CN116559298B - Battery welding quality detection method and device - Google Patents
Battery welding quality detection method and device Download PDFInfo
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- CN116559298B CN116559298B CN202310847608.7A CN202310847608A CN116559298B CN 116559298 B CN116559298 B CN 116559298B CN 202310847608 A CN202310847608 A CN 202310847608A CN 116559298 B CN116559298 B CN 116559298B
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- 238000003466 welding Methods 0.000 title claims abstract description 130
- 238000001514 detection method Methods 0.000 title claims abstract description 54
- 230000007547 defect Effects 0.000 claims description 18
- 238000000034 method Methods 0.000 claims description 8
- 238000004458 analytical method Methods 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 claims description 3
- 238000005530 etching Methods 0.000 claims description 3
- 238000002474 experimental method Methods 0.000 claims description 3
- 230000011218 segmentation Effects 0.000 claims description 3
- 230000005540 biological transmission Effects 0.000 abstract description 4
- 230000004075 alteration Effects 0.000 description 2
- 238000007789 sealing Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
- G01N21/956—Inspecting patterns on the surface of objects
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/04—Analysing solids
- G01N29/045—Analysing solids by imparting shocks to the workpiece and detecting the vibrations or the acoustic waves caused by the shocks
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
- G01N29/44—Processing the detected response signal, e.g. electronic circuits specially adapted therefor
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/20—Image enhancement or restoration by the use of local operators
- G06T5/30—Erosion or dilatation, e.g. thinning
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/136—Segmentation; Edge detection involving thresholding
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
- G01N2021/8887—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
- G06T2207/30152—Solder
-
- 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
Abstract
The invention discloses a battery welding quality detection method, which belongs to the field of batteries, wherein a detection piece is attached to a welding point to form a closed space, the closed space is inflated to burn-through, the virtual welding is detected through vibration transmission, the high protrusion detection of welding materials is performed through collecting an image in the thickness direction (the height direction of the welding point) of a bus bar, the problem that the pixel difference of the image of the welding point caused by the laser welding of the bus bar is small can be solved, and the battery welding quality detection is realized. The invention also relates to a battery welding quality detection device for implementing the battery welding quality detection method.
Description
Technical Field
The invention relates to the field of batteries, in particular to a battery welding quality detection method and device.
Background
At present, a battery pack is used as a power source of an electric automobile, and in the production process, a plurality of electric cores are required to be connected in series or in parallel in a mode of welding a busbar and a pole of each electric core, so that a plurality of small-capacity electric cores form a large-capacity electric core group, and electric transmission is realized.
The welded bus bar needs to detect the welding quality of the welding point, and patent CN113744269B discloses a method for judging the welding quality by collecting an image of the welding point, but the method is applicable to the fact that the material of a welding material (such as a welding rod) and the material of a current collecting disc of a cylindrical battery core have obvious differences, and the welding quality can be judged by the obvious differences of pixel values of a welding point area, but when the bus bar adopts laser welding, no welding rod exists, and the bus bar is melted to realize connection, so that the difference of image pixels is not large, and when the method for judging the welding quality by adopting the image is applied to the laser welding, the accuracy is poor, and particularly the burn-through defect is overcome.
Disclosure of Invention
In order to overcome the defects of the prior art, one of the purposes of the invention is to provide a welding quality detection method for bus bar laser welding when the difference of image pixels is small.
In order to overcome the defects of the prior art, the second aim of the invention is to provide welding quality detection equipment for bus bar laser welding when the difference of image pixels is small.
One of the purposes of the invention is realized by adopting the following technical scheme:
a battery welding quality detection method comprises the following steps:
s1: attaching a detection piece with an opening to a welding point of a busbar, forming a closed space by the detection piece and a part of the busbar with the welding point, filling gas into the closed space for a period of time, and measuring the gas pressure in the closed space, wherein when the gas pressure is kept unchanged, no burn-through defect exists; when the air pressure is reduced, burn-through defects exist;
s2: arranging a plurality of sensors on the electrode lugs, wherein the plurality of sensors are symmetrical about welding points, regularly knocking the bus without the cold joint and the cold joint, collecting data of the plurality of sensors, calculating the propagation speed of vibration in the bus according to the time difference of signals received by the plurality of sensors, building a vibration model according to the propagation speed and the signals received by the sensors, training the vibration model, detecting the bus after the welding is knocked by a piece, and judging whether the cold joint exists or not according to the collected vibration data of the electrode lugs by the vibration model;
s3: collecting a busbar welding point image along the thickness direction of the busbar, performing closed operation on the image, analyzing the welding point to be detected by using threshold segmentation after the closed operation, dividing the welding point and the background according to the threshold value through analysis, and counting the pixel value of the welding point threshold value; and calculating the height of the welding point according to the pixel value occupied by the welding point threshold value, and judging whether the high-salient defect of the welding material exists.
