CN108037130B - Automatic detection method and automatic detection device for tab defects of battery cell - Google Patents
Automatic detection method and automatic detection device for tab defects of battery cell Download PDFInfo
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- 230000007246 mechanism Effects 0.000 claims description 9
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- 230000005611 electricity Effects 0.000 claims description 7
- 238000000605 extraction Methods 0.000 claims description 4
- 238000004458 analytical method Methods 0.000 claims description 3
- 241000252254 Catostomidae Species 0.000 claims description 2
- 210000004027 cell Anatomy 0.000 description 99
- 230000006872 improvement Effects 0.000 description 8
- 230000001678 irradiating effect Effects 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- RYGMFSIKBFXOCR-UHFFFAOYSA-N Copper Chemical compound [Cu] RYGMFSIKBFXOCR-UHFFFAOYSA-N 0.000 description 2
- 210000005056 cell body Anatomy 0.000 description 2
- 229910052802 copper Inorganic materials 0.000 description 2
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- 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
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/14—Measuring arrangements characterised by the use of optical techniques for measuring distance or clearance between spaced objects or spaced apertures
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/26—Measuring arrangements characterised by the use of optical techniques for measuring angles or tapers; for testing the alignment of axes
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- 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
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- 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
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- 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
- G01N2021/845—Objects on a conveyor
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- 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
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Abstract
The invention discloses an automatic detection method and an automatic detection device for tab defects of a battery cell, wherein the method comprises the following steps: transmitting the battery cell to be detected to a preset position, wherein the preset position is on an extension line of a shooting direction of the shooting equipment; shooting image information of a battery cell to be detected; analyzing the image information by adopting a preset tab defect detection strategy to judge whether a tab of the battery cell to be detected has a defect; and if the cell to be detected has no defect, transmitting the cell to be detected to the next station. According to the battery module, whether the electrode lug of the battery cell has defects is automatically analyzed through the image information shot by the camera equipment, so that the labor cost is saved, the accuracy of judging the electrode lug defects is improved, the quality of the battery module is improved, and the assembly speed of the battery module is also improved.
Description
Technical Field
The invention relates to the technical field of battery tab defect detection, in particular to a method and a device for automatically detecting tab defects of a battery core.
Background
The defect of electric core utmost point ear is judged through the manual work to current electric core before assembling into the battery module. Because the pole ear of the battery core is smaller, the judgment accuracy of whether the pole ear of the battery has defects is low. Consequently, electric core is assembling into battery module after, if there is the defect in the battery utmost point ear of electric core, then leads to the copper bar that battery utmost point ear can not get into connection utmost point ear usefulness. At present, to the battery utmost point ear of small defect, cause battery utmost point ear to get into the copper bar through manual operation's mode, to the great battery utmost point ear of defect, then need replace this electric core to assemble again. This reduces both the quality and the assembly rate of the battery module.
In summary, it is urgently needed to solve the problem of low accuracy of defect determination of the battery tab, so as to improve the quality and the assembly rate of the battery module.
Disclosure of Invention
The invention aims to provide an automatic detection method and an automatic detection device for the defects of a battery lug, which aim to solve the problem of low accuracy in the defect judgment of the conventional battery lug.
In order to solve the above problems, the present invention provides an automatic detection method for tab defects of a battery cell, which includes:
transmitting the battery cell to be detected to a preset position, wherein the preset position is on an extension line of a shooting direction of the shooting equipment;
shooting image information of a battery cell to be detected;
analyzing the image information by adopting a preset tab defect detection strategy to judge whether a tab of the battery cell to be detected has a defect;
and if the cell to be detected has no defect, transmitting the cell to be detected to the next station.
As a further improvement of the present invention, the method for capturing image information of a cell to be detected comprises the following steps:
detecting the ambient light intensity around the cell to be detected;
judging whether the ambient light intensity exceeds a preset light intensity threshold value or not;
if the ambient light intensity does not exceed the preset light intensity threshold, then send the light that corresponds with the difference light intensity and shine and wait to detect the electricity core, the difference light intensity is preset light intensity threshold-ambient light intensity.
As a further improvement of the present invention, the method for determining whether the tab of the battery cell to be detected has a defect further comprises:
if the battery cell to be detected has a defect, the battery cell to be detected is transferred to a place where the defective battery cell is placed.
