CN109283182A - A kind of detection method of battery welding point defect, apparatus and system - Google Patents
A kind of detection method of battery welding point defect, apparatus and system Download PDFInfo
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- CN109283182A CN109283182A CN201810874350.9A CN201810874350A CN109283182A CN 109283182 A CN109283182 A CN 109283182A CN 201810874350 A CN201810874350 A CN 201810874350A CN 109283182 A CN109283182 A CN 109283182A
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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
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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
- G01N2021/8854—Grading and classifying of flaws
- G01N2021/8874—Taking dimensions of defect into account
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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 present invention discloses a kind of detection method of battery welding point defect, apparatus and system.Method includes: the characteristic information for receiving battery solder joint；The characteristic information includes depth, surface gray level image；The characteristic information is analyzed and processed, standby signal is obtained.The present invention is by providing corresponding detection device, receive the depth information and surface gray level image of the battery solder joint of the radium-shine scanner acquisition of line, and identifying processing is carried out to gray level image, obtain the size of battery solder joint, and to Data Analysis Services such as depth, the sizes of battery solder joint, standby signal is obtained, the final automatic detection realized to battery solder joint improves accuracy in detection, the detection efficiency of battery welding point defect.After the present apparatus obtains prompt information, there is the prompt equipment of this system according to the standby signal, export the prompt informations such as image, sound, allow battery after point is soldered, can judge whether welding succeeds using vision/sense of hearing, provide convenience for welding personnel.
Description
Technical field
The present invention relates to mechanical vision inspection technology field more particularly to a kind of detection methods of battery welding point defect, dress
It sets and system.
Background technique
Along with being showing improvement or progress day by day for design of electronic products and manufacturing technology, battery is also at essential a part.By
The influence of the factors such as raw material, stabilization of equipment performance, environment, temperature and manual operation, battery are difficult to avoid in process of production each
The welding defect of seed type.Therefore, it is necessary to strictly implement intermediate detection process.Traditional detection means have visual detection and
Line functional test.But the reliability of these detection means, efficiency, accuracy are relatively low.Develop it is a kind of efficiently, it is high speed, high-precision
Degree domestic solder joint automatic checkout equipment be battery manufacture industry there is an urgent need to.
Summary of the invention
The present invention is intended to provide one kind is the present invention is intended to provide one kind overcomes the above problem or at least is partially solved
State detection method, the apparatus and system of a kind of battery welding point defect of problem, with solve traditional visual detection detection means and
The low problem of the reliability of line functional test, efficiency, accuracy.
In order to achieve the above objectives, technical solution of the present invention is specifically achieved in that
One aspect of the present invention provides a kind of detection method of battery welding point defect, comprising: receives battery solder joint
Characteristic information；The characteristic information includes depth, surface gray level image；The characteristic information is analyzed and processed, is mentioned
Show signal；The standby signal is for indicating whether the battery solder joint is qualified.
In addition, described the step of being analyzed and processed to the characteristic information, obtain standby signal, comprising:
Image recognition is carried out to the surface gray level image, obtains the surface image information of the battery solder joint；The table
Face image information includes size；
The depth is compared with first threshold, obtains the first comparison result；And by the size and second threshold ratio
It is right, obtain the second comparison result；According to first comparison result, second comparison result, the standby signal is obtained.
In addition, it is described according to first comparison result, second comparison result, obtain the step of the standby signal
Suddenly, comprising:
If first comparison result is that the depth is not less than the first threshold and second comparison result
It is not less than the second threshold for the size, then obtains qualifying signal；The qualifying signal is for indicating the battery solder joint
It is qualified.
In addition, it is described according to first comparison result, second comparison result, determine the step of the processing result
Suddenly, comprising:
If first comparison result is that the depth is less than the first threshold and second comparison result is
The size is less than the second threshold, then obtains alarm signal；The alarm signal is for indicating that the battery solder joint does not conform to
Lattice.
Another aspect of the present invention provides a kind of detection device of battery welding point defect, comprising: receiving module, for receiving
The characteristic information of battery solder joint；The characteristic information includes depth, surface gray level image；Analysis and processing module, for described
Characteristic information is analyzed and processed, and obtains standby signal；The standby signal is for indicating whether the battery solder joint is qualified.
