Flexible control method and system for handheld laser welding machine

Abstract

The invention discloses a flexible control method and system of a handheld laser welding machine, and relates to the field of welding processes. The method comprises the following steps: obtaining stability information; acquiring a working mode and laser parameters; performing working parameter waveform fitting to obtain a working energy waveform; carrying out handheld data waveform fitting to obtain an execution state waveform; performing similarity fitting according to the working energy waveform and the execution state waveform, determining deviation data, and performing flexible control node configuration based on the deviation data; and performing parameter adaptive control according to the deviation data and the flexible control node. By the adoption of the method, the technical problem that the laser parameters of the handheld laser welding machine cannot directly use fixed numerical values due to different control persons of the handheld laser welding machine is solved, the stability and quality of the welding process are improved by analyzing the handheld stability and conducting self-adaptive control, and the welding quality of the handheld laser welding machine is improved. And meanwhile, the technical effects of operation requirements and skill levels of different users are met.

Description

Technical Field

[0001] The present application relates to the field of welding process technology, and specifically to a flexible control method and system for a handheld laser welder. Background Art

[0002] As an important part of modern welding technology, laser welding technology has significant advantages such as high precision, high efficiency and low thermal impact. With the continuous advancement of laser technology, laser welding has been widely used in many fields, especially in high-precision manufacturing fields such as automobiles, electronics, and aerospace. The application of handheld devices has brought greater flexibility and portability to laser welding. Compared with traditional fixed laser welding equipment, handheld laser welders can adapt to more complex on-site environments and achieve welding of irregular shapes and difficult-to-access parts. This flexibility makes handheld laser welders have broad application prospects in maintenance, modification and special manufacturing. However, the flexible control method of handheld laser welders still faces some challenges. On the one hand, due to the large uncertainty of the operation of handheld devices, factors such as the operator's skill level and operating habits will affect the welding quality. Therefore, how to achieve accurate and stable control of handheld laser welders is an urgent problem to be solved.

[0003] In summary, there is a technical problem in the prior art that the laser parameters of the handheld laser welder cannot be directly fixed values ​​due to the different controllers of the handheld laser welder. Summary of the invention

[0004] Based on this, it is necessary to provide a flexible control method and system for a handheld laser welding machine that can perform adaptive control by analyzing the hand-held stability, thereby improving the stability and quality of the welding process and meeting the operating needs and skill levels of different users.

[0005] In a first aspect, a flexible control method for a handheld laser welder is provided, the method comprising: connecting a built-in monitoring module, extracting monitoring data of the handheld laser welder to perform handheld stability analysis, and obtaining stability information, wherein the monitoring data is real-time monitoring feedback through a built-in sensor; obtaining a working mode and laser parameters, wherein the working mode includes a continuous mode, a quasi-continuous mode, and a pulse mode, and the laser parameters include power, frequency, and pulse width; performing working parameter waveform fitting according to the working mode and laser parameters to obtain a working energy waveform; performing handheld data waveform fitting using the stability information to obtain an execution status waveform; performing similarity fitting according to the working energy waveform and the execution status waveform to determine deviation data, and performing flexible control node configuration based on the deviation data; performing parameter adaptive control through an adaptive control module according to the deviation data and the flexible control node.

[0006] In the second aspect, a flexible control system of a handheld laser welder is provided, the system comprising: a stability analysis module, the stability analysis module is used to connect to the built-in monitoring module, extract the monitoring data of the handheld laser welder to perform handheld stability analysis, and obtain stability information, wherein the monitoring data is real-time monitoring feedback through the built-in sensor; a working mode acquisition module, the working mode acquisition module is used to obtain the working mode and laser parameters, the working mode includes a continuous mode, a quasi-continuous mode, and a pulse mode, and the laser parameters include power, frequency, and pulse width; a working energy waveform acquisition module, the working energy waveform acquisition module is used to perform working parameter waveform fitting according to the working mode and laser parameters to obtain a working energy waveform; an execution state waveform acquisition module, the execution state waveform acquisition module is used to perform handheld data waveform fitting using the stability information to obtain an execution state waveform; a deviation data determination module, the deviation data determination module is used to perform similarity fitting according to the working energy waveform and the execution state waveform, determine the deviation data, and perform flexible control node configuration based on the deviation data; a parameter adaptive control module, the parameter adaptive control module is used to perform parameter adaptive control through an adaptive control module according to the deviation data and the flexible control node.

[0007] According to a third aspect, a computer device is provided, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps according to the first aspect when executing the computer program.

[0008] According to a fourth aspect, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the steps described in the first aspect are implemented.

[0009] The above-mentioned flexible control method and system of a handheld laser welder adopts this method to solve the technical problem that the laser parameters of the handheld laser welder cannot directly use fixed parameters due to different controllers of the handheld laser welder. By analyzing the handheld stability and performing adaptive control, the stability and quality of the welding process are improved, and the technical effect of satisfying the operation requirements and skill levels of different users is achieved.

