Wavelength precision adjustment method, device and laser based on angle sensor

Abstract

The present invention relates to the technical field of wavelength adjustment, and discloses a method, device, and laser for precise wavelength adjustment based on an angle sensor. The method comprises: initializing the laser based on an initial detection parameter combination, and obtaining spatial position mapping data of the angle sensor and the detection beam; calculating an angle deviation matrix and establishing an angle-reflection intensity relationship mapping table; generating a compensation detection parameter combination for the laser; 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 indicator analysis and fusion on the enhanced feature representation to obtain a quality detection result; and solving the global optimal detection parameter combination of the laser based on the quality detection result and generating a laser adjustment control sequence. The method improves the accuracy of quality detection of wavelength-related devices.

Description

Technical Field

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

[0002] Traditional inspection methods rely on fixed-wavelength lasers and single-angle inspection methods, making them incapable of adapting to the diverse inspection requirements of wavelength-dependent components. This results in low accuracy and reliability. Due to the complex structure and large inspection area of wavelength-dependent components, traditional inspection methods struggle to obtain complete and accurate quality information.

[0003] Current detection systems generally suffer from problems such as difficulty in optimizing detection parameters, unstable detection processes, and poor consistency in detection results. This is mainly due to the lack of an effective mechanism for precise wavelength adjustment, which makes it impossible to dynamically adjust 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 angular deviations during the detection process that affect detection accuracy. Although some parameter compensation and correction methods have been adopted in the existing technology, most of them are based on empirical settings or simple feedback adjustments, and lack a systematic theoretical basis and intelligent control strategy. In this case, the detection system has difficulty coping with complex and changing 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 comprising:

[0006] Initialize the laser based on the initial detection parameter combination and obtain spatial position mapping data of the angle sensor and the detection beam;

[0007] According to the spatial position mapping data, an angle deviation matrix is calculated and an angle-reflection intensity relationship mapping table is established;

[0008] Generating a compensation detection parameter combination of the laser based on the angle deviation matrix and the angle-reflection intensity relationship mapping table;

[0009] 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;

[0010] Performing multi-dimensional indicator analysis and fusion on the enhanced feature representation to obtain a quality detection result;

[0011] A global optimal detection parameter combination of the laser is solved according to the quality detection result and a laser adjustment control sequence is generated.

[0012] In a second aspect, the present invention provides a device for accurately adjusting wavelength based on an angle sensor, the device comprising:

[0013] An initialization module is 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;

[0014] A calculation module, configured to calculate an angle deviation matrix and establish an angle-reflection intensity relationship mapping table based on the spatial position mapping data;

[0015] A generating module, configured to generate a compensation detection parameter combination for the laser based on the angle deviation matrix and the angle-reflection intensity relationship mapping table;

[0016] a detection module, configured 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;

[0017] An analysis module, configured to perform multi-dimensional index analysis and fusion on the enhanced feature representation to obtain a quality detection result;

[0018] 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.

[0019] A third aspect of the present invention provides a laser, which is used to execute the above-mentioned method for precise wavelength adjustment based on an angle sensor.

[0020] 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.

[0021] 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, combined with an automatic power control circuit, precise positioning and energy control of the detection light beam are achieved, 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.

[0022] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or understood by practicing the present invention. The purposes and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0023] 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

[0024] Figure 1 Schematic diagram of an embodiment of a method for precise wavelength adjustment based on an angle sensor in an embodiment of the present invention;

[0025] 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

[0026] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0027] The terms "including," "having," and any variations thereof, as used in the embodiments of the present invention are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or device comprising a series of steps or units is not limited to the listed steps or units, but may optionally include other steps or units not listed, or may optionally include other steps or units inherent to the process, method, product, or device.

[0028] 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 introduced in detail. Figure 1 As shown, this method includes the following steps:

[0029] 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;

[0030] It is understandable that the execution subject of the present invention can be a wavelength precision adjustment device based on an angle sensor, or a terminal or a server, which is not limited here. The embodiment of the present invention is described by taking a server as the execution subject as an example.

