Calibration method of full-automatic circuit board cutting machine

Abstract

The invention relates to the technical field of laser heat treatment, and provides a calibration method of a full-automatic circuit board cutting machine. The method comprises the following steps: acquiring physical coordinates of a circuit board of a cutting device through an intelligent sensor, and constructing a reference coordinate system matrix based on the physical coordinates; determining vibration parameters of the cutting device according to coordinates of laser spots emitted by a laser and the reference coordinate system matrix, and generating a nonlinear error component according to the vibration parameters and power information of the laser; generating an error function based on an error matrix formed by the error components, and determining a calibration coefficient vector by solving the error function; closed-loop control is conducted on the laser path of the cutting device through the calibration coefficient vector, the adaptability of the cutting device to complex working conditions is improved by integrating multi-source error factors and establishing a nonlinear mapping relation, and the cutting precision and stability are ensured.

Description

Technical Field

[0001] This application relates to the field of laser heat treatment technology, and more specifically, to a calibration method for a fully automatic circuit board cutting machine. Background Technology

[0002] In the high-end electronics manufacturing sector, especially in intelligent heat treatment production lines, the integration level of circuit boards continues to increase. Fine circuit cutting with a pitch of less than 0.3mm has become a core requirement for industries such as 5G communications and automotive electronics. Traditional laser cutting equipment relies on manual periodic calibration, but fluctuations in ambient temperature, thermal expansion of guide rails, and laser power can lead to the accumulation of cutting errors. Especially in the processing of high-density interconnect boards, even a tiny deviation can cause a short circuit risk, forcing companies to adopt inefficient downtime re-inspection processes.

[0003] Existing technologies typically calibrate cutting devices using static calibration methods. However, this approach cannot adapt to dynamic processing environments, such as the significant differences in thermal deformation patterns between the machine tool's preheating and stable operation phases. Furthermore, linear compensation models struggle to fit nonlinear errors; for example, the error curve caused by vibration mode coupling exhibits non-periodic fluctuations, resulting in calibration accuracy for PCB cutting machines failing to meet normal production requirements. Summary of the Invention

[0004] This application provides a calibration method for a fully automatic circuit board cutting machine, which can at least partially solve the problem of low calibration accuracy of circuit board cutting machines.

[0005] Other features and advantages of this application will become apparent from the following detailed description, or may be learned in part from practice of this application.

[0006] According to one aspect of this application, a calibration method for a fully automatic circuit board cutting machine is provided, comprising: acquiring the physical coordinates of the circuit board of the cutting device through an intelligent sensor, and constructing a reference coordinate system matrix based on the physical coordinates; determining the vibration parameters of the cutting device through the coordinates of the laser spot emitted by the laser and the reference coordinate system matrix, and generating nonlinear error components based on the vibration parameters and the power information of the laser; generating an error function based on the error matrix formed by the error components, and determining a calibration coefficient vector by solving the error function; and performing closed-loop control of the laser path of the cutting device through the calibration coefficient vector.

[0007] In this application, based on the aforementioned scheme, the step of acquiring the physical coordinates of the circuit board of the cutting device through a smart sensor and constructing a reference coordinate system matrix based on the physical coordinates includes: emitting a laser through a photoelectric sensor to illuminate a preset reflection mark point on the edge of the circuit board of the cutting device and receiving the reflected light signal; determining the origin offset based on the position change of the reflected light signal; acquiring the real-time temperature through a temperature sensor and determining the coordinate system rotation angle based on the position change and the real-time temperature; and generating a reference coordinate system matrix based on the origin offset and the coordinate system rotation angle.

[0008] In this application, based on the aforementioned scheme, determining the origin offset based on the positional change of the reflected light signal includes: obtaining the edge length of the circuit board of the cutting device; and determining the origin offset of the mechanical coordinate system based on the positional change of the reflected light signal in the electrical signal and the edge length of the circuit board. for:

[0009]

[0010] in, The value represents the change in position of the reflected light signal on the horizontal and vertical axes, and L represents the length of the circuit board edge of the cutting device.

[0011] In this application, based on the aforementioned scheme, the step of acquiring real-time temperature through a temperature sensor and determining the coordinate system rotation angle based on the position change and the real-time temperature includes: acquiring real-time temperature through a temperature sensor and determining the coordinate system rotation angle based on the position change and the real-time temperature. for:

[0012] in, This represents the temperature factor.

