Lithium niobate waveguide defect rapid discrimination method based on depth map reconstruction

Abstract

The invention relates to the technical field of integrated chip manufacturing, in particular to a lithium niobate waveguide defect rapid discrimination method based on depth map reconstruction, and the method specifically comprises the steps: collecting a transverse equivalent response sequence; constructing a transverse coupling residual error and smoothing the transverse coupling residual error to obtain a coupling residual error image; constructing a depth suppression coefficient matrix, and performing coupling suppression on the transverse equivalent response sequence to obtain a final decoupling depth matrix; generating a primary three-dimensional depth map, extracting a depth peak map, and constructing a binary mask to form a defect candidate mask map; extracting a defect coordinate set corresponding to each waveguide, and performing depth reverse checking on each extracted candidate point to obtain a defect depth value; and calculating defect strength to obtain a final defect judgment result set. The problems that in the prior art, lithium niobate waveguides are low in detection sensitivity and high in misjudgment rate, and it is difficult to rapidly and accurately discriminate defects of all independent waveguides in mass production of lithium niobate chips are solved.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of integrated chip manufacturing, and more particularly, relates to a lithium niobate waveguide defect rapid identification method based on depth atlas reconstruction. BACKGROUND

[0002] In the manufacturing and quality inspection of lithium niobate photonic integrated chips, rapid non-destructive detection of defects in high-density parallel waveguide regions (such as couplers, beam splitters, and waveguide spacings of only 1-3 microns) faces severe challenges: the existing traditional method based on optical scattering depth scanning cannot overcome the inherent evanescent field coupling and scattered light crosstalk between waveguides, resulting in that the collected signals are actually the superposition of scattering contributions of multiple adjacent waveguides at different depths, and further causing serious transverse splicing failure and depth layer aliasing in the depth atlas; this makes it impossible to accurately attribute the scattering signals to specific waveguides in depth inversion, and also cannot effectively distinguish the real defects at deep layers from the mixed projections formed by the shallow scattering bodies of adjacent waveguides, and the transverse boundary and depth positioning of defects are seriously distorted; even if the existing improved method attempts background subtraction or simple filtering, it cannot fundamentally model and separate the complex coupling interference closely related to spatial position and depth, resulting in low detection sensitivity and high misjudgment rate, and it is difficult to meet the actual needs of rapid and accurate identification of defects in each independent waveguide in high-end lithium niobate chip mass production. SUMMARY

[0003] To solve the problems in the prior art, the purpose of the present application is to solve the above-mentioned defects, and further to provide a lithium niobate waveguide defect rapid identification method based on depth atlas reconstruction.

[0004] The application adopts the following technical solutions:

[0005] The first aspect of the application discloses a lithium niobate waveguide defect rapid identification method based on depth atlas reconstruction, as follows:

[0006] S1: Collect the original scattering intensity and dark field intensity of the waveguide signal, and perform normalization processing to obtain a transverse equivalent response sequence;

[0007] S2: Establish a transverse relative response, calculate the transverse difference between adjacent waveguides, construct the transverse coupling residual between parallel waveguides, smooth the transverse coupling residual, and obtain a coupling residual map;

[0008] S3: Based on the coupling residual map, a depth suppression coefficient matrix is constructed to suppress the coupling of the transverse equivalent response sequence, and a preliminary decoupled depth response matrix is formed;

[0009] Meanwhile, the preliminary decoupled depth response matrix is balanced to obtain a final decoupled depth matrix;

[0010] S4: generating a primary three-dimensional depth map based on the final decoupling depth matrix, extracting a depth peak value map, and constructing a binary mask to form a defect candidate mask map;

[0011] S5: extracting a defect coordinate set corresponding to each waveguide from the defect candidate mask map, and performing depth reverse lookup on each candidate point to obtain a defect depth value;

[0012] According to the defect depth value and the defect coordinate set, the defect intensity is calculated to obtain a final defect determination result set.

[0013] Preferably, S1 comprises:

[0014] S11: discretizing continuous waveguide parallel regions to form a sampling grid, and determining a set of lateral sampling points and a set of depth sampling points according to the geometric parameters of the waveguide parallel wiring area;

[0015] The geometric parameters include: a lateral starting coordinate, a waveguide spacing, a target lateral sampling spacing, a depth starting coordinate, a depth sampling spacing, a number of lateral sampling points, and a number of depth sampling points;

[0016] S12: based on the set of lateral sampling points and the set of depth sampling points, analyzing the measured photon count value and the dark field count to obtain an original scattering intensity and a dark field intensity;

[0017] S13: normalizing the original scattering intensity, and then generating a lateral equivalent response sequence in combination with the dark field intensity, and performing truncation processing on the lateral equivalent response sequence.

