Laser welding spatter parameter capture and dust removal simulation method and system

Abstract

The invention discloses a laser welding spatter parameter capture and dust removal simulation method and system, and relates to the technical field of laser welding monitoring and computer simulation. The method specifically comprises the following steps that shooting equipment is configured, the shooting equipment comprises a high-speed camera, an optical filter and a laser light source, the shooting equipment is adjusted to enable the laser light source to illuminate a welding position, and the optical filter is matched with the high-speed camera to filter light interference in the welding process; light reflected by the laser light source is captured, so that a splash image is obtained; calibration is carried out based on features of known sizes in a shooting view, and pixel precision is calculated; two splash images with a time interval are selected, actual splash displacement is calculated according to the pixel displacement values of splash points in the two splash images in combination with the pixel precision, the time interval is divided by the actual splash displacement to obtain the splash speed, and meanwhile the splash number is counted; collecting dust particles in the dust production area by using a viscous sampling medium, and sending the collected viscous sampling medium into microscopic analysis equipment for analysis to obtain particle size distribution of the dust particles; and inputting the splashing speed, the splashing quantity and the dust particle size distribution as a data set into a dust removal simulation model so as to carry out dust removal structure simulation. The method aims at accurately obtaining kinematics and morphological parameters of laser welding spatter under the working condition of strong light interference so as to establish a high-precision dust removal simulation model.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of laser welding monitoring and computer simulation, in particular to a laser welding spatter parameter capturing and dust removal simulation method and system. BACKGROUND

[0002] In the battery manufacturing industry, laser welding is a key process to connect the tab and the connecting piece or the battery shell. However, high-temperature metal spatters are inevitably generated during the laser welding process. If these spatters fall into the liquid injection hole or adhere to the surface of the battery, it will seriously affect the product quality and safety. Therefore, it is crucial to design an efficient dust removal structure during the development of the equipment. Currently, in order to verify the effectiveness of the dust removal structure, the computational fluid dynamics (CFD) method is usually used for evaluation. The accuracy of the simulation is highly dependent on the authenticity of the input boundary conditions, especially the initial velocity, number distribution and particle size distribution of the spatters. However, the existing battery manufacturing equipment is usually equipped with only an ordinary camera or a simple dust removal device for monitoring the welding quality, and does not have the capability to capture the dynamic characteristics of the spatters. The conventional monitoring means is limited by the high-brightness plume and spark interference generated during welding, and cannot clearly capture the spatter trajectory, let alone provide quantitative speed and particle size data. As a result, the simulation model lacks accurate input parameters and can only rely on empirical estimation, which makes the simulation results deviate greatly from the actual working conditions, and it is difficult to effectively guide the optimization design of the dust removal structure.

[0003] Therefore, how to accurately obtain the kinematic and morphological parameters of laser welding spatters under strong light interference working conditions to establish a high-precision dust removal simulation model has become a technical problem to be solved. SUMMARY

[0004] The main purpose of the present application is to provide a laser welding spatter parameter capturing and dust removal simulation method and system, which aims to accurately obtain the kinematic and morphological parameters of laser welding spatters under strong light interference working conditions to establish a high-precision dust removal simulation model.

[0005] In order to achieve the above-mentioned purpose, the present application provides a laser welding spatter parameter capturing and dust removal simulation method, which comprises the following steps: Configure a shooting device, the shooting device comprising a high-speed camera, a filter and a laser light source, adjust the shooting device to make the laser light source illuminate the welding position, and use the filter to filter the light interference of the welding process in cooperation with the high-speed camera to capture the light reflected by the laser light source and obtain a spatter image; Calibrate based on the features of known size in the shooting field of view, and calculate the pixel accuracy; Two of the spatter images with time interval are selected, actual spatter displacement is calculated according to pixel displacement value of the spatter points in the two spatter images combined with the pixel precision, and the actual spatter displacement is divided by the time interval to obtain spatter speed, while the number of spatters is counted; Dust particles are collected by using a viscous sampling medium in a dust generation area, and the collected viscous sampling medium is sent to a microscopic analysis device for analysis to obtain dust particle size distribution; The spatter speed, the number of spatters and the dust particle size distribution are input as a data group into a dust removal simulation model to simulate a dust removal structure.