[0013] In this application, based on the aforementioned scheme, generating the reference coordinate system matrix according to the origin offset and the coordinate system rotation angle includes: generating the reference coordinate system matrix according to the origin offset and the coordinate system rotation angle. for:

[0014] In this application, based on the aforementioned scheme, determining the vibration parameters of the cutting device using the laser spot coordinates emitted by the laser and the reference coordinate system matrix, and generating nonlinear error components based on the vibration parameters and the power information of the laser, includes: acquiring the laser spot coordinates emitted by the laser; determining the global coordinates corresponding to the laser spot coordinates based on the laser spot coordinates and the reference coordinate system matrix; performing modal analysis on the global coordinates to obtain vibration parameters; generating frequency parameters based on the output power and rated power of the laser; and generating nonlinear error components based on the vibration parameters and the frequency parameters.

[0015] In this application, based on the aforementioned scheme, the step of generating an error function based on the error matrix composed of the error components and determining the calibration coefficient vector by solving the error function includes: constructing a nonlinear mapping function based on the pre-trained deep unfolded network matrix and the error components; generating a derivative regularization term based on the error matrix composed of the error components; generating an error function according to the nonlinear mapping function and the derivative regularization term; and solving the error function to determine the calibration coefficient vector.

[0016] In this application, based on the aforementioned scheme, the closed-loop control of the laser path of the cutting device through the calibration coefficient vector includes: generating gain information for dynamic control based on the calibration coefficient vector; determining control parameters based on the gain information; generating a control signal based on the control parameters; and performing closed-loop control of the laser path of the cutting device through the control signal.

[0017] In this application, based on the aforementioned scheme, the vibration parameters include vibration mode amplitude, natural frequency, and phase angle.

[0018] In this application, based on the aforementioned scheme, the step of solving the error function to determine the calibration coefficient vector includes: solving the error function to determine the calibration coefficient vector through iterative optimization.

[0019] According to one aspect of this application, a computer-readable medium is provided having a computer program stored thereon, which, when executed by a processor, implements the calibration method for a fully automatic circuit board cutting machine as described in the above embodiments.

[0020] According to one aspect of this application, an electronic device is provided, comprising: one or more processors; and a storage device for storing one or more programs, which, when executed by the one or more processors, cause the one or more processors to implement the calibration method for a fully automatic circuit board cutting machine as described in the above embodiments.

[0021] According to one aspect of this application, a computer program product or computer program is provided, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the calibration method for a fully automatic circuit board cutting machine provided in the various alternative implementations described above.

[0022] This application's technical solution acquires the physical coordinates of the circuit board of the cutting device using intelligent sensors, and constructs a reference coordinate system matrix based on these physical coordinates. Vibration parameters of the cutting device are determined using the coordinates of the laser spot emitted by the laser and the reference coordinate system matrix. Nonlinear error components are generated based on these vibration parameters and the power information of the laser. An error function is generated based on the error matrix formed by these error components, and a calibration coefficient vector is determined by solving the error function. The laser path of the cutting device is then controlled in a closed loop using the calibration coefficient vector. High-precision closed-loop calibration is achieved through dynamic nonlinear compensation, constructing a reference coordinate system that includes temperature and mechanical offset corrections to eliminate the influence of environmental interference on initial positioning. Secondly, by combining laser spot coordinates and vibration mode analysis, nonlinear error components caused by power fluctuations during the cutting process are captured. Finally, the calibration coefficient vector is solved using the error function to form dynamic gain control parameters, enabling real-time closed-loop adjustment of the laser path. By integrating multiple error factors and establishing a nonlinear mapping relationship, the adaptability of the cutting device to complex working conditions is improved, ensuring cutting accuracy and stability.

[0023] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0024] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0025] Figure 1 The flowchart illustrating the calibration method of a fully automatic circuit board cutting machine in one embodiment of this application is shown schematically.

[0026] Figure 2 The flowchart illustrating the construction of a reference coordinate system matrix is ​​shown in one embodiment of this application.

[0027] Figure 3 The diagram illustrates a calibration device for a fully automatic circuit board cutting machine in one embodiment of this application.

[0028] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application is shown. Detailed Implementation

[0029] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided to make this application more comprehensive and complete, and to fully convey the concept of the exemplary embodiments to those skilled in the art.

[0030] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this application. However, those skilled in the art will recognize that the technical solutions of this application can be practiced without one or more of the specific details, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this application.

[0031] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0032] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0033] The implementation details of the technical solution of this application are described below: Figure 1 A flowchart illustrating a calibration method for a fully automated circuit board cutting machine according to an embodiment of this application is shown. (Refer to...) Figure 1 As shown, the calibration method for this fully automatic circuit board cutting machine includes at least steps S110 to S140, which are described in detail below: S110: Obtain the physical coordinates of the circuit board of the cutting device through the intelligent sensor, and construct a reference coordinate system matrix based on the physical coordinates.

[0034] In this embodiment, a photoelectric sensor array deployed on the edge of the circuit board captures the spatial position of the cutting starting point and the reference marker point in real time. Triangulation is used to convert the light spot displacement into physical coordinate data. Based on the collaborative positioning results of multiple sensor sets, the geometric center is automatically selected as the origin. A two-dimensional rectangular coordinate system is established in combination with the direction of guide rail movement. Finally, the local coordinates are mapped to the global processing reference through matrix transformation, thus completing the construction of the initial positioning framework.