[0018] Preferably, S2 comprises:

[0019] S21: based on the lateral equivalent response sequence, averaging the responses of all lateral sampling positions at each depth sampling point to obtain a depth reference response, calculating the offset of each lateral position according to the depth reference response to obtain a lateral relative response;

[0020] S22: based on the lateral relative response, performing difference calculation on the responses between adjacent two lateral sampling points at each depth sampling point to obtain a lateral difference component;

[0021] S23: constructing a lateral coupling residual map according to the lateral difference component, and performing upper limit truncation processing on the lateral coupling residual map;

[0022] S24: performing smoothing processing on the lateral coupling residual map in the depth direction to obtain a smoothed coupling residual map.

[0023] Preferably, S3 comprises:

[0024] S31: Normalization and truncation are performed on the coupling residual map, the processed coupling residual map is mapped to a coupling coefficient in the interval of 0-1 to obtain a transverse coupling coefficient distribution;

[0025] S32: According to the set coupling suppression weight constant, a deep suppression coefficient matrix with the same dimension as the transverse coupling coefficient distribution is constructed, and the deep suppression coefficient matrix is subjected to lower limit truncation processing.

[0026] S33: According to the deep suppression coefficient matrix, the transverse equivalent response sequence is subjected to coupling suppression to obtain a preliminary decoupled depth response matrix.

[0027] S34: Based on the preliminary decoupled depth response matrix and the transverse equivalent response sequence, the calculated depth layer energy correction coefficient is applied to each coordinate point to obtain a final decoupled depth matrix.

[0028] Preferably, S4 comprises:

[0029] S41: Based on the final decoupled depth matrix, a primary three-dimensional depth map is constructed by introducing a depth mapping coefficient and an equidistant sampling coordinate in the waveguide longitudinal direction.

[0030] S42: The primary three-dimensional depth map is subjected to normalization processing and contrast enhancement processing to obtain a normalized and contrast-enhanced three-dimensional depth map.

[0031] S43: By scanning the depth direction of the normalized three-dimensional depth map, the maximum depth response value of each transverse-longitudinal point is extracted, and after smoothing processing, a depth peak value map is obtained.

[0032] S44: Based on the depth peak value map and a preset defect threshold, a binary mask is constructed, and after connectivity checking and isolated point suppression processing, a defect candidate mask map is formed.

[0033] Preferably, S5 comprises:

[0034] S51: Extracting a defect coordinate set corresponding to each waveguide from the defect candidate mask map.

[0035] S52: Extracting each candidate point in the defect coordinate set, performing depth reverse lookup on each candidate point, and performing weighted average processing to obtain a defect depth value.

[0036] S53: Calculating the defect intensity according to the defect depth value and the defect coordinate set.

[0037] Synchronizing to form a final defect judgment result set.

[0038] The second aspect of the present application discloses a terminal comprising a processor and a storage medium; characterized in that:

[0039] The storage medium is used to store instructions.

[0040] The processor is used to operate according to the instructions to perform the steps of the method of the first aspect.

[0041] The third aspect of the application discloses a computer-readable storage medium, which stores a computer program, and the program is executed by a processor to realize the steps of the method of the first aspect.

[0042] The application has the following advantages compared with the prior art.

[0043] 1. The application realizes high-precision depth dimension decoupling and defect positioning. By smoothing the depth direction of the coupling residual and constructing the decoupling depth matrix, the superimposed scattering signals from different waveguides and different depths that are difficult to distinguish in traditional methods can be effectively separated, so that the accurate depth layer information of each independent defect is clearly presented in the reconstructed three-dimensional depth map, and the depth aliasing problem is overcome.

[0044] 2. The application greatly enhances the lateral recognition and attribution ability of defects. Based on the binary mask generated by the depth peak value graph and the subsequent waveguide attribution algorithm, the extracted defect candidate region can be accurately separated from the coupling background, and accurate attribution can be performed according to the lateral coordinates and the preset waveguide center position, so that the problem of "lateral splicing failure" of defect signals and the inability to determine the specific attribution waveguide when multiple waveguides are arranged side by side is solved, and the lateral boundary sketching and waveguide-level positioning of defects are realized.

[0045] 3. The application realizes rapid and quantitative defect evaluation. Through the defect depth backtracking and intensity calculation process, the final output judgment result set not only contains the accurate waveguide number where the defect is located, but also gives multiple quantitative parameters such as average depth, lateral influence range and normalized intensity, forming a complete and rapid discrimination system for multi-dimensional characteristics of defects, so that the method can be directly applied to the production line quality inspection, and realizes efficient and reliable non-destructive detection and classification of defects in high-density waveguide regions of lithium niobate integrated optical chips. BRIEF DESCRIPTION OF DRAWINGS

[0046] Figure 1 It is a flowchart of the lithium niobate waveguide defect rapid discrimination method based on depth map reconstruction of the application. DETAILED DESCRIPTION

[0047] In order to make the above-mentioned purposes, features and advantages of the application more obvious and easy to understand, the specific embodiments of the application will be described in detail below with reference to the drawings of the specification.

