A method for laser cutting of large-format battery pole pieces

Abstract

The invention discloses a method for laser cutting of large-format battery pole pieces, comprising the steps of constructing a laser cutting system, fixing the pole piece, feeding and focusing a platform, editing a drawing, setting parameters, executing cutting and optimizing process monitoring, wherein the process monitoring optimization further comprises: during the cutting process, using a high-speed camera to monitor the cutting front in real time and shoot three cutting fronts to obtain a monitoring image, performing data analysis on the brightness values ​​of the pixels of the monitoring image to obtain a spark performance value of the monitoring image, judging whether there are sparks generated by laser cutting in the monitoring image and dividing a delay period and a cutting period, judging whether there are problems in the laser cutting process and whether the problems are serious, and if serious, generating a problem analysis signal, constructing a spark performance curve, judging whether the spark performance in the cutting process of the laser cutting system is orderly, and repairing the laser cutting system or optimizing the parameters according to the judgment result.

Description

Technical Field

[0001] The invention relates to the technical field of laser cutting, and in particular to a method for laser cutting of large-format battery pole pieces. Background Art

[0002] With the breakthrough and upgrade of blade battery technology, battery performance and driving range are the key to the upgrade of the entire new energy vehicle industry. Among the many technological innovation processes, blade battery technology is currently a battery technology with excellent performance. With its unique design and excellent performance, new solutions are needed for large-format blade battery pole processing to adapt to new applications.

[0003] In the prior art, the die-cutting process of battery pole pieces generally uses the stress of the knife die to peel off the coating particles and the middle metal foil, and cracks are generated after the breaking strength is reached. The cracks expand and separate, but the process is prone to cause problems such as cracking and burrs on the surface of the pole piece. The metal foil in the middle layer is also prone to plastic strain, resulting in poor yield. In the prior art, the solution size of single-head picosecond laser cutting of battery pole pieces is limited, and it is not suitable for product replacement and has low efficiency.

[0004] On the other hand, there is a lack of effective monitoring methods to accurately grasp the cutting process in real time. Due to factors such as the thermal effects of optical components and the energy fluctuations of laser pulses, the sparks at the cutting front are prone to abnormal performance. These abnormal sparks may mean unstable output of laser energy, which in turn causes a decline in the quality of electrode cutting, such as burrs, uneven cutting width and other defects, which seriously affect the consistency and yield of battery electrodes.

[0005] In view of the above problems, the present invention proposes a method for laser cutting of large-format battery pole pieces. Summary of the invention

[0006] The object of the present invention is to provide a method for laser cutting of large-format battery pole pieces to solve at least one of the above-mentioned problems of the prior art.

[0007] The present invention provides a method for laser cutting of large-format battery pole pieces, comprising the steps of constructing a laser cutting system, fixing the pole piece, feeding and focusing the platform, editing the image file, setting parameters, executing the cutting and optimizing the process monitoring, wherein the process monitoring optimization further comprises the following steps:

[0008] During the cutting process, a high-speed camera is used to monitor the cutting front in real time and shoot three cutting fronts to obtain monitoring images. The brightness values ​​of the pixels in the monitoring images are analyzed to obtain the spark performance values ​​of the monitoring images. According to the spark performance values, it is determined whether there are sparks generated by laser cutting in the monitoring images, and the operation cycle is divided into a delay period and a cutting period.

[0009] Based on the spark performance value of the monitoring image during the cutting period, it is judged whether there is a problem in the laser cutting process of the infrared picosecond laser in the laser cutting system, and the period when the problem occurs is marked as the problem period, and the data of the problem period is processed to obtain the problem representation value, and it is judged whether the problem in the laser cutting process of the infrared picosecond laser is serious according to the problem representation value. If it is serious, a problem analysis signal is generated;

[0010] Based on the generated problem analysis signal, the spark performance curves of each infrared picosecond laser in the laser cutting system during the laser cutting process are constructed, and the spark performance curves in the problem period are marked as problem sub-curves. The problem sub-curves in the cutting period are compared and analyzed to see whether there is a time regularity, and the curve disordered signal and the curve ordered signal are generated respectively.

