Wooden door mortise and tenon machining precision laser real-time calibration method and system

Abstract

The invention provides a wooden door mortise and tenon machining precision laser real-time calibration method and system. According to the method, wood density distribution is detected in a non-contact mode, a three-dimensional gradient map is constructed, the three-dimensional gradient map is matched with the geometric contour of the tenon-and-mortise face, a density mutation area is associated to generate a laser targeting instruction, and laser vertically penetrates through wood; performing texture perception and fiber direction analysis based on the laser diffraction pattern, and outputting phase correction data; the density and the phase characteristics are fused to generate deformation parameters, and a nonlinear calibration function of the tenon-and-mortise gap is constructed; and the predicted deformation quantity and the actual displacement are compared in real time, the tool path is dynamically adjusted, meanwhile, a calibration function is updated through laser scanning actual measurement gap data feedback, and closed-loop calibration is achieved. According to the method, through multi-modal data fusion and a dynamic feedback mechanism, tenon and mortise machining precision self-adaptive optimization driven by the wood density gradient is achieved, and deformation errors caused by uneven materials are remarkably eliminated.

Description

Technical Field

[0001] This application relates to the field of intelligent manufacturing technology for wood products, and in particular to a method and system for real-time laser calibration of the processing accuracy of mortise and tenon joints in wooden doors. Background Technology

[0002] In the automated mortise and tenon joint processing of wooden doors, uneven distribution of wood density gradient and grain fiber direction can lead to unpredictable micro-deformation of the mating surfaces. Traditional processing errors can only compensate for geometric dimensional deviations. Modern high-end wooden door production lines require micron-level control of mortise and tenon gaps, necessitating the development of real-time calibration technology that can dynamically adapt to the nonlinear characteristics of wood materials, especially under high-speed cutting conditions, to simultaneously address the stress concentration problems on the mating surfaces caused by deformation in density abrupt change areas and fiber tearing.

[0003] Current mainstream solutions employ infrared 3D scanning servo compensation systems. These systems use infrared sensors to scan the mortise and tenon mating surfaces, generating point cloud topology and extracting contour geometric deviation data to drive servo motors for dynamic compensation of the tool path. Some optimized solutions incorporate strain gauge feedback mechanisms to monitor local stress changes in the wood during cutting and adjust the feed rate based on a preset deformation threshold library.

[0004] The current mainstream solution combining infrared scanning with servo compensation has three technical bottlenecks: lack of density gradient perception; infrared sensors can only capture surface geometry and cannot penetrate the wood to obtain the density gradient distribution in the transition zone between core and sapwood, making it impossible for the system to predict the latent deformation caused by abrupt density changes; sluggish dynamic response, limited by the viscoelastic properties of wood and the response frequency of strain gauges, resulting in cumulative error effects during high-speed cutting; and uncontrolled texture-mechanical coupling, as existing algorithms ignore the nonlinear coupling mechanism between fiber direction and cutting force, fiber tearing can cause the compensation value to shift, and it is impossible to dynamically correct the phase error caused by wood stress relaxation. Summary of the Invention

[0005] This application provides a laser real-time calibration method and system for the processing accuracy of wooden door tenon joints, which solves the problem of the lack of recognition ability of internal density gradient distribution of wood in the prior art.

[0006] Firstly, this application provides a method for real-time laser calibration of the machining accuracy of mortise and tenon joints in wooden doors, including: Non-contact density distribution data of wood in the wood door processing area is obtained, and a density gradient map is constructed based on the density distribution data by performing a three-dimensional spatial interpolation operation. The density gradient map is matched with the geometric contour of the mortise and tenon mating surface and associated with the density abrupt change region of the wood to generate a targeted constraint command. The targeted constraint command is then used to drive and control the laser emission direction to align with the normal of the mortise and tenon mating surface and penetrate the wood. The diffraction pattern of the laser is acquired and a transformation operation integrating the wood fiber orientation distribution characteristics is performed to generate phase correction data, and a phase feature set combining texture and density is output. The phase feature set and the density gradient map are fused to generate the deformation feature set of the tenon and mortise, and the main influence factor separation operation is performed on the deformation feature set to extract the deformation parameters dominated by the wood density gradient. At the same time, a nonlinear calibration function for the tenon and mortise gap is constructed based on the deformation parameters. The predicted deformation output by the calibration function is compared with the actual machining displacement in real time. A trajectory adjustment signal is generated to control the tool movement path. The adjusted tool movement path is then scanned with a laser to measure the feedback data of the tenon and mortise clearance, and the nonlinear calibration function is updated simultaneously to complete the calibration closed loop.

[0007] Optionally, the phase feature set and the density gradient map are fused to generate a deformation feature set of the mortise and tenon joint, and a main influencing factor separation operation is performed on the deformation feature set to extract deformation parameters dominated by the wood density gradient. Simultaneously, a nonlinear calibration function for the mortise and tenon gap is constructed based on the deformation parameters, including: The phase feature set and the density gradient map are multiplied at corresponding positions at the three-dimensional space grid nodes to generate the deformation feature set; The mesh dataset corresponding to the deformation feature set is decomposed directionally, and the data components that are consistent with the wood grain direction are retained as the main deformation parameters. Based on the main deformation parameters, a polynomial relationship is established in the region of uniform wood density, and a transition function relationship is established in the region of abrupt density change. Based on the requirements of the tenon and mortise gap, the function partition boundary is adaptively adjusted. When the difference in the calculation results of adjacent partitions exceeds a preset threshold, the function partition boundary is redefined and the sampling point density is increased in the transition area. The final output is a nonlinear calibration function for the mortise and tenon gap, which includes the coordinate range of each zone, the function expression of each zone, and the density influence coefficient.

[0008] Optionally, the predicted deformation output by the calibration function is compared with the actual machining displacement in real time to generate a trajectory adjustment signal to control the tool movement path. The adjusted tool movement path is then updated using laser scanning to measure the feedback data of the tenon-mortise clearance, thus completing the calibration closed loop. This includes: The predicted deformation value calculated by the nonlinear calibration function is converted into a correction amount for the tool motion trajectory, wherein the correction component along the wood grain direction is amplified proportionally. The correction amount is superimposed on the preset tool motion path in real time by the motion control system. For straight cutting segments, equal-interval interpolation correction is used, and for curved segments, curvature radius ratio correction is used. After completing the set cutting length, a detection device coaxial with the tool is used to scan the processed surface of the wood to obtain the actual deviation of the mortise and tenon gap size and angle. When the detected actual deviation exceeds the set threshold, the coefficient of the nonlinear calibration function corresponding to the wood density zone is adjusted. If the adjustment still does not meet the requirements, a transition function segment is added in the wood density zone. When the actual machining dimension fluctuation range meets the requirements after continuous correction, the calibration process is terminated and the current machining parameters are locked.

