Intelligent dynamic control method and system for V-CUT machining process

Abstract

The invention discloses an intelligent dynamic control method and system for a V-CUT machining process, and the method comprises the steps: arranging a multispectral laser displacement sensor array at a V-CUT cutter shaft, arranging a high-frequency piezoelectric micro-touch probe at a residual thickness measurement station, and generating point cloud data in real time based on a preset sampling frequency; synchronously mapping the point cloud data into a digital twin model corresponding to the V-CUT equipment, and updating the V-CUT groove depth, the PCB residual thickness and the V-CUT knife edge wear degree corresponding to the twin model in real time; predicting a cutter shaft machining drifting trend according to the groove depth, the residual thickness and the cutter edge abrasion state; and when the drift trend predicted value exceeds the process threshold value, a feed-forward compensation instruction is issued to a cutter shaft servo system, and closed-loop correction in the V-CUT machining process is achieved. According to the invention, production and detection integration can be realized, individual manual detection by personnel after shutdown is not needed, and quality improvement and production efficiency maximization can be effectively ensured.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of printed circuit board processing and manufacturing, and particularly relates to a V-CUT processing intelligent dynamic control method and system. BACKGROUND

[0002] With the continuous expansion of the application scenarios of PCB (printed circuit board) technology, the V-CUT processing technology plays an increasingly important role in PCB manufacturing. V-CUT processing cuts V-shaped grooves on the PCB board, so that the board can be smoothly divided into multiple small units. Since the V-CUT process has very high precision requirements, any slight error will directly affect the quality of the final product. Therefore, improving the intelligence and precision of the V-CUT processing process, and ensuring real-time monitoring and dynamic correction of the processing process, have become urgent problems that need to be solved in the PCB industry.

[0003] Currently, the manufacturers of PCB production equipment usually do not set the function of automatically detecting the V-CUT residual thickness and depth, and need to manually measure on another device. For example, in the case of normal first piece, abnormality of batch production equipment cannot be discovered in time, which may cause batch defects or scrap of products. When the production line is performing V-CUT processing control, a single-line laser displacement sensor is arranged at the outlet of the machine, which intermittently detects the groove depth, and the residual thickness needs to be checked by a manual caliper during the processing process. The data is sparse and lagging. In addition, tool dulling is judged by monitoring the change of spindle current and relying on experience curve; however, due to the interference of many factors such as material and temperature, the false positive rate is high, and the drift amount cannot be predicted.

[0004] Therefore, the present application provides a V-CUT processing intelligent dynamic control method and system, which can predict and adjust the offset at the initial stage of production, automatically detect the residual thickness and depth without stopping for first piece or self-made piece, realize the integration of production and detection, and manually detect without stopping for personnel, which can effectively ensure the quality improvement and maximize the production efficiency. SUMMARY

[0005] Therefore, the present application provides a V-CUT processing intelligent dynamic control method and system, which can predict and adjust the offset at the initial stage of production, automatically detect the residual thickness and depth without stopping for first piece or self-made piece, realize the integration of production and detection, and manually detect without stopping for personnel, which can effectively ensure the quality improvement and maximize the production efficiency.

[0006] To achieve the above technical purposes, the present application adopts the following technical solutions: On the one hand, the present application provides a V-CUT processing intelligent dynamic control method, comprising: A multi-spectral laser displacement sensor array is arranged on the V-CUT tool shaft, and a high-frequency piezoelectric micro-touch probe is arranged at the residual thickness measurement station, and point cloud data is generated in real time based on a preset sampling frequency; The point cloud data is synchronously mapped into the digital twin model corresponding to the V-CUT device, and the V-CUT groove depth, PCB board residual thickness and V-CUT blade wear degree corresponding to the twin model are updated in real time; According to the groove depth, residual thickness and blade wear state, the tool shaft processing drift trend is predicted; When the drift trend prediction value exceeds the process threshold, a feedforward compensation instruction is issued to the tool shaft servo system to realize closed-loop correction of the V-CUT processing process.

