A trough mirror geometry error identification method based on reflected light distribution data

Abstract

The application discloses a kind of based on the trough mirror geometric error identification method of reflection light distribution data, belong to solar thermal technology field.It includes the following steps: obtaining the object identification of target mirror group, structure configuration, detection working condition and current reflection light distribution data, matching corresponding standard reflection light distribution configuration and template set with error type, direction and error amount label;Data is executed background deduction, radiation normalization, coordinate correction, exception handling and matrix, extract centroid, width, symmetry, left and right energy ratio and concentration;Based on current matrix and feature vector, calculate standard deviation and template similarity, determine normal state, single-side angle deviation, double-side inward deviation, double-side outward deviation or double-side same direction deviation, output error direction, error amount, level and reliability.The application makes the data comparable under different structures and detection working conditions, realizes the automatic classification and quantization of trough mirror geometric error.

Description

Technical Field

[0001] This invention relates to the field of solar thermal technology, and more specifically to a method for identifying geometric errors of a slotted reflector based on reflected light distribution data. Background Technology

[0002] Parabolic trough solar thermal collectors are widely used in the field of solar thermal utilization due to their high collection efficiency, mature system structure, and ease of large-scale deployment. However, during installation and long-term operation, the reflectors are susceptible to factors such as assembly deviations, wind loads, gravity loads, and structural loosening, which can lead to deviations in the geometric shape or spatial orientation of the reflecting surface. 1. Existing mirror error detection mainly relies on manual inspection, structural dimension measurement or special optical inspection equipment. The detection process is complicated and the detection cycle is long, which makes it difficult to meet the rapid detection needs of multiple mirror groups in large-scale mirror fields. 2. Existing detection methods usually focus on single parameters such as the mirror profile, installation angle, or displacement of the supporting structure, lacking comprehensive processing of the spatial distribution data of reflected light, making it difficult to directly determine the impact of geometric errors on the actual focusing position, spot width, distribution symmetry, and energy concentration. 3. The normal reflected light distribution varies with different opening widths, design focal lengths, detection postures and detection positions. Existing methods lack a standard reflected light distribution configuration corresponding to the mirror structure configuration, which can easily lead to misjudging the distribution differences caused by different structural parameters or detection conditions as mirror geometric errors. 4. Existing detection methods can usually only determine whether there is a deviation in the reflector, but it is difficult to further distinguish between single-sided angular deviation, double-sided inward deviation, double-sided outward deviation, and double-sided same-direction deviation, and it is also difficult to determine the corresponding error direction, error amount, and error level.

[0003] In summary, existing technologies for detecting geometric errors in trough solar reflectors suffer from problems such as low detection efficiency, insufficient utilization of reflected light distribution data, poor adaptability to standard configurations, and inadequate ability to identify error types and quantities. There is an urgent need for a geometric error identification method for trough solar reflectors that can perform standardized processing, configuration matching, feature extraction, and error identification based on reflected light distribution data. Summary of the Invention

[0004] To address the shortcomings of existing technologies in batch testing, cross-condition comparison, complete light field utilization, and error classification and quantification, this invention provides a method for identifying geometric errors in slotted mirrors based on reflected light distribution data. This method establishes a correlation between the structural configuration of the target mirror assembly and the standard distribution and error template, standardizes the measured reflected light distribution under operating conditions, and performs deviation calculation and template matching in two spaces: the complete matrix and the interpretable distribution features. This yields geometric error identification results that can be directly used for condition assessment, thereby improving the accuracy and automation level of geometric error detection for slotted mirrors.

