High-precision monitoring system for tooth deviation in tooth cutting machining process

Abstract

The invention relates to the technical field of numerical control machining monitoring, in particular to a tooth deviation high-precision monitoring system in a tooth cutting machining process, which comprises an online measurement module, a dynamic compensation module, a deviation calculation module and a result output module which are in signal connection with a numerical control system of a tooth cutting machine tool, the online measurement module, the dynamic compensation module, the deviation calculation module and the result output module are integrated on the processing element; the processing element is used for obtaining workpiece design parameters and constructing a theoretical workpiece model, the online measurement module is used for collecting tooth surface point cloud data in real time in the machining process, the dynamic compensation module is used for correcting vibration errors and temperature errors of the point cloud data, and the deviation calculation module is used for quantifying tooth surface deviation values. And the result output module is used for generating an early warning signal and a dynamic correction instruction and executing system self-calibration. The device and a numerical control system form a closed loop of machining, monitoring, correction and remachining, and finally high-precision real-time monitoring and dynamic correction of tooth deviation are achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of numerical control machining monitoring, in particular to a high-precision monitoring system for tooth deviation in a shaving process. BACKGROUND

[0002] Shaving is a process for finishing gear tooth surfaces, which improves the precision and surface quality of gears by the meshing movement of a shaving cutter and a gear to perform micro-cutting on the tooth surface. In the shaving process, factors such as machine tool vibration, temperature change, tool wear, and machining parameter fluctuation can easily cause tooth deviation in the gear, such as pitch deviation, profile deviation, and helix deviation. These tooth deviations will directly affect the meshing precision, transmission stability, and service life of the formed gear, and in severe cases, can cause the entire transmission system to fail. Therefore, it is crucial to monitor the tooth deviation in the shaving process with high precision.

[0003] In the prior art, contact measurement techniques such as three-coordinate measuring machines are commonly used. Such measurement techniques require offline measurement of workpieces, which not only affects the continuity of machining and reduces production efficiency, but also may affect the measurement accuracy due to probe wear and environmental factors, and cannot monitor deviation changes in real time during the machining process. Non-contact measurement techniques such as line structured light are commonly used. Although such techniques can obtain global tooth surface data online, they lack sufficient light strip clarity under the interference of cooling liquid, have measurement blind spots, have limited point cloud collection accuracy for critical areas such as gear roots, and lack dynamic environmental error compensation mechanisms, making it difficult to meet the real-time monitoring needs of high-precision shaving processes.

[0004] To solve the problems of insufficient precision and poor real-time performance in monitoring tooth deviation in the shaving process in the prior art, a tooth deviation monitoring system for the shaving process is proposed, which integrates online measurement, dynamic compensation, high-precision deviation calculation, and intelligent correction. SUMMARY

[0005] To solve the above problems, the present application provides a high-precision monitoring system for tooth deviation in the shaving process, which improves the precision and real-time performance of tooth deviation monitoring.

[0006] To achieve the above purpose, the technical solution of the present application is as follows: a high-precision monitoring system for tooth deviation in the shaving process, comprising an online measurement module, a dynamic compensation module, a deviation calculation module, and a result output module connected to the numerical control system signal of the shaving machine tool; the online measurement module, the dynamic compensation module, the deviation calculation module, and the result output module are integrated into a processing element. The processing element is used to acquire workpiece design parameters and construct a theoretical workpiece model, the online measurement module is used to collect tooth surface point cloud data in real time during the machining process, the dynamic compensation module is used to correct vibration errors and temperature errors of the point cloud data, the deviation calculation module is used to quantify tooth surface deviation values, and the result output module is used to generate early warning signals, dynamic correction instructions and execute system self-calibration.

[0007] Further, the online measurement module comprises a composite light source unit and an image acquisition unit, and the composite light source unit and the image acquisition unit are linked through synchronous control logic; the composite light source unit projects a cross light plane on the tooth surface by using a blue-green waveband composite line structured light, and penetrates the cooling liquid mist barrier through a double-wavelength intelligent switching algorithm; and the image acquisition unit is used to synchronously acquire light strip images and process and generate standardized PCD format point cloud data.

[0008] Further, the composite light source unit comprises a double-light-path projection assembly and a synchronous control subunit; the double-light-path projection assembly is composed of two groups of line lasers, the line lasers are installed on an adjustable cantilever support, are equipped with a stepper motor driving assembly with a harmonic reducer, have an angle adjustment precision of ±0.01°, the laser optical axis and the axis line of the machine tool spindle have an included angle of 30°-45° in XY plane projection, and the tooth surface overlapping effective measurement area is ≥60%; the synchronous control subunit receives a spindle encoder signal, and the synchronous control subunit is used to calculate the exposure delay compensation value through the formula:

[0009] wherein, is a line laser triggering moment, is a spindle encoder signal moment, is an exposure delay compensation value. Synchronous exposure of the laser and the image acquisition unit is realized.

