CN202471610U - Automatic bottle body defect detecting device based on machine vision - Google Patents
Automatic bottle body defect detecting device based on machine vision Download PDFInfo
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- CN202471610U CN202471610U CN2011205633816U CN201120563381U CN202471610U CN 202471610 U CN202471610 U CN 202471610U CN 2011205633816 U CN2011205633816 U CN 2011205633816U CN 201120563381 U CN201120563381 U CN 201120563381U CN 202471610 U CN202471610 U CN 202471610U
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Abstract
The utility model belongs to the technical field of automatic detection and relates to an automatic bottle body defect detecting device based on machine vision. A bottle body to be detected is conveyed by an assembly line with a guide rail; five cameras are fixed beside the guide rail; the automatic bottle body defect detecting device comprises a front-end camera for shooting a bottle opening image, three bottle body cameras for shooting a bottle body image, and a bottle bottom camera for shooting a bottle bottom image; an encoder is used for sensing a movement beat of the assembly line; an in-place sensor is used for sensing the position of the bottle body; each camera is controlled by a controller according to a sensed signal to shoot the image; the images shot by each camera are sent to a computer; and the computer is used for detecting whether the bottle body has the defects or not according to the images. The utility model further provides an automatic bottle body defect detecting method realized by the device. The automatic bottle body defect detecting device disclosed by the utility model overcomes interference and a large part of dead zone in subjective factors in a manual ocular estimation method, and can enable the defects of the bottle body to be rapidly and accurately detected, so that the detection precision and efficiency of product quality are improved.
Description
Technical field
The utility model belongs to the Automatic Measurement Technique field, particularly about detecting the device of body defective.
Technical background
Along with the aggravation of global economic integration trend, the plastic bottle manufacturing is also increasingly high to the requirement of product quality, forces the company of relevant industries and enterprise in the quality inspection of product, to drop into more manpower financial capacity.In the manufacturing process of plastic bottle, the defective of body is to weigh an importance of product quality.And body not only can cause client's complaint and claim after having the plastic bottle of bad defective and coming into the market, and brings unpredicted fame and economic loss to manufacturer, directly influences the market image of manufacturer, has also damaged client's interests simultaneously.
What carry out the bad detection of body at present mainly is to use manual detection, and in plastic bottle production run process, dissimilar defectives emerge one after another, like bubble, lack material, stain, injure, moulding is bad etc.; Whether the traditional detection mode exists defect problem by operative employee's visual inspection, and carries out corresponding rejecting.The manual detection method is directly perceived, but has big blind area, and it is bigger influenced by subjective factor, and workman's working strength is big, works long hours to be prone to cause visual fatigue, misjudgment occurs, influences the quality testing of product; When line body excessive velocities, the operative employee can't accomplish detection basically.
The utility model content
In view of the above problems, the purpose of the utility model provides a kind of automatic detection device that can adapt to the body detection based on machine vision.The utility model is realized through following technical scheme:
A kind of body defective automatic detection device based on machine vision; Bottle to be checked is fixed with five video cameras by the streamline transmission that has guide rail on the guide rail side, comprises that one is used to take the front-end camera of bottleneck image, three body video camera and bottle end video cameras that are used to take bottle base map picture that are used to take the body image; Wherein, Front-end camera adopts the ring radiant, and other four video cameras all adopt back light, and the observation angle of each body video camera is all different; Scrambler is fixed on the transmission the tip of the axis; The tact of motion that is used for the perception streamline; Be used for perception bottle position to level sensor, the signal of both perception is admitted to controller, by controller each video camera photographic images of signal controlling according to perception; The image that each video camera is taken is admitted to computing machine, whether has defective by computing machine according to image detection bottle to be checked.
The body defective automatic detection device of the utility model through images acquired, detects the body defective, in time reports to the police or rejecting for defective product, thus the quality of assurance product.This device is applied to overcome interference and most of blind area of subjective factor in artificial visually examine's method fully on the similar bottle blowing line body, can detect accuracy of detection of improving the quality of products greatly and efficient by defect problem quick, objective, that exactly body is existed.
Description of drawings
Fig. 1: the utility model hardware system outward appearance is formed synoptic diagram;
Fig. 2: the utility model software detection analytic product process flow diagram.Accompanying drawing mark explanation: 1 computing machine; 2 line bodies; 3 black and white area array cameras; 4 lighting sources; 5 scramblers; 6 servomotors; 7 to level sensor.
Embodiment
Referring to Fig. 1; The body defective automatic detection device based on machine vision of the utility model; Mainly comprise computing machine 1, line body 2, black and white area array camera 3, lighting source 4, scrambler 5, servomotor 6, constitute by black and white Array CCD Camera 3 and the image pick-up card that is installed in the computing machine that lighting source 4 adopts ring light and backlight to level sensor 7, image capturing system.Computer-internal is equipped with IMAQ Control Software and analyzing and detecting software.
This instance is applicable to and detects bottle blowing line body; Be installed in line body front end to level sensor, scrambler is installed on the transmission shaft, and the rotation of scrambler and turning axle keeps synchronously; Be installed in the scrambler on the transmission shaft, all be admitted to the PLC controller to the signal of level sensor and scrambler output; It is to adopt Array CCD Camera that light source adopts ring light and backlight, video camera, and front-end camera is installed in ring light positive top, and other 4 video cameras all adopt backlight; Scrambler is fixed on the transmission the tip of the axis; The tact of motion that is used for the perception streamline; To level sensor is photoelectric sensor; Whether the detection station that is used for perception front-end camera place exists bottle, and whether the PLC controller gets into according to the signal sensing bottle to level sensor and scrambler that receives is detected station and line body movement rhythm, triggers the moment of taking pictures thereby can control each ccd video camera; Video camera, light source, to the power supply of level sensor, PLC programmable controller and motor and driver thereof etc. all through cable by power supply completion in the rack.
