CN104568974A - Area-comparison-algorithm-based soldering lug defect and missing detection method - Google Patents
Area-comparison-algorithm-based soldering lug defect and missing detection method Download PDFInfo
- Publication number
- CN104568974A CN104568974A CN201310502557.0A CN201310502557A CN104568974A CN 104568974 A CN104568974 A CN 104568974A CN 201310502557 A CN201310502557 A CN 201310502557A CN 104568974 A CN104568974 A CN 104568974A
- Authority
- CN
- China
- Prior art keywords
- lamp holder
- area
- defect
- algorithm
- weld tabs
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Abstract
The invention discloses an area-comparison-algorithm-based soldering lug defect and missing detection method for lamp holder product inspection. The soldering lug defect and missing detection method is mainly applied to lamp holder products with clamping mouth type double soldering lugs and clamping mouth type single soldering lugs, is used for detecting defects and missing of the soldering lugs of the lamp holder; an area comparison algorithm is adopted, in a standard and qualified lamp holder image, the area of the soldering lug is within certain limits, if the soldering lug at the tail part of the lamp holder has a defect, the area of the soldering lug is abnormal, and the corresponding area characteristic detecting algorithm is used to calculate the area of two soldering lugs at the tail part of the lamp holder, then the calculated area is compared with the standard value, if the area difference exceeds the set threshold value, the soldering lug is judged to have a defect, and the defect and missing detection on the lamp holder product can be realized, and the quality inspection to the to-be-detected product is completed. The area-comparison-algorithm-based soldering lug defect and missing detection method has the advantages of high detection precision, high response speed, strong anti-jamming capability, good reliability and maintainability, strong universality and the like.
Description
Technical field
The present invention relates to the automatic testing method of lamp holder product quality problem, in particular to the weld tabs defect disappearance problem in lamp holder product quality problem, the coherent detection field of lamp holder product automatic detection system and other product quality problem of appearance should can be applied to based on the weld tabs defect disappearance detection method of Area comparison algorithm.
Background technology
Electric light source is as daily necessities requisite in mankind's daily life, and its annual use and quantity consumed are very huge, and in electric light source production run, have consequence as the quality testing of the critical piece lamp holder of electric light source products.The inspection of current China lamp holder product is main still by means of vision and the subjective judgement ability of people, thus a large amount of manual labor is occupied, and owing to being subject to the eyesight of individual, mood, tired, the impact of the factors such as light, inefficiency, go-on-go difference is large, Detection results is limited, particularly along with the raising of lamp holder production efficiency and production automation level, output is multiplied, then need to drop into more human resources to carry out the quality testing of product, this materially increases the operation cost of manufacturing enterprise, become enterprise to enhance productivity and take into account the bottleneck of benefit.
Summary of the invention
For solving the problem, the object of this invention is to provide a kind of weld tabs defect based on Area comparison algorithm disappearance detection method, improve lamp holder product automatic detection system to the detection efficiency of product quality problem and precision, reduce the operation cost of the examination and test of products, improve the production efficiency of product.
Detection algorithm of the present invention is achieved by the following technical programs:
Weld tabs defect disappearance detection method based on Area comparison algorithm is important step in lamp holder product quality problem automatic detection system, and the method that have employed based on image characteristics extraction realizes the quality testing to lamp holder product.For the weld tabs disappearance defect flaw existed in lamp holder product, this checking system devises pointed stable, lamp holder characteristics algorithm combination efficiently and carries out feature extraction to lamp holder product, to be detected and the Classification and Identification of defect by the algorithm of Area comparison to lamp holder product quality.
The invention has the beneficial effects as follows: rough estimates, under the condition of manual detection, can only reach about 94% to the screening rate of weld tabs disappearance defect in waste product lamp holder, detection speed is about everyone 20-25 per minute.Due to the speed of artificial screening and precision on the low side, need to take a large amount of manual labor, this greatly constrains production efficiency and the economic benefit of enterprise simultaneously.The present invention is exactly how research solve the weld tabs defect disappearance problem in lamp holder product quality problem on-line checkingi and screening problem at industry spot applied for machines vision technique, and be applied to the artificial screening work of production scene replacement inefficiency, the screening rate of expection waste product lamp holder will reach more than 98%, detection speed is more than 200 per minute, can improve detection efficiency and the precision of product compared with manual detection greatly; Weld tabs defect disappearance detection method based on Area comparison algorithm will play an important role in lamp holder automatic detection system, and the successful development of this detection system simultaneously will be subject to the manufacturing very big welcome of lamp holder.
