Motor welding spot control method and system

Abstract

The present invention discloses a motor welding spot control method and system, which specifically relates to the field of motor welding spots, including a data batch division step, a data collection step, a data analysis step, a data comprehensive evaluation step, and a real-time feedback monitoring step. The data collection step includes a welding process data collection unit and a welding spot quality data collection unit, which are used to collect target data in real time. The welding process data collection unit is used to collect welding energy data, welding pressure data, and welding temperature data; the welding spot quality data collection unit is used to collect welding spot geometry data, welding spot internal structure data, and welding spot electrical performance data; the data analysis step includes a welding process data analysis unit and a welding spot quality data analysis unit; the present invention effectively improves the accuracy and practicality of welding spot data by dividing the data of motor welding spots into batches.

Description

Technical Field

[0001] The present invention relates to the technical field of motor welding spots, and more specifically, to a motor welding spot control method and system. Background Art

[0002] With the continuous development of industrial production and the increasing level of automation, motors are increasingly used in various fields, and the requirements for their quality and performance are becoming higher and higher. The quality control technology of motor welding solder joints has brought new challenges and opportunities to motor production due to its key impact on the overall performance of the motor. Accurate solder joint control can ensure the electrical connection stability and mechanical strength of the motor, and meet the needs of high-quality motor production.

[0003] The existing motor welding solder joint control method mainly includes solder joint data acquisition module, data transmission module, solder joint quality analysis module and control feedback module. Through the solder joint data acquisition module, high-precision sensors are installed at each key solder joint position of the motor welding production line to collect data such as solder joint temperature, pressure, welding time and solder consumption, so as to realize real-time monitoring of the welding process; through the data transmission module, the collected data is safely transmitted using encryption algorithms to ensure the accuracy and integrity of the data during the transmission process; through the solder joint quality analysis module, the transmitted data is decrypted and analyzed to dig out possible solder joint defect information and quality abnormalities, providing data support for the stability of motor welding quality; through the control feedback module, technicians can intuitively understand the status of the welding process, realize remote adjustment and control of welding parameters, and timely correct the operating parameters of welding equipment to improve the reliability and stability of motor solder joint quality.

[0004] However, this method still has some shortcomings in practical applications. For example, in terms of data collection, due to the accuracy and sensitivity limitations of the sensor, there may be deviations in the data collection of some solder joints, resulting in incomplete data collection, which has an adverse effect on the subsequent solder joint quality analysis; in terms of solder joint quality analysis, facing massive welding data and complex quality assessment algorithms, it is easy to cause the analysis results to be inaccurate and incomplete, which may lead to the inability to timely discover potential quality problems in solder joints, reducing the ability to control motor production quality.

[0005] Therefore, there is an urgent need to provide a motor welding spot control method and system to solve the problems of insufficient data collection and inaccurate analysis results of the existing motor welding spot control system, so as to further improve the quality and reliability of motor production. Summary of the invention

[0006] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a motor welding spot control method and system, which solves the problems raised in the above-mentioned background technology through the following scheme.

[0007] To achieve the above object, the present invention provides the following technical solution: a motor welding spot control method, comprising:

[0008] S1, data batch division step: used to determine the data to be collected as target data, divide the target data into different batches in an equal time division manner, and mark them as 1, 2, ..., n in sequence;

[0009] S2, data acquisition step: including a welding process data acquisition unit and a solder joint quality data acquisition unit, which are used to acquire target data in real time and transmit the acquired data to the data analysis step. The welding process data acquisition unit is used to acquire welding energy data, welding pressure data and welding temperature data; the solder joint quality data acquisition unit is used to acquire solder joint geometry data, solder joint internal structure data and solder joint electrical performance data;

[0010] S3, data analysis step: including a welding process data analysis unit and a solder joint quality data analysis unit, which are used to collect target data in real time and transmit the collected data to the data comprehensive evaluation step. The welding process data analysis unit includes a welding energy data analysis node, a welding pressure data analysis node, and a welding temperature data analysis node; the solder joint quality data analysis unit includes a solder joint geometry data analysis node, a solder joint internal structure data analysis node, and a solder joint electrical performance data analysis node;

[0011] S4, data comprehensive evaluation step: including a motor welding spot data analysis unit, used for comprehensively analyzing the analysis results transmitted in the data analysis step, and transmitting the analysis results to the real-time feedback monitoring step;

[0012] S5, real-time feedback monitoring step: used to establish a preset value of the motor welding spot comprehensive evaluation index, judge the motor welding spot comprehensive evaluation index value according to the preset value of the motor welding spot comprehensive evaluation index, and send a corresponding signal according to the judgment result.

[0013] Preferably, the welding energy data includes the welding current rising slope Ws, the welding current pulse flat top time fluctuation value Wf and the inverse of the welding energy pulse trailing edge falling time Ec; the welding pressure data includes the welding pressure loading acceleration Pa, the welding process pressure center offset Op and the welding pressure unloading vibration frequency Pf; the welding temperature data includes the welding preheating zone temperature gradient Wt, the welding molten pool center and edge temperature difference Ed and the welding cooling phase change temperature interval residence time Cp; the weld spot geometry data includes the weld spot three-dimensional shape fractal dimension Ds, the weld spot contour least squares ellipse fitting major axis to minor axis ratio Mr and the weld spot surface micro-convex average spacing Js; the weld spot internal structure data includes the weld spot internal dislocation density Sd and the interface energy Se of different crystal phases inside the weld spot; the weld spot electrical performance data includes the high-frequency skin depth change rate Rf, the temperature and thermoelectric potential change Tp and the weld spot and ground loop parasitic inductance Gp.

[0014] Preferably, the welding energy data analysis node is used to establish a welding energy data calculation model, and the welding energy data transmitted in the data acquisition step is imported into the welding energy data calculation model to obtain a welding energy quality coefficient value. The welding energy data calculation model is specifically expressed as:

[0015] ,

[0016] in, Indicates the welding energy quality coefficient value calculated for the i-th time, Ws i Indicates the rising slope of the welding current collected for the i-th time, Wf i Indicates the fluctuation value of the flat-top time of the welding current pulse collected for the i-th time, Ec i represents the inverse of the falling time of the trailing edge of the welding energy pulse collected for the i-th time, σ represents the standard deviation of the inverse of the falling time of the trailing edge of the welding energy pulse, and μ represents the mean of the inverse of the falling time of the trailing edge of the welding energy pulse.