The method that realizes: whether PLC controller (not drawing among the figure) gets into according to the signal sensing bottle to level sensor and scrambler that receives is detected station and line body movement rhythm; Send the camera trigger pip; Front-end camera at first begins to take the bottleneck image, for bottleneck burr, bottleneck are injured, the scarce material of bottleneck etc. provides the image support; Operation along with the line body; Ensuing three cameras are respectively from different angle shots, and the observation angle scope of each camera is 120 degree, three camera interlocks; Guarantee the panorama of body,, body bubble bad for moulding, body stain, broken hole etc. provide complete image support; Last video camera is taken a bottle base map picture, for injure at the bottom of the bottle, bottle basis bubble, broken hole etc. provide the image support; The image of all collections all is transferred to computing machine, by software image is carried out defect analysis.
As shown in Figure 2, software is divided into following several method according to different detection softwares:
1. bottleneck burr: camera triggers and takes pictures; Image pre-service (comprise image binaryzation, corrosion is expanded etc., make bottleneck edge more clear); Search the bottleneck edge; Circle, cylindrical in the match bottleneck; Detect the cylindrical outside and interior inner round side gray-scale value whether in normal range.
2. bottleneck is injured, injure in the bottle end, bottleneck lacks material, moulding is bad: camera triggers and takes pictures; The localization method different according to the different detection choice of location; Surveyed area is carried out template matches, and similarity is lower than preset threshold values and then determines that it is bad.
3. body bubble, bottle basis bubble, body stain, broken hole: camera triggers and takes pictures; Because bottle itself is transparent, when there was above-mentioned defective in a part, it is big that the gray-scale value of the image at this position is wanted, and according to this principle, adopts following method to carry out defects detection: image is carried out binary conversion treatment; The non-surveyed area of mask (covering); The tested image of qualified figure image subtraction that use prestores if residue picture gray-scale value is too high, is higher than certain preset threshold value, then is judged to be bad.
Analysis result is integrated,, unified to reject by the device for eliminating of rear end if there have a place to detect to be bad then by alarm equipment alarm.
Claims (1)
1. body defective automatic detection device based on machine vision; Bottle to be checked comprises that by the streamline transmission that has guide rail video camera and light source is characterized in that, described video camera has 5; Be separately fixed at the other diverse location of guide rail; Comprise that one is used to take the front-end camera of bottleneck image, three body video camera and bottle end video cameras that are used to take bottle base map picture that are used to take the body image, wherein, front-end camera adopts the ring radiant; Other four video cameras all adopt back light, and the observation angle of each body video camera is all different; Scrambler is fixed on the transmission the tip of the axis; The tact of motion that is used for the perception streamline; Be used for perception bottle position to level sensor, the signal of both perception is admitted to controller, by controller each video camera photographic images of signal controlling according to perception; The image that each video camera is taken is admitted to computing machine, whether has defective by computing machine according to image detection bottle to be checked.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2011205633816U CN202471610U (en) | 2011-12-29 | 2011-12-29 | Automatic bottle body defect detecting device based on machine vision |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2011205633816U CN202471610U (en) | 2011-12-29 | 2011-12-29 | Automatic bottle body defect detecting device based on machine vision |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN202471610U true CN202471610U (en) | 2012-10-03 |
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Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN2011205633816U Expired - Fee Related CN202471610U (en) | 2011-12-29 | 2011-12-29 | Automatic bottle body defect detecting device based on machine vision |
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| Country | Link |
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| CN (1) | CN202471610U (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102539443A (en) * | 2011-12-29 | 2012-07-04 | 天津普达软件技术有限公司 | Bottle body defect automatic detection device based on machine vision and method thereof |
| CN108580333A (en) * | 2018-04-17 | 2018-09-28 | 湖北理工学院 | Level sensing study of platform based on machine vision and design |
| CN110132974A (en) * | 2018-02-08 | 2019-08-16 | 克朗斯股份公司 | The monitoring method and bottle washing machine of bottle unit |
| CN111426697A (en) * | 2020-05-09 | 2020-07-17 | 北京妙想科技有限公司 | Body defect visual inspection device |
| CN113203748A (en) * | 2021-03-09 | 2021-08-03 | 深兰科技（上海）有限公司 | Follow bottle and shoot device and bottle check out test set |
-
2011
- 2011-12-29 CN CN2011205633816U patent/CN202471610U/en not_active Expired - Fee Related
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102539443A (en) * | 2011-12-29 | 2012-07-04 | 天津普达软件技术有限公司 | Bottle body defect automatic detection device based on machine vision and method thereof |
| CN102539443B (en) * | 2011-12-29 | 2013-07-03 | 天津普达软件技术有限公司 | Bottle body defect automatic detection method based on machine vision |
| CN110132974A (en) * | 2018-02-08 | 2019-08-16 | 克朗斯股份公司 | The monitoring method and bottle washing machine of bottle unit |
| CN108580333A (en) * | 2018-04-17 | 2018-09-28 | 湖北理工学院 | Level sensing study of platform based on machine vision and design |
| CN111426697A (en) * | 2020-05-09 | 2020-07-17 | 北京妙想科技有限公司 | Body defect visual inspection device |
| CN113203748A (en) * | 2021-03-09 | 2021-08-03 | 深兰科技（上海）有限公司 | Follow bottle and shoot device and bottle check out test set |
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Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20121003 Termination date: 20141229 |
|
| EXPY | Termination of patent right or utility model |