imported into a quality evaluation unit or algorithm model. This 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 optical path difference threshold and stress gradient threshold can be set; when the optical path difference amplitude or stress concentration in the defect area exceeds a certain warning line, the system will assign a higher risk score.

[0105] The following methods can be used for tiered assessment:

[0106] First, read the magnitude 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 predetermined safety limit.

[0108] Third, by using a weighting function or rule table, the defect strength and stress influence range can be integrated into a single score, or a comprehensive score can be given based on multiple indicators.

[0109] If specific process requirements or application scenarios need to be considered (such as band, power threshold, etc.), additional factors can be added 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 like "Excellent," "Qualified," "Under Observation," and "Unqualified," or reflect the overall quality risk of the crystal in the form of a numerical score. Subsequently, the quality judgment result and specific defect parameters will be output as an inspection report. This report is usually presented in electronic file or visualization form, including: a defect location diagram showing the coordinate position and distribution of each defect area; defect strength and stress parameters, listing key values ​​such as optical path difference amplitude and stress gradient; suggested treatment plans or screening results, such as additional testing of high-risk defect areas, re-grinding and polishing, or direct exclusion of 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 the reliability of crystal quality control and subsequent device processing or use.

[0112] As an optional implementation, the quality evaluation unit or algorithm model can be implemented by hardware logic circuits, embedded systems, or software modules (such as running on a host computer or server) to receive features such as optical path difference amplitude, stress parameters, and spatial coordinates of each region in the "defect location information" and output the judgment result on the severity or quality level of the calcium fluoride crystal defect.

[0113] For example, a rule-based quality assessment model could be used, which is based on pre-defined evaluation rules or decision tables and can be implemented without large-scale data training.

[0114] In practical implementation, a series of graded 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 of a defect area exceeds D2 and the stress concentration exceeds S2, it can be judged as a "high-risk defect" with a quality level of "unacceptable," requiring further annealing or polishing. If it only exceeds a certain threshold, it may be classified as "acceptable" or "requires observation." Under this rule system, each threshold can be set according to different application scenarios. For example, high-energy laser applications usually correspond to stricter upper limits for the optical path difference amplitude threshold D and the stress concentration threshold S, while these may be relaxed for infrared optics. This rule model can quickly determine defect risk and is easy to maintain and expand, making it 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 requiring 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 employed. 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 (e.g., laser damage threshold, imaging distortion level, etc.) are recorded. These samples are divided into training 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, the model can predict or evaluate any newly detected crystal defect information and output the 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 the inspection report will indicate that it needs to be replaced or reprocessed; if the score is low, it is classified as "qualified" or "excellent." If there is enough detection data and real-world usage scenarios are constantly updated, feedback results can be continuously collected, 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 both of the above examples, regardless of whether a rule-based or machine learning approach is used, the model input revolves around "defect location information," including optical path difference measurement, stress distribution characteristics, crystal physical coordinates, and environmental information. Therefore, it is closely related to the aforementioned steps of this invention (especially S104). The model output is generally a graded label or risk score, and can also incorporate production line requirements to formulate multi-level screening strategies and automatically generate inspection reports for subsequent decision-making. Through this quality evaluation unit or algorithm model, this invention can transform multi-dimensional defect information into intuitive quantitative evaluation results, significantly improving the efficiency and accuracy of inspection.

[0117] As an optional implementation method, see [link to implementation details]. Figure 2 The flowchart provided in this application describes a method for obtaining first optical path difference data to characterize the refractive index distribution, including steps S201 to S203, wherein:

[0118] S201: Based on the reference position, establish a registration model between pixel coordinates and calcium fluoride crystal physical coordinates, and perform coordinate transformation processing on the noise-reduced interference fringe pattern to obtain the registered interference fringe pattern.

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

[0120] S203: Based on the environmental parameters, the phase information is compensated and calculated to obtain the first optical path difference data.

