CN107516308A - A kind of battery cap front visible detection method - Google Patents
A kind of battery cap front visible detection method Download PDFInfo
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- CN107516308A CN107516308A CN201710544998.5A CN201710544998A CN107516308A CN 107516308 A CN107516308 A CN 107516308A CN 201710544998 A CN201710544998 A CN 201710544998A CN 107516308 A CN107516308 A CN 107516308A
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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
- G06T7/0006—Industrial image inspection using a design-rule based approach
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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
- G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
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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
- G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
- G01N21/952—Inspecting the exterior surface of cylindrical bodies or wires
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/11—Region-based segmentation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/12—Edge-based segmentation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/13—Edge detection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
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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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- 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
- G06T2207/10—Image acquisition modality
- G06T2207/10004—Still image; Photographic image
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- 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
Abstract
The invention discloses a kind of battery cap front visible detection method, including camera is demarcated, the direct picture of battery cap is obtained by camera；Direct picture and battery cap are subjected to size comparison, obtain correction coefficient；The positive edge radian of battery cap and more intermediate annular body are detected by direct picture, underproof battery cap is separated；The positive defects of vision region of battery cap is detected by direct picture, underproof battery cap is separated；The positive welding point defect region of battery cap is detected by direct picture and is separated underproof battery cap；It is qualified to be determined as by the battery cap of above-mentioned detecting step；The present invention carries out IMAQ by camera to the front of battery cap, and the present invention realizes the quality testing of battery cap using image processing techniques, and detection speed is fast, and the degree of accuracy is high.
Description
Technical field
The present invention relates to cell art, more specifically to a kind of battery cap front visible detection method.
Background technology
Battery cap is the core component of battery, not only acts as the effect of conductive electrode, there is provided Cell closure function and is carried
For the effect of safety-valve, its quality directly affects service life and the personal safety of battery, therefore before battery installation, needs
Strict outward appearance is carried out to battery cap to detect.
In cell production process, easily there is the positive face of a variety of production defects, especially battery cap in battery cap
Easily there are a variety of mass defects.With the continuous development of New Energy Industry, to the quality requirement more and more higher of battery cap, still
Current most of battery manufacture enterprises are all to carry out outward appearance detection to battery cap using the method for artificial detection, due to artificial inspection
Degree of testing the speed is slow, is influenceed by artificial mood and experience, and easy flase drop missing inspection situation, product quality hardly results in guarantee, it is difficult to full
The large batch of product complete detection requirement of foot.
The content of the invention
The technical problem to be solved in the present invention is：A kind of intelligent battery cap front visible detection method is provided.
The present invention solve its technical problem solution be：
A kind of battery cap front visible detection method, comprises the following steps：
Step A：Camera is demarcated, the direct picture of battery cap is obtained by camera；
Step B：Direct picture and battery cap are subjected to size comparison, obtain correction coefficient；
Step C：The positive edge radian of battery cap and more intermediate annular body are detected by direct picture, judged
It is whether qualified, if unqualified, underproof battery cap is separated, if qualified, continuation down performs；
Step D：The positive quality testing region of battery cap is detected by direct picture, it is qualified to judge whether,
If unqualified, underproof battery cap is separated, if qualified continuation down performs；
Step E：The positive solder joint situation of battery cap is detected by direct picture, it is qualified to judge whether, if
It is unqualified, underproof battery cap is separated, if qualified, continuation down performs；
Step F：It is qualified to be determined as by above-mentioned steps C to the step E battery caps detected；
Wherein described step C to step E orders can exchange.
As the further improvement of above-mentioned technical proposal, the step B comprises the following steps：
Step B1：ROI region positioning is carried out to the direct picture；
Step B2：Point measures corresponding to optional two in the ROI region and battery cap entity, will measure
Two values of gained are compared acquisition correction coefficient.
As the further improvement of above-mentioned technical proposal, the step B1 following steps：
Step B11：Processing is filtered to the direct picture；
Step B12：Image binaryzation processing is carried out to the direct picture；
Step B13：Contour extraction processing is carried out to the direct picture；
Step B14：Circular fit processing is carried out to the direct picture, obtains ROI region.