[0017] Preferably, the welding pressure data analysis node is used to establish a welding pressure data calculation model, and the welding pressure data transmitted in the data acquisition step is imported into the welding pressure data calculation model to obtain the welding pressure stability coefficient value. The welding pressure data calculation model is specifically expressed as:

[0018] ,

[0019] in, Indicates the welding pressure stability coefficient value calculated for the i-th time, Pa i Op represents the welding pressure loading acceleration collected for the i-th time, i Pf represents the pressure center offset of the welding process collected for the i-th time. iRepresents the welding pressure unloading vibration frequency collected for the i-th time.

[0020] Preferably, the welding temperature data analysis node is used to establish a welding temperature data calculation model, and the welding temperature data transmitted in the data acquisition step is imported into the welding temperature data calculation model to obtain a welding temperature rationality coefficient value. The welding temperature data calculation model is specifically expressed as:

[0021] ,

[0022] in, Indicates the reasonableness coefficient of the welding temperature calculated for the i-th time, Wt i represents the temperature gradient of the welding preheating zone collected for the i-th time, Ed i represents the temperature difference between the center and edge of the welding pool collected for the i-th time, Cp i It represents the residence time in the welding cooling phase change temperature interval collected for the i-th time.

[0023] Preferably, the solder joint geometry data analysis node is used to establish a solder joint geometry data calculation model, and the solder joint geometry data transmitted in the data acquisition step is imported into the solder joint geometry data calculation model to obtain the solder joint geometry quality characteristic value, and the solder joint geometry data calculation model is specifically expressed as:

[0024] ,

[0025] in, Denotes the geometric quality characteristic value of the solder joint calculated for the i-th time, Ds i represents the fractal dimension of the three-dimensional shape of the solder joint collected for the i-th time, Mr i It represents the ratio of the major axis to the minor axis of the least squares ellipse fitting of the solder joint contour collected for the i-th time, Represents the ratio of the major axis to the minor axis of the least squares ellipse fitting of the standard solder joint contour, Js i It represents the average spacing of micro-convex bodies on the solder joint surface collected for the i-th time.

[0026] Preferably, the solder joint internal structure data analysis node is used to establish a solder joint internal structure data calculation model, and the solder joint internal structure data transmitted in the data acquisition step is imported into the solder joint internal structure data calculation model to obtain the solder joint internal microstructure excellence coefficient value, and the solder joint internal structure data calculation model is specifically expressed as:

[0027] ,

[0028] in, represents the excellent coefficient value of the internal microstructure of the solder joint calculated for the i-th time, Sd i represents the internal dislocation density of the solder joint collected for the i-th time, Sei Represents the interfacial energy of different crystal phases inside the solder joint collected for the i-th time.

[0029] Preferably, the solder joint electrical performance data analysis node is used to establish a solder joint electrical performance data calculation model, and the solder joint electrical performance data transmitted in the data acquisition step is imported into the solder joint electrical performance data calculation model to obtain a solder joint electrical performance excellence coefficient value, and the solder joint electrical performance data calculation model is specifically expressed as:

[0030] ,

[0031] in, Indicates the excellent coefficient value of the electrical performance of the solder joint calculated for the i-th time, Rf i represents the rate of change of high-frequency skin depth collected for the i-th time, Tp i Gp represents the temperature and thermoelectric potential changes collected for the i-th time. i It represents the parasitic inductance between the solder joint and the ground loop collected for the i-th time.

[0032] Preferably, the motor welding spot data analysis unit is used to establish a motor welding spot data calculation model, and the welding energy quality coefficient value, welding pressure stability coefficient value, welding temperature rationality coefficient value, welding spot geometry quality characteristic value, welding spot internal microstructure excellence coefficient value and welding spot electrical performance excellence coefficient value transmitted by the data analysis step are introduced into the motor welding spot data calculation model to obtain the motor welding spot comprehensive evaluation index value, and the motor welding spot data calculation model is specifically expressed as:

[0033] ,

[0034] Where A represents the calculated comprehensive evaluation index value of the motor welding spot, , , represents the welding energy quality coefficient value calculated for the i-th time, represents the welding pressure stability coefficient value calculated for the i-th time, represents the reasonableness coefficient of the welding temperature calculated for the i-th time, represents the geometric quality characteristic value of the solder joint calculated for the i-th time, represents the minimum value of the calculated solder joint geometry quality characteristic, represents the maximum value of the calculated solder joint geometry quality characteristic, represents the value of the excellent coefficient of the internal microstructure of the solder joint calculated for the i-th time, Indicates the minimum value of the calculated solder joint internal microstructure excellence coefficient, Indicates the maximum value of the calculated internal microstructure excellence coefficient of the solder joint. represents the excellent coefficient value of the electrical performance of the solder joint calculated for the i-th time, Indicates the minimum value of the calculated solder joint electrical performance coefficient. It indicates the maximum value of the calculated solder joint electrical performance coefficient, i indicates starting from the i-th number, and n indicates ending at the n-th number.

[0035] Preferably, a motor welding spot control system is characterized by comprising:

[0036] Data batch division module: used to determine the data to be collected as target data, divide the target data into different batches according to equal time division, and mark them as 1, 2, ..., n in sequence;

[0037] Data acquisition module: including welding process data acquisition unit and solder joint quality data acquisition unit, used to acquire target data in real time and transmit the acquired data to the data analysis module. The welding process data acquisition unit is used to acquire welding energy data, welding pressure data and welding temperature data; the solder joint quality data acquisition unit is used to acquire solder joint geometry data, solder joint internal structure data and solder joint electrical performance data;

[0038] Data analysis module: including welding process data analysis unit and solder joint quality data analysis unit, used to collect target data in real time and transmit the collected data to the data comprehensive evaluation module. The welding process data analysis unit includes welding energy data analysis node, welding pressure data analysis node and welding temperature data analysis node; the solder joint quality data analysis unit includes collecting solder joint geometry data analysis node, solder joint internal structure data analysis node and solder joint electrical performance data analysis node;

[0039] Data comprehensive evaluation module: including a motor welding spot data analysis unit, used for comprehensively analyzing the analysis results transmitted by the data analysis module, and transmitting the analysis results to the real-time feedback monitoring module;

[0040] Real-time feedback monitoring module: used to establish a preset value of the comprehensive evaluation index of the motor welding spot, judge the comprehensive evaluation index value of the motor welding spot according to the preset value of the comprehensive evaluation index of the motor welding spot, and send a corresponding signal according to the judgment result.