[0010] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 It is a schematic flow chart of a flexible control method of a handheld laser welder in one embodiment; Figure 2 A schematic diagram of a process for obtaining a working energy waveform of a flexible control method for a handheld laser welder in one embodiment; Figure 3 It is a structural block diagram of a flexible control system of a handheld laser welding machine in one embodiment; Figure 4 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment.

[0012] Explanation of the reference numerals: stability analysis module 11 , working mode acquisition module 12 , working energy waveform acquisition module 13 , execution state waveform acquisition module 14 , deviation data determination module 15 , parameter adaptive control module 16 . DETAILED DESCRIPTION

[0013] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0014] like Figure 1 As shown, the present application provides a flexible control method for a handheld laser welder, the method comprising: Connect the built-in monitoring module to extract the monitoring data of the handheld laser welder for handheld stability analysis and obtain stability information, where the monitoring data is real-time monitoring feedback through the built-in sensor; A handheld laser welder is a device that uses a laser beam as an energy source for welding. Through the high energy density of the laser beam, the surface of the workpiece is locally heated to above the melting point, causing it to melt and fuse with another workpiece. During the welding process, the laser beam is focused into a light spot with a very small diameter through an optical system. By controlling parameters such as the power, focal length and welding speed of the beam, accurate and efficient welding is achieved. Flexible control refers to the use of an adaptive and flexible control strategy for a system that changes frequently and requires flexible response, so as to quickly adapt to the various changes and uncertainties faced by the system. In this application, since each person's hand-held stability is different, the hand-held stability is monitored and adaptive control is performed according to the set parameters. By providing a flexible control method for a handheld laser welder, adaptive control can be performed for different hand-held stabilities.

[0015] The handheld laser welder is connected to a built-in monitoring module, which refers to a monitoring system integrated inside the handheld laser welder for real-time monitoring of various parameters and states of the handheld laser welder. Data is collected through built-in sensors, where the collected data is the monitoring data of the handheld laser welder, where the monitoring data is real-time monitoring feedback through built-in sensors, and these data are fed back to the control system or user in real time. By analyzing the monitoring data, handheld stability analysis is performed, that is, the stability of the handheld laser welder is evaluated. For example, by analyzing the data of the accelerometer, the vibration of the welder during operation can be understood; by analyzing the data of the gyroscope, the posture change of the welder can be understood. The monitoring data can determine whether the stability of the handheld laser welder is good and obtain stability information. Through data analysis and processing, key information about handheld stability, that is, stability information, including vibration amplitude, posture change frequency, etc., can be extracted. The stability information can be used to evaluate the performance of the welder and serve as a basis for improving and optimizing operations. By connecting the built-in monitoring module and extracting the monitoring data of the handheld laser welder, handheld stability analysis can be performed and stability information can be obtained. The performance of the welder can be better understood, and corresponding measures can be taken to optimize the operation and improve the welding quality.

[0016] The sensor includes an accelerometer, a gyroscope, and a pressure sensor, and the accelerometer or gyroscope is used to monitor the handheld motion trajectory and position balance to obtain movement stability data; The pressure sensor is arranged on the hand-held part to monitor the hand-held pressure distribution and pressure change to obtain the grip stability data; The movement stability data and the grasping stability data are aligned according to monitoring synchronization, and a fusion analysis is performed based on the movement stability data and the grasping stability data to determine the stable state of the handheld laser welder and obtain the stability information, including the fluctuation nodes and the fluctuation amplitudes thereof.

[0017] The sensor includes an accelerometer, a gyroscope, and a pressure sensor. The accelerometer can measure the acceleration changes of the welder in different directions, and can deduce the motion trajectory of the handheld laser welder. The gyroscope can monitor the angular velocity and direction changes of the welder, and then evaluate its position balance. The handheld laser welder is monitored by the accelerometer and the gyroscope to obtain the monitoring data. According to the monitoring data, the mobile stability data, such as the mean and standard deviation of the displacement, velocity, acceleration, and the changes in angular velocity and angular acceleration, can be calculated, so as to understand the dynamic stability during the hand-held process and obtain the mobile stability data. The pressure sensor is set on the handheld part, which can monitor the pressure distribution of the user's hand on the welder in real time. By continuously monitoring the pressure data, the changes in pressure during the operation can be analyzed. The above data can reflect the grip stability, such as the uniformity of pressure, the stability of pressure changes, etc., and then the grip stability data can be obtained. The mobile stability data and the grip stability data are aligned according to the monitoring synchronization. Since the accelerometer, gyroscope and pressure sensor have different sampling frequencies and response times, they need to be synchronized to ensure the consistency of the timestamps, so as to perform subsequent accurate fusion analysis. Fusion analysis is performed according to the mobile stability data and the grip stability data. Fusion analysis refers to the fusion of the mobile stability data and the grip stability data, and the dynamic and static stability of the handheld laser welder are comprehensively considered. For example, it can be analyzed whether the pressure distribution and pressure change also show corresponding trends at the moment when the acceleration or angular velocity changes greatly. Based on the results of the fusion analysis, the stable state of the handheld laser welder can be judged. For example, when the mobile stability data and the grip stability data are both in a lower fluctuation range, it can be considered that the welder is in a stable state; determine the stable state of the handheld laser welder, and obtain the stability information, including the fluctuation node and its fluctuation amplitude, the fluctuation node refers to the moment when the stability changes suddenly, and the fluctuation amplitude refers to the size of the stability change. According to the obtained stability information, the performance of the handheld laser welder can be evaluated, and feedback can be provided to the operator to adjust the handheld posture or operation mode to improve the welding quality. Through comprehensive monitoring and data analysis of accelerometers, gyroscopes and pressure sensors, the handheld stability of handheld laser welders can be comprehensively evaluated, providing strong support for optimizing operations and improving welding quality.