As a further improvement of the present invention, analyzing image information by using a preset tab defect detection strategy to determine whether a tab of a to-be-detected cell has a defect, includes:
extracting an edge curve of the battery cell to be detected in the image information by adopting a preset tab defect detection strategy, wherein the edge curve comprises a positive tab curve and a negative tab curve;
obtaining an actual distance between the two tabs and an actual angle between each tab and a preset horizontal line according to the positive tab curve and the negative tab curve;
if the actual distance does not exceed the preset distance threshold and the actual angle does not exceed the preset angle threshold, judging that the electrode lug of the battery cell to be detected has no defect;
and if the actual distance exceeds a preset distance threshold or the actual angle exceeds a preset angle threshold, judging that the pole ear of the battery cell to be detected has a defect.
In order to solve the above problems, the present invention further provides an apparatus for automatically detecting a tab defect of a battery cell, including:
the conveying belt is used for conveying the battery cell to be detected to a preset position, and the preset position is on an extension line of the shooting direction of the shooting equipment;
the camera equipment is used for shooting image information of the battery cell to be detected;
the processor is used for analyzing the image information by adopting a preset tab defect detection strategy so as to judge whether a tab of the battery cell to be detected has a defect, and the processor is respectively electrically connected with the camera equipment and the conveyor belt;
the conveying belt is further used for transmitting the battery cell to be detected to the next station if the battery cell to be detected does not have defects.
As a further improvement of the present invention, it further comprises:
the light intensity detection sensor is used for detecting the ambient light intensity around the cell to be detected;
the processor is also used for judging whether the ambient light intensity exceeds a preset light intensity threshold value, and the processor is respectively electrically connected with the light intensity detection sensor and the light source module;
the light source module is used for emitting light corresponding to the difference light intensity and irradiating the battery cell to be detected if the ambient light intensity does not exceed the preset light intensity threshold, and the difference light intensity is equal to the preset light intensity threshold-the ambient light intensity.
As a further improvement of the present invention, it further comprises:
and the defective battery cell transfer mechanism is used for transferring the battery cell to be detected to a place where the defective battery cell is placed if the battery cell to be detected has a defect.
As a further improvement of the present invention, the defective cell transfer mechanism includes:
the clamping component is used for clamping the battery cell with the defect;
and the driving assembly is used for driving the clamping component to move upwards and/or downwards relative to the conveyor belt, so that the defective battery cell leaves the conveyor belt.
As a further improvement of the invention, the clamping member is provided with a plurality of suckers.
As a further refinement of the invention, the processor comprises:
the edge curve extraction module is used for extracting an edge curve of the battery cell to be detected in the image information by adopting a preset tab defect detection strategy, wherein the edge curve comprises a positive tab curve and a negative tab curve;
the correlation parameter acquisition module is used for acquiring an actual distance between the two lugs and an actual angle between each lug and a preset horizontal line according to the positive lug curve and the negative lug curve;
the qualified tab judging module is used for judging that the tab of the battery cell to be detected has no defect if the actual distance does not exceed the preset distance threshold and the actual angle does not exceed the preset angle threshold;
and the defective tab judging module is used for judging that the tab of the battery cell to be detected has defects if the actual distance exceeds a preset distance threshold or the actual angle exceeds a preset angle threshold.
Compared with the prior art, the battery module and the method have the advantages that whether the electrode lug of the battery cell has defects is automatically analyzed through the image information shot by the camera equipment, so that labor cost is saved, the accuracy of judging the electrode lug defects is improved, the quality of the battery module is improved, and the assembly speed of the battery module is improved.
Drawings
Fig. 1 is a schematic flow chart of a tab defect automatic detection method of a battery cell according to a first embodiment of the present invention;
fig. 2 is a schematic flow chart of a tab defect automatic detection method of a battery cell according to a second embodiment of the present invention;
fig. 3 is a schematic flow chart of a tab defect automatic detection method of a battery cell according to a third embodiment of the present invention;
fig. 4 is a schematic flow chart illustrating an embodiment of a defect determination process in the method for automatically detecting tab defects of a battery cell according to the present invention;
fig. 5 is a schematic overall structure diagram of an embodiment of the automatic tab defect detection apparatus for a battery cell of the present invention;
FIG. 6 is a schematic view of a portion of the structure of FIG. 5;
fig. 7 is a functional module schematic diagram of an embodiment of a processor in the automatic tab defect detection apparatus for a battery cell according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Fig. 1 shows an embodiment of the method for automatically detecting tab defects of a battery cell according to the present invention. In this embodiment, the method for automatically detecting the tab defect of the battery cell includes the following steps:
and step S1, transmitting the battery cell to be detected to a preset position, wherein the preset position is on the camera shooting direction extension line of the camera shooting equipment.