[0005] To achieve the above objectives, the present invention provides the following technical solution: A method for identifying geometric errors in slotted mirrors based on reflected light distribution data includes the following steps: S1. Obtain the object identification information, structural configuration parameters, detection condition parameters, and current reflected light distribution data collected by the reflected light detection component of the target reflector group; S2. Based on the object identification information and structural configuration parameters, determine the standard reflected light distribution configuration and error template set corresponding to the target reflector group from the preset configuration set, wherein the error template set includes reflected light distribution templates corresponding to different geometric error types, error directions and error amounts; S3. Based on the detection conditions parameters, the current reflected light distribution data is processed by background signal subtraction, radiation intensity normalization, coordinate correction, abnormal data processing, and matrix processing to obtain the current reflected light distribution matrix. S4. Extract at least two of the following from the current reflected light distribution matrix: spot centroid position, peak position, distribution width, distribution symmetry, left-right region energy ratio, and energy concentration, and construct the current reflected light distribution feature vector; S5. Calculate the deviation between the current reflected light distribution matrix and the current reflected light distribution feature vector and the standard reflected light distribution configuration, and calculate the similarity between them and the reflected light distribution templates in the error template set to obtain the standard distribution deviation result and the error template matching result. S6. Based on the standard distribution deviation results and error template matching results, determine the geometric error state of the target reflector group and generate geometric error identification results; The geometric error identification results include at least one of the following: normal state, unilateral angular deviation, bilateral inward deviation, bilateral outward deviation, and bilateral same-direction deviation, as well as the corresponding error direction, error amount, and error level.

[0006] Furthermore, in S1: The object identification information includes the target reflector group number and location information; The structural configuration parameters include the mirror opening width, design focal length, preset detection posture, and preset detection position of the reflected light detection component; The detection parameters include direct solar radiation intensity, the current attitude angle of the target reflector group, and the current position of the reflected light detection component.

[0007] Furthermore, in S1: The current reflected light distribution data is collected by a reflected light detection component located within the reflected light propagation area corresponding to the target reflector group. The reflected light detection component includes a reflected light detection plate formed by multiple photosensitive detection units arranged in a preset spatial position. Each photosensitive detection unit is used to output a corresponding detection signal according to the intensity of the received reflected light. The detection signals are arranged according to the position of each photosensitive detection unit to form the current reflected light distribution data.

[0008] Furthermore, in S2: The preset configuration set includes standard reflected light distribution configurations and error template sets corresponding to different mirror opening widths, design focal lengths, preset detection postures, and detection positions; The standard reflected light distribution configuration includes at least one of the following: standard reflected light distribution matrix, standard spot centroid position, standard distribution width, standard distribution symmetry, and standard energy concentration. The error template set includes reflected light distribution templates corresponding to single-sided angular deviation, double-sided inward deviation, double-sided outward deviation, and double-sided same-direction deviation under different error directions and error amounts; The standard reflected light distribution configuration and error template set are pre-generated through ray tracing calculations, calibration experiments, or a combination of both, and are stored in association with the corresponding structural configuration parameters.

[0009] Furthermore, in step S3, the processing of the current reflected light distribution data includes: The current reflected light distribution data is compared with the pre-acquired background distribution data to eliminate ambient scattered light and background signal of the detection components; The difference-processed data is normalized based on the current direct solar radiation intensity to obtain normalized reflected light distribution data. Based on the position, orientation, and detection area coordinates of the reflected light detection component, the normalized reflected light distribution data is mapped to a preset standard coordinate system; Invalid, saturated, and outlier data are identified and corrected, and the processed detection area is divided into M×N data units to generate the current reflected light distribution matrix.

[0010] Furthermore, in step S4, the process of constructing the current reflected light distribution feature vector includes: Based on the position of each data unit in the current reflected light distribution matrix and the corresponding light intensity, determine the position of the light spot centroid, the peak position, and the distribution width; The detection area is divided into a first detection area and a second detection area that are symmetrical about the preset center line. The distribution symmetry and the energy ratio of the left and right areas are determined based on the received energy of the two detection areas. The energy concentration is determined based on the ratio of the energy received in the preset central area to the total energy received in the detection area. Arrange at least two of the following in a preset order: the centroid position of the light spot, the peak position, the distribution width, the distribution symmetry, the energy ratio of the left and right regions, and the energy concentration, to obtain the current reflected light distribution feature vector.