[0048] In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application. However, it will be appreciated that the present application can be practiced in a variety of ways beyond the specifics set forth herein, which can be practiced in any number of manners without departing from the spirit of the application. These and other variations are possible and can be made by those skilled in the art in view of the teachings herein, and the scope of the present application should not be limited to the details given herein.

[0049] Secondly, the "one embodiment" or "embodiment" referred to herein means a specific feature, structure or characteristic that can be included in at least one implementation of the present application. "In one embodiment" appearing in different places in the specification does not mean the same embodiment, nor is it an embodiment that is independent or alternative to other embodiments.

[0050] Embodiment I:

[0051] As shown in Figure 1 , the lithium niobate waveguide defect rapid identification method based on depth atlas reconstruction in the embodiment of the present application, as shown in Figure 1 , includes the following specific steps:

[0052] S1: Collect the original scattering intensity and dark field intensity of the waveguide signal, and perform normalization processing to obtain a transverse equivalent response sequence;

[0053] S1 includes:

[0054] S11: Discretize the continuous waveguide parallel region to form a sampling grid, and determine a transverse sampling point set and a depth sampling point set according to the geometric parameters of the waveguide parallel wiring region;

[0055] The geometric parameters include: a transverse starting coordinate , a waveguide spacing , a target transverse sampling spacing , a depth starting coordinate , a depth sampling spacing , a number of transverse sampling points , and a number of depth sampling points ;

[0056] Exemplarily, in the present embodiment, the value range of the transverse starting coordinate is 0.0-1000.0; the value range of the waveguide spacing is 1.0-3.0; the value range of the target transverse sampling spacing is 0.1-0.5; the value range of the depth starting coordinate is 0.0-20.2; the value range of the depth sampling spacing is 0.05-0.5; the number of transverse sampling points is an integer, and the value range thereof is 50-200; the number of depth sampling points is an integer, and the value range of the integer is 50-300;

[0057] The set of lateral sampling points is specifically: along the lateral direction of the multi-waveguide parallel wiring, according to the lateral starting coordinate , the target lateral sampling interval and the number of lateral sampling points , the i-th lateral sampling point coordinate is calculated as:

[0058] ; wherein, is the i-th lateral sampling point coordinate; k is the index of the lateral sampling point, and it should be noted that in the embodiment, the number of lateral sampling points is 1-K; It should be noted that the target lateral sampling interval

[0059] satisfies , so as to ensure that there is at least one independent sampling point between every two waveguides; The set of depth sampling points is specifically: in the depth direction, according to the depth starting coordinate

[0060] , the depth sampling interval and the number of depth sampling points , the i-th depth sampling point coordinate is calculated as:

[0061] ; wherein, is the i-th depth sampling point coordinate; i is the index of the depth sampling point, and it should be noted that in the embodiment, the number of depth sampling points is 1-I;

[0062] Meanwhile, all the lateral sampling points and the depth sampling points are traversed to form the set of lateral sampling points and the set of depth sampling points ;

[0063] It should be noted that the depth sampling interval ensures that at least 5-10 depth sampling points are covered in the typical thickness range of the defect;

[0064] S12: based on the set of lateral sampling points and the set of depth sampling points, the measured photon counting value and the dark field counting are analyzed to obtain the original scattering intensity and the dark field intensity;

[0065] Exemplarily, in the embodiment, at each lateral sampling point coordinate , the position of the scanning light spot is adjusted correspondingly, so that the center of the light spot is aligned with , and at the position, by adjusting the focal point position or the sampling depth of the detector, at each depth sampling point coordinate ​​Scattering measurement is performed in the vicinity to obtain a photon count value ;

[0066] In the condition of turning off the laser, scattering measurement is performed under a single-point exposure time to obtain a dark-field count ;

[0067] The original scattering intensity is specifically: ; The dark-field intensity is specifically: the dark-field count is divided by the single-point exposure time to obtain the dark-field intensity ; It should be noted that, in the embodiment, the single-point exposure time is set by the acquisition software; It should also be noted that, in the embodiment, S12 aims to convert the optical scattering information on the spatial grid into quantifiable intensity data, to provide a basis for subsequent construction of a comparable lateral response sequence, and to weaken the interference of the system background on the multi-waveguide coupling analysis through dark-field subtraction; S13: normalize the original scattering intensity, then generate a lateral equivalent response sequence in combination with the dark-field intensity, and perform truncation processing on the lateral equivalent response sequence.