[0121] In existing optical detection schemes, interference fringe patterns often only reflect the brightness distribution at pixel coordinates, making it difficult to accurately map the crystal's physical coordinates. If the crystal size is large or the imaging system resolution does not match the field of view, it can lead to inaccurate alignment of the refractive index distribution. Furthermore, neglecting the influence of ambient temperature and humidity during interference fringe unwrapping can result in accumulated errors in phase calculations, failing to accurately reflect the microscopic refractive index changes within the calcium fluoride crystal. To address these issues, this application further proposes establishing a registration model between pixel coordinates and physical coordinates, combined with a phase compensation strategy for environmental parameters. Through coordinate transformation, phase unwrapping, and numerical correction, the interference fringe pattern is converted into accurate optical path difference data.

[0122] In practice, a registration model can be constructed first by using the acquired reference positions and establishing 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 its actual position on the crystal surface. Subsequently, a coordinate transformation is performed on the interferometric fringe pattern after preliminary noise reduction to obtain the "registered interferometric fringe pattern," ensuring that the spatial distribution of the fringe phase is consistent with the physical coordinates of the crystal.

[0123] Based on the registered image, the periodic entanglement of the fringe phase is removed using a phase unwrapping algorithm. Common methods include branch-cut, region growing, or least squares. After phase unwrapping, targeted compensation calculations can be performed based on recorded 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 deviates by a certain proportion from 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, reducing phase deviation through numerical compensation. Finally, the compensated phase distribution is converted into optical path difference values, forming the first optical path difference data used to characterize the refractive index distribution of calcium fluoride crystals.

[0124] In one 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. Four visible alignment markers are set at the crystal periphery, and their pixel coordinates are identified in the camera. An affine transformation is used to solve for the transformation matrix, mapping the pixel coordinates to a 50mm×50mm crystal physical coordinate system. After this transformation on the denoised fringe pattern, Goldstein's branch-cut unwrapping algorithm is executed to obtain the preliminary phase distribution. Then, records showing an ambient temperature increase of approximately 0.8°C compared to the calibration time are read, and the phase value of each pixel is corrected by 0.3% according to the estimated temperature coefficient. Finally, the optical path difference result is output.

[0125] By employing this registration model, phase unwrapping, and environmental compensation methods, the problems of inconsistent interferometric imaging and crystal physical coordinates, as well as phase deviations caused by environmental fluctuations, are significantly resolved, resulting in a more accurate refractive index distribution. Consequently, calcium fluoride crystals can achieve perfect alignment with stress field data under the same coordinate reference in subsequent stress detection or defect assessment, greatly improving the reliability of defect localization and quantitative evaluation. This has significant engineering value for high-precision optical components and high-energy laser applications.

[0126] As an optional implementation, please refer to Figure 3 The flowchart provided in this application illustrates a method for obtaining phase information characterizing the refractive index distribution of calcium fluoride crystals, including steps S301 to S305, wherein:

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

[0128] S302: Based on a preset phase gradient threshold, identify the phase jump region present in the initial wrapped phase map, and establish a shear line along the phase gradient in the phase jump region;

[0129] S303: The phase data on both sides of the shear line are sequentially dewound to generate a locally unwound phase map;

[0130] S304: Perform stitching and fusion on each local unwrapped phase map to obtain a complete global unwrapped phase map;

[0131] S305: Perform noise reduction processing on the global unwrapped phase map to obtain the final phase information characterizing the refractive index distribution of the calcium fluoride crystal.

[0132] In existing phase unwrapping algorithms, if only global least squares or simple region growth methods are relied upon, unwrapping failure or phase distortion is likely to occur at the points where the phase transition of the interference fringes is drastic. Especially when the calcium fluoride crystal is large and the fringe distribution is complex, such methods often cannot achieve both high accuracy and high efficiency.