[0031] Specifically, the wavelength, power, and angle parameters in the initial detection parameter combination are quantified to determine the operating conditions of the laser in its initial state, ensuring that the system can be effectively controlled and adjusted. By quantifying the wavelength, power, and angle, a stable initial operating state is obtained, which is input as a base state into the proportional-integral control unit of the automatic power control circuit. Based on this, the output power of the laser is subject to closed-loop feedback control. The power value of the detection beam is obtained by real-time detection of the laser output power. Based on the power value of the detection beam, a detection beam is generated for measurement, 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 energy density and distribution of the detection beam are used to monitor the uniformity and stability of the laser output, and the beam energy is optimized through adjustment of the modulation unit to ensure that the characteristics of the detection beam meet the expected standards. The detection beam's emission angle is matched to the angle sensor's reception angle in real time. The angle sensor's high-speed sampling circuit acquires the detection beam's spatial angle data, ensuring that the angular matching relationship between the detection beam and the angle sensor reflects the system's dynamic changes in real time. The spatial angle data is subjected to noise reduction filtering and data smoothing. By filtering out random noise in the angle data and smoothing the data, a more stable and representative angle detection curve is generated. Based on the angle detection curve, the emission and reception angles of the detection beam are mapped to spatial coordinates to obtain the angle sensor's spatial position feature points, which describe the laser beam's propagation path and its corresponding angle information. The spatial feature points are discretized according to the angle sensor's sampling interval to construct an initial spatial mapping model. This initial spatial mapping model describes the spatial position variation of the laser beam and its corresponding relationship with the angle sensor. Spatial curvature analysis and feature enhancement are performed on the initial spatial mapping model. This curvature analysis of the spatial feature points provides a better understanding of the curvature variation of the beam's propagation path, enabling more precise control of laser adjustment. Feature enhancement processing strengthens the details of the model so that it can better reflect the actual propagation characteristics of the laser beam.

[0032] 102. Calculate an angle deviation matrix based on the spatial position mapping data and establish an angle-reflection intensity relationship mapping table;

[0033] Specifically, the angle sensor received signal strength in the spatial position mapping data is thresholded and calibrated to determine the angle reference data. Thresholding the received signal effectively eliminates noise and interference, retaining only valid signals. Maximum calibration ensures the selected signal strength is representative and stable, forming the angle reference data. The angle reference data is reordered according to the angle sensor's scanning interval to form an ordered angle signal. Missing data is supplemented through linear interpolation to obtain a complete and continuous angle sequence. The continuous angle sequence is scanned point by point at the angle sensor sampling points, and the difference is calculated to obtain angle deviation data. This point-by-point scanning process refines the angle deviation calculation, ensuring that the angle change at each sampling point is accurately captured, providing more accurate angle deviation information. The angle deviation data is then imported into the angle error correction module, where the angle error curve is corrected using a polynomial fitting method. This polynomial fitting method effectively corrects the original angle error, compensating for deviations caused by various environmental factors or mechanical errors, to obtain a compensated angle deviation value. The compensated angle deviation value is then reconstructed into a two-dimensional matrix to generate a two-dimensional reconstruction matrix describing the angle deviation. By matrixing the data, one-dimensional angle deviation information is converted into two-dimensional spatial information. The reconstructed two-dimensional matrix is then boundary-filled and smoothed to eliminate sudden changes or discontinuities at the matrix boundaries, resulting in an angle deviation matrix. Reflected light intensity is collected at each element of the angle deviation matrix, and the reflection intensity at each location is measured using a photodetector to obtain a reflection intensity matrix. The reflection intensity matrix and the angle deviation matrix together reflect the relationship between angle variation and reflected light intensity. The angle deviation matrix and the reflection intensity matrix are synchronously mapped to obtain mapping point pairs containing angles and reflection intensities. These mapping point pairs contain reflection intensity information at different angles, describing the corresponding relationship between angles and reflection intensities. The mapping point pairs are segmented and outliers are removed to obtain valid mapping data pairs. Valid mapping data pairs are then subjected to partitioned statistics and feature extraction. By statistically analyzing the mapping data in different intervals, characteristic information between angle and reflection intensity within each interval is extracted. This process reveals the variation patterns between angle and reflection intensity within different intervals, 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.

[0034] 103. Generate a compensation detection parameter combination for the laser based on the angle deviation matrix and the angle-reflection intensity relationship mapping table;