[0009] Optionally, a density gradient map is constructed by performing a three-dimensional spatial interpolation operation based on the density distribution data, including: A non-contact scanning device emits multi-band detection signals along the surface and internal depth of the wood door processing area, and receives the signal intensity attenuation sequence after penetrating the wood. By performing back projection calculations on each spatial location point where the signal strength attenuation sequence is located, the unit volume mass value of each location point at different depth layers is obtained. Establish a three-dimensional spatial grid coordinate system, and use the unit volume mass value of each spatial location point as the grid node value; For any spatial location point that is not the value of the grid node, the unit volume mass value of the adjacent grid node is used to calculate the continuous density value of the corresponding location. The density change rate of adjacent grid nodes is calculated layer by layer along the thickness direction of the wood, and the region where the density change rate exceeds a set threshold is marked as the density abrupt boundary. Connect all density abrupt boundary lines to form a three-dimensional isosurface, and output the density change rate vector field between the three-dimensional isosurfaces as a density gradient map.

[0010] Optionally, the density gradient map is matched with the geometric contour of the mortise and tenon mating surface and associated with the density abrupt change region of the wood to generate targeted constraint instructions, including: Extract the design geometric contour of the mortise and tenon mating surface, discretize the design geometric contour into a set of triangular facets, and calculate the coordinates of the center point and the direction of the normal vector of each point in the set of triangular facets. Establish a spatial mapping relationship between the density gradient map and the center point, and locate the density abrupt change boundary corresponding to each center point; With the density abrupt change boundary as the center, a spherical action domain is formed by expanding outwards, with the radius proportional to the local density change rate. When the angle between the normal vector and the density gradient vector within the spherical domain is less than a certain angle, a targeting constraint instruction is generated, which includes the corresponding triangular facet number, the normal vector correction angle, and the laser penetration depth.

[0011] Optionally, applying the targeted constraint command to drive and control the laser emission direction to align with the normal of the mortise and tenon mating surface and penetrate the wood includes: The triangular facet numbers contained in the target constraint command are analyzed, and the laser emitter is driven to move to the corresponding geometric contour position. The pitch and yaw axes of the laser emitter are adjusted according to the normal vector correction angle contained in the target constraint command, so that the laser center axis coincides with the corrected normal vector; Based on the required penetration depth, adjust the refractive power of the laser focusing lens group so that the focal point is located at the corresponding depth inside the wood; Trigger pulsed laser emission, maintaining the duration of a single emission inversely proportional to the local density value of the wood.

[0012] Optionally, a transformation operation integrating texture-aware optics and wood fiber orientation distribution features is performed to generate phase-corrected data, outputting a joint texture and density phase feature set, including: A diffraction pattern sensor array is arranged on the exit side of the laser penetrating the wood to record the light and dark distribution matrix formed by the laser spots; The light and dark distribution matrix is ​​radially segmented to extract the stripe width variation sequence along the wood fiber extension direction; Establish a mapping relationship between the direction of the wood fibers and the stripe width variation sequence. When the difference in width between adjacent stripes exceeds the average fiber spacing, it is marked as a fiber breakage feature point. Using the fiber breakage feature point as a reference, the phase offset is calculated in all directions to generate a phase correction grid covering the entire scanning area; The offset of each node in the phase correction mesh is multiplied by the density gradient value at the corresponding position to output a phase feature set that combines texture and density.

[0013] Secondly, this application provides a real-time laser calibration system for the processing accuracy of wooden door tenon joints, comprising: The execution module is used to acquire non-contact density distribution data of wood in the wood door processing area, and to perform three-dimensional spatial interpolation operation based on the density distribution data to construct a density gradient map; The generation module is used to match the density gradient map with the geometric contour of the mortise and tenon mating surface and associate it with the density change region of the wood, generate a target constraint command, and apply the target constraint command to drive and control the laser emission direction to align with the normal of the mortise and tenon mating surface and penetrate the wood. The acquisition module is used to acquire the diffraction pattern of the laser and perform a transformation operation that integrates the wood fiber orientation distribution characteristics with texture-aware optics to generate phase correction data and output a phase feature set that combines texture and density. The extraction module is used to fuse the phase feature set and the density gradient map to generate the deformation feature set of the tenon and mortise, and to perform a main influence factor separation operation on the deformation feature set to extract the deformation parameters dominated by the wood density gradient. At the same time, a nonlinear calibration function for the tenon and mortise gap is constructed based on the deformation parameters. The generation module is also used to compare the predicted deformation output by the calibration function with the actual machining displacement in real time, generate a trajectory adjustment signal to control the tool movement path, and update the nonlinear calibration function by using laser scanning to measure the feedback data of the tenon and mortise clearance on the adjusted tool movement path, thereby completing the calibration closed loop.

[0014] Thirdly, this application provides a computing device, including a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are invoked and executed by the processing component to implement a real-time laser calibration method for the processing accuracy of wooden door tenon joints as described in the first aspect above.

[0015] Fourthly, this application provides a computer storage medium storing a computer program, which, when executed by a computer, implements a real-time laser calibration method for the machining accuracy of wooden door tenons and mortises as described in the first aspect.

[0016] This application acquires wood density distribution data and constructs a three-dimensional density gradient map non-contactly, enabling it to penetrate and identify density abrupt change zones within the wood. By matching the density gradient map with the mortise and tenon geometric contours to generate targeted constraint commands, it can drive a laser to penetrate the wood with normal precision. By acquiring laser diffraction patterns and fusing fiber orientation features to perform texture-aware transformation, it generates phase correction data to address fiber tearing and offset. By fusing the phase feature set and density gradient map to generate a deformation feature set, it extracts the density gradient-dominated deformation parameters. By constructing a nonlinear calibration function, it compares the predicted deformation with the actual displacement in real time, dynamically adjusts the tool path with a μs-level response, and updates the calibration function in a closed loop based on the laser-measured mortise and tenon gap data.