[0035] like Figure 2 As shown, in one embodiment of this application, the physical coordinates of the circuit board of the cutting device are obtained through a smart sensor, and a reference coordinate system matrix is ​​constructed based on the physical coordinates, including: S210 emits a laser through a photoelectric sensor to illuminate a preset reflective mark on the edge of the circuit board of the cutting device and receives the reflected light signal; S220, determine the origin offset based on the change in position of the reflected light signal; S230: The real-time temperature is obtained through a temperature sensor, and the rotation angle of the coordinate system is determined based on the position change and the real-time temperature. S240, Generate a reference coordinate system matrix based on the origin offset and the coordinate system rotation angle.

[0036] In one embodiment of this application, the first step in establishing the initial positioning reference is to determine the origin of the mechanical coordinate system. A photoelectric sensor emits a laser to illuminate pre-set reflective markers on the edge of the circuit board, receives the reflected light signal, and converts it into an electrical signal. Based on the positional changes of the reflected light signal on the detector, and combined with triangulation, the physical coordinates of the origin are calculated to ensure precise fixing of the cutting starting point.

[0037] For example, this embodiment employs a photoelectric origin sensor, such as a PSD position-sensitive detector. It emits a laser beam to illuminate a reflective marker point on the edge of the circuit board, receives the reflected light signal, converts it into an electrical signal, and determines the physical position of the mechanical coordinate system origin, i.e., the origin offset, based on the change in position of the reflected light signal within the electrical signal. for:

[0038]

[0039] in, This represents the change in position of the reflected light signal on the horizontal and vertical axes. L This indicates the length of the circuit board edge of the cutting device.

[0040] Optionally, temperature sensors can be placed near the circuit board fixture to continuously collect ambient temperature data. By combining this data with the material's coefficient of thermal expansion, the impact of temperature changes on the coordinate system is calculated, and the origin coordinates and rotation angle are dynamically adjusted. This process ensures that the equipment maintains high-precision positioning under different temperature environments, providing a stable reference for subsequent cutting.

[0041] In one embodiment of this application, the displacement of the stage is monitored in real time. High-precision optical scales are installed on the X-axis and Y-axis guide rails of the device. A reading head captures minute movements of the guide rails, converting the displacement data into electrical signals. This data is used to correct the coordinate system rotation angle. Real-time temperature is obtained through a temperature sensor, and the coordinate system rotation angle is determined based on the position change and the real-time temperature. for:

[0042] in, This indicates the temperature factor. Rotating the coordinate system by an angle ensures the cutting path is synchronized with the mechanical movement, avoiding positioning deviations caused by guide rail errors.

[0043] In one embodiment of this application, a reference coordinate system matrix is ​​generated based on the origin offset and the coordinate system rotation angle. for:

[0044] By calculating the reference coordinate system matrix, the matrix form is compatible with the coordinate transformation requirements of subsequent steps, providing a unified reference framework for error detection. This transforms the measured coordinates of the laser spot to the global coordinate system, a prerequisite for subsequent error matrix calculation.

[0045] The above process uses photoelectric sensors to capture the displacement of reflective markers on the edge of the circuit board, and combines this with temperature data to calculate the origin offset and coordinate system rotation angle, eliminating initial positioning deviations caused by thermal deformation. Specifically, the detection of reflective markers can capture sub-micron deformation of the mechanical guide rail caused by temperature changes, and dynamically correct the origin position to avoid offset of the cutting start point. The coordinate system rotation angle calculation can compensate for coordinate system deflection caused by circuit board clamping tilt or machine tool foundation settlement, ensuring that the global coordinate system is consistent with the machining datum, and providing a unified reference framework for subsequent error analysis.

[0046] S120, the vibration parameters of the cutting device are determined by the coordinates of the laser spot emitted by the laser and the reference coordinate system matrix, and a nonlinear error component is generated based on the vibration parameters and the power information of the laser.

[0047] In one embodiment of this application, when the laser emitted by the laser illuminates the circuit board, the position change of the laser spot is captured in real time by a sensor. This coordinate data is transformed into an established reference coordinate system to eliminate initial positioning errors. The dynamic changes in the laser spot position are analyzed to extract periodic vibration signals and identify vibration modes of different frequencies and their amplitudes. Simultaneously, the real-time power output of the laser is monitored to discover a nonlinear correlation between power fluctuations and laser spot offset. Finally, the periodic error caused by vibration and the nonlinear error caused by power changes are combined to form a comprehensive error component, providing a dynamic adjustment basis for subsequent calibration.