[0010] Further, the image acquisition unit comprises a CMOS camera, a polarized light filtering assembly and an adaptive exposure unit; the polarized light filtering assembly suppresses tooth surface reflection through a motor-driven rotatable polarized plate, and the adaptive exposure unit dynamically adjusts the camera gain and exposure time based on the formula:

[0011] wherein, G is a CMOS camera gain, is a CMOS camera initial gain, k is an adaptive coefficient, is a light strip image gray histogram statistical value. The image acquisition unit processes images through multi-frame adaptive median filtering and gray barycenter method sub-pixel extraction, and generates point cloud data of ≥40,000 points of a single tooth in combination with a triangulation principle.

[0012] Further, the dynamic compensation module comprises a vibration compensation unit and a temperature drift unit, and the vibration compensation unit and the temperature drift unit are connected with an environment sensor; the environment sensor comprises a three-axis accelerometer array installed on a main shaft of a machine tool and temperature sensors installed on a front end of the main shaft, a workpiece clamping seat and a cutting area; the dynamic compensation module receives point cloud data of the online measurement module, and outputs the point cloud data to the deviation calculation module after vibration and temperature error correction.

[0013] Further, the vibration compensation unit comprises a three-axis MEMS accelerometer array and a phase synchronization subunit; the three-axis MEMS accelerometer array has a sampling frequency of 100 Hz, and vibration data are processed through Kalman filtering, based on the formula:

[0014] wherein, represents a point cloud displacement vector caused by vibration in the gear machining process, is a time-domain vibration acceleration vector; the displacement vector is calculated to correct the point cloud through rigid transformation; the phase synchronization subunit realizes time-domain alignment of vibration data and a main shaft rotation angle through a phase-locked loop technology.

[0015] Further, the temperature drift unit comprises a high-precision temperature sensor and a finite element thermal analysis auxiliary model; the temperature sensor has a measurement accuracy of ±0.1 ℃ and a sampling frequency of 50 Hz, and is based on the formula:

[0016] wherein, is a length change of the workpiece caused by temperature, represents an original length of a feature of the workpiece, is a material linear expansion coefficient, is a temperature change of a key area; the thermal expansion amount is calculated, the thermal expansion amount is converted into a normal deformation deviation of a gear surface through the auxiliary model, and the point cloud after vibration compensation is corrected again.

[0017] Further, the deviation calculation module comprises a point cloud registration unit and a deviation mapping unit; the point cloud registration unit aligns the point cloud with a theoretical workpiece model through a two-step method of coarse registration and fine registration; the coarse registration is based on a random sample consensus algorithm to fit an end surface plane and determine a workpiece axis through cylindrical fitting; the fine registration adopts an improved ICP algorithm by introducing a gear surface curvature weight, and a registration error is ≤0.5 μm.

[0018] Further, the deviation mapping unit adopts NURBS surface reconstruction technology to construct an actual gear surface, through the formula:

[0019] wherein, is an actual point coordinate, is the theoretical point coordinate, and n is a theoretical tooth surface normal vector; The normal deviation of each point on the tooth surface is calculated, and the tooth spacing deviation, tooth profile deviation and tooth direction deviation are automatically classified and counted to generate a deviation heat map and a standardized deviation data file.

[0020] Further, the result output module includes an edge contact early warning unit, a dynamic correction unit and a reference calibration component; the edge contact early warning unit triggers early warning based on a threshold and generates a local modification strategy, the dynamic correction unit converts the modification strategy into a G code correction instruction, and the reference calibration component adopts an involute template with a precision of ≤1 μm, and generates a formula:

[0021] wherein, is a system parameter to be calibrated (including a CMOS camera internal parameter and a structured light plane equation), is a measured point coordinate of the calibration template, is a theoretical point coordinate of the calibration template; Periodically perform system self-calibration.

[0022] The principle of the above scheme is as follows: Taking online acquisition-dynamic correction-deviation quantification-closed loop correction as the core, high-precision tooth deviation monitoring is realized through the cooperation of various modules. First, the processing element constructs a theoretical model according to the design parameters of the workpiece; the online measurement module uses a blue-green composite line structured light to project a cross light plane, which is resistant to cooling liquid interference, and synchronously acquires light strip images, which are processed by noise reduction and sub-pixel extraction to generate point clouds; the dynamic compensation module uses an accelerometer and a temperature sensor to correct vibration displacement and thermal deformation errors, respectively; the deviation calculation module quantifies tooth surface deviation by coarse-fine two-step registration of point clouds and theoretical models; the result output module generates early warning and correction instructions in real time, and periodically uses a high-precision template for self-calibration to form a closed loop with the numerical control system, efficiently completing tooth deviation monitoring and adjustment during tooth cutting processing.

[0023] Compared with the prior art, the above scheme has the following beneficial effects: 1. In the present scheme, the online measurement module synchronously acquires tooth surface data throughout the machining process without interrupting the machining or removing the workpiece, which not only ensures the continuity of machining but also avoids repeated clamping errors, thereby improving production efficiency. Through a dual-wavelength intelligent switching algorithm and dynamic adjustment of laser power, the laser power effectively penetrates the cooling liquid mist barrier; the cross light plane design and multi-camera cooperative acquisition ensure coverage of all areas of the tooth tip and tooth root, eliminating measurement blind spots; combined with sub-pixel level light strip extraction and dynamic compensation, the point cloud data precision is improved and the tooth deviation measurement error is reduced.

