Gallium nitride welding energy control method and system

Abstract

The invention discloses a gallium nitride welding energy control method and system, and belongs to the technical field of gallium nitride welding. The method comprises the steps that original welding parameters during operation of the gallium nitride laser transmitter are obtained, a landmark area is obtained according to the original welding parameters and calibrated as welding body real-time monitoring data and internal path load data, and a welding period is equally divided to construct welding nodes; a full-process closed-loop system of data acquisition, analysis and decision, feedback execution and data precipitation is constructed through a welding energy control center; real-time monitoring and dynamic regulation provide an instant response basis for energy accurate matching, efficient utilization of energy accumulates a large amount of high-quality welding data for a system, and a historical database is fed back to optimize threshold parameters, such as internal and external temperature thresholds of a welding body, power upper and lower limit coefficients and the like; and a multi-module collaborative intelligent closed-loop management system is constructed, and continuous optimization and upgrading of the welding process are promoted.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of gallium nitride welding, in particular to a gallium nitride welding energy control method and system. BACKGROUND

[0002] As a high-efficiency and precise welding method, the gallium nitride welding technology has significant advantages in the field of new energy battery packaging. Relying on the high energy density characteristics of the gallium nitride laser, the laser beam can be focused on a very small area to realize the rapid melting and firm connection of precise components such as battery shells and cover plates. The gallium nitride welding technology has the characteristics of high welding precision, small heat-affected zone, low workpiece deformation and residual stress, and can meet the stringent requirements of battery production on welding quality. It has become an important choice for high-end battery welding processes and effectively supports the efficient mass production of precise devices such as batteries.

[0003] In the prior art, when the welding energy decreases due to external interference, there is a lack of real-time monitoring and immediate auxiliary heating linkage mechanism, which cannot maintain the stability of the welding energy through dynamic energy supplement, further aggravating the negative impact of energy fluctuation on the welding quality. Due to the lack of precise energy monitoring and control means, there is a mismatch between energy output and actual demand in some welding processes. Excessive energy not only causes waste, but also may cause damage to the microstructure of battery components due to local overheating, increasing the process failure rate.

[0004] In view of the above technical defects, a solution is proposed. SUMMARY

[0005] The purpose of the present application is to provide a gallium nitride welding energy control method and system to solve the problems.

[0006] To achieve the above purpose, the present application provides the following technical scheme: a gallium nitride welding energy control method, comprising the following steps:

[0007] S1, obtaining the welding original parameters during the operation of the gallium nitride laser emitter, obtaining the landmark area calibration as the welding real-time monitoring data and the internal passage load data according to the welding original parameters, and equally dividing the welding period to construct the welding node;

[0008] S2, performing data slicing and threshold analysis processing on the obtained real-time monitoring data to generate the welding body temperature anomaly signal;

[0009] S3, sequentially disassembling and analyzing the components of the obtained welding part dynamic data to generate the welding part visible normal signal about the visible graphical parameters of the welding area, the welding part visible abnormal signal, and the trend anomaly point and color display mark about the step temperature trend of the welding area;

[0010] S4, joint analysis of the results generated by the weld body temperature abnormal signal and the weld part dynamic data component, generate gallium nitride temperature adjustment signal and weld part visible abnormal signal;

[0011] S5, obtain the internal passage load data and the historical power output threshold of the corresponding historical perfect welding sample, jointly construct the floating curve, and generate the unstable curve and the excessive curve according to the trend of the floating curve, which are used to feedback the state of the gallium nitride laser emitter during welding and the direction of adjustment needed.

[0012] Further, the processing process of the welding original data in S1 is as follows:

[0013] Obtain the running time line of the gallium nitride laser emitter, intercept the time period from the initial time to the current time of the group of welding original data, mark the time period as the welding period, and divide the welding period equally to construct a plurality of welding nodes, and correspond one by one according to the welding node and the welding original data acquisition time to construct the node data set.

[0014] A part of the welding original data is marked as the weld real-time monitoring data according to the external collection of the gallium nitride laser emitter body surface, and another part of the welding original data is marked as the internal passage load data according to the internal collection of the gallium nitride laser emitter.

[0015] Further, the processing process of the welding original data in S2 is as follows:

[0016] After obtaining the welding real-time monitoring data, the data slicing processing is performed, the temperature data generated according to the contact of the gallium nitride laser emitter surface is marked as the weld surface layer temperature value, and the temperature data generated according to the non-contact of the gallium nitride laser emitter surface is marked as the near environment temperature value.

[0017] Further, the pre-stored weld internal temperature threshold and weld external temperature threshold are called and analyzed with the weld surface layer temperature value and the near environment temperature value, when the weld surface layer temperature value is less than the weld internal temperature threshold, and the near environment temperature value is less than the weld external temperature threshold, it is judged that the current weld working state is normal, and no signal is generated; when the weld surface layer temperature value is greater than or equal to the weld internal temperature threshold, and the near environment temperature value is greater than or equal to the weld external temperature threshold, it is judged that the current weld working state has temperature abnormality, and the weld temperature abnormal signal is generated.