[0048] In one embodiment of this application, vibration parameters of the cutting device are determined using the coordinates of the laser spot emitted by the laser and the reference coordinate system matrix. Nonlinear error components are then generated based on the vibration parameters and the power information of the laser, including: Obtain the coordinates of the laser spot emitted by the laser, and determine the global coordinates corresponding to the laser spot coordinates based on the laser spot coordinates and the reference coordinate system matrix; Modal analysis is performed on the global coordinates to obtain vibration parameters, wherein the vibration parameters include vibration mode amplitude, natural frequency, and phase angle; Frequency parameters are generated based on the laser's output power and rated power; Based on the vibration parameters and the frequency parameters, a nonlinear error component is generated.

[0049] In one embodiment of this application, the first step in dynamic error detection is to acquire the laser spot position in real time. A four-quadrant photodetector is used to accurately capture the spot coordinates. Interference signals are filtered out by a differential circuit, and then processed by a high-precision analog-to-digital converter to obtain the coordinates of the laser spot emitted by the laser. Based on the laser spot coordinates and the reference coordinate system matrix, the global coordinates corresponding to the laser spot coordinates are determined. for: : in, This indicates the coordinates of the laser spot.

[0050] Subsequently, modal analysis is performed on the global coordinates, and vibration parameters are automatically identified using a spectral peak detection algorithm. By separating the errors caused by mechanical vibration, rapid spectral analysis is performed on the collected position data to automatically identify the main frequencies and amplitudes of the equipment vibration. By converting the time-domain signal into frequency-domain features, periodic errors caused by mechanical factors such as guide rail vibration and motor rotation can be accurately extracted, avoiding confusion with laser power fluctuations. The vibration parameters include vibration mode amplitude, natural frequency, and phase angle.

[0051] In one embodiment of this application, frequency parameters are generated based on the output power and rated power of the laser. By compensating for the influence of laser power changes, the actual output energy of the laser is monitored synchronously and compared with a preset reference power to dynamically calculate the influence of energy fluctuations on the spot position.

[0052] Subsequently, the error model is automatically adjusted based on power changes, and the offset caused by non-mechanical factors is incorporated into the error matrix in real time to ensure that the cutting path is always consistent with the target trajectory. Based on the vibration parameters and the frequency parameters, nonlinear error components are generated. for:

[0053] in, These represent the vibration mode amplitude, natural frequency, and phase angle, respectively. These represent the output power and rated power of the laser, respectively. Represents the power factor. k and n These represent the identifier and quantity of vibration parameters, respectively. By separating mechanical vibration from power fluctuations, the underestimation of errors caused by traditional linear superposition is avoided.

[0054] The above process transforms the laser spot coordinates to a reference coordinate system, extracts the vibration amplitude through modal analysis, and generates error components by combining power fluctuations. Its technical effectiveness lies in quantifying the coupling effect of multi-source interference. Specifically, vibration modal analysis can identify information such as the amplitude corresponding to the machine tool's resonant frequency, distinguishing between structural vibration and random interference, and providing frequency domain characteristics for error compensation. Nonlinear modeling of power fluctuations and spot offset, such as the shift in the material vaporization threshold caused by changes in laser energy density, can capture the power-error correlation neglected by traditional linear models, improving the completeness of error prediction.

[0055] S130, Based on the error matrix formed by the error components, an error function is generated, and the calibration coefficient vector is determined by solving the error function.

[0056] In one embodiment of this application, based on the error matrix obtained by dynamic error detection, typical error patterns are first extracted from historical data as a basis function library. These basis functions can characterize the vibration and power coupling characteristics under different working conditions. Then, a dual-objective error function containing fitting accuracy and parameter smoothness terms is constructed, and the model complexity is adaptively adjusted by dynamically balancing the weights of the two terms. Finally, an iterative optimization algorithm is used to gradually adjust the basis function weight coefficients. The calculation is terminated when the prediction error decreases below a threshold for several consecutive iterations. The generated coefficient vector is the optimal calibration parameter that balances real-time performance and generalization ability.

[0057] In one embodiment of this application, an error function is generated based on the error matrix formed by the error components, and a calibration coefficient vector is determined by solving the error function, including: Based on the pre-trained deep unfolded network matrix and the error components, a nonlinear mapping function is constructed; Based on the error matrix formed by the error components, a derivative regularization term is generated; An error function is generated based on the nonlinear mapping function and the derivative regularization term; Solve the error function to determine the calibration coefficient vector.

