Wavelength accurate adjusting method and device based on angle sensor and laser

Abstract

The invention relates to the technical field of wavelength adjustment, and discloses an accurate wavelength adjustment method and device based on an angle sensor and a laser, and the method comprises the steps: carrying out the initialization of the laser based on an initial detection parameter combination, and obtaining the spatial position mapping data of the angle sensor and a detection light beam; calculating to obtain an angle deviation matrix and establishing an angle-reflection intensity relation mapping table; generating a compensation detection parameter combination of the laser; performing spiral scanning detection based on the compensation detection parameter combination to obtain initial feature representation, and performing feature enhancement to obtain enhanced feature representation; performing multi-dimensional index analysis and fusion on the enhanced feature representation to obtain a quality detection result; and solving a global optimal detection parameter combination of the laser according to a quality detection result, and generating a laser adjustment control sequence. The method improves the accuracy of quality detection of the wavelength-related device.

Description

Technical Field

[0001] The present invention relates to the technical field of wavelength adjustment, and in particular to a wavelength precise adjustment method, device and laser based on an angle sensor. Background Art

[0002] Traditional detection methods rely on fixed wavelength lasers and single angle detection methods, which cannot adapt to the detection needs of different types of wavelength-related devices, resulting in low accuracy and reliability of detection results. Due to the complex structure and large detection area of ​​wavelength-related devices, traditional detection methods are difficult to obtain complete and accurate quality information.

[0003] The current detection systems generally have problems such as difficulty in optimizing detection parameters, unstable detection process, and poor consistency of detection results. This is mainly due to the lack of an effective wavelength precision adjustment mechanism, which makes it impossible to dynamically adjust the detection parameters according to different characteristics. At the same time, there is also a lack of precise control over the spatial position and energy density of the detection light beam, resulting in light intensity fluctuations and angle deviations during the detection process that affect the detection accuracy. Although some parameter compensation and correction methods have been adopted in the prior art, most of them are based on empirical settings or simple feedback adjustments, lacking a systematic theoretical basis and intelligent control strategy. In this case, the detection system is difficult to cope with complex and changeable detection environments, and cannot guarantee the repeatability and reliability of the detection results. Summary of the invention

[0004] The present invention provides a wavelength precise adjustment method, device and laser based on an angle sensor, which are used to improve the accuracy of quality detection of wavelength-related components.

[0005] In a first aspect, the present invention provides a method for accurately adjusting wavelength based on an angle sensor, the method for accurately adjusting wavelength based on an angle sensor comprising: Initialize the laser based on the initial detection parameter combination and obtain spatial position mapping data of the angle sensor and the detection beam; According to the spatial position mapping data, an angle deviation matrix is ​​calculated and an angle-reflection intensity relationship mapping table is established; Generate a compensation detection parameter combination of the laser based on the angle deviation matrix and the angle-reflection intensity relationship mapping table; Performing spiral scanning detection based on the compensation detection parameter combination to obtain an initial feature representation, and performing feature enhancement to obtain an enhanced feature representation; Performing multi-dimensional index analysis and fusion on the enhanced feature representation to obtain a quality detection result; The global optimal detection parameter combination of the laser is solved according to the quality detection result and a laser adjustment control sequence is generated.

[0006] In a second aspect, the present invention provides a wavelength precision adjustment device based on an angle sensor, the wavelength precision adjustment device based on an angle sensor comprising: An initialization module, used to initialize the laser based on an initial detection parameter combination and obtain spatial position mapping data of the angle sensor and the detection beam; A calculation module, used to calculate an angle deviation matrix and establish an angle-reflection intensity relationship mapping table according to the spatial position mapping data; A generating module, used for generating a compensation detection parameter combination of the laser based on the angle deviation matrix and the angle-reflection intensity relationship mapping table; A detection module, used for performing spiral scanning detection based on the compensation detection parameter combination to obtain an initial feature representation, and performing feature enhancement to obtain an enhanced feature representation; An analysis module, used to perform multi-dimensional index analysis and fusion on the enhanced feature representation to obtain a quality detection result; A solution module is used to solve the global optimal detection parameter combination of the laser according to the quality detection result and generate a laser adjustment control sequence.

[0007] A third aspect of the present invention provides a laser, which is used to execute the above-mentioned wavelength precise adjustment method based on the angle sensor.

[0008] A fourth aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores instructions, which, when executed on a computer, enable the computer to execute the above-mentioned method for precise wavelength adjustment based on an angle sensor.

[0009] In the technical solution provided by the present invention, by establishing a spatial position mapping relationship between the angle sensor and the detection light beam, the detection light beam is accurately positioned and energy controlled in combination with an automatic power control circuit, thereby improving the stability and reliability of the detection system; a dual feedback mechanism of an angle deviation matrix and an angle-reflection intensity relationship mapping table is adopted to achieve dynamic adjustment of wavelength compensation and energy density threshold, thereby ensuring the optimal configuration of detection parameters; a detection strategy of spiral scanning and multi-dimensional feature enhancement is utilized to obtain more comprehensive and accurate feature information, thereby improving the spatial resolution and feature extraction capability of the detection; through local feature subspace division and multi-dimensional indicator analysis methods, accurate quality assessment and grading are achieved, thereby enhancing the credibility of the detection results; based on the solution of the global optimal detection parameter combination and the control sequence generation mechanism, a complete parameter optimization and control strategy is established to ensure the intelligence and automation level of the detection process.

[0010] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0011] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 A schematic diagram of an embodiment of a method for accurately adjusting wavelength based on an angle sensor in an embodiment of the present invention; Figure 2 Schematic diagram of an embodiment of a wavelength precision adjustment device based on an angle sensor in an embodiment of the present invention. DETAILED DESCRIPTION

[0013] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0014] The terms "including" and "having" and any variations thereof mentioned in the embodiments of the present invention are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device end including a series of steps or units is not limited to the listed steps or units, but may optionally include other steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or device ends.

[0015] To facilitate understanding of this embodiment, a wavelength precise adjustment method based on an angle sensor disclosed in an embodiment of the present invention is first described in detail. Figure 1 As shown, the method comprises the following steps: 101. Initialize the laser based on the initial detection parameter combination, and obtain spatial position mapping data of the angle sensor and the detection beam; It is understandable that the execution subject of the present invention may be a wavelength precision adjustment device based on an angle sensor, or may be a terminal or a server, which is not specifically limited here. The embodiment of the present invention is described by taking a server as the execution subject as an example.

[0016] Specifically, the wavelength parameter, power parameter and angle parameter in the initial detection parameter combination are quantified respectively to determine the working conditions of the laser in the initial state to ensure that the system can be effectively controlled and adjusted. By quantifying the wavelength, power and angle, a stable initial working state is obtained, which is input as the basic state into the proportional integral control unit of the automatic power control circuit. On this basis, the output power of the laser will be subject to closed-loop feedback control, and the power value of the detection beam is obtained by real-time detection of the output power of the laser. Based on the power value of the detection beam, a detection beam for measurement is generated, and the energy density distribution of the detection beam is measured according to a preset power threshold to obtain an energy density distribution measurement result. The energy density distribution measurement result is input into the modulation unit of the automatic power control circuit to obtain the energy distribution curve of the beam. The uniformity and stability of the laser output are monitored by detecting the energy density and distribution of the beam, and the optimization of the beam energy is achieved by adjusting the modulation unit to ensure that the characteristics of the detection beam meet the expected standards. The emission angle of the detection beam is matched with the receiving angle of the angle sensor in real time, and the angle data of the detection beam in space is obtained through the high-speed sampling circuit of the angle sensor to ensure that the angle matching relationship between the detection beam and the angle sensor can reflect the dynamic changes of the system in real time. The spatial angle data is subjected to noise reduction filtering and data smoothing. By filtering out the random noise in the angle data and smoothing the data, a more stable and representative angle detection curve is obtained. Based on the angle detection curve, the emission angle and the receiving angle of the detection beam are mapped to spatial coordinates to obtain the position feature points of the angle sensor in space, which are used to describe the propagation path of the laser emission beam in space and its corresponding angle information. The spatial position feature points are spatially discretized according to the sampling interval of the angle sensor to construct an initial spatial mapping model. The initial spatial mapping model describes the position change law of the laser emission beam in space and its corresponding relationship with the angle sensor. The initial spatial mapping model is subjected to spatial curvature analysis and feature enhancement processing. By analyzing the curvature of the spatial position feature points, the curvature change of the beam propagation path in space can be better understood, so as to achieve more precise control over the adjustment of the laser. Feature enhancement processing strengthens the details of the model so that it can better reflect the actual propagation characteristics of the laser beam.