[0018] Further, the analysis and processing process of the weld part according to the weld state in S3 is as follows:

[0019] The dynamic data of the welding part under the gallium nitride laser emitter is obtained, and the dynamic data of the welding part is composed of the visible pattern parameters of the welding zone and the step temperature trend of the welding zone. The visible pattern parameters of the welding zone are filtered frame by frame according to the corresponding welding nodes. The single-frame sample pattern parameters of the starting node, the center node and the end node in the welding node are selected in turn. The threshold sample pattern parameters summarized by the pre-stored historical perfect welding sample at this stage are called. The threshold sample pattern coefficients are obtained by combining the difference ranges between a plurality of threshold sample pattern parameters. The starting node, the center node and the end node of the visible pattern parameters of the welding zone are analyzed in turn in combination with the corresponding threshold sample pattern parameters. When the starting node, the center node and the end node of the visible pattern parameters of the welding zone are close to the corresponding threshold sample pattern parameters, and the difference of the comparison result is less than the threshold sample pattern coefficient, it is judged that the visible state of the welding process of the gallium nitride laser emitter on the welding part in the welding node meets the standard, and the visible normal signal of the welding part is generated. When the starting node, the center node and the end node of the visible pattern parameters of the welding zone are close to the corresponding threshold sample pattern parameters, and the difference of the comparison result is greater than or equal to the threshold sample pattern coefficient, it is judged that the visible state of the welding process of the gallium nitride laser emitter on the welding part in the welding node does not meet the standard, and the visible abnormal signal of the welding part is generated. The generated visible normal signal or visible abnormal signal of the welding part is brought into the data obtained in the welding node as data summary, and is marked as the visible pattern parameters of the welding zone.

[0020] Further, the step temperature trend of the welding zone is filtered frame by frame according to the corresponding welding nodes. The temperature residual acquisition values of the welding part left by the welding process are obtained according to the starting node, the center node and the end node in the welding node. The center area of the welding point radiates in a circular ring state around the center area. The preset concentric circle interval diameter difference is called. The concentric circle group is constructed. The temperature residual acquisition values in different ranges in the corresponding concentric circle group of the starting node, the center node and the end node in the welding node are marked. The time trend of the welding node is taken as the horizontal axis, and the temperature from low to upper limit is taken as the vertical axis. The temperature residual acquisition values in different area ranges in the corresponding concentric circle group of the starting node, the center node and the end node in the adjacent several welding nodes are connected in sequence to construct a fluctuation curve. The curve threshold value summarized by the pre-stored historical perfect welding sample at this stage is called. The fluctuation curve is analyzed in combination. It is marked as the step temperature trend of the welding zone.

[0021] According to the upper and lower difference median values constructed between the maximum value, the minimum value and the average value of the historical temperature residual acquisition values of the generated curve threshold value, the trend rising limit value and the trend falling limit value are obtained. During the joint analysis of the fluctuation curve and the curve threshold value, when there is a part exceeding the trend rising limit value or the trend falling limit value, it is marked as a trend abnormal point, and the welding node generating the trend abnormal point is marked and displayed in color. Red rising / yellow falling.

[0022] Further, the S4 processes the gallium nitride laser emitter temperature-related data as follows:

[0023] After obtaining the welding body temperature abnormal signal and the welding dynamic data, when the welding dynamic data contains visible normal signal of the welding and the step temperature trend of the welding area without color display, it is judged that the welding of the welding piece by the gallium nitride laser emitter is normal, and the gallium nitride laser emitter body has abnormal temperature dissipation, and a gallium nitride temperature adjustment signal is generated; when the welding dynamic data contains visible abnormal signal of the welding piece and color display of the step temperature trend of the welding area, it is judged that the welding of the welding piece by the gallium nitride laser emitter is abnormal, and according to the visible abnormal signal of the welding piece, the red step temperature trend of the welding area and the yellow step temperature trend of the welding area, a first control signal, a second control signal and a third control signal are generated.

[0024] Further, the S5 analyzes the internal passage load data as follows:

[0025] The real-time output power value and the laser irradiation port size value of the gallium nitride laser emitter are obtained, which are calibrated as internal passage load data. The laser irradiation port size value and the real-time output power value corresponding to the welding node are intercepted, the maximum value and the minimum value of the real-time output power value are screened, the average value of the remaining data is calibrated, the median value between the maximum value and the minimum value and the average value is obtained, which is marked as a power upper limit coefficient and a power lower limit coefficient in turn, the material type, thickness and irradiation port threshold table value of the workpiece in the corresponding welding node are obtained, the historical power output threshold value of the corresponding historical perfect welding sample is obtained, the output estimation range value of the material type and thickness of the workpiece in the corresponding welding node after normalization and decoupling processing on the irradiation port threshold table value, and the historical output threshold value and the output estimation range value are used to construct a reference output power range value.