[0058] In one embodiment of this application, the first step in generating adaptive calibration coefficients is to construct an optimization model. Based on the detected error matrix, a set of pre-trained basis functions is selected as an error pattern library. These basis functions are learned from historical data and can cover common mechanical vibration and power fluctuation characteristics. By weighted combination of these basis functions, an attempt is made to fit the real-time error data with the fewest parameters, providing an initial framework for subsequent parameter adjustments. Based on the pre-trained deep unfolded network matrix and the error components, a nonlinear mapping function is constructed. F for:

[0059] in, These represent the pre-trained deep unfolded network matrices, Indicates the first p The weight coefficients of each basis function This represents the error matrix composed of error components. p and P These represent the parameter identifier and the total number of parameters, respectively.

[0060] In one embodiment of this application, a regularization mechanism is introduced by dynamically adjusting the model complexity to automatically balance fitting accuracy and parameter stability based on the current error magnitude. When the error is large, the model allows for more flexible parameter adjustments to quickly approximate the true error; when the error is small, the model limits the rate of parameter change to avoid overcorrection due to noise interference. This process is achieved by calculating the statistical characteristics of the error energy in real time. Based on the error matrix composed of the error components, a derivative regularization term is generated. Z for:

[0061] in, t and N These represent the identifier and total number of the error components, respectively. This represents the mean of the weighting coefficients. The fitting accuracy and parameter smoothness are balanced by adjusting the derivative regularization term.

[0062] In one embodiment of this application, an error function is generated based on the nonlinear mapping function and the derivative regularization term. for:

[0063] In one embodiment of this application, after generating the error function, the error function is iteratively optimized and solved. Optionally, an efficient numerical optimization algorithm is used to gradually adjust the weight coefficients starting from the initial parameters. In each iteration, the prediction error under the current parameter combination is calculated, and the parameters are updated along the direction of the fastest error decrease. When the error decrease is less than a preset threshold in several consecutive iterations, or when the maximum number of iterations is reached, the optimization process terminates. The final set of parameters generated is the adaptive calibration coefficient, which is combined to generate a calibration coefficient vector for real-time control of the laser path.

[0064] The above process constructs a nonlinear mapping based on a deep unfolded network and optimizes the calibration coefficients using derivative regularization terms. This achieves highly generalizable adaptive calibration. By transforming the nonlinear optimization problem into multi-layer parameter adjustment through deep unfolded networks, it can fit the complex coupling relationships of multi-dimensional variables such as vibration, power, and temperature, avoiding the limitations of manually designed basis functions. Derivative regularization terms suppress high-frequency parameter oscillations, ensuring a smooth transition of calibration coefficients under changing operating conditions, preventing control signal jitter caused by overfitting, and improving the algorithm's adaptability to different materials.

[0065] S140 performs closed-loop control of the laser path of the cutting device through calibration coefficient vector.

[0066] In one embodiment of this application, the control parameters are dynamically adjusted according to the calibration coefficient, and the error compensation amount is converted into a driving signal for the laser galvanometer. Multi-dimensional correction instructions are synthesized through a proportional-integral-differential strategy to drive the dual-axis galvanometer to adjust the laser emission angle in real time, so that the cutting path automatically fits the target trajectory. At the same time, the corrected position data is fed back to the initial detection module to form a continuously optimized calibration cycle, ensuring that sub-micron level processing accuracy can still be maintained even when there is environmental interference or equipment aging.

[0067] In one embodiment of this application, closed-loop control of the laser path of the cutting device is performed using a calibration coefficient vector, including: Gain information for dynamic control is generated based on the calibration coefficient vector; Based on the gain information, control parameters are determined, and control signals are generated according to the control parameters. The laser path of the cutting device is controlled in a closed loop using the control signal.

[0068] In this embodiment, the first step of real-time feedback control is to dynamically adjust the control parameters. Based on the generated calibration coefficient vector, the gain weights of the proportional, integral, and derivative terms are automatically calculated and used as control parameters. Specifically, the proportional term directly responds to the current error magnitude, the integral term accumulates historical errors to eliminate residual deviations, and the derivative term predicts the error change trend. The three terms work together to ensure that the control signal is both sensitive and stable.

[0069] Then, a multi-dimensional control signal is synthesized based on the gain weights of the proportional, integral, and derivative terms. The error matrix is ​​decomposed into... X shaft and Y The independent components of each axis are calculated, and the output values ​​of the control parameters for each axis are calculated separately. By weighted superposition of the control terms, a composite signal is generated that simultaneously suppresses mechanical vibration and power fluctuations, ensuring that the laser galvanometer synchronously corrects path offset in both directions.

[0070] Next, the composite signal is input to the laser galvanometer driver for hardware-level path correction. The control signal is converted into analog voltage via a digital-to-analog converter, driving the dual-axis galvanometer to rapidly adjust the reflection angle. The voltage signal is linearly related to the galvanometer deflection angle. Precise calibration ensures that every volt change in voltage corresponds to a sub-micron level path correction, achieving high-precision closed-loop control. The corrected laser path is fed back to the initial positioning module in real time, forming a calibration cycle. The error matrix and control parameters are dynamically updated based on the latest path data, ensuring that cutting accuracy is maintained even with environmental changes or equipment aging, forming an adaptive long-term stable operation mechanism.