[0041] Technical effects and advantages of the present invention:

[0042] 1. The present invention effectively improves the accuracy and practicality of the solder joint data by dividing the data of the motor solder joints into batches. By collecting welding energy data, welding pressure data, welding temperature data, solder joint geometry data, solder joint internal structure data and solder joint electrical performance data in multiple dimensions, this multi-faceted data collection mode has greatly broken through the limitation of the single source of traditional solder joint detection data, and provides a sufficient and reliable information foundation for subsequent solder joint quality assessment;

[0043] 2. The present invention analyzes the collected data in depth through data evaluation, and then calculates the welding energy quality coefficient value, welding pressure stability coefficient value, welding temperature rationality coefficient value, solder joint geometry quality characteristic value, solder joint internal microstructure excellence coefficient value and solder joint electrical performance excellence coefficient value, and clearly points out the factors that may affect the quality of solder joints;

[0044] 3. The accuracy and effectiveness of the evaluation results are significantly enhanced by comprehensive weighing and deep integration of the data evaluation results. Through real-time monitoring and continuous tracking, once an abnormal weld is detected, an alarm signal is immediately issued, and relevant technicians and managers can quickly grasp the status and potential risks of motor welding, and take timely actions to adjust and optimize the welding process and parameters, providing strong guarantees for achieving high-precision motor welding weld control and scientific and reasonable decision-making and deployment. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 It is a schematic diagram of the structure of the method of the present invention;

[0046] Figure 2 It is a schematic diagram of the system structure of the present invention. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0048] As attached Figure 1 A motor welding spot control method shown in the figure specifically includes: a data batch division step, a data collection step, a data analysis step, a data comprehensive evaluation step and a real-time feedback monitoring step.

[0049] S1. Data batch division step: used to determine the data to be collected as target data, divide the target data into different batches in an equal time division manner, and mark them as 1, 2, ..., n in sequence.

[0050] In this embodiment, it is specifically necessary to explain that: the method of dividing by equal time is based on the characteristics of each target data. According to the real-time requirements of each target data, the database is run by the method to collect data once at equal intervals and divided into different collection times.

[0051] S2, data acquisition step: including a welding process data acquisition unit and a solder joint quality data acquisition unit, which are used to acquire target data in real time and transmit the acquired data to the data analysis step. The welding process data acquisition unit is used to acquire welding energy data, welding pressure data and welding temperature data; the solder joint quality data acquisition unit is used to acquire solder joint geometry data, solder joint internal structure data and solder joint electrical performance data.

[0052] In this embodiment, it is specifically necessary to explain that: the welding energy data includes the welding current rising slope Ws, the welding current pulse flat top time fluctuation value Wf and the inverse of the welding energy pulse trailing edge falling time Ec; the welding pressure data includes the welding pressure loading acceleration Pa, the welding process pressure center offset Op and the welding pressure unloading vibration frequency Pf; the welding temperature data includes the welding preheating zone temperature gradient Wt, the welding molten pool center and edge temperature difference Ed and the welding cooling phase change temperature interval residence time Cp; the solder joint geometry data includes the solder joint three-dimensional shape fractal dimension Ds, the solder joint contour least squares ellipse fitting major axis to minor axis ratio Mr and the solder joint surface micro-convex average spacing Js; the solder joint internal structure data includes the solder joint internal dislocation density Sd and the interface energy Se of different crystal phases inside the solder joint; the solder joint electrical performance data includes the high-frequency skin depth change rate Rf, the temperature and thermoelectric potential change Tp and the solder joint and ground loop parasitic inductance Gp.

[0053] The rising slope of the welding current determines the speed at which energy is injected into the welding part in a short period of time. The larger the slope, the faster the welding material can obtain enough heat to start melting, which helps to improve welding efficiency. However, if the slope is too large, it may cause local overheating of the welding material and defects such as spatter. It is crucial for the uniformity of the initial melting of the weld. The appropriate slope can make all parts of the weld evenly heated in the initial stage, laying the foundation for subsequent good fusion. The acquisition method is: a high-precision, high-bandwidth current sensor is connected in series in the welding circuit, and the real-time collected current data is transmitted to a high-speed data acquisition system. The acquisition system obtains data on the change of current over time at an extremely high sampling frequency. Then, these data are differentiated and calculated through a special digital signal processing algorithm to obtain the rising slope of the welding current.

[0054] The flat-top time fluctuation value of the welding current pulse refers to the length of time that the welding current remains relatively stable after reaching the peak value. The flat-top time fluctuation value reflects the accuracy of this stable stage. At this stage, the welding material continues to absorb energy for melting and fusion. A smaller fluctuation value means that the energy is continuously and stably input, which can ensure the uniformity of the internal structure of the weld and form a high-quality weld. If the fluctuation value is too large, local overheating or insufficient energy areas may appear inside the weld, resulting in inconsistent weld strength, internal voids and other problems. The collection method is: using a high-precision time counter combined with a current threshold judgment method, that is, when the welding current rises to the set flat-top current threshold, the time counter starts timing, and when the current drops below the threshold, the timing ends. The flat-top time fluctuation value of the welding current pulse is obtained through measurement and statistical analysis of multiple welding processes.

[0055] The inverse of the falling time of the trailing edge of the welding energy pulse is related to the speed of energy withdrawal at the end of welding. During the solidification process of the weld, a suitable energy withdrawal speed helps to control the crystallization morphology of the material. A faster withdrawal speed may cause the weld to solidify quickly, but it may also cause excessive internal stress; while a too slow withdrawal speed may cause the weld to be subjected to unnecessary heat during the solidification process, affecting its microstructure and performance. By controlling this parameter, the crystallization conditions during the solidification process of the weld can be optimized, and the quality and reliability of the weld can be improved. The acquisition method is as follows: first, the time of the welding current falling stage is accurately measured. This requires the use of high-precision time measurement equipment with a resolution of microseconds. Start timing when the welding current begins to drop from the peak value, and stop timing when the current drops to a value close to zero. Then take the inverse of the measured falling time to obtain the inverse of the falling time of the trailing edge of the welding energy pulse.

[0056] The welding pressure loading acceleration determines the dynamic characteristics of pressure application. When the electrode and the welding part begin to contact, the magnitude of the acceleration directly affects the impact force between the two. Appropriate acceleration can make the electrode and the welding part in good contact, ensuring that the initial contact resistance is within a reasonable range. If the acceleration is too large, it may cause surface damage to the welding part and affect the subsequent welding quality; while if the acceleration is too small, it may cause poor contact between the electrode and the welding part, making the current conduction uneven, thereby affecting the formation of the weld. The collection method is: a high-precision accelerometer is installed on the pressure application device of the welding electrode, and its measurement accuracy is ±0.1N / ms². The accelerometer directly measures the acceleration change during the pressure loading process and transmits the analog signal to the signal conditioning circuit. After the signal conditioning circuit amplifies and filters the signal, it converts it into a digital signal and transmits it to the control system for storage and analysis. When the accelerometer is installed, it is closely connected to the pressure application device, and its measurement direction is consistent with the pressure loading direction to measure the pressure loading acceleration.