[0011] Based on the generated disordered curve signal and ordered curve signal, it is judged whether the spark performance in the cutting process of the laser cutting system is orderly, and the laser cutting system is repaired or the parameters are adjusted and optimized according to the judgment result.

[0012] Beneficial effects of the present invention:

[0013] 1. The present invention provides a method for laser cutting of large-format battery pole pieces. A high-power picosecond laser has good end face cutting effect, few melt beads, small heat impact and high precision. Three heads process products simultaneously, which is suitable for large-format pole pieces. It has fast changeover, one-time cutting and fast cutting speed. The overall efficiency is more than 3 times higher than that of single-head processing pole piece products. The software integration is high, the operation is simple, and the equipment size is relatively small compared to other structures.

[0014] 2. The present invention uses a high-speed camera to monitor the cutting front in real time, and through data analysis of the brightness value of the pixels in the monitoring image, it can accurately determine the generation of sparks during the laser cutting process, and effectively divide the operation cycle into a delay period and a cutting period. This method can promptly discover potential problems of the infrared picosecond laser in the laser cutting system during the cutting process, accurately locate the problem period, obtain the problem characterization value through data processing, and then accurately evaluate the severity of the problem. This technology not only improves the stability and safety of the cutting process, but also greatly reduces the time and cost of fault repair, ensuring the high quality and efficiency of large-format battery pole laser cutting.

[0015] 3. The present invention constructs a spark performance curve and marks the problem sub-curve, which can accurately capture the anomalies in the laser cutting process. By comparing and analyzing the time laws of the problem sub-curve, it generates ordered and disordered signals, providing a scientific basis for judging the cutting process. This method not only improves the stability of the cutting process, but also guides system maintenance and parameter optimization, ensuring efficient and safe laser cutting, and greatly improving product quality and production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 It is a flowchart of the steps of a large-format battery pole piece laser cutting method provided by an embodiment of the present invention;

[0018] Figure 2 This is a flowchart of specific steps for obtaining spark performance values ​​in a large-format battery pole piece laser cutting method provided in Embodiment 2 of the present invention;

[0019] Figure 3 It is a schematic diagram of the simultaneous processing trajectory of laser multi-head splicing adopted in a large-format battery pole piece laser cutting method provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0020] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings 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 should fall within the scope of protection of the present invention.

[0021] Embodiment 1: Figure 1 and Figure 3 As shown, a method for laser cutting of a large-format battery pole piece provided by an embodiment of the present invention specifically includes the following steps:

[0022] S1. Constructing a laser cutting system: three infrared picosecond lasers are arranged in parallel at a spacing of 330 mm. The infrared picosecond laser beam with a power of 300 W emitted by each laser is finally focused into a 69 μm spot after passing through the optical path focusing system. The optical path focusing system includes a beam expander, a galvanometer and a field lens.

[0023] S2. Pole piece fixation: Place the large-format battery pole piece to be cut on the adsorption bottom plate, and adjust the adsorption force to ensure the stable position of the pole piece;

[0024] S3, platform feeding and focusing: Use the platform's Y-axis to feed the pole piece under the galvanometer working position. The positioning accuracy of the Y-axis is controlled to be less than 10μm. Then, the three-head galvanometer focusing system is sent to the precise focal position through the Z-axis. The repeatability of the Z-axis positioning must be within 5μm.

[0025] S4. Graphics editing: Use graphics editing software to create three 330mm parallel lines. The line spacing can be set arbitrarily within a certain range according to the actual width of the pole piece. Ensure that the misalignment of the three lines is less than 10μm and the parallelism is less than 2°. Splice the three lines in length direction to the required length. The document format is dxf or dwg.

[0026] S5. Parameter setting: Import the edited document into the control software, and set the parameters in the control software, including setting the cutting direction, setting the trigger command for the three heads to emit light at the same time and the same delay time, and setting the process parameters according to the material thickness;

[0027] S6, cutting execution: start the laser cutting system to cut at the same time, perform laser multi-head splicing and simultaneous processing on the pole piece, and splice with a single head width of 330mm, ensuring that the splicing angle is less than 2°, and the laser overlap misalignment of the splicing seam is less than 10μm, and a large-format pole piece product with an overall length that meets the standard is obtained through one-time processing;

[0028] S7. Process monitoring and optimization: Use high-speed cameras to monitor and optimize the laser cutting process of large-format battery pole pieces.