Further, in step S1, the maximum pressure value of the enclosed space is smaller than a preset value, where the preset value is obtained by experiments, so that the excessive pressure of the enclosed space is avoided, and the unburned welding point is extruded through.
Further, in step S2, vibration is applied to the bus bar above each sensor, and each vibration is generated, the signals received by n sensors are C n 2 Two by two time differences according to C between n sensors n 2 Two-by-two distance differences, corresponding C is calculated n 2 The propagation speed can be obtained by applying m times of vibration at different positions n 2 The average value of the propagation speeds is taken as the final propagation speed.
Further, in step S2, training the vibration model specifically includes training the welding points with different sizes, so that the vibration model is applicable to the welding points with different sizes.
Further, in step S2, the striking position of the detecting member when striking the welded busbar is any position other than the welding point on the welded busbar.
Further, in step S3, a background plate is further disposed, where the background plate is located at a side portion of the busbar, and a color of the background plate is different from a color of the busbar and a color of the welding point, so as to form a chromatic aberration.
Further, in step S3, the use of the closed operation for the image specifically includes the steps of:
selecting the shape and the size of a mask, and performing binary expansion operation on an image target area;
selecting the shape and the size of a mask, and performing binary etching operation on an image target area;
and performing difference set operation on the binary image.
Further, the inflated binary image is denoted as I mld The corroded binary image is designated as I mle The difference image is denoted as I ls The specific difference set calculation method comprises the following steps: i mld -I ml 、I mld -I mle 、I ml -I mle Any one of the following.
The second purpose of the invention is realized by adopting the following technical scheme:
the battery welding quality detection device is used for implementing any one of the battery welding quality detection methods, and comprises a detection piece, an air pressure sensor, a processor, a camera and a vibration sensor, wherein the air pressure sensor is arranged in the detection piece and positioned in the detection piece, the vibration sensor is arranged on a welded battery cell tab, the vibration sensor, the air pressure sensor and the camera are electrically connected with the processor, the detection piece is attached to a welding point of a busbar, and a closed space is formed between the detection piece and a part of busbar with the welding point.
Compared with the prior art, the method for detecting the welding quality of the battery forms a closed space through the detection piece, the burning-through detection is carried out on the inflation of the closed space, the cold joint detection is carried out through vibration transmission, the high-prominence detection of the welding seam material is carried out through collecting the images in the thickness direction (the height direction of the welding point) of the bus bar, and through the steps, the problem that the pixel difference of the image of the welding point caused by the laser welding of the bus bar is small can be solved, so that the detection of the welding quality of the battery is realized.
Drawings
Fig. 1 is a flowchart of a battery welding quality detection method according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It will be understood that when an element is referred to as being "fixed to" another element, it can be directly on the other element or be present as another intermediate element through which the element is fixed. When an element is referred to as being "connected" to another element, it can be directly connected to the other element or intervening elements may also be present. When an element is referred to as being "disposed on" another element, it can be directly on the other element or intervening elements may also be present. The terms "vertical," "horizontal," "left," "right," and the like are used herein for illustrative purposes only.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.
As shown in fig. 1, the method for detecting the welding quality of the battery comprises the following steps:
s1: attaching a detection piece with an opening to a welding point of a busbar, forming a closed space by the detection piece and a part of the busbar with the welding point, filling gas into the closed space for a period of time, and measuring the gas pressure in the closed space, wherein when the gas pressure is kept unchanged, no burn-through defect exists; when the air pressure is reduced, burn-through defects exist;
s2: arranging a plurality of sensors on the electrode lugs, wherein the plurality of sensors are symmetrical about welding points, regularly knocking the bus without the cold joint and the cold joint, collecting data of the plurality of sensors, calculating the propagation speed of vibration in the bus according to the time difference of signals received by the plurality of sensors, building a vibration model according to the propagation speed and the signals received by the sensors, training the vibration model, detecting the bus after the welding is knocked by a piece, and judging whether the cold joint exists or not according to the collected vibration data of the electrode lugs by the vibration model;
s3: collecting a busbar welding point image along the thickness direction of the busbar, performing closed operation on the image, analyzing the welding point to be detected by using threshold segmentation after the closed operation, dividing the welding point and the background according to the threshold value through analysis, and counting the pixel value of the welding point threshold value; and calculating the height of the welding point according to the pixel value occupied by the welding point threshold value, and judging whether the high-salient defect of the welding material exists.