[0011] Furthermore, in step S5, the process of determining the standard distribution deviation result and the error template matching result includes: The difference between the current reflected light distribution matrix and the standard reflected light distribution matrix is ​​calculated for corresponding data cells to obtain the reflected light distribution deviation matrix and the matrix deviation value. The current reflected light distribution feature vector is compared with the standard distribution feature parameters to obtain at least one of the following: spot centroid position deviation, peak position deviation, distribution width deviation, distribution symmetry deviation, left and right region energy ratio deviation, and energy concentration deviation. The standard distribution deviation result is determined based on the matrix deviation value and the deviation of each feature; Calculate the similarity between the current reflected light distribution matrix and its eigenvector and each reflected light distribution template and its eigenvector in the error template set to obtain the comprehensive matching value for each error template. Error templates whose comprehensive matching values ​​meet the preset matching conditions are identified as target error templates. The matching confidence level is determined based on the comprehensive matching value of the target error templates, and error template matching results are generated.

[0012] Furthermore, in step S6, the process of determining the geometric error identification result includes: When the standard distribution deviation result is within the preset allowable range, the target reflector group is determined to be in normal condition; When the standard distribution deviation result exceeds the preset allowable range and the matching confidence reaches the preset confidence threshold, the target reflector group is determined to be in a state of single-sided angle deviation, double-sided inward deviation, double-sided outward deviation and double-sided same-direction deviation according to the error type and error direction corresponding to the target error template. The error amount of the target reflector group is determined by interpolation calculation based on the error amount corresponding to the target error template or the comprehensive matching value of adjacent error amount templates, and the error level is determined based on the comparison result of the error amount and the preset level threshold.