[0007] Further, the multi-spectral laser displacement sensor array is distributed in a fan shape outside the rotation plane of the V-CUT tool shaft, and outputs multiple laser lines of different wavelengths; each laser line is arranged at an equal angular distance with the center of the tool shaft as the center, and is projected to the outer edge of the blade at a fixed included angle with the rotation plane, for detecting the blade wear and groove depth cross-sectional profile.

[0008] Further, the high-frequency piezoelectric micro-touch probe is installed behind the tool shaft and coaxial with the V-CUT groove center line; the front end of the probe is a spherical stylus, and the stylus axis is perpendicular to the lower surface of the PCB, for measuring the groove residual thickness and ensuring that the residual thickness measurement direction is consistent with the board thickness direction.

[0009] Further, the point cloud data is synchronously mapped into the digital twin model corresponding to the V-CUT device, and the V-CUT groove depth, PCB board residual thickness and V-CUT blade wear degree corresponding to the twin model are updated in real time, including: A three-dimensional geometric body corresponding to the physical V-CUT device is established in the digital twin model, and the geometric body includes the tool shaft, the blade, the PCB board and their coordinate systems; The point cloud data output by the multi-spectral laser displacement sensor array is synchronized with the tool shaft encoder angle through time stamping, to obtain spatial coordinates corresponding to the outer edge of the blade and the groove cross section; The residual thickness data output by the high-frequency piezoelectric micro-touch probe is given a time stamp through the same clock source, and is mapped to the PCB lower surface node in the digital twin model based on the groove center line as a reference; Coordinate transformation is performed in the digital twin model to make the point cloud data coincide with the geometric body coordinate system, forming a three-dimensional graph of the V-CUT device updated in real time; Based on the three-dimensional graph of the V-CUT device, the groove depth, residual thickness and blade wear degree in the digital twin model are calculated and updated.

[0010] Further, based on the three-dimensional graph of the V-CUT device, the groove depth, residual thickness and blade wear degree in the digital twin model are calculated and updated, including: Performing cross-section slicing on the real-time three-dimensional topography within the digital twin model, extracting the minimum Z-direction distance from the trench bottom to the upper surface of the PCB as the current trench depth value; Reading the mapped stylus displacement value at the same cross-section, calculating the thickness difference from the upper surface to the lower surface of the PCB as the current residual thickness value; ICP registration of the real-time blade edge point cloud with the initial reference profile, determining the average radius reduction and the collapse volume according to the registration result, and determining the wear degree based on the radius reduction and the collapse volume.

[0011] Further, the method further comprises: Retrieving the corresponding drift coefficient according to the wear state of the blade edge in the digital twin model; Based on the drift coefficient, calculating the depth drift amount prediction value according to the real-time trench depth and residual thickness, and the calculation formula is: In the formula, is the trench depth drift prediction value; is the real-time trench depth, is the real-time residual thickness; , are the drift coefficients corresponding to the blade edge wear grade, respectively; , are the first-piece reference values, respectively.

[0012] Further, the method further comprises: if the corrected drift trend prediction value still exceeds the process threshold, the digital twin triggers the emergency stop and alarm light of the physical device.

[0013] In another aspect, the present application also provides a V-CUT processing process intelligent dynamic control system for realizing the V-CUT processing process intelligent dynamic control method described above, comprising: a multi-spectral laser displacement sensor array distributed in a fan shape outside the V-CUT blade shaft rotation plane, a high-frequency piezoelectric micro-touch probe arranged behind the blade shaft coaxial with the V-CUT trench center line, and a control module connected with the multi-spectral laser displacement sensor array and the high-frequency piezoelectric micro-touch probe. The multi-spectral laser displacement sensor array is used to detect the blade edge wear and the trench depth cross-sectional profile; The high-frequency piezoelectric micro-touch probe is used to measure the trench residual thickness; The control module is used for synchronously mapping the point cloud data into a digital twin model corresponding to the V-CUT device, updating the V-CUT groove depth, the PCB residual thickness and the V-CUT knife edge wear degree corresponding to the twin model in real time, predicting the tool shaft machining drift trend according to the groove depth, the residual thickness and the knife edge wear state, and issuing a feedforward compensation instruction to the tool shaft servo system when the drift trend prediction value exceeds a process threshold, so that closed-loop correction of the V-CUT machining process is realized.