As the further improvement of above-mentioned technical proposal, the step C comprises the following steps：
Step C1：The marginal point of ROI region is obtained in direct picture, circular fit is carried out to acquired marginal point,
And the first diameter obtained by digital simulation；
Step C2：Judge whether first diameter meets the requirements, if do not met, battery cap is separated, such as
Fruit meets, and continuation down performs；
Step C3：The more intermediate annular body marginal point of ROI region is obtained in direct picture, acquired marginal point is carried out
Circular fit, and the Second bobbin diameter obtained by digital simulation；
Step C4：Judge whether the Second bobbin diameter meets the requirements, if do not met, battery cap is separated, such as
Fruit meets, and continuation down performs.
As the further improvement of above-mentioned technical proposal, the step D comprises the following steps：
Step D1：Noise processed is removed to the ROI region on direct picture, strengthens ROI region visual effect,
Binary conversion treatment is carried out to the ROI region；
Step D2：Black connected region is extracted in the ROI region after step D1 processing, judges the black connected region
Whether the area and profile length in domain are met the requirements, if do not met, battery cap is separated, if qualified, are continued
Down perform.
As the further improvement of above-mentioned technical proposal, the step E comprises the following steps：
Step E1：Gray processing processing is carried out to the ROI region on direct picture, then carried out at Gaussian smoothing filter
Reason, strengthen ROI region visual effect, finally carry out binary conversion treatment, extract solder joint connected region；
Step E2：The projection in horizontal direction is carried out to the ROI region on direct picture, obtains projection histogram,
The feature of the projection histogram is extracted, calculates Pasteur's distance of the projection histogram, judges whether Pasteur's distance closes
Lattice, if unqualified, it was demonstrated that bridge defects occurs in solder joint, and battery cap is separated, if qualified, judges that the solder joint connects
Whether logical region area is met the requirements, if do not met, battery cap is separated, if qualified, continuation down performs.
The beneficial effects of the invention are as follows：The present invention carries out IMAQ by camera to the front of battery cap, to institute
After the direct picture of collection is handled, by direct picture to the positive edge radian of battery cap, more intermediate annular body, quality
Detection zone and solder joint situation are detected and judge whether qualified, while underproof battery cap are separated, this
The quality testing of battery cap is realized in invention using image processing techniques, and detection speed is fast, and the degree of accuracy is high.
Brief description of the drawings
Technical scheme in order to illustrate the embodiments of the present invention more clearly, make required in being described below to embodiment
Accompanying drawing is briefly described.Obviously, described accompanying drawing is the part of the embodiment of the present invention, rather than is all implemented
Example, those skilled in the art on the premise of not paying creative work, can also obtain other designs according to these accompanying drawings
Scheme and accompanying drawing.
Fig. 1 is the overall flow figure of detection method of the present invention；
Fig. 2 is step B of the present invention specific embodiment flow chart；
Fig. 3 is step C of the present invention specific embodiment flow chart；
Fig. 4 is step D of the present invention specific embodiment flow chart；
Fig. 5 is step E of the present invention specific embodiment flow chart；
Fig. 6 makes the electrical schematic diagram of battery cap vision detection system of the present invention.
Embodiment
Carried out below with reference to the design of embodiment and accompanying drawing to the present invention, concrete structure and caused technique effect clear
Chu, complete description, to be completely understood by the purpose of the present invention, feature and effect.Obviously, described embodiment is this hair
Bright part of the embodiment, rather than whole embodiments, based on embodiments of the invention, those skilled in the art is not paying
The other embodiment obtained on the premise of creative work, belongs to the scope of protection of the invention.In addition, be previously mentioned in text
All connection/annexations, not singly refer to component and directly connect, and refer to be added deduct by adding according to specific implementation situation
Few couple auxiliary, to form more excellent draw bail.Each technical characteristic in the invention, in not conflicting conflict
Under the premise of can be with combination of interactions.
1~Fig. 5 of reference picture, in order to improve the efficiency of battery cap quality of production detection and the degree of accuracy, the invention
A kind of battery cap front visible detection method is disclosed, it is whether qualified mainly for detection of battery cap front quality, it is described
Detection method comprises the following steps：
Step A：Camera is demarcated, the direct picture of battery cap is obtained by camera；
Step B：Direct picture and battery cap are subjected to size comparison, obtain correction coefficient；
Step C：The positive edge radian of battery cap and more intermediate annular body are detected by direct picture, judged
It is whether qualified, if unqualified, underproof battery cap is separated, if qualified, continuation down performs；
Step D：The positive quality testing region of battery cap is detected by direct picture, it is qualified to judge whether,
If unqualified, underproof battery cap is separated, if qualified continuation down performs；
Step E：The positive solder joint situation of battery cap is detected by direct picture, it is qualified to judge whether, if
It is unqualified, underproof battery cap is separated, if qualified, continuation down performs；
Step F：It is qualified to be determined as by above-mentioned steps C to the step E battery caps detected；
Wherein described step C to step E orders can exchange.