[0017] 102. Calculate the angle deviation matrix according to the spatial position mapping data and establish an angle-reflection intensity relationship mapping table; Specifically, the angle sensor receiving signal strength in the spatial position mapping data is threshold segmented and calibrated to determine the angle reference data. By threshold segmenting the received signal, noise signals and interference data are effectively eliminated, and only valid signals are retained, while the maximum value calibration ensures that the selected signal strength is representative and stable, forming the angle reference data. The angle reference data is rearranged in sequence according to the scanning interval of the angle sensor to form an ordered angle signal, and the missing data is supplemented by linear interpolation to obtain a complete and continuous angle sequence. The continuous angle sequence is scanned point by point and the difference is calculated according to the sampling points of the angle sensor to obtain the angle deviation data. The point-by-point scanning process can refine the calculation of the angle deviation, ensure that the angle change of each sampling point is accurately captured, and provide more accurate angle deviation information. The angle deviation data is imported into the angle error correction module, and the angle error curve is corrected by using the polynomial fitting method. The polynomial fitting method effectively corrects the original angle error, compensates for the deviation caused by various environmental factors or mechanical errors, and obtains the compensated angle deviation value. The compensated angle deviation value is reconstructed into a two-dimensional matrix to generate a two-dimensional reconstruction matrix describing the angle deviation. By matrixing the data, the one-dimensional angle deviation information is converted into two-dimensional spatial information. The reconstructed two-dimensional matrix is ​​filled and smoothed to eliminate the mutation or discontinuity at the matrix boundary to obtain the angle deviation matrix. The reflected light intensity is collected at each matrix element position of the angle deviation matrix, and the reflection intensity at each position is measured by a photoelectric detector to obtain the reflection intensity matrix. The reflection intensity matrix and the angle deviation matrix jointly reflect the relationship between the angle change and the reflected light intensity. The angle deviation matrix and the reflection intensity matrix are synchronously mapped to obtain a mapping point pair containing angle and reflection intensity. The mapping point pair contains reflection intensity information at different angles, which is used to describe the corresponding relationship between angle and reflection intensity. The mapping point pair is segmented and the outliers are removed to obtain a valid mapping data pair. The valid mapping data pair is partitioned and feature extracted. By statistically analyzing the mapping data in different intervals, the feature information between angle and reflection intensity in different intervals is extracted. Through this process, the changing law between angle and reflection intensity in different intervals is found, thereby describing the relationship between them. Based on these feature information, a mapping rule is constructed according to the corresponding relationship between angle and reflection intensity to obtain an angle-reflection intensity relationship mapping table.

[0018] 103. Generate a compensation detection parameter combination of the laser based on the angle deviation matrix and the angle-reflection intensity relationship mapping table; Specifically, the angle deviation values ​​in the angle deviation matrix are normalized, and the angle deviation values ​​are converted into a relatively uniform scale to eliminate the calculation deviation caused by inconsistent dimensions. Combined with the weight adjustment factor of the wavelength, the adjusted angle deviation data is converted into an angle deviation compensation weight, which is used to characterize the contribution of each angle deviation to the wavelength adjustment process. The angle deviation compensation weight is imported into the wavelength control module of the laser, and combined with the wavelength characteristic curve of the laser, a first wavelength compensation parameter is generated. The wavelength characteristic curve describes the correspondence between the laser wavelength and various control factors. By combining the angle deviation compensation weight and the wavelength characteristic curve, a first wavelength compensation parameter matching the laser output is generated. These compensation parameters are used to preliminarily adjust the wavelength of the detection beam to optimize the beam characteristics. During the adjustment process, the feedback data of the angle sensor is collected to obtain a wavelength compensation effect value, which reflects the real-time response of the angle sensor during the wavelength adjustment process and can be used to judge the quality of the adjustment effect. The wavelength compensation effect value is compared with the initial angle deviation, and a compensation correction coefficient is generated by an error analysis method to obtain a second wavelength compensation parameter. The comparison process effectively evaluates the accuracy of the initial wavelength adjustment, and obtains a more accurate compensation correction coefficient through quantitative analysis of the error. Using this correction coefficient, the initial wavelength compensation parameter is corrected to obtain a second wavelength compensation parameter that is more in line with actual needs. While adjusting the wavelength compensation parameter, the reflection intensity data in the angle-reflection intensity relationship mapping table is calibrated according to the range of the photoelectric detector, and the reference value of the reflection intensity is set to obtain the reference point of the energy density. The calibration of the reflection intensity can ensure that the measured data maintains a linear response within the range of the photoelectric detector, avoiding measurement distortion caused by range overrun or data saturation. At the same time, the reflection intensity reference value is set to clarify the reference level of the energy density to ensure that the energy output during the adjustment process achieves the expected effect, thereby providing a stable energy reference for wavelength adjustment. The energy density reference point is matched with the detection lower and upper limits of the photoelectric detector, and a multi-level energy density control point is obtained by the interval segmentation method, and an energy density threshold is generated accordingly. The energy density threshold is used to characterize the variation law of the beam energy in different intervals, and can effectively control beams of different energy levels. By setting a multi-level energy density control point, the energy output of the beam is finely adjusted at different energy levels to meet the different requirements for beam energy during the wavelength adjustment process. The second wavelength compensation parameter is associated and matched with the energy density threshold to form an optimal parameter configuration and obtain a compensation detection parameter combination.

[0019] 104. Perform spiral scanning detection based on the compensation detection parameter combination to obtain an initial feature representation, and perform feature enhancement to obtain an enhanced feature representation; Specifically, the compensation detection parameter combination is input into the control unit of the laser, and the laser control unit generates a spiral scanning path sequence according to the set scanning strategy. In this process, the generation of the spiral scanning path follows the order from the inner ring to the outer ring to ensure the comprehensiveness and uniformity of the coverage. Through the spiral scanning path sequence, the laser control unit accurately controls the motion trajectory of the detection beam to form continuous scanning trajectory points to describe the path of the laser beam. The scanning trajectory points are sampled in an angle step, and the reflected light intensity signal of each sampling point is collected by the angle sensor, and these signals are synchronously recorded to obtain the reflected signal data. The reflected signal data is associated and mapped with the position information of the scanning trajectory points, and the overall morphology is reconstructed through the corresponding relationship between the reflected light intensity and the position to obtain the initial feature representation. The initial feature representation describes the basic morphological information of the measured object, including the degree of smoothness and the convex and concave inequality characteristics. The initial feature representation is layered according to different wavelength ranges to obtain layered wavelength feature data. The layered wavelength feature data is associated with the spatial position of the detection beam, and the morphological features are extracted to obtain spatial distribution feature data. Feature selection and weight allocation are performed on the layered wavelength feature data to obtain enhanced wavelength feature data. The most representative features are extracted from multi-level data to reduce data redundancy and improve the efficiency and accuracy of analysis. By assigning corresponding weights to these features, the influence of important features is highlighted to obtain enhanced wavelength feature data. At the same time, regional clustering and boundary enhancement are performed on the spatial distribution feature data to obtain enhanced spatial feature data. Regional clustering is used to cluster spatial regions with similar characteristics to facilitate the distinction of different regional features in subsequent analysis, while boundary enhancement can more clearly define the boundaries of each region, making the enhanced spatial feature data have higher resolution and better interpretability. The enhanced wavelength feature data and the enhanced spatial feature data are combined and reconstructed to obtain enhanced feature representation.