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

[0134] Specifically, a two-dimensional phase transformation can be performed on the registered interference fringe pattern to map the fringe brightness information into wrapped phase data. During this process, preliminary phase estimation can be made based on optical path geometry or fringe period. To identify phase jump regions, a phase gradient threshold can be set, and the gradient levels of adjacent pixels in the initial wrapped phase pattern can be scanned. Regions exceeding the threshold are identified as phase jump zones or high-gradient jump regions, and shear lines are established around their peripheries to isolate the phase jump points from normal regions. Subsequently, the phase pattern divided by the shear lines is subjected to local block or region-growing unwrapping processing. Each block is unfolded according to the principle of phase continuity, allowing the phase to gradually transition from the jump point to the surrounding areas, generating a local unwrapped phase pattern. For multiple local unwrapping results, they can be stitched and fused in coordinate space. By correcting the phase difference between adjacent regions at the stitching boundary, a complete global unwrapped phase pattern is formed. To reduce high-frequency noise or local residual errors, a denoising or filtering operation can be applied after global unwrapping, such as wavelet denoising, frequency domain filtering, or adaptive smoothing, to suppress residual fringe noise and speckle. The resulting phase distribution can retain the low-frequency and high-frequency information of the stripes relatively completely without being excessively destroyed by the phase transition.

[0135] For example, after initial phase transformation of the registered interference fringe pattern with a size of 512×512 pixels, a phase gradient threshold T can be set to determine local phase abrupt changes. When a local gradient greater than T is detected, a branch-cut line is immediately established at the outer edge of the region to separate it from other regions and prevent invalid phase propagation. For each segmented block, dewinding is performed step by step. If the phase difference between adjacent pixels is less than a certain acceptable threshold, the original phase extension is retained; if it exceeds the threshold, phase compensation or additional statistical judgment is performed. During stitching, a common reference pixel is set at the edge of adjacent blocks to ensure the relative consistency of the block phase. After obtaining the complete unwrapped phase, if high-frequency noise is still found locally, frequency domain filtering can be used to remove strong noise frequency components, or bilateral filtering can be used to reduce peak interference, ultimately smoothing the unwrapped phase pattern into a globally continuous phase distribution.

[0136] This method exhibits more stable unwrapping capabilities for complex scenarios such as multiple fringes, high gradient jumps, and local noise. Compared to traditional global least squares or simple region growing algorithms, it reduces the probability of unwrapping failures in large-scale fringes and local phase misalignments, significantly improving the accuracy of refractive index distribution restoration. By employing this approach of shearing lines for local unwrapping, re-splicing, and noise reduction, it effectively addresses challenges such as large-area jumps or defects in the initial wrapped phase map causing local phase distortion, thereby ensuring high-precision coupling analysis of subsequent optical path difference and stress field data.

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

[0138] While identifying the phase transition region, the pixel coordinates of the stress concentration region are extracted from the first stress field data, and an adaptive phase gradient threshold is set for the corresponding phase transition region.

[0139] Multiple iterative unwrapping processes are performed on the phase data on both sides of the shear line within the stress concentration region to generate a locally unwrapped phase map;

[0140] During the global stitching and fusion process, local phase shift correction is performed on the unwrapped phase based on the stress distribution in the stress concentration area.

[0141] The local unwrapped phase map, which has undergone local phase shift correction, is stitched and fused with the unwrapped phase maps of other regions to obtain the final global phase information characterizing the refractive index distribution of calcium fluoride crystals.

[0142] In existing phase unwrapping procedures, if a certain region of the crystal experiences severe stress concentration and fringe distortion, the usual uniform phase gradient threshold or single iteration often fails to reliably unwrap the fringe in these extreme regions. To address this issue, this scheme fully utilizes the high-stress concentration region information provided by the first stress field data when performing phase unwrapping on the registered interference fringe pattern. It performs adaptive threshold adjustment and multiple iterations of unwrapping in this region, and incorporates local phase shift correction based on stress distribution during global stitching to ensure a smooth transition between the unwrapping results in the high-stress region and surrounding areas.

