CN110220910A - A kind of lithium battery total quality on-line monitoring system and method based on machine vision - Google Patents
A kind of lithium battery total quality on-line monitoring system and method based on machine vision Download PDFInfo
- Publication number
- CN110220910A CN110220910A CN201910376717.9A CN201910376717A CN110220910A CN 110220910 A CN110220910 A CN 110220910A CN 201910376717 A CN201910376717 A CN 201910376717A CN 110220910 A CN110220910 A CN 110220910A
- Authority
- CN
- China
- Prior art keywords
- lithium battery
- image
- module
- machine vision
- line monitoring
- 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.)
- Withdrawn
Links
Classifications
-
- 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
-
- 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
-
- 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
Abstract
The present invention relates to lithium battery quality monitoring technical fields, disclose a kind of lithium battery total quality on-line monitoring system based on machine vision, comprising: image capture module, the image of multiple angles for acquiring lithium battery；Data transmission module；Image processing module, for handling the image that data transmission module transmits；Analysis module, the lithium battery feature for extracting to image processing module are analyzed, and mass defect is found out；Display module.The invention also discloses a kind of lithium battery total quality on-line monitoring method based on machine vision.The image that the lithium battery total quality on-line monitoring system based on machine vision passes through multiple angles of acquisition lithium battery, image is handled, extract the feature of lithium battery, lithium battery feature is analyzed, find out mass defect, it solves the monitoring mode manually checked there are working efficiencies low, monitor incomplete problem.
Description
Technical field
The present invention relates to lithium battery quality monitoring technical field, the comprehensive matter of specifically a kind of lithium battery based on machine vision
Measure on-line monitoring system and method.
Background technique
Machine vision is fast-developing branch of artificial intelligence.In brief, machine vision is exactly to use machine
It measures and judges instead of human eye.NI Vision Builder for Automated Inspection will be ingested by machine vision product (i.e. image-pickup device)
Target is converted into picture signal, sends dedicated image processing system to, obtains the shape information of target subject, according to pixel point
The information such as cloth and brightness, color, are transformed into digitized signal；Picture system carries out various operations to these signals to extract target
Feature.
Traditional lithium battery quality monitoring is carried out by way of manually checking, and working efficiency is low, monitors not comprehensive.Needle
To the above problem, the invention proposes a kind of lithium battery total quality on-line monitoring system and method based on machine vision.
Summary of the invention
The lithium battery total quality on-line monitoring system and side that the purpose of the present invention is to provide a kind of based on machine vision
Method, to solve the problems mentioned in the above background technology.
To achieve the above object, the invention provides the following technical scheme:
A kind of lithium battery total quality on-line monitoring system based on machine vision, comprising:
Image capture module, the image of multiple angles for acquiring lithium battery, by camera come electric from multiple angle shot lithiums
Pond achievees the purpose that lithium battery Image Acquisition；
Data transmission module is used for transmission the image of multiple angles of the lithium battery of image capture module acquisition, is passed by data
The image transmitting of the multiple angles for the lithium battery that defeated module can acquire image capture module is to image processing module, to scheme
As processing module handles it；
Image processing module obtains the brightness and saturation degree of image for handling the image that data transmission module transmits
Plane, using the application of morphology and threshold operator in luminance picture, the minor change of compensation brightness obtains the shape of lithium battery
State information, pixel distribution, brightness and colouring information extract the feature of lithium battery；
Analysis module, the lithium battery feature for extracting to image processing module are analyzed, are compared with preset threshold,
Obtain analysis as a result, finding out mass defect；
Display module facilitates personnel to understand, check for showing the analysis result of analysis module over the display.
As a further solution of the present invention: the lithium battery total quality on-line monitoring system based on machine vision is also
Including the module that calibrates for error, the module that calibrates for error is for correcting camera error and systematic error, so that analysis result is more
It is accurate to add.
As further scheme of the invention: the lithium battery total quality on-line monitoring system based on machine vision
It further include WIFI transmission module and terminal, terminal includes mobile phone, plate, computer, and WIFI transmission module is led to for that will analyze result
It crosses WIFI network and is transmitted to terminal, by the cooperation of WIFI transmission module and terminal, can check analysis as a result, making at the terminal
It is more convenient to obtain the lithium battery total quality on-line monitoring system use based on machine vision, intelligence degree is high.