[0018] Acquire a working mode and laser parameters, wherein the working mode includes a continuous mode, a quasi-continuous mode, and a pulse mode, and the laser parameters include power, frequency, and pulse width; Obtaining the working mode of the handheld laser welder refers to covering a variety of different welding methods to meet the welding requirements of different materials and thicknesses. The working modes described in this application include continuous mode, quasi-continuous mode, and pulse mode. In the continuous mode, the laser will continuously output a stable laser beam with stable power and energy output. This mode is suitable for scenes that require continuous welding and have high requirements for welding speed, such as welding of long welds; the quasi-continuous mode combines the characteristics of the continuous mode and the pulse mode, outputs a laser beam within a certain time interval to form a continuous laser pulse sequence. This mode can reduce the thermal load of the laser while maintaining a certain welding speed, and is suitable for scenes with certain requirements for welding quality and speed; in the pulse mode, the laser outputs laser pulses at a certain frequency and pulse width, and the energy of each pulse can reach a very high level in a short time and then decrease rapidly. This mode has little thermal effect on the welding material and is suitable for materials that are sensitive to heat input or scenes that require precise control of welding heat effects. Laser parameters refer to the parameters corresponding to the handheld laser welder in different working modes of the handheld laser welder. The laser parameters include power, frequency, and pulse width. The power is the energy output by the laser welder, which determines the heat input during welding. The frequency refers to the repetition rate of the laser pulse, that is, the number of pulses emitted per unit time. The pulse width refers to the duration of a single laser pulse, which determines the energy distribution of each pulse and the heat input of the welding point. Power, frequency, and pulse width are important laser parameters of handheld laser welders, which are interrelated and jointly affect the welding effect. In actual operation, it is necessary to select a suitable combination of parameters according to specific welding requirements and material properties to achieve the best welding quality and efficiency.

[0019] Performing working parameter waveform fitting according to the working mode and laser parameters to obtain a working energy waveform; According to the working mode and laser parameters of the handheld laser welder, the data acquisition system of the device or the external measuring device is used to record the data of the laser output change over time, and a suitable mathematical model or algorithm is selected to perform waveform fitting. The parameters of the fitting model are adjusted according to the laser parameters (power, frequency, pulse width). For example, in the pulse mode, the width and height of the pulse can be directly mapped to the corresponding parameters of the fitting model; the working energy waveform is generated by the fitting model, and the working energy waveform describes the change of the laser output energy over time. By obtaining the working energy waveform, a data basis is provided for subsequent operations.

[0020] like Figure 2 As shown, according to the working mode, the timing characteristics of the laser output are obtained; Analyze the laser intensity, energy value, and energy distribution characteristics according to the laser parameters to obtain laser energy characteristics; The timing characteristics of the laser output are integrated with the laser energy characteristics to obtain the timing output data of the laser energy, and the timing output data of the laser energy is used to perform curve fitting to obtain the working energy waveform.

[0021] According to the working mode and laser parameters of the handheld laser welder, the timing characteristics of the laser output can be obtained. The timing characteristics describe the change of the laser output over time. Different working modes correspond to different timing characteristics. In the continuous mode, the laser outputs continuously with a stable power, and the timing characteristics are manifested as a smooth straight line. In the quasi-continuous mode, the laser output consists of a series of pulses, and there is a certain interval between each pulse. The timing characteristics are manifested as a series of pulse sequences with interval distribution. In the pulse mode, the laser is output in the form of high-frequency pulses. The width and interval of each pulse can be adjusted, and the timing characteristics are manifested as a high-frequency pulse sequence. The laser energy characteristics mainly include laser intensity, energy value and energy distribution. These characteristics can be obtained by analyzing the laser parameters. The laser intensity is directly related to the power. The higher the power, the greater the laser intensity. The energy value can be calculated by multiplying the power by time, which represents the total energy of the laser output over a period of time. The energy distribution describes the distribution of laser energy at different time points or different spatial positions. By calculating and analyzing these parameters, the energy characteristics of the laser can be obtained; by fusing the timing characteristics and energy characteristics, the timing output data of the laser energy can be obtained, which includes the changes in the laser output over time and also reflects the distribution of the laser energy during these changes. The timing output data of the laser energy is used for curve fitting, that is, the timing output data is fitted into a smooth curve on a plane. The working energy waveform describes the changes in the laser energy over time during the entire welding process, including the peak and valley values ​​of the energy and the distribution of the energy. Through the above method, a working energy waveform that reflects both the timing characteristics of the laser output and the characteristics of the laser energy is obtained, which lays the foundation for the subsequent analysis and optimization of the welding process.