[0143] In practice, the central extremum of the stress field data can be used as a reference point for the stress concentration region. A certain range covering this region is calculated based on the stress amplitude; for example, all pixels with stress amplitudes higher than the global average plus twice the standard deviation are designated as "high-stress blocks." A higher initial threshold G0 is assigned to these high-stress blocks during phase jump detection to tolerate larger phase gradient jumps. A separate shear line is established for these high-stress blocks, and a branch-cut method is used to close and cut along the edge of the phase jump to prevent large jumps from affecting the surrounding stable region.

[0144] After the shear line is generated, a five-iteration strategy can be adopted for the phase unwinding process of the high-stress block:

[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 This represents the average stress amplitude or stress gradient calculation result of the stress block in this iteration. f(·) can be a linear or exponential function, used to dynamically correct the phase gradient tolerance. Subsequently, the phase difference between each pixel and its neighboring pixels is compared one by one. Pixels that exceed the updated threshold are temporarily marked as "pixels to be verified". Then, the phase difference is checked in its local neighborhood using region growing or least squares method to detect whether there is a large erroneous phase jump. If so, phase compensation is performed or the original value is retained. After each iteration, the relative relationship between stress amplitude and phase data is checked again to determine whether to maintain or increase / decrease the threshold in the next round, until the iteration rounds are exhausted or the rate of change of phase difference converges to an extremely low level.

[0146] After unwrapping the high-stress blocks, a local unwrapped phase map is obtained. However, phase zero-point drift or discontinuities may still exist during edge stitching. Therefore, during the global stitching and fusion stage, local phase shift correction can be applied to boundary pixels based on the directional distribution of the high-stress block in the stress field data. For example, if the average phase difference exceeds a certain threshold at the edge transition, the shift can be calculated based on the stress peak and the difference in stress gradient with the surrounding area, ensuring that the edge phase seamlessly connects to the external unwrapped region. By performing similar local corrections at the boundary between each high-stress block and the external stable region, the damage caused by large gradient jumps to the entire phase map can be significantly reduced.

[0147] As an optional implementation, performing local phase shift correction on the unwrapping phase based on the stress distribution in the stress concentration region includes:

[0148] Based on the first stress field data, the phase offset is calculated for the stress amplitude of each pixel in the stress concentration region;

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

[0150] In existing interference fringe unwrapping processes, when significant stress concentration regions exist within a calcium fluoride crystal, the unwrapped phase corresponding to these regions often exhibits noticeable local shifts or distortions, particularly at the junctions with relatively stable surrounding regions, where phase abrupt changes or misalignments are prone to occur. This local phase discontinuity severely affects the accuracy of subsequent refractive index distribution analysis and reduces the reliability of locating microscopic defects within the crystal. To effectively address this technical problem, in this embodiment, after performing phase unwrapping processing in the stress concentration regions, the obtained first stress field data is further used to perform precise shift 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 region can be analyzed to calculate the corresponding local phase shift. In the specific calculation, firstly, based on the photoelastic effect of the crystal material and the parameters of the optical measurement system, the linear or nonlinear relationship between stress amplitude and refractive index is determined. Then, the stress field data at each pixel location is transformed to obtain a function relationship with stress as input and phase shift as output, thereby obtaining the corresponding pixel-by-pixel phase shift. After completing the above calculation, this pixel-by-pixel phase shift is directly superimposed onto the previously locally unwrapped phase map, achieving fine correction of the original unwrapped phase data pixel by pixel, generating a locally corrected phase distribution.