[0020] 105. Perform multi-dimensional index analysis and fusion on the enhanced feature representation to obtain quality detection results; Specifically, the enhanced feature representation is gridded according to the structure of the morphology, and the entire area is divided into multiple local feature subspaces by using a uniform grid segmentation method to obtain a subspace distribution structure. Wavelength features are extracted for each local feature subspace in the subspace distribution structure. By analyzing the wavelength response data, the wavelength change feature points at different positions are identified, and the wavelength feature index is obtained, which reflects the response characteristics to the wavelength in different regions and helps understand the propagation behavior and local characteristics of the laser. In order to analyze these features, the wavelength feature index is analyzed for spatial continuity, and the morphology change law between regions is obtained by associating local adjacent features to obtain the morphology feature index, revealing how it changes in space, especially the distribution of convexities, depressions or other structural features. The reflected light intensity data in the morphology feature index is hierarchically counted, and by analyzing the distribution law of light intensity, the defect feature points that exist can be identified, and the light intensity feature index is obtained. The introduction of the light intensity feature index helps to identify and locate abnormal areas, such as cracks, depressions or pollution, which often affect the propagation and reflection of the laser. The wavelength characteristic index, morphology characteristic index and light intensity characteristic index are combined, and a characteristic evaluation system is constructed through multi-dimensional characteristic correlation analysis to obtain the local characteristic score. The local characteristic score reflects the performance of each subspace in each characteristic dimension. Based on the local characteristic score, a multi-level evaluation is performed to construct the local quality evaluation index. The local quality evaluation can effectively classify and evaluate the quality of different regions by comprehensively scoring each feature, and identify the regions with good performance and defects. The local quality evaluation index is spatially reconstructed and the data is merged to obtain the global quality distribution map, which reflects the difference in quality between different regions. According to the preset quality grade standard, the global quality distribution map is graded and the quality inspection results are output. The quality is divided into different grades to facilitate a better understanding of the overall quality performance. Through the grade division, it is identified which areas meet the quality requirements and which areas need improvement.

[0021] 106. Solve the global optimal detection parameter combination of the laser according to the quality detection result and generate the laser adjustment control sequence.

[0022] Specifically, a multi-dimensional data analysis is performed on the quality detection results, and the weight relationship of parameters such as wavelength, power and angle that affect the quality is identified by analyzing the various factors affecting the quality. By decomposing the quality influencing factors, the weight coefficients of wavelength parameters, power parameters and angle parameters are obtained, that is, the importance of each parameter in affecting the quality, and the parameter influence weight is obtained. The parameter influence weight is associated with the initial detection parameter combination, and the adjustment range of each parameter is determined by calculating the parameter sensitivity to obtain the parameter optimization interval. The wavelength parameters, power parameters and angle parameters in the parameter optimization interval are combined and traversed, and the candidate parameter sequence is obtained by the multi-parameter joint optimization method. Multi-parameter joint optimization is a process of traversing all possible parameter combinations, and by trying different parameter combinations one by one, the candidate parameter sequence that best meets the quality requirements is found. The candidate parameter sequence is cross-validated with the quality detection results, and the optimal parameter group is screened out through the matching analysis of the quality indicators to obtain the global optimal detection parameter combination. The global optimal detection parameter combination is stability checked to ensure its stability in practical applications. Through the method of parameter perturbation analysis, each parameter is perturbed slightly, and based on these analysis results, parameter adjustment rules are constructed to obtain the final parameter adjustment scheme. The formulation of the parameter adjustment scheme aims to enable the laser to maintain accurate adjustment of wavelength, power and angle under different working environments. The parameter adjustment scheme is decomposed in time sequence according to the response characteristics of the laser, and a control step sequence is generated by controlling the timing arrangement to obtain the control execution timing. The generation of the control step sequence is to ensure that the changes of various parameters of the laser during the adjustment process can be coordinated to avoid distortion of the adjustment effect due to too fast or too slow changes in a certain parameter. By decomposing the timing of the parameter adjustment scheme, the specific time point and step length of each adjustment operation are clarified, making the adjustment process more accurate and smooth. The control execution timing is encoded with control instructions. Through the conversion of the instruction mapping table, the corresponding wavelength control instructions, power control instructions and angle control instructions are generated to obtain sub-item control instructions. These sub-item control instructions adjust and control the wavelength, power and angle of the laser respectively, ensuring that each key parameter can be adjusted according to the predetermined strategy. The sub-item control instructions are integrated in the execution order to obtain the laser adjustment control sequence, which describes the specific content and execution time of each step of the laser operation in the adjustment process.

[0023] In the embodiment of the present invention, by establishing a spatial position mapping relationship between the angle sensor and the detection light beam, the detection light beam is accurately positioned and energy controlled in combination with an automatic power control circuit, thereby improving the stability and reliability of the detection system; a dual feedback mechanism of an angle deviation matrix and an angle-reflection intensity relationship mapping table is adopted to achieve dynamic adjustment of wavelength compensation and energy density threshold, thereby ensuring the optimal configuration of detection parameters; a detection strategy of spiral scanning and multi-dimensional feature enhancement is utilized to obtain more comprehensive and accurate feature information, thereby improving the spatial resolution and feature extraction capability of the detection; through local feature subspace division and multi-dimensional indicator analysis methods, accurate quality assessment and grading are achieved, thereby enhancing the credibility of the detection results; based on the solution of the global optimal detection parameter combination and the control sequence generation mechanism, a complete parameter optimization and control strategy is established to ensure the intelligence and automation level of the detection process.

[0024] In a specific embodiment, the process of executing step 101 may specifically include the following steps: The wavelength parameter, power parameter and angle parameter in the initial detection parameter combination are quantized respectively to obtain an initial working state, and the initial working state is input into a proportional integral control unit of an automatic power control circuit to perform closed-loop feedback control on the output power of the laser to obtain a detection beam power value; Generate a detection beam based on the detection beam power value, measure the energy density distribution of the detection beam according to a preset power threshold, obtain an energy density distribution measurement result, and input the energy density distribution measurement result into a modulation unit of an automatic power control circuit to obtain a beam energy distribution curve; The emission angle of the detection beam is matched with the receiving angle of the angle sensor in real time, and the spatial angle data is obtained through the high-speed sampling circuit of the angle sensor; Perform noise reduction filtering and data smoothing on the spatial angle data to obtain an angle detection curve, and perform spatial coordinate mapping on the emission angle and the receiving angle of the detection beam based on the angle detection curve to obtain the spatial position feature points of the angle sensor; The spatial position feature points are spatially discretized according to the sampling interval of the angle sensor to obtain an initial spatial mapping model, and the initial spatial mapping model is subjected to spatial curvature analysis and feature enhancement processing to obtain spatial position mapping data.

[0025] Specifically, the wavelength parameter, power parameter and angle parameter in the initial detection parameter combination are quantized respectively, and the continuous physical quantity is converted into an operable discrete value. Assume that the wavelength parameter is , the power parameter is , the angle parameter is , by appropriately quantizing these parameters, the quantized initial working state is obtained. The quantization formula is expressed as: ; in, It is The value of the quantization level, Indicates the current physical parameter value (such as λ, or ), and are the minimum and maximum values ​​of the parameters, is the number of quantization levels. Through this quantization formula, the continuous wavelength, power and angle parameters are converted into discrete working states to form a stable and repeatable initial working state. The quantized initial working state is input into the proportional integral control unit (PI controller) of the automatic power control circuit to perform closed-loop feedback control on the output power of the laser. The purpose of closed-loop feedback control is to control the output power of the laser. Keep it near the set value to avoid power fluctuations caused by the environment or other factors. The control rule of PI control is: ; in, is the control signal, is the proportional gain, is the integral gain, The PI controller automatically adjusts the laser power output to obtain a stable detection beam power value. Based on the detection beam power value Generate a detection beam and measure the energy density distribution of the detection beam according to a preset power threshold. By measuring the energy density distribution, the energy density distribution measurement result is obtained. The measurement result is input into the modulation unit in the automatic power control circuit to generate the energy distribution curve of the light beam, which reflects the energy distribution of the laser beam in space and ensures that the energy output of the laser beam meets the expected requirements of the system. Receiving angle with angle sensor Real-time matching is performed, and spatial angle data is acquired through the high-speed sampling circuit of the angle sensor. The function of the high-speed sampling circuit is to collect the spatial angle changes of the detection light beam at a high frequency, so as to achieve precise control of the angle matching. In order to improve the accuracy of the data, the acquired spatial angle data is subjected to noise reduction filtering and data smoothing. The purpose of noise reduction filtering is to remove random noise in the angle data and ensure the purity of the data, which is achieved by using a low-pass filter. Data smoothing is to smooth the angle data through a certain mathematical algorithm (such as the moving average method) to eliminate short-term jitter in the data and obtain a more continuous and stable angle detection curve. Based on the angle detection curve, the emission angle and the receiving angle of the detection light beam are mapped to spatial coordinates to obtain the spatial position feature points of the angle sensor. Assume that the spatial position of the detection beam is given by Coordinate representation, angle data Associated with the position coordinates to form a set of spatial position feature points . These feature points are used to describe the propagation trajectory of the detection beam in space. The spatial position feature points are spatially discretized according to the sampling interval of the angle sensor to construct an initial spatial mapping model. Discretization is the process of converting continuous spatial position feature points into discrete coordinate grids. Through spatial discretization, a preliminary model describing the motion trajectory of the laser in space is obtained. The initial spatial mapping model is subjected to spatial curvature analysis and feature enhancement processing. The purpose of curvature analysis is to quantify the curvature of the detection beam propagating in space, so as to determine the degree of deflection of the beam at different positions. The curvature is calculated using the following formula: ; in, are the derivative and second-order derivative of the position coordinates, respectively. Represents the curvature value. Curvature analysis reveals the deflection points of the light beam during propagation, providing a basis for adjustment. Through feature enhancement processing, the key features in the spatial model are strengthened so that the model can better reflect the actual propagation characteristics of the laser beam. By processing the initial spatial mapping model, the spatial position mapping data is obtained.