[0029] Embodiment 2: Figure 1 As shown, a method for laser cutting of a large-format battery pole piece provided by an embodiment of the present invention, in the steps described in the first embodiment, the laser cutting process of the large-format battery pole piece is monitored and optimized, specifically comprising the following steps:

[0030] Step 1: During the cutting process, a high-speed camera is used to monitor the cutting front in real time and shoot three cutting fronts to obtain monitoring images. The brightness values ​​of the pixels in the monitoring images are analyzed to obtain the spark performance values ​​of the monitoring images. According to the spark performance values, it is determined whether there are sparks generated by laser cutting in the monitoring images, and the operation cycle is divided into a delay period and a cutting period.

[0031] In some embodiments, a high-speed camera is used to monitor the cutting front in real time;

[0032] Specifically, a number of detection time points are uniformly taken within the operation cycle, and the intervals between the detection time points are all equal. The operation cycle represents the time from starting the laser cutting system to the time when the three infrared picosecond lasers in the laser cutting system complete one laser cutting.

[0033] A high-speed camera is respectively arranged at the three field mirrors, and the shooting direction of the high-speed camera is consistent with the focusing direction of the laser beam. The three cutting fronts are photographed simultaneously at the current detection time point by the high-speed camera, and the photographed image is marked as a monitoring image. The monitoring images photographed at the same detection time point are grouped into a simultaneous monitoring image group, and the monitoring images photographed by the same high-speed camera are grouped into a co-location monitoring image group, and the sizes of the monitoring images are all the same;

[0034] The obtained monitoring image was analyzed using MATLAB software. Specifically, the imread function was used to read the test block image file, and the size function was used to obtain the image size, which includes the number of rows, columns, and channels of the image. The captured test block image is a color image with 3 channels, that is, the image consists of three color channels: red (R), green (G), and blue (B). The R, G, and B values ​​of specific pixels are obtained by specifying the index of rows and columns. The color perception brightness formula is used to calculate the color of the image. Calculate the brightness value Y of the pixel, where the brightness value Y represents the black and white brightness of a pixel;

[0035] For example, the size function is used to obtain the size information of the image, and the number of rows, columns, and channels of the image are 1080, 1920, and 3, respectively. For the pixel point with coordinates (100, 200) in the image, its R value is 180, G value is 160, and B value is 140. The brightness value Y is calculated by the formula to be 158.6;

[0036] like Figure 2 As shown, the specific steps for obtaining the spark performance value are:

[0037] Compare the brightness value of each pixel in the monitoring image with the brightness threshold;

[0038] If the brightness value of a pixel is less than or equal to the brightness threshold, it means that the pixel in the monitoring image does not belong to the spark range generated by laser cutting;

[0039] If the brightness value of a pixel is greater than the brightness threshold, it means that the pixel in the monitoring image belongs to the spark range generated by laser cutting, and the pixel is marked as a spark pixel;

[0040] Based on any monitoring image, the number of spark pixels in the monitoring image is obtained, and the ratio is processed with the total number of pixels in the monitoring image to obtain the spark number ratio of the monitoring image, which is marked as HG;

[0041] The brightness values ​​of all spark pixels in the monitoring image are summed and averaged to obtain the spark brightness mean of the monitoring image, and the ratio is processed with the brightness threshold to obtain the spark brightness ratio of the monitoring image, which is marked as HL;

[0042] The obtained spark number ratio HG and spark brightness ratio HL are processed and the formula The spark performance value HB of the monitoring image is calculated, where a1 and a2 are both preset proportional coefficients, a1=2.331, a2=1.467;

[0043] Compare the obtained spark performance value with the performance value threshold;

[0044] If the spark performance value of the monitoring image is greater than or equal to the threshold, it means that there are sparks generated by laser cutting in the monitoring image, and the monitoring image is marked as a spark image;

[0045] If the spark performance value of the monitoring image is less than the threshold, it means that there is no spark generated by laser cutting in the monitoring image, and the monitoring image is marked as a spark-free image;