[0071] The above process utilizes calibration coefficients to dynamically adjust control parameters, generating control signals to drive the galvanometer correction path. This constructs a real-time correction mechanism resistant to interference. The dynamic gain adjustment automatically switches control strategies based on the error amplitude: for large errors, the proportional term is strengthened for rapid convergence; for small errors, the integral term is strengthened to eliminate residuals; and the derivative term continuously suppresses vibration interference. Simultaneously, closed-loop feedback transmits the corrected path data back to the initial positioning module, forming a continuously optimized calibration cycle. This ensures that the equipment maintains stable cutting accuracy even under long-term operating conditions such as ambient temperature fluctuations and laser power attenuation.

[0072] This application's technical solution acquires the physical coordinates of the circuit board of the cutting device using intelligent sensors, and constructs a reference coordinate system matrix based on these physical coordinates. Vibration parameters of the cutting device are determined using the coordinates of the laser spot emitted by the laser and the reference coordinate system matrix. Nonlinear error components are generated based on these vibration parameters and the power information of the laser. An error function is generated based on the error matrix formed by these error components, and a calibration coefficient vector is determined by solving the error function. The laser path of the cutting device is then controlled in a closed loop using the calibration coefficient vector. High-precision closed-loop calibration is achieved through dynamic nonlinear compensation, constructing a reference coordinate system that includes temperature and mechanical offset corrections to eliminate the influence of environmental interference on initial positioning. Secondly, by combining laser spot coordinates and vibration mode analysis, nonlinear error components caused by power fluctuations during the cutting process are captured. Finally, the calibration coefficient vector is solved using the error function to form dynamic gain control parameters, enabling real-time closed-loop adjustment of the laser path. By integrating multiple error factors and establishing a nonlinear mapping relationship, the adaptability of the cutting device to complex working conditions is improved, ensuring cutting accuracy and stability.

[0073] The following describes embodiments of the calibration device for a fully automatic circuit board cutting machine according to this application, which can be used to execute the calibration method for the fully automatic circuit board cutting machine in the above embodiments of this application. It is understood that the calibration device for the fully automatic circuit board cutting machine can be a computer program (including program code) running on a computer device, for example, the calibration device for the fully automatic circuit board cutting machine is an application software; the calibration device for the fully automatic circuit board cutting machine can be used to execute the corresponding steps in the method provided in the embodiments of this application. For details not disclosed in the embodiments of the calibration device for the fully automatic circuit board cutting machine of this application, please refer to the embodiments of the calibration method for the fully automatic circuit board cutting machine described above in this application.

[0074] Figure 3 A block diagram of a calibration apparatus for a fully automatic circuit board cutting machine according to an embodiment of this application is shown.

[0075] Reference Figure 3 As shown, a calibration device for a fully automatic circuit board cutting machine according to an embodiment of this application includes: The acquisition unit is used to acquire the physical coordinates of the circuit board of the cutting device through a smart sensor, and to construct a reference coordinate system matrix based on the physical coordinates; The vibration unit is used to determine the vibration parameters of the cutting device by using the coordinates of the laser spot emitted by the laser and the reference coordinate system matrix, and to generate nonlinear error components based on the vibration parameters and the power information of the laser. The calibration unit is used to generate an error function based on the error matrix formed by the error components, and to determine the calibration coefficient vector by solving the error function. The control unit is used to perform closed-loop control of the laser path of the cutting device through a calibration coefficient vector.

[0076] In this application, based on the aforementioned scheme, the step of acquiring the physical coordinates of the circuit board of the cutting device through a smart sensor and constructing a reference coordinate system matrix based on the physical coordinates includes: emitting a laser through a photoelectric sensor to illuminate a preset reflection mark point on the edge of the circuit board of the cutting device and receiving the reflected light signal; determining the origin offset based on the position change of the reflected light signal; acquiring the real-time temperature through a temperature sensor and determining the coordinate system rotation angle based on the position change and the real-time temperature; and generating a reference coordinate system matrix based on the origin offset and the coordinate system rotation angle.

[0077] In this application, based on the aforementioned scheme, determining the origin offset based on the positional change of the reflected light signal includes: obtaining the edge length of the circuit board of the cutting device; and determining the origin offset of the mechanical coordinate system based on the positional change of the reflected light signal in the electrical signal and the edge length of the circuit board. for:

[0078]

[0079] in, The value represents the change in position of the reflected light signal on the horizontal and vertical axes, and L represents the length of the circuit board edge of the cutting device.