[0026] In a specific embodiment, the process of executing step 102 may specifically include the following steps: Perform threshold segmentation and maximum value calibration on the angle sensor receiving signal strength in the spatial position mapping data to obtain angle reference data, and rearrange and linearly interpolate the angle reference data in sequence according to the scanning interval of the angle sensor to obtain a continuous angle sequence; Scan the continuous angle sequence point by point and calculate the difference according to the angle sensor sampling points to obtain the angle deviation data, and import the angle deviation data into the angle error correction module, correct the angle error curve by the polynomial fitting method, and obtain the compensated angle deviation value; Performing two-dimensional matrix reconstruction on the compensated angle deviation value to obtain a two-dimensional reconstruction matrix, performing boundary filling and smoothing processing on the two-dimensional reconstruction matrix to obtain an angle deviation matrix, and collecting reflected light intensity at each matrix element position of the angle deviation matrix, obtaining the corresponding reflection intensity measurement value through a photoelectric detector to obtain a reflection intensity matrix; The angle deviation matrix and the reflection intensity matrix are synchronously mapped to obtain mapping point pairs. The mapping point pairs are segmented and outliers are eliminated to obtain valid mapping data pairs. The valid mapping data pairs are partitioned and feature extracted. The mapping rules are constructed according to the corresponding relationship between angle and reflection intensity to obtain the angle-reflection intensity relationship mapping table.

[0027] Specifically, the angle sensor received signal strength in the spatial position mapping data is threshold segmented and the maximum value is calibrated. The signal strength is divided into valid signals and invalid signals according to a certain threshold, effectively eliminating noise data and retaining only signals with practical significance. Suppose the angle sensor received signal strength is , by choosing the threshold , the conditions for defining a valid signal are After threshold segmentation, the obtained signal strength is calibrated to determine the maximum value. The maximum value calibration process is expressed by the following formula: ; in, represents the normalized signal intensity, is the maximum value of the signal obtained by calibration. The purpose of normalization is to convert the signal strength into a relative value so that data of different strengths can be compared and processed uniformly. The angle reference data is rearranged and linearly interpolated according to the scanning interval of the angle sensor. After rearrangement, if there are missing points in the data, the missing parts are supplemented by linear interpolation to obtain a continuous angle sequence. The formula for linear interpolation is: ; in, It's time The corresponding interpolation angle is are the angle values ​​of the known adjacent data points, is the corresponding time. Through the interpolation method, a continuous angle sequence is formed. According to the sampling points of the angle sensor, the continuous angle sequence is scanned point by point, and the difference between adjacent points is calculated to obtain the angle deviation data. Assume that the angle value is , the calculation of the difference is expressed as: ; in, is the angle difference value of adjacent points. The angle deviation data reflects the change of angle at different positions, which is convenient for subsequent error correction. The angle deviation data is imported into the angle error correction module, and the angle error curve is corrected using the polynomial fitting method. Polynomial fitting uses a low-order polynomial to approximate the angle error curve. Suppose the fitting polynomial is: ; in, is the angle value obtained by fitting, are the fitted polynomial coefficients, is the independent variable, usually position or time. Through polynomial fitting, the error in the angle deviation curve is smoothed and corrected to obtain the compensated angle deviation value, so that the angle change during the adjustment process is smoother. The compensated angle deviation value is reconstructed into a two-dimensional matrix to obtain a two-dimensional reconstructed matrix that describes the angle change. The two-dimensional matrix is ​​boundary filled and data smoothed. Boundary filling is used to eliminate the discontinuity at the edge of the matrix, while smoothing can make the angle data inside the matrix more uniform to obtain an angle deviation matrix. The reflected light intensity is collected for each matrix element position of the angle deviation matrix, and the reflection intensity measurement value corresponding to each position is obtained through a photoelectric detector to generate a reflection intensity matrix. Assume that the reflected light intensity is , Represents the angle deviation matrix position The reflection intensity value on the surface. The function of the reflection intensity matrix is ​​to describe the reflection characteristics of light under different angle deviations. The angle deviation matrix and the reflection intensity matrix are synchronously mapped to obtain a series of mapping point pairs. . These mapping point pairs contain the correspondence between angle and reflected light intensity. The mapping point pairs are segmented and outliers are removed to obtain valid mapping data pairs. The purpose of outlier removal is to ensure the accuracy and reliability of the data, so that subsequent analysis results are more reliable. Partition statistics and feature extraction are performed on valid mapping data pairs. Partition statistics are used to independently analyze data in different regions, thereby revealing the characteristic differences between angles and reflection intensities in different regions. By extracting these feature data, the relationship mapping rules between angles and reflection intensity are constructed, and finally the angle-reflection intensity relationship mapping table is obtained.

[0028] In a specific embodiment, the process of executing step 103 may specifically include the following steps: Normalizing the angle deviation values ​​in the angle deviation matrix and adjusting the wavelength weights to obtain angle deviation compensation weights; The angle deviation compensation weight is imported into the laser wavelength control module, and a first wavelength compensation parameter is generated according to the wavelength characteristic curve of the laser; The wavelength of the detection light beam is adjusted according to the first wavelength compensation parameter, and feedback data of the angle sensor after adjustment is collected to obtain a wavelength compensation effect value; The wavelength compensation effect value is compared with the initial angle deviation, and a compensation correction coefficient is generated through error analysis to obtain a second wavelength compensation parameter; The reflection intensity data in the angle-reflection intensity relationship mapping table is calibrated according to the photoelectric detector range, and a reflection intensity reference value is set to obtain an energy density reference point; The energy density reference point is matched with the detection lower limit and upper limit of the photodetector, and multi-level energy density control points are obtained by interval segmentation to obtain the energy density threshold; The second wavelength compensation parameter and the energy density threshold are associated and matched and optimal parameter configuration is performed to obtain a compensation detection parameter combination.