[0024] 2、The scheme, through the vibration compensation unit and the temperature drift unit constructs the coupling error correction model, real-time correction vibration displacement and thermal deformation deviation, effectively offset the interference of environmental factors on the measurement, makes the deviation calculation based on the real tooth surface data, further improves the reliability of monitoring results. Through the result output module real-time generates early warning signal and dynamic correction instruction, from the delay of deviation data acquisition to the execution adjustment of numerical control system is extremely low, can timely correct the processing parameters; at the same time, based on the LSTM algorithm, the deviation trend is predicted, and the deviation overrun risk is avoided in advance, and the unqualified product rate is reduced.

[0025] 3、The scheme, through the reference calibration assembly, periodically automatically executes self-calibration, optimizes system parameters by using high-precision involute sample plate, ensures long-term stability of measurement accuracy, reduces frequent manual intervention, reduces operation and maintenance cost, and ensures consistency of measurement results of different batches of workpieces. BRIEF DESCRIPTION OF DRAWINGS

[0026] Figure 1 The figure is a schematic diagram of the system framework of the embodiment of the present application. Figure 2 The figure is a schematic diagram of the system processing flow of the embodiment of the present application. Figure 3 The figure is a schematic diagram of the system module framework of the embodiment of the present application. DETAILED DESCRIPTION

[0027] The technical solutions of the present application will be described in detail below with reference to the drawings. Obviously, the described embodiments are part of the embodiments of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor belong to the scope of protection of the present application.

[0028] Further described in detail through specific embodiments: In the traditional tooth processing process, there are many deficiencies in the monitoring of tooth deviation. The common contact type measurement method, such as using three coordinate measuring machine and other equipment, can achieve a certain accuracy, but the operation process is complicated, the workpiece needs to be taken off from the machine tool, measured in a special measuring environment, and then clamped for subsequent tooth processing after the measurement is completed; this not only affects the continuity of tooth processing, reduces the production efficiency; and repeated clamping of workpiece may cause tooth profile error of tooth processing; secondly, the frequent contact between the measuring head and the tooth surface may cause the wear of the measuring head, and also affect the measurement accuracy, and the measuring head may cause slight wear to the tooth surface. Thirdly, such measurement method has strict requirements on the environment, and small changes in temperature, humidity and vibration and other environmental factors may cause deviation of the measurement result.

[0029] The visual measurement and laser scanning technology in the existing non-contact measurement can obtain the global data of the tooth surface online, but the precision still cannot meet the needs of high-precision gear machining. For example, the detection sensitivity of micro tooth deviation is insufficient, especially when processing complex tooth profile, the limitation of the measurement algorithm makes it difficult to accurately distinguish and quantify the subtle tooth deviation, and it is difficult to provide accurate basis for timely adjusting the machining parameters. Moreover, the existing non-contact measurement technology often has poor real-time performance, and cannot output the tooth deviation monitoring results in real time during the machining process, which makes it difficult for the operator to obtain the abnormal conditions in the gear machining process in time, resulting in the production of unqualified products and increasing the production cost.

[0030] For the existing gear machining machine tool on the automatic production line, the tooth deviation high-precision monitoring system of the present embodiment is combined to monitor the tooth deviation during the gear machining process. The tooth deviation high-precision monitoring system (hereinafter referred to as monitoring system) during the gear machining process is shown in the monitoring system framework as shown in Figure 1 The monitoring system framework includes an online measurement module, a dynamic compensation module, a deviation calculation module and a result output module connected with the numerical control system signal of the gear machining machine tool. The online measurement module, the dynamic compensation module, the deviation calculation module and the result output module are integrated in a processing element. The processing element of the present embodiment is an industrial PC, which is integrated in the machine tool workbench and integrated with Windows system or Linux system.

[0031] Before the workpiece gear machining starts, that is, in the machining preparation (workpiece clamping and machining parameter setting or acquisition) stage, the workpiece blank is installed in the clamped gear machining machine tool, and the industrial PC obtains the related design parameters of the workpiece, including the module, the number of teeth, the tooth profile angle, etc. In the present embodiment, the industrial PC directly obtains the related design parameters of the workpiece from the numerical control system. In some embodiments, the industrial PC inputs the related design parameters of the workpiece, and each module in the industrial PC obtains the related design parameters of the workpiece. The industrial PC constructs a theoretical workpiece model according to the related design parameters of the workpiece. In some embodiments, the industrial PC can also be a microprocessor, a general-purpose processor or other processing elements.