[0152] In one specific embodiment, the above correction process can be performed on the unwrapped phase map of a calcium fluoride crystal with a size of 512×512 pixels. Assume that a region of approximately 20mm×20mm in the center of the crystal exhibits significant stress concentration, has been identified as a high-stress area with a high stress amplitude (e.g., 2.5 times the average stress value across the entire field). First, a quantization model between stress amplitude and phase offset is established based on the photoelastic coefficient and crystal thickness parameters. The specific phase offset of each pixel in this region is calculated. 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 gradually moving away from the center decreases to zero. Then, the calculated phase offset is superimposed pixel by pixel onto the unwrapped phase map at the corresponding location, significantly improving the original local distortion or discontinuity and effectively eliminating the phase difference with adjacent regions.

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

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

[0155] Initial values ​​for the initial phase distribution within the stress concentration region are set for iteration, and phase continuity boundary conditions are defined 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 in the current unwrapping result.

[0157] During each iteration, the phase data is adjusted sequentially along both sides of the shear line so that the error evaluation function gradually decreases.

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

[0159] In conventional local unwrapping, if a large phase jump exists in the stress concentration region, a simple one-time iteration often fails to continuously unfold the phase at the jump point, and is prone to forming "faults" or "loops" on both sides of the shear line. To address this phenomenon, this application introduces multi-round iterative fine correction within the phase map after shear line segmentation, ensuring that each iteration prioritizes eliminating large gradient jumps along the direction of stress focusing, and ultimately obtains a smooth and continuous local unwrapping phase map.

[0160] Specifically, the registered and environmentally compensated wrapper phase is first taken as the initial iteration field, and phase continuity is locked at the shear line boundary: that is, the phase value of each pixel on the shear line remains unchanged throughout all iterations, thus providing a stable reference for the internal phase unfolding. Subsequently, an error evaluation function E that considers both phase difference and stress intensity is constructed, which can be in the form of:

[0161]

[0162] Where i and j are the horizontal and vertical coordinate indices of the pixel to be processed in the stress concentration region in the two-dimensional coordinate system (or pixel matrix), respectively, and φ i,j Let be the current phase value of the pixel to be iterated. The phase average of its four neighboring pixels, σ i,j Let Ω be the stress amplitude at that pixel, α be a constant balancing the phase difference and stress weight, and Ω be the set of pixels within the stress concentration region. This design allows high-stress pixels to obtain a larger phase adjustment weight during iteration.

[0163] In each iteration cycle, each pixel to be processed within the stress concentration region is scanned sequentially, and the change in E, ΔE, before and after the current iteration is calculated. When ΔE < 0, it indicates an improved fit, meaning that a step-by-step gradient descent strategy is used to move the pixel's phase towards the neighborhood average by a small step size δφ. If ΔE ≥ 0, the pixel is skipped, and the original phase is retained. After one complete scan, the error function value is re-evaluated, and the step size δφ for the next round is adjusted accordingly. If the iteration convergence is slow, the step size is increased appropriately; otherwise, it is kept constant or decreased to accelerate convergence.

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

[0165] By employing a multi-iteration dewinding strategy, not only can the phase be precisely unfolded in the stress concentration region, but the residual error caused by large gradient jumps can also be effectively suppressed, providing a more reliable local basis for subsequent global phase stitching and refractive index distribution reconstruction.

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

[0167] Before each iteration begins, based on the environmental parameters in the first state information, the threshold correction rule and iteration step size correction rule corresponding to the current environmental conditions are searched and loaded, and the phase gradient threshold and iteration step size are updated.

[0168] Using the updated phase gradient threshold and iteration step size, the phase data on both sides of the shear line are subjected to iterative unwinding operation round by round;