[0029] Specifically, the angle deviation values ​​in the angle deviation matrix are normalized and the wavelength weights are adjusted. The purpose of normalization is to standardize the angle deviation values ​​so that their data values ​​fall within a uniform range, thereby eliminating the dimension difference and facilitating subsequent calculations. Suppose the angle deviation value is , the normalized angle deviation value It is expressed by the following formula: ; in, and are the minimum and maximum values ​​in the angle deviation matrix respectively. After normalization, the normalized angle deviation value and the wavelength adjustment weight are adjusted by wavelength weight. Multiply the product to get the angle deviation compensation weight ; in, Represents the weight factor of wavelength adjustment, which is used to control the degree of influence of angle on wavelength adjustment. The angle deviation compensation weight is an important parameter in the wavelength adjustment process, which quantifies the contribution of each angle deviation to wavelength adjustment. The angle deviation compensation weight is imported into the laser wavelength control module, and the first wavelength compensation parameter is generated by combining the wavelength characteristic curve of the laser. The wavelength characteristic curve describes the change of the output wavelength of the laser under different control signals. Assume that the wavelength characteristic curve is expressed by the following relationship: ; in, is the output wavelength, is a function describing the wavelength characteristic curve, is the power control parameter of the laser. By inputting the angle deviation compensation weight To the wavelength control module, combined with the power control parameters, generate the first wavelength compensation parameters , used to preliminarily adjust the wavelength of the detection beam so that the output wavelength meets the system's requirements for laser characteristics as much as possible. The wavelength of the detection beam is adjusted according to the first wavelength compensation parameter, and the feedback data of the angle sensor after adjustment is collected to obtain the wavelength compensation effect value By collecting the feedback data from the angle sensor, the real-time response of the laser after wavelength adjustment is obtained to determine whether the adjusted wavelength meets expectations. The wavelength compensation effect value is compared with the initial angle deviation, and the compensation correction coefficient is generated through error analysis. The purpose of error analysis is to quantify the deviation between the actual wavelength adjustment effect and the expected value, and to perform a secondary adjustment on the wavelength through the generated compensation correction coefficient to obtain a more accurate second wavelength compensation parameter. During the wavelength adjustment process, the reflection intensity data in the angle-reflection intensity relationship mapping table is calibrated. The photoelectric detector is used to detect the reflected light intensity. The calibration process is to ensure that the measurement result of the photoelectric detector is consistent with the actual reflected light intensity. Assume that the reflection intensity is , the range of the photodetector is , the calibrated reflection intensity It is expressed as: ; Normalization process normalizes the reflection intensity data to a value between 0 and 1. Set the reflection intensity reference value , used to determine the energy density reference point of the laser under specific conditions. The reference value is set based on the system's specific requirements for laser output energy, and this reference point is used to evaluate whether the laser output at different positions meets the requirements. The energy density reference point is matched with the detection lower and upper limits of the photodetector, and multi-level energy density control points are obtained through interval segmentation. These control points form energy density thresholds. The energy density threshold is used to describe the laser energy distribution in different areas. By dividing the energy density into multiple levels, it ensures that the laser output energy is kept within a reasonable range under different operating conditions, avoiding the negative impact of excessive or low power. and energy density threshold Perform correlation matching and optimal parameter configuration to obtain the final compensation detection parameter combination. The correlation matching process combines the wavelength compensation parameters and the energy density control points to ensure that the wavelength and energy output of the laser are consistent, thereby achieving the best adjustment effect. Through the optimal parameter configuration, a set of parameters is found in the multi-dimensional control space of the system to achieve the best output performance of the laser.

[0030] In a specific embodiment, the process of executing step 104 may specifically include the following steps: The compensation detection parameter combination is input into the laser control unit, a spiral scanning path sequence is generated in the order from the inner ring to the outer ring, and the detection beam movement is controlled according to the spiral scanning path sequence to obtain the scanning trajectory points; The scanning track points are sampled in an angle step, and the reflected light intensity signal of each sampling point is collected by an angle sensor and recorded synchronously to obtain the reflected signal data; The reflected signal data is correlated and mapped with the position information of the scanning trajectory points, and the topography is reconstructed through the corresponding relationship between the reflected light intensity and the position to obtain the initial feature representation; The initial feature representation is layered according to different wavelength ranges to obtain layered wavelength feature data, and the layered wavelength feature data is associated with the spatial position of the detection light beam and the morphological feature is extracted to obtain spatial distribution feature data; Performing feature selection and weight allocation on the layered wavelength feature data to obtain enhanced wavelength feature data, and performing regional clustering and boundary enhancement on the spatial distribution feature data to obtain enhanced spatial feature data; The enhanced wavelength feature data and the enhanced spatial feature data are combined and reconstructed to obtain an enhanced feature representation.

[0031] Specifically, the compensation detection parameter combination is input into the laser control unit to achieve precise adjustment of the laser. According to the set scanning strategy, the laser control unit generates a spiral scanning path sequence, which is gradually expanded from the inner ring to the outer ring to ensure full coverage of the entire wavelength-related device. The spiral scanning path is described by the polar coordinate formula: ; in, is the radius of the scan path, Indicates the scanning angle, and are the initial offset and step length parameters of the spiral path, respectively. Through this formula, a gradually expanding spiral trajectory is generated to control the laser detection beam to move along the preset path on the wavelength-related device to obtain the scanning trajectory points. The scanning trajectory points are sampled in an angle step to obtain the specific information of the reflected light intensity signal, so as to analyze the optical characteristics of . Assume that the angle of each sampling point is , the reflected light intensity signal of each sampling point is collected by the angle sensor, and the obtained signal is expressed as At the same time, each reflected light intensity signal collected is synchronously recorded with its corresponding position data, which constitutes a set of reflected signal data for subsequent morphology reconstruction. By associating and mapping the reflected signal data with the position information of the scanning trajectory points, the initial morphology of the wavelength-dependent device can be reconstructed based on the correspondence between the reflected light intensity and the spatial position. Assuming that the position of the wavelength-dependent device is given by The corresponding reflected light intensity is , the reconstructed initial feature representation is expressed as: ; in, Indicates the wavelength-dependent device at position In this way, a complete reflection characteristic diagram is generated, reflecting the optical characteristics of the wavelength-dependent device at different positions. The initial characteristics are layered according to different wavelength ranges to obtain layered wavelength characteristic data. Assume that the characteristic data corresponding to different wavelength ranges are , the data obtained after stratification processing is expressed as These data reflect the wavelength-dependent devices The reflective characteristics under the condition of light. The layered wavelength feature data is associated with the spatial position of the detection beam, and the morphological features of the wavelength-related devices are extracted to obtain spatial distribution feature data, which describes the spatial inhomogeneity of the wavelength-related devices and the law of change at different wavelengths, which helps to understand the optical properties of wavelength-related devices and judge the quality of materials. Feature selection and weight assignment are performed on the layered wavelength feature data to obtain enhanced wavelength feature data. The feature selection process is to extract the most representative features from multi-level data, thereby removing redundant information and ensuring efficient data processing. Different weights are assigned to the selected features to obtain enhanced wavelength feature data. Assuming the weight is , the enhanced wavelength characteristic data is expressed as: ; in, is the enhanced wavelength characteristic data, Assigned to wavelength feature weights. By weight distribution, feature data with a greater impact on quality are emphasized to enhance the sensitivity of detection. At the same time, regional clustering and boundary enhancement processing are performed on the spatially distributed feature data to obtain enhanced spatial feature data. Regional clustering is the aggregation of spatial regions with similar characteristics to facilitate subsequent feature analysis. For example, a density-based clustering algorithm (such as DBSCAN) is used to cluster data to identify different regional structures on wavelength-dependent devices. Boundary enhancement processing is used to emphasize the boundaries between different regions, making the spatial distribution of feature data clearer and facilitating subsequent analysis and understanding. The enhanced wavelength feature data and the enhanced spatial feature data are combined and reconstructed to obtain an enhanced feature representation of the wavelength-dependent device. The enhanced feature representation includes the comprehensive characteristics of the wavelength-dependent device at different wavelengths and different spatial positions, and can more comprehensively and accurately describe the optical characteristics of the wavelength-dependent device.

[0032] Among them, feature selection and weight allocation are performed on the layered wavelength feature data to obtain enhanced wavelength feature data, and regional clustering and boundary enhancement are performed on the spatial distribution feature data to obtain enhanced spatial feature data, including: characteristic intensity calculation is performed on each layer of wavelength data in the layered wavelength feature data, and effective wavelength features are extracted through light intensity threshold screening to obtain wavelength feature intensity values; wavelength feature intensity values ​​are graded according to light intensity, and corresponding weight coefficients are set for each grade to obtain a wavelength feature weight table; weight coefficients in the wavelength feature weight table are normalized, and weight distribution is adjusted according to wavelength response characteristics to obtain an optimized weight sequence; the optimized weight sequence is weightedly combined with the layered wavelength feature data to highlight the main wavelength features according to the weight size to obtain enhanced Strong wavelength feature data; block the spatial distribution feature data according to the regional structure, divide the feature clustering area according to the feature distribution density, and obtain the regional clustering result; extract the boundary points in the regional clustering result, determine the boundary range according to the morphological characteristics, and obtain the boundary feature points; perform spatial connection processing on the boundary feature points, construct the boundary contour according to the positional relationship between the feature points, and obtain the initial boundary line; smooth the initial boundary line, optimize the boundary shape according to the structural characteristics, and obtain the enhanced boundary line; perform feature fusion on the enhanced boundary line and the regional clustering result, reconstruct the boundary feature according to the spatial distribution law, and obtain the enhanced spatial feature; verify the feature integrity of the enhanced spatial feature, confirm the feature enhancement effect according to the morphological requirements, and obtain the enhanced spatial feature data.