[0026] Further, the welding node reference timeline is used to construct the X-axis, the Y-axis is constructed from 0 to the preset upper limit of the actual output power value, the floating curves of the real-time output power value, the reference output power range value and the average value are drawn in the dot connection line mode, the part of the floating curve of the real-time output power value far away from the floating curve of the average value and exceeding the power upper limit coefficient or the power lower limit coefficient is calibrated as an unstable curve, and the part of the floating curve of the real-time output power value exceeding the floating curve of the reference output power range value is marked as an excessive curve.

[0027] A gallium nitride welding energy control system, comprising the following steps:

[0028] Welding energy control center: store the parameters generated during the operation of the gallium nitride laser emitter, and prestore the threshold value, construct the welding database, receive the feedback signal and control the gallium nitride laser emitter to operate;

[0029] Comprehensive data joint acquisition module: the data collected during the operation of the gallium nitride laser emitter are preliminarily processed, the welding period and the welding node are constructed according to time, the welding temperature abnormal signal is generated and sent to the welding temperature control risk analysis module;

[0030] Welding temperature control risk analysis module: the acquired real-time monitoring data are continuously and deeply analyzed to generate visible normal signal of the welded part, visible abnormal signal of the welded part, trend abnormal point and color display mark, and are sent to the welding energy control center;

[0031] Welding power state evaluation module: the internal passage load data and the historical power output threshold value are used to construct a floating curve, whether there is an unstable curve or an excessive curve in different sections is determined according to the trend of the floating curve, and the state of the gallium nitride laser emitter during welding and the direction needing to be adjusted are fed back.

[0032] The beneficial effects of the present application are:

[0033] 1. The present application can accurately identify temperature abnormalities, pattern deviations and temperature trend fluctuations in the welding process by real-time capturing of parameters such as the surface layer temperature of the welded body and the near environment temperature through the comprehensive data joint acquisition module, and deeply disassembling the dynamic data of the welded part through the welding temperature control risk analysis module.

[0034] 2. The present application realizes dynamic matching of energy output and welded part demand by comparing real-time output power with power threshold value of historical perfect welding samples, and marking unstable curve and excessive curve through floating curve analysis. BRIEF DESCRIPTION OF DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description only show some of the embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0036] Figure 1 The method flowchart of the present application is shown in the figure.

[0037] Figure 2 The system flowchart of the present application is shown in the figure. DETAILED DESCRIPTION

[0038] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0039] Embodiment one: please refer to Figure 1 - Figure 2 The present embodiment is a gallium nitride welding energy control method and system, including the following steps.

[0040] S1, the welding energy control center stores the parameters generated during the operation of the gallium nitride laser emitter and the pre-stored threshold value, constructs a welding database, obtains the welding original parameters during the operation of the gallium nitride laser emitter, obtains the landmark area calibration as the welding real-time monitoring data and the internal passage load data according to the welding original parameters, equally divides the welding period to construct the welding nodes, simultaneously receives the feedback signal and controls the gallium nitride laser emitter to perform operation control; the processing process of the welding original data in S1 is as follows.

[0041] S11, the operation time line of the gallium nitride laser emitter is obtained, the time period from the initial time to the current time of the group of welding original data is intercepted, the time period is marked as the welding period, the welding period is equally divided to construct a plurality of groups of welding nodes, and the node data set is constructed according to the one-to-one correspondence between the welding nodes and the welding original data acquisition time.

[0042] S12, a part of the welding original data is calibrated as the welding real-time monitoring data according to the external collection of the gallium nitride laser emitter body surface, and another part of the welding original data is calibrated as the internal passage load data according to the internal collection of the gallium nitride laser emitter.

[0043] S2, the comprehensive data joint acquisition module processes the real-time monitoring data obtained during the operation of the gallium nitride laser emitter by data slicing and threshold analysis, generates a welding body temperature anomaly signal, and sends the signal to the welding temperature control risk analysis module; the processing process of S2 on the obtained welding body real-time monitoring data is as follows:

[0044] S21, the welding body real-time monitoring data is processed by data slicing, the temperature data generated by the contact of the gallium nitride laser emitter body surface is marked as the welding body surface layer temperature value, and the temperature data generated by the non-contact of the gallium nitride laser emitter body surface is marked as the near environment temperature value; it should be noted that the welding body surface layer temperature value is collected by a thermocouple sensor in contact with the gallium nitride laser emitter body surface, which is high-temperature resistant and suitable for materials such as titanium alloy;