In addition, the analysis and processing module includes:
Picture recognition module obtains the table of the battery solder joint for carrying out image recognition to the surface gray level image
Face image information；The surface image information includes size；
Computing module obtains the first comparison result for comparing the depth with first threshold；And by the size
It is compared with second threshold, obtains the second comparison result；And it according to first comparison result, second comparison result, obtains
To the standby signal.
In addition, if first comparison result is the depth not less than the first threshold and second ratio
It is that the size is not less than the second threshold to result, then the computing module obtains qualifying signal；The qualifying signal is used
It is qualified in the expression battery solder joint.
In addition, if first comparison result is that the depth is less than the first threshold and second comparison
As a result it is less than the second threshold for the size, then the computing module obtains alarm signal；The alarm signal is used for table
Show that the battery solder joint is unqualified.
Another aspect of the present invention additionally provides a kind of detection system of battery welding point defect, comprising: acquisition device, processing dress
It sets, suggestion device；The processing unit is the described in any item batteries based on depth detection and plane monitoring-network of claim 5-8
Welding point defect detection device；
The acquisition device is used to acquire the characteristic information of battery solder joint；The characteristic information of the battery solder joint includes depth
Information, surface gray level image.
The processing unit is used to obtain standby signal to the feature information processing of the battery solder joint；
The suggestion device is used to export prompt information according to the standby signal；
In addition, the acquisition device is the radium-shine scanner of line.
In addition, the suggestion device includes display screen and/or warning light and/or loudspeaker.
In addition, the prompt information includes text and/or color and/or sound.
Detection method, several systems of device of a kind of battery welding point defect provided by the invention, by utilizing the radium-shine scanning of line
Instrument combines three-dimensional depth information with two dimensional image processing technique, is combined in this way so that solder joint detects relatively reliable, accuracy rate
It is higher, and allow battery after point is soldered, it can judge whether welding succeeds using vision/sense of hearing.Scheme provided by the invention
It may replace a large amount of artificial on current production line risk with reduction defective products inflow client.
Detailed description of the invention
Fig. 1 is a kind of flow chart of the detection method for battery welding point defect that the embodiment of the present invention one provides；
Fig. 2 is the step flow chart for including of step 120 in Fig. 1；
Fig. 3 is the embodiment of the present invention two to the improved flow chart of steps of Fig. 2；
Fig. 4 is a kind of schematic diagram of the detection device for battery welding point defect that the embodiment of the present invention three provides；
Fig. 5 is detailed process schematic diagram when Fig. 4 shown device executes method shown in Fig. 1；
Fig. 6 is detailed process schematic diagram when Fig. 4 shown device executes improved method shown in Fig. 3；
Fig. 7 is a kind of schematic diagram of the detection system for battery welding point defect that the embodiment of the present invention three provides.
Specific embodiment
Invention is further described in detail combined with specific embodiments below.
Embodiment one
Fig. 1 is detection method, the process of apparatus and system for a kind of battery welding point defect that the embodiment of the present invention one provides
Figure.As shown in Figure 1, method includes the following steps:
Step S110: the characteristic information of battery solder joint is received.
Specifically, the characteristic information may include depth, surface gray level image.The characteristic information can be used for analyzing battery
The defect of solder joint judges whether battery solder joint is qualified.
Further, case depth information and surface ash that the radium-shine scanner of line acquires battery solder joint to be detected can be used
Degree figure.
Step S120: being analyzed and processed the characteristic information, obtains for indicating whether the battery solder joint is qualified
Standby signal.
Specifically, it as shown in Fig. 2, being analyzed and processed to the characteristic information, specifically includes:
Step S122: carrying out image recognition to the surface gray level image, obtains the surface image letter of the battery solder joint
Breath.
Specifically, the surface image information may include size.Further, two dimensional image processing technique can be used, it is right
The gray level image such as is filtered at a series of image procossing, orients the position of pad, and detect the big of battery solder joint
It is small.
Step S122: the depth is compared with first threshold, obtains the first comparison result.By the size and the second threshold
Value compares, and obtains the second comparison result.According to first comparison result, second comparison result, the prompt letter is obtained
Number.