[0035] Specifically, the angle deviation values in the angle deviation matrix are normalized to convert them to a relatively uniform scale, eliminating calculation errors caused by inconsistent dimensions. Combined with the wavelength weight adjustment factor, the adjusted angle deviation data is converted into angle deviation compensation weights, which represent the contribution of each angle deviation to the wavelength adjustment process. The angle deviation compensation weights are imported into the laser's wavelength control module and combined with the laser's wavelength characteristic curve to generate first wavelength compensation parameters. The wavelength characteristic curve describes the correspondence between the laser wavelength and various control factors. By combining the angle deviation compensation weights with the wavelength characteristic curve, first wavelength compensation parameters matching the laser output are generated. These compensation parameters are used to initially adjust the wavelength of the detection beam to optimize the beam characteristics. During the adjustment process, feedback data from 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 assess the effectiveness of the adjustment. The wavelength compensation effect value is compared with the initial angle deviation, and a compensation correction coefficient is generated through error analysis to obtain the second wavelength compensation parameter. This comparison process effectively evaluates the accuracy of the initial wavelength adjustment and, through quantitative error analysis, yields a more accurate compensation correction coefficient. Using this correction factor, the initial wavelength compensation parameters are modified to obtain second wavelength compensation parameters that better meet actual requirements. While adjusting the wavelength compensation parameters, the reflection intensity data in the angle-reflection intensity relationship mapping table is calibrated according to the photodetector's range, and a reflection intensity reference value is set to obtain an energy density reference point. This reflection intensity calibration ensures that the measured data maintains a linear response within the photodetector's range, avoiding measurement distortion caused by range overshoot or data saturation. Furthermore, setting the reflection intensity reference value clarifies the energy density reference level, ensuring that the energy output during the adjustment process achieves the desired effect, thereby providing a stable energy reference for wavelength adjustment. The energy density reference point is matched to the photodetector's lower and upper detection limits. Using interval segmentation, multi-level energy density control points are generated, and energy density thresholds are generated based on these points. The energy density threshold characterizes the variation of beam energy within different intervals and enables effective control of beams of different energy levels. By setting these multi-level energy density control points, the beam energy output can be finely adjusted at different energy levels to meet varying beam energy requirements during wavelength adjustment. 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.

[0036] 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;

[0037] Specifically, the compensation detection parameter combination is input into the laser control unit, which generates a spiral scanning path sequence based on the set scanning strategy. During this process, the spiral scanning path is generated in an inner-to-outer loop sequence to ensure comprehensive and uniform coverage. Using this spiral scanning path sequence, the laser control unit precisely controls the trajectory of the detection beam, forming a continuous scanning trajectory point that describes the path of the laser beam. The scanning trajectory points are sampled in angular steps. An angle sensor collects the reflected light intensity signal at each sampling point and synchronously records these signals to obtain reflection signal data. The reflection signal data is mapped to the position information of the scanning trajectory points. Based on the correspondence between reflected light intensity and position, the overall topography is reconstructed to obtain an initial feature representation. This initial feature representation describes basic topographic information of the measured object, including smoothness and convexity and concavity. The initial feature representation is layered according to different wavelength ranges to obtain layered wavelength feature data. The layered wavelength feature data is then associated with the spatial position of the detection beam, and topographic features are extracted to obtain spatially distributed feature data. Feature selection and weight assignment 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 analysis efficiency and accuracy. By assigning appropriate weights to these features, the influence of important features is highlighted, and enhanced wavelength feature data is obtained. 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 aggregate 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 an enhanced feature representation.

[0038] 105. Perform multi-dimensional indicator analysis and fusion on the enhanced feature representation to obtain quality detection results;

[0039] Specifically, the enhanced feature representation is gridded according to the topographic structure. Using a uniform grid partitioning method, the entire region is divided into multiple local feature subspaces, resulting in a subspace distribution structure. Wavelength features are extracted for each local feature subspace within the subspace distribution structure. By analyzing the wavelength response data, characteristic points of wavelength variation at different locations are identified, resulting in wavelength characteristic indices. These reflect the wavelength response characteristics of different regions and help understand the propagation behavior and local characteristics of the laser. To analyze these characteristics, spatial continuity analysis is performed on the wavelength characteristic indices. By correlating local adjacent features, the topographic variation patterns between regions are determined, resulting in topographic characteristic indices that reveal spatial variations, particularly the distribution of protrusions, depressions, or other structural features. The reflected light intensity data within the topographic characteristic indices is subjected to hierarchical statistics. By analyzing the intensity distribution patterns, defect characteristic points can be identified, resulting in intensity characteristic indices. The introduction of intensity characteristic indices helps identify and locate abnormal areas, such as cracks, depressions, or contamination, which often affect laser propagation and reflection. The wavelength characteristic index, morphology characteristic index, and light intensity characteristic index are combined, and a characteristic evaluation system is constructed through multi-dimensional feature correlation analysis to obtain a 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 a local quality evaluation index. By comprehensively scoring each feature, the local quality evaluation can effectively classify and evaluate the quality of different regions and identify areas with good performance and defects. The local quality evaluation index is spatially reconstructed and data merged to obtain a global quality distribution map, which reflects the differences 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 possible to identify which areas meet the quality requirements and which areas need improvement.

[0040] 106. Solve the global optimal detection parameter combination of the laser based on the quality detection results and generate a laser adjustment control sequence.