[0032] The modules are described in detail as follows: The online measurement module is the data acquisition front end of the gear machining tooth deviation monitoring system, connects the numerical control system with the subsequent dynamic compensation module, and obtains the tooth surface three-dimensional data in real time during the machining process through the non-contact structured light measurement technology. Its core functions are anti-interference light projection-synchronous image acquisition-high precision light strip processing-tooth surface point cloud generation, which are as follows: The online measurement module is composed of a composite light source unit and an image acquisition unit, both of which are linked through synchronous control logic to complete the whole process from light signal projection to point cloud output. The composite light source unit is used to project high-penetration cross light planes to the tooth surface, breaking through the interference of the cooling liquid mist barrier and ensuring that the light strip is completely covered on the tooth surface (including the tooth top and tooth root). The image acquisition unit is used to synchronously acquire the light strip image modulated by the tooth profile, and through noise reduction and sub-pixel level light strip extraction, the two-dimensional image information is converted into three-dimensional point cloud data, providing original data support for subsequent dynamic compensation.

[0033] Specifically, the composite light source unit is equipped with a double light path projection assembly, and the composite light source unit is used to project cross light planes to the tooth surface by the double light path projection assembly (composed of two groups of linear lasers) in a blue-green waveband composite linear structured light. Among them, the linear laser is installed on the machine tool cantilever support, which is fixed by a Z-axis guide rail slider and can be adjusted up and down. Each group of lasers is equipped with a stepper motor drive assembly with a harmonic reducer, with an angle adjustment accuracy of ±0.01°, ensuring that the two laser beams form an effective measurement area of ≥60% in the tooth surface overlapping area. The projection angle of the laser optical axis and the machine tool spindle axis in the XY plane is set to 30°~45°, covering the tooth top (workpiece protruding area) and tooth root (workpiece recessed area), avoiding measurement blind area; the output end integrates a lens group to optimize the uniformity of the light strip. In view of the problem that the light strip is blurred due to the cooling liquid mist barrier during processing, the output power and phase of the double-wavelength laser are controlled through fiber coupling, and an intelligent wavelength switching algorithm is adopted: Preferably, 550~580nm waveband laser is selected, which has higher liquid mist penetration ability; combined with the laser intensity attenuation model:

[0034] wherein I represents the light intensity after the laser penetrates the cooling liquid, represents the initial light intensity of the laser, represents the absorption coefficient of the cooling liquid, and d represents the laser penetration distance.

[0035] The laser power is dynamically adjusted to ensure that the light strip is still clear and distinguishable in the liquid mist environment.

[0036] The composite light source unit is also equipped with a synchronous control subunit, and the composite light source unit is used to receive the encoder signal of the gear cutting machine tool spindle through the synchronous control subunit, and the synchronous exposure of the linear laser and the image acquisition unit is realized through the programmable logic controller (PLC), avoiding image misplacement caused by spindle rotation: the synchronous triggering time calculation formula is:

[0037] wherein, is the linear laser triggering time, is the spindle encoder signal time, The exposure delay compensation value is dynamically adjusted according to the main shaft speed and is adapted to different machining conditions.

[0038] Specifically, the image acquisition unit comprises a CMOS camera and a polarized light filtering assembly, wherein the polarized light filtering assembly is composed of a rotatable polarizer and a driving motor; the polarizer is automatically rotated and adjusted by the driving motor, and the optimal polarization angle is matched in real time by combining image gray scale statistical analysis to suppress the metal reflection light on the tooth surface and avoid light bar breakage caused by reflection; the CMOS camera acquisition rate is set to 100 fps to ensure synchronization with the main shaft rotation and the laser trigger, and each frame of image can cover the complete tooth surface of a single tooth. The image acquisition unit is also equipped with an adaptive exposure unit, which is used to dynamically adjust the CMOS camera gain parameter according to the tooth surface reflection intensity to avoid overexposure or underexposure of the light bar, and the gain calculation formula is:

[0039] wherein G is the CMOS camera gain, is the initial gain of the CMOS camera, k is the adaptive coefficient, is the light bar image gray scale histogram statistical value; by monitoring the gray scale distribution in real time, the exposure time (range 10~100 μs) and the gain are adjusted synchronously to ensure clear light bar edges.

[0040] The image acquisition unit is used to perform two-step processing on the collected light bar image to improve the light bar center positioning accuracy: (1) Multi-frame adaptive median filtering, window size 5x5, to remove coolant reflection noise, filter out isolated noise points and retain light bar continuous contour; (2) Sub-pixel level light bar center extraction, based on gray centroid method to calculate light bar center coordinates, formula:

[0041] wherein, represents the x coordinate of the light bar center, represents the gray scale value at x; combined with the deep learning sub-pixel positioning algorithm, the light bar center positioning accuracy is improved to 0.1 pixel level. Wherein x is the pixel coordinate of the light bar along the horizontal direction, used to identify the position of a certain point on the light bar in the horizontal dimension, x traverses all horizontal pixel coordinates in the light bar area, combined with the gray scale value at the corresponding position, the horizontal coordinate of the light bar center is finally calculated as to realize sub-pixel level light bar center positioning.