Specifically, if first comparison result is that the depth is not less than the first threshold and described second
Comparison result is that the size is not less than the second threshold, then obtains for indicating the qualified qualified letter of the battery solder joint
Number.If first comparison result is that the depth is less than the first threshold and second comparison result is described
Size is less than the second threshold, then obtains for indicating the underproof alarm signal of battery solder joint.Optionally, described
One threshold value, the second threshold can according to the actual situation, demand, set.Such as:
The present embodiment one knows gray level image by receiving the depth information and surface gray level image of battery solder joint
Other places reason, obtains the size of battery solder joint.And then from two depth of battery solder joint, size dimensions, at operational analysis
Reason realizes the analysis to battery welding point defect, achievees the purpose that judge whether battery solder joint is qualified, improves the inspection of battery welding point defect
The accuracy of survey.
Embodiment two
As shown in figure 3, the present embodiment two improves on the basis of example 1, further to improve battery solder joint
The accuracy of defects detection.Specific improvement is as follows:
(1) the step S122 in one step S120 of embodiment is improved, obtains step S122 ', specifically includes:
The surface image information of the battery solder joint obtained in step S122 using image processing techniques further includes battery solder joint
Gray uniformization.The gray uniformization of battery solder joint gray level image can be used as the another characteristic information of analysis battery solder joint.
(2) it is based on (1), corresponding improvement is made to the step S122 in one step S120 of embodiment, obtains step S122 ', has
Body includes:
The depth is compared with first threshold, obtains the first comparison result.The size is compared with second threshold, is obtained
To the second comparison result.The gray uniformization is compared with third threshold value, obtains third comparison result.According to described
One comparison result, second comparison result, third comparison result, obtain the standby signal.
Specifically, if first comparison result is that the depth is not less than the first threshold and described second
Comparison result is that the size is not less than the second threshold and the third comparison result is that the gray uniformization is not small
In the third threshold value, then the qualifying signal for indicating the battery solder joint qualification is obtained.If first comparison result
It is less than the first threshold for the depth and second comparison result is that the size is less than the second threshold, with
And the third comparison result is that the gray uniformization is less than the third threshold value, then obtains for indicating the battery solder joint
Underproof alarm signal.The third threshold value can also according to the actual situation, demand, set.
The present embodiment two on the basis of example 1, by carrying out identifying processing to gray level image, obtains battery solder joint
Gray uniformization.It is equal from the depth, size, gray scale of battery solder joint by increasing this dimension of battery solder joint gray uniformization
Three dimensions of evenness are set out, and are handled through operational analysis, the analysis to battery welding point defect, and further raising battery solder joint lacks
Fall into the accuracy of detection.
Embodiment three
Fig. 4 is that a kind of of the offer of the embodiment of the present invention three is detected based on the battery welding point defect of depth detection and plane monitoring-network
The schematic diagram of device.The device is for executing method provided by embodiment one, embodiment two.As shown in figure 4, the device packet
It includes: receiving module 221, analysis and processing module 222, output module 223.Wherein, analysis and processing module 222 includes image procossing mould
Block, computing module.
Receiving module 221 receives the characteristic information of battery solder joint, and the characteristic information is sent to analysis and processing module
222.The characteristic information may include depth, surface gray level image.
Analysis and processing module 222 is analyzed and processed the characteristic information, obtains standby signal, and shown prompt is believed
Number it is sent to output module 223.Specifically, image processing module to the surface gray level image from receiving module 221 into
Row image recognition obtains the surface image information of the battery solder joint.Computing module will be believed from the depth of receiving module 221
Surface image information from image processing module is carried out calculation process by breath, obtains the standby signal, and be sent to output
Module 223.When the device that the present embodiment three provides is used to execute the method for embodiment one, computing module believes the depth
The calculation process of breath, surface image information, specifically refers to the step 120 in embodiment one.When the dress that the present embodiment three provides
When setting the method for executing embodiment two, computing module is to the calculation process of the depth information, surface image information, specifically
It can refer to embodiment two.Details are not described herein again.
Output module 203 exports the standby signal.
For example, Fig. 5 is the detailed process schematic diagram when device that the present embodiment three provides executes the method for embodiment one.Such as
Shown in Fig. 5, receiving module 221 receives depth information, the surface gray level image of battery solder joint.Image processing module is to the surface
Gray level image carries out image recognition, obtains the size of battery solder joint.When the comparison for the depth and first threshold for carrying out battery solder joint
When, if the depth of battery surface solder joint is not less than first threshold, variable a=1 is returned, a=0 is otherwise returned；It is electric when carrying out
When the comparison of the size of pool surface solder joint and second threshold, if the size of battery solder joint is not less than second threshold, change is returned to
B=1 is measured, b=0 is otherwise returned.Solder joint depth is compared, spot size compares the variable returned and carries out and door operation c=a*b.