[0041] Specifically, a multidimensional data analysis is performed on the quality inspection results. By analyzing the various factors affecting quality, the weighted relationships among parameters such as wavelength, power, and angle, which influence quality, are identified. By decomposing the quality-influencing factors, weight coefficients for the wavelength, power, and angle parameters are obtained, indicating the importance of each parameter in influencing quality, and thus the parameter impact weights. The parameter impact weights are then correlated with the initial inspection parameter combination, and the parameter sensitivity is calculated to determine the adjustment range for each parameter, resulting in the parameter optimization interval. Combinations of wavelength, power, and angle parameters within the parameter optimization interval are then traversed, and a candidate parameter sequence is obtained through a multi-parameter joint optimization method. This multi-parameter joint optimization method involves traversing all possible parameter combinations, trying different parameter combinations one by one, and finding the candidate parameter sequence that best meets quality requirements. The candidate parameter sequence is then cross-validated with the quality inspection results, and the optimal parameter set is selected through quality indicator match analysis, resulting in the globally optimal inspection parameter combination. This globally optimal inspection parameter combination is then subjected to a stability check to ensure its stability in practical applications. Using parameter perturbation analysis, each parameter is perturbed slightly. Based on these analysis results, parameter adjustment rules are constructed to produce a final parameter adjustment plan. The parameter adjustment plan is designed to ensure that the laser maintains precise wavelength, power, and angle adjustment under varying operating conditions. The parameter adjustment plan is decomposed into a time series based on the laser's response characteristics. A control step sequence is generated through control timing arrangement to obtain the control execution sequence. This control step sequence ensures that changes in various laser parameters during the adjustment process are coordinated, avoiding distortion of the adjustment effect caused by excessively fast or slow changes in a single parameter. By decomposing the parameter adjustment plan, the specific timing and step size of each adjustment step are clearly defined, making the adjustment process more precise and smooth. Control instructions are encoded within the control execution sequence. Through conversion of the instruction mapping table, corresponding wavelength control instructions, power control instructions, and angle control instructions are generated, resulting in sub-item control instructions. These sub-item control instructions adjust the laser's wavelength, power, and angle, respectively, ensuring that each key parameter is 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 adjustment process.

[0042] In an embodiment of the present invention, by establishing a spatial position mapping relationship between the angle sensor and the detection light beam, combined with an automatic power control circuit, precise positioning and energy control of the detection light beam are achieved, 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.

[0043] In a specific embodiment, the process of executing step 101 may specifically include the following steps:

[0044] The wavelength parameter, power parameter and angle parameter in the initial detection parameter combination are quantized respectively to obtain the initial working state, and the initial working state is input into the proportional integral control unit of the automatic power control circuit to perform closed-loop feedback control on the output power of the laser to obtain the detection beam power value;

[0045] generating a detection beam based on the detection beam power value, measuring the energy density distribution of the detection beam according to a preset power threshold to obtain an energy density distribution measurement result, and inputting the energy density distribution measurement result into a modulation unit of an automatic power control circuit to obtain a beam energy distribution curve;

[0046] 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;

[0047] Perform noise reduction filtering and data smoothing on the spatial angle data to obtain an angle detection curve. Based on the angle detection curve, perform spatial coordinate mapping on the emission angle and reception angle of the detection beam to obtain the spatial position feature points of the angle sensor.

[0048] 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.

[0049] 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 properly quantizing these parameters, the initial working state after quantization is obtained. The quantization formula is expressed as:

[0050] ;

[0051] 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, forming 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:

[0052] ;

[0053] in, is the control signal, is the proportional gain, is the integral gain, The system deviation is the difference between the set value and the actual output. 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 the 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 obtained 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 light 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:

[0054] ;

[0055] 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 beam during propagation, providing a basis for adjustment. Feature enhancement strengthens key features in the spatial model, enabling the model to better reflect the actual propagation characteristics of the laser beam. By processing the initial spatial mapping model, spatial position mapping data is obtained.

[0056] In a specific embodiment, the process of executing step 102 may specifically include the following steps:

[0057] Perform threshold segmentation and maximum calibration on the angle sensor received signal strength in the spatial position mapping data to obtain angle reference data, and then rearrange and linearly interpolate the angle reference data according to the scanning interval of the angle sensor to obtain a continuous angle sequence;

[0058] Scan the continuous angle sequence point by point according to the angle sensor sampling points and calculate the difference to obtain the angle deviation data. The angle deviation data is then imported into the angle error correction module. The angle error curve is corrected using a polynomial fitting method to obtain the compensated angle deviation value.

[0059] Performing a two-dimensional matrix reconstruction on the compensated angle deviation value to obtain a two-dimensional reconstruction matrix, performing boundary filling and smoothing on the two-dimensional reconstruction matrix to obtain an angle deviation matrix, and collecting the 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;

[0060] 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 subjected to partition statistics and feature extraction. The mapping rules are constructed according to the correspondence between angle and reflection intensity to obtain the angle-reflection intensity relationship mapping table.