[0080] In this application, based on the aforementioned scheme, the step of acquiring real-time temperature through a temperature sensor and determining the coordinate system rotation angle based on the position change and the real-time temperature includes: acquiring real-time temperature through a temperature sensor and determining the coordinate system rotation angle based on the position change and the real-time temperature. for:

[0081] in, This represents the temperature factor.

[0082] In this application, based on the aforementioned scheme, generating the reference coordinate system matrix according to the origin offset and the coordinate system rotation angle includes: generating the reference coordinate system matrix according to the origin offset and the coordinate system rotation angle. for:

[0083] In this application, based on the aforementioned scheme, determining the vibration parameters of the cutting device using the laser spot coordinates emitted by the laser and the reference coordinate system matrix, and generating nonlinear error components based on the vibration parameters and the power information of the laser, includes: acquiring the laser spot coordinates emitted by the laser; determining the global coordinates corresponding to the laser spot coordinates based on the laser spot coordinates and the reference coordinate system matrix; performing modal analysis on the global coordinates to obtain vibration parameters; generating frequency parameters based on the output power and rated power of the laser; and generating nonlinear error components based on the vibration parameters and the frequency parameters.

[0084] In this application, based on the aforementioned scheme, the step of generating an error function based on the error matrix composed of the error components and determining the calibration coefficient vector by solving the error function includes: constructing a nonlinear mapping function based on the pre-trained deep unfolded network matrix and the error components; generating a derivative regularization term based on the error matrix composed of the error components; generating an error function according to the nonlinear mapping function and the derivative regularization term; and solving the error function to determine the calibration coefficient vector.

[0085] In this application, based on the aforementioned scheme, the closed-loop control of the laser path of the cutting device through the calibration coefficient vector includes: generating gain information for dynamic control based on the calibration coefficient vector; determining control parameters based on the gain information; generating a control signal based on the control parameters; and performing closed-loop control of the laser path of the cutting device through the control signal.

[0086] In this application, based on the aforementioned scheme, the vibration parameters include vibration mode amplitude, natural frequency, and phase angle.

[0087] In this application, based on the aforementioned scheme, the step of solving the error function to determine the calibration coefficient vector includes: solving the error function to determine the calibration coefficient vector through iterative optimization.

[0088] This application's technical solution acquires the physical coordinates of the circuit board of the cutting device using intelligent sensors, and constructs a reference coordinate system matrix based on these physical coordinates. Vibration parameters of the cutting device are determined using the coordinates of the laser spot emitted by the laser and the reference coordinate system matrix. Nonlinear error components are generated based on these vibration parameters and the power information of the laser. An error function is generated based on the error matrix formed by these error components, and a calibration coefficient vector is determined by solving the error function. The laser path of the cutting device is then controlled in a closed loop using the calibration coefficient vector. High-precision closed-loop calibration is achieved through dynamic nonlinear compensation, constructing a reference coordinate system that includes temperature and mechanical offset corrections to eliminate the influence of environmental interference on initial positioning. Secondly, by combining laser spot coordinates and vibration mode analysis, nonlinear error components caused by power fluctuations during the cutting process are captured. Finally, the calibration coefficient vector is solved using the error function to form dynamic gain control parameters, enabling real-time closed-loop adjustment of the laser path. By integrating multiple error factors and establishing a nonlinear mapping relationship, the adaptability of the cutting device to complex working conditions is improved, ensuring cutting accuracy and stability.

[0089] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application is shown.

[0090] It should be noted that the computer system of the electronic device in this embodiment is only an example and should not impose any limitations on the function and scope of use of the embodiments of this application.

[0091] In this embodiment, the computer system includes a central processing unit 401, which can perform various appropriate actions and processes based on a program stored in a read-only memory 402 or a program loaded from a storage section 408 into a random access memory 403, such as executing the calibration method of the fully automatic circuit board cutting machine described in the above embodiment. The random access memory 403 also stores various programs and data required for system operation. The central processing unit 401, the read-only memory 402, and the random access memory 403 are interconnected via a bus 404. An input / output interface 405 is also connected to the bus 404.

[0092] The following components are connected to the input / output interface 405: an input section 406 including a keyboard, mouse, etc.; an output section 407 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 408 including a hard disk, etc.; and a communication section 409 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the input / output interface 405 as needed. A removable medium 411, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 410 as needed so that computer programs read from it can be installed into the storage section 408 as needed.

[0093] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 409, and / or installed from removable medium 411. When the computer program is executed by central processing unit 401, it performs various functions defined in the system of this application.

[0094] It should be noted that the computer-readable medium shown in the embodiments of this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying a computer-readable computer program. The transmitted data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wired, etc., or any suitable combination thereof.

[0095] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0096] The units described in the embodiments of this application can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the specific unit itself.

[0097] According to one aspect of this application, a computer program product or computer program is provided, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the methods provided in the various alternative implementations described above.