[0017] Further, the phase feature set and density gradient map are multiplied at the 3D mesh nodes to generate a deformation feature set. The directional decomposition of the mesh data retains components consistent with the texture direction. A polynomial function relationship is established in the density uniform region, and a hyperbolic tangent transition function is constructed in the density abrupt change region. When the difference between the calculation results of adjacent partitions exceeds a threshold, the function boundary is dynamically redrawn and the sampling point density in the transition region is increased. Finally, a nonlinear calibration function containing the partition coordinate range, function expression, and density influence coefficient is output. The dot product operation achieves dimensionality reduction through the fusion of physical quantities of texture phase and density gradient; the directional decomposition locks the main deformation components, improving the signal-to-noise ratio; the partition function modeling reduces the fitting error in the density abrupt change region; the boundary redrawing mechanism and transition region sampling optimization improve the compensation accuracy of the pine end face-core transition region; and finally, the nonlinear calibration calculation is completed, resulting in high uniformity of the mortise and tenon joint gap.

[0018] These or other aspects of this application will become more apparent in the following description of the embodiments. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 A flowchart of a laser real-time calibration method for the processing accuracy of mortise and tenon joints in wooden doors, provided in this application, is shown. Figure 2 This application provides a schematic diagram of the structure of a laser real-time calibration system for the processing accuracy of mortise and tenon joints in wooden doors. Figure 3 A schematic diagram of the structure of a computing device provided in this application is shown. Detailed Implementation

[0021] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0022] Currently, high-end wooden door mortise and tenon joint processing faces three fundamental challenges: First, the equipment is like "blind men touching an elephant," only able to scan the surface shape of the wood, completely unable to perceive the density variations of the internal material, such as the sudden density change at the junction of the heartwood and bark, resulting in the mortise and tenon appearing to fit perfectly but actually warping internally; second, the system response has a fatal delay, with error compensation commands taking 0.25 seconds to be transmitted, equivalent to the time it takes for a person to blink, causing small errors to snowball during high-speed processing; third, treating the wood as a "solid piece of iron," ignoring the direction of the fiber texture, is like cutting cloth without distinguishing the warp and weft, leading to fiber tearing during cutting, with actual measured finished product dimensions deviating by more than a quarter.

[0023] This application pioneers a "laser-guided diagnostic + real-time intelligent control" technology: First, a special laser penetrates the wood, similar to an upgraded version of a supermarket barcode scanner, generating a "3D material map" that displays internal density changes. Then, based on the map, the laser angle is intelligently calibrated to ensure vertical penetration of key areas. Next, the rainbow-like light spots formed by the laser are analyzed, similar to detecting the oleophobic coating on a mobile phone, intelligently identifying fiber orientation and generating compensation parameters. Finally, a self-learning mathematical model is established, similar to dynamic congestion avoidance in navigation software, automatically comparing predicted deformation with actual deviations every 0.01 seconds and fine-tuning the tool trajectory in real time. This solution achieves breakthroughs: high density mutation detection rate, improved response speed, and reduced fiber tearing deviation, ultimately enabling the mortise and tenon joint clearance control to reach 1 / 10 the precision of a human hair, equivalent to the level of craftsmanship required for two A4 sheets of paper to be tightly fitted together.

[0024] In some of the processes described in the specification, claims, and accompanying drawings of this application, multiple operations appearing in a specific order are included. However, it should be clearly understood that these operations may not be executed in the order they appear herein, or may be executed in parallel. The operation numbers, such as 101, 102, etc., are merely used to distinguish different operations and do not themselves represent any execution order. Furthermore, these processes may include more or fewer operations, and these operations may be executed sequentially or in parallel. It should be noted that the descriptions such as "first," "second," etc., in this document are used to distinguish different messages, devices, modules, etc., and do not represent a chronological order, nor do they limit "first" and "second" to different types.

[0025] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0026] Figure 1 This application provides a flowchart of a method for real-time laser calibration of the machining accuracy of wooden door tenons and mortises, as shown in the embodiments of this application. Figure 1As shown, the method includes: 101. Obtain non-contact density distribution data of wood in the wood door processing area, and construct a density gradient map based on the density distribution data by performing a three-dimensional spatial interpolation operation; Optionally, step 101 may specifically include the following steps: 1011. A non-contact scanning device is used to transmit multi-band detection signals along the surface and internal depth of the wood door processing area, and the signal intensity attenuation sequence after penetrating the wood is received. 1012. After back-projection calculation of each spatial location point where the signal strength attenuation sequence is located, the unit volume mass value of each location point at different depth layers is obtained; 1013. Establish a three-dimensional spatial grid coordinate system, and use the unit volume mass value of each spatial location point as the grid node value; 1014. For any spatial location point that is not the value of the grid node, the continuous density value at the corresponding location is obtained by calculating the unit volume mass value of the adjacent grid nodes. 1015. Calculate the density change rate of adjacent grid nodes layer by layer along the thickness direction of the wood, and mark the region where the density change rate exceeds a set threshold as the density abrupt change boundary; 1016. Connect all density abrupt boundary lines to form a three-dimensional isosurface, and output the density change rate vector field between the three-dimensional isosurfaces as a density gradient map.

[0027] In the above scheme, multi-band detection signal refers to the simultaneous transmission of scanning waves at multiple frequencies, similar to the combined use of X-ray and B-ultrasound during a physical examination; signal intensity attenuation sequence refers to the degree of energy reduction of the scanning wave after penetrating the wood; unit volume mass value represents the actual weight of wood per cubic centimeter; three-dimensional spatial grid coordinate system divides the wood into tiny cubic units according to length, width, and height; continuous density value is the density estimate of the region between grids; density change rate refers to the increase or decrease in wood density per millimeter of thickness; density abrupt change boundary is the dividing line of drastic density change; three-dimensional isosurface is the spatial surface formed by all density abrupt change points; density change rate vector field is a three-dimensional model using directional arrows to represent the density change trend.