[0061] Specifically, the angle sensor received signal strength in the spatial position mapping data is threshold segmented and calibrated to its maximum value. 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. Assume that the signal strength received by the angle sensor is , by choosing the threshold , the conditions for defining a valid signal are After threshold segmentation, the obtained signal intensity is calibrated to determine the maximum value. The maximum value calibration process is expressed by the following formula:

[0062] ;

[0063] in, represents the normalized signal intensity, is the maximum value of the calibrated signal. The purpose of normalization is to convert signal strength into relative values, allowing data of different intensities to 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:

[0064] ;

[0065] in, It's time The corresponding interpolation angle is are the known angle values of 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:

[0066] ;

[0067] in, is the angle difference between 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. Let the fitting polynomial be:

[0068] ;

[0069] 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 reconstruction matrix that describes the angle change. The two-dimensional matrix is subjected to boundary filling and data smoothing. 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, and obtain the 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 the photoelectric detector to generate a reflection intensity matrix. Let the reflected light intensity be , Represents the angle deviation matrix position The reflection intensity value on the reflection intensity matrix is used 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 credible. Partition statistics and feature extraction are performed on valid mapping data pairs. Partition statistics are used to independently analyze data in different areas, thereby revealing the characteristic differences between angles and reflection intensities in different areas. By extracting these feature data, the relationship mapping rules between angles and reflection intensities are constructed, and finally the angle-reflection intensity relationship mapping table is obtained.

[0070] In a specific embodiment, the process of executing step 103 may specifically include the following steps:

[0071] Normalizing the angle deviation values in the angle deviation matrix and adjusting the wavelength weights to obtain angle deviation compensation weights;

[0072] Importing the angle deviation compensation weight into the laser wavelength control module, and generating a first wavelength compensation parameter according to the wavelength characteristic curve of the laser;

[0073] Adjusting the wavelength of the detection light beam according to the first wavelength compensation parameter, and collecting feedback data of the angle sensor after adjustment to obtain a wavelength compensation effect value;

[0074] Comparing the wavelength compensation effect value with the initial angle deviation, generating a compensation correction coefficient through error analysis, and obtaining a second wavelength compensation parameter;

[0075] The reflection intensity data in the angle-reflection intensity relationship mapping table is calibrated according to the photoelectric detector range, and the reflection intensity reference value is set to obtain the energy density reference point;

[0076] 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;

[0077] The second wavelength compensation parameter and the energy density threshold are correlated and matched and the optimal parameter configuration is performed to obtain a compensation detection parameter combination.

[0078] 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. Assume that the angle deviation value is , the normalized angle deviation value It is expressed by the following formula:

[0079] ;

[0080] 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. Multiply the product to get the angle deviation compensation weight

[0081] ;

[0082] in, This represents the wavelength adjustment weighting factor, used to control the degree of influence of angle on wavelength adjustment. The angle deviation compensation weight is a key parameter in the wavelength adjustment process, quantifying the contribution of each angle deviation to wavelength adjustment. The angle deviation compensation weight is imported into the laser wavelength control module and combined with the laser's wavelength characteristic curve to generate the first wavelength compensation parameter. The wavelength characteristic curve describes how the laser's output wavelength changes under different control signals. Assume that the wavelength characteristic curve is represented by the following relationship:

[0083] ;

[0084] 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 parameter , 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 the 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 adjust the wavelength twice by generating the 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 photodetector is used to detect the reflected light intensity. The calibration process is to ensure that the measurement result of the photodetector is consistent with the actual reflected light intensity. Assume that the reflection intensity is , the range of the photodetector is , the calibrated reflection intensity Expressed as:

[0085] ;

[0086] 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 the energy density threshold 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 remains within a reasonable range under different operating conditions, avoiding the negative impact of excessively high or low power. and energy density threshold Correlation matching and optimal parameter configuration are performed 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 consistency between the laser wavelength and energy output, thereby achieving the optimal regulation effect. Through optimal parameter configuration, a set of parameters is found within the system's multidimensional control space to achieve the optimal laser output performance.

[0087] In a specific embodiment, the process of executing step 104 may specifically include the following steps:

[0088] 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;

[0089] Perform angle step sampling on the scanning track points, collect the reflected light intensity signal of each sampling point through the angle sensor and record it synchronously to obtain the reflected signal data;

[0090] The reflected signal data is correlated and mapped with the position information of the scanning trajectory points, and the topography is reconstructed through the correspondence between the reflected light intensity and the position to obtain the initial feature representation;

[0091] 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 beam and the morphological features are extracted to obtain spatial distribution feature data;

[0092] Perform feature selection and weight allocation on the layered wavelength feature data to obtain enhanced wavelength feature data, and perform regional clustering and boundary enhancement on the spatial distribution feature data to obtain enhanced spatial feature data;

[0093] The enhanced wavelength feature data and the enhanced spatial feature data are combined and reconstructed to obtain enhanced feature representation.