[0006] Preferably, the laser light source emits laser light with a temperature of 500 degrees Celsius, and when the shooting device is configured, copper foil or aluminum foil is used to coat and protect high-temperature-intolerant positions around the illumination area of the laser light source.

[0007] Preferably, before the step of adjusting the shooting device to make the laser light source illuminate the welding position, the method further comprises the steps of evaluating the working condition and manually controlling: when the product to be welded reaches the welding position, manually control each working step instruction of the laser welding opening device, the working step instruction includes starting dust removal, equipment reaching the welding position, starting welding and protection gas.

[0008] Preferably, when the shooting device is configured, the horizontal direction and the vertical direction of the spatter image are consistent with the required horizontal direction and vertical direction in the dust removal simulation model, and the focusing plane of the high-speed camera is adjusted to be parallel to the welding track of the laser welding.

[0009] Preferably, the step of selecting two of the spatter images with time interval specifically selects an initial image of spatter generation as the first image, and selects the next image immediately after the initial image as the second image.

[0010] Preferably, in the step of calculating actual spatter displacement according to pixel displacement value of the spatter points in the two spatter images combined with the pixel precision, the center position of the spatter in the initial image and the next image is specifically grabbed, and the pixel coordinate difference value of the center position is calculated as the pixel displacement value.

[0011] Preferably, the step of calculating the pixel precision specifically includes: obtaining actual length value and actual width value of the feature with known size, measuring horizontal pixel size and vertical pixel size of the feature with known size in the spatter image or the image for calibration, and determining the ratio of the actual length value to the horizontal pixel size and the ratio of the actual width value to the vertical pixel size as the pixel precision.

[0012] Preferably, the step of counting the number of splashes further comprises: repeatedly selecting a splash image and calculating a splash speed to calculate a maximum value, a minimum value and a distribution trend of the splash speed within a certain sample range, and record the number of splashes within the certain sample range.

[0013] Preferably, the adhesive sampling medium is a special adhesive paper, an adhesive tape or a paper sheet, and the adhesive sampling medium is placed flat in the dust generating area when collecting dust particles.

[0014] Preferably, the dust removal simulation model is a particle tracking simulation model, and when the data set is input, a random function or a normal distribution function matched with the data set is selected as an input condition of particle entrance in the simulation software.

[0015] The application also discloses a laser welding splash parameter capturing and dust removal simulation system, comprising: The shooting module comprises a high-speed camera, a filter and a laser light source, and is used for filtering light interference of a welding process by the filter in cooperation with the high-speed camera and capturing light reflected by the laser light source to obtain a splash image when the laser light source illuminates a welding position; The processing module is configured to perform the following operations: calibration based on a feature with a known size in a shooting field of view and calculation of pixel accuracy; selection of two splash images with a time interval, calculation of actual splash displacement based on pixel displacement values of splash points in the two splash images in combination with the pixel accuracy, and calculation of a splash speed by dividing the actual splash displacement by the time interval while counting the number of splashes; The dust fall detection module comprises an adhesive sampling medium and a microscopic analysis device, the adhesive sampling medium is used for collecting dust particles in a dust generating area, and the microscopic analysis device is used for analyzing the collected adhesive sampling medium to obtain a dust particle size distribution; The simulation module is configured to receive a data set composed of the splash speed, the number of splashes and the dust particle size distribution, and perform dust removal structure simulation by using the data set as an input parameter.