[0033] In a specific embodiment, the process of executing step 105 may specifically include the following steps: The enhanced feature representation is meshed according to the morphological structure, and the region is divided into multiple local feature subspaces by a uniform mesh segmentation method to obtain the subspace distribution structure; Extract wavelength features from each local feature subspace in the subspace distribution structure, obtain wavelength change feature points through wavelength response data analysis, and obtain wavelength feature indicators; The spatial continuity analysis of wavelength characteristic index is carried out, and the regional morphological change law is obtained through the local adjacent characteristic association processing to obtain the morphological characteristic index; The reflected light intensity data in the morphological characteristic index is statistically graded, and the defect characteristic points are obtained by analyzing the light intensity distribution law to obtain the light intensity characteristic index; The wavelength characteristic index, morphology characteristic index and light intensity characteristic index are combined, and a characteristic evaluation system is constructed through multi-dimensional characteristic correlation analysis to obtain a local characteristic score; Perform multi-level quality evaluation on local feature scores, construct local quality evaluation indicators, and perform spatial reconstruction and data merging on local quality evaluation indicators to obtain a global quality distribution map; The global quality distribution map is graded according to the preset quality grade standard and the quality inspection results are output.

[0034] Specifically, the enhanced feature representation is gridded, and the entire region is divided into multiple local feature subspaces by uniform grid segmentation. Suppose the region is , which is divided into sub-regions, each sub-region is recorded as ,in and Represent the row and column numbers of the subspace respectively. Through grid division, the complex features are decomposed into multiple local feature subspaces, so that the features in each subspace can be analyzed and processed independently. Wavelength features are extracted for each local feature subspace in the subspace distribution structure, and the response of each subspace at different wavelengths is analyzed to determine the characteristic changes of the region at different wavelengths. Assume that the wavelength response data is , for each subspace Analyze and obtain the characteristic points of wavelength change These feature points are used to describe the optical behavior of each subspace under different wavelength conditions and ultimately form wavelength characteristic indicators. Wavelength characteristic indicators help evaluate the reflection and absorption characteristics at different wavelengths. The wavelength characteristic indicators are subjected to spatial continuity analysis to obtain the morphological change law of the region. Through the association processing of local adjacent features, the spatial relationship between each local feature subspace is analyzed and the continuity of the morphology is determined. Suppose two adjacent subspaces are and , and their wavelength characteristic points are and By calculating the difference between adjacent feature points , describing the changes between adjacent regions: ; This difference reveals the change trend between adjacent subspaces. By correlating all adjacent subspaces, a complete morphological feature index is obtained to describe the change of wavelength-related devices in different spatial regions, such as convex and concave morphological features. The reflected light intensity data contained in the morphological feature index is hierarchically counted to obtain the defect feature points on the wavelength-related device. By analyzing the distribution law of reflected light intensity, the abnormal area in the wavelength-related device is identified. Suppose the reflected light intensity data is By counting the reflected light intensity data in each subspace, it is determined whether there is an abnormal reflection phenomenon in the area, such as too high or too low reflection intensity, which means there is a defect or pollution. Through analysis, the defect feature points of the wavelength-related device are extracted to form the light intensity feature index. The wavelength feature index, morphology feature index and light intensity feature index are combined to construct a feature evaluation system for multi-dimensional feature correlation analysis. Assume that each feature index is ,and , the score of the feature evaluation system is calculated by the following weighted formula: ; in, Subspace The local feature score of They are the weight factors of wavelength characteristics, morphology characteristics and light intensity characteristics respectively. The weight setting is adjusted according to actual needs to highlight the characteristics that have a greater impact on the overall quality. Through the above calculations, the local feature score of each subspace is obtained to quantify the quality of each local area. A multi-level quality evaluation is performed on the local feature score to construct a local quality evaluation index. The feature score of each local subspace is classified to determine the quality level of the area. For example, the feature score is divided into multiple levels, such as excellent, good, medium, poor, etc. The local quality evaluation index is spatially reconstructed and the data is merged to obtain a global quality distribution map of the entire wavelength-related device. ,in Represents the spatial coordinates on the wavelength-dependent device. According to the preset quality grade standard, the global quality distribution map is graded to output the final quality test results. The preset quality grade standard is set according to the quality requirements in a specific application scenario. For example, in precision optical devices, the surface quality is required to meet a certain standard to ensure optical performance. By grading the global quality distribution map, it is determined which areas meet the quality requirements and which areas need to be corrected or further processed.

[0035] Among them, a multi-level quality evaluation is performed on the local feature scores, a local quality evaluation index is constructed, and the local quality evaluation index is spatially reconstructed and data merged to obtain a global quality distribution map; the global quality distribution map is graded according to the preset quality grade standard, and the quality detection result is output, including: the local feature scores are layered according to the regional location, and the evaluation standards are set according to the detection requirements of different regions to obtain a layered evaluation benchmark; the layered evaluation benchmark is compared and analyzed with the local feature scores, and the quality indicators of each layer are determined according to the regional feature scores to obtain local quality evaluation data; the neighborhood feature correlation analysis is performed on the local quality evaluation data, and the evaluation weight is adjusted according to the score difference of adjacent regions to obtain the local quality evaluation index; the local quality evaluation index is located and mapped according to the spatial structure, and a spatial correlation map is established according to the regional distribution relationship to obtain to the quality distribution structure; perform data normalization on the evaluation indicators in the quality distribution structure, unify the evaluation scale according to the indicator value range, and obtain the standardized quality indicators; perform interpolation and reconstruction on the standardized quality indicators in the spatial position, fill the blank areas according to the spatial continuity requirements, and obtain the continuous quality distribution; merge the regional data of the continuous quality distribution, integrate the local features according to the quality integrity requirements, and obtain the global quality distribution map; compare the quality indicators in the global quality distribution map with the preset quality grade thresholds, determine the quality grade boundaries according to the grading rules, and obtain the initial grading results; perform boundary optimization on the initial grading results, adjust the grading boundaries according to the continuity requirements of the quality grades, and obtain the optimized grading map; output the optimized grading map according to the quality inspection standards, generate a quality inspection report according to the grading statistical results, and obtain the quality inspection results.

[0036] In a specific embodiment, the process of executing step 106 may specifically include the following steps: Perform multi-dimensional data analysis on the quality inspection results, obtain the weight coefficients of wavelength parameters, power parameters and angle parameters by decomposing the quality influencing factors, and obtain the parameter influencing weights; The parameter influence weights are combined with the initial detection parameters for correlation analysis, and the adjustment range of each parameter is determined by parameter sensitivity calculation to obtain the parameter optimization interval; The wavelength parameters, power parameters and angle parameters within the parameter optimization interval are combined and traversed, and a candidate parameter sequence is obtained through multi-parameter joint optimization. The candidate parameter sequence is cross-validated with the quality detection results, and the optimal parameter group is screened through quality indicator matching analysis to obtain the global optimal detection parameter combination; The stability of the global optimal detection parameter combination is checked, and the parameter adjustment rules are constructed through parameter perturbation analysis to obtain the parameter adjustment scheme. The parameter adjustment scheme is then decomposed in time sequence according to the response characteristics of the laser, and a control step sequence is generated through control timing arrangement to obtain the control execution timing. The control execution sequence is encoded with control instructions, and wavelength control instructions, power control instructions and angle control instructions are generated through instruction mapping table conversion to obtain sub-item control instructions, which are then integrated in execution order to obtain a laser adjustment control sequence.