[0094] 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. This path sequence gradually expands 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:

[0095] ;

[0096] 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, and the laser detection beam is controlled to move along the preset path on the wavelength-dependent device to obtain the scanning trajectory points. The scanning trajectory points are sampled in steps of angles to obtain the specific information of the reflected light intensity signal, thereby analyzing the optical characteristics of . Assuming 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 correlating 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:

[0097] ;

[0098] in, Indicates the wavelength-dependent device at position In this way, a complete reflection characteristic diagram is generated, which reflects 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 layered processing is expressed as , these data reflect the wavelength-dependent devices in the wavelength The reflection characteristics under the condition of light. The layered wavelength characteristic data is associated with the spatial position of the detection beam, and the morphological characteristics of the wavelength-related device are extracted to obtain the spatial distribution characteristic data, which describes the spatial inhomogeneity of the wavelength-related device and the change law at different wavelengths. It helps to understand the optical properties of the wavelength-related device and judge the quality of the material. Feature selection and weight assignment are performed on the layered wavelength characteristic data to obtain enhanced wavelength characteristic data. The feature selection process is to extract the most representative features from multi-level data, thereby removing redundant information and ensuring the efficiency of data processing. Different weights are assigned to the selected features to obtain enhanced wavelength characteristic data. Assuming the weight is , the enhanced wavelength characteristic data is expressed as:

[0099] ;

[0100] in, is the enhanced wavelength characteristic data, Assigned to wavelength feature weights. Through weight distribution, feature data with a greater impact on quality is 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 to aggregate 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.

[0101] Among them, feature selection and weight distribution 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 of each layer of wavelength data in the layered wavelength feature data, extracting effective wavelength features through light intensity threshold screening, and obtaining wavelength feature intensity values; grading the wavelength feature intensity values according to the light intensity, and setting corresponding weight coefficients for each level to obtain a wavelength feature weight table; normalizing the weight coefficients in the wavelength feature weight table, adjusting the weight distribution according to the wavelength response characteristics, and obtaining an optimized weight sequence; performing weighted combination of the optimized weight sequence and the layered wavelength feature data, highlighting the main wavelength features according to the weight size, and obtaining enhanced spatial feature data. 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 features, 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 features, 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.

[0102] In a specific embodiment, the process of executing step 105 may specifically include the following steps:

[0103] The enhanced feature representation is gridded according to the morphological structure, and the region is divided into multiple local feature subspaces by a uniform grid segmentation method to obtain the subspace distribution structure;

[0104] 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;

[0105] The spatial continuity analysis of wavelength characteristic index is carried out, and the regional morphological change law is obtained by local adjacent feature correlation processing to obtain the morphological characteristic index;

[0106] 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;

[0107] 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;

[0108] 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;

[0109] The global quality distribution map is graded according to the preset quality grade standard and the quality inspection results are output.

[0110] 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 wavelength change characteristic points 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 under different wavelengths. Spatial continuity analysis is performed on the wavelength characteristic indicators to obtain the morphological change law of the region. By correlating 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:

[0111] ;

[0112] This difference reveals the trend of change between adjacent subspaces. By correlating all adjacent subspaces, a complete morphological feature index is obtained to describe the change of wavelength-dependent 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-dependent device. By analyzing the distribution law of the reflected light intensity, the abnormal area in the wavelength-dependent device is identified. Assume that 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 contamination. 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:

[0113] ;

[0114] in, For 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 a wavelength-dependent device. The global quality distribution map is graded according to pre-set quality standards to produce the final quality inspection results. Pre-set quality standards are set based on the quality requirements of specific application scenarios. For example, in precision optical devices, surface quality must meet a specific standard to ensure optical performance. By grading the global quality distribution map, it is determined which areas meet the quality requirements and which require correction or further processing.

[0115] 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 results are 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 a local quality evaluation index; the local quality evaluation index is positioned 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 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 a continuous quality distribution; merge the regional data of the continuous quality distribution, integrate the local features according to the quality integrity requirements, and obtain a 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 an 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.

[0116] In a specific embodiment, the process of executing step 106 may specifically include the following steps:

[0117] 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 influence weights;

[0118] 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;

[0119] The wavelength parameters, power parameters and angle parameters within the parameter optimization range 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;

[0120] The stability of the global optimal detection parameter combination is checked. The parameter adjustment rules are constructed through parameter perturbation analysis to obtain the parameter adjustment scheme. The parameter adjustment scheme is then decomposed into a time sequence according to the response characteristics of the laser. The control step sequence is generated through control timing arrangement to obtain the control execution timing.