[0057] The pressure center offset of the welding process reflects the uniformity of pressure distribution on the contact surface between the welding electrode and the weld. Ideally, the pressure should be evenly distributed on the contact surface so that each point in the welding part is subjected to the same pressure. However, due to factors such as electrode shape, installation accuracy, and surface flatness of the welding material, the pressure center may be offset. A large offset will cause excessive pressure on one side of the weld and insufficient pressure on the other side, resulting in good fusion on one side of the weld and poor fusion on the other side, which seriously affects the quality and strength of the weld. The collection method is: multiple micro pressure sensors are evenly distributed around the welding electrode to form a sensor array. During the welding process, each sensor measures the pressure value at its location in real time and transmits the data to the control system. The control system calculates the position of the pressure center through a complex algorithm based on the position information and pressure data of the sensor, and compares it with the geometric center of the electrode to obtain the pressure center offset.

[0058] The welding pressure unloading vibration frequency indicates that when the pressure is unloaded, the stress inside the weld will be redistributed. If the vibration frequency is too high, tiny cracks may be generated inside the weld, and these cracks may expand during subsequent use, causing the weld to fail. By monitoring and controlling this vibration frequency, the stress state of the weld during the pressure unloading process can be evaluated, and corresponding measures can be taken to reduce the risk of microcracks in the weld. The collection method is: using a pressure sensor to collect pressure signals during the unloading process. The collected pressure signal is an analog signal that varies with time, which is transmitted to the signal conditioning circuit for preprocessing such as amplification and filtering. Then, a spectrum analysis device is used to perform spectrum analysis on the preprocessed signal. The spectrum analysis device has a high frequency resolution of ±0.1kHz. By analyzing the characteristics of the pressure signal in the frequency domain, the vibration frequency component is extracted, thereby obtaining the vibration frequency during the welding pressure unloading process.

[0059] The temperature gradient of the welding preheating zone is a key parameter. It reflects how fast the temperature in the preheating zone changes with distance. A reasonable temperature gradient can enable the welding material to achieve uniform thermal expansion during the preheating process and avoid thermal stress concentration caused by excessive temperature differences. If the temperature gradient is uneven, thermal stress may be generated inside the welding material, affecting the quality of the solder joint during subsequent welding, such as causing cracks or deformation of the solder joint. The collection method is: multiple miniature thermocouples are arranged at a certain interval around the welding area to form a temperature gradient measurement network. The measurement accuracy of the thermocouple is ±0.5℃ / mm. Each thermocouple measures the temperature at its location in real time and transmits the temperature data to the control system. The control system calculates the temperature difference between adjacent thermocouples through a numerical calculation method based on the position information of the thermocouple and the measured temperature value, and then obtains the temperature gradient.

[0060] The temperature difference between the center and the edge of the welding pool has an important influence on the direction and speed of the liquid flow in the pool. During the welding process, the flow of liquid in the pool will affect the distribution of elements inside the weld. A large temperature difference will cause strong convection of the liquid from the center to the edge of the weld, which will drive the redistribution of elements in the welding material. By monitoring and controlling this temperature difference, the distribution of elements inside the weld can be optimized, and the quality and performance of the weld can be improved, such as improving the strength and corrosion resistance of the weld. The acquisition method is: use a high-resolution infrared thermal imager to shoot the welding pool. The temperature resolution of the infrared thermal imager is ±2°C, which can clearly distinguish the temperature distribution at the center and edge of the weld pool. During the shooting process, ensure that the lens of the thermal imager is perpendicular to the surface of the welding pool and the distance is appropriate to obtain an accurate temperature image. After the thermal image is processed, the temperature values ​​of the center and edge of the weld pool are extracted by the image analysis algorithm, and the temperature difference between the two is calculated.

[0061] The residence time of the welding cooling phase change temperature interval represents the key phase change temperature interval in which the solder joint material changes from liquid to solid. The residence time plays a decisive role in the proportion and morphology of the crystal phase. Different crystal phases have different properties. The appropriate residence time can make the solder joint form an ideal crystal structure and improve the strength, toughness and other properties of the solder joint. If the residence time is too short, it may lead to incomplete crystallization and produce a loose structure; if the residence time is too long, it may cause the grain to grow and reduce the performance of the solder joint. The collection method is: embed a micro temperature sensor inside the solder joint, and the measurement accuracy of the sensor is ±0.1s. These sensors can measure the temperature change inside the solder joint in real time. Through the study and determination of the phase change temperature interval of the welding material, when the solder joint temperature enters the phase change temperature interval, the control system starts timing. When the temperature leaves the phase change temperature interval, the timing stops, and the time obtained is the phase change temperature interval residence time.

[0062] The fractal dimension of the three-dimensional shape of the solder joint describes the complexity of the solder joint surface. The fractal dimension is closely related to the mechanical bite and electrical contact performance of the solder joint. A higher fractal dimension means that the solder joint surface has a more complex microstructure, which helps to increase the mechanical bite area between the solder joint and other components and improve the connection strength of the solder joint. At the same time, the complex surface structure is also conducive to increasing electrical contact points, reducing contact resistance, and improving electrical performance. The acquisition method is: using a three-dimensional laser scanner to scan the solder joint surface. The scanner obtains the three-dimensional coordinate information of the solder joint surface with extremely high accuracy (accuracy is ±0.001). The scanned three-dimensional data point cloud is transmitted to the computer, and the data is processed by a special fractal analysis algorithm. These algorithms are based on fractal geometry theory and determine the fractal dimension of the solder joint by calculating the coverage, roughness and other characteristics of the solder joint surface at different scales.

[0063] The ratio of the major axis to the minor axis of the least squares ellipse fitting of the solder joint contour reflects the ellipticity of the solder joint shape. Ideally, the shape of the solder joint should be symmetrical, but due to various factors in the welding process, the solder joint may have a certain degree of elliptical deformation. The abnormal change of this ratio can be used as a basis for judging whether there are asymmetric factors in the welding process. If the ratio deviates from the normal range, it may mean that the solder joint is subjected to uneven force or energy in a certain direction, which will affect the quality and performance of the solder joint, such as causing the strength of the solder joint in certain directions to decrease. The collection method is as follows: first, the contour data of the solder joint is obtained using a three-dimensional profile measuring instrument. The three-dimensional profile measuring instrument obtains the coordinate information of each point on the solder joint contour with high precision through a contact or non-contact measurement method. The measured contour data is transmitted to a computer and the data is processed using a least squares ellipse fitting algorithm. The algorithm calculates the length of the major axis and minor axis of the ellipse by finding the ellipse that best fits the solder joint contour, and then obtains the ratio of the major axis to the minor axis.