[0028] In this embodiment, firstly, in step 1011: in the pine door panel processing area of ​​the factory, a scanning device transmits three-band signals of 1.0GHz / 2.4GHz / 5.8GHz along the surface and internal depth of the wood door processing area. Similar to multi-frequency transmission in a router, the signal strength attenuation sequence is measured by the receiver after penetrating the wood; for example, the 2.4GHz wave attenuates by 30dB at a depth of 2cm. Secondly, in step 1012: a back projection calculation is performed on each scanning point. For example, the unit volume mass value at location (10,20,30) = original signal strength × attenuation coefficient, i.e. Where μ is the absorption coefficient of pine wood, taken as 0.15 / cm, and m = 0.82 g / cm³ when the measured depth d = 3 cm. Next, in step 1013: a three-dimensional spatial grid coordinate system with a side length of 1 mm is established, and the mass values ​​of the 520 location points calculated in the previous step are stored in the corresponding grid nodes as grid node values. Then, in step 1014: for any spatial location point whose grid node value is not mentioned, such as (10.5, 20.3, 30.7), the continuous density value of the corresponding location is obtained by weighted averaging of 8 adjacent nodes, where the formula is: The weights w are distributed according to the reciprocal of the distance, resulting in ρ = 0.79 g / cm³. Then, in step 1015, the density change rate between adjacent layers is calculated along the wood thickness direction. For example, the density of layer Z=5mm is 0.8 g / cm³, which abruptly changes to 1.2 g / cm³ at Z=6mm, a change rate of 50% / mm exceeding the 30% threshold, and is marked as an abrupt boundary. Finally, in step 1016, all abrupt boundaries are connected to form a surface, and the density change direction between surfaces is extracted, such as from the core to the bark, outputting a 3D density gradient map with arrows.

[0029] In practical applications, in the wooden door production workshop of Company A, when processing Class B pine door panels, a standard scanning device is used to perform step 101: emitting a 0.5-8GHz sweep frequency signal to penetrate the wood, establishing a 300×200×60 three-dimensional mesh system in a processing area of ​​200mm long × 150mm wide × 30mm thick; detection revealed a transition zone with a density ranging from 0.75g / cm³ to 1.15g / cm³ in a layer 15-18mm deep from the surface. Through three-dimensional reconstruction, a gradient map is output, clearly showing the radial density increase band extending from the core material to the sapwood.

[0030] This solution achieves "transparent" analysis of the internal structure of wood: penetrating scanning overcomes the limitations of surface detection; three-dimensional mesh reconstruction enables millimeter-level positioning of density distribution; intelligent identification of areas with drastic density changes and construction of a three-dimensional gradient model provide accurate material basis for subsequent processing compensation, significantly reducing the risk of processing deformation caused by uneven internal materials.

[0031] 102. Match the density gradient map with the geometric contour of the mortise and tenon mating surface and associate it with the density change region of the wood to generate a targeted constraint command. Apply the targeted constraint command to drive and control the laser emission direction to align with the normal of the mortise and tenon mating surface and penetrate the wood. Optionally, step 102 may specifically include the following steps: 1021. Extract the design geometric contour of the mortise and tenon mating surface, discretize the design geometric contour into a set of triangular facets, and calculate the coordinates of the center point and the direction of the normal vector of each point in the set of triangular facets. 1022. Establish a spatial mapping relationship between the density gradient map and the center point, and locate the density abrupt change boundary corresponding to each center point; 1023. With the density abrupt change boundary as the center, a spherical action domain is formed by expanding outwards, with the radius proportional to the local density change rate; 1024. When the angle between the normal vector and the density gradient vector within the spherical domain is less than a certain angle, a targeting constraint instruction containing the corresponding triangular facet number, the normal vector correction angle, and the laser penetration depth is generated.

[0032] 1025. Analyze the triangular facet numbers contained in the target constraint command and drive the laser emitter to move to the corresponding geometric contour position; 1026. Adjust the pitch and yaw axes of the laser emitter according to the normal vector correction angle contained in the target constraint command, so that the laser center axis coincides with the corrected normal vector; 1027. Based on the required penetration depth, adjust the diopter of the laser focusing lens group so that the focal point is located at the corresponding depth inside the wood; 1028. Trigger pulsed laser emission, maintaining the duration of a single emission inversely proportional to the local density value of the wood.

[0033] In the above scheme, the design geometric contour refers to the shape of the design drawing of the mortise and tenon structure; the triangular facet set is the set of small triangular puzzle pieces that divide the contour; the center point coordinates and normal vector refer to the center position and vertical direction of each triangular piece; the spatial mapping relationship is the method of mapping the position of the triangle to the internal density map of the wood; the density mutation boundary is the dividing line of the drastic change in the internal density of the wood; the spherical action domain is the spherical influence area formed with the mutation boundary as the center; the normal vector correction angle is the fine-tuning value of adjusting the laser irradiation direction; and the penetration depth refers to the internal position of the wood that the laser needs to reach.

[0034] In this embodiment, firstly, in step 1021, the geometric contour of the mortise and tenon surface in the design drawing is discretized into a set of triangular facets, such as 500 triangular mesh units, in the pine door panel tenon processing area. The center position of each triangular facet is automatically calculated, for example, the center point coordinates of number 103 are 15 mm, 20 mm, and 5 mm, and its perpendicular surface direction is calculated, for example, the vector direction of 0, 0, 1. Secondly, in step 1022, the center point coordinates of 103 are input into the density gradient map system, and the corresponding position is matched, such as the existence of a key density abrupt change layer at a depth of 5 mm, and the density abrupt change boundary corresponding to each center point is located; for example, if the wood density abruptly changes from 0.8 g / cm³ to 1.2 g / cm³, the abrupt change boundary coordinates are automatically calibrated to 15.2 mm, 20.1 mm, and 5.3 mm. Next, in step 1023, a spherical space is established with the abrupt boundary coordinates as the center and the effective area radius R equal to 3 mm based on a local density change rate of 40% per millimeter. The more drastic the density change, the larger the effective area. This spherical region covers the center point of the 103 triangular facet. Then, in step 1024, the cosine value of the angle between the 103 normal vectors 0, 0, 1 and the maximum density gradient vectors 0.1, 0.2, 0.9 within the spherical region is detected (0.95, corresponding to an angle of 18 degrees). When the angle between the normal vector and the density gradient vector within the spherical effective area is less than a certain angle, such as less than a 20-degree threshold, a targeting command is generated, including triangular facet number 103, a normal vector correction angle of 2 degrees, and a penetration depth of 8 mm. Subsequently, in step 1025, the control system analyzes the number 103 and drives the laser motion mechanism to precisely position it at the corresponding geometric contour location; such as the processing area coordinates of 15 mm, 20 mm, and 5 mm. Next, in step 1026, the laser gimbal is adjusted according to a 2-degree correction angle to fine-tune the emission direction from the original 0, 0, 1 vector to a new direction of 0.035, 0, 0.999, ensuring it is perpendicular to the wood fibers and aligning the laser's central axis with the corrected normal vector. Then, in step 1027, based on the 8 mm penetration depth requirement, the optical lens group is automatically adjusted to focus the laser at the corresponding depth within the wood; for example, the diopter is adjusted from +3D to +5D, positioning the laser focus in the density-abrupt core region within the wood at a depth of 8 mm. Finally, in step 1028, based on the high density of 1.2 g / cm³ in this region, the pulse duration is automatically set to 50 microseconds, with higher density resulting in shorter pulse times, triggering the laser to penetrate the wood and capture the diffraction signal.