[0042] After the image acquisition unit performs the above two-step processing on the collected light bar image, combined with the CMOS camera system calibration parameters, the tooth surface three-dimensional point cloud is generated through the principle of triangulation, and the specific steps are as follows: First, the intrinsic parameters (focal length, distortion coefficient) of the CMOS camera and the equation of the structured light plane are obtained using a checkerboard calibration board, serving as the benchmark for point cloud coordinate calculation. Then, based on the light stripe phase information and calibration parameters, the three-dimensional coordinates of each point on the tooth surface are calculated using a triangulation algorithm, with the following formula:

[0043] In the formula, In the image of the tooth surface of the workpiece Phase value at coordinates, The intrinsic parameters of the CMOS camera are calibrated. The generated point cloud data has approximately 40,000 points per tooth, and the density meets the requirements for detecting minor deviations on the tooth surface. In some scenarios, multiple CMOS cameras can be used for collaborative acquisition (field of view overlap ≥60%) to further cover the tooth tip and root edge areas and completely eliminate measurement blind spots.

[0044] The online measurement module ultimately outputs standardized PCD format tooth surface point cloud data, which is transmitted in real time to the dynamic compensation module via industrial Ethernet. This provides high-precision point cloud data for subsequent vibration-temperature coupling error correction and simultaneously feeds back the acquisition status to the CNC system, such as "acquisition normal" and "blurred light stripe alarm," ensuring that machining and measurement are synchronized in a closed loop.

[0045] The dynamic compensation module serves as the central hub for point cloud error correction. Its core function is to eliminate the interference of vibration and temperature in the machining environment on the original point cloud; it corrects the error-contaminated point cloud data into high-precision actual tooth surface point cloud data, providing a true data foundation for subsequent deviation calculations. Specifically: The dynamic compensation module consists of a vibration compensation unit and a temperature drift unit. The vibration compensation unit corrects point cloud displacement deviations caused by machine tool spindle and table vibrations by calculating displacement using acceleration data, thus achieving rigid transformation correction. The temperature drift unit corrects workpiece thermal deformation caused by machining heat (cutting heat, ambient temperature changes) by using temperature data to correct tooth surface normal deviations. Vibration and temperature data are acquired through environmental sensors, including a triaxial accelerometer array mounted on the machine tool spindle and a temperature sensor mounted on the workpiece clamping / cutting zone. The dynamic compensation module synchronously receives PCD format point cloud data output from the online measurement module.

[0046] Specifically, the vibration compensation unit includes a triaxial MEMS accelerometer array and a phase synchronization subunit. The triaxial MEMS accelerometer array has an accuracy of ±0.01g and a sampling frequency of 100Hz. It is fixed to the end face of the machine tool spindle tail via a fixture to capture key spindle vibrations, and data is transmitted via a low-noise coaxial cable. The phase synchronization subunit receives the machine tool spindle rotation angle signal and uses phase-locked loop technology to align the vibration data with the spindle rotation angle in the time domain, avoiding correction deviations caused by phase misalignment. The vibration error correction process is as follows: Firstly, the original vibration acceleration data is processed by Kalman filter algorithm to remove high-frequency interference (such as cutting impact noise) and obtain pure time-domain vibration acceleration vector ; then the acceleration is converted into point cloud displacement vector by twice integration, and the formula is:

[0047] , wherein, represents the point cloud displacement vector caused by vibration during the gear cutting process; then the displacement vector is applied to the original point cloud data, and the three-dimensional coordinates of each point are corrected by matrix transformation to eliminate the point cloud offset caused by vibration, such as the point position deviation of the tooth surface caused by the radial runout of the main shaft.

[0048] Specifically, the temperature drift unit includes a high-precision temperature sensor and an auxiliary model; the measurement accuracy of the high-precision temperature sensor is ±0.1℃, and the sampling frequency is 50Hz; in the embodiment, the number of high-precision temperature sensors is 3, which are respectively installed at the front end of the main shaft, the workpiece clamping seat and the cutting area to collect the temperature changes of the key areas in real time ; the auxiliary model is based on the finite element thermal analysis model of the workpiece material, and the preset material linear expansion coefficient , such as the linear expansion coefficient of 45# steel . The thermal deformation error correction process is as follows: Firstly, the thermal expansion amount is calculated, the characteristic length change of the workpiece is calculated according to the thermal expansion model, and the formula is:

[0049] , wherein, is the length change of the workpiece caused by temperature, represents the original length of the workpiece characteristic. Then, the is converted into the normal deformation deviation of each point on the tooth surface, and the point cloud after vibration compensation is modified again; then the thermal correction weight is dynamically adjusted according to the machining parameters (such as spindle speed and cutting depth).

[0050] The dynamic compensation module finally outputs the standardized PCD point cloud data after vibration error correction and thermal deformation error correction, and transmits it to the deviation calculation module in real time through industrial Ethernet, and at the same time, the error correction state is fed back to the numerical control system, such as "vibration correction completed" and "temperature threshold alarm", to ensure that the deviation calculation is based on the real tooth surface data without environmental interference.

[0051] The deviation calculation module is the data processing core of the monitoring system, and the core function is to align the corrected point cloud data with the theoretical workpiece model, and through surface reconstruction and normal comparison, the deviation values of each position on the tooth surface are quantified, such as tooth spacing deviation, tooth profile deviation and tooth direction deviation, to provide deviation data that can be directly used for adjustment for the result output module.