[0046] Exemplarily, the number of spark pixels in the monitoring image is counted as 50,000, which is compared with the total number of pixels in the monitoring image, which is 2,073,600, to obtain a spark number ratio HG of the monitoring image of about 0.0241. The brightness values ​​of all spark pixels are summed and averaged, and the ratio is processed with the brightness threshold, to obtain a spark brightness ratio HL of the monitoring image of about 1.5. The spark performance value HB of the monitoring image is calculated by the formula to be about 2.257. The spark performance value is compared with the performance value threshold, and the performance value threshold is set to be 1.1. Since 2.257>1.1, it means that the infrared picosecond laser is performing laser cutting, and the monitoring image is marked as a spark image;

[0047] Take a flag value flag and set it to 0 at the beginning of each operation cycle, and analyze the simultaneous monitoring image group at the current detection time point;

[0048] If all monitoring images in the monitoring image group are spark-free images and the flag value is 0, it means that the laser cutting system is in a delay state and a delay signal is generated;

[0049] If there is a spark image in the monitoring image group at the same time, it means that the laser cutting system is already in the cutting state, and a cutting signal is generated and the flag value is set to 1;

[0050] It should be noted that the delay state only exists before the cutting state starts, and the purpose of the flag value is to mark the end of the delay state. If the laser cutting system has an abnormal cutting interruption in the cutting state, resulting in no spark images in the simultaneous monitoring image group, the flag value can distinguish it from the delay state;

[0051] The period with a flag value of 0 in the operation cycle is marked as a delay period, and the period with a flag value of 1 in the operation cycle until the current detection time point is marked as a cutting period;

[0052] Step 2: Based on the spark performance value of the monitoring image during the cutting period, determine whether there is a problem in the infrared picosecond laser laser cutting process in the laser cutting system, and mark the period where the problem occurs as the problem period, perform data processing on the problem period to obtain the problem representation value, and determine whether the problem in the infrared picosecond laser laser cutting process is serious according to the problem representation value. If serious, generate a problem analysis signal;

[0053] In some embodiments, based on the marked cutting time period, the laser cutting progress of the laser cutting system is analyzed;

[0054] Specifically, based on any co-location monitoring image group, the spark performance value of the monitoring image of the co-location monitoring image group during the cutting period is obtained, the difference between the value and the performance standard value is processed and the absolute value is taken to obtain the absolute difference of the spark performance of the monitoring image, and the difference is compared with the absolute difference threshold;

[0055] If the absolute difference of the spark performance of the monitoring image is less than or equal to the absolute difference threshold, it means that the spark performance of the monitoring image is normal at this time, and the laser cutting process of the infrared picosecond laser corresponding to the same-position monitoring image group is normal, and a normal cutting signal is generated;

[0056] If the absolute difference of the spark performance of the monitoring image is greater than the absolute difference threshold, it means that the spark performance of the monitoring image is abnormal at this time, and there is a problem in the laser cutting process of the infrared picosecond laser corresponding to the same-position monitoring image group, and a cutting problem signal is generated;

[0057] Take a flag value num and assign it a value of 0 at the beginning of each operation cycle. If a cutting problem signal is generated and the num value is 0, assign the num value to 1. If a cutting normal signal is generated, assign the num value to 0.

[0058] Mark the period when the num value is continuously 1 as a problem period. The continuous num value being 1 means that the num value is 1 at two or more adjacent detection time points. If the num value is 1 and the num value at adjacent detection time points is not 1, then the detection time point with the num value of 1 is marked as a problem period;

[0059] It should be noted that the function of the flag value num is to mark the start and end of any problem period;

[0060] Obtaining the interval duration between adjacent problem periods, and comparing it with an interval duration threshold, wherein the interval duration represents the interval duration between the end point of a previous problem period and the start point of a next problem period;

[0061] If the interval between adjacent problem periods is greater than or equal to the interval threshold, it means that the two problem periods are far apart;

[0062] If the interval between adjacent problem periods is less than the interval threshold, it means that the interval between the two problem periods is close, and the two problem periods are merged into one problem period;

[0063] The comparison is performed on all adjacent problem periods within the cutting period until there are no adjacent problem periods within the cutting period whose interval duration is greater than or equal to the interval duration threshold;

[0064] Based on any problem period, the duration of the problem period is obtained and the ratio of the duration of the problem period to the duration of the cutting period is processed to obtain the problem duration ratio of the problem period, which is marked as WS;

[0065] Obtain the absolute differences of spark performance of all monitoring images in the same-location monitoring image group during the problem period, sum them up and take the average, and obtain the average absolute difference of spark performance during the problem period. Ratio the obtained average absolute difference of spark performance with the absolute difference threshold to obtain the problem degree ratio of the problem period, which is marked as WD.