[0121] 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. The sub-item control instructions are then integrated in the execution order to obtain the laser adjustment control sequence.

[0122] Specifically, a 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. Assume that the quality inspection result is , including many factors, such as wavelength ,power and angles Through multiple regression analysis, the influence of these parameters on quality is shown:

[0123] ;

[0124] 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 to quantify the influence of each parameter on the quality and 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 parameter optimization range. Assume that the initial values of the wavelength, power and angle parameters are , and its optimization interval is expressed as:

[0125] ;

[0126] ;

[0127] ;

[0128] in, Represent the adjustment range of wavelength, power and angle parameters respectively. These parameter optimization intervals are determined through 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 through a multi-parameter joint optimization method. An optimal set of parameter combinations is found 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 selected by analyzing the matching degree of the quality indicators. Let the quality indicator be , the matching degree is calculated by the following formula:

[0129] ;

[0130] in, For the The matching degree of the parameter combination, As 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. 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, avoiding system instability due to 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 to 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. ,The control sequence includes the adjustment process of all parameters, which can effectively control the laser to achieve precise adjustment of wavelength, power and angle.

[0131] 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. The candidate parameter sequence is cross-validated with the quality detection result, and the optimal parameter group is screened through quality index 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; segmenting 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 optimal detection parameter sequence according to the quality index matching analysis. 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 between each group of parameters in the candidate parameter sequence and the quality detection result is analyzed, 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 size, 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; the stable parameter combination is subjected to multiple rounds of quality verification, 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.

[0132] 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 device for accurately adjusting wavelength based on an angle sensor includes:

[0133] 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;

[0134] A calculation module 202 is used to calculate an angle deviation matrix and establish an angle-reflection intensity relationship mapping table based on the spatial position mapping data;

[0135] A generating module 203 is configured to generate a compensation detection parameter combination for the laser based on the angle deviation matrix and the angle-reflection intensity relationship mapping table;

[0136] A detection module 204 is configured to perform a spiral scanning detection based on a combination of compensation detection parameters to obtain an initial feature representation, and perform feature enhancement to obtain an enhanced feature representation;

[0137] Analysis module 205, used to perform multi-dimensional index analysis and fusion on the enhanced feature representation to obtain quality detection results;

[0138] The solving 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.

[0139] 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 achieve 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 achieve dynamic adjustment of wavelength compensation and energy density threshold, ensuring the optimal configuration of 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 capability of detection; through local feature subspace division and multi-dimensional indicator analysis methods, accurate quality assessment and grading are achieved, 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.

[0140] 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 entities, and the laser in the embodiment of the present invention is described in detail from the perspective of hardware processing.

[0141] An embodiment of the present invention provides a laser, which is used to implement the steps of the above-mentioned method for precise wavelength adjustment based on an angle sensor.

[0142] The present invention also provides a computer-readable storage medium, which can be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. The computer-readable storage medium stores instructions. When the instructions are run on a computer, the computer executes the steps of the angle sensor-based wavelength precise adjustment method.

[0143] Those skilled in the art will 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.

[0144] If the integrated unit is implemented as 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, or the portion that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0145] 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 above embodiments, those skilled in the art should understand that the technical solutions described in the above embodiments can still be modified, or some of the technical features thereof can 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 for the laser based on the angle deviation matrix and the angle-reflection intensity relationship mapping table; specifically comprising: normalizing the angle deviation value in the angle deviation matrix and adjusting the wavelength weight to obtain an angle deviation compensation weight; importing the angle deviation compensation weight into a laser wavelength control module, and generating a first wavelength compensation parameter according to the wavelength characteristic curve of the laser; adjusting the wavelength of the detection beam according to the first wavelength compensation parameter, and collecting the adjusted angle sensor feedback data to obtain a wavelength compensation effect value; comparing the wavelength compensation effect value with the initial angle deviation, generating a compensation correction coefficient through error analysis, and obtaining a second wavelength compensation parameter; calibrating the reflection intensity data in the angle-reflection intensity relationship mapping table according to the photoelectric detector range, and setting a reflection intensity reference value 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 a multi-level energy density control point through interval segmentation, and obtaining an energy density threshold; correlating and matching the second wavelength compensation parameter and the energy density threshold and configuring the optimal parameters to obtain a compensation detection parameter combination; 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 indicator analysis and fusion on the enhanced feature representation to obtain a quality detection result; A 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, 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: Quantizing the wavelength parameter, power parameter, and angle parameter in the initial detection parameter combination to obtain an initial working state, and inputting the initial working state 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; generating a detection beam based on the detection beam power value, measuring the energy density distribution of the detection beam according to a preset power threshold to obtain an energy density distribution measurement result, and inputting 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 the high-speed sampling circuit of the angle sensor; Performing noise reduction filtering and data smoothing 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 a sampling interval of an angle sensor to obtain an initial spatial mapping model, and spatial curvature analysis and feature enhancement processing are performed on the initial spatial mapping model to obtain spatial position mapping data.