[0037] Specifically, multi-dimensional data analysis is performed on the quality inspection results to identify the key factors affecting the quality. The weight coefficients of wavelength parameters, power parameters and angle parameters are extracted by decomposing the quality influencing factors. Suppose the quality inspection result is , including many influencing factors, such as wavelength ,power and angle Through multiple regression analysis, the influence of these parameters on quality is shown: ; in, are the weight coefficients of wavelength, power and angle parameters respectively, Represents the random error of the system. These weight coefficients are obtained through regression analysis, and the influence of each parameter on the quality is quantified to obtain the parameter influence weight. The parameter influence weight is combined with the initial detection parameters for correlation analysis to determine the sensitivity of each parameter to the quality. By calculating the sensitivity of the parameters, it is identified which parameter change has the greatest impact on the quality, and the adjustment range of each parameter is determined to obtain the optimization range of the parameters. Assume that the initial values ​​of the wavelength, power and angle parameters are , and its optimization interval is expressed as: ; ; ; in, Respectively represent the adjustment range of wavelength, power and angle parameters. These parameter optimization intervals are determined by sensitivity analysis, with the aim of ensuring that the adjustment of each parameter has a positive impact on the quality while avoiding over-adjustment or under-adjustment. The wavelength, power and angle parameters within the parameter optimization interval are combined and traversed, and a candidate parameter sequence is obtained by a multi-parameter joint optimization method. Find a set of optimal parameter combinations to achieve the best quality level. Let the candidate parameters be , by traversing all possible combinations, a series of candidate parameter sequences are obtained. The candidate parameter sequences are cross-validated with the quality test results, and the optimal parameter group is screened out by analyzing the matching degree of quality indicators. Let the quality indicator be , the matching degree is calculated by the following formula: ; in, For the The matching degree of the parameter combination, is the target quality indicator, is the number of detections. By calculating the matching degree of all candidate parameter combinations, the parameter group with the smallest matching degree is screened out, which is the global optimal detection parameter combination. The global optimal detection parameter combination is stability checked to ensure the reliability of the combination under different conditions. The stability check is achieved through parameter perturbation analysis, that is, a small perturbation is performed on each parameter to observe the change in quality. Through perturbation analysis, parameter adjustment rules are constructed to obtain a stable parameter adjustment scheme. On this basis, the parameter adjustment scheme is time-sequentially decomposed according to the response characteristics of the laser, and a control step sequence is generated through control timing arrangement to obtain the control execution sequence. The generation of the control step sequence ensures that the adjustment step and time interval of each parameter match to avoid system instability caused by sudden changes in the adjustment process. The control execution sequence is encoded with control instructions to achieve specific control of the laser. Each adjustment action is converted into a corresponding control instruction, and the instruction is mapped into specific wavelength control instructions, power control instructions, and angle control instructions through the instruction mapping table, which are respectively. These sub-item control instructions are used to adjust the various parameters of the laser to ensure that its output meets the expected requirements. The sub-item control instructions are integrated in the execution order to obtain a complete laser adjustment control sequence. ,This control sequence includes the adjustment process of all parameters, which can effectively control the laser to achieve precise adjustment of wavelength, power and angle.

[0038] Among them, the wavelength parameters, power parameters and angle parameters in the parameter optimization interval are combined and traversed, and a candidate parameter sequence is obtained through multi-parameter joint optimization, and the candidate parameter sequence is cross-validated with the quality detection result, and the optimal parameter group is screened through quality indicator matching analysis to obtain the global optimal detection parameter combination, including: discretizing the wavelength parameter optimization interval according to the wavelength adjustment accuracy, determining the wavelength sampling point according to the wavelength adjustment characteristics, and obtaining the wavelength parameter sequence; segmentally sampling the power parameter optimization interval according to the power control accuracy, setting the sampling interval according to the power stability requirement, and obtaining the power parameter sequence; uniformly sampling the angle parameter optimization interval according to the angle control resolution, determining the angle value point according to the angle adjustment range, and obtaining the angle parameter sequence; performing three-dimensional combination of the wavelength parameter sequence, the power parameter sequence and the angle parameter sequence, and obtaining the angle parameter sequence according to the parameter The constraint relationship between them is used to generate a valid parameter group to obtain an initial parameter combination; the initial parameter combination is input into the parameter verification module, and unreasonable parameter combinations are eliminated according to the system response characteristics to obtain a candidate parameter sequence; the correspondence analysis is performed on each group of parameters in the candidate parameter sequence and the quality detection result, and the matching degree is calculated according to the quality index requirements to obtain the parameter matching degree; the parameter matching degrees are sorted according to the numerical values, and the screening threshold is set according to the quality detection standard to obtain a high-matching parameter group; parameter stability analysis is performed on the high-matching parameter group, and the parameter reliability is determined according to the parameter fluctuation range to obtain a stable parameter combination; multiple rounds of quality verification are performed on the stable parameter combination, and the repeatability of the parameter combination is evaluated according to the verification results to obtain a high-quality parameter group; a comprehensive performance evaluation is performed on the high-quality parameter group, and the optimal parameter configuration is determined according to the multi-dimensional quality index to obtain the global optimal detection parameter combination.

[0039] The above describes the wavelength precise adjustment method based on the angle sensor in the embodiment of the present invention. The following describes the wavelength precise adjustment device based on the angle sensor in the embodiment of the present invention. Figure 2 In one embodiment of the present invention, a wavelength precision adjustment device based on an angle sensor includes: Initialization module 201, used to initialize the laser based on the initial detection parameter combination and obtain spatial position mapping data of the angle sensor and the detection beam; A calculation module 202, used to calculate an angle deviation matrix and establish an angle-reflection intensity relationship mapping table according to the spatial position mapping data; A generating module 203, used to generate a compensation detection parameter combination of a laser based on an angle deviation matrix and an angle-reflection intensity relationship mapping table; A detection module 204 is used to perform spiral scanning detection based on the compensation detection parameter combination to obtain an initial feature representation, and perform feature enhancement to obtain an enhanced feature representation; The analysis module 205 is used to perform multi-dimensional index analysis and fusion on the enhanced feature representation to obtain a quality detection result; The solution module 206 is used to solve the global optimal detection parameter combination of the laser according to the quality detection result and generate a laser adjustment control sequence.

[0040] Through the coordinated cooperation of the above-mentioned components, by establishing the spatial position mapping relationship between the angle sensor and the detection beam, and combining the automatic power control circuit to realize the precise positioning and energy control of the detection beam, the stability and reliability of the detection system are improved; the dual feedback mechanism of the angle deviation matrix and the angle-reflection intensity relationship mapping table is adopted to realize the dynamic adjustment of the wavelength compensation and the energy density threshold, and ensure the optimal configuration of the detection parameters; the detection strategy of spiral scanning and multi-dimensional feature enhancement is used to obtain more comprehensive and accurate feature information, and improve the spatial resolution and feature extraction ability of the detection; through the local feature subspace division and multi-dimensional indicator analysis method, the accurate evaluation and grading of quality are realized, and the credibility of the detection results is enhanced; based on the solution of the global optimal detection parameter combination and the control sequence generation mechanism, a complete parameter optimization and control strategy is established to ensure the intelligence and automation level of the detection process.

[0041] above Figure 2 The wavelength precision adjustment device based on the angle sensor in the embodiment of the present invention is described in detail from the perspective of modular functional entity, and the laser in the embodiment of the present invention is described in detail from the perspective of hardware processing.

[0042] An embodiment of the present invention provides a laser, which is used to implement the steps of the above-mentioned wavelength precise adjustment method based on an angle sensor.

[0043] The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions are executed on a computer, the computer executes the steps of the method for precise wavelength adjustment based on an angle sensor.

[0044] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, systems and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0045] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the whole or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program code.

[0046] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A wavelength precise adjustment method based on an angle sensor, characterized in that: The method comprises: Initialize the laser based on the initial detection parameter combination and obtain spatial position mapping data of the angle sensor and the detection beam; According to the spatial position mapping data, an angle deviation matrix is ​​calculated and an angle-reflection intensity relationship mapping table is established; Generate a compensation detection parameter combination of the laser based on the angle deviation matrix and the angle-reflection intensity relationship mapping table; Performing spiral scanning detection based on the compensation detection parameter combination to obtain an initial feature representation, and performing feature enhancement to obtain an enhanced feature representation; Performing multi-dimensional index analysis and fusion on the enhanced feature representation to obtain a quality detection result; The global optimal detection parameter combination of the laser is solved according to the quality detection result and a laser adjustment control sequence is generated.

2. The wavelength precise adjustment method based on the angle sensor according to claim 1 is characterized in that: Initializing the laser based on the initial detection parameter combination and obtaining spatial position mapping data of the angle sensor and the detection beam includes: The wavelength parameter, power parameter and angle parameter in the initial detection parameter combination are quantized respectively to obtain an initial working state, and the initial working state is input into a proportional integral control unit of an automatic power control circuit to perform closed-loop feedback control on the output power of the laser to obtain a detection beam power value; Generate a detection beam based on the detection beam power value, measure the energy density distribution of the detection beam according to a preset power threshold to obtain an energy density distribution measurement result, and input the energy density distribution measurement result into a modulation unit of an automatic power control circuit to obtain a beam energy distribution curve; Matching the emission angle of the detection light beam with the receiving angle of the angle sensor in real time, and acquiring spatial angle data through a high-speed sampling circuit of the angle sensor; Performing noise reduction filtering and data smoothing processing on the spatial angle data to obtain an angle detection curve, and performing spatial coordinate mapping on the emission angle and the receiving angle of the detection light beam based on the angle detection curve to obtain spatial position feature points of the angle sensor; The spatial position feature points are spatially discretized according to the sampling interval of the angle sensor to obtain an initial spatial mapping model, and the initial spatial mapping model is subjected to spatial curvature analysis and feature enhancement processing to obtain spatial position mapping data.