It should be noted that the preset position in the present embodiment may also be within the effective imaging range of the imaging apparatus. Preferably, the preset position is on an image pickup direction extension line of the image pickup apparatus.
And step S2, capturing image information of the battery cell to be detected.
And step S3, analyzing the image information by adopting a preset tab defect detection strategy to judge whether the tab of the battery cell to be detected has defects. And if the cell to be detected has no defect, executing step S4.
And step S4, transmitting the battery cell to be detected to the next station.
Whether the utmost point ear of image information automatic analysis electric core that this embodiment was shot through camera equipment has the defect, has both saved the cost of labor, has also promoted the judgement rate of accuracy of utmost point ear defect, and then has both promoted the quality of battery module, has also promoted the equipment speed of battery module.
When the method for automatically detecting the lug defect of the battery cell is applied to the use process of the automatic detection device for the lug defect of the battery cell, the automatic detection device for the lug defect of the battery cell is placed in a factory, so that the condition of insufficient light is possibly caused. Therefore, on the basis of the above embodiment, in another embodiment, before the step S2, the method further includes:
and step S10, detecting the ambient light intensity around the battery cell to be detected.
Step S11, determining whether the ambient light intensity exceeds a preset light intensity threshold. If the ambient light intensity does not exceed the preset light intensity threshold, step S12 is executed.
And step S12, emitting light corresponding to the difference light intensity and irradiating the battery cell to be detected, wherein the difference light intensity is a preset light intensity threshold value-ambient light intensity.
This embodiment real-time detection waits to detect the ambient light intensity around the electric core, and under the not enough condition of light, provides the light of certain intensity to ensure that camera equipment shoots under appointed light intensity, thereby ensured the definition of photo, and then carry out analysis processes according to the photo that the definition is high, promoted and judged the rate of accuracy, so that further promoted the quality of battery module and the equipment rate of battery module.
When the method for automatically detecting the lug defect of the battery cell is applied to the device for automatically detecting the lug defect of the battery cell, if the lug of the battery cell has a problem, the lug needs to be processed immediately, so that the automatic processing speed is prevented from being influenced. Therefore, on the basis of the above embodiment, in other embodiments, referring to fig. 3, after step S3, if the cell to be detected has a defect, step S20 is executed.
And step S20, transferring the battery cell to be detected to a place where the defective battery cell is placed.
According to the embodiment, the defective battery cell is automatically transferred to the position where the defective battery cell is placed, so that the influence on subsequent battery cell detection is avoided, and the operator can conveniently perform unified processing on the defective battery cell (such as reassembling a battery tab or correcting the battery tab), so that the automatic performance of battery cell detection and the user experience are improved.
When the method for automatically detecting the tab defect of the battery cell is applied to the device for automatically detecting the tab defect of the battery cell, the tab detection needs to be easily realized, so that on the basis of the above embodiment, in other embodiments, referring to fig. 4, step S3 includes:
and step S30, extracting an edge curve of the battery cell to be detected in the image information by adopting a preset tab defect detection strategy, wherein the edge curve comprises a positive tab curve and a negative tab curve.
And step S31, obtaining the actual distance between the two tabs and the actual angle between each tab and a preset horizontal line according to the positive tab curve and the negative tab curve.
The battery cell includes a tab and a battery cell body, and a connection point between the battery cell body and the tab is used as a reference line (i.e., a preset horizontal line). Further, the positive electrode tab and the negative electrode tab of the battery cell are arranged on the same side of the battery cell. The actual distance can be the distance between the inner axis of the anode tab and the inner axis of the cathode tab. The actual angle can be an included angle between the inner side axis of the positive electrode tab and the reference line, and can also be an included angle between the inner side axis of the negative electrode tab and the reference line.
Step S32, determine whether the actual distance exceeds the preset distance threshold, and determine whether the actual angle exceeds the preset angle threshold. If the actual distance does not exceed the preset distance threshold and the actual angle does not exceed the preset angle threshold, step S33 is executed. If the actual distance exceeds the preset distance threshold or the actual angle exceeds the preset angle threshold, step S34 is executed.
And step S33, judging that the tab of the battery cell to be detected has no defect.
And step S34, judging that the tab of the battery cell to be detected has defects.