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

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

[0171] In conventional multi-iteration unwinding, if dynamic changes in environmental conditions are ignored, deviations in temperature, humidity, or light source power can lead to phenomena such as local convergence or amplified jumps, resulting in difficulty in unwinding or decreased accuracy. Therefore, this implementation first reads environmental parameters from the first state information before each iteration, such as current temperature, relative humidity, and light source output stability. Then, it dynamically updates the phase gradient threshold and iteration step size according to pre-set threshold correction rules and iteration step size correction rules. For example, if the ambient temperature 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 increased by 10%. If the light source stability is below 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 mentioned above. In each iteration, the phase data on both sides of the shear line are unwrapped and adjusted according to the latest rules, and the degree of decrease in the iteration error evaluation function is calculated in real time. After one iteration is completed, the system uses the reference position in the first state information to perform incremental correction on the registration model of the currently generated local phase map and the physical coordinates of the calcium fluoride crystal—that is, to fine-tune the affine or distortion coefficients in the model, correct the registration drift caused by the iteration steps and environmental influences, and write the updated model into storage to ensure the spatial alignment in the next iteration or subsequent splicing.

[0173] The entire iterative loop continues until a preset stopping condition is met. Iteration stops when the number of iterations reaches the upper limit or the phase difference change falls below a pre-set convergence threshold (e.g., average phase change per pixel less than 0.001 radians), and the local unwrapped phase map is output. This approach balances real-time corrections to environmental disturbances with maintaining high-precision matching between the local phase and crystal physical coordinates through incremental updates of the registration model. This significantly improves the stability and accuracy of phase unwrapping in high-stress areas, providing a more robust and reliable data foundation for subsequent global stitching and defect localization.

[0174] As an optional implementation, the step of performing correlation analysis between 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, spatial registration is performed on the first optical path difference data and the first stress field data to align them in the same coordinate system.

[0176] In the aligned data, the optical path difference gradient and stress gradient are calculated separately, and the optical path difference gradient anomaly region and stress gradient anomaly region are identified.

[0177] Overlap analysis is performed on the optical path difference gradient anomaly region and the stress gradient anomaly region to extract candidate defect regions that simultaneously exhibit optical path difference anomalies and stress anomalies within the same region.

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

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

[0180] In practical applications, optical path difference data and stress field data often originate from different imaging systems and are affected by measurement noise and sampling differences. Direct pixel-by-pixel comparison can easily lead to false positives or false negatives. To address the challenges of registration and anomaly identification in such data fusion, this application first utilizes 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 stress field matrix are mapped to a unified crystal physical coordinate system. During this process, affine or perspective transformations are performed using the previously obtained coordinate transformation matrix. Then, bilinear interpolation or cubic convolution interpolation is used to fill in the holes, ensuring seamless alignment of the two images 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 magnitude at each pixel, thus obtaining the "optical path difference gradient map" and "stress gradient map". Based on statistical methods, the global mean of the gradient map plus three standard deviations is used as thresholds to identify optical path difference gradient anomaly regions and stress gradient anomaly regions. Next, a logical AND operation is performed on these two binarized regions in the same coordinate system to extract a set of candidate defect regions that exhibit both abrupt changes in refractive index and stress concentration. Sporadic noise is removed through morphological dilation and erosion, and connected component analysis or region labeling algorithms are used to obtain multiple unconnected candidate defect regions.

[0182] For each candidate defect region, the system calculates the average optical path difference of all pixels in that region from the optical path difference matrix based on the wavelength of the light source and the conversion relationship between phase and optical path difference, and converts it into absolute optical path difference amplitude as the defect intensity of that region. Simultaneously, in the stress gradient map, pixels within the corresponding region undergo a minimum bounding circle or distance transformation to statistically determine the maximum distance from the farthest pixel whose stress gradient is still above a threshold to the region center, which is used as the stress influence radius of the suspected defect. Using the registered physical coordinate system, the centroid position of each connected region is mapped to the defect position coordinates on the crystal, and the aforementioned defect intensity and stress influence radius are packaged together into "defect location information".

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

[0184] Through the above-mentioned registration, gradient calculation and overlap analysis and other multi-step refinement processes, this application significantly improves the reliability of the joint detection of refractive index anomalies and stress anomalies, avoids misjudgment caused by single features, and realizes high-precision positioning and quantitative evaluation of tiny defects inside calcium fluoride crystals.