Specifically, before IMAQ is carried out to the battery cap, it is necessary first to photograph used in IMAQ
Machine is demarcated, that is, the parameter of camera is set, to improve the precision of acquired image；After direct picture is collected,
Need according to the direct picture size and battery cap actual size, calculate correction coefficient, the correction coefficient is used for
Certain area size in direct picture is converted into actual size during subsequent detection, so as to judge whether the region meets technology
Code requirement；The positive edge radian of battery cap, more intermediate annular body, matter are specifically just detected by the direct picture afterwards
Detection zone and solder joint situation these contents are measured, as long as thering is one not meet technical requirements in above-mentioned several detection contents,
It will be judged as unqualified, and automatically separate underproof battery cap.Detection method of the present invention is exactly
Intellectualized detection is carried out to above-mentioned several contents using image processing techniques, instead of traditional is detection side with the naked eye
Case, greatly increase accuracy in detection and detection efficiency.The other step C to step E belongs to specific detection and judged
Step, the change of its sequencing will not bring influence, therefore no matter step C to step E sequencing on the technical program
How to arrange, belong to the protection domain of the invention.
Be further used as preferred embodiment, in the invention embodiment, in the step B firstly the need of
The region of acquisition battery cap from the full detail of direct picture, i.e. ROI (interested) region, therefore described in present embodiment
Step B comprises the following steps：
Step B1：ROI region positioning is carried out to the direct picture；
Step B2：Point measures corresponding to optional two in the ROI region and battery cap entity, will measure
Two values of gained are compared acquisition correction coefficient.
Specifically, ROI region is positioned by following steps in the invention embodiment：
Step B11：Processing is filtered to the direct picture；
Step B12：Image binaryzation processing is carried out to the direct picture；
Step B13：Contour extraction processing is carried out to the direct picture；
Step B14：Circular fit processing is carried out to the direct picture, obtains ROI region.
Pass through the step B11 to B14, it becomes possible to which the ROI region for being in battery cap extracts from direct picture
Come, i.e., described ROI region is the profile of battery cap in direct picture.
Preferred embodiment is further used as, step C described in the invention embodiment is used for battery
The positive edge radian of block and more intermediate annular body size are detected, and detect the purpose of the positive edge radian of battery cap
It is to judge whether the battery cap overall dimensions meet the requirements, if the marginal arc of battery cap is spent greatly, in further battery
The steadiness of battery cap is difficult to ensure that in assembling process, if battery cap marginal arc is spent small, may result in battery cap
It is difficult to assemble；If the more intermediate annular body is undersized, if causing the reliability of cell electrical contacts to reduce.Specifically, originally
Step C comprises the following steps described in innovation and creation：
Step C1：The marginal point of ROI region is obtained in direct picture, circular fit is carried out to acquired marginal point,
And the first diameter obtained by digital simulation；
Step C2：Judge whether first diameter meets the requirements, if do not met, battery cap is separated, such as
Fruit meets, and continuation down performs；
Step C3：The more intermediate annular body marginal point of ROI region is obtained in direct picture, acquired marginal point is carried out
Circular fit, and the Second bobbin diameter obtained by digital simulation；
Step C4：Judge whether the Second bobbin diameter meets the requirements, if do not met, battery cap is separated, such as
Fruit meets, and continuation down performs.
Detection method described in the invention passes through the diameter of a circle being fitted to battery cap marginal point and correction system
Number, is calculated the first diameter, by judging first diameter whether in the range of the first threshold pre-set, and then sentences
Whether disconnected battery cap edge radian meets the requirements；The similarly diameter of a circle by being fitted to the more intermediate annular body marginal point
And correction coefficient, Second bobbin diameter is calculated, by judging the Second bobbin diameter whether in the Second Threshold model pre-set
In enclosing, and then judge whether the more intermediate annular body size meets the requirements.
It is further used as preferred embodiment, quality testing area described in step D in the invention embodiment
Domain specifically refers to the cut of battery cap physically, rust spot, the region such as soiled and pit, if above-mentioned area occurs in battery cap
Domain, easily influences the visual appearance of battery cap, while also the electric conductivity of battery can be affected, and has to upper
The detection for stating region equally has its necessity.Specifically step D comprises the following steps described in the invention specific embodiment：
Step D1：Noise processed is removed to the ROI region on direct picture, strengthens ROI region visual effect,
Binary conversion treatment is carried out to the ROI region；
Step D2：Black connected region is extracted in the ROI region after step D1 processing, the black connected region is
For the cut of battery cap physically, rust spot, the region such as soiled and pit, judge the black connected region area and
Whether profile length is met the requirements, if do not met, battery cap is separated, if qualified, continuation down performs.