[0068] Exemplarily, in the embodiment, the lateral equivalent response sequence is specifically: ; wherein, represents a relative scattering response at a coordinate ; is the original scattering intensity; is the dark-field intensity; is a reference intensity, and it should be noted that, in the embodiment, the average scattering intensity of a defect-free standard waveguide under the same working condition is taken as the reference intensity, and the value range is greater than zero;

[0069] Then, all coordinates are traversed to obtain a lateral equivalent response sequence;

[0070] According to a preset upper limit response value and a lower limit value 0 , truncation is performed:

[0071] The smaller value between and is taken as the final lateral equivalent response sequence output ;

[0072] It should be noted that in the embodiment, S13 aims to map the original scattering data to a lateral equivalent response sequence, which on one hand maintains the actual scattering difference between the multi-waveguides, and on the other hand eliminates the system-level dimensional difference;

[0073] S2: establishing a lateral relative response, constructing a lateral coupling residual between the parallel waveguides by calculating a lateral difference between adjacent waveguides, smoothing the lateral coupling residual, and obtaining a coupling residual map;

[0074] S2 includes:

[0075] S21: based on the lateral equivalent response sequence, averaging the responses of all lateral sampling positions at each depth sampling point to obtain a depth reference response, calculating the offset of each lateral position according to the depth reference response, and obtaining a lateral relative response;

[0076] Exemplarily, in the embodiment, an acquisition strategy of a depth reference response is provided, and specifically: ; wherein, is the depth reference response, represents the average response of all parallel waveguides at the depth sampling point , and aims to represent the overall background scattering level of the depth layer;

[0077] An acquisition strategy of a lateral relative response is also provided, and specifically: ; wherein, is the lateral relative response, represents the relative response value at the coordinate , and it should be noted that in the embodiment, a positive value of indicates scattering stronger than the average level, and a negative value indicates scattering weaker than the average level;

[0078] S22: based on the lateral relative response, performing difference calculation on the responses between adjacent two lateral sampling points at each depth sampling point to obtain a lateral difference;

[0079] Exemplarily, in the embodiment, an acquisition strategy of a lateral difference is provided, and specifically: ; wherein, represents the lateral relative response at the next lateral position at the same depth sampling point ; is the lateral relative response;

[0080] For the boundary point , the is set to 0 or copied in a manner;

[0081] It should be noted that in the embodiment, the transverse difference component The larger the value, the stronger the response difference between the two adjacent sampling positions at the depth, reflecting more significant transverse structural discontinuity;

[0082] S23: Construct a transverse coupling residual map according to the transverse difference component, and perform upper limit truncation processing on the transverse coupling residual map;

[0083] Exemplarily, in the embodiment, an acquisition strategy of a transverse coupling residual value is provided, specifically: ; Wherein, represents the transverse coupling residual value at the coordinate ; is a coupling scaling coefficient, used to adjust the numerical range of the residual according to the system calibration result; is the transverse difference component; represents the response difference value between adjacent waveguides;

[0084] Traverse all coordinates to obtain a transverse coupling residual map ;

[0085] According to the preset allowed maximum residual intensity , the transverse coupling residual map is upper limited and truncated:

[0086] The smaller value between the transverse coupling residual map and the allowed maximum residual intensity is taken as the new transverse coupling residual map output;

[0087] It should be noted that in the embodiment, S23 converts the difference component between adjacent waveguides into a transverse coupling residual map, and limits the numerical range thereof, so that the coupling strong area and the coupling weak area can be more intuitively distinguished during subsequent smoothing and feature extraction in the depth direction;

[0088] S24: Smooth the transverse coupling residual map in the depth direction to obtain a smoothed coupling residual map.

[0089] Exemplarily, in the embodiment, the smoothing processing of the transverse coupling residual map is specifically: ; Wherein, the smoothed coupling residual graph; representing the coupling residual value at the coordinate representing the coupling residual value at the coordinate representing the coupling residual value at the coordinate representing the coupling residual value at the coordinate

[0090] It should be noted that in the present embodiment, the boundary points and are obtained by copying adjacent points;

[0091] It should be further noted that in the present embodiment, S34 converts the lateral coupling residual graph into a stable lateral coupling residual graph, which not only preserves the spatial distribution characteristics of the crosstalk between multiple waveguides, but also reduces the influence of random fluctuations;

[0092] S3: based on the coupling residual graph, constructing a depth suppression coefficient matrix, coupling suppressing the lateral equivalent response sequence to form a preliminary decoupled depth response matrix;

[0093] Meanwhile, the preliminary decoupled depth response matrix is balanced to obtain a final decoupled depth matrix;

[0094] S3 includes:

[0095] S31: performing normalization and truncation processing on the coupling residual graph, mapping the processed coupling residual graph into a coupling coefficient in the interval of 0-1 to obtain a lateral coupling coefficient distribution;