[0022] Using the stability information to perform handheld data waveform fitting to obtain an execution state waveform; Collect stability data related to handheld operation through sensors, accelerometers or other monitoring equipment to evaluate unstable factors such as vibration and shaking during operation. Analyze the stability data and extract key stability features, including the frequency, amplitude, duration, etc. of vibration, which can reflect the degree of instability during handheld operation. Establish a stability model, apply the stability model to the handheld data waveform, and perform fitting operations. The purpose of fitting is to adjust the shape and parameters of the handheld data waveform according to the stability information so that it can more accurately reflect the execution status. Through the fitting operation, the execution status waveform adjusted by the stability information can be obtained. The execution status waveform refers to the unstable factors during the handheld operation, which can more realistically reflect the execution status of the device. By obtaining the execution status waveform, a basis is provided for subsequent comparative studies.

[0023] Performing similarity fitting between the working energy waveform and the execution state waveform to determine deviation data, and performing flexible control node configuration based on the deviation data; The working energy waveform and the execution state waveform are similarly fitted, that is, the similarity between the two waveforms and the difference between them are found. In this application, the working energy waveform and the execution state waveform are similarly fitted according to dynamic time warping. The dynamic time warping refers to calculating the best matching path between the two sequences by dynamic programming, so as to obtain the similarity between the working energy waveform and the execution state waveform; based on the similarity fitting, the deviation data can be determined. The deviation data reflects the difference between the working energy waveform and the execution state waveform, including the size, position and duration of the deviation. According to the deviation data, the configuration of the flexible control node can be performed. The flexible control node refers to the node that can dynamically adjust the control parameters according to the real-time data during the welding process. By reasonably configuring these nodes, the welding process can be more finely and flexibly controlled to reduce the deviation and improve the welding quality. Through the above method, the welding process is dynamically adjusted and optimized according to the real-time data, so as to improve the welding quality and efficiency.

[0024] Aligning the working energy waveform and the execution state waveform on a time axis according to a timing relationship; Creating a timing matrix, wherein each element of the timing matrix is ​​a numerical Euclidean distance between the working energy and the execution state at a corresponding time point; Based on the timing matrix, an element path search is performed according to a constraint route, and a distance accumulation value of the search path is calculated, wherein the constraint route includes a search start point, a search end point, and a search direction, and the search start point is the first row and first column element; Based on the distance accumulated value, determining a minimum accumulated value, and obtaining a similarity between the working energy waveform and the execution state waveform; Differences are identified based on the similarities to obtain the deviation data.

[0025] Ensure that the working energy waveform and the execution status waveform are strictly aligned on the time axis. Since both are time series data, each data point corresponds to a specific time point, so the order of the data points can be adjusted or interpolated to ensure that their time axes are consistent; create a time series matrix whose number of rows and columns corresponds to the number of time points of the two waveforms, and each element in the matrix represents the numerical Euclidean distance between the working energy and the execution state at the corresponding time point. The Euclidean distance is used to quantify the difference between the two states in numerical terms. In the time series matrix, the element path search is performed according to the predetermined constraint route. In this application, the constraint route includes the search starting point, which is usually the first row and first column element of the matrix, and the search end point is generally the last row and last column element of the matrix or other specific positions; and the search direction, the search direction includes unidirectional, bidirectional and specific paths. During the search process, the distance cumulative value of all elements on the path from the starting point to the current search position is calculated, and the cumulative value reflects the overall difference between the working energy and the execution state from the starting point to the current position. The minimum cumulative value represents the minimum difference accumulation between the working energy waveform and the execution status waveform in the entire timing process, which is used as an indicator to measure the similarity of the two waveforms: the smaller the cumulative value, the higher the similarity; the larger the cumulative value, the lower the similarity. Based on the minimum cumulative value and the cumulative values ​​of other search paths, differences can be identified and deviation data can be obtained. Deviation data may include information such as the size of the difference at a specific time point, the frequency of the difference, and the duration of the difference. By analyzing the deviation data, we can gain an in-depth understanding of the differences between the working energy waveform and the execution status waveform and their causes.

[0026] According to the deviation data and the flexible control node, parameter adaptive control is performed through an adaptive control module.

[0027] The obtained deviation data is analyzed in detail, including the size, duration, frequency of occurrence and specific positions of the deviations in the working energy waveform and the execution status waveform. By analyzing the deviation data, the problems existing in the welding process and the degree of influence on the welding quality can be understood. Based on the analysis results of the deviation data, the appropriate flexible control node is selected for parameter adjustment. The flexible control node is a point in the welding process where the control parameters can be dynamically adjusted according to the real-time data. For example, more control nodes are required to achieve fine adjustment in areas with large deviations. According to the characteristics of the deviation data and the flexible control node, an adaptive control module is formulated. The adaptive control module can receive the welding data and the deviation data in real time and automatically adjust the control parameters according to the control strategy. During the welding process, the adaptive control module continuously adjusts the control parameters according to the real-time data and the deviation information. Through the above method, the adaptive control module can realize the adaptive control of the welding parameters according to the characteristics of the deviation data and the flexible control node, thereby reducing the deviation, improving the welding quality, and realizing the intelligence and automation of the welding process.