[0185] Based on the same inventive concept, this application also provides a calcium fluoride crystal defect detection system corresponding to the calcium fluoride crystal defect detection method. Since the principle of the system in this application is similar to the calcium fluoride crystal defect detection method described above, the implementation of the system can refer to the implementation of the method, and the repeated parts will not be described again.

[0186] Reference Figure 4 The diagram shown is a schematic of the calcium fluoride crystal defect detection system provided in this application. The system includes:

[0187] The acquisition module 10 is used 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;

[0188] The first processing module 20 is used to perform optical uniformity detection on the calcium fluoride crystal, obtain the 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 the refractive index distribution based on the first state information.

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

[0190] The positioning module 40 is used to perform correlation analysis between the first optical path difference data and the first stress field data to generate defect positioning information; wherein, the defect positioning information includes: defect location, defect strength, and stress influence range of the suspected defect;

[0191] The judgment module 50 is used to quantitatively evaluate the defect area of ​​the calcium fluoride crystal based on the defect location information, generate a quality judgment result, and output a test report based on the quality judgment result.

[0192] Those skilled in the art will recognize that the units and algorithm steps of the various examples 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 implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art 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, The method comprises the following steps: obtaining a calcium fluoride crystal to be detected, and performing pretreatment to obtain first state information; wherein the first state information is used to record the reference position and environmental parameters of the calcium fluoride crystal in the detection process; performing optical uniformity detection 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 the refractive index distribution based on the first state information; performing stress birefringence detection on the calcium fluoride crystal to obtain polarization state change data of the calcium fluoride crystal; performing solving processing on the polarization state change data and obtaining first stress field data for characterizing the stress distribution based on the first state information; performing 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 comprises: defect position, defect intensity and stress influence range of suspected defects; performing quantitative evaluation on the defect area of the calcium fluoride crystal according to the defect positioning information, generating a quality judgment result, and outputting a detection report based on the quality judgment result; the first optical path difference data for characterizing the refractive index distribution comprises: based on the reference position, establishing a registration model between pixel coordinates and calcium fluoride crystal physical coordinates, and performing coordinate transformation processing on the interference fringe pattern after noise reduction to obtain a registered interference fringe pattern; 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; based on the environmental parameters, performing compensation calculation on the phase information to obtain the first optical path difference data; the phase information characterizing the refractive index distribution of the calcium fluoride crystal comprises: performing two-dimensional phase conversion on the registered interference fringe pattern to obtain an initial wrapped phase image; based on a preset phase gradient threshold, identifying the phase jump area existing in the initial wrapped phase image, and establishing a shear line along the phase gradient in the phase jump area; performing unwrapping processing on the phase data on both sides of the shear line in sequence to generate a local unwrapped phase image; performing splicing fusion on each local unwrapped phase image to obtain a complete global unwrapped phase image; performing noise reduction processing on the global unwrapped phase image to obtain the final phase information characterizing the refractive index distribution of the calcium fluoride crystal; the phase unwrapping algorithm comprises: while identifying the phase jump area, extracting the pixel coordinates of the stress concentration area from the first stress field data, and setting an adaptive phase gradient threshold for the corresponding phase jump area; performing multiple iteration unwrapping processing on the phase data on both sides of the shear line in the stress concentration area to generate a local unwrapped phase image; in the global splicing fusion process, according to the stress distribution of the stress concentration area, performing local phase offset correction on the unwrapped phase; splicing and fusing the local unwrapped phase image after local phase offset correction with the unwrapped phase image of other areas to obtain the global phase information characterizing the refractive index distribution of the calcium fluoride crystal; The generating the local unwrapping phase map comprises: before each iteration starts, based on the environmental parameters in the first state information, searching and loading the threshold correction rule and the iteration step correction rule corresponding to the current environmental condition, updating the phase gradient threshold value and the iteration step; using the updated phase gradient threshold value and the iteration step, performing a round of iteration unwrapping operation on the phase data on both sides of the shear line; After each iteration, the reference position in the first state information is used to incrementally update the registration model of the local unwrapping phase and the physical coordinates of the calcium fluoride crystal, and the updated registration model is recorded; when the number of iterations reaches a pre-set upper limit, or the phase difference change in the iteration process is lower than a pre-set threshold, the local unwrapping phase map corresponding to the stress concentration area is output.