Return finally with door operation result, if result is c=1, then it represents that product is qualified, and output module 203 exports qualifying signal, no
Then product is unqualified, and output module 223 exports alarm signal.
For example, Fig. 6 is the detailed process schematic diagram when device that the present embodiment three provides executes the method for embodiment two.Such as
Shown in Fig. 6, receiving module 221 receives depth information, the surface gray level image of battery solder joint.Image processing module is to the surface
Gray level image carries out image recognition, obtains size, the gray uniformization of battery solder joint.When the depth and first for carrying out battery solder joint
When the comparison of threshold value, if the depth of battery surface solder joint is not less than first threshold, variable a=1 is returned, a=is otherwise returned
0；When the comparison of the size and second threshold that carry out battery surface solder joint, if the size of battery solder joint is not less than the second threshold
Value, then return to variable b=1, otherwise return to b=0；When the comparison for the gray uniformization and third threshold value for carrying out battery surface solder joint
When, if the gray uniformization of battery solder joint is not less than third threshold value, variable d=1 is returned, d=0 is otherwise returned.By solder joint
Depth compares, spot size compares the variable returned and carries out and door operation c=a*b*d.Return finally with door operation result, if
It as a result is c=1, then it represents that product is qualified, and output module 203 exports qualifying signal, and otherwise product is unqualified, output module 223
Export alarm signal.
The present embodiment three passes through the device provided for executing two method of embodiment one or embodiment, executes image recognition skill
Art and thresholding algorithm replace a large amount of artificial detections on current production line, Jin Erti to battery welding point defect automated analysis
The efficiency and accuracy of high battery solder joint monitoring, reduce the risk that defective products flows into client.
Example IV
Fig. 7 is that a kind of of the offer of the embodiment of the present invention four is detected based on the battery welding point defect of depth detection and plane monitoring-network
The schematic diagram of system.As shown in fig. 7, the system includes: acquisition device 210, processing unit 220, suggestion device 230；Processing dress
Setting 220 can be used the battery welding point defect detection device based on depth detection and plane monitoring-network of the offer of embodiment three.
Acquisition device 210 is used to acquire the characteristic information of battery solder joint, and the characteristic information is sent to processing module
220.The characteristic information of battery solder joint includes depth information, surface gray level image.
Processing unit 220 is used to obtain standby signal to the feature information processing of the battery solder joint.
Suggestion device 230 is used to export prompt information according to the standby signal.
Processing of the processing unit 220 to the characteristic information in four system of the present embodiment, the erasable content for examining embodiment three,
It no longer illustrates herein.
Further, the radium-shine scanner of line can be used in acquisition device 210.
Further, display screen and/or warning light and/or loudspeaker can be used in suggestion device 230.
Further, the prompt information includes text and/or color and/or sound.
The system that the present embodiment four provides utilizes the radium-shine scanner of line by three-dimensional depth information and two dimensional image processing technique
It combines, is combined in this way so that solder joint detection is relatively reliable, accuracy rate is higher.
It should be understood by those skilled in the art that, embodiments herein can provide as method, system or computer program
Product.Therefore, complete hardware embodiment, complete software embodiment or reality combining software and hardware aspects can be used in the application
Apply the form of example.Moreover, it wherein includes the computer of computer usable program code that the application, which can be used in one or more,
The computer program implemented in usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.) produces
The form of product.
The application is referring to method, the process of equipment (system) and computer program product according to the embodiment of the present application
Figure and/or block diagram describe.It should be understood that every one stream in flowchart and/or the block diagram can be realized by computer program instructions
The combination of process and/or box in journey and/or box and flowchart and/or the block diagram.It can provide these computer programs
Instruct the processor of general purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine, so that being generated by the instruction that computer or the processor of other programmable data processing devices execute for real
The device for the function of being specified in present one or more flows of the flowchart and/or one or more blocks of the block diagram.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates,
Enable the manufacture of device, the command device realize in one box of one or more flows of the flowchart and/or block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or
The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one
The step of function of being specified in a box or multiple boxes.