[0064] The average spacing of the micro-convex bodies on the solder joint surface directly affects the actual contact area and contact resistance of the solder joint. At the microscopic level, the solder joint surface is not completely smooth, but there are many micro-convex bodies. The spacing between these micro-convex bodies determines the number and distribution of actual contact points. A smaller average spacing means more contact points, which can increase the effective contact area between the solder joint and other components, reduce contact resistance, and improve electrical performance. At the same time, the appropriate micro-convex body spacing also helps to better disperse stress under mechanical pressure and improve the mechanical properties of the solder joint. The collection method is: use an atomic force microscope to scan the solder joint surface. The atomic force microscope uses the interaction force between the probe and the atoms on the solder joint surface to obtain the microscopic morphology information of the surface. Its vertical resolution can reach ±0.1nm, and it can clearly distinguish the height and position of the micro-convex bodies. After the scanned surface morphology data is processed, the micro-convex bodies are identified by an image analysis algorithm, and the average spacing between them is calculated.

[0065] The dislocation density inside the solder joint indicates that the dislocation density inside the solder joint is closely related to the strength and plastic deformation capacity of the solder joint. Dislocation is a defect in the arrangement of atoms in a crystalline material, and they move and interact when the material is subjected to stress. A higher dislocation density means that the dislocation is easier to move when the material is subjected to stress, so that the solder joint has better plastic deformation capacity and can absorb more energy without breaking. However, too high a dislocation density may also lead to stress concentration inside the material and reduce the strength of the solder joint. Therefore, controlling and understanding the dislocation density inside the solder joint is crucial for evaluating the performance of the solder joint, and the collection method is: observing the ultra-thin section of the solder joint through a transmission electron microscope. The transmission electron microscope uses the principle that the electron beam penetrates the sample and images on a fluorescent screen or detector, and can provide high-resolution microstructure images. When preparing ultra-thin sections of solder joints, special slicing techniques are required to ensure that the thickness of the slices is thin enough and that the internal structure of the solder joint is not damaged during the slicing process. The prepared ultra-thin slices are placed on the sample stage of the transmission electron microscope, and a clear image of the internal microstructure of the solder joint is obtained by adjusting the parameters of the electron beam and the focusing of the microscope. Specialized dislocation counting software is then used to identify and count the dislocations in the image and calculate the dislocation density.

[0066] The interface energy of different crystal phases inside the solder joint affects the bonding strength and stability between different crystal phases. During the solidification process of the solder joint, a variety of different crystal phases may be formed, and the interface between these crystal phases is the weak link inside the solder joint. The size of the interface energy determines the bonding force between the crystal phases. Lower interface energy means that the crystal phases are more likely to combine to form a stable structure, thereby improving the overall strength and stability of the solder joint. On the contrary, high interface energy may cause easy separation between the crystal phases, reducing the performance of the solder joint. The collection method is: using a high-resolution scanning probe microscope combined with a thermodynamic analysis method to measure the interface energy of different crystal phases inside the solder joint. The scanning probe microscope obtains the physical property information of the surface through the interaction between the probe and the sample surface. First, the solder joint surface is scanned using a scanning probe microscope to identify the boundary area of ​​different crystal phases. Then, by changing the distance and force between the probe and the sample, the energy change at the crystal phase boundary is measured. At the same time, combined with thermodynamic theory and model, the measurement data is analyzed and calculated to obtain the interface energy of different crystal phases.

[0067] The high-frequency skin depth change rate reflects the adaptability of the solder joint to the high-frequency signal. The appropriate change rate can ensure uniform current distribution during high-frequency operation, reduce local overheating, reduce resistance loss, improve electrical performance and stability, avoid solder joint aging and cracking, and ensure the reliability of high-frequency operation of the motor. The acquisition method is: apply high-frequency pulse current to the solder joint, and measure around the solder joint with a high-frequency magnetic field sensor with an accuracy of ±0.01% / MHz. When the current passes through, the sensor collects data on the change of magnetic field strength with frequency. Through the data acquisition system and algorithm, the skin depth at different frequencies is calculated according to the relationship between the magnetic field and the skin depth, and then the change rate is obtained.

[0068] The temperature and thermoelectric potential changes indicate that the solder joints are affected by temperature changes during motor operation. Thermoelectric potential is the electromotive force generated by the temperature gradient. If this parameter is too large, an additional voltage signal will be introduced into the circuit, resulting in measurement errors or interference with other signals, affecting the normal operation of the motor. Monitoring this parameter can evaluate the electrical stability of the solder joints under temperature changes, ensure good electrical performance at different temperatures, and reduce electrical failures. The collection method is: test the solder joints with a special thermoelectric potential measurement device. Place the solder joint in an environment where the temperature can be precisely controlled, such as a constant temperature box or thermal cycle equipment, and measure the thermoelectric potential by connecting two different metal wires at the solder joint. The measurement accuracy is ±0.1μV / ℃. Change the temperature and record the thermoelectric potential value to obtain the thermoelectric potential-temperature curve, and calculate the change in different temperature ranges.

[0069] The parasitic inductance between the solder joint and the ground loop is described as follows: parasitic inductance is a non-ideal electrical parameter of the solder joint in the circuit. In high-frequency circuits or circuits with high requirements for electromagnetic compatibility, it will affect the high-frequency response characteristics of the circuit, such as causing signal distortion and reducing anti-interference capabilities. Measuring and controlling this parameter can optimize circuit design, improve high-frequency performance and electromagnetic compatibility, and ensure stable operation of the motor in a complex electromagnetic environment. The acquisition method is to measure the solder joint with a vector network analyzer and a special inductance measurement fixture. Connect the solder joint and the ground loop to the fixture, and the analyzer sends test signals of different frequencies to the circuit to measure the reflection and transmission signal characteristics. Combined with the fixture calibration parameters, the parasitic inductance is calculated using an internal algorithm.

[0070] S3, data analysis step: including a welding process data analysis unit and a solder joint quality data analysis unit, which are used to collect target data in real time and transmit the collected data to the data comprehensive evaluation step. The welding process data analysis unit includes a welding energy data analysis node, a welding pressure data analysis node, and a welding temperature data analysis node; the solder joint quality data analysis unit includes a solder joint geometry data analysis node, a solder joint internal structure data analysis node, and a solder joint electrical performance data analysis node.