Accompanying drawing explanation
Fig. 1 is lamp holder product automatic detection system organizational structure design schematic diagram.
Fig. 2 compares before and after pre-service after product image acquisition to be checked.
Fig. 3 specification product to be checked and weld tabs defect disappearance product compare.
Fig. 4 is based on the region growing thought algorithm of Area comparison.
Embodiment
Below in conjunction with the drawings and specific embodiments, illustrate the present invention further, these embodiments should be understood only be not used in for illustration of the present invention and limit the scope of the invention, after having read the present invention, the amendment of those skilled in the art to the various equivalent form of value of the present invention has all fallen within the application's claims limited range.
As shown in Figure 1, weld tabs defect based on Area comparison algorithm lacks detection method in lamp holder product automatic detection system, substandard products mainly for weld tabs defect deletion condition detect: lamp holder product carries out ordered arrangement by vibration feeder, by belt feeding workbench in order by lamp holder product place to be checked, when lamp holder product runs to product place to be checked, be arranged on proximity switch near product place to be checked by generation pulse signal, this signal sends into PC by switch card, PC controls image pick-up card and gathers lamp holder product image to internal memory by industrial camera after receiving signal, then image recognition processing software carries out analyzing and processing to lamp holder image, differentiate whether this lamp holder is specification product, as the situation that weld tabs defect lacks appears in lamp holder product, then identify its defect type and send rejecting signal by switch card to corresponding rejecting mechanism and carry out classification rejecting, not constantly running like this.
As shown in Figure 2, carrying out in Product checking process, in the process that lamp holder image is gathered, in order to reduce the discrimination of the interference of background, outstanding lamp holder to be checked, raising image, the background designs at place to be checked for lamp holder is become black, namely lamp holder image gathers under black background, the extraction of follow-up lamp holder image procossing and the lamp holder feature of being more convenient for like this, in order to improve the execution efficiency of successive image Processing Algorithm, reduce the interference of useless region in picture, first we carried out lamp holder location and dividing processing to the initial pictures collected.Figure 3 shows that comparing after carrying out image procossing under the complete and defect deletion condition of the lamp holder product weld tabs of collection.
As shown in Figure 4, the computational algorithm based on region growing thought designed in the calculating of weld tabs size is described.Region growing refers to from certain pixel, according to certain criterion, progressively adds the pixel of closing on, and when certain conditions are met, region growing stops.Mainly contain three characteristic areas composition shown in Fig. 4, one is the fringe region of lamp holder, and this is a white rings region be communicated with, and is two weld tabs regions in addition, and they are two independent white portions be communicated with respectively.Search for characteristic area is located, and native system have employed simple searching algorithm, is specially, adopt the method for lining by line scan, pretreated lamp holder image being scanned, having continuous print 20 pixels to be white when scanning in a line) time, then think and searched characteristic area.As Seed Points, area and centroid calculation are carried out to this characteristic area using any point in these 20 pixels, then search for next characteristic area in the same way and carry out area and centroid calculation, only to the feature extraction completed all characteristic areas.
Claims (2)
1. based on the weld tabs disappearance detection method of Area comparison algorithm, it is characterized in that: mainly for the weld tabs defect flaw problem in lamp holder product quality, by the lamp holder product automatic detection system of machine vision, the image information of product to be checked is extracted through camera, transfer to computing machine, analysis identification and the feature extraction process of image is carried out by image processing software, software algorithm according to Area comparison detects the weld tabs defect disappearance problem in lamp holder product problem to be checked, differentiates whether product quality meets the requirements.
