CN112676676A - Tab welding method - Google Patents
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- CN112676676A CN112676676A CN202011487707.1A CN202011487707A CN112676676A CN 112676676 A CN112676676 A CN 112676676A CN 202011487707 A CN202011487707 A CN 202011487707A CN 112676676 A CN112676676 A CN 112676676A
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- 238000003466 welding Methods 0.000 title claims abstract description 188
- 238000000034 method Methods 0.000 title claims abstract description 85
- 230000008569 process Effects 0.000 claims abstract description 39
- 239000000463 material Substances 0.000 claims abstract description 26
- 238000012545 processing Methods 0.000 claims abstract description 25
- 239000007788 liquid Substances 0.000 claims abstract description 7
- 230000035515 penetration Effects 0.000 claims description 20
- 238000001514 detection method Methods 0.000 claims description 15
- 230000007547 defect Effects 0.000 claims description 14
- 230000005236 sound signal Effects 0.000 claims description 10
- 230000004927 fusion Effects 0.000 claims description 6
- 230000008859 change Effects 0.000 claims description 3
- 230000003287 optical effect Effects 0.000 claims description 3
- 230000010355 oscillation Effects 0.000 claims description 3
- 239000002893 slag Substances 0.000 claims description 3
- 230000005856 abnormality Effects 0.000 claims 1
- 238000004458 analytical method Methods 0.000 description 3
- 238000004880 explosion Methods 0.000 description 3
- 230000008676 import Effects 0.000 description 3
- 238000004519 manufacturing process Methods 0.000 description 3
- 238000011897 real-time detection Methods 0.000 description 3
- 230000002159 abnormal effect Effects 0.000 description 2
- 238000013145 classification model Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 238000010891 electric arc Methods 0.000 description 2
- 238000003756 stirring Methods 0.000 description 2
- HBBGRARXTFLTSG-UHFFFAOYSA-N Lithium ion Chemical compound [Li+] HBBGRARXTFLTSG-UHFFFAOYSA-N 0.000 description 1
- 238000013528 artificial neural network Methods 0.000 description 1
- 230000003749 cleanliness Effects 0.000 description 1
- 238000012937 correction Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000011143 downstream manufacturing Methods 0.000 description 1
- 230000017525 heat dissipation Effects 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 210000001503 joint Anatomy 0.000 description 1
- 229910001416 lithium ion Inorganic materials 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000011148 porous material Substances 0.000 description 1
- 238000007789 sealing Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/10—Energy storage using batteries
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Abstract
The invention provides a tab welding method, which comprises the following steps: acquiring a first image of a pre-weld region, and processing and analyzing the first image to obtain related data; processing and analyzing the related data in real time to guide real-time online adjustment of laser welding process parameters; wherein the relevant data includes one or more of a height of material, a surface finish, and weld coordinates. Processing and analyzing the first image of the pre-welding area to obtain necessary pre-welding information, so that the laser welding process parameters are adjusted in real time, the influence of material warping on welding quality is reduced, and real-time welding seam tracking is realized; the problem of welding partially because of the assembly error identification that leads to not in place when solving notes liquid hole welding.
Description
Technical Field
The invention relates to the technical field of battery assembly, in particular to a tab welding method.
Background
With the development of new energy industry, electric vehicles are more and more widely applied. The soft package lithium ion battery has the advantages of light weight, high specific capacity, good safety performance, small internal resistance, flexible design and the like, and is widely used in the market. Of course, the endurance mileage, the stability and the safety of the battery of the electric vehicle are receiving more and more attention. How to improve the endurance mileage of the electric automobile, improve the energy density of the power battery, improve the safety of the power battery, and improve the heat dissipation capacity of the single battery becomes the key for the development of the electric automobile in future.
In the process of manufacturing the battery cell module, the tab of the battery cell needs to be welded to the current collecting disc, and the poor welding of the tab and the current collecting disc often occurs in the tab welding process. Products with poor welding are put into use, which can cause large internal resistance, high temperature and even welding falling and ignition in the using process, and the performance and the safety of the power battery can be greatly influenced.
Disclosure of Invention
The invention provides a tab welding method, which is used for solving the defect that poor welding of a tab and a current collecting plate frequently occurs in a tab welding process in the prior art.
The invention provides a tab welding method, which comprises the following steps:
acquiring a first image of a pre-weld region, and processing and analyzing the first image to obtain related data;
processing and analyzing the related data in real time to guide real-time online adjustment of laser welding process parameters;
wherein the relevant data includes one or more of a height of material, a surface finish, and weld coordinates.