[0096] Exemplarily, in the present embodiment, the normalization processing on the coupling residual graph is specifically: ;

[0097] the normalized coupling residual graph, used to represent the relative coupling strength at the coordinate ; is a reference residual value, it should be noted that in the present embodiment, is obtained according to the statistical quantity of the coupling residual graph ;

[0098] According to the preset upper limit constant , the normalized coupling residual graph is upper truncated:

[0099] The smaller value between the normalized coupling residual graph and the upper limit constant is taken as the final coupling residual graph output;

[0100] The lateral coupling coefficient distribution is specifically:

[0101] ; wherein, For the transverse coupling coefficient distribution, it is to be noted that in the present embodiment, the transverse coupling coefficient distribution has a value range of 0-1, and it is to be further noted that the closer to 1 indicates that the transverse coupling at the position is stronger, and the closer to 0 indicates that the coupling is weaker;

[0102] S32: According to the set coupling suppression weight constant, a depth suppression coefficient matrix with the same dimension as the transverse coupling coefficient distribution is constructed, and the lower limit truncation processing is performed on the depth suppression coefficient matrix.

[0103] It is to be noted that in the present embodiment, the coupling suppression weight constant has a value range of 0.3-0.9;

[0104] Exemplarily, in the present embodiment, the depth suppression coefficient matrix is specifically:

[0105] It is to be noted that in the present embodiment, the depth suppression coefficient matrix has a value range of to 1; when is close to 1, is close to , indicating strong suppression; when is close to 0, is close to 1, indicating almost no suppression;

[0106] The lower limit constant is set at the same time, and the lower limit truncation is performed on :

[0107] The smaller value between the depth suppression coefficient matrix and the lower limit constant is taken as the final depth suppression coefficient matrix output;

[0108] It is to be further noted that in the present embodiment, S32 aims to map the transverse coupling coefficient distribution to a specific depth suppression coefficient matrix, and construct a depth response reduction template that changes adaptively with the coupling strength in space;

[0109] S33: According to the depth suppression coefficient matrix, the coupling suppression is performed on the transverse equivalent response sequence to obtain a preliminary decoupled depth response matrix;

[0110] Exemplarily, in the present embodiment, the preliminary decoupled depth response matrix is specifically:

[0111] At each coordinate , the transverse equivalent response sequence is multiplied by the corresponding suppression coefficient matrix​ multiplying, a preliminary decoupling depth response matrix is obtained ;

[0112] wherein, is a preliminary decoupling depth response matrix, representing a preliminary correction value at coordinates ;

[0113] It should be noted that when is close to 1, it indicates that the coupling at this position is weak, and the corrected response is close to the original response; when is close to , it indicates that the coupling at this position is strong, and the corrected response will be significantly suppressed;

[0114] It should also be noted that in the embodiment, S33 realizes the transition from discovering coupling problems to weakening the coupling effect, so that the deep defect signal is partially highlighted from the background in the multi-waveguide strong coupling area.

[0115] S34: Based on the preliminary decoupling depth response matrix and the transverse equivalent response sequence, the calculated depth layer energy correction coefficient is applied to each coordinate point to obtain the final decoupling depth matrix.

[0116] Exemplarily, in the embodiment, a strategy for obtaining a depth layer energy correction coefficient is provided, specifically:

[0117] First, the average value of the transverse equivalent response sequence at each depth is calculated , specifically:

[0118] ; wherein, is the transverse equivalent response;

[0119] Then, the average value of the preliminary decoupling response sequence at the same depth is calculated , specifically: ; wherein, is the preliminary decoupling response sequence;

[0120] The depth layer energy correction coefficient is specifically: ; wherein, is a small constant to prevent the denominator from being zero, and it should be noted that in the embodiment, the value of ranges from to ;

[0121] The final decoupling depth matrix is specifically: ; wherein, for the final decoupling depth response value at coordinates ;

[0122] It should be further noted that in the embodiment, S34 suppresses the contribution of the local coupling serious area within a reasonable range while keeping the overall energy of each depth layer similar to the original state, thereby forming the final decoupling depth matrix with overall energy comparability and local crosstalk suppression capability;

[0123] S4: generating a primary three-dimensional depth atlas based on the final decoupling depth matrix, extracting a depth peak value map, and constructing a binary mask to form a defect candidate mask map;

[0124] S4 includes:

[0125] S41: constructing a primary three-dimensional depth atlas based on the final decoupling depth matrix by introducing a depth mapping coefficient and an equidistant sampling coordinate in the longitudinal direction of the waveguide;