As further scheme of the invention: described image acquisition module includes front side camera, upside camera and left side
Camera, front side camera are used to shoot the main view image of lithium battery, and upside camera is used to shoot the overhead view image of lithium battery, left side phase
Machine is used to shoot the side elevation image of lithium battery, achievees the purpose that multiple angle acquisition images with this.
As the present invention further scheme: the signal output end of described image acquisition module and data transmission module
Signal input part is electrically connected, and the signal output end of data transmission module and the signal input part of image processing module electrically connect
It connects, by the cooperation of image capture module, data transmission module and image processing module, realizes and acquire image capture module
The image transmitting of multiple angles of lithium battery handled to image processing module.
As further scheme of the invention: the signal output end of described image processing module and the signal of analysis module
Input terminal is electrically connected, and the signal output end of analysis module and the signal input part of display module are electrically connected, image procossing mould
Block carries out analysis and obtains analysis as a result, analysis result is passed to analysis module, analysis module is transferred to after the image procossing of acquisition
Display module is defeated by be shown.
A kind of lithium battery total quality on-line monitoring method based on machine vision, comprising the following steps:
The image for acquiring multiple angles of lithium battery, from multiple angle shot lithium batteries, reaches lithium battery image by camera
The purpose of acquisition；
Transmit the image of multiple angles of the lithium battery of acquisition；
Image is handled, the brightness and saturation degree plane of image are obtained, using morphology and threshold operator in luminance picture
In application, the minor change of compensation brightness obtains shape information, pixel distribution, brightness and the colouring information of lithium battery, extracts
The feature of lithium battery out；
Lithium battery feature is analyzed, is compared with preset threshold, obtains analysis as a result, finding out mass defect；
Analysis result is shown over the display, personnel is facilitated to understand, check.
Compared with prior art, the beneficial effects of the present invention are:
The lithium battery total quality on-line monitoring system based on machine vision passes through the image of multiple angles of acquisition lithium battery,
Image is handled, shape information, pixel distribution, brightness and the colouring information of lithium battery is obtained, extracts the spy of lithium battery
Sign, analyzes lithium battery feature, compares with preset threshold, finds out mass defect, analysis result can be in display
Upper display facilitates the understanding of personnel, checks, solves the monitoring mode manually checked there are working efficiencies low, monitors incomplete
The problem of face.
Detailed description of the invention
Fig. 1 is the structural block diagram of the lithium battery total quality on-line monitoring system based on machine vision.
Fig. 2 is the functional block diagram of the lithium battery total quality on-line monitoring system based on machine vision.
In figure: 1- image capture module, 2- data transmission module, 3- image processing module, 4- analysis module, 5- error school
Quasi-mode block, 6- display module, 7-WIFI transmission module, 8- terminal.
Specific embodiment
The technical solution of the patent is explained in further detail With reference to embodiment.
Embodiment 1
Referring to FIG. 1-2, in the embodiment of the present invention, a kind of lithium battery total quality on-line monitoring system based on machine vision,
Include:
Image capture module 1, the image of multiple angles for acquiring lithium battery, specifically, by camera come from multiple angles
Lithium battery is shot, achievees the purpose that lithium battery Image Acquisition；
Data transmission module 2 is used for transmission the image of multiple angles of the lithium battery of the acquisition of image capture module 1, passes through data
The image transmitting of the multiple angles for the lithium battery that transmission module 2 can acquire image capture module 1 to image processing module 3,
So that image processing module 3 handles it；
Image processing module 3, the image for transmitting to data transmission module 2 are handled, and obtain the brightness and saturation of image
Plane is spent, using the application of morphology and threshold operator in luminance picture, the minor change of compensation brightness obtains lithium battery
Shape information, pixel distribution, brightness and colouring information extract the feature of lithium battery；
Analysis module 4, the lithium battery feature for extracting to image processing module 3 are analyzed, and are carried out pair with preset threshold
Than obtaining analysis as a result, finding out mass defect；
Display module 6 facilitates personnel to understand, check for showing the analysis result of analysis module 4 over the display.