[0016] The above technical solution has the following advantages: By configuring a shooting device containing a high-speed camera, a filter and a laser light source, laser active illumination and narrow-band filtering are used to effectively filter the strong light interference in the welding process, and high signal-to-noise ratio imaging of the splashing particles is realized. By calculating the pixel displacement of the splashing points in two images with a time interval, and combining pixel accuracy calibration, the initial velocity of the splashing can be accurately calculated, and the distribution data can be obtained by counting the number of splashes in the image. Combined with the physical layer viscosity sampling and microscopic analysis, the microscopic particle size distribution that is difficult to accurately measure by image method is obtained. Finally, the measured velocity, quantity and particle size data are input as boundary conditions into the dust removal simulation model, a data closed loop from physical detection to digital simulation is constructed, which significantly improves the accuracy and reliability of the dust removal structure simulation verification, and provides a scientific basis for the dust removal optimization of lithium battery manufacturing equipment. BRIEF DESCRIPTION OF DRAWINGS

[0017] The present application will be described in detail below with specific embodiments and drawings, in which: Figure 1 A flowchart of the laser welding splashing parameter capturing and dust removal simulation method provided for Embodiment One of the present application is shown. DETAILED DESCRIPTION

[0018] In order for those skilled in the art to better understand the present application, 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 a part 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 should be within the scope of protection of the present application.

[0019] Embodiment One As shown in Figure 1 , the present embodiment provides a laser welding splashing parameter capturing and dust removal simulation method, aiming to solve the problem that the existing lithium battery manufacturing equipment cannot obtain accurate splashing parameters for dust removal structure simulation verification.

[0020] Before shooting, it is necessary to evaluate whether the scene supports shooting under the required working condition. This includes evaluating whether there is enough space to set up the shooting device, and whether it is necessary to remove the device mechanism that blocks the view. On the lithium battery production line, some positioning welding product mechanisms or dust removal pipelines may block the shooting angle. Therefore, it is necessary to evaluate whether these mechanisms can be temporarily removed. If it is confirmed that there is no obstruction to the view or the obstructing mechanism has been removed, and there is enough space to set up, the subsequent steps can be performed.

[0021] The shooting device is configured, and the shooting device mainly comprises a high-speed camera, a filter and a laser light source. In actual working conditions, in order to overcome the strong light interference of welding arc light and metal vapor, the laser is used as an active illumination means in the embodiment. The shooting device is adjusted to make the laser light source illuminate the welding position, and the filter is used to filter the light interference in the welding process together with the high-speed camera. The wavelength band of the filter is selected to match the wavelength of the laser light source, so that only the light reflected by the laser light source is captured or mainly captured. In this way, the background noise in the image is greatly suppressed, and the splashing particles are clearly presented as high-light features, solving the problem of low signal-to-noise ratio in the traditional illumination mode.

[0022] The laser light source emits laser energy with extremely high density, and the temperature thereof can reach 500 degrees Celsius. In the lithium battery manufacturing equipment, plastic air pipes or sensor cables of pneumatic elements are often arranged, and these components cannot withstand such high temperature. If direct irradiation is performed, the equipment is easily damaged. Therefore, when the shooting device is configured, the high-temperature-resistant position around the laser light source illumination area needs to be coated for protection. In the embodiment, the copper foil or aluminum foil commonly used in the manufacturing of battery cells is used to wrap the above-mentioned high-temperature-resistant position, and the high reflectivity and heat resistance of the metal foil are used to block the laser heat, so as to ensure the safety of the original production equipment while ensuring the shooting effect. At the same time, it should be noted that due to the high energy of the laser, the operator needs to maintain a certain safety distance from the laser welding position and the laser light source illumination position during the erection and debugging process to avoid safety accidents.

[0023] Before formal shooting, the shooting device needs to be debugged and tested to ensure the shooting effect. During the test shooting, the operator needs to adjust the angle of the high-speed camera to align with the welding position, and adjust the frame rate, exposure and other image parameters of the camera, until the features of the welding splashing in the image can be clearly captured. In addition, an artificial control mechanism needs to be established. Generally, the action of the automatic production line is very fast, which is not conducive to debugging and capturing specific moments. In the embodiment, after artificial or automatic feeding of the equipment, when the welded product reaches the welding position, the operator controls each step instruction of the laser welding opening device through the control system. These step instructions include starting dust removal, the equipment reaching the welding position, starting welding and protection gas. By dividing the continuous automatic action into controllable single-step instructions, the shooting personnel can accurately synchronize the triggering time of the high-speed camera, so as to ensure that the splashing explosion moment of the welding starting moment is not missed, and the most complete splashing data is obtained.