[0126] It should be noted that in the embodiment, the depth mapping coefficient is obtained from experimental calibration according to the film thickness, light penetration depth, and waveguide mode distribution, and the value range is 0.1-1.0; the equidistant sampling coordinate in the longitudinal direction of the waveguide has a value range of 1-J;

[0127] Exemplarily, in the embodiment, the primary three-dimensional depth atlas is specifically: ; wherein, is the primary three-dimensional depth atlas, representing a primary depth atlas value in a three-dimensional space ; is the final decoupling depth matrix, representing a final decoupling depth response value at coordinates ;

[0128] It should be further noted that since the waveguide has a stable structure along the longitudinal direction, the equidistant sampling coordinate is copied or interpolated in the dimension, so that the atlas forms a three-dimensional structure;

[0129] S42: performing normalization processing and contrast enhancement processing on the primary three-dimensional depth atlas to obtain a normalized and contrast-enhanced three-dimensional depth atlas;

[0130] Exemplarily, in the embodiment, the entire atlas data is scanned and its extreme values are recorded to obtain the maximum value and the minimum value of the atlas;

[0131] The normalization of the primary three-dimensional depth map is specifically as follows: ; wherein, To prevent the denominator from being zero, it should be noted that in the present embodiment, The value range of is ;

[0132] The contrast enhancement of the primary three-dimensional depth map is specifically as follows: ; wherein, is the normalized and contrast-enhanced three-dimensional depth map, is a nonlinear contrast coefficient, it should be noted that in the present embodiment, The value range of

[0133] It should be further noted that in the present embodiment, S42 unifies the value range of the primary three-dimensional depth map, eliminates the difference in absolute value, and makes the defect area more prominent through contrast enhancement;

[0134] S43: By scanning the depth direction of the normalized three-dimensional depth map, the maximum depth response value of each horizontal-longitudinal point is extracted, and after smoothing, a depth peak value map is obtained.

[0135] Exemplarily, in the present embodiment, the maximum depth response value is specifically as follows: ;

[0136] The smoothing coefficient is set, and then depth neighborhood averaging is used for smoothing, specifically as follows: ; wherein, is the depth peak value map, representing the maximum value of the normalized three-dimensional depth map in all depth layers at each horizontal-longitudinal point ; is the depth peak value of the previous horizontal point , the current equidistant sampling coordinate ; is the depth peak value of the next horizontal point , the current equidistant sampling coordinate ; is the smoothing coefficient, it should be noted that in the present embodiment, The value range of

[0137] It should be noted that the smoothing formula is used to stabilize lateral continuity, so that the defect area presents a continuous peak band.

[0138] S44: Based on the depth peak map and the preset defect threshold, a binary mask is constructed, and after connectivity checks and isolated point suppression, a defect candidate mask map is formed.

[0139] For example, in this embodiment, the defect threshold The value range is 0.2-0.6;

[0140] The binarization mask is specifically: ; Among them, if If the determination point is a potential defect point, it is marked as 1 in the mask image; if If the value is zero, then the point is considered a normal region and marked as 0.

[0141] If there are consecutive 1s in the neighborhood of any point, then retain that point;

[0142] If there are no consecutive 1s in the neighborhood of any point, i.e. it is an isolated point, then the isolated point is suppressed.

[0143] It should be noted that, in this embodiment, S44 aims to effectively extract continuous peak regions from the three-dimensional depth map, so that the defect region can show its location and lateral range on the two-dimensional plane.

[0144] S5: Extract the set of defect coordinates corresponding to each waveguide from the defect candidate mask image, and perform depth lookup on each extracted candidate point to obtain the defect depth value;

[0145] Based on the defect depth value and the defect coordinate set, the defect strength is calculated to obtain the final defect judgment result set.

[0146] S5 includes:

[0147] S51: Extract the set of defect coordinates corresponding to each waveguide from the defect candidate mask image.

[0148] For example, in this embodiment, the lateral center position of each waveguide is preset as the waveguide center coordinate. It should be noted that m takes values ​​from 1 to M, and the spacing is... ;

[0149] Then set the horizontal attribution tolerance. Ninja range It should be noted that, in this embodiment, the lateral attribution tolerance range... The range of values ​​is ;

[0150] The defect coordinate set corresponding to each waveguide is specifically: ; The defect candidate point coordinate set of the mth waveguide;

[0151] If the center points of multiple waveguides overlap, the waveguide with the smallest distance is taken as the attribution object for attribution processing;

[0152] It should be further explained that in the embodiment, S51 aims to map the two-dimensional mask area back to the specific waveguide, realize preliminary defect waveguide separation, and get rid of the aliasing problem caused by parallel waveguide coupling;

[0153] S52: Extract each candidate point in the defect coordinate set, perform depth backtracking on each candidate point, and perform weighted average processing to obtain the defect depth value.