[0028] Determining the difference relationship between the stability monitoring data and the laser operating parameters according to the deviation data; activating the parameter analysis model in the adaptive control module, performing laser operating parameter analysis according to the difference relationship between the stability monitoring data and the laser operating parameters, and outputting target laser operating parameters; The target laser operating parameters and the currently set laser parameters are used to perform compensation relationship analysis to generate adaptive compensation parameters, the compensation insertion time node is determined according to the flexible control node, and parameter control is performed through the adaptive control module according to the adaptive compensation parameters and the compensation insertion time node.

[0029] The deviation data is analyzed in detail, including the size of the deviation, the trend of change, and the location of the deviation. The stability monitoring data is compared with the laser working parameters to identify the difference between the two. The stability monitoring data includes stability-related indicators such as vibration, temperature, and pressure during the welding process, while the laser working parameters involve data such as laser power, scanning speed, and focal length. According to the deviation data, the difference relationship between the stability monitoring data and the laser working parameters is determined; in the adaptive control module, the parameter analysis model is activated. This model is used to conduct an in-depth analysis of the laser working parameters according to the difference relationship model, and the current laser working parameters are analyzed using the parameter analysis model. Based on the analysis results, the target laser working parameters are output. These parameters are the laser working parameter values ​​that are considered to improve the welding quality and stability after considering the difference relationship of the stability monitoring data. The target laser working parameters are compared with the currently set laser parameters to perform compensation relationship analysis. This analysis aims to determine the parameter range and adjustment direction that need to be adjusted to achieve a smooth transition from the current parameters to the target parameters. Based on the results of the compensation relationship analysis, adaptive compensation parameters are generated. These parameters reflect the specific values ​​and methods that need to be adjusted, and are used to compensate for the difference between the current laser working parameters and the target parameters. Combined with the configuration of the flexible control node, the insertion time node of the compensation parameter is determined. These nodes should choose the appropriate time in the welding process to adjust the parameters to avoid adverse effects on the welding quality. According to the adaptive compensation parameters and compensation insertion time nodes, the laser working parameters are controlled in real time through the adaptive control module. This includes adjusting parameters such as laser power and scanning speed to ensure the stability and quality of the welding process. According to the above method, the difference relationship between the stability monitoring data and the laser working parameters is deeply analyzed according to the deviation data, and the laser working parameters are accurately adjusted and optimized through the adaptive control module. This helps to improve the stability and quality of the welding process and achieve more efficient welding operations.

[0030] Collect monitoring data of handheld laser welders and build digital twin simulation space; Based on the stability monitoring data and laser working parameters, the simulation adjustment step is configured and the simulation parameter set is constructed; Based on the digital twin simulation space, the simulation parameter set is simulated to establish a simulation data set, wherein the simulation data set includes stability monitoring data, laser operating parameters, and welding damage / error range; The constraint conditions of the welding damage / error range are set, and the simulation data set is used to take the welding damage / error range as the dependent variable and the parameter relationship between the stability monitoring data and the laser working parameters as the independent variable for learning to construct the parameter analysis model.

[0031] Clearly need monitoring data to reflect the performance and stability of the handheld laser welder, including laser power, scanning speed, focal length, welding temperature, vibration, weld quality, etc. According to the monitoring indicators, select appropriate sensors and data acquisition equipment to ensure that the monitoring data can be obtained accurately and in real time. Based on the physical characteristics and working principle of the handheld laser welder, establish a corresponding digital simulation model. The simulation model should be able to simulate the changes and interactions of various parameters during the welding process. Set conditions similar to the actual working environment in the simulation model, including temperature, humidity, air pressure, etc., to ensure the accuracy of the simulation results. Based on the stability monitoring data and laser working parameters, generate a series of different parameter combinations to form a simulation parameter set, which should cover the working range and boundary conditions; in the digital twin simulation space, use the simulation parameter set to perform simulation, record various data during the simulation process, and organize the simulation results into a data set, including stability monitoring data, laser working parameters, and corresponding welding damage / error range information. According to actual needs, set the constraints of welding damage / error range, such as maximum allowable error, minimum quality requirements, etc.; use the simulation data set, take the welding damage / error range as the dependent variable, and take the parameter relationship between stability monitoring data and laser working parameters as the independent variable for machine learning, and build a parameter analysis model that can accurately reflect the parameter relationship through continuous iteration and optimization. Through the above method, the monitoring data of the handheld laser welder is used to build a digital twin simulation space, and the parameter analysis model is built based on the simulation data set for subsequent parameter optimization and adaptive control to improve the stability and quality of the welding process.

[0032] Build a handheld user database, including user codes, user operation levels, and historical monitoring data; Matching the user code to perform user operation level matching, performing user stability evaluation based on the historical monitoring data, and determining a user stability coefficient; Configure a compensation coefficient according to the user operation level and the user stability coefficient; Pre-compensating the laser parameters based on a compensation coefficient configured by a user; Setting adaptive constraint values ​​according to the working mode and laser parameters; Based on the pre-compensated laser parameters, adaptive adjustment is performed within the adaptive constraint value according to the adaptive compensation parameters obtained in real time.