2. The method of claim 1, wherein the calcium fluoride crystal is characterized by, The obtaining the first state information comprises: Calibrating 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, and obtaining the reference position; Obtaining the temperature, humidity and light source stability parameters in the current detection environment to obtain the environmental parameters.

3. The method of claim 1, wherein the calcium fluoride crystal is characterized by: The performing local phase offset correction on the unwrapping phase according to the stress distribution of the stress concentration area comprises: Based on the first stress field data, the phase offset is calculated for the stress amplitude of each pixel point in the stress concentration area; The phase offset is superimposed on the corresponding pixel of the local unwrapping phase map to generate a corrected local unwrapping phase map.

4. The method of claim 1, wherein the calcium fluoride crystal is characterized by, The performing multiple iteration unwrapping processes on the phase data on both sides of the shear line in the stress concentration area to generate a local unwrapping phase map further comprises: Setting an iteration initial value for the initial phase distribution in the stress concentration area, and defining a phase continuity boundary condition at the shear line; Based on the phase continuity and the stress amplitude, an iteration error evaluation function is constructed for quantifying the phase difference between adjacent pixels in the current unwrapping result; In each iteration process, the phase data is adjusted along both sides of the shear line in sequence, so that the error evaluation function gradually decreases; When the number of iterations reaches a pre-set upper limit or the error evaluation function is lower than a threshold, the local unwrapping phase map of the stress concentration area is output.

5. The method of claim 4, wherein the calcium fluoride crystal is characterized by: The correlating analysis of the first optical path difference data and the first stress field data to generate defect positioning information comprises: Based on the reference position recorded in the first state information, the first optical path difference data and the first stress field data are spatially registered to align them in the same coordinate system; In the aligned data, the optical path difference gradient and the stress gradient are calculated respectively, and the optical path difference gradient abnormal area and the stress gradient abnormal area are identified; The optical path difference gradient abnormal area and the stress gradient abnormal area are overlapped and analyzed to extract the candidate defect area where the optical path difference abnormality and the stress abnormality exist simultaneously; 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 counted to obtain the stress influence range of the suspected defect; The candidate defect region is marked as a defect position under the same coordinate system, and the defect positioning information is generated based on the defect intensity and the stress influence range.

6. A calcium fluoride crystal defect detection system for implementing the calcium fluoride crystal defect detection method according to any one of claims 1 to 5, characterized by, The method comprises the steps of: The acquisition module is configured to acquire a calcium fluoride crystal to be detected, and perform pretreatment to obtain first state information; the first state information is used to record a reference position and environmental parameters of the calcium fluoride crystal in a detection process; The first processing module is configured to perform optical uniformity detection on the calcium fluoride crystal, and acquire 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 representing a refractive index distribution based on the first state information; The second processing module is configured to perform stress birefringence detection on the calcium fluoride crystal, and acquire polarization state change data of the calcium fluoride crystal; perform solving processing on the polarization state change data, and obtain first stress field data for representing a stress distribution based on the first state information; The positioning module is configured to perform correlation analysis on the first optical path difference data and the first stress field data, and generate defect positioning information; the defect positioning information comprises a defect position, a defect intensity, and a stress influence range of a suspected defect; The determination module is configured to perform quantitative evaluation on a defect region of the calcium fluoride crystal according to the defect positioning information, generate a quality determination result, and output a detection report based on the quality determination result.

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