[0024] Embodiment two On the basis of the hardware construction of embodiment one, the data acquisition and optical calculation process are further described in the embodiment.

[0025] In order to ensure that the two-dimensional image data can be accurately mapped to the three-dimensional simulation model, when configuring the shooting device, the horizontal direction and the vertical direction of the splashing image need to be consistent with the required horizontal direction and vertical direction in the dust removal simulation model. At the same time, the focusing plane of the high-speed camera is adjusted to be parallel to the welding track of the laser welding. This strict alignment of the geometric position eliminates the influence of perspective distortion on the speed decomposition, so that the subsequently calculated component speed can be directly used as the simulation boundary condition.

[0026] Before obtaining the image data, accurate spatial calibration must be performed. The present embodiment calculates the pixel precision based on the calibration of the known size features in the shooting field of view. The known size features can be positioning holes, screws on the welding fixture, or pre-placed calibration blocks.

[0027] The calculation process is as follows: the actual length value and the actual width value of the known size feature are obtained, and then the horizontal pixel size and the vertical pixel size of the feature are measured in the splashing image or a specially shot calibration image. The ratio of the actual length value to the horizontal pixel size is determined as the horizontal pixel precision , and the ratio of the actual width value to the vertical pixel size is determined as the vertical pixel precision . The specific calculation logic is as follows: , wherein represents the actual size (length or width) of the feature, represents the corresponding pixel number (horizontal or vertical pixel size) of the feature in the image. By calculating the precision in the horizontal and vertical directions respectively, the possible small distortion of the aspect ratio of the lens can be corrected.

[0028] After obtaining a clear sequence of splashing images, the initial speed of the splashing is needed to be calculated. In order to obtain the most accurate simulation entrance parameters, the present embodiment selects two splashing images with a time interval, specifically selects the initial image of the splashing as the first image, and selects the next image immediately after the initial image as the second image. In this very short time interval, the influence of gravity and wind resistance on the splashing is minimal, and its displacement is closest to the initial state.

[0029] The calculation process is as follows: first, the frame rate of the high-speed camera is calculated to calculate the interval time of the images , and the calculation formula is . Next, the center position of the splashing in the initial image and the next image is grabbed, the pixel coordinates of the center position in the two images are read respectively, and the pixel coordinate difference is calculated as the pixel displacement value. According to the pixel displacement value of the splashing point in the two splashing images and the aforementioned pixel precision, the actual splashing displacement is calculated. The calculation logic of the actual splashing displacement is as follows: (Compute horizontal and vertical components separately). Finally, divide the actual splatter displacement by the time interval between the two images to obtain the splatter velocity i.e. To make the simulation more robust, instead of calculating a single particle, this embodiment repeatedly selects a splatter image and calculates the splatter velocity to calculate the maximum, minimum and distribution trend of the splatter velocity in a certain sample range, while counting the number of splatters. This statistically-based data set can truly reflect the splatter dispersion characteristics during the welding process, avoiding simulation bias caused by a single data.

[0030] Embodiment Three This embodiment focuses on the collection of physical parameters and the formation of a simulation closed loop. Although a high-speed camera can accurately capture the velocity and number, for micron-level dust particles, it is difficult to accurately measure the particle size distribution through images due to the limitation of optical resolution.