[0033] A handheld user library is constructed to pre-store the user's habits and welding level. The handheld user library includes user codes, user operation levels, and historical monitoring data. User codes assign a unique code to each user for easy identification and management; user operation levels set operation levels for users based on factors such as user skill levels and experience, and can be evaluated through historical operation records, training results, and other methods; historical monitoring data collects and stores monitoring data of users in the process of using handheld laser welding machines, including stability monitoring data, laser working parameters, and the like. According to the user's code, the corresponding user operation level is retrieved from the handheld user library, and the user operation level is matched. Based on the historical monitoring data, the stability performance of the user during operation is analyzed. The stability of the user can be quantified by calculating stability indicators such as standard deviation and coefficient of variation. According to the stability indicators, the user stability coefficient is determined, which reflects the stability of the user during operation. According to the user operation level and the user stability coefficient, a corresponding compensation coefficient is configured for each user. The compensation coefficient is used to adjust the laser parameters to compensate for differences and instability during user operation. The user with a higher operation level and a better stability coefficient has a smaller compensation coefficient; otherwise, it is larger. Before welding begins, the laser parameters are pre-compensated according to the compensation coefficients configured by the user. The purpose of pre-compensation is to adjust the laser parameters in advance according to the user's operating characteristics and stability to improve the stability and quality of the welding process. According to the working mode, such as continuous welding, spot welding, etc. and the laser parameters, the adaptive constraint value is set. The adaptive constraint value defines the allowable range of the laser parameters during the adaptive adjustment process to ensure that the adjustment process is carried out within a safe and effective range. During the welding process, according to the adaptive compensation parameters obtained in real time, the laser parameters are adaptively adjusted within the adaptive constraint value. The adaptive compensation parameters are obtained based on real-time monitoring data and parameter analysis models, and are used to adjust the laser parameters in real time to optimize the welding process. By continuously adjusting the laser parameters to adapt to the user's operating characteristics and stability, the welding quality and efficiency are improved. According to the above method, a handheld user library is constructed, and the laser parameters are pre-compensated and adaptively adjusted according to the user's operating level and stability. This helps to improve the stability and quality of the welding process while meeting the operating needs and skill levels of different users.

[0034] In summary, the beneficial effects of this method include: The invention solves the technical problem in the prior art that the laser parameters of the handheld laser welder cannot be directly fixed due to the different controllers of the handheld laser welder. By analyzing the handheld stability and performing adaptive control, the stability and quality of the welding process are improved, and the technical effect of satisfying the operation requirements and skill levels of different users is achieved. like Figure 3As shown, the embodiment of the present application includes a flexible control system of a handheld laser welder, the system comprising: A stability analysis module 11, which is used to connect to the built-in monitoring module, extract monitoring data of the handheld laser welder to perform handheld stability analysis, and obtain stability information, wherein the monitoring data is real-time monitoring feedback through the built-in sensor; A working mode acquisition module 12, the working mode acquisition module 12 is used to acquire working modes and laser parameters, the working modes include continuous mode, quasi-continuous mode, and pulse mode, and the laser parameters include power, frequency, and pulse width; A working energy waveform acquisition module 13, wherein the working energy waveform acquisition module 13 is used to perform working parameter waveform fitting according to the working mode and laser parameters to obtain a working energy waveform; An execution state waveform acquisition module 14, wherein the execution state waveform acquisition module 14 is used to perform handheld data waveform fitting using the stability information to obtain an execution state waveform; A deviation data determination module 15, the deviation data determination module 15 is used to perform similarity fitting according to the working energy waveform and the execution state waveform, determine deviation data, and perform flexible control node configuration based on the deviation data; The parameter adaptive control module 16 is used to perform parameter adaptive control through an adaptive control module according to the deviation data and the flexible control node.

[0035] Furthermore, the embodiment of the present application also includes: A movement stability data acquisition module, wherein the movement stability data acquisition module is used for the sensor including an accelerometer, a gyroscope, and a pressure sensor, and the movement trajectory and position balance of the handheld device are monitored by the accelerometer or the gyroscope to obtain movement stability data; A gripping stability data acquisition module, wherein the gripping stability data acquisition module is used to set the pressure sensor on the handheld part, monitor the handheld pressure distribution and pressure change, and obtain gripping stability data; A data alignment module is used to align the movement stability data and the gripping stability data according to monitoring synchronization, perform fusion analysis based on the movement stability data and the gripping stability data, determine the stable state of the handheld laser welder, and obtain the stability information, including fluctuation nodes and fluctuation amplitudes thereof.

[0036] Furthermore, the embodiment of the present application also includes: A timing feature acquisition module, the timing feature acquisition module is used to acquire the timing feature of the laser output according to the working mode; A laser energy characteristic acquisition module, wherein the laser energy characteristic acquisition module is used to analyze the laser intensity, energy value, and energy distribution characteristics according to the laser parameters to obtain laser energy characteristics; A curve fitting module is used to fuse the timing characteristics of the laser output with the laser energy characteristics to obtain the timing output data of the laser energy, and to perform curve fitting using the timing output data of the laser energy to obtain the working energy waveform.