[0035] In practical applications, in the wood processing workshop of Company A, when performing mortise and tenon processing on Class B wood workpieces, step 102 is executed: the geometric contour of the mortise and tenon mating surface is discretized into 380 triangular facets; based on the density gradient map, a sudden change zone with density from 0.75 g / cm³ to 1.15 g / cm³ is identified at a depth of 5 mm in the workpiece; a targeting command is generated for the center point of triangular facet number 195, driving the laser emitter to shift by 1.8 degrees and focus to a depth of 7 mm, penetrating the area with a pulse duration of 75 microseconds.

[0036] This solution enables intelligent linkage between laser and the internal structure of wood: by precisely matching geometric contours and density abrupt changes, the laser incident angle and penetration intensity are dynamically controlled to ensure that the detection signal penetrates the key material change area vertically, providing a high-quality data foundation for subsequent texture analysis.

[0037] 103. Acquire the diffraction pattern of the laser and perform a transformation operation that integrates the wood fiber orientation distribution characteristics with texture-aware optics to generate phase correction data, and output a phase feature set that combines texture and density; Optionally, step 103 may specifically include the following steps: 1031. Arrange a diffraction pattern sensor array on the exit side of the laser penetrating the wood and record the light and dark distribution matrix formed by the laser spots; 1032. The light and dark distribution matrix is ​​radially segmented to extract the stripe width variation sequence along the wood fiber extension direction; 1033. Establish a mapping relationship between the direction of the wood fibers and the stripe width variation sequence. When the difference in width between adjacent stripes exceeds the average fiber spacing, it is marked as a fiber breakage feature point. 1034. Using the fiber breakage feature point as a reference, calculate the phase offset in all directions to generate a phase correction grid covering the entire scanning area; 1035. Multiply the offset of each node in the phase correction mesh with the density gradient value at the corresponding position to output a phase feature set that combines texture and density.

[0038] In the above scheme, the diffraction pattern sensor array refers to a combination of light sensors arranged densely like a mobile phone camera; the brightness and darkness distribution matrix refers to the data of the arrangement of bright and dark spots formed after the laser penetrates the wood; radial segmentation refers to the radial cutting pattern from the center outward, like cutting a cake; the stripe width variation sequence is a record of the change in the width of the light spot along the direction of the wood grain; the average fiber spacing represents the average distance between the wood grain threads; the fiber breakage feature point is the location marker of the breakage in the wood grain; the phase offset refers to the slight positional deviation value of the light caused by the breakage of the grain; and the phase correction grid is a data model that records the correction amount of the entire area using grid nodes.

[0039] In this embodiment, firstly, in step 1031, a 100×100 sensor array is arranged at the laser penetration point exit of the pine wood door panel to record the light and dark distribution matrix formed by a diffraction spot with a diameter of 8 mm. The central bright area has a diameter of 0.5 mm, and the edges show alternating light and dark stripes. Secondly, in step 1032, the light and dark distribution matrix is ​​radially segmented into a radial pattern along the pine wood grain at a 30-degree angle, and 10 consecutive stripe width sequences are extracted, such as 0.15 mm, 0.17 mm, 0.13 mm, 0.20 mm, 0.22 mm, etc. Then, in step 1033, a mapping relationship between the wood fiber direction and the stripe width variation sequence is established. For example, if the difference between the width of the 3rd stripe (0.13 mm) and the 4th stripe (0.20 mm) is 0.07 mm, and the difference between adjacent stripe widths exceeds the average fiber spacing, it is marked as a fiber breakage feature point; if it exceeds the allowable difference of 0.05 mm (0.18 mm average pine fiber spacing), the fiber breakage point is marked in the 5th row and 8th column. Then, in step 1034, the phase shift is calculated outward from the break point. For example, the shift at a distance of 2 mm from the break point is calculated using the following formula: Where k=2π, s=0.5 mm is the attenuation coefficient, and d=2 mm yields an offset of 0.25 radians, generating a phase correction mesh covering the entire 8 mm region. Finally, in step 1035, the mesh node offset of 0.25 radians is multiplied by the density value of 1.15 g / cm³, outputting a joint phase feature set, such as 0.288 radians·g / cm³.

[0040] In practical applications, in the wood processing system of Company A, step 103 is performed on type B wooden workpieces: laser diffraction patterns are acquired through an 80×80 sensor array; the stripe width is detected to change abruptly from 0.12 mm to 0.25 mm along the 45-degree texture direction; the break point is marked in coordinate 15 rows and 20 columns and the correction mesh is calculated; the phase feature set is output for subsequent processing compensation.

[0041] This solution enables precise analysis of the wood's internal texture: by intelligently identifying laser diffraction features, it effectively captures potential areas such as fiber breakage; by combining density distribution data to generate joint phase features, it provides key material structure basis for high-precision processing compensation, significantly improving the adaptability of mortise and tenon mating surfaces.

[0042] 104. The phase feature set and the density gradient map are fused to generate the deformation feature set of the tenon and mortise, and the main influence factor separation operation is performed on the deformation feature set to extract the deformation parameters dominated by the wood density gradient. At the same time, a nonlinear calibration function for the tenon and mortise gap is constructed based on the deformation parameters. Optionally, step 104 may specifically include the following steps: 1041. Perform dot product operations on the phase feature set and the density gradient map at corresponding positions in the three-dimensional space grid nodes to generate the deformation feature set; 1042. Perform directional decomposition on the grid dataset corresponding to the deformation feature set, and retain the data components that are consistent with the direction of wood grain as the main deformation parameters; 1043. Based on the main deformation parameters, establish a polynomial relationship in the region of uniform wood density and a transition function relationship in the region of abrupt density change; 1044. Based on the requirements of the tenon and mortise gap, the function partition boundary is adaptively adjusted. When the difference in the calculation results of adjacent partitions exceeds a preset threshold, the function partition boundary is redefined and the sampling point density is increased in the transition area. 1045. The final output is a nonlinear calibration function for the mortise and tenon gap, which includes the zone coordinate range, the function expression of each zone, and the density influence coefficient.