In specific detection process, it is necessary first to accurately extract above-mentioned region to be detected, it is right in this detection method
ROI region on direct picture is removed noise and vision enhancement processing, effectively prominent cut, rust spot, soiled and recessed
The defects of vision regions such as hole, carry out binary conversion treatment, by cut, rust spot, the defects of vision such as soiled and pit region again afterwards
Become black connected region, afterwards in conjunction with the correction coefficient judge black connected region area and overall size whether
Meet the requirements, if undesirable, battery cap is separated, in particular it is required that by the black connected region area
Judge compared with the area threshold pre-set, and by the profile length of the black connected region and pre-set
Profile length threshold value is compared judgement.
Preferred embodiment is further used as, step E is mainly for detection of electricity in the invention embodiment
Whether block positive solder joint situation in pond meets demand of technical standard, and detecting the solder joint situation includes needing to detect solder joint face
Product, the black degree of the weldering of solder joint and whether there is rosin joint phenomenon.Specifically step E bags described in the invention specific embodiment
Include following steps：
Step E1：Gray processing processing is carried out to the ROI region on direct picture, then carried out at Gaussian smoothing filter
Reason, strengthen ROI region visual effect, finally carry out binary conversion treatment, extract solder joint connected region, the solder joint connected region generation
Black region is welded on the technology solder joint of table；
Step E2：The projection in horizontal direction is carried out to the ROI region on direct picture, obtains projection histogram,
The feature of the projection histogram is extracted, calculates Pasteur's distance of the projection histogram, judges whether Pasteur's distance closes
Lattice, if unqualified, it was demonstrated that bridge defects occurs in solder joint, and battery cap is separated, if qualified, judges that the solder joint connects
Whether logical region is met the requirements, if do not met, battery cap is separated, if qualified, continuation down performs.
Gray processing and gaussian filtering process specifically are carried out to the ROI region of direct picture first in the step E, so
Afterwards in enhancing ROI region image visual effect, finally carry out binary conversion treatment and extracted solder joint connected region with realizing.It
The projection that ROI region after afterwards will be treated is carried out in horizontal direction obtains projection histogram, calculates the projection histogram
Pasteur's distance, by Pasteur's distance of gained compared with the Pasteur's distance threshold pre-set, judge that Pasteur's distance is
It is no qualified, if unqualified, it was demonstrated that bridge defects occur for battery cap solder joint, it is necessary to be isolated away；Finally to the weldering
Point connected region area detected, by by solder joint connected region area compared with the solder joint threshold value pre-set,
It is qualified to judge whether, if unqualified, battery cap is separated.
It is that detection in all directions is carried out to the battery cap in addition, the detection method described in the invention also needs to
Increase battery cap reverse side vision-based detection step after step E.Also include step G after step E described in the invention, by electricity
Pond block upset, the verso images of battery cap are obtained by camera, verso images and battery cap actual size are entered
Row compares, and obtains another correction coefficient, the edge bound edge according to the verso images to battery cap reverse side, cut lack afterwards
Fall into region and welding breakdown area to be detected, judge whether above-mentioned zone meets technical requirements, if do not met, just by electricity
Pond block is separated.Wherein battery cap verso images are carried out with edge bound edge detection, scratch defects region and welding are hit
The specific steps for wearing region detection are similar with step C and step D in battery cap direct picture detection process.
Reference picture 6, the invention also disclose a kind of battery cap vision detection system simultaneously, including for obtaining electricity
The industrial camera of pond block direct picture and verso images, automatic feed mechanism, automatic turning mechanism, Pneumatic separation mechanism,
Transport establishment, industrial computer and PLC processor, the PLC processor control industrial camera, automatic charging machine respectively
Structure, automatic turning mechanism, Pneumatic separation mechanism and the startup optimization of transport establishment, the industrial computer and industrial camera
It is connected for carrying out image procossing；Specifically, the battery cap is transported in transport establishment by automatic feed mechanism, now
Industrial camera gathers the direct picture of battery cap, is afterwards overturn battery cap by automatic turning mechanism, now industrial
Camera gathers the verso images of battery cap, and the direct picture gathered and verso images are transferred to work by industrial camera
Industry computer carries out processing detection, judges whether battery cap is qualified, and testing result is transferred into PLC processor, has at PLC
Reason device control Pneumatic separation mechanism separates underproof battery cap.Pass through the battery cap vision detection system energy
Enough intelligent quality detections for realizing battery cap automatically and sort operation, detection efficiency is high, while also ensures there is higher standard
Exactness.