3. The wavelength precise adjustment method based on the angle sensor according to claim 2 is characterized in that: The step of calculating an angle deviation matrix and establishing an angle-reflection intensity relationship mapping table according to the spatial position mapping data includes: Performing threshold segmentation and maximum value calibration on the angle sensor received signal strength in the spatial position mapping data to obtain angle reference data, and reordering and linearly interpolating the angle reference data according to the scanning interval of the angle sensor to obtain a continuous angle sequence; Scanning the continuous angle sequence point by point and calculating the difference according to the angle sensor sampling points to obtain angle deviation data, and importing the angle deviation data into the angle error correction module, correcting the angle error curve by a polynomial fitting method, and obtaining a compensated angle deviation value; Performing two-dimensional matrix reconstruction on the compensated angle deviation value to obtain a two-dimensional reconstruction matrix, performing boundary filling and smoothing processing on the two-dimensional reconstruction matrix to obtain an angle deviation matrix, and collecting reflected light intensity at each matrix element position of the angle deviation matrix, obtaining corresponding reflection intensity measurement values ​​through a photoelectric detector to obtain a reflection intensity matrix; The angle deviation matrix and the reflection intensity matrix are synchronously mapped to obtain mapping point pairs, and data segmentation and outlier elimination are performed on the mapping point pairs to obtain valid mapping data pairs. Partition statistics and feature extraction are performed on the valid mapping data pairs, and mapping rules are constructed according to the corresponding relationship between angle and reflection intensity to obtain an angle-reflection intensity relationship mapping table.

4. The wavelength precise adjustment method based on the angle sensor according to claim 3 is characterized in that: The generating of the compensation detection parameter combination of the laser based on the angle deviation matrix and the angle-reflection intensity relationship mapping table comprises: Normalizing the angle deviation values ​​in the angle deviation matrix and adjusting the wavelength weights to obtain angle deviation compensation weights; Importing the angle deviation compensation weight into a laser wavelength control module, and generating a first wavelength compensation parameter according to a wavelength characteristic curve of the laser; The wavelength of the detection light beam is adjusted according to the first wavelength compensation parameter, and feedback data of the angle sensor after adjustment is collected to obtain a wavelength compensation effect value; The wavelength compensation effect value is compared with the initial angle deviation, and a compensation correction coefficient is generated through error analysis to obtain a second wavelength compensation parameter; The reflection intensity data in the angle-reflection intensity relationship mapping table are calibrated according to the photoelectric detector range, and a reflection intensity reference value is set to obtain an energy density reference point; Matching the energy density reference point with the detection lower limit and upper limit of the photoelectric detector, obtaining multi-level energy density control points through interval segmentation, and obtaining an energy density threshold; The second wavelength compensation parameter and the energy density threshold are associated and matched and optimal parameter configuration is performed to obtain a compensation detection parameter combination.

5. The wavelength precise adjustment method based on the angle sensor according to claim 4 is characterized in that: The step of performing spiral scanning detection based on the compensation detection parameter combination to obtain an initial feature representation, and performing feature enhancement to obtain an enhanced feature representation comprises: The compensation detection parameter combination is input into the laser control unit, a spiral scanning path sequence is generated in the order from the inner ring to the outer ring, and the detection beam movement is controlled according to the spiral scanning path sequence to obtain scanning trajectory points; Angle step sampling is performed on the scanning trajectory points, and the reflected light intensity signal of each sampling point is collected by an angle sensor and recorded synchronously to obtain reflected signal data; Correlation mapping is performed between the reflection signal data and the position information of the scanning track points, and the topography is reconstructed through the correspondence between the reflection light intensity and the position to obtain an initial feature representation; Performing layered processing on the initial feature representation according to different wavelength ranges to obtain layered wavelength feature data, and correlating the layered wavelength feature data with the spatial position of the detection light beam and extracting the morphological features to obtain spatial distribution feature data; Performing feature selection and weight allocation on the layered wavelength feature data to obtain enhanced wavelength feature data, and performing regional clustering and boundary enhancement on the spatial distribution feature data to obtain enhanced spatial feature data; The enhanced wavelength feature data and the enhanced spatial feature data are feature combined and reconstructed to obtain an enhanced feature representation.

6. The wavelength precise adjustment method based on the angle sensor according to claim 5 is characterized in that: The multi-dimensional indicator analysis and fusion of the enhanced feature representation to obtain the quality detection result includes: The enhanced feature representation is gridded according to the morphological structure, and the region is divided into a plurality of local feature subspaces by a uniform grid segmentation method to obtain a subspace distribution structure; Extract wavelength features from each local feature subspace in the subspace distribution structure, obtain wavelength change feature points through wavelength response data analysis, and obtain wavelength feature indicators; Performing spatial continuity analysis on the wavelength characteristic index, obtaining regional morphology change rules through local adjacent feature association processing, and obtaining morphology characteristic index; Performing hierarchical statistics on the reflected light intensity data in the morphological characteristic index, obtaining defect characteristic points through light intensity distribution law analysis, and obtaining a light intensity characteristic index; Combining the wavelength characteristic index, the morphology characteristic index and the light intensity characteristic index, constructing a characteristic evaluation system through multi-dimensional characteristic association analysis, and obtaining a local characteristic score; Performing multi-level quality evaluation on the local feature scores, constructing local quality evaluation indicators, and spatially reconstructing and merging data on the local quality evaluation indicators to obtain a global quality distribution map; The global quality distribution map is graded according to a preset quality grade standard, and a quality detection result is output.

7. The wavelength precise adjustment method based on the angle sensor according to claim 6 is characterized in that: The step of solving the global optimal detection parameter combination of the laser according to the quality detection result and generating a laser adjustment control sequence includes: Performing multidimensional data analysis on the quality detection results, obtaining weight coefficients of wavelength parameters, power parameters and angle parameters by decomposing quality influencing factors, and obtaining parameter influencing weights; The parameter influence weights are combined with the initial detection parameters for correlation analysis, and the adjustment range of each parameter is determined by parameter sensitivity calculation to obtain the parameter optimization interval; Combining and traversing the wavelength parameters, power parameters and angle parameters within the parameter optimization interval, obtaining a candidate parameter sequence by multi-parameter joint optimization, cross-validating the candidate parameter sequence with the quality detection result, and screening the optimal parameter group by quality indicator matching analysis to obtain a global optimal detection parameter combination; Performing stability check on the global optimal detection parameter combination, constructing parameter adjustment rules through parameter perturbation analysis, obtaining parameter adjustment schemes, and performing time sequence decomposition on the parameter adjustment schemes according to the response characteristics of the laser, generating a control step sequence through control timing arrangement, and obtaining control execution timing; The control execution sequence is encoded with control instructions, and wavelength control instructions, power control instructions and angle control instructions are generated through instruction mapping table conversion to obtain sub-item control instructions, and the sub-item control instructions are integrated according to the execution order to obtain a laser adjustment control sequence.

8. A wavelength precision adjustment device based on an angle sensor, characterized in that: The device is used to perform the wavelength precise adjustment method based on the angle sensor according to any one of claims 1 to 7, comprising: An initialization module, used to initialize the laser based on an initial detection parameter combination and obtain spatial position mapping data of the angle sensor and the detection beam; A calculation module, used to calculate an angle deviation matrix and establish an angle-reflection intensity relationship mapping table according to the spatial position mapping data; A generating module, used for generating a compensation detection parameter combination of the laser based on the angle deviation matrix and the angle-reflection intensity relationship mapping table; A detection module, used for performing spiral scanning detection based on the compensation detection parameter combination to obtain an initial feature representation, and performing feature enhancement to obtain an enhanced feature representation; An analysis module, used to perform multi-dimensional index analysis and fusion on the enhanced feature representation to obtain a quality detection result; A solution module is used to solve the global optimal detection parameter combination of the laser according to the quality detection result and generate a laser adjustment control sequence.

9. A laser, characterized in that: The laser is used to perform the wavelength precise adjustment method based on an angle sensor as claimed in any one of claims 1 to 7.

10. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions are executed by the processor, the method for precise wavelength adjustment based on an angle sensor as described in any one of claims 1 to 7 is implemented.

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