[0066] Get the number of problem periods within the cutting period, marked as WG;

[0067] The obtained problem duration ratio WS, problem degree ratio WD and the number of problem time periods WG are processed and the formula is used The problem characterization value BZ of the co-located monitoring image group is calculated, where b1 and b2 are both preset proportional coefficients, b1=3.419, b2=0.316;

[0068] Compare the obtained problem representation value with the problem representation threshold;

[0069] If the problem characterization value is less than or equal to the problem characterization threshold, it means that the infrared picosecond laser laser cutting process corresponding to the co-located monitoring image group is normal;

[0070] If the problem characterization value is greater than the problem characterization threshold, it indicates that a serious problem occurs in the laser cutting process of the infrared picosecond laser corresponding to the co-located monitoring image group, and the laser cutting system is suspended at the end of the current operation cycle and a problem analysis signal is generated;

[0071] The technical solution of an embodiment of the present invention is: during the cutting process, a high-speed camera is used to monitor the cutting front in real time and shoot three cutting fronts to obtain a monitoring image, and the brightness value of the pixel points of the monitoring image is analyzed to obtain the spark performance value of the monitoring image, and it is judged whether there are sparks generated by laser cutting in the monitoring image according to the spark performance value, and the operation cycle is divided into a delay period and a cutting period; based on the spark performance value of the monitoring image in the cutting period, it is judged whether there is a problem with the infrared picosecond laser laser cutting process in the laser cutting system, and the period where the problem occurs is marked as a problem period, and the problem period is processed to obtain a problem characterization value, and it is judged whether the problem with the infrared picosecond laser laser cutting process is serious according to the problem characterization value. If serious, a problem analysis signal is generated.

[0072] Embodiment 3: Figure 1 As shown, a method for laser cutting of a large-format battery pole piece provided by an embodiment of the present invention, in the steps described in the first embodiment, the laser cutting process of the large-format battery pole piece is monitored and optimized, and specifically also includes the following steps:

[0073] Step 3: Based on the generated problem analysis signal, construct the spark performance curves in the laser cutting process of each infrared picosecond laser in the laser cutting system, and mark the spark performance curves in the problem period as problem sub-curves, compare and analyze whether there is a time regularity between the problem sub-curves in the cutting period, and generate curve disordered signals and curve ordered signals respectively;

[0074] In some embodiments, based on the generated problem analysis signal, the problem time period of each co-located monitoring image group of the laser cutting system is analyzed at the end of the current operation cycle;

[0075] Specifically, based on any co-location monitoring image group, a spark performance curve of the co-location monitoring image group is constructed with time as the horizontal coordinate and the spark performance value as the vertical coordinate, and the spark performance curve in the problem period is marked as a problem sub-curve, and the problem sub-curve is marked with a serial number according to the time sequence; any two problem sub-curves in the same spark performance curve are analyzed;

[0076] Represent the problem subcurve as a data series: , where n represents the serial number of the problem sub-curve, kni represents the spark performance value corresponding to the problem sub-curve at the i-th detection time point, and m represents the number of detection time points in the problem sub-curve;

[0077] Get the number of detection time points in the two problem sub-curves respectively, perform difference processing on the two and take the absolute value to get the curve length difference, mark it as QC, and compare it with the curve length difference threshold;

[0078] If the curve length difference is greater than or equal to the curve length difference threshold, the two problem sub-curves are judged to be dissimilar;

[0079] If the curve length difference is less than the curve length difference threshold, it is determined that the two problem sub-curves may be similar, and a similarity analysis signal is generated;