[0071] In this embodiment, it is specifically required to be explained that: the welding energy data analysis node is used to establish a welding energy data calculation model, and the welding energy data transmitted in the data acquisition step is imported into the welding energy data calculation model to obtain the welding energy quality coefficient value. The welding energy data calculation model is specifically expressed as:

[0072] ,

[0073] in, Indicates the welding energy quality coefficient value calculated for the i-th time, Ws i Indicates the rising slope of the welding current collected for the i-th time, Wf i Indicates the fluctuation value of the flat-top time of the welding current pulse collected for the i-th time, Ec i represents the inverse of the falling time of the trailing edge of the welding energy pulse collected for the i-th time, σ represents the standard deviation of the inverse of the falling time of the trailing edge of the welding energy pulse, and μ represents the mean of the inverse of the falling time of the trailing edge of the welding energy pulse.

[0074] In this embodiment, it is specifically required to be explained that: the welding pressure data analysis node is used to establish a welding pressure data calculation model, and the welding pressure data transmitted in the data acquisition step is imported into the welding pressure data calculation model to obtain the welding pressure stability coefficient value. The welding pressure data calculation model is specifically expressed as:

[0075] ,

[0076] in, Indicates the welding pressure stability coefficient value calculated for the i-th time, Pa i Op represents the welding pressure loading acceleration collected for the i-th time, i Pf represents the pressure center offset of the welding process collected for the i-th time. i Represents the welding pressure unloading vibration frequency collected for the i-th time.

[0077] In this embodiment, it is specifically required to be explained that: the welding temperature data analysis node is used to establish a welding temperature data calculation model, and the welding temperature data transmitted in the data acquisition step is imported into the welding temperature data calculation model to obtain a welding temperature rationality coefficient value. The welding temperature data calculation model is specifically expressed as:

[0078] ,

[0079] in, Indicates the reasonableness coefficient of the welding temperature calculated for the i-th time, Wt i represents the temperature gradient of the welding preheating zone collected for the i-th time, Ed i represents the temperature difference between the center and edge of the welding pool collected for the i-th time, Cp iIt represents the residence time in the welding cooling phase change temperature interval collected for the i-th time.

[0080] In this embodiment, it is specifically required to be explained that: the solder joint geometry data analysis node is used to establish a solder joint geometry data calculation model, and the solder joint geometry data transmitted in the data acquisition step is imported into the solder joint geometry data calculation model to obtain the solder joint geometry quality characteristic value. The solder joint geometry data calculation model is specifically expressed as:

[0081] ,

[0082] in, Denotes the geometric quality characteristic value of the solder joint calculated for the i-th time, Ds i represents the fractal dimension of the three-dimensional shape of the solder joint collected for the i-th time, Mr i It represents the ratio of the major axis to the minor axis of the least squares ellipse fitting of the solder joint contour collected for the i-th time, Represents the ratio of the major axis to the minor axis of the least squares ellipse fitting of the standard solder joint contour, Js i It represents the average spacing of micro-convex bodies on the solder joint surface collected for the i-th time.

[0083] In this embodiment, it should be specifically explained that: the solder joint internal structure data analysis node is used to establish a solder joint internal structure data calculation model, and the solder joint internal structure data transmitted in the data acquisition step is imported into the solder joint internal structure data calculation model to obtain the solder joint internal microstructure excellence coefficient value, and the solder joint internal structure data calculation model is specifically expressed as:

[0084] ,

[0085] in, represents the excellent coefficient value of the internal microstructure of the solder joint calculated for the i-th time, Sd i represents the internal dislocation density of the solder joint collected for the i-th time, Se i Represents the interfacial energy of different crystal phases inside the solder joint collected for the i-th time.

[0086] In this embodiment, it is specifically required to be explained that: the solder joint electrical performance data analysis node is used to establish a solder joint electrical performance data calculation model, and the solder joint electrical performance data transmitted in the data acquisition step is imported into the solder joint electrical performance data calculation model to obtain the solder joint electrical performance excellent coefficient value, and the solder joint electrical performance data calculation model is specifically expressed as:

[0087] ,

[0088] in, Indicates the excellent coefficient value of the electrical performance of the solder joint calculated for the i-th time, Rf iTp represents the rate of change of high-frequency skin depth collected for the i-th time. i Gp represents the temperature and thermoelectric potential changes collected for the i-th time. i It represents the parasitic inductance between the solder joint and the ground loop collected for the i-th time.

[0089] S4, data comprehensive evaluation step: including a motor welding spot data analysis unit, which is used to comprehensively analyze the analysis results transmitted by the data analysis step, and transmit the analysis results to the real-time feedback monitoring step.

[0090] In this embodiment, it is specifically required to be explained that: the motor welding spot data analysis unit is used to establish a motor welding spot data calculation model, and the welding energy quality coefficient value, welding pressure stability coefficient value, welding temperature rationality coefficient value, welding spot geometry quality characteristic value, welding spot internal microstructure excellence coefficient value and welding spot electrical performance excellence coefficient value transmitted by the data analysis step are imported into the motor welding spot data calculation model to obtain the motor welding spot comprehensive evaluation index value. The motor welding spot data calculation model is specifically expressed as:

[0091] ,

[0092] Where A represents the calculated comprehensive evaluation index value of the motor welding spot, , , represents the welding energy quality coefficient value calculated for the i-th time, represents the welding pressure stability coefficient value calculated for the i-th time, represents the reasonableness coefficient of the welding temperature calculated for the i-th time, represents the geometric quality characteristic value of the solder joint calculated for the i-th time, represents the minimum value of the calculated solder joint geometry quality characteristic, represents the maximum value of the calculated geometric quality characteristics of the solder joint, represents the excellent coefficient value of the internal microstructure of the solder joint calculated for the i-th time, Indicates the minimum value of the calculated solder joint internal microstructure excellence coefficient, Indicates the maximum value of the calculated internal microstructure excellence coefficient of the solder joint. represents the excellent coefficient value of the electrical performance of the solder joint calculated for the i-th time, Indicates the minimum value of the calculated solder joint electrical performance coefficient. It indicates the maximum value of the calculated solder joint electrical performance coefficient, i indicates starting from the i-th number, and n indicates ending at the n-th number.

[0093] S5. Real-time feedback monitoring step: used to establish a preset value of the comprehensive evaluation index for the motor welding solder joints, judge the value of the comprehensive evaluation index for the motor welding solder joints according to the preset value of the comprehensive evaluation index for the motor welding solder joints, and send corresponding signals according to the judgment results.