[0031] In the dust generation area, use a viscous sampling medium to collect dust particles. The viscous sampling medium can be a special adhesive paper, an adhesive tape or a paper sheet. When collecting, make sure that the viscous sampling medium is flat and clean, and the operator should wear a dust-free glove to place the viscous sampling medium flat in the dust generation area, such as the lower air outlet of the welding station or the area where splatters are concentrated, and try to avoid touching the adhesive surface directly to prevent contamination. After collection, the viscous sampling medium is sent to a microscopic analysis device for analysis. During the transfer process, a dust-free glove is also needed to place the viscous sampling medium on the object slide of the microscopic analysis device. The microscopic analysis device can be a cleanliness particle automatic detection and analysis microscope, which can automatically scan the surface of the medium, identify and count the number of particles in different particle size intervals, and thus obtain a high-precision dust particle size distribution.

[0032] Finally, integrate the data sets obtained in the above steps. The data set includes the splatter velocity (including the distribution trend) and the number of splatters obtained by the optical method, and the dust particle size distribution obtained by the physical method. These three groups of data are input into the dust removal simulation model as input parameters. The dust removal simulation model usually uses a particle tracking simulation model (DPM). When inputting data, select a random function or a normal distribution function in the simulation software that matches the data set as the input condition of the particle inlet. For example, fit the velocity distribution as a normal distribution function to input the model, and fit the particle size distribution as a Rosin-Rammler distribution function to input the model. Through this simulation based on measured data, the dust generation process of laser welding can be truly reproduced, so as to accurately evaluate the dust removal efficiency and flow field rationality of the dust removal structure, greatly shortening the equipment development cycle.

[0033] Embodiment Four The embodiment provides a laser welding splash parameter capturing and dust removal simulation system for executing the above method. The system comprises a shooting module, a processing module, a dust fall detection module and a simulation module.

[0034] The shooting module is used for image acquisition and comprises a high-speed camera, a filter and a laser light source. The laser light source is used for providing high-intensity background light suppression illumination during welding, and the filter is used for cooperating with the high-speed camera to capture only light in the laser wave band, so that a splash image with high signal-to-noise ratio is obtained. The processing module is configured to perform calibration and calculation of data. It receives image data from the high-speed camera, calibrates based on a feature with a known size in the shooting field of view and calculates pixel accuracy. The processing module further selects two splash images with a time interval (preferably an initial frame and a next frame), calculates the actual displacement according to the pixel displacement of the splash points in the two images combined with the pixel accuracy, and calculates the splash speed combined with the time interval, and simultaneously counts the splash quantity through an image recognition algorithm. The dust fall detection module is used for physical layer particle size analysis and comprises a sticky sampling medium and a microscopic analysis device. The sticky sampling medium is arranged in a dust production area to perform physical sampling, and the microscopic analysis device performs microscopic scanning on the sampled medium to output particle size distribution data. The simulation module is configured to receive a data group composed of the splash speed, the splash quantity and the dust particle size distribution generated by the processing module and the dust fall detection module. The simulation module internally runs a particle tracking algorithm, uses the data group as an entrance boundary condition of a particle source, numerically simulates the airflow field and particle trajectory of a dust removal structure, and outputs dust removal efficiency evaluation results. The system breaks through the data link from a physical phenomenon to digital simulation through the cooperation of software and hardware.

[0035] The above merely describes specific embodiments of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for simulating laser welding spatter parameters and dust removal, characterized in that, Includes the following steps: The camera is configured with a high-speed camera, a filter, and a laser light source. The camera is adjusted so that the laser light source illuminates the welding position. The filter is used in conjunction with the high-speed camera to filter out light interference during the welding process, so as to capture the light reflected from the laser light source and obtain a spatter image. Calibration is performed based on features of known dimensions within the shooting field of view, and pixel accuracy is calculated. Two splash images with a time interval are selected. The actual splash displacement is calculated based on the pixel displacement value of the splash point in the two splash images and the pixel precision. The actual splash position is removed and the splash speed is obtained with the time interval. At the same time, the number of splashes is counted. Dust particles are collected in the dust-generating area using a viscous sampling medium, and the collected viscous sampling medium is sent to a microscopic analysis device for analysis to obtain the particle size distribution of the dust particles. The splashing velocity, splashing quantity, and dust particle size distribution are input as data sets into the dust removal simulation model to simulate the dust removal structure.