[0080] Based on the generated similarity analysis signal, the data sequences corresponding to the two problematic sub-curves are processed to obtain the longer data sequence, delete the QC data at the end of the longer data sequence, unify the lengths of the two data sequences, and calculate the distance using the Euclidean distance formula:

[0081]

[0082] The Euclidean distance between the two data sequences is calculated, wherein c represents the number of problem sub-curves between the two problem sub-curves, and the Euclidean distance represents the similarity between the two data sequences;

[0083] Compare the obtained Euclidean distance of the two data sequences with the distance threshold;

[0084] If the Euclidean distance between two data sequences is greater than or equal to the distance threshold, it means that the two data sequences are not similar;

[0085] If the Euclidean distance between two data sequences is less than the distance threshold, it means that the two data sequences are highly similar, and the problem sub-curves corresponding to the two data sequences are classified into the same problem sub-curve group;

[0086] Performing the analysis on all problematic sub-curves within the same spark performance curve, if there is a problematic sub-curve that is not classified into any problematic sub-curve group, classifying the problematic sub-curve itself into a problematic sub-curve group and marking the problematic sub-curve group as an unordered sub-curve group;

[0087] Based on any problem sub-curve group, obtain the interval durations between the starting points of all adjacent problem sub-curves in the problem sub-curve group, and perform variance processing on them to obtain the interval duration variance;

[0088] Compare the interval duration variance with the variance threshold;

[0089] If the interval time variance is greater than or equal to the variance threshold, it means that there is no time regularity between the problem sub-curves in the problem sub-curve group, and the problem sub-curve group is marked as an unordered sub-curve group;

[0090] If the interval time variance is less than the variance threshold, it means that there is periodicity between the problem sub-curves in the problem sub-curve group, and the problem sub-curve group is marked as an ordered sub-curve group;

[0091] Based on the marked ordered sub-curve group, the interval durations between the starting points of all adjacent problem sub-curves in the ordered sub-curve group are summed and averaged to obtain the similar period of the ordered sub-curve group. The variance of the similar periods of all ordered sub-curve groups in the cutting period is processed to obtain the variance of the similar period, which is marked as XC.

[0092] Obtain the number of all disordered sub-curve groups in the cutting period, and perform ratio processing on it and the number of all problematic sub-curve groups in the cutting period to obtain the curve disorder ratio, which is marked as QW;

[0093] The obtained similar period variance XC and curve disorder ratio QW are processed by data, and the formula is: The disorder analysis value WB in the cutting period is calculated, where s1 and s2 are both preset proportional coefficients, s1=2.137, s2=1.253;

[0094] The obtained disorder analysis value is compared with the disorder analysis threshold;

[0095] If the disorder analysis value is greater than or equal to the disorder analysis threshold, it means that there is no time regularity between the problematic sub-curves within the cutting period, and a curve disorder signal is generated;

[0096] If the disorder analysis value is less than the disorder analysis threshold, it means that there is periodicity between the problematic sub-curves within the cutting period, and the curve is generated with an ordered signal;

[0097] Step 4: judging whether the spark performance in the cutting process of the laser cutting system is orderly based on the generated disordered curve signal and the ordered curve signal, and repairing the laser cutting system or adjusting and optimizing the parameters according to the judgment result;

[0098] In some embodiments, if any co-located monitoring image group generates a curve disorder signal, it is determined that the spark performance in the cutting process of the laser cutting system is disordered, and a repairman is arranged to repair the laser cutting system;

[0099] If the three co-located monitoring image groups in the laser cutting system all generate orderly curve signals, it is judged that the sparks in the cutting process of the laser cutting system are orderly. According to the periodic law reflected by the ordered sub-curve group, the pulse frequency setting of the pulse laser is checked, and the pulse frequency is fine-tuned in small steps to optimize and adjust the parameters.

[0100] The technical solution of the embodiment of the present invention is: based on the generated problem analysis signal, construct the spark performance curve of each infrared picosecond laser in the laser cutting process of the laser cutting system, and mark the spark performance curve in the problem period as a problem sub-curve, compare and analyze whether there is a time regularity between the problem sub-curves in the cutting period, and generate a curve disorder signal and a curve ordered signal respectively; based on the generated curve disorder signal and curve ordered signal, judge whether the spark performance in the cutting process of the laser cutting system is orderly, and repair the laser cutting system or adjust the parameters for optimization according to the judgment result.