[0154] Exemplarily, in the embodiment, the depth backtracking on each candidate point is specifically: ; Wherein, The defect depth sequence of the mth waveguide contains the depth peak position corresponding to each defect candidate point on the waveguide; The normalized and contrast-enhanced three-dimensional depth map;

[0155] If a waveguide corresponds to multiple candidate points, then Also contains multiple depth values;

[0156] The weighted average processing is specifically: ; wherein, The final defect depth value after weighted average processing; The preset weight coefficient, it should be noted that in the embodiment, The value range of is 0.1-1.0;

[0157] It should be further explained that in the embodiment, S52 realizes the depth-level defect positioning of the independent waveguide by accurately positioning the depth peak to the specific depth layer;

[0158] S53: Calculate the defect intensity according to the defect depth value and the defect coordinate set;

[0159] Synchronize to form the final defect judgment result set.

[0160] Exemplarily, in the embodiment, the defect intensity Specifically, ; wherein, is the defect strength of the mth waveguide; represents the number of candidate points, and the more the number, the larger the lateral size of the defect; is the final defect depth value after weighted averaging;

[0161] arrange the defect depth value , the lateral width of the defect and the defect strength into a final defect determination result set output.

[0162] Embodiment Two:

[0163] The embodiment provides an electronic device, comprising a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0164] The processor executes the above-mentioned lithium niobate waveguide defect rapid identification method based on depth atlas reconstruction by calling the computer program stored in the memory.

[0165] The electronic device can have great differences due to different configurations or performances, and can include one or more processors (Central Processing Units, CPUs) and one or more memories, wherein the memory stores at least one computer program, which is loaded and executed by the processor to realize the above-mentioned lithium niobate waveguide defect rapid identification method based on depth atlas reconstruction provided by the method embodiment. The electronic device can also include other components for realizing device functions, for example, the electronic device can also have a wired or wireless network interface and an input and output interface and other components to input and output data. This embodiment will not be described here.

[0166] Embodiment Three:

[0167] The embodiment provides a computer readable storage medium, which stores an erasable computer program;

[0168] When the computer program runs on the computer device, the computer device executes the above-mentioned lithium niobate waveguide defect rapid identification method based on depth atlas reconstruction.

[0169] For example, the computer readable storage medium can be a read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory, RAM), a read-only optical disc (Compact Disc Read-Only Memory, CD-ROM), a magnetic tape, a floppy disk and an optical data storage device, etc.

[0170] It should be understood that the magnitude of the sequence number of each process described above does not mean the order of execution, and the execution order of each process should be determined according to its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0171] It should be understood that determining B according to A does not mean that B is determined only according to A, but B can also be determined according to A and / or other information.

[0172] The above embodiments can be realized wholly or partially by software, hardware, firmware or any other combination. When realized by software, the above embodiments can be realized wholly or partially in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the flow or function according to the embodiments of the present application is wholly or partially generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another, for example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center through a wired network or / and wireless network. The computer-readable storage medium can be any available medium accessible by a computer or a data storage device such as a server, data center and the like containing one or more available medium collections. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a DVD) or a semiconductor medium. The semiconductor medium can be a solid-state disk.

[0173] Those skilled in the art can realize that the units and algorithm steps of the examples described in combination with the disclosed embodiments of the present application can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solution. The skilled person can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0174] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system, device and unit described above can refer to the corresponding process in the foregoing method embodiments, which will not be described here.

[0175] In several embodiments provided by the present application, it should be understood that the disclosed system, device and method can be implemented in other manners. For example, the described device embodiment is merely illustrative. For example, the division of the units is only a division in one embodiment. For other embodiments, multiple units or components can be combined or integrated into another system, or some features can be ignored or not implemented. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections between different units, or the displayed or discussed mutual couplings or direct couplings or communication connections, can be indirect couplings or communication connections through some interfaces, devices or units, and can be in electrical, mechanical or other forms.

[0176] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one place, or they may be distributed on multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.

[0177] In addition, the functional units in each embodiment of the present application can be integrated into a processing unit, or each unit can be physically present separately, or two or more units can be integrated into one unit.

[0178] In the description of the specification, the description of the terms "one embodiment", "an example", "a specific example" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0179] The basic principles and main features of the present application and the advantages of the present application have been shown and described above. It should be understood by those skilled in the art that the present application is not limited by the above embodiments, and the above embodiments and descriptions in the specification are only to illustrate the principles of the present application. Without departing from the spirit and scope of the present application, various changes and improvements can be made to the present application, and these changes and improvements all fall within the scope of the claimed present application. The scope of protection of the present application is defined by the appended claims and their equivalents.