[0045] S22, the pre-stored welding body internal temperature threshold and welding body external temperature threshold are analyzed and processed with the welding body surface layer temperature value and the near environment temperature value; it should be noted that the near environment temperature value is collected by a non-contact infrared thermometer installed in the 30-50cm area around the gallium nitride laser emitter, which varies according to the actual environment, with an accuracy of ±0.5℃;

[0046] S23, when the welding body surface layer temperature value is less than the welding body internal temperature threshold, and the near environment temperature value is less than the welding body external temperature threshold, it is judged that the current welding body operation state is normal, and no signal is generated;

[0047] S24, when the welding body surface layer temperature value is greater than or equal to the welding body internal temperature threshold, and the near environment temperature value is greater than or equal to the welding body external temperature threshold, it is judged that the current welding body operation exists temperature anomaly, and a welding body temperature anomaly signal is generated; after the welding energy control center receives the welding body temperature anomaly signal, the relevant data for generating the welding body temperature anomaly signal is retrieved for secondary analysis;

[0048] S25, if the welding body temperature anomaly signal is slightly higher than the welding body internal temperature threshold, which does not reach the shutdown threshold, the welding energy control center triggers the built-in heat dissipation module of the gallium nitride laser emitter, such as a miniature water cooling circulation system, to enhance the heat dissipation efficiency and reduce the surface temperature;

[0049] S26, if the welding body temperature anomaly signal is accompanied by a near environment temperature value far exceeding the welding body external temperature threshold, the welding energy control center simultaneously reduces the output power of the gallium nitride laser emitter by 10%-20%, dynamically adjusts according to the temperature exceeding amplitude, and reduces the heat output;

[0050] S27, if the temperature continues to rise to the preset shutdown threshold, the shutdown threshold is set according to the historical data and the protection upper threshold set by the gallium nitride laser emitter manufacturer, and the pre-stored gallium nitride laser emitter is immediately sent to the shutdown instruction by the welding energy control center, and the audible and light alarm is triggered; after manual inspection and adjustment, it is restarted.

[0051] S3, the welding temperature control risk analysis module sequentially disassembles and analyzes the obtained components of the welding part dynamic data, generates welding part visible normal signals about visible graphical parameters of the welding zone, welding part visible abnormal signals, and trend abnormal points and color display markers about the temperature trend of the welding zone, and sends them to the welding energy control center; S3 analyzes and processes the welding part according to the welding body state as follows;

[0052] S31, the welding part dynamic data below the gallium nitride laser emitter is obtained, the welding part dynamic data is composed of visible graphical parameters of the welding zone and temperature trend of the welding zone, the visible graphical parameters of the welding zone are selected frame by frame according to the corresponding welding nodes, the single-frame sample parameters of the starting node, the center node and the end node in the welding node are sequentially selected, the threshold sample parameter summarized by the pre-stored historical perfect welding sample at this stage is called, the threshold sample coefficient is obtained by combining the difference range between a plurality of threshold sample parameters, the starting node, the center node and the end node of the visible graphical parameters of the welding zone are sequentially analyzed in combination with the corresponding threshold sample parameters, it should be noted that the visible graphical parameters of the welding zone are collected frame by frame by a high-speed industrial camera, the frame rate is ≥1000fps, the sample parameters are extracted by cooperating with the image recognition algorithm, the temperature residual value is collected by an infrared thermal imager, the resolution is ≥640×512, and a fluctuation curve is generated by thermal imaging analysis;

[0053] S32, when the starting node, the center node and the end node of the visible graphical parameters of the welding zone are close to the corresponding threshold sample parameters, and the difference between the comparison results is less than the threshold sample coefficient, it is judged that the visible state of the gallium nitride laser emitter to the welding part in the welding node meets the standard, the welding part visible normal signal is generated and fed back to the welding energy control center, and no action or instruction is triggered;

[0054] S33, when the starting node, the center node and the end node of the visible graphical parameters of the welding zone are close to the corresponding threshold sample parameters, and the difference between the comparison results is greater than or equal to the threshold sample coefficient, it is judged that the visible state of the gallium nitride laser emitter to the welding part in the welding node does not meet the standard, the welding part visible abnormal signal is generated, and the generated welding part visible normal signal or welding part visible abnormal signal is brought into the data obtained in the welding node as data summary, and is marked as the visible graphical parameters of the welding zone;

[0055] S34, after the welding visible abnormal signal is fed back to the welding energy control center, the welding energy control center drives the beam focusing adjustment component of the gallium nitride laser emitter, such as an electric focusing mirror, and specifically adjusts the position of the laser beam focus according to the actual gallium nitride laser emitter configuration to ensure alignment with the welding zone; at the same time, the sample parameters of the corresponding historical perfect sample are called, the laser irradiation time is fine-tuned in the range of ±0.1s, which is used for optimizing the consistency of the pattern;