[0014] Further, the multispectral laser displacement sensor array adopts independent bandpass filters and polarizers in each channel of the array, and is integrally packaged in an aluminum shell purged with nitrogen.

[0015] Further, the system further comprises a three-color tower lamp and an audible and visual alarm, and the alarm is directly driven by the control module through a GPIO.

[0016] Compared with the prior art, the present application has the following advantages: (1) By arranging the multispectral laser displacement sensor array and the high-frequency piezoelectric micro touch probe on the V-CUT tool shaft, the groove depth, the residual thickness and the knife edge wear and other key information are collected in real time, the state of each link in the machining process is accurately mastered, abnormalities can be found in time, manual intervention is reduced, and the production accuracy and automation level are improved.

[0017] (2) The digital twin technology is used to synchronously map the real-time data into the digital model of the V-CUT device, so that the global monitoring of the machining process is realized. By continuously updating the digital twin model, the device and the machining state are always kept in the latest state, which greatly improves the intelligent and visual management ability of the system.

[0018] (3) The drift trend of the tool shaft machining is predicted by analyzing the real-time data, potential machining deviations are identified in advance, quality fluctuations in the machining process can be effectively prevented, the production of defective products is reduced, and the production cost is reduced; the tool shaft servo system is automatically adjusted by the feedforward compensation instruction, so that the accuracy of the machining process is ensured. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 The flowchart of the intelligent dynamic control method of the V-CUT machining process provided by the present application; Figure 2 The structural diagram of the control module provided by the present application. DETAILED DESCRIPTION

[0020] The preferred embodiments of the present application will be specifically described below in combination with the drawings, wherein the drawings constitute a part of the present application, and are used to illustrate the principles of the embodiments of the present application, and are not used to limit the scope of the present application.

[0021] Example 1 Referring to Figure 1 , Figure 1 A flowchart of the intelligent dynamic control method for the V-CUT processing provided by the embodiment is shown, which comprises the following steps: Step S101: A multi-spectral laser displacement sensor array is arranged on the V-CUT tool shaft, and a high-frequency piezoelectric micro-touch probe is arranged on the residual thickness measuring station, and point cloud data is generated in real time based on a preset sampling frequency; Step S102: The point cloud data is synchronously mapped into the digital twin model corresponding to the V-CUT device, and the V-CUT groove depth, the PCB board residual thickness and the V-CUT blade wear degree corresponding to the twin model are updated in real time; Step S103: The tool shaft processing drift trend is predicted according to the groove depth, the residual thickness and the blade wear state; Step S104: When the drift trend prediction value exceeds the process threshold, a feedforward compensation instruction is issued to the tool shaft servo system to realize closed-loop correction of the V-CUT processing process.

[0022] The intelligent dynamic control method for the V-CUT processing provided by the embodiment realizes real-time collection of key data such as groove depth, residual thickness and blade wear during the processing by arranging a multi-spectral laser displacement sensor array and a high-frequency piezoelectric micro-touch probe on the V-CUT tool shaft, and realizes dynamic updating and prediction analysis through digital twin technology. When the tool shaft processing drift trend exceeds the process threshold, feedforward compensation is automatically performed, which improves the processing precision. The method improves the processing quality, equipment life and production efficiency, reduces the scrap rate, and improves the automation and intelligent level of the production process.

[0023] As a preferred embodiment, in step S101, the multi-spectral laser displacement sensor array is distributed in a fan shape outside the rotation plane of the V-CUT tool shaft, and outputs multiple laser lines of different wavelengths; each laser line is arranged at an equal angle distance with the center of the tool shaft as the center, and is projected to the outer edge of the blade at a fixed included angle with the rotation plane, for detecting the blade wear and the groove depth cross-sectional profile.