The better embodiment of the present invention is illustrated above, but the invention is not limited to the implementation
Example, those skilled in the art can also make a variety of equivalent modifications on the premise of without prejudice to spirit of the invention or replace
Change, these equivalent modifications or replacement are all contained in the application claim limited range.
Claims (6)
1. a kind of battery cap front visible detection method, it is characterised in that comprise the following steps：
Step A：Camera is demarcated, the direct picture of battery cap is obtained by camera；
Step B：Direct picture and battery cap are subjected to size comparison, obtain correction coefficient；
Step C：The positive edge radian of battery cap and more intermediate annular body are detected by direct picture, judged whether
It is qualified, if unqualified, underproof battery cap is separated, if qualified, continuation down performs；
Step D：The positive quality testing region of battery cap is detected by direct picture, it is qualified to judge whether, if
It is unqualified, underproof battery cap is separated, if qualified, continuation down performs；
Step E：The positive solder joint situation of battery cap is detected by direct picture, it is qualified to judge whether, if do not conformed to
Lattice, underproof battery cap is separated, if qualified, continuation down performs；
Step F：It is qualified to be determined as by above-mentioned steps C to the step E battery caps detected；
Wherein described step C to step E orders can exchange.
2. a kind of battery cap front visible detection method according to claim 1, it is characterised in that the step B includes
Following steps：
Step B1：ROI region positioning is carried out to the direct picture；
Step B2：Point measures corresponding to optional two in the ROI region and battery cap entity, by measurement gained
Two values be compared acquisition correction coefficient.
A kind of 3. battery cap front visible detection method according to claim 2, it is characterised in that the step B1 with
Lower step：
Step B11：Processing is filtered to the direct picture；
Step B12：Image binaryzation processing is carried out to the direct picture；
Step B13：Contour extraction processing is carried out to the direct picture；
Step B14：Circular fit processing is carried out to the direct picture, obtains ROI region.
4. a kind of battery cap front visible detection method according to claim 3, it is characterised in that the step C includes
Following steps：
Step C1：The marginal point of ROI region is obtained in direct picture, circular fit is carried out to acquired marginal point, and count
Calculate the first diameter of fitting gained；
Step C2：Judge whether first diameter meets the requirements, if do not met, battery cap is separated, if symbol
Close, continuation down performs；
Step C3：The more intermediate annular body marginal point of ROI region is obtained in direct picture, acquired marginal point is carried out circular
Fitting, and the Second bobbin diameter obtained by digital simulation；
Step C4：Judge whether the Second bobbin diameter meets the requirements, if do not met, battery cap is separated, if symbol
Close, continuation down performs.
5. a kind of battery cap front visible detection method according to claim 3, it is characterised in that the step D includes
Following steps：
Step D1：Noise processed is removed to the ROI region on direct picture, strengthens ROI region visual effect, to institute
State ROI region and carry out binary conversion treatment；
Step D2：Black connected region is extracted in the ROI region after step D1 processing, judges the black connected region
Whether area and profile length are met the requirements, if do not met, battery cap is separated, if qualified, are continued down
Perform.
6. a kind of battery cap front visible detection method according to claim 3, it is characterised in that the step E includes
Following steps：
Step E1：Gray processing processing is carried out to the ROI region on direct picture, then carries out Gaussian smoothing filter processing, is increased
Strong ROI region visual effect, finally carries out binary conversion treatment, extracts solder joint connected region；
Step E2：The projection in horizontal direction is carried out to the ROI region on direct picture, obtains projection histogram, extraction
The feature of the projection histogram, Pasteur's distance of the projection histogram is calculated, judge whether Pasteur's distance is qualified, such as
Fruit is unqualified, it was demonstrated that bridge defects occurs in solder joint, and battery cap is separated, if qualified, judges the solder joint connected region
Whether domain is met the requirements, if do not met, battery cap is separated, if qualified, continuation down performs.