2. The laser welding spatter parameter capture and dust removal simulation method as described in claim 1, characterized in that, The laser emitted by the laser source reaches a temperature of 500 degrees Celsius. When configuring the shooting equipment, copper foil or aluminum foil is used to cover and protect the high-temperature-resistant areas around the area illuminated by the laser source.

3. The laser welding spatter parameter capture and dust removal simulation method as described in claim 1, characterized in that, Before the step of adjusting the imaging device to illuminate the welding position with the laser light source, the process also includes a step of assessing the working conditions and performing manual control: when the product to be welded reaches the welding position, the laser welding start device is manually controlled for each step instruction, including starting dust removal, the device reaching the welding position, starting welding, and shielding gas.

4. The laser welding spatter parameter capture and dust removal simulation method as described in claim 1, characterized in that, When configuring the shooting equipment, the horizontal and vertical directions of the splash image are made consistent with the horizontal and vertical directions required in the dust removal simulation model, and the focus plane of the high-speed camera is adjusted to be parallel to the welding trajectory of the laser welding.

5. The laser welding spatter parameter capture and dust removal simulation method as described in claim 1, characterized in that, The selection of two splash images with a time interval specifically involves selecting the initial image generated by the splash as the first image and selecting the next image immediately following the initial image as the second image.

6. The laser welding spatter parameter capture and dust removal simulation method as described in claim 5, characterized in that, In the step of calculating the actual splash displacement based on the pixel displacement value of the splash point in the two splash images and the pixel precision, the center position of the splash in the initial image and the next image is specifically captured, and the pixel coordinate difference of the center position is calculated as the pixel displacement value.

7. The laser welding spatter parameter capture and dust removal simulation method as described in claim 1, characterized in that, The specific steps for calculating pixel accuracy are as follows: obtaining the actual length and actual width values ​​of the feature of the known size, measuring the horizontal and vertical pixel dimensions of the feature of the known size in the splash image or the image used for calibration, and determining the ratio of the actual length value to the horizontal pixel dimension and the ratio of the actual width value to the vertical pixel dimension as the pixel accuracy.

8. The laser welding spatter parameter capture and dust removal simulation method as described in claim 1, characterized in that, The step of counting splashes further includes: repeatedly selecting splash images and calculating splash speeds to calculate the maximum, minimum and distribution trends of splash speeds within a certain sample range, and recording the number of splashes within the certain sample range.

9. The laser welding spatter parameter capture and dust removal simulation method as described in claim 1, characterized in that, The viscous sampling medium is a special adhesive paper, adhesive tape, or paper sheet. When collecting dust particles, the viscous sampling medium is placed flat in the dust-generating area.

10. The laser welding spatter parameter capture and dust removal simulation method as described in claim 1, characterized in that, The dust removal simulation model is a particle tracking simulation model. When inputting the data set, a random function or normal distribution function that matches the data set is selected in the simulation software as the input condition for the particle inlet.

11. A laser welding spatter parameter capture and dust removal simulation system, characterized in that, include: The imaging module includes a high-speed camera, a filter, and a laser light source. When the laser light source illuminates the welding position, the filter, in conjunction with the high-speed camera, filters out light interference during the welding process and captures the light reflected from the laser light source to obtain a spatter image. The processing module is configured to perform the following operations: calibrate and calculate pixel accuracy based on features of known size within the field of view; Two splash images with a time interval are selected. The actual splash displacement is calculated based on the pixel displacement value of the splash point in the two splash images and the pixel precision. The actual splash position is removed and the splash speed is obtained with the time interval. At the same time, the number of splashes is counted. The dust detection module includes a viscous sampling medium and a microscopic analysis device. The viscous sampling medium is used to collect dust particles in the dust-generating area, and the microscopic analysis device is used to analyze the collected viscous sampling medium to obtain the particle size distribution of the dust particles. The simulation module is configured to receive a data set consisting of the splash velocity, the number of splashes, and the particle size distribution of dust particles, and use the data set as input parameters to simulate the dust removal structure.

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