[0037] Furthermore, the embodiment of the present application also includes: A time axis alignment module, the time axis alignment module is used to perform time axis alignment on the working energy waveform and the execution state waveform according to a time sequence relationship; A timing matrix creation module, wherein the timing matrix creation module is used to create a timing matrix, wherein each element in the timing matrix is ​​a numerical Euclidean distance between the working energy and the execution state at a corresponding time point; An element path search module, the element path search module is used to perform element path search according to a constraint route based on the timing matrix, and calculate the distance accumulation value of the search path, the constraint route includes a search start point, a search end point, and a search direction, and the search start point is the first row and first column element; A minimum accumulated value determination module, the minimum accumulated value determination module is used to determine a minimum accumulated value based on the distance accumulated value, and obtain a similarity between the working energy waveform and the execution state waveform; A deviation data acquisition module is used to perform difference identification according to the similarity to obtain the deviation data.

[0038] Furthermore, the embodiment of the present application also includes: A difference relationship determination module, the difference relationship determination module is used to determine the difference relationship between the stability monitoring data and the laser operating parameters according to the deviation data; A target laser operating parameter output module, the target laser operating parameter output module is used to activate the parameter analysis model in the adaptive control module, perform laser operating parameter analysis according to the difference relationship between the stability monitoring data and the laser operating parameters, and output the target laser operating parameters; A compensation relationship analysis module, wherein the compensation relationship analysis module is used to perform compensation relationship analysis using the target laser operating parameters and the currently set laser parameters, generate adaptive compensation parameters, determine the compensation insertion time node according to the flexible control node, and perform parameter control through the adaptive control module according to the adaptive compensation parameters and the compensation insertion time node.

[0039] Furthermore, the embodiment of the present application also includes: A digital twin simulation space construction module, wherein the digital twin simulation space construction module is used to collect monitoring data of the handheld laser welder and construct a digital twin simulation space; A simulation parameter set construction module, wherein the simulation parameter set construction module is used to configure a simulation adjustment step size and construct a simulation parameter set based on stability monitoring data and laser operating parameters; A simulation module, wherein the simulation module is used to simulate the simulation parameter set based on the digital twin simulation space to establish a simulation data set, wherein the simulation data set includes stability monitoring data, laser operating parameters, and welding damage / error range; A parameter analysis model construction module is used to set constraints on the welding damage / error range, use the simulation data set to take the welding damage / error range as a dependent variable, and take the parameter relationship between the stability monitoring data and the laser working parameters as an independent variable for learning to construct the parameter analysis model.

[0040] Furthermore, the embodiment of the present application also includes: A handheld user library construction module, which is used to construct a handheld user library, including user codes, user operation levels, and historical monitoring data; A user stability coefficient determination module, the user stability coefficient determination module is used to match the user code to perform user operation level matching, perform user stability evaluation based on the historical monitoring data, and determine the user stability coefficient; A compensation coefficient configuration module, the compensation coefficient configuration module is used to configure the compensation coefficient according to the user operation level and the user stability coefficient; A pre-compensation module, the pre-compensation module is used to pre-compensate the laser parameters based on a compensation coefficient configured by a user; An adaptive constraint value setting module, the adaptive constraint value setting module is used to set an adaptive constraint value according to the working mode and laser parameters; The adaptive adjustment module is used to perform adaptive adjustment within the adaptive constraint value based on the pre-compensated laser parameters and the adaptive compensation parameters obtained in real time.

[0041] For a specific embodiment of a flexible control system of a handheld laser welder, please refer to the embodiment of a flexible control method of a handheld laser welder mentioned above, which will not be repeated here. The above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0042] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 4 As shown. The computer device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store news data and data such as time attenuation factors. The network interface of the computer device is used to communicate with an external terminal through a network connection. The computer program is executed by the processor to implement a flexible control method for a handheld laser welder.

[0043] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0044] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, steps of a flexible control method for a handheld laser welder are implemented.

[0045] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of a flexible control method for a handheld laser welder are implemented.

[0046] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0047] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application.

Claims

1. A flexible control method for a handheld laser welder, characterized in that: The method comprises: Connect the built-in monitoring module to extract the monitoring data of the handheld laser welder for handheld stability analysis and obtain stability information, where the monitoring data is real-time monitoring feedback through the built-in sensor; Acquire a working mode and laser parameters, wherein the working mode includes a continuous mode, a quasi-continuous mode, and a pulse mode, and the laser parameters include power, frequency, and pulse width; Performing working parameter waveform fitting according to the working mode and laser parameters to obtain a working energy waveform; Using the stability information to perform handheld data waveform fitting to obtain an execution state waveform; Performing similarity fitting between the working energy waveform and the execution state waveform to determine deviation data, and performing flexible control node configuration based on the deviation data; According to the deviation data and the flexible control node, parameter adaptive control is performed through an adaptive control module.