[0101] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0102] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A method for laser cutting of large-format battery pole pieces, characterized in that: It includes the steps of building a laser cutting system, fixing the pole piece, feeding and focusing the platform, editing the drawing, setting parameters, executing the cutting and optimizing the process monitoring, among which the process monitoring optimization includes the following steps: Real-time monitoring and shooting of three cutting fronts to obtain monitoring images, data analysis of the brightness values ​​of the pixels in the monitoring images to obtain the spark performance values ​​of the monitoring images, and dividing the operation cycle into a delay period and a cutting period; Based on the spark performance value of the monitoring image during the cutting period, it is judged whether there is a problem in the laser cutting process of the infrared picosecond laser in the laser cutting system, and the period where the problem occurs is marked as the problem period, and the data of the problem period is processed to obtain the problem representation value, and the problem analysis signal is generated; Based on the generated problem analysis signal, the spark performance curves of each infrared picosecond laser in the laser cutting system during the laser cutting process are constructed, and the spark performance curves in the problem period are marked as problem sub-curves. The problem sub-curves in the cutting period are compared and analyzed to see whether there is a time regularity, and the curve disordered signal and the curve ordered signal are generated respectively. Based on the generated disordered curve signal and ordered curve signal, it is judged whether the spark performance in the cutting process of the laser cutting system is orderly, and the laser cutting system is repaired or the parameters are adjusted and optimized according to the judgment result.

2. The method for laser cutting of large-format battery pole pieces according to claim 1, characterized in that: The specific method of dividing the operation cycle into the delay period and the cutting period is: Compare the obtained spark performance value with the performance value threshold; If the spark performance value of the monitoring image is greater than or equal to the threshold, the monitoring image is marked as a spark image; if the spark performance value of the monitoring image is less than the threshold, the monitoring image is marked as a non-spark image; Take a flag value flag and assign it a value of 0 at the beginning of each operation cycle, analyze the simultaneous monitoring image group at the current detection time point, and generate a delay signal if all the monitoring images in the simultaneous monitoring image group are spark-free images and the flag value is 0; if there is a spark image in the simultaneous monitoring image group, generate a cutting signal and assign the flag value to 1; The period in which the flag value is 0 in the operation cycle is marked as the delay period, and the period in which the flag value is 1 in the operation cycle until the current detection time point is marked as the cutting period.

3. The method for laser cutting of large-format battery pole pieces according to claim 2, characterized in that: The specific method of obtaining the spark performance value is: Compare the brightness value of each pixel in the monitoring image with the brightness threshold; If the brightness value of a pixel is greater than the brightness threshold, the pixel is marked as a spark pixel; Based on any monitoring image, the spark number ratio of the monitoring image is calculated and marked as HG; The brightness values ​​of all spark pixels in the monitoring image are processed to obtain the spark brightness ratio of the monitoring image, which is marked as HL; The obtained spark number ratio HG and spark brightness ratio HL are processed, and the spark performance value HB of the monitoring image is calculated by the formula.

4. The method for laser cutting of large-format battery pole pieces according to claim 2, characterized in that: The specific method of acquiring the simultaneous monitoring image group is: Evenly select several detection time points during the operation cycle; The three cutting fronts are photographed simultaneously at the current detection time point by a high-speed camera, the photographed image is marked as a monitoring image, and the monitoring images taken at the same detection time point are grouped into a simultaneous monitoring image group, and the monitoring images taken by the same high-speed camera are grouped into a co-located monitoring image group, and the monitoring images are all the same size.

5. The method for laser cutting of large-format battery pole pieces according to claim 1, characterized in that: The specific method of obtaining the problem analysis signal is as follows: Based on any problem period, the problem duration ratio of the problem period is calculated and marked as WS; The problem degree ratio of the problem period is calculated and marked as WD; Get the number of problem periods within the cutting period, marked as WG; The obtained problem duration ratio WS, problem degree ratio WD and number of problem time periods WG are processed, and the problem characterization value BZ of the same-location monitoring image group is calculated by the formula; Compare the obtained problem representation value with the problem representation threshold; If the problem characterization value is greater than the problem characterization threshold, a problem analysis signal is generated.