[0056] S35, the welding zone step temperature trend is obtained according to the temperature residual values of the starting node, the center node and the terminal node in the corresponding welding node, which are obtained by frame-by-frame screening in the welding node, and the temperature residual values in different ranges of the corresponding concentric circle group of the starting node, the center node and the terminal node are labeled, and the temperature residual values in different regions of the corresponding concentric circle group of the starting node, the center node and the terminal node in the welding node are sequentially connected to form a fluctuation curve, and the welding zone step temperature trend is obtained by joint analysis of the fluctuation curve and the pre-stored curve threshold value of the historical perfect welding sample; and

[0057] S36, according to the upper and lower difference values constructed between the maximum value, the minimum value and the average value of the historical temperature residual values of the generated curve threshold value, the trend rising limit value and the trend falling limit value are obtained, and during the joint analysis of the fluctuation curve and the curve threshold value, when there is a part exceeding the trend rising limit value or the trend falling limit value, it is marked as a trend abnormal point, and the welding node generating the trend abnormal point is marked and displayed in color, red rising / yellow falling;

[0058] S37, when the red trend abnormal point is detected and fed back to the welding energy control center, the temperature exceeds the trend rising limit value, the welding energy control center starts the reverse regulation of the temperature heating ring, the temperature heating ring is a component equipped on the gallium nitride laser emitter, which is specifically configured according to the group of gallium nitride laser emitters, and is only used to regulate the temperature heating function, to reduce the heating power or suspend heating, and at the same time increase the welding zone cooling airflow, for example, through a micro air pump, to inhibit the excessive rise of temperature;

[0059] S38, after detecting the yellow trend abnormal point and feeding back to the welding energy control center, the temperature is lower than the trend falling limit value, the welding energy control center enhances the output power of the temperature heating ring, which is increased in steps, with an increase of 5% at each step, to supplement the welding energy and stabilize the welding zone temperature gradient.

[0060] S4, the results generated by the welding body temperature anomaly signal and the welding part dynamic data component are jointly analyzed to generate a gallium nitride temperature adjustment signal and a welding part visible abnormal signal; the process of S4 for summarizing and analyzing the temperature related data of the gallium nitride laser emitter is as follows;

[0061] S41, after obtaining the welding body temperature abnormal signal and the welding part dynamic data, when the welding part dynamic data contains the visible normal signal of the welding part and the step temperature trend of the colorless welding area, it is judged that the welding part is normally treated by the gallium nitride laser emitter, and the gallium nitride laser emitter body has abnormal temperature heat dissipation. A gallium nitride temperature adjustment signal is generated and fed back to the welding energy control center. The welding energy control center starts the standby heat dissipation channel, such as an additional fan group, and adjusts the working current of the gallium nitride laser emitter to stabilize in a ±5% fluctuation range, balancing heat generation and output efficiency;

[0062] S42, when the welding dynamic data contains the visible abnormal signal of the welding part and the colorized step temperature trend of the welding area, it is judged that the welding part is abnormally treated by the gallium nitride laser emitter. According to the visible abnormal signal of the welding part contained in the welding dynamic data, the red step temperature trend of the welding area / yellow step temperature trend of the welding area, a first control signal, a second control signal and a third control signal are generated correspondingly;

[0063] S43, when the welding energy control center receives the first control signal, the welding energy control center slightly adjusts the laser output power in the range of +3% to +5%, prolongs the welding node duration by 0.2s, and supplements the energy to correct the temperature drop trend when the visible abnormal signal of the welding part and the yellow trend point are slight abnormal;

[0064] S44, when the welding energy control center receives the second control signal, the welding energy control center starts double closed loop control, synchronously reduces the laser power by-5% and enhances the cooling air flow when the visible abnormal signal of the welding part and the red trend point are moderate abnormal, and records the node parameters to the database for subsequent optimization adjustment;

[0065] S45, when the welding energy control center receives the third control signal, the welding energy control center immediately stops, locks the gallium nitride laser emitter and generates a detailed abnormal report containing node time, temperature curve, graphical parameters when the visible abnormal signal of the welding part and the significant red / yellow trend point are serious abnormal, and restarts after manually calibrating the temperature heating ring and beam focusing assembly that can be set on the gallium nitride laser emitter.