[0043] In the above scheme, dot product operation refers to multiplying the values ​​of corresponding positions of two sets of data; directional decomposition is the operation of extracting data features along a specific angle; the main deformation parameters represent the core factors that have the greatest impact on the deformation of the tenon and mortise; polynomial relations are used to describe the mathematical laws of simple regions; transition function relations are the smooth mathematical expression of complex changing regions; partition boundaries are the intersection lines of different mathematical models; and density influence coefficients represent the degree of effect of density changes on deformation.

[0044] In this embodiment, firstly, in step 1041, at a point coordinate (e.g., 20 mm, 30 mm, 10 mm) in the three-dimensional mesh system of the pine door panel tenon area, a phase feature value of 0.25 radians·grams per cubic centimeter is taken and multiplied by a density gradient value of 1.15 grams per cubic centimeter per millimeter to obtain a deformation feature value of 0.2875 radians·mm, thus obtaining the corresponding deformation feature set. Secondly, in step 1042, the mesh dataset corresponding to the deformation feature set is decomposed along the door panel grain direction at a 30-degree angle, retaining the data component consistent with the wood grain direction (e.g., retaining the directional component of 0.263 radians·mm and discarding other directional interference values). Then, in step 1043, based on the main deformation parameters, a quadratic polynomial function is used to calculate the deformation in the density uniform area, using the following formula: Where a, b, and c are fitting coefficients. For example, the expression Δd = 0.005x²; a hyperbolic tangent function is established in the density abrupt change region, with the formula: ; Where k is the proportionality coefficient. Let Δρ be the baseline density and Δρ be the transition interval. For example, Δd = tanh((ρ-1.0) / 0.1). Then, in step 1044, the function partition boundary is adaptively adjusted according to the requirements of the tenon and mortise gap. When the calculated difference between the two sides of the partition boundary exceeds the threshold of 0.01 mm by 0.02 mm, the boundary is adjusted from coordinate 20.5 mm to 21.0 mm, and the number of sampling points is tripled in the new transition zone. Finally, in step 1045, the parameter set with a density influence coefficient of 0.15 is output for the partition range of 20 mm to 21 mm using the hyperbolic tangent function and 21 mm to 25 mm using the polynomial function.

[0045] In practical applications, in the wood processing system of Company A, step 104 is performed on type B wooden workpieces: fusing phase features and density gradients at three-dimensional mesh points; extracting principal deformation parameters along a set direction; establishing a partition function model; adjusting the boundary to a new position according to the gap standard; and outputting a nonlinear calibration function containing a function expression.

[0046] This solution achieves intelligent modeling of deformation characteristics: it accurately identifies the main influencing factors through data fusion; it establishes mathematical relationships in different regions to adapt to changes in wood properties; it dynamically optimizes function boundaries to ensure model accuracy; and finally, it outputs a highly adaptable calibration function to improve processing precision.

[0047] 105. In real time, compare the predicted deformation output by the calibration function with the actual machining displacement, generate a trajectory adjustment signal to control the tool movement path, and use laser scanning to measure the feedback data of the tenon and mortise clearance on the adjusted tool movement path while updating the nonlinear calibration function to complete the calibration closed loop.

[0048] Optionally, step 105 may specifically include the following steps:

[0049] 1051. The predicted deformation value calculated by the nonlinear calibration function is converted into a correction amount for the tool motion trajectory, wherein the correction component along the wood grain direction is amplified proportionally.

[0050] 1052. The correction amount is superimposed on the preset tool motion path in real time through the motion control system. For straight cutting segments, equal-interval interpolation correction is used, and for curved segments, curvature radius ratio correction is used.

[0051] 1053. After completing the set cutting length, use a detection device coaxial with the tool to scan the processed surface of the wood to obtain the actual mortise and tenon gap size and angle deviation.

[0052] 1054. When the detected actual deviation exceeds the set threshold, adjust the coefficient of the nonlinear calibration function corresponding to the wood density zone. If the adjustment still does not meet the requirements, add a transition function segment in the wood density zone.

[0053] 1055. When the actual machining dimension fluctuation range meets the requirements after continuous correction, terminate the calibration process and lock the current machining parameters.

[0054] In the above scheme, the predicted deformation value is the estimated amount of wood deformation in advance; the correction amount refers to the tool movement distance that needs to be adjusted; the equal-interval interpolation is like adjusting by evenly dotting points on a straight line; the radius of curvature ratio correction refers to fine-tuning according to the arc ratio at the curve; the coaxial detection device is a measuring probe installed next to the tool; the actual deviation is the difference between the measured size after processing and the design; the newly added transition function segment is equivalent to adding a buffer curve in the abrupt change region.

[0055] In this embodiment, firstly, in step 1051, the system calculates the predicted deformation value of the pine tenon position (0.12 mm) using the nonlinear calibration function. Then, based on the 30-degree grain direction, this directional correction is amplified and converted into a tool motion trajectory correction, such as amplifying it to 0.15 mm, while maintaining a constant 0.12 mm perpendicular to the grain direction. Secondly, in step 1052, the motion control system superimposes the correction amount onto the preset tool motion path in real time. For example, in a 200 mm long straight cutting segment, the straight segment uses an interpolation formula:

[0056]

[0057] Where ΔP_max is the maximum correction amount of 0.15 mm, and L_step is the step size of 10 mm when setting correction points every 10 mm, L_total=200 mm, and when the 5th point is at position i=5, ΔP_5=0.15×(5×10) / 200=0.0375 mm; in the curve segment with a radius of 80 mm, the adjustment is made according to the curvature ratio, and the formula is:

[0058]

[0059] Where r=30 mm is the current radius of curvature, R=80 mm is the reference radius, k=1.2, and ΔR=1.2×0.15×(1-30 / 80)=0.118 mm. Next, in step 1053, after completing the set cutting length (e.g., when completing 50 mm), the laser probe on the tool scans the machined surface. The measured tenon width is 0.05 mm narrower than the design value, and the deviation of the actual formed tenon-mortise gap size and angle is obtained, such as an angle deviation of 0.3 degrees. Then, in step 1054, because the 0.05 mm deviation exceeds the threshold of 0.03 mm, the coefficient of the density uniformity zone function is adjusted from 0.15 to 0.17. If the deviation still exceeds the tolerance after adjustment and retesting, a transition function segment is added between coordinates 50-55 mm. Finally, in step 1055, after three consecutive corrections, the measured dimensional fluctuation meets the requirement of less than 0.01 mm, the system terminates the calibration process and locks the current machining parameters.