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| CN108188036A (en) * | 2017-12-29 | 2018-06-22 | 福建猛狮新能源科技有限公司 | The system of automatic detection li battery shell |
| CN108362739A (en) * | 2018-03-30 | 2018-08-03 | 昆山华誉自动化科技有限公司 | The method for detecting the equipment and detection welding battery quality of welding battery quality |
| CN108846836A (en) * | 2018-05-31 | 2018-11-20 | 慕贝尔汽车部件（太仓）有限公司 | Spring detection device, spring detection method and device |
| CN109283182A (en) * | 2018-08-03 | 2019-01-29 | 江苏理工学院 | A kind of detection method of battery welding point defect, apparatus and system |
| CN109685789A (en) * | 2018-12-24 | 2019-04-26 | 广州超音速自动化科技股份有限公司 | The battery core surface gummed paper detection method and device of view-based access control model detection |
| CN109859186A (en) * | 2019-01-31 | 2019-06-07 | 江苏理工学院 | A kind of lithium battery mould group positive and negative anodes detection method based on halcon |
| CN114047195A (en) * | 2021-11-11 | 2022-02-15 | 合肥工业大学智能制造技术研究院 | New energy battery cap defect detection method and system |
| CN117723491A (en) * | 2024-02-07 | 2024-03-19 | 宁德时代新能源科技股份有限公司 | Detection system and detection method for battery cell explosion-proof valve |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH10261388A (en) * | 1997-03-19 | 1998-09-29 | Furukawa Battery Co Ltd:The | Quality inspection method and device for applied condition of sealant applying part |
| CN105548216A (en) * | 2016-01-15 | 2016-05-04 | 浙江野马电池有限公司 | Visual detection method for appearance of semi-finished battery |
| CN105548201A (en) * | 2016-01-15 | 2016-05-04 | 浙江野马电池有限公司 | Battery welding cap visual-inspection method |
| CN106251352A (en) * | 2016-07-29 | 2016-12-21 | 武汉大学 | A kind of cover defect inspection method based on image procossing |
-
2017
- 2017-07-06 CN CN201710544998.5A patent/CN107516308B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH10261388A (en) * | 1997-03-19 | 1998-09-29 | Furukawa Battery Co Ltd:The | Quality inspection method and device for applied condition of sealant applying part |
| CN105548216A (en) * | 2016-01-15 | 2016-05-04 | 浙江野马电池有限公司 | Visual detection method for appearance of semi-finished battery |
| CN105548201A (en) * | 2016-01-15 | 2016-05-04 | 浙江野马电池有限公司 | Battery welding cap visual-inspection method |
| CN106251352A (en) * | 2016-07-29 | 2016-12-21 | 武汉大学 | A kind of cover defect inspection method based on image procossing |
Non-Patent Citations (1)
| Title |
|---|
| 闫旭: "基于机器视觉的电池尾端缺陷检测算法的研究", 《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》 * |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108188036A (en) * | 2017-12-29 | 2018-06-22 | 福建猛狮新能源科技有限公司 | The system of automatic detection li battery shell |
| CN108362739A (en) * | 2018-03-30 | 2018-08-03 | 昆山华誉自动化科技有限公司 | The method for detecting the equipment and detection welding battery quality of welding battery quality |
| CN108362739B (en) * | 2018-03-30 | 2023-11-10 | 昆山华誉自动化科技有限公司 | Device for detecting welding quality of battery and method for detecting welding quality of battery |
| CN108846836A (en) * | 2018-05-31 | 2018-11-20 | 慕贝尔汽车部件（太仓）有限公司 | Spring detection device, spring detection method and device |
| CN108846836B (en) * | 2018-05-31 | 2021-04-02 | 慕贝尔汽车部件（太仓）有限公司 | Spring detection equipment, spring detection method and device |
| CN109283182A (en) * | 2018-08-03 | 2019-01-29 | 江苏理工学院 | A kind of detection method of battery welding point defect, apparatus and system |
| CN109685789A (en) * | 2018-12-24 | 2019-04-26 | 广州超音速自动化科技股份有限公司 | The battery core surface gummed paper detection method and device of view-based access control model detection |
| CN109859186A (en) * | 2019-01-31 | 2019-06-07 | 江苏理工学院 | A kind of lithium battery mould group positive and negative anodes detection method based on halcon |
| CN114047195A (en) * | 2021-11-11 | 2022-02-15 | 合肥工业大学智能制造技术研究院 | New energy battery cap defect detection method and system |
| CN117723491A (en) * | 2024-02-07 | 2024-03-19 | 宁德时代新能源科技股份有限公司 | Detection system and detection method for battery cell explosion-proof valve |
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