Further, the lithium battery total quality on-line monitoring system based on machine vision further includes the mould that calibrates for error
Block 5, the module that calibrates for error 5 is for correcting camera error and systematic error, so that analysis result is more accurate.
Further, the lithium battery total quality on-line monitoring system based on machine vision further includes WIFI transmission mould
Block 7 and terminal 8, terminal 8 include mobile phone, plate, computer, and WIFI transmission module 7 is passed for that will analyze result by WIFI network
Terminal 8 is transported to, by the cooperation of WIFI transmission module 7 and terminal 8, can check analysis as a result, being based on this in terminal 8
The lithium battery total quality on-line monitoring system use of machine vision is more convenient, and intelligence degree is high.
Specifically, described image acquisition module 1 includes front side camera, upside camera and left camera, front side camera is used for
The main view image of lithium battery is shot, upside camera is used to shoot the overhead view image of lithium battery, and left camera is for shooting lithium battery
Side elevation image, multiple angle acquisition images are achieved the purpose that with this.
Specifically, the signal output end of described image acquisition module 1 and the signal input part of data transmission module 2 electrically connect
It connects, the signal output end of data transmission module 2 and the signal input part of image processing module 3 are electrically connected, and pass through Image Acquisition
The cooperation of module 1, data transmission module 2 and image processing module 3 realizes the lithium battery for acquiring image capture module 1
The image transmitting of multiple angles is handled to image processing module 3.
Specifically, the signal output end of described image processing module 3 and the signal input part of analysis module 4 are electrically connected,
The signal output end of analysis module 4 and the signal input part of display module 6 are electrically connected, the figure of 3 pairs of image processing module acquisitions
As being transferred to analysis module 4 after processing, analysis module 4 carries out analysis and obtains analysis as a result, analysis result is transferred to display mould
Block 6 is shown.
Embodiment 2
In the embodiment of the present invention, a kind of lithium battery total quality on-line monitoring method based on machine vision, comprising the following steps:
The image for acquiring multiple angles of lithium battery, from multiple angle shot lithium batteries, reaches lithium battery image by camera
The purpose of acquisition；
Transmit the image of multiple angles of the lithium battery of acquisition；
Image is handled, the brightness and saturation degree plane of image are obtained, using morphology and threshold operator in luminance picture
In application, the minor change of compensation brightness obtains shape information, pixel distribution, brightness and the colouring information of lithium battery, extracts
The feature of lithium battery out；
Lithium battery feature is analyzed, is compared with preset threshold, obtains analysis as a result, finding out mass defect；
Analysis result is shown over the display, personnel is facilitated to understand, check.
Better embodiment of the invention is explained in detail above, but the present invention is not limited to above-mentioned embodiment party
Formula within the knowledge of one of ordinary skill in the art can also be without departing from the purpose of the present invention
Various changes can be made.
Claims (7)
1. a kind of lithium battery total quality on-line monitoring system based on machine vision characterized by comprising
Image capture module (1), the image of multiple angles for acquiring lithium battery；
Data transmission module (2) is used for transmission the image of multiple angles of the lithium battery of image capture module (1) acquisition；
Image processing module (3) is handled for the image that transmit to data transmission module (2), obtain the brightness of image with
Saturation degree plane, using the application of morphology and threshold operator in luminance picture, the minor change of compensation brightness obtains lithium electricity
Shape information, pixel distribution, brightness and the colouring information in pond, extract the feature of lithium battery；
Analysis module (4) is analyzed for the lithium battery feature that extracts to image processing module (3), with preset threshold into
Row comparison obtains analysis as a result, finding out mass defect；
Display module (6), for showing the analysis result of analysis module (4) over the display.
2. the lithium battery total quality on-line monitoring system according to claim 1 based on machine vision, which is characterized in that
The lithium battery total quality on-line monitoring system based on machine vision further includes calibrate for error module (5), and calibrate for error mould
Block (5) is for correcting camera error and systematic error.
3. the lithium battery total quality on-line monitoring system according to claim 1 or 2 based on machine vision, feature exist
In the lithium battery total quality on-line monitoring system based on machine vision further includes WIFI transmission module (7) and terminal
(8), terminal (8) includes mobile phone, plate, computer, and WIFI transmission module (7) is transmitted to for that will analyze result by WIFI network
Terminal (8).