3. The wavelength precise adjustment method based on the angle sensor according to claim 2, characterized in that: The step of calculating an angle deviation matrix and establishing an angle-reflection intensity relationship mapping table based on the spatial position mapping data includes: Performing threshold segmentation and maximum calibration on the angle sensor received signal strength in the spatial position mapping data to obtain angle reference data, and performing sequential rearrangement and linear interpolation completion on the angle reference data according to a 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 to correct the angle error curve using a polynomial fitting method to obtain a compensated angle deviation value; Performing a two-dimensional matrix reconstruction on the compensated angle deviation value to obtain a two-dimensional reconstructed matrix, performing boundary filling and smoothing on the two-dimensional reconstructed matrix to obtain an angle deviation matrix, and collecting reflected light intensity at each matrix element position of the angle deviation matrix, obtaining a 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, and data segmentation and outlier removal 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 correspondence between angles and reflection intensities to obtain an angle-reflection intensity relationship mapping table.

4. The wavelength precise adjustment method based on the angle sensor according to claim 1, characterized in that: The spiral scanning detection is performed based on the compensation detection parameter combination to obtain an initial feature representation, and feature enhancement is performed to obtain an enhanced feature representation, including: Inputting the compensation detection parameter combination into the laser control unit, generating a spiral scanning path sequence in the order from the inner ring to the outer ring, and controlling the movement of the detection beam according to the spiral scanning path sequence to obtain scanning trajectory points; Performing angle step sampling on the scanning track points, collecting the reflected light intensity signal of each sampling point through an angle sensor and synchronously recording it to obtain reflected signal data; Correlating and mapping the reflected signal data with the position information of the scanning trajectory points, reconstructing the topography through the correspondence between the reflected light intensity and the position, and obtaining 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 assignment 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.

5. The wavelength precise adjustment method based on the angle sensor according to claim 4 is characterized in that: The multi-dimensional indicator analysis and fusion of the enhanced feature representation to obtain a quality detection result includes: Gridding the enhanced feature representation according to the morphological structure, dividing the region into a plurality of local feature subspaces by a uniform grid segmentation method, and obtaining a subspace distribution structure; Extracting wavelength features from each local feature subspace in the subspace distribution structure, obtaining wavelength change feature points through wavelength response data analysis, and obtaining wavelength feature indicators; Performing spatial continuity analysis on the wavelength characteristic index, obtaining regional morphology change rules through local adjacent feature correlation processing, and obtaining morphology characteristic index; Performing hierarchical statistics on the reflected light intensity data in the morphological characteristic index, obtaining defect feature points by analyzing the light intensity distribution law, and obtaining the light intensity characteristic index; Performing feature combination on the wavelength characteristic index, the morphology characteristic index, and the light intensity characteristic index, constructing a feature evaluation system through multi-dimensional feature correlation analysis, and obtaining a local feature score; Performing multi-level quality evaluation on the local feature scores to construct local quality evaluation indicators, and performing spatial reconstruction and data merging 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.

6. The wavelength precise adjustment method based on the angle sensor according to claim 5, 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 influence 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 through multi-parameter joint optimization, cross-validating the candidate parameter sequence with the quality detection results, and screening the optimal parameter group through 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 to obtain a parameter adjustment scheme, and performing time sequence decomposition on the parameter adjustment scheme according to the response characteristics of the laser, generating a control step sequence through control timing arrangement, and obtaining a control execution timing; The control execution sequence is encoded with control instructions, and wavelength control instructions, power control instructions and angle control instructions are converted through an instruction mapping table 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.

7. 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 an angle sensor according to any one of claims 1 to 6, comprising: An initialization module is 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, configured to calculate an angle deviation matrix and establish an angle-reflection intensity relationship mapping table based on the spatial position mapping data; A generating module, configured to generate a compensation detection parameter combination for the laser based on the angle deviation matrix and the angle-reflection intensity relationship mapping table; a detection module, configured 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; An analysis module, configured 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.

8. A laser, characterized in that: The laser is used to perform the angle sensor-based wavelength precise adjustment method according to any one of claims 1 to 6.

9. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions are executed by a processor, the method for precise wavelength adjustment based on an angle sensor according to any one of claims 1 to 6 is implemented.

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