[0060] In practical applications, on the wood processing line of Company A, step 105 is performed on type B workpieces: amplify the texture direction correction amount based on the predicted deformation value; correct the tool path in segments; the measured gap deviation after cutting is 0.04 mm; after adjusting the calibration function coefficients is ineffective, add a transition segment; and lock the parameters after continuous correction to meet the standard.

[0061] This solution enables the self-evolution of machining accuracy: it corrects tool paths in a timely manner through real-time feedback; it uses intelligent judgment functions to optimize the process; and it automatically locks in the optimal parameters, ultimately forming a closed-loop calibration system with learning capabilities, effectively improving product consistency.

[0062] This plan Figure 2 This application provides a schematic diagram of a laser real-time calibration method system for the processing accuracy of wooden door tenon joints, as shown in the embodiment of this application. Figure 2 As shown, the system includes:

[0063] Execution module 21 is used to acquire non-contact density distribution data of wood in the wood door processing area, and to construct a density gradient map by performing three-dimensional spatial interpolation operation based on the density distribution data;

[0064] The generation module 22 is used to match the density gradient map with the geometric contour of the mortise and tenon mating surface and associate it with the density change region of the wood, generate a target constraint command, and apply the target constraint command to drive and control the laser emission direction to align with the normal of the mortise and tenon mating surface and penetrate the wood.

[0065] Acquisition module 23 is used to acquire the diffraction pattern of the laser and perform a transformation operation that integrates the texture-aware optics and the orientation distribution characteristics of wood fibers to generate phase correction data, and output a phase feature set that combines texture and density.

[0066] Extraction module 24 is used to fuse the phase feature set and the density gradient map to generate the deformation feature set of the tenon and mortise, and to perform a main influence factor separation operation on the deformation feature set to extract the deformation parameters dominated by the wood density gradient. At the same time, a nonlinear calibration function for the tenon and mortise gap is constructed based on the deformation parameters.

[0067] The generation module 22 is also used to compare the predicted deformation output by the calibration function with the actual machining displacement in real time, generate a trajectory adjustment signal to control the tool movement path, and update the nonlinear calibration function by using laser scanning to measure the feedback data of the tenon and mortise clearance on the adjusted tool movement path, thereby completing the calibration closed loop.

[0068] Figure 2 The aforementioned laser real-time calibration system for the processing accuracy of wooden door tenon joints can perform... Figure 1The implementation principle and technical effects of the laser real-time calibration method for the mortise and tenon joint processing accuracy of wooden doors described in the above embodiment will not be repeated here. The specific operation methods of each module and unit in the laser real-time calibration system for the mortise and tenon joint processing accuracy of wooden doors described in the above embodiment have been described in detail in the embodiments related to this method, and will not be elaborated upon here.

[0069] In one possible design, Figure 2 The laser real-time calibration system for the mortise and tenon joint processing accuracy of wooden doors shown in the embodiment can be implemented as a computing device, such as... Figure 3 As shown, the computing device may include a storage component 31 and a processing component 32;

[0070] The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are invoked and executed by the processing component 32.

[0071] The processing component 32 is used for the above Figure 1 The embodiment describes a laser real-time calibration method for the processing accuracy of wooden door tenon joints.

[0072] The processing component 32 may include one or more processors to execute computer instructions to complete all or part of the steps in the above-described method. Alternatively, the processing component may be implemented as one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above-described method.

[0073] Storage component 31 is configured to store various types of data to support operations at the terminal. The storage component can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0074] Of course, computing devices may also include other components, such as input / output interfaces, display components, communication components, etc.

[0075] Input / output interfaces provide interfaces between processing components and peripheral interface modules, which can be output devices, input devices, etc.

[0076] The communication components are configured to facilitate wired or wireless communication between computing devices and other devices.

[0077] The computing device can be a physical device or an elastic computing host provided by a cloud computing platform. In this case, the computing device can refer to a cloud server, and the aforementioned processing components, storage components, etc., can be basic server resources rented or purchased from the cloud computing platform.

[0078] This application also provides a computer storage medium storing a computer program, which, when executed by a computer, can perform the above-described functions. Figure 1 The embodiment shown illustrates a laser real-time calibration method for the processing accuracy of mortise and tenon joints in wooden doors.

[0079] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0080] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0081] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0082] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for real-time laser calibration of the machining accuracy of mortise and tenon joints in wooden doors, characterized in that, include: Non-contact density distribution data of wood in the wood door processing area is obtained, and a density gradient map is constructed based on the density distribution data by performing a three-dimensional spatial interpolation operation. The density gradient map is matched with the geometric contour of the mortise and tenon mating surface and associated with the density abrupt change region of the wood to generate a targeted constraint command. The targeted constraint command is then used to drive and control the laser emission direction to align with the normal of the mortise and tenon mating surface and penetrate the wood. The diffraction pattern of the laser is acquired and a transformation operation integrating the wood fiber orientation distribution characteristics is performed to generate phase correction data, and a phase feature set combining texture and density is output. The phase feature set and the density gradient map are fused to generate the deformation feature set of the tenon and mortise, and the main influence factor separation operation is performed on the deformation feature set to extract the deformation parameters dominated by the wood density gradient. At the same time, a nonlinear calibration function for the tenon and mortise gap is constructed based on the deformation parameters. The predicted deformation output by the calibration function is compared with the actual machining displacement in real time. A trajectory adjustment signal is generated to control the tool movement path. The adjusted tool movement path is then scanned with a laser to measure the feedback data of the tenon and mortise clearance, and the nonlinear calibration function is updated simultaneously to complete the calibration closed loop.

2. The method according to claim 1, characterized in that, The phase feature set and the density gradient map are fused to generate a deformation feature set for the mortise and tenon joint. A main influencing factor separation operation is performed on the deformation feature set to extract deformation parameters dominated by the wood density gradient. Simultaneously, a nonlinear calibration function for the mortise and tenon gap is constructed based on these deformation parameters, including: The phase feature set and the density gradient map are multiplied at corresponding positions at the three-dimensional space grid nodes to generate the deformation feature set. The mesh dataset corresponding to the deformation feature set is decomposed directionally, and the data components that are consistent with the wood grain direction are retained as the main deformation parameters. Based on the main deformation parameters, a polynomial relationship is established in the region of uniform wood density, and a transition function relationship is established in the region of abrupt density change. Based on the requirements of the tenon and mortise gap, the function partition boundary is adaptively adjusted. When the difference in the calculation results of adjacent partitions exceeds a preset threshold, the function partition boundary is redefined and the sampling point density is increased in the transition area. The final output is a nonlinear calibration function for the mortise and tenon gap, which includes the coordinate range of each zone, the function expression of each zone, and the density influence coefficient.