In a typical configuration, calculating equipment includes one or more processors (CPU), input/output interface, net
Network interface and memory.
Memory may include the non-volatile memory in computer-readable medium, random access memory (RAM) and/
Or the forms such as Nonvolatile memory, such as read-only memory (ROM) or flash memory (flashRAM).Memory is computer-readable medium
Example.
Computer-readable medium includes permanent and non-permanent, removable and non-removable media can be by any method
Or technology come realize information store.Information can be computer readable instructions, data structure, the module of program or other data.
The example of the storage medium of computer includes, but are not limited to phase change memory (PRAM), static random access memory (SRAM), moves
State random access memory (DRAM), other kinds of random access memory (RAM), read-only memory (ROM), electric erasable
Programmable read only memory (EEPROM), flash memory or other memory techniques, read-only disc read only memory (CD-ROM) (CD-ROM),
Digital versatile disc (DVD) or other optical storage, magnetic cassettes, tape magnetic disk storage or other magnetic storage devices
Or any other non-transmission medium, can be used for storage can be accessed by a computing device information.As defined in this article, it calculates
Machine readable medium does not include temporary computer readable media (transitory media), such as the data-signal and carrier wave of modulation.
The above is only embodiments herein, are not intended to limit this application.To those skilled in the art,
Various changes and changes are possible in this application.It is all within the spirit and principles of the present application made by any modification, equivalent replacement,
Improve etc., it should be included within the scope of the claims of this application.
Claims (12)
1. a kind of detection method of battery welding point defect, which is characterized in that the described method comprises the following steps:
Receive the characteristic information of battery solder joint；The characteristic information includes depth, surface gray level image；
The characteristic information is analyzed and processed, standby signal is obtained；The standby signal is for indicating the battery solder joint
It is whether qualified.
2. being obtained the method according to claim 1, wherein described be analyzed and processed the characteristic information
The step of standby signal, comprising:
Image recognition is carried out to the surface gray level image, obtains the surface image information of the battery solder joint；The exterior view
As information includes size；
The depth is compared with first threshold, obtains the first comparison result；And compare the size with second threshold, it obtains
To the second comparison result；According to first comparison result, second comparison result, the standby signal is obtained.
3. according to the method described in claim 2, it is characterized in that, it is described according to first comparison result, it is described second ratio
Pair as a result, the step of obtaining the standby signal, comprising:
If first comparison result is that the depth is not less than the first threshold and second comparison result is institute
Size is stated not less than the second threshold, then obtains qualifying signal；The qualifying signal is for indicating that the battery solder joint is qualified.
4. according to the method in claim 2 or 3, which is characterized in that described according to first comparison result, described second
Comparison result, the step of determining the processing result, comprising:
If first comparison result is that the depth is less than the first threshold and second comparison result is described
Size is less than the second threshold, then obtains alarm signal；The alarm signal is for indicating that the battery solder joint is unqualified.
5. a kind of detection device of battery welding point defect, which is characterized in that described device includes:
Receiving module (221), for receiving the characteristic information of battery solder joint；The characteristic information includes depth, surface grayscale image
Picture；
Analysis and processing module (222) obtains standby signal for being analyzed and processed to the characteristic information；The prompt letter
Number for indicating whether the battery solder joint is qualified.
6. device according to claim 5, which is characterized in that the analysis and processing module includes:
Picture recognition module obtains the exterior view of the battery solder joint for carrying out image recognition to the surface gray level image
As information；The surface image information includes size；
Computing module obtains the first comparison result for comparing the depth with first threshold；And by the size and the
Two threshold values compare, and obtain the second comparison result；And according to first comparison result, second comparison result, obtain institute
State standby signal.
7. device according to claim 6, which is characterized in that if first comparison result is that the depth is not less than
The first threshold and second comparison result are that the size is not less than the second threshold, then the computing module
Obtain qualifying signal；The qualifying signal is for indicating that the battery solder joint is qualified.
8. device according to claim 6 or 7, which is characterized in that if first comparison result is that the depth is small
It is less than the second threshold in the first threshold and second comparison result for the size, then the computing module
Obtain alarm signal；The alarm signal is for indicating that the battery solder joint is unqualified.