2. The method according to claim 1, characterized in that The extracting of monitoring data of the handheld laser welder to perform handheld stability analysis and obtain stability information includes: The sensor includes an accelerometer, a gyroscope, and a pressure sensor, and the accelerometer or gyroscope is used to monitor the handheld motion trajectory and position balance to obtain movement stability data; The pressure sensor is arranged on the hand-held part to monitor the hand-held pressure distribution and pressure change to obtain the grip stability data; The movement stability data and the grasping stability data are aligned according to monitoring synchronization, and a fusion analysis is performed based on the movement stability data and the grasping stability data to determine the stable state of the handheld laser welder and obtain the stability information, including the fluctuation nodes and the fluctuation amplitudes thereof.

3. The method according to claim 1, characterized in that Performing working parameter waveform fitting according to the working mode and laser parameters to obtain a working energy waveform includes: According to the working mode, obtaining the timing characteristics of the laser output; Analyze the laser intensity, energy value, and energy distribution characteristics according to the laser parameters to obtain laser energy characteristics; The timing characteristics of the laser output are integrated with the laser energy characteristics to obtain the timing output data of the laser energy, and the timing output data of the laser energy is used to perform curve fitting to obtain the working energy waveform.

4. The method according to claim 3, characterized in that Determining deviation data by performing similarity fitting between the working energy waveform and the execution state waveform, including: Aligning the working energy waveform and the execution state waveform on a time axis according to a timing relationship; Creating a timing matrix, wherein each element of the timing matrix is ​​a numerical Euclidean distance between the working energy and the execution state at a corresponding time point; Based on the timing matrix, an element path search is performed according to a constraint route, and a distance accumulation value of the search path is calculated, wherein the constraint route includes a search start point, a search end point, and a search direction, and the search start point is the first row and first column element; Based on the distance accumulated value, determining a minimum accumulated value, and obtaining a similarity between the working energy waveform and the execution state waveform; Differences are identified based on the similarities to obtain the deviation data.

5. The method according to claim 1, characterized in that According to the deviation data and the flexible control node, parameter control is performed through an adaptive control module, including: Determining the difference relationship between the stability monitoring data and the laser operating parameters according to the deviation data; activating the parameter analysis model in the adaptive control module, performing laser operating parameter analysis according to the difference relationship between the stability monitoring data and the laser operating parameters, and outputting target laser operating parameters; The target laser operating parameters and the currently set laser parameters are used to perform compensation relationship analysis to generate adaptive compensation parameters, the compensation insertion time node is determined according to the flexible control node, and parameter control is performed through the adaptive control module according to the adaptive compensation parameters and the compensation insertion time node.

6. The method according to claim 5, characterized in that Before performing parameter adaptive control through an adaptive control module according to the deviation data and the flexible control node, the method further includes: Collect monitoring data of handheld laser welders and build digital twin simulation space; Based on the stability monitoring data and laser working parameters, the simulation adjustment step is configured and the simulation parameter set is constructed; Based on the digital twin simulation space, the simulation parameter set is simulated to establish a simulation data set, wherein the simulation data set includes stability monitoring data, laser operating parameters, and welding damage / error range; The constraint conditions of the welding damage / error range are set, and the simulation data set is used to take the welding damage / error range as the dependent variable and the parameter relationship between the stability monitoring data and the laser working parameters as the independent variable for learning to construct the parameter analysis model.

7. The method according to claim 5, characterized in that The method further comprises: Build a handheld user database, including user codes, user operation levels, and historical monitoring data; Matching the user code to perform user operation level matching, performing user stability evaluation based on the historical monitoring data, and determining a user stability coefficient; Configure a compensation coefficient according to the user operation level and the user stability coefficient; Pre-compensating the laser parameters based on a compensation coefficient configured by a user; Setting adaptive constraint values ​​according to the working mode and laser parameters; Based on the pre-compensated laser parameters, adaptive adjustment is performed within the adaptive constraint value according to the adaptive compensation parameters obtained in real time.

8. A flexible control system for a handheld laser welder, characterized in that: The system comprises: A stability analysis module, which is used to connect to the built-in monitoring module, extract monitoring data of the handheld laser welder to perform handheld stability analysis, and obtain stability information, wherein the monitoring data is real-time monitoring feedback through the built-in sensor; A working mode acquisition module, the working mode acquisition module is used to acquire working modes and laser parameters, the working modes include continuous mode, quasi-continuous mode and pulse mode, and the laser parameters include power, frequency and pulse width; A working energy waveform acquisition module, wherein the working energy waveform acquisition module is used to perform working parameter waveform fitting according to the working mode and laser parameters to obtain a working energy waveform; An execution state waveform acquisition module, the execution state waveform acquisition module is used to perform handheld data waveform fitting using the stability information to obtain an execution state waveform; a deviation data determination module, the deviation data determination module being used to perform similarity fitting according to the working energy waveform and the execution state waveform, determine deviation data, and perform flexible control node configuration based on the deviation data; A parameter adaptive control module is used to perform parameter adaptive control through an adaptive control module according to the deviation data and the flexible control node.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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