[0013] The technical solution provided by this invention has the following advantages compared with the prior art: 1. This invention uses a configuration index consisting of the mirror opening width, design focal length, preset detection posture, and preset detection position. First, it selects a standard reflected light distribution configuration and error template set that match the target mirror group from the preset configuration set. Then, it performs deviation calculation and template matching. Different structural specifications and detection arrangements no longer share a single fixed reference. This can isolate the normal distribution differences caused by structural parameters and detection positions from the identification link, reduce the possibility of misjudging configuration differences as geometric errors, and improve the adaptability of this solution to different slotted mirror structures. 2. The current reflected light distribution data is processed sequentially with background signal subtraction, direct solar radiation intensity normalization, coordinate correction, outlier processing, and unified matrixing. Background subtraction is used to eliminate ambient scattered light and background radiation from the detection components. Radiation normalization is used to suppress changes in incident irradiance. Coordinate correction is used to eliminate differences in the position and orientation of the detection components. Outlier processing is used to reduce the impact of invalid, saturated, and outlier data. The above processing transforms the data from different detection times and under different operating conditions to the same intensity and spatial coordinate reference, thereby improving the comparability, repeatability, and stability of subsequent identification results of the reflected light distribution data. 3. The spatial distribution of reflected light on the detection section is directly acquired using a photosensitive detection unit array. At the same time, the current reflected light distribution matrix and a feature vector composed of centroid position, peak position, distribution width, distribution symmetry, energy ratio of left and right regions, and energy concentration are constructed. The distribution matrix retains fine-grained light intensity information at each spatial position, while the feature vector extracts light spot morphology parameters with clear physical meaning. Together, they establish a direct correspondence between the geometric state of the reflector and the actual focusing result, avoiding indirect judgment of error based solely on structural size, single-point angle, or single light spot index. This allows the recognition result to more completely reflect the comprehensive impact of geometric error on focusing position, light spot morphology, and energy concentration. 4. Collaborate on normal state determination and error type identification: Use the matrix deviation and feature deviation of the current distribution relative to the standard distribution to determine whether it exceeds the normal allowable range. At the same time, use the fusion results of matrix similarity and feature similarity to determine the best matching error template. The complete distribution information and low-dimensional physical features complement each other, and the standard distribution deviation determination and template matching constrain each other, which can reduce the identification ambiguity caused by local noise, single feature fluctuations or similar spot shapes. 5. This invention establishes reflected light distribution templates labeled with error type, error direction, and error amount for different geometric errors. It incorporates physical responses such as centroid shift and left-right energy asymmetry caused by unilateral deviation, spot narrowing and increased concentration caused by bilateral inward deviation, spot widening and decreased concentration caused by bilateral outward deviation, and overall shift and symmetry maintenance caused by bilateral same-direction deviation into the identification criteria. By the correspondence between template labels and optical response laws, the form and direction of error occurrence can be clearly identified while judging anomalies. Constraints are imposed by matching confidence and the difference between the largest and second largest matching values, which can also avoid forcibly classifying low-confidence data into existing error types, thereby improving the credibility of the identification conclusion. 6. Multiple error quantity templates are set under the same error type and direction, and weighted interpolation is performed based on the comprehensive matching value of adjacent error quantity templates. This allows the discrete template to provide continuous or finer-grained error quantity estimates. Subsequently, the error quantity is compared with the configured level threshold, and the error level is output. At the same time, the result processing unit associates the error type, direction, error quantity, level, and matching confidence with the target reflector group number and location. The system can not only answer whether the reflector is abnormal and the type of abnormality, but also generate quantitative results that can be used for verification, maintenance priority ranking, and batch status management of the mirror field, realizing a closed loop of light field acquisition - error identification - maintenance decision data output. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0015] Figure 1 This is a flowchart of the present invention; Figure 2 This is a data diagram of the reflected light distribution data processing and feature extraction of the present invention; Figure 3 This is a schematic diagram of the reflected light distribution templates corresponding to different geometric error types in this invention; Figure 4 This is a schematic diagram of the structure of a parabolic trough solar collector system and the distribution of the reflected light detection components. Among them, 1. Parabolic trough solar collector system, 2. Reflector, 3. Heat absorber tube, 4. Heat transfer medium inlet, 5. Heat transfer medium outlet, 6. Reflected light detection component, 7. Photosensitive detection unit array. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0017] like Figures 1-4 As shown, a method for identifying geometric errors of a trough-type reflector based on reflected light distribution data is used to identify geometric errors of the reflectors in a trough-type solar thermal collector system 1. The method includes the following steps: S1. Obtain the object identification information, structural configuration parameters, detection condition parameters, and current reflected light distribution data collected by the reflected light detection component of the target reflector group.

[0018] The object identification information is used to determine the current detection object, including the target reflector group number, installation location number, or corresponding heat collection unit identification information, so as to distinguish and associate the detection data of different reflector groups.

[0019] The structural configuration parameters are used to characterize the geometric features of the target mirror assembly, including the mirror opening width, design focal length, mirror assembly size parameters, and relative position parameters of the heat absorption tube. Based on the above structural configuration parameters, the reflected light propagation area and detection area range corresponding to the target mirror assembly can be determined.

[0020] The detection operating parameters are used to describe the current detection status, including the reflector's operating attitude, the detection board's installation position, the intensity of direct solar radiation, and environmental operating parameters, to ensure the effectiveness of the data collected under different detection conditions.

[0021] The current reflected light distribution data is collected by the reflected light detection component 6, specifically, as follows: Figure 4 As shown, a reflection light detection component 6 is set in the reflection light propagation area corresponding to the target reflector group. The reflection light detection component 6 includes a detection plate and a photosensitive detection unit array 7 set on the detection plate. Multiple photosensitive detection units are arranged in two dimensions according to a preset spatial position. Each photosensitive detection unit is used to receive the reflected light at the corresponding position and output a corresponding detection signal according to the received light intensity.