9. a kind of detection system of battery welding point defect characterized by comprising acquisition device (210), processing unit (220),
Suggestion device (230)；The processing unit (220) is a kind of described in any item inspections of battery welding point defect of claim 5-8
Survey device；
The acquisition device (210) is used to acquire the characteristic information of battery solder joint；The characteristic information of the battery solder joint includes deep
Spend information, surface gray level image；
The processing unit (220) is used to obtain standby signal to the feature information processing of the battery solder joint；
The suggestion device (230) is used to export prompt information according to the standby signal.
10. system according to claim 9, which is characterized in that the acquisition device (210) is the radium-shine scanner of line.
11. system according to claim 9, which is characterized in that the suggestion device includes display screen and/or warning light
And/or loudspeaker.
12. system according to claim 9, which is characterized in that the prompt information include text and/or color and/or
Sound.
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Cited By (7)
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| CN111307812A (en) * | 2019-03-05 | 2020-06-19 | 南昌工程学院 | Welding spot appearance detection method based on machine vision |
| CN111462110A (en) * | 2020-04-20 | 2020-07-28 | 广东利元亨智能装备股份有限公司 | Welding seam quality detection method, device and system and electronic equipment |
| CN113470005A (en) * | 2021-07-23 | 2021-10-01 | 广东奥普特科技股份有限公司 | Welding spot detection device and welding spot detection method for cylindrical battery cap |
| CN115423811A (en) * | 2022-11-04 | 2022-12-02 | 长春光华微电子设备工程中心有限公司 | Method and device for registering welding points on chip |
| CN116203027A (en) * | 2023-01-05 | 2023-06-02 | 惠州市德赛智储科技有限公司 | Welding spot appearance detection method, detection system and storage medium |
| CN117649406A (en) * | 2024-01-29 | 2024-03-05 | 宁德时代新能源科技股份有限公司 | Method, device, equipment and storage medium for detecting welding defect of sealing nail |
| CN117649406B (en) * | 2024-01-29 | 2024-06-07 | 宁德时代新能源科技股份有限公司 | Method, device, equipment and storage medium for detecting welding defect of sealing nail |
Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006047077A (en) * | 2004-08-04 | 2006-02-16 | Seiko Epson Corp | Method and device for detecting line defects of screen |
| CN102567745A (en) * | 2011-12-29 | 2012-07-11 | 北京航天时代光电科技有限公司 | Automatic detection method of optical fiber fusion quality |
| CN102735611A (en) * | 2012-06-21 | 2012-10-17 | 宁德新能源科技有限公司 | Method for detecting resistance welding strength of lithium ion battery, and apparatus thereof |
| CN103810459A (en) * | 2012-11-07 | 2014-05-21 | 上海航天设备制造总厂 | Image recognition device and solar array welding system by using same |
| CN103846538A (en) * | 2012-11-29 | 2014-06-11 | 上海航天设备制造总厂 | Image recognition device and battery array welding system utilizing same |
| CN103862154A (en) * | 2012-12-10 | 2014-06-18 | 上海空间电源研究所 | Image identifying system and method for resistance welding of solar battery array circuit |
| CN104867145A (en) * | 2015-05-15 | 2015-08-26 | 广东工业大学 | IC element solder joint defect detection method based on VIBE model |
| CN105606620A (en) * | 2016-01-29 | 2016-05-25 | 广州立为信息技术服务有限公司 | PCBA welding spot detection method and system based on vision |
| CN106404533A (en) * | 2016-08-29 | 2017-02-15 | 华霆（合肥）动力技术有限公司 | Welding spot detection method |
| CN106471333A (en) * | 2014-07-08 | 2017-03-01 | 日产自动车株式会社 | Flaw detection apparatus and production system |
| CN106825958A (en) * | 2017-03-16 | 2017-06-13 | 深圳市光大激光科技股份有限公司 | Integrated welding is agreed to play and takes the photograph structure and battery core automatic welding detection means and method |
| CN107516308A (en) * | 2017-07-06 | 2017-12-26 | 佛山科学技术学院 | A kind of battery cap front visible detection method |