[0024] As a specific embodiment, the multi-spectral laser displacement sensor array scans through multiple laser lines at the same time through different wavebands, including visible light, near-infrared light and ultraviolet light, which can eliminate the errors caused by copper foil reflection and solder mask color difference, and obtain sub-micron level groove depth, angle and surface topography data, so as to obtain the depth and three-dimensional profile of the V-CUT groove.

[0025] As a specific embodiment, the array is composed of no less than 8 laser lines with different center wavelengths (λ = 450 nm, 520 nm, 635 nm, 808 nm, 850 nm, 905 nm, 940 nm, 980 nm), which are distributed in a 120° fan shape at 5 mm outside the rotation plane of the tool shaft; at 10 mm behind the V-CUT tool, 8 laser lines with different wavelengths cross the groove. Each laser line is arranged at an equal angle of 15° with the center of the tool shaft as the center, ensuring that at least 3 laser lines cover the outer edge of the blade every 1° of rotation; the radial angle between the laser line light direction and the blade is θ = 30° ± 1°, in order to reduce saturation caused by high light reflection of copper foil; each laser line is equipped with an independent band-pass filter and a polarizer to filter out environmental stray light and improve the signal-to-noise ratio ≥ 40 dB; the whole array is packaged in an aluminum alloy shell purged with nitrogen, and a sapphire window is provided at the front end of the shell to prevent dust from adhering; the shell temperature is controlled to T = 25 ℃ ± 0.5 ℃. During subsequent monitoring, the "Z value" (i.e. groove depth) from the bottom of the groove to the upper surface of the PCB is measured by the triangulation method.

[0026] After one rotation of the tool shaft, a spiral line-shaped point cloud (X, Y are the circumferential coordinates of the tool shaft, and Z is the radius / depth) is generated, and different colors are used to correspond to different reflectivities, thereby suppressing the light reflection error of the copper foil.

[0027] As a preferred embodiment, the high-frequency piezoelectric micro-touch probe is installed behind the tool shaft coaxially with the center line of the V-CUT groove; the front end of the probe is a spherical stylus, and the stylus axis is perpendicular to the lower surface of the PCB, which is used to measure the residual thickness of the groove and ensures that the residual thickness measurement direction is consistent with the plate thickness direction.

[0028] Specifically, the high-frequency piezoelectric micro-touch probe is installed 30 mm behind the tool coaxially with the center line of the V-CUT groove, and the perpendicularity between the end face of the probe and the lower surface of the PCB is ≤ 0.02 mm; the front end of the probe is a ruby spherical stylus with a ball diameter R = 0.5 mm and a surface roughness Ra ≤ 0.1 µm; the elastic stroke of the probe is Δz = 500 µm, and the pre-pressing amount is set to 100 µm, ensuring that the touch force F ≤ 0.3 N; the probe is driven by a piezoelectric stack, with a natural frequency f0 ≥ 12 kHz and a sampling frequency set to no less than 5 kHz; the inside of the probe shell is filled with high-damping silicone gel to suppress high-frequency vibration interference on the signal; the tail of the probe is connected to a charge amplifier through a flexible coaxial cable, the cable length is ≤ 1.5 m, the shielding layer is 360° grounded, and the noise is < 50 µV; the whole probe is fixed by a vacuum suction type micro slide, with a stroke of ± 2 mm for automatic zero calibration; a micro compressed air nozzle is provided between the slide and the probe, which blows the stylus end face before each measurement to prevent dust accumulation and cause errors.

[0029] The point cloud generated after the probe scanning has no lateral coordinates, only a "thickness curve", a single-channel point list (t, Z) of "time-displacement", and each Z value is the current residual thickness. The thickness value is pasted to the same section of the laser point cloud to realize the registration of the upper and lower surfaces.

[0030] To quantify the impact of the heated elongation of the tool shaft or the heated warping of the PCB, in some embodiments, the method further comprises: reading the main shaft motor current, servo motor temperature rise, and instantaneous depth drift of the laser point cloud feedback in real time within the digital twin model, calculating the tool shaft thermal elongation and PCB warping through a pre-set thermal-mechanical coupling empirical model or neural network, superimposing the tool shaft thermal elongation and PCB warping to the current groove depth and residual thickness results to complete the thermal deformation compensation and synchronously update the twin database.