According to the tab welding method provided by the invention, the tab welding method further comprises the following steps:
detecting the distance value between the tab and the welding head;
and comparing the distance value with a preset reference value to obtain a comparison result, and adjusting the welding focal length based on the comparison result.
According to the tab welding method provided by the invention, the tab welding method further comprises the following steps:
acquiring weld width data and real-time penetration data of a keyhole in a welding process;
and processing and analyzing the real-time penetration data and the weld width data in real time so as to guide real-time online adjustment of the laser welding process parameters.
According to the tab welding method provided by the invention, the tab welding method further comprises the following steps:
and acquiring a sound signal in the welding process, and processing and analyzing the sound signal to obtain a first type of the welding defect.
According to the pole lug welding method provided by the invention, the sound signal is a welding sound signal caused by pressure stirring of plasma sprayed from a small hole in a small hole mode in a welding process, a welding sound signal generated by continuous impact of a molten pool and high-frequency oscillation of the inner part of an electric arc in an electric arc welding process or an internal sound signal generated by material redistribution caused by change of the inner structure of a material.
According to the tab welding method provided by the invention, the first type comprises one or more of internal pores, slag inclusion, internal cracks, lack of penetration and lack of fusion.
According to the tab welding method provided by the invention, the acquisition mode of the real-time penetration data is as follows:
and emitting detection laser into the liquid molten pool and receiving the reflected signal, and acquiring the real-time fusion depth data in the welding process by using an optical coherence principle.
According to the tab welding method provided by the invention, when the real-time penetration data exceeds the set value range, an abnormal welding seam alarm is sent out.
According to the tab welding method provided by the invention, the tab welding method further comprises the following steps:
acquiring a second image of the welded area, and processing and analyzing the second image to obtain a second type of the welding defect;
wherein the second type includes one or more of a skip weld, a flash point, and a pinhole.
According to the tab welding method provided by the invention, the tab welding method further comprises the following steps:
acquiring the height of the surface after welding and the roughness of the surface after welding;
and processing and analyzing the height of the surface after welding and the roughness of the surface after welding so as to guide the real-time online adjustment of the parameters of the laser welding process.
According to the tab welding method provided by the invention, the first image of the area before welding is processed and analyzed to obtain necessary information before welding, so that the laser welding process parameters are adjusted in real time, the influence of material warping on welding quality is reduced, and real-time seam tracking is realized; the problem of welding partially because of the assembly error identification that leads to not in place when solving notes liquid hole welding.
Drawings
In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings needed for the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
Fig. 1 is a flow chart of a tab welding method provided by the present invention;
fig. 2 is an appearance diagram of the tab welding provided by the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The tab welding method of the present invention will be described with reference to fig. 1 to 2. The tab welding method comprises pre-welding detection, in-welding detection and post-welding detection.
As shown in fig. 1, a tab welding method according to an embodiment of the present invention includes:
s10, acquiring a first image of the pre-welding area, and processing and analyzing the first image to obtain related data;
s20, processing and analyzing the relevant data in real time to guide real-time online adjustment of the laser welding process parameters;
wherein the relevant data includes one or more of a height of the material, a surface finish, and weld coordinates.
It should be noted that the material height, the material surface finish and the weld position are mainly detected before welding. The method comprises the steps of obtaining a material height, obtaining a material surface finish, obtaining a welding seam position, and comparing the obtained material height with a preset material height, the obtained material surface finish with a preset material surface finish, and the obtained welding seam position with a preset welding seam position, so that the method is used for guiding real-time online adjustment of laser welding process parameters.
It can be understood that image acquisition and processing are carried out on the pre-welding area based on the modes of process optics, machine vision and the like, and data such as the height, the surface finish degree, the welding seam coordinate and the like of the material are obtained; and the detected data is processed and analyzed in real time through the intelligent laser welding system and is used for guiding the real-time online adjustment of the laser welding process parameters. Wherein the machine vision system comprises a camera and a light source.
In the embodiment of the invention, the first image of the area before welding is processed and analyzed to obtain necessary information before welding, so that the parameters of the laser welding process are adjusted in real time, the influence of material warping on the welding quality is reduced, and real-time welding seam tracking is realized; the problem of welding partially because of the assembly error identification that leads to not in place when solving notes liquid hole welding.
Acquiring data through an API (application programming interface) of an integrated import matching system, processing and analyzing the data in an intelligent laser welding system, and actively adjusting the movement track of a butt joint; real-time detection may be performed in a coaxial/paraxial manner with the weld head.