This embodiment judges that actual distance does not exceed when predetermineeing the distance threshold value and actual angle does not exceed and predetermineeing the angle threshold value, then judges that the utmost point ear of this electricity core does not have the defect, like this, only needs to extract anodal utmost point ear curve and negative pole utmost point ear curve to obtain actual distance and actual angle according to anodal utmost point ear curve and negative pole utmost point ear curve, consequently, this processing procedure easily realizes, thereby reduced the design degree of difficulty coefficient, so that reduced design cost.
Fig. 5 shows an embodiment of the automatic tab defect detection device for a battery cell of the invention. In this embodiment, the automatic tab defect detection device for the battery cell includes a conveyor belt 10, an image pickup apparatus 11, and a processor (not shown in the figure).
The conveying belt 10 is used for conveying the battery cell 12 to be detected to a preset position, and the preset position is on an extension line of a shooting direction of the shooting equipment 11; the camera device 11 is configured to capture image information of the battery cell 12 to be detected; the processor is used for analyzing the image information by adopting a preset tab defect detection strategy so as to judge whether a tab of the battery cell 12 to be detected has a defect, and the processor is electrically connected with the camera equipment 11 and the conveyor belt 10 respectively; the conveyor belt 10 is further configured to, if the cell 12 to be detected has no defect, transmit the cell 12 to be detected to a next station.
It should be noted that the processor in the present embodiment may be provided in the image pickup apparatus, or may be provided in another location so as to control both the conveyor belt and the image pickup apparatus.
On the basis of the foregoing embodiment, in other embodiments, the device for automatically detecting a tab defect of an electrical core further includes a light intensity detection sensor (not shown in the figure) and a light source module (not shown in the figure).
The light intensity detection sensor is used for detecting the ambient light intensity around the cell 12 to be detected; the processor is also used for judging whether the ambient light intensity exceeds a preset light intensity threshold value, and the processor is respectively electrically connected with the light intensity detection sensor and the light source module; the light source module is used for emitting light corresponding to the difference light intensity and irradiating the cell 12 to be detected if the ambient light intensity does not exceed the preset light intensity threshold, and the difference light intensity is equal to the preset light intensity threshold-the ambient light intensity.
It should be noted that the light intensity of the environment around the cell to be detected is detected, and the cell to be detected is irradiated, so that the light intensity detection sensor and the light source module can be arranged adjacent to the camera device.
On the basis of the above embodiments, in other embodiments, referring to fig. 5, the apparatus for automatically detecting tab defects of a battery cell further includes a defective battery cell transfer mechanism 20. The defective battery cell transferring mechanism 20 is configured to, if the battery cell 12 to be detected has a defect, transfer the battery cell 12 to be detected to a place where the defective battery cell is placed.
It should be noted that the automatic tab defect detection apparatus for a battery cell of the present embodiment includes a mounting bracket 21, wherein one side of the mounting bracket 21 is provided with the image pickup device 11, and the other side is provided with the defective battery cell transfer mechanism 20.
Specifically, referring to fig. 6, the defective cell transfer mechanism 20 includes a clamping member 201 and a drive assembly 202.
The clamping component 201 is used for clamping a defective battery cell; a drive assembly 202 for driving the gripping member 201 upwardly and/or downwardly relative to the conveyor belt 10 so that a defective cell exits the conveyor belt 10.
Specifically, the mounting bracket 21 is provided with a guide rail, a sliding chain is arranged on the guide rail, and the driving assembly 202 comprises a 7-shaped connecting piece, one end of the 7-shaped connecting piece is connected with the sliding chain, and the other end of the 7-shaped connecting piece is connected with the clamping member 201.
In this embodiment, the camera device 11 and the defective battery cell transfer mechanism 20 are respectively disposed on two sides of the mounting bracket 21, so that the spatial layout is fully utilized, and the structure of the automatic tab defect detection device is simplified.
Further, a plurality of suction cups 2011 are provided on the holding member 201.
This embodiment passes through the sucking disc and adsorbs electric core body, has avoided other modes centre gripping electricity core to harm electricity core, thereby lose and handle this electricity core, so that become the chance of flawless electricity core. Like this, further promoted the qualification rate of holistic electric core.
On the basis of the above embodiment, in other embodiments, referring to fig. 7, the processor includes an edge curve extraction module 30, an associated parameter acquisition module 31, a qualified tab determination module 32, and a defective tab determination module 33.