[0022] The detection signals output by each photosensitive detection unit are combined according to their spatial arrangement to form the current reflected light distribution data. The current reflected light distribution data is used to characterize the spatial distribution characteristics of the reflected light in the current state of the target mirror group and serves as the data basis for subsequent geometric error identification.

[0023] S2. Based on the object identification information and structural configuration parameters, determine the standard reflected light distribution configuration and error template set corresponding to the target reflector group from the preset configuration set, wherein the error template set includes reflected light distribution templates corresponding to different geometric error types, error directions and error amounts.

[0024] like Figure 3 As shown, based on the possible geometric error forms of the reflector, a reflected light distribution template corresponding to different error states is pre-established. The different geometric error states include single-sided angle deviation, double-sided inward deviation, double-sided outward deviation, and double-sided same-direction deviation. Different error states correspond to different light spot positions, distribution widths, and energy concentration degree variation patterns.

[0025] Based on the possible geometric deviations of the reflector, a corresponding error template set is pre-established. The error template set includes reflected light distribution templates under different states such as single-sided angular deviation, double-sided inward deviation, double-sided outward deviation, and double-sided same-direction deviation. Each error template corresponds to a different error direction and error amount.

[0026] Through the above matching process, the standard reflected light distribution configuration and error template set corresponding to the target reflector group are determined, providing data basis for subsequent reflected light distribution deviation calculation and geometric error identification.

[0027] S3. Based on the detection conditions parameters, perform background signal subtraction, radiation intensity normalization, coordinate correction, abnormal data processing, and matrix processing on the current reflected light distribution data to obtain the current reflected light distribution matrix.

[0028] like Figure 2 As shown, the raw reflected light distribution data output by the reflected light detection component is first preprocessed, including background signal subtraction, radiation intensity normalization, coordinate correction, and abnormal data processing. Then, it is converted into an M×N reflected light distribution matrix according to the spatial arrangement of the photosensitive detection units.

[0029] Based on the current reflected light distribution data and detection parameters obtained in S1, the data is preprocessed to eliminate the influence of different detection conditions on the reflected light distribution results.

[0030] First, the current reflected light distribution data is compared with the pre-acquired background signal data to remove ambient scattered light and the background signal generated by the photosensitive detection unit itself, thus obtaining effective reflected light response data: ; in, This indicates the output value of the photosensitive detection unit corresponding to the current detection position. Indicates the background signal value. This represents the effective reflected light data after background removal; Based on the direct solar radiation intensity under the current testing conditions, the effective reflected light data is normalized to reduce the impact of different solar radiation conditions on the testing results. ; in, This indicates the current intensity of direct solar radiation. This represents the normalized reflected light distribution data; Then, based on the installation position, detection posture, and detection area coordinates of the reflected light detection component, the normalized reflected light data is coordinate corrected so that the data under different detection states are mapped to a unified coordinate system. The corrected data undergoes anomaly processing, identifying and correcting invalid data, saturated data, and data that significantly deviates from the normal range. Finally, based on the spatial arrangement of the photosensitive detection units, the processed reflected light data is arranged according to two-dimensional positions, divided into M×N data units, forming the current reflected light distribution matrix: ; The current reflected light distribution matrix is ​​used to characterize the spatial light distribution of the target mirror group in its current state, and serves as the data basis for subsequent reflected light feature extraction and geometric error matching and identification.

[0031] S4. Extract at least two of the following from the current reflected light distribution matrix: spot centroid position, peak position, distribution width, distribution symmetry, left-right region energy ratio, and energy concentration, and construct the current reflected light distribution feature vector.

[0032] Based on the current reflected light distribution matrix obtained in step S3, the spatial distribution features of the reflected light are extracted to obtain feature parameters that can characterize the geometric state changes of the target mirror group.