On the basis of the above embodiment, the tab welding method further includes:
detecting the distance value between the tab and the welding head;
and comparing the distance value with a preset reference value to obtain a comparison result, and adjusting the welding focal length based on the comparison result.
It should be noted that, in the pre-welding detection, the height measuring sensor is used to detect the distance between the tab and the welding head and compare the distance with a reference value, and if the distance is not equal to the reference value, the welding focal length is changed until the distance is the same, so as to adjust the distance to the accurate welding position, thereby improving the welding quality.
On the basis of the above embodiment, the tab welding method further includes:
acquiring weld width data and real-time penetration data of a keyhole in a welding process;
and processing and analyzing the real-time penetration data and the weld width data in real time so as to guide the real-time online adjustment of the laser welding process parameters.
The penetration is a distance between the deepest position of the molten portion of the base material and the surface of the base material.
It should be noted that, the laser welding penetration on-line detection system based on structured light vision obtains the real-time penetration data of the keyhole in the welding process, and the detected real-time penetration data and the weld width data are processed and analyzed in real time through the intelligent laser welding system, i.e. the decisive parameter data of the laser welding quality is obtained, so as to adjust the laser welding process parameters in real time.
It can be understood that when the tab is subjected to laser welding, welding parameters can be properly increased, welding penetration is increased, production efficiency is improved, and production cost is reduced.
In the embodiment of the invention, data are acquired through an API (application programming interface) of an integrated import matching system, data processing and analysis are carried out in an intelligent laser welding system, and laser process parameters are actively adjusted; real-time detection may be performed in a coaxial/paraxial manner with the weld head.
On the basis of the above embodiment, the tab welding method further includes:
and acquiring a sound signal in the welding process, and processing and analyzing the sound signal to obtain a first type of the welding defect.
It should be noted that the acoustic signal is a welding acoustic signal caused by pressure stirring of plasma ejected from a small hole in a small hole mode during welding, a welding acoustic signal generated by continuous impact of a molten pool and high-frequency oscillation of the inside of an arc during arc welding, or an internal acoustic signal generated by material redistribution due to a change in the internal structure of a material.
It is understood that the first type includes one or more of internal porosity, slag inclusions, internal cracks, lack of penetration, and lack of fusion.
In the embodiment of the invention, the waveform analysis of a time domain, a frequency domain and a time-frequency domain is carried out on a large amount of collected acoustic signal data by adopting Fourier transform, wavelet transform and S transform, a welding defect identification and classification model is constructed by combining with an RNN neural network, and then the acoustic signal collected in the detection process is input into the welding defect identification and classification model to obtain the first type of the welding defect.
On the basis of the above embodiment, the real-time penetration data is obtained by the following specific method:
and emitting detection laser into the liquid molten pool and receiving the reflected signal, and acquiring real-time fusion depth data in the welding process by using an optical coherence principle.
It should be noted that when the real-time penetration data exceeds the set value range, an abnormal welding seam alarm can be given.
On the basis of the above embodiment, the tab welding method further includes:
collecting a second image of the welded area, and processing and analyzing the second image to obtain a second type of the welding defect;
wherein the second type includes one or more of a skip weld, a flash point, and a pinhole.
In the embodiment of the invention, the recognition of NG conditions such as missing welding, explosion points, pinholes and the like after laser welding is researched based on computer vision, so that the problems of detection of the number of welding spots and detection of explosion points and missing welding defects of the laser welding of the current collecting plate are solved; the detection problems of weld joint explosion, welding leakage and pinhole defects in sealing welding and liquid filling hole welding are solved.
It should be noted that the speckle images on the weld joint are collected, and the real appearance profile of the weld joint is obtained by combining the result of camera calibration. And reconstructing a three-dimensional model of the welding seam through a three-dimensional reconstruction algorithm according to the second type of the welding defect and the real appearance profile of the welding seam, thereby obtaining a three-dimensional model image of the welding quality detection result.
On the basis of the above embodiment, the tab welding method further includes:
acquiring the height of the surface after welding and the roughness of the surface after welding;
and (4) processing and analyzing the height of the surface after welding and the roughness of the surface after welding so as to guide the real-time online adjustment of the parameters of the laser welding process.
The height of the surface after laser welding and the roughness of the surface after welding are obtained based on process optics and machine vision, and detection data are processed and analyzed in real time through an intelligent laser welding system and are used for guiding real-time online adjustment of laser welding process parameters and recording, verifying and reporting of the process parameters.