2. the software algorithm of Area comparison according to claim 1, it is characterized in that: by the area of the qualified weld tabs of standard of comparison, if there is defect in lamp holder afterbody weld tabs, then its weld tabs area will occur abnormal, so corresponding software algorithm can be adopted to calculate the size of two weld tabs of lamp holder afterbody, then compare with standard value, if size difference exceeds setting threshold value, then judge that weld tabs has defect; The calculating of butt welding sheet area, this algorithm design is based on the computational algorithm of region growing thought.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310502557.0A CN104568974A (en) | 2013-10-22 | 2013-10-22 | Area-comparison-algorithm-based soldering lug defect and missing detection method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310502557.0A CN104568974A (en) | 2013-10-22 | 2013-10-22 | Area-comparison-algorithm-based soldering lug defect and missing detection method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN104568974A true CN104568974A (en) | 2015-04-29 |
Family
ID=53085541
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201310502557.0A Pending CN104568974A (en) | 2013-10-22 | 2013-10-22 | Area-comparison-algorithm-based soldering lug defect and missing detection method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104568974A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109472767A (en) * | 2018-09-07 | 2019-03-15 | 浙江大丰实业股份有限公司 | Stage lamp miss status analysis system |
| CN109544547A (en) * | 2018-11-30 | 2019-03-29 | 湘潭大学 | A kind of bayonet type autobulb lamp cap top open defect detection method |
| CN112669460A (en) * | 2020-12-31 | 2021-04-16 | 新拓三维技术(深圳)有限公司 | Workpiece defect detection method and system and computer readable storage medium |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7295314B1 (en) * | 1998-07-10 | 2007-11-13 | Nanometrics Incorporated | Metrology/inspection positioning system |
| CN102221557A (en) * | 2011-03-31 | 2011-10-19 | 南京航空航天大学 | Automatic detecting device and detection method for quality of lamp holder based on machine vision |
-
2013
- 2013-10-22 CN CN201310502557.0A patent/CN104568974A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7295314B1 (en) * | 1998-07-10 | 2007-11-13 | Nanometrics Incorporated | Metrology/inspection positioning system |
| CN102221557A (en) * | 2011-03-31 | 2011-10-19 | 南京航空航天大学 | Automatic detecting device and detection method for quality of lamp holder based on machine vision |
Non-Patent Citations (3)
| Title |
|---|
| 王琪: "基于机器视觉的灯头产品质量检验系统研究", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
| 王琪等: "基于机器视觉的灯头产品质量在线检验系统研究", 《计算机测量与控制》 * |
| 胡鹏等: "全自动灯头质量机器视觉检测系统", 《灯与照明》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109472767A (en) * | 2018-09-07 | 2019-03-15 | 浙江大丰实业股份有限公司 | Stage lamp miss status analysis system |
| CN109472767B (en) * | 2018-09-07 | 2022-02-08 | 浙江大丰实业股份有限公司 | Stage lamp missing state analysis system |
| CN109544547A (en) * | 2018-11-30 | 2019-03-29 | 湘潭大学 | A kind of bayonet type autobulb lamp cap top open defect detection method |
| CN112669460A (en) * | 2020-12-31 | 2021-04-16 | 新拓三维技术(深圳)有限公司 | Workpiece defect detection method and system and computer readable storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102284431B (en) | On-line detection grading device for lithium ion battery pole piece and method thereof | |
| CN205643194U (en) | Touch -control ITO film conducting layer defect detection system based on machine vision | |
| CN203750868U (en) | Computer vision-based burr detection device | |
| CN103808730B (en) | Engine cam component surface defect inspection method | |
| CN205538710U (en) | Inductance quality automatic check out system based on machine vision | |
| CN104614379A (en) | Plate surface defect detection system and method | |
| CN208313802U (en) | A kind of chip pin defect detecting system based on machine vision | |
| WO2012027869A1 (en) | Online quality detection method for closure assembly | |
| CN101696945A (en) | On-line detection method of machine vision system to photovoltaic glass flaws | |
| CN110517233A (en) | A kind of defect classification learning system and its classification method based on artificial intelligence | |
| CN104568974A (en) | Area-comparison-algorithm-based soldering lug defect and missing detection method | |
| CN106248680A (en) | A kind of engine commutator quality detecting system based on machine vision and detection method | |
| CN106353340B (en) | A kind of rodlike high reflectance surface defects of parts detection method | |
| CN109507205A (en) | A kind of vision detection system and its detection method | |
| CN105784719A (en) | Machine vision inspection terminal capable of sorting goods | |
| CN102303018B (en) | Method for automatically detecting burrs of injector steel needles by using machine vision system | |
| CN104833925A (en) | Fuel cell bipolar plate detection method and system based on machine vision | |
| CN111766245A (en) | Button battery negative electrode shell defect detection method based on machine vision | |
| CN103308593A (en) | Defect intelligent identification detection system for magnetic powder welding flaw detection | |
| CN202700832U (en) | Dynamic identification device of inferior products in production | |
| CN202074946U (en) | Cigarette case appearance detecting device | |
| CN102305603B (en) | Method for automatically detecting inclination of steel needle of injector by machine vision system | |
| CN102305797A (en) | Method for automatically detecting foreign matter of medical product package by using machine vision system | |
| CN202171575U (en) | Machine vision detection device for detecting optics lens appearance | |
| CN104568978A (en) | Lamp holder optical head defect detection method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WD01 | Invention patent application deemed withdrawn after publication | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20150429 |