[0033] First, based on the position coordinates of each data unit in the current reflected light distribution matrix and the corresponding reflected light intensity, the centroid position of the reflected light distribution spot is calculated. This centroid position is used to characterize the offset of the current reflected light energy center relative to the standard position. The calculation method is as follows: ; ; in, This represents the reflected light intensity corresponding to the i-th and j-th detection units. , This indicates the position coordinates of the detection unit; The peak position is determined based on the data unit corresponding to the maximum light intensity in the current reflected light distribution matrix; the width of the reflected light distribution is determined based on the light intensity distribution range, which is used to determine the state of light spot diffusion or contraction. At the same time, the detection area is divided into two regions, left and right, according to the preset center line. The received energy of the two regions is calculated respectively to obtain the symmetry of the reflected light distribution and the energy ratio of the left and right regions, which is used to determine whether there is a unidirectional shift in the reflected light. The energy concentration of reflected light is determined by the ratio between the energy received in the central region and the total energy received in the entire detection area, which is used to characterize the degree of concentration of reflected light. Arrange at least two of the extracted feature parameters—centroid position, peak position, distribution width, distribution symmetry, left-right region energy ratio, and energy concentration—in a preset order to form the current reflected light distribution feature vector: ; Where F represents the current reflected light distribution feature vector, which is used for subsequent matching calculations with the standard reflected light distribution configuration and error template. This represents the nth characteristic parameter of the reflected light distribution.

[0034] S5. Calculate the deviation between the current reflected light distribution matrix and the current reflected light distribution feature vector and the standard reflected light distribution configuration, and calculate the similarity between them and the reflected light distribution templates in the error template set to obtain the standard distribution deviation result and the error template matching result.

[0035] Specifically, based on the current reflected light distribution matrix obtained in step S3 and the current reflected light distribution feature vector constructed in step S4, the deviation is first calculated with the corresponding standard reflected light distribution configuration determined in step S2 to determine the degree of difference between the current reflected light distribution and the standard distribution under normal conditions.

[0036] First, the current reflected light distribution matrix is ​​compared with the standard reflected light distribution matrix at corresponding positions to calculate the reflected light intensity deviation of each detection unit, thus obtaining the reflected light distribution deviation matrix: ; in, This represents the light intensity value of the i-th,j-th data cell in the current reflected light distribution matrix. This represents the light intensity value at the corresponding position in the standard reflected light distribution matrix; Then, the overall deviation value is calculated based on the reflected light distribution deviation matrix. At the same time, the current reflected light distribution feature vector is compared with the feature parameters in the standard reflected light distribution configuration to obtain at least one of the following: spot centroid position deviation, peak position deviation, distribution width deviation, symmetry deviation, left and right region energy ratio deviation, and energy concentration deviation. Based on the matrix deviation results and the characteristic parameter deviation results, the standard distribution deviation of the current reflected light distribution relative to the standard state is determined comprehensively. Finally, the current reflected light distribution matrix and the current reflected light distribution feature vector are compared with the reflected light distribution templates in the error template set to calculate the similarity and obtain the matching values ​​corresponding to different error templates. The reflected light distribution templates in the error template set correspond to different geometric error states such as single-sided angle deviation, double-sided inward deviation, double-sided outward deviation, and double-sided same-direction deviation.

[0037] By comparing the comprehensive matching values ​​corresponding to each error template, the target error template that is closest to the current reflected light distribution is determined, and the error template matching result is generated. The error template matching result includes the target error type and the corresponding matching confidence level.

[0038] S6. Based on the standard distribution deviation results and error template matching results, determine the geometric error state of the target reflector group and generate geometric error identification results; The geometric error identification results include at least one of the following: normal state, unilateral angular deviation, bilateral inward deviation, bilateral outward deviation, and bilateral same-direction deviation, as well as the corresponding error direction, error amount, and error level.