[0094] In this embodiment, it should be specifically noted that: the preset value of the comprehensive evaluation index for the motor welding solder joints is marked as A def , when A def =< A, a normal signal is sent. This signal indicates that the preset value of the comprehensive evaluation index for the motor welding solder joints is less than or equal to the value of the comprehensive evaluation index for the motor welding solder joints, indicating that the welding state of the motor solder joints is normal; when A def > A, a warning signal is sent to relevant technical management personnel. This signal indicates that the preset value of the comprehensive evaluation index for the motor welding solder joints is greater than the value of the comprehensive evaluation index for the motor welding solder joints, indicating that the welding state of the motor solder joints is poor.

[0095] Based on the above solution and appendix Figure 2 , the embodiment of the present application also discloses a control system for motor welding solder joints, including:

[0096] Data batch division module: used to determine the data to be collected as target data, divide the target data into different batches in the way of equal-time division, and mark them as 1, 2,..., n in sequence;

[0097] Data acquisition module: including a welding process data acquisition unit and a solder joint quality data acquisition unit, used to collect the target data in real time and transmit the collected data to the data analysis module. The welding process data acquisition unit is used to collect welding energy data, welding pressure data, and welding temperature data; the solder joint quality data acquisition unit is used to collect solder joint geometry data, solder joint internal structure data, and solder joint electrical performance data;

[0098] Data analysis module: including a welding process data analysis unit and a solder joint quality data analysis unit, used to collect the target data in real time and transmit the collected data to the data comprehensive evaluation module. The welding process data analysis unit includes a welding energy data analysis node, a welding pressure data analysis node, and a welding temperature data analysis node; the solder joint quality data analysis unit includes a solder joint geometry data analysis node, a solder joint internal structure data analysis node, and a solder joint electrical performance data analysis node;

[0099] Data comprehensive evaluation module: including a motor welding solder joint data analysis unit, used to comprehensively analyze the analysis results transmitted by the data analysis module and transmit the analysis results to the real-time feedback monitoring module;

[0100] Real-time feedback monitoring module: used to establish a preset value of the comprehensive evaluation index of the motor welding spot, judge the comprehensive evaluation index value of the motor welding spot according to the preset value of the comprehensive evaluation index of the motor welding spot, and send a corresponding signal according to the judgment result.

[0101] The present invention effectively improves the accuracy and practicality of the solder joint data by dividing the data of the motor solder joints into batches. By collecting welding energy data, welding pressure data, welding temperature data, solder joint geometry data, solder joint internal structure data and solder joint electrical performance data in multiple dimensions, this multi-faceted data collection mode has greatly broken through the limitation of the single source of traditional solder joint detection data, and provides a sufficient and reliable information foundation for subsequent solder joint quality evaluation. Through data evaluation, the collected data is deeply analyzed, and then the welding energy quality coefficient value, welding pressure stability coefficient value, welding temperature rationality coefficient value, solder joint geometry quality characteristic value, solder joint internal microstructure excellence coefficient value and solder joint electrical performance excellence coefficient value are calculated, and the factors that may affect the quality of the solder joint are clearly pointed out. By comprehensively weighing and deeply integrating the data evaluation results, the accuracy and effectiveness of the evaluation results are significantly enhanced. Through real-time monitoring and continuous tracking, once an abnormal weld is detected, an alarm signal will be issued immediately. Relevant technicians and managers can quickly understand the status and potential risks of motor welding, and take timely actions to adjust and optimize welding processes and parameters, providing strong guarantees for achieving high-precision motor welding spot control and scientific and reasonable decision-making and deployment.

[0102] Secondly: In the drawings of the embodiments disclosed in the present invention, only the structures related to the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other;

[0103] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A motor welding spot control method, characterized in that: include: S1, data batch division step: used to determine the data to be collected as target data, divide the target data into different batches in an equal time division manner, and mark them as 1, 2, ..., n in sequence; S2, data acquisition step: including a welding process data acquisition unit and a solder joint quality data acquisition unit, which are used to acquire target data in real time and transmit the acquired data to the data analysis step, wherein the welding process data acquisition unit is used to acquire welding energy data, welding pressure data and welding temperature data; the solder joint quality data acquisition unit is used to acquire solder joint geometry data, solder joint internal structure data and solder joint electrical performance data; The welding energy data includes the welding current rising slope Ws, the welding current pulse flat top time fluctuation value Wf and the welding energy pulse trailing edge falling time inverse Ec; the welding pressure data includes the welding pressure loading acceleration Pa, the welding process pressure center offset Op and the welding pressure unloading vibration frequency Pf; the welding temperature data includes the welding preheating zone temperature gradient Wt, the welding molten pool center and edge temperature difference Ed and the welding cooling phase change temperature interval residence time Cp; the solder joint geometry data includes the solder joint three-dimensional shape fractal dimension Ds, the solder joint contour least squares ellipse fitting major axis to minor axis ratio Mr and the solder joint surface micro-convex average spacing Js; the solder joint internal structure data includes the solder joint internal dislocation density Sd and the interface energy Se of different crystal phases inside the solder joint; the solder joint electrical performance data includes the high-frequency skin depth change rate Rf, the temperature and thermoelectric potential change Tp and the solder joint and ground loop parasitic inductance Gp; S3, data analysis step: including a welding process data analysis unit and a solder joint quality data analysis unit, which are used to collect target data in real time and transmit the collected data to the data comprehensive evaluation step; the welding process data analysis unit includes a welding energy data analysis node, a welding pressure data analysis node and a welding temperature data analysis node; the solder joint quality data analysis unit includes a solder joint geometry data analysis node, a solder joint internal structure data analysis node and a solder joint electrical performance data analysis node; The welding energy data analysis node is used to establish a welding energy data calculation model, import the welding energy data transmitted in the data acquisition step into the welding energy data calculation model, and obtain the welding energy quality coefficient value. The welding energy data calculation model is specifically expressed as: ， in, Indicates the welding energy quality coefficient value calculated for the i-th time, Ws i Indicates the rising slope of the welding current collected for the i-th time, Wf i Indicates the fluctuation value of the flat-top time of the welding current pulse collected for the i-th time, Ec i represents the inverse of the falling time of the trailing edge of the welding energy pulse collected for the i-th time, σ represents the standard deviation of the inverse of the falling time of the trailing edge of the welding energy pulse, and μ represents the mean of the inverse of the falling time of the trailing edge of the welding energy pulse; S4, data comprehensive evaluation step: including a motor welding spot data analysis unit, used for comprehensively analyzing the analysis results transmitted in the data analysis step, and transmitting the analysis results to the real-time feedback monitoring step; S5, real-time feedback monitoring step: used to establish a preset value of the motor welding spot comprehensive evaluation index, judge the motor welding spot comprehensive evaluation index value according to the preset value of the motor welding spot comprehensive evaluation index, and send a corresponding signal according to the judgment result.