[0052] The deviation calculation module is composed of a point cloud registration unit and a deviation mapping unit; the point cloud registration unit is used to ensure the alignment accuracy through a two-step method of coarse registration and fine registration, and solve the problem of spatial alignment of the corrected point cloud data and the theoretical model; the deviation mapping unit is used to calculate the normal deviation of each point on the tooth surface based on the aligned point cloud data and the theoretical model, and generate a deviation heat map and a deviation parameter table through surface reconstruction; wherein the corrected point cloud data is derived from the state compensation module output, and the theoretical model is derived from the pre-stored industrial PC (based on workpiece design parameters such as module and tooth number).

[0053] Specifically, the point cloud registration unit is used to perform coarse registration based on the random sample consensus algorithm and principal component analysis, with the workpiece end face and axis as the feature reference. First, the end face point set is extracted from the corrected point cloud data, and the end face plane is aligned with the theoretical end face through the random sample consensus algorithm. The fitting end face plane equation is as follows:

[0054] Wherein a, b, c, d are plane equation coefficients, and x, y, z are end face point cloud coordinates. Then the dedendum circle / tooth tip circle point set is extracted from the point cloud, and the actual axis of the workpiece is determined through the cylindrical fitting algorithm, and is aligned with the theoretical axis. The initial deviation of the point cloud and the theoretical model is reduced to within 10μm, laying a foundation for fine registration. The point cloud registration unit is used to perform fine registration based on the improved ICP algorithm. First, if the point cloud density in the dedendum area is lower than the threshold, the radial basis function interpolation is used to encrypt, to ensure the registration accuracy of the key area; the corresponding point weight is calculated based on the tooth surface curvature, and the formula is as follows:

[0055] Wherein, is the weight adjustment parameter, is the reference curvature value of the tooth surface, is the actual point curvature. The weight of the area with large curvature (such as the dedendum transition area) is higher, and the alignment is prioritized; then the weighted distance is minimized as the target, and the objective function is as follows:

[0056] Wherein, is the weight coefficient based on the tooth surface curvature, represents the measured and corrected point cloud coordinate vector, is the corresponding point coordinate vector of the theoretical workpiece model. Then the optimal rotation matrix and translation vector are calculated through iteration, so that the final registration error is ≤0.5μm; the iteration calculation formula is as follows:

[0057] Wherein, R and t represent the optimal rotation matrix and translation vector of the tooth surface respectively, R is the rotation matrix, and t is the translation vector.

[0058] Specifically, the deviation mapping unit is used to calculate the deviation value data of each position of the tooth surface by adopting the NURBS surface reconstruction. First, based on the aligned point cloud data, the actual tooth surface curve is constructed by the NURBS surface formula:

[0059] wherein u and v are both surface parameters, are both spline basis functions, is a weight factor, is a control vertex coordinate. The pre-stored theoretical tooth surface NURBS curve (constructed based on the design parameters) is called to ensure that the parameterization reference of the two is consistent. Then for each point on the actual tooth surface curve, the distance between the actual point and the theoretical point is calculated along the normal direction of the theoretical tooth surface, and the formula is:

[0060] wherein is the actual point coordinate, is the theoretical point coordinate, and n is the theoretical tooth surface normal vector. Then based on the calculation result, the tooth spacing deviation (the difference value of the adjacent tooth surface deviation), the tooth profile deviation (the maximum value of the deviation in the tooth profile line direction), and the tooth direction deviation (the deviation change in the tooth width direction) are automatically classified and counted to generate a single tooth deviation parameter table.

[0061] The deviation calculation module finally outputs a deviation heat map and standardized deviation data; wherein the deviation heat map directly shows the deviation distribution of each region of the tooth surface; and the standardized deviation data contains the normal deviation value of each point and the classified deviation parameters. The output deviation heat map and standardized deviation data are transmitted to the result output module through the industrial Ethernet, and at the same time, the registration state is fed back to the dynamic compensation module, such as “registration success” and “point cloud density insufficient alarm”.

[0062] The result output module is the closed-loop control terminal of the monitoring system, and its core function is to generate an early warning signal and a dynamic correction instruction based on the deviation calculation result, to realize system self-calibration, to convert the deviation data into machine tool executable adjustment parameters, and to finally realize the processing closed loop of measurement-calculation-adjustment.

[0063] The result output module is composed of an edge contact early warning unit, a dynamic correction unit, and a reference calibration component. The edge contact early warning unit is used to monitor the over-limit points in the deviation data in real time, to trigger an alarm and to generate a local modification strategy; the dynamic correction unit is used to convert the modification strategy into machine tool executable gear cutting tool feed correction parameters and to output to the numerical control system; and the reference calibration component is used to periodically perform system self-calibration to ensure long-term measurement accuracy. The deviation data is derived from the deviation calculation module, and the machine tool operation parameters are derived from the numerical control system.