[0039] Based on the standard distribution deviation results and error template matching results obtained in step S5, the current geometric state of the target reflector group is determined: When the standard distribution deviation result is within the preset allowable range, the target reflector group is determined to be in a normal state, and a normal state identification result is generated; When the standard distribution deviation result exceeds the preset allowable range, the geometric error state corresponding to the target reflector group is determined according to the target template type and matching confidence in the error template matching result.

[0040] When the overall distribution of reflected light shifts along a certain direction, and the changes in the spot width and energy concentration are small, it is determined that there is a two-sided same-direction deviation in the target reflector group; when the center position of the reflected light distribution shifts in one direction, it is determined that there is a one-sided angular deviation; when the width of the reflected light distribution decreases and the energy concentration increases, it is determined that there is a two-sided inward deviation; when the range of the reflected light distribution expands and the energy concentration decreases, it is determined that there is a two-sided outward deviation.

[0041] In addition, based on the error parameters corresponding to the target error template, the direction and amount of the current geometric error are determined, and the corresponding error level is determined based on the relationship between the error amount and the preset level threshold.

[0042] Finally, geometric error identification results are generated, including the geometric error type, error direction, error amount, and error level of the target reflector group, which are used for subsequent reflector maintenance and condition assessment.

[0043] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions will not cause the essence of the corresponding technical solutions to deviate from the protection scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for identifying geometric errors of a slotted mirror based on reflected light distribution data, characterized in that, Includes the following steps: S1. Obtain the object identification information, structural configuration parameters, detection condition parameters, and current reflected light distribution data collected by the reflected light detection component of the target reflector group; S2. Based on the object identification information and structural configuration parameters, determine the standard reflected light distribution configuration and error template set corresponding to the target reflector group from the preset configuration set, wherein the error template set includes reflected light distribution templates corresponding to different geometric error types, error directions and error amounts; S3. Based on the detection conditions parameters, the current reflected light distribution data is processed by background signal subtraction, radiation intensity normalization, coordinate correction, abnormal data processing, and matrix processing to obtain the current reflected light distribution matrix. S4. Extract at least two of the following from the current reflected light distribution matrix: spot centroid position, peak position, distribution width, distribution symmetry, left-right region energy ratio, and energy concentration, and construct the current reflected light distribution feature vector; S5. Calculate the deviation between the current reflected light distribution matrix and the current reflected light distribution feature vector and the standard reflected light distribution configuration, and calculate the similarity between them and the reflected light distribution templates in the error template set to obtain the standard distribution deviation result and the error template matching result. S6. Based on the standard distribution deviation results and error template matching results, determine the geometric error state of the target reflector group and generate geometric error identification results; The geometric error identification results include at least one of the following: normal state, unilateral angular deviation, bilateral inward deviation, bilateral outward deviation, and bilateral same-direction deviation, as well as the corresponding error direction, error amount, and error level.

2. The method for identifying geometric errors of a slotted mirror based on reflected light distribution data according to claim 1, characterized in that, In S1: The object identification information includes the target reflector group number and location information; The structural configuration parameters include the mirror opening width, design focal length, preset detection posture, and preset detection position of the reflected light detection component; The detection parameters include direct solar radiation intensity, the current attitude angle of the target reflector group, and the current position of the reflected light detection component.

3. The method for identifying geometric errors of a slotted mirror based on reflected light distribution data according to claim 1 or 2, characterized in that, In S1: The current reflected light distribution data is collected by a reflected light detection component located within the reflected light propagation area corresponding to the target reflector group. The reflected light detection component includes a reflected light detection plate formed by multiple photosensitive detection units arranged in a preset spatial position. Each photosensitive detection unit is used to output a corresponding detection signal according to the intensity of the received reflected light. The detection signals are arranged according to the position of each photosensitive detection unit to form the current reflected light distribution data.