In the embodiment of the invention, the online detection of the surface quality of the laser welding is realized, and the extra step of surface inspection after welding is eliminated; preventing welding defects from causing more waste in downstream processes.
It can be understood that data are acquired through an API (application programming interface) of the integrated import matching system, and data processing and analysis are carried out in the intelligent laser welding system; real-time detection may be performed in a coaxial/paraxial manner with the weld head.
As shown in fig. 2, the tab welding method provided by the embodiment of the invention has the advantages of high welding efficiency, large welding breadth and higher requirements on assembly of the product; by adopting a 1500 w-based mode laser, a galvanometer welding head and a refrigerating machine, each welding position can be welded with a plurality of tracks, the welding appearance is good, and the welding strength is high.
According to the tab welding method provided by the embodiment of the invention, the surface cleanliness, the smoothness and the weld width of the material can be adjusted before welding, and the method is used for guiding the real-time online adjustment of the laser welding process parameters; acquiring the depth of a molten pool in welding, and judging the quality according to different thickness attributes of different materials; and performing postweld automatic compensation and tracking after welding, such as welding deviation correction and the like.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A tab welding method is characterized by comprising the following steps:
acquiring a first image of a pre-weld region, and processing and analyzing the first image to obtain related data;
processing and analyzing the related data in real time to guide real-time online adjustment of laser welding process parameters;
wherein the relevant data includes one or more of a height of material, a surface finish, and weld coordinates.
2. The tab welding method as claimed in claim 1, further comprising:
detecting the distance value between the tab and the welding head;
and comparing the distance value with a preset reference value to obtain a comparison result, and adjusting the welding focal length based on the comparison result.
3. The tab welding method as set forth in claim 1 or 2, further comprising:
acquiring weld width data and real-time penetration data of a keyhole in a welding process;
and processing and analyzing the real-time penetration data and the weld width data in real time so as to guide real-time online adjustment of the laser welding process parameters.
4. The tab welding method as claimed in claim 3, further comprising:
and acquiring a sound signal in the welding process, and processing and analyzing the sound signal to obtain a first type of the welding defect.
5. The tab welding method as set forth in claim 4, wherein the acoustic signal is a welding acoustic signal caused by a pressure toggle of a plasma jetted from the keyhole in a keyhole mode during welding, a welding acoustic signal generated due to a continuous impact of a molten pool and a high frequency oscillation of an arc interior itself during arc welding, or an internal acoustic signal in which mechanical energy is converted into acoustic energy due to a material redistribution caused by a change in an internal structure of the material.
6. The method of welding the tab as claimed in claim 4, wherein the first type includes one or more of internal porosity, slag inclusions, internal cracks, lack of penetration, and lack of fusion.
7. The tab welding method according to claim 3, wherein the real-time penetration data is obtained by:
and emitting detection laser into the liquid molten pool and receiving the reflected signal, and acquiring the real-time fusion depth data in the welding process by using an optical coherence principle.
8. The tab welding method according to claim 3, wherein when the real-time penetration data exceeds a set value range, a weld abnormality alarm is issued.
9. The tab welding method as set forth in claim 1 or 2, further comprising:
acquiring a second image of the welded area, and processing and analyzing the second image to obtain a second type of the welding defect;
wherein the second type includes one or more of a skip weld, a flash point, and a pinhole.
10. The tab welding method as claimed in claim 9, further comprising:
acquiring the height of the surface after welding and the roughness of the surface after welding;
and processing and analyzing the height of the surface after welding and the roughness of the surface after welding so as to guide the real-time online adjustment of the parameters of the laser welding process.
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|---|---|---|---|---|
| JP2022505531A (en) * | 2018-11-13 | 2022-01-14 | リヴィアン アイピー ホールディングス，エルエルシー | A method for welding one or more weld points on a frame, visual system, and battery for weld location detection in a battery cell pack. |
| JP7098058B2 (en) | 2018-11-13 | 2022-07-08 | リヴィアン アイピー ホールディングス，エルエルシー | A method for welding one or more weld points on a frame, visual system, and battery for weld location detection in a battery cell pack. |
| US11890705B2 (en) | 2018-11-13 | 2024-02-06 | Rivian Ip Holdings, Llc | Weld location detection in a battery cell pack |
| CN115347332A (en) * | 2022-10-18 | 2022-11-15 | 宁德新能源科技有限公司 | Electrochemical device and electric equipment |
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Application publication date: 20210420 |