[0066] Embodiment two: S5, the welding power state evaluation module obtains the internal passage load data and the historical power output threshold value of the corresponding historical perfect welding sample, jointly constructs the floating curve, and according to the trend of the floating curve, the unstable curve and the excessive curve are generated to mark the feedback of the state of the gallium nitride laser emitter during welding and the direction needing to be adjusted; the analysis process of S5 to the internal passage load data is as follows: it needs to be explained that the real-time output power value is collected by a laser power meter, the range is 0-500W, the accuracy is ±1%, it is installed in the light path of the irradiation port of the gallium nitride laser emitter, the size value of the laser irradiation port is collected by a laser diameter measuring instrument, which is non-contact and has a resolution of 0.001mm, which can monitor the change of the spot diameter of the irradiation port in real time, and is not limited to this, and the specific configuration is determined according to the actual gallium nitride laser emitter;

[0067] S51, the real-time output power value and the laser irradiation port size value of the gallium nitride laser emitter are obtained, which are marked as internal passage load data, the internal laser irradiation port size value and the real-time output power value corresponding to the welding node are intercepted, the maximum value and the minimum value in the real-time output power value are screened, the average value in the remaining data is marked, the median value between the maximum value and the minimum value and the average value is obtained, and they are marked as the power upper limit coefficient and the power lower limit coefficient in turn;

[0068] S52, the material type, thickness and irradiation port threshold table value of the workpiece in the corresponding welding node are obtained, the historical power output threshold value of the corresponding historical perfect welding sample is obtained, the output estimation range value of the material type and thickness of the workpiece in the corresponding welding node after the normalization de-dimensioning processing on the irradiation port threshold table value is obtained, and the reference output power range value is constructed by the historical output threshold value and the output estimation range value;

[0069] S53, the welding node reference timeline is constructed as the X-axis, the actual output power value is constructed as the Y-axis from 0 to the preset upper limit, the floating curve of the real-time output power value, the reference output power range value and the average value is drawn in the dot connecting line mode, the part of the floating curve of the real-time output power value far away from the average value and exceeding the power upper limit coefficient or the power lower limit coefficient is marked as the unstable curve, and the part of the floating curve of the real-time output power value exceeding the floating curve of the reference output power range value is marked as the excessive curve;

[0070] S54, when the welding energy control center receives the feedback of the unstable curve, the welding energy control center calls the power stabilization module of the gallium nitride laser emitter, for example, including a PID regulator, to correct the output power in real time, when the curve exceeds the power upper limit coefficient, the driving voltage is reduced; when it is lower than the power lower limit coefficient, the driving voltage is increased, so that the power fluctuation is controlled within ±2%;

[0071] S55, when the welding energy control center receives the excess curve, the welding energy control center compares the reference output power range value, and can compress the laser emission pulse width by pulse width modulation (PWM) technology, shorten by 10% at each level, until the actual output power falls within the reference range; if the excess continues, trigger power warning and reduce the irradiation port size, which can be controlled by an adjustable diaphragm, which is an adjustable device installed in the gallium nitride laser emitter irradiation light path, and its core function is to control the effective size of the laser irradiation port by changing its aperture size, thereby adjusting the cross-sectional area of the output laser beam.

[0072] In combination with Embodiment One and Embodiment Two, the core advantage of the present application is not only the separate effects of real-time regulation and energy optimization, but also the construction of a full-process closed-loop system of data acquisition-analysis decision-execution feedback-data sedimentation by the welding energy control center; real-time monitoring and dynamic regulation provide an immediate response basis for energy precise matching, while efficient use of energy accumulates a large amount of high-quality welding data for the system, which in turn optimizes the threshold parameters of the historical database, such as the internal and external temperature thresholds of the weld body, the upper and lower limit coefficients of power, etc.; the intelligent mechanism of multi-module cooperation enables the system to continuously adapt to the welding needs of different materials and different thickness workpieces, continuously improves the process adaptability and intelligent level, constructs a multi-module cooperative intelligent closed-loop management system, and promotes the continuous optimization and upgrading of the welding process.

[0073] The above is merely an example and description of the structure of the present application, and those skilled in the art can make various modifications or supplements or use similar ways to replace the described specific embodiments, as long as they do not deviate from the structure of the application or exceed the scope defined by the present claims, which shall be within the protection scope of the present application.

[0074] In the description of the present specification, the description of the terms "one embodiment", "example", "specific example" and the like means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner, and the relevant fittings include couplings, lead screws, gears, gaskets and other commonly used mechanical connecting parts in the field, and are not limited thereto, and the connecting mode is replaced and used according to the actual use.

[0075] The preferred embodiments of the application disclosed above are only to facilitate the elucidation of the application. The preferred embodiments do not describe all the details of the application and limit the application to the specific embodiments. Obviously, many modifications and variations can be made in light of the teachings above. The description is chosen and described in order to provide the best illustration of the application and its practical application to those skilled in the art and to enable those skilled in the art to best utilize the application. The application is limited only by the claims and their full scope and equivalents.