4. The method for identifying geometric errors of a slotted mirror based on reflected light distribution data according to claim 1, characterized in that, In S2: The preset configuration set includes standard reflected light distribution configurations and error template sets corresponding to different mirror opening widths, design focal lengths, preset detection postures, and detection positions; The standard reflected light distribution configuration includes at least one of the following: standard reflected light distribution matrix, standard spot centroid position, standard distribution width, standard distribution symmetry, and standard energy concentration. The error template set includes reflected light distribution templates corresponding to single-sided angular deviation, double-sided inward deviation, double-sided outward deviation, and double-sided same-direction deviation under different error directions and error amounts; The standard reflected light distribution configuration and error template set are pre-generated through ray tracing calculations, calibration experiments, or a combination of both, and are stored in association with the corresponding structural configuration parameters.

5. The method for identifying geometric errors of a slotted mirror based on reflected light distribution data according to claim 1, characterized in that, In step S3, the processing procedure for the current reflected light distribution data includes: The current reflected light distribution data is compared with the pre-acquired background distribution data to eliminate ambient scattered light and background signal of the detection components; The difference-processed data is normalized based on the current direct solar radiation intensity to obtain normalized reflected light distribution data. Based on the position, orientation, and detection area coordinates of the reflected light detection component, the normalized reflected light distribution data is mapped to a preset standard coordinate system; Invalid, saturated, and outlier data are identified and corrected, and the processed detection area is divided into M×N data units to generate the current reflected light distribution matrix.

6. The method for identifying geometric errors of a slotted mirror based on reflected light distribution data according to claim 1, characterized in that, In step S4, the process of constructing the current reflected light distribution feature vector includes: Based on the position of each data unit in the current reflected light distribution matrix and the corresponding light intensity, determine the position of the light spot centroid, the peak position, and the distribution width; The detection area is divided into a first detection area and a second detection area that are symmetrical about the preset center line. The distribution symmetry and the energy ratio of the left and right areas are determined based on the received energy of the two detection areas. The energy concentration is determined based on the ratio of the energy received in the preset central area to the total energy received in the detection area. Arrange at least two of the following in a preset order: the centroid position of the light spot, the peak position, the distribution width, the distribution symmetry, the energy ratio of the left and right regions, and the energy concentration, to obtain the current reflected light distribution feature vector.

7. The method for identifying geometric errors of a slotted mirror based on reflected light distribution data according to claim 1, characterized in that, In step S5, the process of determining the standard distribution deviation result and the error template matching result includes: The difference between the current reflected light distribution matrix and the standard reflected light distribution matrix is ​​calculated for corresponding data cells to obtain the reflected light distribution deviation matrix and the matrix deviation value. The current reflected light distribution feature vector is compared with the standard distribution feature parameters to obtain at least one of the following: spot centroid position deviation, peak position deviation, distribution width deviation, distribution symmetry deviation, left and right region energy ratio deviation, and energy concentration deviation. The standard distribution deviation result is determined based on the matrix deviation value and the deviation of each feature; Calculate the similarity between the current reflected light distribution matrix and its eigenvector and each reflected light distribution template and its eigenvector in the error template set to obtain the comprehensive matching value for each error template. Error templates whose comprehensive matching values ​​meet the preset matching conditions are identified as target error templates. The matching confidence level is determined based on the comprehensive matching value of the target error templates, and error template matching results are generated.

8. The method for identifying geometric errors of a slotted mirror based on reflected light distribution data according to claim 7, characterized in that, In step S6, the process of determining the geometric error identification result includes: When the standard distribution deviation result is within the preset allowable range, the target reflector group is determined to be in normal condition; When the standard distribution deviation result exceeds the preset allowable range and the matching confidence reaches the preset confidence threshold, the target reflector group is determined to be in a state of single-sided angle deviation, double-sided inward deviation, double-sided outward deviation and double-sided same-direction deviation according to the error type and error direction corresponding to the target error template. The error amount of the target reflector group is determined by interpolation calculation based on the error amount corresponding to the target error template or the comprehensive matching value of adjacent error amount templates, and the error level is determined based on the comparison result of the error amount and the preset level threshold.

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