[0098] In another aspect, this application also provides a computer-readable medium, which may be included in the electronic device described in the above embodiments; or it may exist independently and not assembled into the electronic device. The computer-readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to implement the calibration method of the fully automatic circuit board cutting machine described in the above embodiments.

[0099] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of this application, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0100] Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, touch terminal, or network device, etc.) to execute the methods according to the embodiments of this application.

[0101] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein.

[0102] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A calibration method for a fully automatic circuit board cutting machine, characterized in that, include: The physical coordinates of the circuit board of the cutting device are obtained by intelligent sensors, and a reference coordinate system matrix is ​​constructed based on the physical coordinates; The vibration parameters of the cutting device are determined by the coordinates of the laser spot emitted by the laser and the reference coordinate system matrix, and nonlinear error components are generated based on the vibration parameters and the power information of the laser. Based on the error matrix formed by the error components, an error function is generated, and the calibration coefficient vector is determined by solving the error function. The laser path of the cutting device is controlled in a closed loop by using a calibration coefficient vector.

2. The calibration method for the fully automatic circuit board cutting machine according to claim 1, characterized in that, The physical coordinates of the circuit board of the cutting device are obtained through intelligent sensors, and a reference coordinate system matrix is ​​constructed based on the physical coordinates, including: A laser is emitted by a photoelectric sensor to illuminate a pre-set reflective mark on the edge of the circuit board of the cutting device, and the reflected light signal is received. The origin offset is determined based on the change in position of the reflected light signal; The real-time temperature is obtained by a temperature sensor, and the rotation angle of the coordinate system is determined based on the position change and the real-time temperature. A reference coordinate system matrix is ​​generated based on the origin offset and the coordinate system rotation angle.

3. The calibration method for the fully automatic circuit board cutting machine according to claim 2, characterized in that, The origin offset is determined based on the change in position of the reflected light signal, including: Obtain the circuit board edge length of the cutting device; The offset of the origin of the mechanical coordinate system is determined based on the positional change of the reflected light signal in the electrical signal and the edge length of the circuit board. for: in, The value represents the change in position of the reflected light signal on the horizontal and vertical axes, and L represents the length of the circuit board edge of the cutting device.

4. The calibration method for the fully automatic circuit board cutting machine according to claim 3, characterized in that, Real-time temperature is acquired via a temperature sensor, and the coordinate system rotation angle is determined based on the position change and the real-time temperature, including: The real-time temperature is obtained by a temperature sensor, and the rotation angle of the coordinate system is determined based on the position change and the real-time temperature. for: in, This represents the temperature factor.

5. The calibration method for the fully automatic circuit board cutting machine according to claim 4, characterized in that, Based on the origin offset and the coordinate system rotation angle, a reference coordinate system matrix is ​​generated, including: Generate a reference coordinate system matrix based on the origin offset and the coordinate system rotation angle. for: 。 6. The calibration method for the fully automatic circuit board cutting machine according to claim 1, characterized in that, The vibration parameters of the cutting device are determined by using the coordinates of the laser spot emitted by the laser and the reference coordinate system matrix. Based on the vibration parameters and the power information of the laser, nonlinear error components are generated, including: Obtain the coordinates of the laser spot emitted by the laser, and determine the global coordinates corresponding to the laser spot coordinates based on the laser spot coordinates and the reference coordinate system matrix; Modal analysis was performed on the global coordinates to obtain vibration parameters; Frequency parameters are generated based on the laser's output power and rated power; Based on the vibration parameters and the frequency parameters, a nonlinear error component is generated.

7. The calibration method for the fully automatic circuit board cutting machine according to claim 1, characterized in that, Based on the error matrix formed by the error components, an error function is generated, and the calibration coefficient vector is determined by solving the error function, including: Based on the pre-trained deep unfolded network matrix and the error components, a nonlinear mapping function is constructed; Based on the error matrix formed by the error components, a derivative regularization term is generated; An error function is generated based on the nonlinear mapping function and the derivative regularization term; Solve the error function to determine the calibration coefficient vector.

8. The calibration method for the fully automatic circuit board cutting machine according to claim 1, characterized in that, Closed-loop control of the laser path of the cutting device is achieved through calibration coefficient vectors, including: Gain information for dynamic control is generated based on the calibration coefficient vector; Based on the gain information, control parameters are determined, and control signals are generated according to the control parameters. The laser path of the cutting device is controlled in a closed loop using the control signal.

9. The calibration method for the fully automatic circuit board cutting machine according to claim 6, characterized in that, The vibration parameters include vibration mode amplitude, natural frequency, and phase angle.

10. The calibration method for the fully automatic circuit board cutting machine according to claim 7, characterized in that, Solving the error function to determine the calibration coefficient vector includes: The calibration coefficient vector is determined by solving the error function through iterative optimization.

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