| CN107515230A (en) * | 2017-10-17 | 2017-12-26 | 广东正业科技股份有限公司 | A kind of welding system and product inspection method |
| CN107945184A (en) * | 2017-11-21 | 2018-04-20 | 安徽工业大学 | A kind of mount components detection method positioned based on color images and gradient projection |
-
2018
- 2018-08-03 CN CN201810874350.9A patent/CN109283182A/en active Pending
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006047077A (en) * | 2004-08-04 | 2006-02-16 | Seiko Epson Corp | Method and device for detecting line defects of screen |
| CN102567745A (en) * | 2011-12-29 | 2012-07-11 | 北京航天时代光电科技有限公司 | Automatic detection method of optical fiber fusion quality |
| CN102735611A (en) * | 2012-06-21 | 2012-10-17 | 宁德新能源科技有限公司 | Method for detecting resistance welding strength of lithium ion battery, and apparatus thereof |
| CN103810459A (en) * | 2012-11-07 | 2014-05-21 | 上海航天设备制造总厂 | Image recognition device and solar array welding system by using same |
| CN103846538A (en) * | 2012-11-29 | 2014-06-11 | 上海航天设备制造总厂 | Image recognition device and battery array welding system utilizing same |
| CN103862154A (en) * | 2012-12-10 | 2014-06-18 | 上海空间电源研究所 | Image identifying system and method for resistance welding of solar battery array circuit |
| CN106471333A (en) * | 2014-07-08 | 2017-03-01 | 日产自动车株式会社 | Flaw detection apparatus and production system |
| CN104867145A (en) * | 2015-05-15 | 2015-08-26 | 广东工业大学 | IC element solder joint defect detection method based on VIBE model |
| CN105606620A (en) * | 2016-01-29 | 2016-05-25 | 广州立为信息技术服务有限公司 | PCBA welding spot detection method and system based on vision |
| CN106404533A (en) * | 2016-08-29 | 2017-02-15 | 华霆（合肥）动力技术有限公司 | Welding spot detection method |
| CN106825958A (en) * | 2017-03-16 | 2017-06-13 | 深圳市光大激光科技股份有限公司 | Integrated welding is agreed to play and takes the photograph structure and battery core automatic welding detection means and method |
| CN107516308A (en) * | 2017-07-06 | 2017-12-26 | 佛山科学技术学院 | A kind of battery cap front visible detection method |
| CN107515230A (en) * | 2017-10-17 | 2017-12-26 | 广东正业科技股份有限公司 | A kind of welding system and product inspection method |
| CN107945184A (en) * | 2017-11-21 | 2018-04-20 | 安徽工业大学 | A kind of mount components detection method positioned based on color images and gradient projection |
Non-Patent Citations (2)
| Title |
|---|
| 中国通信学会主编: "《第六届全国计算机应用联合学术会议论文集 （上册）》", 31 December 2002 * |
| 青岛英谷教育科技股份有限公司著: "《快速成型技术》", 1 February 2018 * |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111307812A (en) * | 2019-03-05 | 2020-06-19 | 南昌工程学院 | Welding spot appearance detection method based on machine vision |
| CN111462110A (en) * | 2020-04-20 | 2020-07-28 | 广东利元亨智能装备股份有限公司 | Welding seam quality detection method, device and system and electronic equipment |
| CN113470005A (en) * | 2021-07-23 | 2021-10-01 | 广东奥普特科技股份有限公司 | Welding spot detection device and welding spot detection method for cylindrical battery cap |
| CN113470005B (en) * | 2021-07-23 | 2022-03-18 | 广东奥普特科技股份有限公司 | Welding spot detection device and welding spot detection method for cylindrical battery cap |
| CN115423811A (en) * | 2022-11-04 | 2022-12-02 | 长春光华微电子设备工程中心有限公司 | Method and device for registering welding points on chip |
| CN116203027A (en) * | 2023-01-05 | 2023-06-02 | 惠州市德赛智储科技有限公司 | Welding spot appearance detection method, detection system and storage medium |
| CN116203027B (en) * | 2023-01-05 | 2024-01-26 | 惠州市德赛智储科技有限公司 | Welding spot appearance detection method, detection system and storage medium |
| CN117649406A (en) * | 2024-01-29 | 2024-03-05 | 宁德时代新能源科技股份有限公司 | Method, device, equipment and storage medium for detecting welding defect of sealing nail |
| CN117649406B (en) * | 2024-01-29 | 2024-06-07 | 宁德时代新能源科技股份有限公司 | Method, device, equipment and storage medium for detecting welding defect of sealing nail |
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