The edge curve extraction module 30 is configured to extract an edge curve of the to-be-detected battery cell 12 in the image information by using a preset tab defect detection strategy, where the edge curve includes a positive tab curve and a negative tab curve; the correlation parameter obtaining module 31 is configured to obtain an actual distance between two tabs and an actual angle between each tab and a preset horizontal line according to the positive tab curve and the negative tab curve; the qualified tab determining module 32 is configured to determine that a tab of the battery cell 12 to be detected has no defect if the actual distance does not exceed the preset distance threshold and the actual angle does not exceed the preset angle threshold; and the defective tab judging module 33 is configured to judge that a tab of the battery cell 12 to be detected has a defect if the actual distance exceeds the preset distance threshold or the actual angle exceeds the preset angle threshold.
The above detailed description of the embodiments of the present invention is provided as an example, and the present invention is not limited to the above described embodiments. It will be apparent to those skilled in the art that any equivalent modifications or substitutions can be made within the scope of the present invention, and thus, equivalent changes and modifications, improvements, etc. made without departing from the spirit and scope of the present invention should be included in the scope of the present invention.
Claims (8)
1. An automatic detection method for tab defects of a battery cell is characterized by comprising the following steps:
the method comprises the steps that a battery cell to be detected is conveyed to a preset position, and the preset position is located on an extension line of a shooting direction of shooting equipment;
shooting image information of the battery cell to be detected;
analyzing the image information by adopting a preset tab defect detection strategy to judge whether a tab of the battery cell to be detected has a defect;
if the cell to be detected has no defect, transmitting the cell to be detected to the next station;
adopting and presetting utmost point ear defect detection strategy analysis image information to judge whether the utmost point ear of waiting to detect electric core has the defect, include:
extracting an edge curve of the battery cell to be detected in the image information by adopting a preset tab defect detection strategy, wherein the edge curve comprises a positive tab curve and a negative tab curve;
obtaining an actual distance between the two tabs and an actual angle between each tab and a preset horizontal line according to the positive tab curve and the negative tab curve;
if the actual distance does not exceed a preset distance threshold and the actual angle does not exceed a preset angle threshold, judging that the tab of the battery cell to be detected has no defect;
and if the actual distance exceeds a preset distance threshold or the actual angle exceeds a preset angle threshold, judging that the pole lug of the battery cell to be detected has a defect.
2. The method according to claim 1, wherein the step of capturing image information of the battery cell to be detected comprises:
detecting the ambient light intensity around the battery cell to be detected;
judging whether the ambient light intensity exceeds a preset light intensity threshold value or not;
if the ambient light intensity does not exceed the preset light intensity threshold, light corresponding to the difference light intensity is emitted and irradiates the cell to be detected, and the difference light intensity is equal to the preset light intensity threshold-the ambient light intensity.
3. The method according to claim 1, wherein the step of determining whether the tab of the battery cell to be detected has a defect further comprises:
and if the battery cell to be detected has defects, transferring the battery cell to be detected to a place where the defective battery cell is placed.
4. The utility model provides a utmost point ear defect automatic checkout device of electricity core which characterized in that, it includes:
the conveying belt is used for conveying the battery cell to be detected to a preset position, and the preset position is on an extension line of the shooting direction of the shooting equipment;
the camera equipment is used for shooting image information of the battery cell to be detected;
the processor is used for analyzing the image information by adopting a preset tab defect detection strategy so as to judge whether a tab of the battery cell to be detected has a defect, and the processor is respectively electrically connected with the camera equipment and the conveyor belt; the processor includes:
the edge curve extraction module is used for extracting an edge curve of the battery cell to be detected in the image information by adopting a preset tab defect detection strategy, wherein the edge curve comprises a positive tab curve and a negative tab curve;
the correlation parameter acquisition module is used for acquiring an actual distance between two tabs and an actual angle between each tab and a preset horizontal line according to the positive tab curve and the negative tab curve;
the qualified tab judging module is used for judging that the tab of the battery cell to be detected has no defect if the actual distance does not exceed a preset distance threshold and the actual angle does not exceed a preset angle threshold;
the defective tab judging module is used for judging that the tab of the battery cell to be detected has a defect if the actual distance exceeds a preset distance threshold or the actual angle exceeds a preset angle threshold;
the conveying belt is further used for conveying the battery cell to be detected to the next station if the battery cell to be detected does not have defects.