Specifically, in step S1, the end of the detecting element abuts against the surface of the busbar through the sealing ring, so as to form a closed space, and sealing is achieved. The inner wall of the detection part is provided with air holes, the detection part is of a hollow structure, the inside of the detection part is connected with an air source through the air holes, and the air source charges air into the closed space through the air holes. The air pressure sensor is arranged on the detection piece and is used for detecting the air pressure in the closed space. At the welding point of the busbar surface, a welding hole is usually provided for positioning at the time of welding. The welding points are also located at the welding holes, and in this embodiment, the welding tracks are round and encircle the welding holes. The weld holes can also provide positioning for the inspection piece to inspect. In this embodiment, the detecting member is cylindrical, and the inner diameter of the detecting member is 4-7mm larger than the outer diameter of the welding track. In the process of filling gas, the maximum pressure value of the airtight space is smaller than a preset value, the preset value is obtained through experiments, the condition that the pressure of the airtight space is too high is avoided, the unburned welding points are extruded and penetrated, and the bus bar without burning-through defects is damaged at the welding positions due to the fact that the gas pressure is too high is caused.
Specifically, in step S2, vibration is applied to the bus bar above each sensor, and each vibration is performed such that the signals received by n sensors are C n 2 Two by two time differences according to C between n sensors n 2 Two-by-two distance differences, corresponding C is calculated n 2 The propagation speed can be obtained by applying m times of vibration at different positions n 2 The average value of the propagation speeds is taken as the final propagation speed. Training the vibration model specifically includes training the welding points of different sizes, so that the vibration model is applicable to the welding points of different sizes. The knocking position of the detecting piece when knocking the welded busbar is any other position except the welding point on the welded busbar, so that the influence on the welding quality of the welding point due to knocking the welding point during detection is avoided.
Specifically, in step S3, a background plate is further disposed, where the background plate is located at a side portion of the busbar, and a color of the background plate is different from a color of the busbar and a color of the welding point, so as to form a color difference. Calculating the height of the welding point through chromatic aberration, specifically using a closed operation on the image, wherein the closed operation comprises the following steps:
selecting the shape and the size of a mask, and performing binary expansion operation on an image target area;
selecting the shape and the size of a mask, and performing binary etching operation on an image target area;
and performing difference set operation on the binary image.
The expanded binary image is designated as I mld The corroded binary image is designated as I mle The difference image is denoted as I ls The specific difference set calculation method comprises the following steps: i mld -I ml 、I mld -I mle 、I ml -I mle To find out the junction of the background plate and the welding point, namely the edge area of the welding point. When the height of the welding point is consistent with a preset value, judging that the welding point material has no high protruding defect; and when the height of the welding point is inconsistent with the preset value, judging that the high-protruding defect of the welding material exists. The preset value is within 5% error of the height of the welding point when the welding point material is not high enough to protrude the defect theoretically.
The invention also relates to a battery welding quality detection device for implementing the battery welding quality detection method, which comprises a detection piece, an air pressure sensor, a processor, a camera and a vibration sensor, wherein the air pressure sensor is arranged in the detection piece and positioned in the detection piece, the vibration sensor is arranged on a welded battery cell tab, the vibration sensor, the air pressure sensor and the camera are electrically connected with the processor, the detection piece is attached to a welding point of a busbar, the detection piece and a part of the busbar with the welding point form a closed space, after a period of air is filled into the closed space, the air pressure sensor measures the air pressure in the closed space and transmits the air pressure to the processor, and the processor judges whether a burn-through defect exists according to the air pressure; the detecting piece regularly knocks the welded busbar to enable the busbar to vibrate, the vibration sensor collects vibration of the battery cell electrode lugs welded with the busbar and transmits vibration data to the processor, and the processor judges whether cold welding exists or not; the camera collects the busbar welding point image along the thickness direction of the busbar and transmits the image to the sensor, and the sensor judges whether the welding line material high-prominence defect exists according to the image.