[0064] Specifically, the edge contact early warning unit is configured to preset a deviation threshold based on a workpiece tolerance requirement For each point in the deviation data, threshold comparison is performed, and the formula is:

[0065] Wherein, is a warning flag, when , it indicates that the warning is triggered, and the out-of-limit point position is marked on the industrial PC interface. The edge contact early warning unit is also configured to generate a local modification strategy based on a threshold and a region growing out-of-limit area identification algorithm and an expert system. First, adjacent out-of-limit points are divided into a single modification area through a region growing algorithm, and then the modification amount is calculated according to the maximum deviation value of the area, and the formula is:

[0066] Wherein, is a correction coefficient, is the maximum deviation value in the area; and then a local modification strategy of the modification area coordinates and the modification amount is generated.

[0067] Specifically, the dynamic correction unit is configured to convert the radial modification amount into a radial feed amount correction value of the gear cutting tool, adjust the smoothing coefficient of the correction parameter according to the spindle speed of the machine tool and the cutting force (to avoid vibration caused by sudden feed), convert the correction parameter into G code instructions recognizable by the numerical control system, and compare the corrected feed amount with the safety range of the machine tool. If it exceeds the range, it will be suspended and an alarm will be given. Wherein, the G code instructions are transmitted to the numerical control system through industrial Ethernet; the instruction execution state of the numerical control system is received, and if no feedback is received within 100 ms, the instruction is retransmitted to ensure that the adjustment takes effect. The dynamic correction unit is also configured to use an LSTM algorithm to predict the deviation trend of the next tooth based on historical deviation data, and output a pre-correction instruction in advance.

[0068] Specifically, the reference calibration assembly includes a high-precision involute template and a special fixture, which is installed on the machine tool workbench. In this embodiment, the system self-calibration period is once every 24 hours, and in some embodiments, it can also be triggered when the system issues a precision decline alarm. The self-calibration process is as follows: First, the fixture automatically positions the involute template to the measurement reference position, and the industrial PC recognizes the template profile; then the template is completely measured through the online measurement module and the dynamic compensation module to generate actual point cloud data of the template; then the actual point cloud data of the template is compared with the theoretical model of the template, and the system parameters are optimized through the least squares method, and the formula is:

[0069] Wherein, The system parameters to be calibrated (in this embodiment, the CMOS camera intrinsic parameters and the structured light plane equation), The measured point coordinates of the calibration template, The theoretical point coordinates of the calibration template. By measuring and analyzing the template, the system parameters are calibrated, and the template is re-measured to verify the accuracy of the monitoring system.

[0070] The result output module finally outputs the early warning signal, dynamic correction instruction (G code instruction), and calibration report. The early warning signal is used to remind the operator to handle the overrun problem; the dynamic correction instruction is used to drive the numerical control system to adjust the gear cutter feed parameters; and the calibration report is used to record the self-calibration result.

[0071] During the entire machining process, the monitoring system also obtains the running parameters of the gear cutting machine from the numerical control system in real time, including the spindle speed, feed speed, cutting force, and other running parameters. By analyzing these running parameters and combining the tooth deviation data, the system can further determine the cause of the tooth deviation. For example, if the cutting force suddenly increases and the tooth profile deviation also appears abnormal, it may be that the tool is severely worn or interference occurs during cutting. The system will promptly issue an alarm prompt so that the operator can promptly check and adjust the tool.

[0072] When the workpiece machining is completed, the formed workpiece remains in a stationary state, and the monitoring system again measures the entire workpiece comprehensively and generates a complete tooth deviation report. The tooth deviation report records the measurement results of the tooth spacing deviation, tooth profile deviation, and tooth direction deviation of each tooth surface in detail, and compares and analyzes them with the design values in the theoretical workpiece model. The operator can evaluate whether the machining quality of the workpiece meets the requirements according to the data in the report. If there are individual tooth deviations still exceeding the tolerance range, the operator can perform targeted correction machining on the workpiece or adjust the machining process parameters of the subsequent batch of workpieces to improve the machining quality.

[0073] Obviously, the above embodiments are merely examples for clear illustration, and are not limitations on the embodiments. Based on the above description, other different forms of changes or variations can be made by those of ordinary skill in the art. Here, it is not necessary or possible to exhaust all embodiments. The obvious changes or variations derived therefrom are still within the protection scope of the present application.