Claims

1. A method for controlling the welding energy of gallium nitride, characterized by, Comprise the following steps: S1, obtain the welding original parameter during the operation of the gallium nitride laser emitter, and obtain the landmark area calibration as the weld real-time monitoring data and the internal passage load data according to the welding original parameter, divide the welding period to construct the welding node; S2, the real-time monitoring data obtained is subjected to data slicing and threshold analysis processing to generate the weld temperature anomaly signal; S3, the components of the welding part dynamic data obtained are sequentially disassembled and analyzed to generate the welding part visible normal signal and the welding part visible abnormal signal about the visible graphical parameters of the welding area, and the trend abnormal point and color display mark about the step temperature trend of the welding area; S4, the results generated by the weld temperature anomaly signal and the welding part dynamic data components are jointly analyzed to generate the gallium nitride temperature adjustment signal and the welding part visible abnormal signal; S5, the internal passage load data and the historical power output threshold of the corresponding historical perfect welding sample are obtained to jointly construct the floating curve, and the unstable curve and the excessive curve are generated according to the trend calibration of the floating curve, which are used to feedback the state of the gallium nitride laser emitter during welding and the direction needing adjustment.

2. The gallium nitride welding energy control method according to claim 1, characterized in that, The processing process of the welding original data in S1 is as follows: The operation time line of the gallium nitride laser emitter is obtained, the time period from the initial time to the current time of the group of welding original data is intercepted, the time period is marked as the welding period, the welding period is divided to construct a plurality of groups of welding nodes, and the node data set is constructed according to the one-to-one correspondence between the welding nodes and the welding original data acquisition time; A part of the welding original data is calibrated as the weld real-time monitoring data according to the external collection of the gallium nitride laser emitter body surface, and another part of the welding original data is calibrated as the internal passage load data according to the internal collection of the gallium nitride laser emitter.

3. The gallium nitride welding energy control method according to claim 1, characterized in that, The processing process of the welding original data in S1 is as follows: The welding original data is subjected to data slicing processing, the temperature data generated according to the contact of the gallium nitride laser emitter body surface is marked as the weld surface layer temperature value, and the temperature data generated according to the non-contact of the gallium nitride laser emitter body surface is marked as the near environment temperature value.

4. The method of claim 3, wherein the soldering energy is controlled by the following equation: ###0001### where, P is the soldering energy, t is the time, T is the temperature, and k is a constant. The pre-stored weld internal temperature threshold and weld external temperature threshold are called and analyzed with the weld surface layer temperature value and the near environment temperature value, when the weld surface layer temperature value is less than the weld internal temperature threshold, and the near environment temperature value is less than the weld external temperature threshold, it is judged that the current weld operation state is normal, and no signal is generated; when the weld surface layer temperature value is greater than or equal to the weld internal temperature threshold, and the near environment temperature value is greater than or equal to the weld external temperature threshold, it is judged that the current weld operation has temperature anomaly, and the weld temperature anomaly signal is generated.

5. The method of claim 1, wherein the soldering energy is controlled by the amount of the nitrogen gas supplied to the soldering tool. The analysis processing process of the welding part according to the weld state in S3 is as follows: The dynamic data of the welding part under the gallium nitride laser emitter is obtained, and the dynamic data of the welding part is composed of the visible pattern parameters of the welding area and the step temperature trend of the welding area. The visible pattern parameters of the welding area are filtered frame by frame according to the corresponding welding nodes, and the single-frame sample pattern parameters of the starting node, the center node and the end node in the welding node are selected in turn. The threshold sample pattern parameters summarized by the pre-stored historical perfect welding sample at this stage are called, and the difference range between a plurality of threshold sample pattern parameters is obtained. The threshold sample pattern coefficient is obtained by combining the starting node, the center node and the end node of the visible pattern parameters of the welding area with the corresponding threshold sample pattern parameters. When the starting node, the center node and the end node of the visible pattern parameters of the welding area are close to the corresponding threshold sample pattern parameters, and the difference between the comparison results is less than the threshold sample pattern coefficient, it is judged that the visible state of the gallium nitride laser emitter to the welding part in the welding node meets the standard, and the visible normal signal of the welding part is generated. When the starting node, the center node and the end node of the visible pattern parameters of the welding area are close to the corresponding threshold sample pattern parameters, and the difference between the comparison results is greater than or equal to the threshold sample pattern coefficient, it is judged that the visible state of the gallium nitride laser emitter to the welding part in the welding node does not meet the standard, and the visible abnormal signal of the welding part is generated. The generated visible normal signal or visible abnormal signal of the welding part is brought into the data obtained in the welding node as data summary, and is marked as the visible pattern parameters of the welding area.