[0031] As a preferred embodiment, in step S102, the synchronous mapping of the point cloud data to the digital twin model corresponding to the V-CUT device updates the V-CUT groove depth, PCB plate residual thickness, and V-CUT blade wear degree corresponding to the digital twin model in real time, including: A three-dimensional geometric body corresponding to the physical V-CUT device is established in the digital twin model, and the geometric body includes a tool shaft, a tool blade, a PCB plate, and their coordinate systems; The point cloud data output by the multi-spectral laser displacement sensor array is synchronized with the tool shaft encoder angle through a time stamp to obtain spatial coordinates corresponding to the outer edge of the tool blade and the groove section; The residual thickness data output by the high-frequency piezoelectric micro-touch probe is given a time stamp through the same clock source and mapped to the PCB lower surface node in the digital twin model based on the groove center line; Coordinate transformation is performed within the digital twin model to make the point cloud data coincide with the geometric body coordinate system, forming a real-time updated three-dimensional graph of the V-CUT device; Based on the three-dimensional graph of the V-CUT device, the groove depth, residual thickness, and blade wear degree in the digital twin model are calculated and updated.

[0032] As a preferred embodiment, based on the three-dimensional graph of the V-CUT device, the groove depth, residual thickness, and blade wear degree in the digital twin model are calculated and updated, including: The real-time three-dimensional topography is sliced within the digital twin model to extract the minimum Z-direction distance from the groove valley to the PCB upper surface as the current groove depth value; The mapped stylus displacement value is read at the same section to calculate the thickness difference between the PCB upper surface and the lower surface as the current residual thickness value; The real-time tool blade outer edge point cloud is ICP registered with the initial reference profile, the average radius reduction and the collapse volume are determined according to the registration result, and the wear degree is determined based on the radius reduction and the collapse volume.

[0033] As a specific embodiment, the amount of blade wear is quantified as discrete levels L ∈ {0, 1, 2, 3} (0 level is a new blade, 3 level is severe wear), and is updated in real time within the digital twin model, and in the digital twin, a preset depth drift coefficient corresponding to each wear level L is provided.

[0034] As a preferred embodiment, in step S103, the blade axis machining drift trend is predicted according to the groove depth, the residual thickness, and the blade wear state, including: a corresponding drift coefficient is called according to the blade wear degree within the digital twin model; Based on the drift coefficient, the depth drift amount prediction value is calculated according to the real-time groove depth and the residual thickness, and the calculation formula is: In the formula, is the groove depth drift prediction value; is the real-time groove depth, is the real-time residual thickness; , are drift coefficients corresponding to the blade wear levels, respectively; , are the first piece reference values, respectively.

[0035] As a preferred embodiment, the method further includes: if the corrected drift trend prediction value still exceeds the process threshold, the digital twin triggers the emergency stop and alarm light of the physical device.

[0036] Embodiment 2 The embodiment provides a V-CUT machining process intelligent dynamic control system for realizing the V-CUT machining process intelligent dynamic control method described in the above technical solution, which comprises: a multi-spectral laser displacement sensor array distributed in a fan shape outside a V-CUT blade axis rotation plane, a high-frequency piezoelectric micro-touch probe arranged behind the blade axis coaxially with a V-CUT groove center line, and a control module connected with the multi-spectral laser displacement sensor array and the high-frequency piezoelectric micro-touch probe. The multi-spectral laser displacement sensor array is used for detecting blade wear and groove depth cross-sectional profile; The high-frequency piezoelectric micro-touch probe is used for measuring groove residual thickness; The control module is used for synchronously mapping point cloud data into a digital twin model corresponding to a V-CUT device, updating the V-CUT groove depth, the PCB board residual thickness, and the V-CUT blade wear degree corresponding to the digital twin model in real time, predicting the blade axis machining drift trend according to the groove depth, the residual thickness, and the blade wear state, and issuing a feedforward compensation instruction to a blade axis servo system when the drift trend prediction value exceeds a process threshold, so as to realize closed-loop correction of the V-CUT machining process.