2. A motor welding spot control method according to claim 1, characterized in that: The welding pressure data analysis node is used to establish a welding pressure data calculation model, import the welding pressure data transmitted in the data acquisition step into the welding pressure data calculation model, and obtain the welding pressure stability coefficient value. The welding pressure data calculation model is specifically expressed as: ， in, Indicates the welding pressure stability coefficient value calculated for the i-th time, Pa i Op represents the welding pressure loading acceleration collected for the i-th time, i Pf represents the pressure center offset of the welding process collected for the i-th time. i Represents the welding pressure unloading vibration frequency collected for the i-th time.

3. The motor welding spot control method according to claim 1, characterized in that: The welding temperature data analysis node is used to establish a welding temperature data calculation model, import the welding temperature data transmitted in the data acquisition step into the welding temperature data calculation model, and obtain the welding temperature rationality coefficient value. The welding temperature data calculation model is specifically expressed as: ， in, Indicates the reasonableness coefficient of the welding temperature calculated for the i-th time, Wt i represents the temperature gradient of the welding preheating zone collected for the i-th time, Ed i represents the temperature difference between the center and edge of the welding pool collected for the i-th time, Cp i It represents the residence time in the welding cooling phase change temperature interval collected for the i-th time.

4. The motor welding spot control method according to claim 1, characterized in that: The solder joint geometry data analysis node is used to establish a solder joint geometry data calculation model, import the solder joint geometry data transmitted in the data acquisition step into the solder joint geometry data calculation model, and obtain the solder joint geometry quality characteristic value. The solder joint geometry data calculation model is specifically expressed as: ， in, Denotes the geometric quality characteristic value of the solder joint calculated for the i-th time, Ds i represents the fractal dimension of the three-dimensional shape of the solder joint collected for the i-th time, Mr i It represents the ratio of the major axis to the minor axis of the least squares ellipse fitting of the solder joint contour collected for the i-th time, Represents the ratio of the major axis to the minor axis of the least squares ellipse fitting of the standard solder joint contour, Js i It represents the average spacing of micro-convex bodies on the solder joint surface collected for the i-th time.

5. The motor welding spot control method according to claim 1, characterized in that: The solder joint internal structure data analysis node is used to establish a solder joint internal structure data calculation model, import the solder joint internal structure data transmitted in the data acquisition step into the solder joint internal structure data calculation model, and obtain the solder joint internal microstructure excellence coefficient value. The solder joint internal structure data calculation model is specifically expressed as: ， in, represents the excellent coefficient value of the internal microstructure of the solder joint calculated for the i-th time, Sd i represents the internal dislocation density of the solder joint collected for the i-th time, Se i Represents the interface energy of different crystal phases inside the solder joint collected for the i-th time.

6. A motor welding spot control method according to claim 1, characterized in that: The solder joint electrical performance data analysis node is used to establish a solder joint electrical performance data calculation model, import the solder joint electrical performance data transmitted in the data acquisition step into the solder joint electrical performance data calculation model, and obtain the solder joint electrical performance excellent coefficient value. The solder joint electrical performance data calculation model is specifically expressed as: ， in, Indicates the excellent coefficient value of the electrical performance of the solder joint calculated for the i-th time, Rf i represents the rate of change of high-frequency skin depth collected for the i-th time, Tp i Gp represents the temperature and thermoelectric potential changes collected for the i-th time. i It represents the parasitic inductance between the solder joint and the ground loop collected for the i-th time.

7. The motor welding spot control method according to claim 1, characterized in that: The motor welding spot data analysis unit is used to establish a motor welding spot data calculation model, and imports the welding energy quality coefficient value, welding pressure stability coefficient value, welding temperature rationality coefficient value, welding spot geometry quality characteristic value, welding spot internal microstructure excellence coefficient value and welding spot electrical performance excellence coefficient value transmitted by the data analysis step into the motor welding spot data calculation model to obtain the motor welding spot comprehensive evaluation index value. The motor welding spot data calculation model is specifically expressed as: ， Where A represents the calculated comprehensive evaluation index value of the motor welding spot, , , represents the welding energy quality coefficient value calculated for the i-th time, represents the welding pressure stability coefficient value calculated for the i-th time, represents the reasonableness coefficient of the welding temperature calculated for the i-th time, represents the geometric quality characteristic value of the solder joint calculated for the i-th time, represents the minimum value of the calculated solder joint geometry quality characteristic, represents the maximum value of the calculated geometric quality characteristics of the solder joint, represents the excellent coefficient value of the internal microstructure of the solder joint calculated for the i-th time, Indicates the minimum value of the calculated solder joint internal microstructure excellence coefficient, Indicates the maximum value of the calculated internal microstructure excellence coefficient of the solder joint. represents the excellent coefficient value of the electrical performance of the solder joint calculated for the i-th time, Indicates the minimum value of the calculated solder joint electrical performance coefficient. It indicates the maximum value of the calculated solder joint electrical performance coefficient, i indicates starting from the i-th number, and n indicates ending at the n-th number.

8. A motor welding spot control system, used to implement a motor welding spot control method as described in any one of claims 1 to 7, characterized in that: include: Data batch division module: used to determine the data to be collected as target data, divide the target data into different batches according to equal time division, and mark them as 1, 2, ..., n in sequence; Data acquisition module: including welding process data acquisition unit and welding spot quality data acquisition unit, used to collect target data in real time and transmit the collected data to the data analysis module; The welding process data acquisition unit is used to collect welding energy data, welding pressure data and welding temperature data; the solder joint quality data acquisition unit is used to collect solder joint geometry data, solder joint internal structure data and solder joint electrical performance data; Data analysis module: including a welding process data analysis unit and a solder joint quality data analysis unit, which are used to collect target data in real time and transmit the collected data to the data comprehensive evaluation module. The welding process data analysis unit includes a welding energy data analysis node, a welding pressure data analysis node, and a welding temperature data analysis node; the solder joint quality data analysis unit includes a solder joint geometry data analysis node, a solder joint internal structure data analysis node, and a solder joint electrical performance data analysis node; Data comprehensive evaluation module: including a motor welding spot data analysis unit, used for comprehensively analyzing the analysis results transmitted by the data analysis module, and transmitting the analysis results to the real-time feedback monitoring module; Real-time feedback monitoring module: used to establish a preset value of the comprehensive evaluation index of the motor welding spot, judge the comprehensive evaluation index value of the motor welding spot according to the preset value of the comprehensive evaluation index of the motor welding spot, and send a corresponding signal according to the judgment result.

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