6. The method of claim 5, wherein the soldering energy is controlled by the amount of the nitrogen gas supplied to the soldering tool. The step temperature trend of the welding area is filtered frame by frame according to the corresponding welding nodes, and the temperature residual acquisition value of the welding part left by the welding process is obtained according to the starting node, the center node and the end node in the welding node. The temperature residual acquisition value is radiated in a circular ring state from the center area of the welding point to the surrounding, the preset concentric circle interval diameter difference is called, the concentric circle group is constructed, and the temperature residual acquisition value in different ranges in the corresponding concentric circle group of the starting node, the center node and the end node in the welding node is marked. Taking the time trend of the welding node as the horizontal axis and the temperature from low to upper limit as the vertical axis, the temperature residual acquisition values in different area ranges in the corresponding concentric circle group of the starting node, the center node and the end node in the adjacent several welding nodes are sequentially connected to construct a fluctuation curve. The curve threshold value summarized by the pre-stored historical perfect welding sample at this stage is called, and is combined with the fluctuation curve for joint analysis, and is marked as the step temperature trend of the welding area. According to the upper and lower difference median value constructed between the maximum value, the minimum value and the average value of the historical temperature residual acquisition value of the generated curve threshold value, the trend rising limit value and the trend falling limit value are obtained. During the joint analysis of the fluctuation curve and the curve threshold value, when there is a part exceeding the trend rising limit value or the trend falling limit value, it is marked as a trend abnormal point, and the welding node generating the trend abnormal point is marked and displayed in color, and the red rising / yellow falling.

7. The method of claim 1, wherein the soldering energy is controlled by a pulse width modulation (PWM) signal. The S4 processes the temperature-related data of the gallium nitride laser emitter as follows: After the abnormal temperature signal of the welding body and the dynamic data of the welding part are obtained, when the dynamic data of the welding part contains the visible normal signal of the welding part and the step temperature trend of the welding area without color display, it is judged that the welding part is normally treated by the gallium nitride laser emitter, and the gallium nitride laser emitter body has abnormal temperature dissipation, and a gallium nitride temperature adjustment signal is generated; when the dynamic data of the welding contains the visible abnormal signal of the welding part, and the step temperature trend of the welding area with color display, it is judged that the welding part treated by the gallium nitride laser emitter has abnormality, and according to the visible abnormal signal of the welding part, the red step temperature trend of the welding area / the yellow step temperature trend of the welding area contained in the dynamic data of the welding, a first control signal, a second control signal and a third control signal are generated correspondingly.

8. The method of claim 7, wherein the soldering energy is controlled by the amount of the nitrogen gas supplied to the soldering tool. The analysis process of the S5 on the internal passage load data is as follows: The real-time output power value and the laser irradiation port size value of the gallium nitride laser emitter are obtained, which are calibrated as internal passage load data. The laser irradiation port size value and the real-time output power value corresponding to the welding node are intercepted, the maximum value and the minimum value in the real-time output power value are screened, the average value in the remaining data is calibrated, the median value between the maximum value and the minimum value and the average value is obtained, which is marked as the power upper limit coefficient and the power lower limit coefficient in turn, the material type, thickness and irradiation port threshold table value of the workpiece in the corresponding welding node are obtained, the historical power output threshold value of the corresponding historical perfect welding sample is obtained, the output estimation range value of the material type and thickness of the workpiece in the corresponding welding node after normalization and decoupling processing on the irradiation port threshold table value is obtained, and the reference output power range value is constructed by the historical output threshold value and the output estimation range value.

9. The method of claim 8, wherein the soldering energy is controlled by the amount of the nitrogen gas supplied to the soldering tool. The X-axis is constructed according to the welding node reference timeline, the Y-axis is constructed from 0 to the preset upper limit according to the unit of the actual output power value, the floating curves of the real-time output power value, the reference output power range value and the average value are drawn in the dot connecting line mode, the part of the floating curve of the real-time output power value far away from the floating curve of the average value and exceeding the power upper limit coefficient or the power lower limit coefficient is calibrated as the unstable curve, and the part of the floating curve of the real-time output power value exceeding the floating curve of the reference output power range value is marked as the excessive curve.

10. A gallium nitride welding energy control system for use in a gallium nitride welding energy control method according to any one of claims 1 to 9, characterized by, The following steps are included: The welding energy control center: stores the parameters generated during the operation of the gallium nitride laser emitter, and pre-stores the threshold value, constructs the welding database, receives the feedback signal and controls the operation of the gallium nitride laser emitter; The comprehensive data joint acquisition module: preliminarily processes the data collected during the operation of the gallium nitride laser emitter, constructs the welding cycle and the welding node according to time, generates the welding body temperature abnormal signal and sends it to the welding temperature control risk analysis module; The welding temperature control risk analysis module: continuously and deeply analyzes the obtained real-time monitoring data, generates the visible normal signal of the welding part, the visible abnormal signal of the welding part, the trend abnormal point and the color display mark, and sends them to the welding energy control center; The welding temperature control risk analysis module: continuously and deeply analyzes the obtained real-time monitoring data, generates the visible normal signal of the welding part, the visible abnormal signal of the welding part, the trend abnormal point and the color display mark, and sends them to the welding energy control center; The welding power state evaluation module: obtains the inner passage load data and the historical power output threshold to construct a floating curve, and marks whether there is an unstable curve or an excessive curve in different sections according to the trend of the floating curve, which is used for feeding back the state of the gallium nitride laser emitter during welding and the direction needing to be adjusted.

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