[0037] As a specific embodiment, as shown in Figure 2 The control module 200 comprises: A data synchronization unit 201 for receiving the point cloud stream of the multi-spectral laser array and the residual thickness stream of the piezoelectric micro-touch probe, and performing clock alignment, coordinate registration, and timestamp writing; A digital modeling unit 202 for loading the corresponding digital twin model of the V-CUT device, mapping the synchronized data into groove depth, residual thickness, and blade wear grade, and updating the twin database; A drift prediction unit 203 for calling the drift coefficient according to the wear grade, taking the current time as the endpoint, continuously intercepting a fixed number or fixed time length of sequences as a sliding window, and performing linear or empirical model calculation on the groove depth and residual thickness in the sliding window to output the blade axis depth drift prediction value; A feedforward compensation unit 204 for generating servo feed compensation instructions when the predicted drift value exceeds the process threshold, and issuing them to the blade axis servo driver through the EtherCAT or CANopen bus.

[0038] An abnormality handling unit 205 for triggering an emergency stop logic, driving a three-color light and an audible and visual alarm, and uploading an abnormality snapshot to the cloud when the compensation is invalid or the drift continues to increase.

[0039] As a preferred embodiment, the multi-spectral laser displacement sensor array adopts independent bandpass filters and polarizers in each channel of the array, and is packaged in an aluminum shell purged with nitrogen.

[0040] As a preferred embodiment, the system further comprises a three-color tower light and an audible and visual alarm, which is directly driven by the control module through GPIO.

[0041] The above is only a preferred specific embodiment of the present application, but the protection scope of the present application is not limited thereto. Any changes or replacements within the technical scope disclosed by the present application can be easily thought of by those skilled in the art, and should be covered within the protection scope of the present application.

Claims

1. A method for intelligent dynamic control of V-CUT processing, characterized in that, include: A multispectral laser displacement sensor array is arranged on the V-CUT tool axis, and a high-frequency piezoelectric micro-touch probe is arranged at the residual thickness measurement station to generate point cloud data in real time based on preset sampling frequencies. Point cloud data is synchronously mapped to the digital twin model corresponding to the V-CUT device, and the V-CUT trench depth, PCB board residual thickness and V-CUT blade wear degree corresponding to the twin model are updated in real time. Predict the machining drift trend of the tool shaft based on the groove depth, residual thickness, and tool edge wear condition; When the predicted drift trend exceeds the process threshold, a feedforward compensation command is sent to the tool axis servo system to achieve closed-loop correction of the V-CUT machining process.

2. The intelligent dynamic control method for V-CUT processing according to claim 1, characterized in that, The multispectral laser displacement sensor array is distributed in a fan shape on the outside of the rotation plane of the V-CUT cutter shaft, and outputs multiple laser lines of different wavelengths. Each laser line is arranged at equal angles with the center of the cutter shaft as the center, and is projected onto the outer edge of the cutting edge at a fixed angle with the rotation plane, which is used to detect the wear of the cutting edge and the cross-sectional profile of the groove depth.

3. The intelligent dynamic control method for V-CUT processing according to claim 1, characterized in that, The high-frequency piezoelectric micro-touch probe is installed behind the cutter shaft and is coaxial with the center line of the V-CUT trench. The front end of the probe is a spherical stylus with its axis perpendicular to the lower surface of the PCB. It is used to measure the residual thickness of the trench and ensures that the measurement direction of the residual thickness is consistent with the board thickness direction.