6. The method for laser cutting of large-format battery pole pieces according to claim 5, characterized in that: The specific method of obtaining the problem period is as follows: Take a flag value num and assign it a value of 0 at the beginning of each operation cycle. If a cutting problem signal is generated and the num value is 0, assign the num value to 1. If a cutting normal signal is generated, assign the num value to 0. Mark the period in which the num value is continuously 1 as a problem period; Obtain the interval duration between adjacent problem periods and compare it with the interval duration threshold; If the interval between adjacent problem periods is less than the interval threshold, the two problem periods are merged into one problem period; Compare and merge all adjacent problem periods within the cutting period.

7. The method for laser cutting of large-format battery pole pieces according to claim 6, characterized in that: The specific method of obtaining the cutting problem signal and the cutting normal signal is as follows: Based on any co-located monitoring image group, the absolute difference of the spark performance of the monitoring image is calculated and compared with the absolute difference threshold; If the absolute difference of the spark performance of the monitoring image is less than or equal to the absolute difference threshold, a normal cutting signal is generated; If the absolute difference of the spark performance of the monitoring image is greater than the absolute difference threshold, a cutting problem signal is generated.

8. The method for laser cutting of large-format battery pole pieces according to claim 1, characterized in that: The specific method of obtaining the curve disordered signal and the curve ordered signal is: Based on the marked ordered sub-curve group, the similar period variance is calculated and marked as XC; Get the number of all disordered sub-curve groups within the cutting period, and calculate the curve disorder ratio, marked as QW; The obtained similar period variance XC and curve disorder ratio QW are processed, and the disorder analysis value WB in the cutting period is calculated by the formula; The obtained disorder analysis value is compared with the disorder analysis threshold; If the disorder analysis value is greater than or equal to the disorder analysis threshold, a curve disorder signal is generated; If the disorder analysis value is less than the disorder analysis threshold, a curve ordered signal is generated.

9. The method for laser cutting of large-format battery pole pieces according to claim 8, characterized in that: The specific method of obtaining the ordered sub-curve group and the unordered sub-curve group is: Based on the generated similarity analysis signal, the longer data sequence is obtained, QC data at the end of the longer data sequence is deleted, and after unifying the lengths of the two data sequences, the Euclidean distance of the two data sequences is calculated using the Euclidean distance calculation formula; Compare the obtained Euclidean distance of the two data sequences with the distance threshold; If the Euclidean distance between two data sequences is less than the distance threshold, the problem sub-curves corresponding to the two data sequences are classified into the same problem sub-curve group; Analyze all the problem sub-curves in the same spark performance curve, and mark the problem sub-curve group as an unordered sub-curve group; Based on any problem sub-curve group, the interval duration variance is calculated, and the interval duration variance is compared with the variance threshold; If the interval duration variance is greater than or equal to the variance threshold, the problematic sub-curve group is marked as an unordered sub-curve group; If the interval duration variance is less than the variance threshold, the problematic sub-curve group is marked as an ordered sub-curve group.

10. The method for laser cutting of large-format battery pole pieces according to claim 9, characterized in that: The specific method of obtaining the similarity analysis signal is: Based on any co-location monitoring image group, a spark performance curve of the co-location monitoring image group is constructed with time as the horizontal coordinate and the spark performance value as the vertical coordinate, and the spark performance curve in the problem period is marked as a problem sub-curve, and the problem sub-curve is marked with a serial number according to the time sequence, and any two problem sub-curves in the same spark performance curve are analyzed; Represent the problem subcurve as a data series , where n represents the serial number of the problem sub-curve, kni represents the spark performance value corresponding to the problem sub-curve at the i-th detection time point, and m represents the number of detection time points in the problem sub-curve; Get the number of detection time points in the two problem sub-curves respectively, perform difference processing on the two and take the absolute value to get the curve length difference, mark it as QC, and compare it with the curve length difference threshold; If the curve length difference is less than the curve length difference threshold, it is determined that the two problem sub-curves may be similar, and a similarity analysis signal is generated.

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