Claims

1. A high-precision monitoring system for tooth deviation during tooth cutting, characterized in that, It includes an online measurement module, a dynamic compensation module, a deviation calculation module, and a result output module that are connected to the CNC system of the gear cutting machine tool. The online measurement module, dynamic compensation module, deviation calculation module, and result output module are integrated into the processing element. The processing element is used to acquire workpiece design parameters and construct a theoretical workpiece model. The online measurement module is used to collect tooth surface point cloud data in real time during the processing. The dynamic compensation module is used to correct the vibration error and temperature error of the point cloud data. The deviation calculation module is used to quantify the tooth surface deviation value. The result output module is used to generate early warning signals, dynamic correction instructions and execute system self-calibration. The online measurement module includes a composite light source unit and an image acquisition unit, which are linked by synchronous control logic. The composite light source unit uses blue-green band composite line structured light to project a cross light plane onto the tooth surface and penetrates the coolant fog barrier through a dual-wavelength intelligent switching algorithm. The image acquisition unit is used to synchronously acquire light stripe images and process them to generate standardized PCD format point cloud data. The dynamic compensation module includes a vibration compensation unit and a temperature drift unit, both of which are connected to environmental sensors. The environmental sensors include a triaxial accelerometer array mounted on the machine tool spindle and temperature sensors mounted on the front end of the spindle, the workpiece clamping seat, and the cutting zone. The dynamic compensation module receives point cloud data from the online measurement module, corrects for vibration and temperature errors, and outputs it to the deviation calculation module. The deviation calculation module includes a point cloud registration unit and a deviation mapping unit. The point cloud registration unit aligns the point cloud with the theoretical workpiece model through a two-step method of coarse registration and fine registration. The coarse registration is based on fitting the end face plane with a random sampling consensus algorithm and determining the workpiece axis through cylindrical fitting. The fine registration adopts an improved ICP algorithm that introduces tooth surface curvature weights, and the registration error is ≤0.5μm. The result output module includes an edge contact early warning unit, a dynamic correction unit, and a reference calibration component. The edge contact early warning unit triggers an early warning based on threshold comparison and generates a local shaping strategy. The dynamic correction unit converts the shaping strategy into G-code correction instructions. The reference calibration component uses an involute template with an accuracy ≤1μm, and uses the formula: ； in, The system parameters to be calibrated include CMOS camera intrinsic parameters and structured light plane equations. To calibrate the coordinates of the measured points on the template, To calibrate the coordinates of the theoretical points on the template; Perform system self-calibration regularly.

2. The high-precision tooth deviation monitoring system during tooth cutting according to claim 1, characterized in that, The composite light source unit includes a dual-path projection assembly and a synchronous control subunit. The dual-path projection assembly consists of two sets of line lasers, each mounted on an adjustable cantilever bracket and equipped with a stepper motor drive assembly with a harmonic reducer. The angle adjustment accuracy is ±0.01°, and the angle between the laser optical axis and the machine tool spindle axis projected onto the XY plane is 30°~45°. The effective measurement area of ​​tooth surface overlap is ≥60%. The synchronous control subunit receives signals from the spindle encoder and uses the formula: ； in, The trigger time of the line laser. When the main spindle encoder signal is received, This is the exposure delay compensation value; To achieve synchronous exposure of the laser and the image acquisition unit.

3. The high-precision monitoring system for tooth deviation during tooth cutting according to claim 1, characterized in that, The image acquisition unit includes a CMOS camera, a polarization filter assembly, and an adaptive exposure unit; the polarization filter assembly suppresses tooth surface reflection by using a motor-driven rotatable polarizer; the adaptive exposure unit is based on the formula: ； Where G represents the CMOS camera gain. Here, k represents the initial gain of the CMOS camera, and k is the adaptive coefficient. These are the statistical values ​​of the grayscale histogram of the light stripe image; The camera gain and exposure time are dynamically adjusted; the image acquisition unit processes the image through multi-frame adaptive median filtering and gray-scale centroid subpixel extraction, and generates point cloud data with ≥40,000 points per tooth by combining the principle of triangulation.

4. The high-precision tooth deviation monitoring system during tooth cutting according to claim 1, characterized in that, The vibration compensation unit includes a triaxial MEMS accelerometer array and a phase synchronization subunit; the triaxial MEMS accelerometer array has a sampling frequency of 100Hz, and the vibration data is processed by Kalman filtering based on the formula: ； in, This represents the point cloud displacement vector caused by vibration during the tooth-grinding process. This is the time-domain vibration acceleration vector; The displacement vector is calculated, and the point cloud is rigidly transformed and corrected; the phase synchronization subunit realizes the time domain alignment of vibration data with the spindle rotation angle through phase-locked loop technology.

5. The high-precision monitoring system for tooth deviation during tooth cutting according to claim 1, characterized in that, The temperature drift unit includes a high-precision temperature sensor and a finite element thermal analysis auxiliary model; the temperature sensor has a measurement accuracy of ±0.1℃ and a sampling frequency of 50Hz, based on the formula: ； in, The change in workpiece length caused by temperature. Indicates the original length of the workpiece feature. This is the coefficient of linear expansion of the material. Temperature changes in key areas; The thermal expansion is calculated, and the thermal expansion is converted into the normal deformation deviation of the tooth surface using an auxiliary model. The point cloud after vibration compensation is then corrected.

6. The high-precision monitoring system for tooth deviation during tooth cutting according to claim 1, characterized in that, The deviation mapping unit uses NURBS surface reconstruction technology to construct the actual tooth surface, using the formula: ； in, These are the actual point coordinates. Let n be the theoretical point coordinates, and n be the theoretical tooth surface normal vector. Calculate the normal deviation at each point on the tooth surface, automatically classify and statistically analyze the tooth pitch deviation, tooth profile deviation, and tooth direction deviation, and generate a deviation heatmap and standardized deviation data file.

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