4. The intelligent dynamic control method for V-CUT processing according to claim 1, characterized in that, The process of synchronously mapping point cloud data to a digital twin model corresponding to the V-CUT device, and updating the V-CUT trench depth, PCB board residual thickness, and V-CUT blade wear degree corresponding to the twin model in real time, includes: In the digital twin model, a three-dimensional geometry is established that corresponds to the physical V-CUT device. The geometry includes the cutter axis, the cutter blade, the PCB board, and their coordinate system. The point cloud data output by the multispectral laser displacement sensor array is synchronized with the angle of the cutter shaft encoder through a timestamp to obtain the spatial coordinates corresponding to the outer edge of the cutting edge and the groove section. The residual thickness data output by the high-frequency piezoelectric micro-touch probe is timestamped using the same clock source and mapped to the PCB lower surface node in the digital twin model with the trench centerline as the reference. Perform coordinate transformation within the digital twin model to make the point cloud data coincide with the geometric coordinate system, forming a real-time updated 3D graphic of the V-CUT device; Based on the 3D graphics of the V-CUT device, the groove depth, residual thickness, and tool edge wear in the digital twin model are calculated and updated.

5. The intelligent dynamic control method for V-CUT processing according to claim 4, characterized in that, Based on the 3D graphics from the V-CUT device, calculate and update the groove depth, residual thickness, and tool edge wear in the digital twin model, including: Perform cross-sectional slicing on the real-time 3D topography within the digital twin model, and extract the minimum Z-axis distance from the bottom of the trench to the upper surface of the PCB as the current trench depth value; Read the mapped stylus displacement value at the same cross section, calculate the thickness difference between the upper and lower surfaces of the PCB, and use it as the current residual thickness value; The real-time blade edge point cloud is registered with the initial reference profile using ICP. The average radius reduction and chipping volume are determined based on the registration results. The degree of wear is then determined based on the radius reduction and chipping volume.

6. The intelligent dynamic control method for V-CUT processing according to claim 1, characterized in that, The method of predicting the machining drift trend of the tool shaft based on the groove depth, residual thickness, and tool edge wear state includes: Within the digital twin model, the corresponding drift coefficient is retrieved based on the degree of blade wear; Based on the drift coefficient, the predicted depth drift value is calculated according to the real-time trench depth and residual thickness. The calculation formula is as follows:   In the formula, This is the predicted value for trench depth drift; For real-time trench depth, For real-time residual thickness; , These are the drift coefficients corresponding to the cutting edge wear level; , These are the baseline values ​​for the first piece.

7. The intelligent dynamic control method for V-CUT processing according to claim 1, characterized in that, Also includes: If the corrected drift trend prediction still exceeds the process threshold, the digital twin will trigger the physical equipment to stop and activate the alarm lights.

8. A V-CUT machining process intelligent dynamic control system, used to implement the V-CUT machining process intelligent dynamic control method according to any one of claims 1-7, characterized in that, include: A multispectral laser displacement sensor array is arranged in a fan shape on the outer side of the V-CUT cutter shaft rotation plane; a high-frequency piezoelectric micro-touch probe is set behind the cutter shaft and coaxial with the center line of the V-CUT groove; and a control module is connected to the multispectral laser displacement sensor array and the high-frequency piezoelectric micro-touch probe of the control module. The multispectral laser displacement sensor array is used to detect blade wear and the cross-sectional profile of groove depth; The high-frequency piezoelectric micro-touch probe is used to measure the residual thickness of the trench. The control module is used to synchronously map point cloud data into a digital twin model corresponding to the V-CUT device, and update the V-CUT trench depth, PCB board residual thickness, and V-CUT tool edge wear degree corresponding to the twin model in real time; predict the tool axis machining drift trend based on the trench depth, residual thickness, and tool edge wear state; when the predicted drift trend value exceeds the process threshold, send a feedforward compensation command to the tool axis servo system to realize closed-loop correction of the V-CUT machining process.

9. The intelligent dynamic control system for V-CUT processing according to claim 8, characterized in that, The multispectral laser displacement sensor array uses independent bandpass filters and polarizers for each channel within the array, and is encapsulated in a nitrogen-purged aluminum shell.

10. The intelligent dynamic control system for V-CUT processing according to claim 8, characterized in that, The system also includes a three-color tower light and an audible and visual alarm, the alarm being directly driven by the control module via GPIO.

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