5. The automatic detection device for the tab defect of the battery cell according to claim 4, further comprising:
the light intensity detection sensor is used for detecting the ambient light intensity around the cell to be detected;
the processor is also used for judging whether the ambient light intensity exceeds a preset light intensity threshold value, and the processor is respectively electrically connected with the light intensity detection sensor and the light source module;
the light source module is configured to emit light corresponding to a difference light intensity and irradiate the to-be-detected battery cell if the ambient light intensity does not exceed a preset light intensity threshold, where the difference light intensity is equal to the preset light intensity threshold — the ambient light intensity.
6. The automatic detection device for the tab defect of the battery cell according to claim 4, further comprising:
and the defective battery cell transfer mechanism is used for transferring the battery cell to be detected to a place where the defective battery cell is placed if the battery cell to be detected has a defect.
7. The device of claim 6, wherein the defective cell transfer mechanism comprises:
the clamping component is used for clamping the battery cell with the defect;
a drive assembly for driving the gripping member to move up and/or down relative to the conveyor belt so that the defective cell exits the conveyor belt.
8. The automatic detection device for the tab defect of the battery cell according to claim 7, wherein a plurality of suckers are arranged on the clamping member.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711258573.4A CN108037130B (en) | 2017-12-01 | 2017-12-01 | Automatic detection method and automatic detection device for tab defects of battery cell |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711258573.4A CN108037130B (en) | 2017-12-01 | 2017-12-01 | Automatic detection method and automatic detection device for tab defects of battery cell |
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| Publication Number | Publication Date |
|---|---|
| CN108037130A CN108037130A (en) | 2018-05-15 |
| CN108037130B true CN108037130B (en) | 2020-10-16 |
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| CN109187546A (en) * | 2018-07-23 | 2019-01-11 | 广州超音速自动化科技股份有限公司 | Lithium battery pole ear mixes detection method and tab welding detection system |
| CN109187547A (en) * | 2018-07-23 | 2019-01-11 | 广州超音速自动化科技股份有限公司 | Lithium battery pole ear solder joint welds broken detection method and tab welding detection system |
| CN109100226B (en) * | 2018-09-05 | 2021-04-02 | 华霆（合肥）动力技术有限公司 | Welding detection device and detection method |
| CN110824371A (en) * | 2019-11-08 | 2020-02-21 | 广东利元亨智能装备股份有限公司 | Battery detection method and device, electronic equipment and readable storage medium |
| CN110779446A (en) * | 2019-11-08 | 2020-02-11 | 广东利元亨智能装备股份有限公司 | Battery detection method and device, electronic equipment and battery detection system |
| CN111261825B (en) * | 2020-01-24 | 2023-03-21 | 苏州杰锐思智能科技股份有限公司 | Method and equipment for regulating and controlling angle deviation of positive and negative electrode tabs |
| CN112104968B (en) * | 2020-09-15 | 2021-10-15 | 沈阳风驰软件股份有限公司 | Wireless earphone appearance defect detection system and detection method |
| CN112525917A (en) * | 2020-11-12 | 2021-03-19 | 欣旺达电动汽车电池有限公司 | Battery cell tab detection method, device and system and storage medium |
| CN113222900A (en) * | 2021-04-16 | 2021-08-06 | 深圳市安仕新能源科技有限公司 | Pole lug polarity detection method and detection device, terminal equipment and storage medium |
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| CN114923428A (en) * | 2022-03-08 | 2022-08-19 | 广州超音速自动化科技股份有限公司 | Battery cell tab margin detection equipment and detection method |
| KR20240050400A (en) * | 2022-04-11 | 2024-04-18 | 컨템포러리 엠퍼렉스 테크놀로지 씨오., 리미티드 | Method and device for detecting taps |
| CN115829921B (en) * | 2022-09-16 | 2024-01-05 | 宁德时代新能源科技股份有限公司 | Method, apparatus and computer readable storage medium for detecting cell defects |
| CN117781914A (en) * | 2024-02-28 | 2024-03-29 | 宁德时代新能源科技股份有限公司 | Tab dislocation detection system and method |
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| CN202075237U (en) * | 2011-04-28 | 2011-12-14 | 河南科技大学 | On-line detection and grading device for lithium ion battery pole piece |
| CN104155298B (en) * | 2014-08-12 | 2017-01-25 | 哈尔滨工业大学 | Light intensity compensation and image gray value based method for measuring water content of soil surface |
| CN105548212B (en) * | 2016-02-03 | 2018-12-25 | 杭州晶耐科光电技术有限公司 | A kind of touched panel glass surface blemish on-line automaticization detection system and method |
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