3. The method according to claim 1, characterized in that, The predicted deformation output by the calibration function is compared with the actual machining displacement in real time to generate a trajectory adjustment signal to control the tool movement path. The adjusted tool movement path is then updated using laser scanning to measure the feedback data of the tenon-mortise clearance, thus completing the calibration closed loop. This includes: The predicted deformation value calculated by the nonlinear calibration function is converted into a correction amount for the tool motion trajectory, wherein the correction component along the wood grain direction is amplified proportionally. The correction amount is superimposed on the preset tool motion path in real time by the motion control system. For straight cutting segments, equal-interval interpolation correction is used, and for curved segments, curvature radius ratio correction is used. After completing the set cutting length, a detection device coaxial with the tool is used to scan the processed surface of the wood to obtain the actual deviation of the mortise and tenon gap size and angle. When the detected actual deviation exceeds the set threshold, the coefficient of the nonlinear calibration function corresponding to the wood density zone is adjusted. If the adjustment still does not meet the requirements, a transition function segment is added in the wood density zone. When the actual machining dimension fluctuation range meets the requirements after continuous correction, the calibration process is terminated and the current machining parameters are locked.

4. The method according to claim 1, characterized in that, Based on the density distribution data, a density gradient map is constructed by performing a three-dimensional spatial interpolation operation, including: A non-contact scanning device emits multi-band detection signals along the surface and internal depth of the wood door processing area, and receives the signal intensity attenuation sequence after penetrating the wood. By performing back projection calculations on each spatial location point where the signal strength attenuation sequence is located, the unit volume mass value of each location point at different depth layers is obtained. Establish a three-dimensional spatial grid coordinate system, and use the unit volume mass value of each spatial location point as the grid node value; For any spatial location point that is not the value of the grid node, the unit volume mass value of the adjacent grid node is used to calculate the continuous density value of the corresponding location. The density change rate of adjacent grid nodes is calculated layer by layer along the thickness direction of the wood, and the region where the density change rate exceeds a set threshold is marked as the density abrupt boundary. Connect all density abrupt boundary lines to form a three-dimensional isosurface, and output the density change rate vector field between the three-dimensional isosurfaces as a density gradient map.

5. The method according to claim 1, characterized in that, Matching the density gradient map with the geometric contour of the mortise and tenon mating surface and associating it with the density abrupt change regions of the wood generates targeted constraint instructions, including: Extract the design geometric contour of the mortise and tenon mating surface, discretize the design geometric contour into a set of triangular facets, and calculate the coordinates of the center point and the direction of the normal vector of each point in the set of triangular facets. Establish a spatial mapping relationship between the density gradient map and the center point, and locate the density abrupt change boundary corresponding to each center point; With the density abrupt change boundary as the center, a spherical action domain is formed by expanding outwards, with the radius proportional to the local density change rate. When the angle between the normal vector and the density gradient vector within the spherical domain is less than a certain angle, a targeting constraint instruction is generated, which includes the corresponding triangular facet number, the normal vector correction angle, and the laser penetration depth.

6. The method according to claim 1, characterized in that, The application of the targeted constraint command to drive and control the laser emission direction to align with the normal of the mortise and tenon mating surface and penetrate the wood includes: The triangular facet numbers contained in the target constraint command are analyzed, and the laser emitter is driven to move to the corresponding geometric contour position. The pitch and yaw axes of the laser emitter are adjusted according to the normal vector correction angle contained in the target constraint command, so that the laser center axis coincides with the corrected normal vector; Based on the required penetration depth, adjust the refractive power of the laser focusing lens group so that the focal point is located at the corresponding depth inside the wood; Trigger pulsed laser emission, maintaining the duration of a single emission inversely proportional to the local density value of the wood.

7. The method according to claim 1, characterized in that, A transformation operation that integrates texture-aware optics and the orientation distribution characteristics of wood fibers is performed to generate phase-corrected data, outputting a joint phase feature set of texture and density, including: A diffraction pattern sensor array is arranged on the exit side of the laser penetrating the wood to record the light and dark distribution matrix formed by the laser spots; The light and dark distribution matrix is ​​radially segmented to extract the stripe width variation sequence along the wood fiber extension direction; Establish a mapping relationship between the direction of the wood fibers and the stripe width variation sequence. When the difference in width between adjacent stripes exceeds the average fiber spacing, it is marked as a fiber breakage feature point. Using the fiber breakage feature point as a reference, the phase offset is calculated in all directions to generate a phase correction grid covering the entire scanning area; The offset of each node in the phase correction mesh is multiplied by the density gradient value at the corresponding position to output a phase feature set that combines texture and density.

8. A laser real-time calibration system for the processing accuracy of mortise and tenon joints in wooden doors, characterized in that, include: Non-contact density distribution data of wood in the wood door processing area is obtained, and a density gradient map is constructed based on the density distribution data by performing a three-dimensional spatial interpolation operation. The density gradient map is matched with the geometric contour of the mortise and tenon mating surface and associated with the density abrupt change region of the wood to generate a targeted constraint command. The targeted constraint command is then used to drive and control the laser emission direction to align with the normal of the mortise and tenon mating surface and penetrate the wood. The diffraction pattern of the laser is acquired and a transformation operation integrating the wood fiber orientation distribution characteristics is performed to generate phase correction data, and a phase feature set combining texture and density is output. The phase feature set and the density gradient map are fused to generate the deformation feature set of the tenon and mortise, and the main influence factor separation operation is performed on the deformation feature set to extract the deformation parameters dominated by the wood density gradient. At the same time, a nonlinear calibration function for the tenon and mortise gap is constructed based on the deformation parameters. The predicted deformation output by the calibration function is compared with the actual machining displacement in real time. A trajectory adjustment signal is generated to control the tool movement path. The adjusted tool movement path is then scanned with a laser to measure the feedback data of the tenon and mortise clearance, and the nonlinear calibration function is updated simultaneously to complete the calibration closed loop.

9. A computing device, characterized in that, It includes a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are invoked and executed by the processing component to implement a real-time laser calibration method for the processing accuracy of wooden door tenon joints as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that, The device contains a computer program that, when executed by a computer, implements a real-time laser calibration method for the machining accuracy of wooden door tenons and mortises as described in any one of claims 1 to 7.

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