Claims

1. A method for rapid identification of defects in a lithium niobate waveguide based on depth map reconstruction, characterized in that, The method comprises: S1: Collecting the original scattering intensity and dark field intensity of the waveguide signal, and performing normalization processing to obtain a transverse equivalent response sequence; S2: Establishing a transverse relative response, calculating the transverse difference between adjacent waveguides, constructing the transverse coupling residual between parallel waveguides, smoothing the transverse coupling residual, and obtaining a coupling residual map; S3: Based on the coupling residual map, a depth suppression coefficient matrix is constructed, and the transverse equivalent response sequence is coupled to suppress to form a preliminary decoupled depth response matrix; At the same time, the preliminary decoupled depth response matrix is balanced to obtain a final decoupled depth matrix; S4: Based on the final decoupled depth matrix, a primary three-dimensional depth map is generated, a depth peak value map is extracted, and a binary mask is constructed to form a defect candidate mask map; S5: Extracting the defect coordinate set corresponding to each waveguide from the defect candidate mask map, and performing depth reverse lookup on each candidate point extracted to obtain a defect depth value; According to the defect depth value and the defect coordinate set, the defect intensity is calculated to obtain a final defect judgment result set.

2. The method of claim 1, wherein the method further comprises: S1 comprises: S11: Discretizing the continuous waveguide parallel region to form a sampling grid, and determining a transverse sampling point set and a depth sampling point set according to the geometric parameters of the waveguide parallel wiring region; The geometric parameters include: transverse starting coordinates, waveguide spacing, target transverse sampling spacing, depth starting coordinates, depth sampling spacing, number of transverse sampling points, and number of depth sampling points; S12: Based on the transverse sampling point set and the depth sampling point set, the measured photon counting value and the dark field counting are analyzed to obtain the original scattering intensity and the dark field intensity; S13: The original scattering intensity is normalized, and then the transverse equivalent response sequence is generated in combination with the dark field intensity, and the transverse equivalent response sequence is truncated.

3. The method of claim 2, wherein S2 Comprise: S21: Based on the transverse equivalent response sequence, the average value of the response of all transverse sampling positions is calculated at each depth sampling point to obtain a depth reference response, and the offset of each transverse position is calculated according to the depth reference response to obtain a transverse relative response; S22: Based on the transverse relative response, the response between adjacent two transverse sampling points is calculated at each depth sampling point to obtain a transverse difference; S23: The transverse coupling residual map is constructed according to the transverse difference, and the transverse coupling residual map is truncated to the upper limit; S24: The transverse coupling residual map is smoothed in the depth direction to obtain a smoothed coupling residual map.

4. The method of claim 3, wherein S3 Comprise: S31: The coupling residual map is normalized and truncated, the processed coupling residual map is mapped to a coupling coefficient in the interval of 0-1 to obtain a transverse coupling coefficient distribution; S32: According to the set coupling suppression weight constant, a depth suppression coefficient matrix with the same dimension as the transverse coupling coefficient distribution is constructed, and the depth suppression coefficient matrix is truncated to the lower limit.

5. The method of claim 4, wherein the method further comprises: S3 further comprises: S33: According to the depth suppression coefficient matrix, the transverse equivalent response sequence is coupled to suppress to obtain a preliminary decoupled depth response matrix; S34: Based on the preliminary decoupling depth response matrix and the lateral equivalent response sequence, the calculated depth layer energy correction coefficient is applied to each coordinate point to obtain the final decoupled depth matrix.

6. The method for fast discrimination of LiNbO3 waveguide defects based on depth map reconstruction according to claim 5, wherein S4 Comprising: S41: Based on the final decoupled depth matrix, a primary three-dimensional depth atlas is constructed by introducing a depth mapping coefficient and an equidistant sampling coordinate in the longitudinal direction of the waveguide; S42: The primary three-dimensional depth atlas is normalized and contrast enhanced to obtain a normalized and contrast enhanced three-dimensional depth atlas; S43: By scanning the depth direction of the normalized three-dimensional depth atlas, the maximum depth response value of each lateral-longitudinal point is extracted and smoothed to obtain a depth peak value map.

7. The method of claim 6, wherein the method further comprises: S4 also comprises: S44: Based on the depth peak value map and the preset defect threshold, a binary mask is constructed, and a connectivity check and isolated point suppression processing are performed to form a defect candidate mask map.

8. The method of claim 7, wherein S5 Comprising: S51: Extracting the defect coordinate set corresponding to each waveguide from the defect candidate mask map.

9. The method of claim 8, wherein the method further comprises: S5 also comprises: S52: Extracting each candidate point in the defect coordinate set, performing depth reverse lookup on each candidate point, and performing weighted average processing to obtain a defect depth value.

10. The method of claim 8, wherein the method further comprises: S5 also comprises: S53: Calculating the defect intensity according to the defect depth value and the defect coordinate set; Synchronize to form a final defect judgment result set.

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