According to the battery welding quality detection method, the detection piece is used for forming a closed space, the closed space is inflated for burning-through detection, the virtual welding detection is carried out through vibration transmission, the high projection detection of the welding material is carried out by collecting the thickness direction (the height direction of the welding point) image of the bus bar, the problem that the pixel difference of the welding point image caused by the laser welding of the bus bar is small can be solved, and the battery welding quality detection is realized.
The foregoing examples illustrate only a few embodiments of the invention, which are described in detail and are not to be construed as limiting the scope of the invention. It should be noted that, for those skilled in the art, it is possible to make several modifications and improvements without departing from the concept of the present invention, which are equivalent to the above embodiments according to the essential technology of the present invention, and these are all included in the protection scope of the present invention.
Claims (3)
1. The battery welding quality detection method is characterized by comprising the following steps of:
s1: attaching a detection piece with an opening to a welding point of a busbar, forming a closed space by the detection piece and a part of the busbar with the welding point, filling gas into the closed space for a period of time, and measuring the gas pressure in the closed space, wherein when the gas pressure is kept unchanged, no burn-through defect exists; when the air pressure is reduced, burn-through defects exist;
s2: arranging a plurality of sensors on the electrode lugs, wherein the plurality of sensors are symmetrical about the welding point, regularly knocking the bus without the cold joint and the cold joint, collecting data of the plurality of sensors, calculating the propagation speed of vibration in the bus according to the time difference of signals received by the plurality of sensors, specifically, applying vibration to the bus above each sensor, wherein the signals received by n sensors have C when each vibration occurs n 2 Two by two time differences according to C between n sensors n 2 Two-by-two distance differences, corresponding C is calculated n 2 The propagation speed can be obtained by applying m times of vibration at different positions n 2 The method comprises the steps of establishing a vibration model according to the propagation speed and a sensor receiving signal, training the vibration model, wherein training of the vibration model specifically comprises training of welding points with different sizes, enabling the vibration model to be applicable to the welding points with different sizes, detecting a welded busbar knocked by a piece, judging whether virtual welding exists or not according to collected tab vibration data when the knocking position of the welded busbar is any other position except the welding point on the welded busbar;
s3: setting up the background board, the background board is located the lateral part of busbar, the colour of background board with the busbar with the colour of welding point is different, forms the colour difference, gathers busbar welding point image along busbar thickness direction, uses the operation of closing to the image specifically to include the following steps: selecting the shape and the size of a mask, and performing binary expansion operation on an image target area; selecting the shape and the size of a mask, and performing binary etching operation on an image target area; for binary image I ml Performing difference set operation, and recording the expanded binary image as I mld The corroded binary image is designated as I mle The difference image is denoted as I ls The specific difference set calculation method comprises the following steps: i mld -I ml 、I mld -I mle 、I ml -I mle The method comprises the steps of (1) analyzing a required detection welding point by using threshold segmentation after closing operation, dividing the welding point and a background according to a threshold value through analysis, and counting the size of a pixel value occupied by the threshold value of the welding point; and calculating the height of the welding point according to the pixel value occupied by the welding point threshold value, and judging whether the high-salient defect of the welding material exists.
2. The battery welding quality detection method according to claim 1, characterized in that: in step S1, the maximum pressure value of the enclosed space is smaller than a preset value, where the preset value is obtained through experiments, so that the excessive pressure of the enclosed space is avoided, and the unburned welding point is extruded and penetrated.
3. A battery welding quality detection apparatus for implementing the battery welding quality detection method according to any one of claims 1 to 2, characterized in that: including detecting piece, air pressure sensor, treater, camera and vibration sensor, air pressure sensor install in detecting piece and be located detect the inside, vibration sensor installs in the electric core tab after the welding, vibration sensor air pressure sensor and the camera with treater electric connection, detect the piece and paste on the welding point of busbar, detect the piece and form airtight space with the partial busbar that has the welding point.
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| CN202310847608.7A CN116559298B (en) | 2023-07-12 | 2023-07-12 | Battery welding quality detection method and device |
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| CN202310847608.7A CN116559298B (en) | 2023-07-12 | 2023-07-12 | Battery welding quality detection method and device |
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| CN116559298A (en) | 2023-08-08 |
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