4. the lithium battery total quality on-line monitoring system according to claim 3 based on machine vision, which is characterized in that
Described image acquisition module (1) includes front side camera, upside camera and left camera, and front side camera is used to shoot the master of lithium battery
Visible image, upside camera are used to shoot the overhead view image of lithium battery, and left camera is used to shoot the side elevation image of lithium battery.
5. the lithium battery total quality on-line monitoring system according to claim 1 based on machine vision, which is characterized in that
The signal output end of described image acquisition module (1) and the signal input part of data transmission module (2) are electrically connected, data transmission
The signal output end of module (2) and the signal input part of image processing module (3) are electrically connected.
6. the lithium battery total quality on-line monitoring system according to claim 1 based on machine vision, which is characterized in that
The signal output end of described image processing module (3) and the signal input part of analysis module (4) are electrically connected, analysis module (4)
Signal output end and display module (6) signal input part be electrically connected.
7. a kind of lithium battery total quality on-line monitoring method based on machine vision, which comprises the following steps:
Acquire the image of multiple angles of lithium battery；
Transmit the image of multiple angles of the lithium battery of acquisition；
Image is handled, the brightness and saturation degree plane of image are obtained, using morphology and threshold operator in luminance picture
In application, the minor change of compensation brightness obtains shape information, pixel distribution, brightness and the colouring information of lithium battery, extracts
The feature of lithium battery out；
Lithium battery feature is analyzed, is compared with preset threshold, obtains analysis as a result, finding out mass defect；
Analysis result is shown over the display.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910376717.9A CN110220910A (en) | 2019-05-05 | 2019-05-05 | A kind of lithium battery total quality on-line monitoring system and method based on machine vision |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910376717.9A CN110220910A (en) | 2019-05-05 | 2019-05-05 | A kind of lithium battery total quality on-line monitoring system and method based on machine vision |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110220910A true CN110220910A (en) | 2019-09-10 |
Family
ID=67820811
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910376717.9A Withdrawn CN110220910A (en) | 2019-05-05 | 2019-05-05 | A kind of lithium battery total quality on-line monitoring system and method based on machine vision |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110220910A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110632086A (en) * | 2019-11-04 | 2019-12-31 | 大连中启伟创科技有限公司 | Injection molding surface defect detection method and system based on machine vision |
| CN115060320A (en) * | 2022-06-20 | 2022-09-16 | 武汉涛初科技有限公司 | Power lithium battery production quality on-line monitoring and analyzing system based on machine vision |
-
2019
- 2019-05-05 CN CN201910376717.9A patent/CN110220910A/en not_active Withdrawn
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110632086A (en) * | 2019-11-04 | 2019-12-31 | 大连中启伟创科技有限公司 | Injection molding surface defect detection method and system based on machine vision |
| CN115060320A (en) * | 2022-06-20 | 2022-09-16 | 武汉涛初科技有限公司 | Power lithium battery production quality on-line monitoring and analyzing system based on machine vision |
| CN115060320B (en) * | 2022-06-20 | 2023-09-29 | 武汉涛初科技有限公司 | Online monitoring and analyzing system for production quality of power lithium battery based on machine vision |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN205622739U (en) | Focusing device and system | |
| CN103402117B (en) | Based on the video image color cast detection method of Lab chrominance space | |
| CN110220910A (en) | A kind of lithium battery total quality on-line monitoring system and method based on machine vision | |
| CN110009530A (en) | A kind of nerve network system and method suitable for portable power inspection | |
| CN107588855B (en) | Detection method, detection device and the terminal device of transformer equipment temperature | |
| CN109167997A (en) | A kind of video quality diagnosis system and method | |
| CN110428762B (en) | OLED panel aging test luminescence characteristic detection method based on pixel brightness | |
| CN109596054A (en) | The size detection recognition methods of strip workpiece | |
| CN112616018B (en) | Stackable panoramic video real-time splicing method | |
| CN108712627A (en) | Video conference content and quality detection apparatus and detection method | |
| CN104700424A (en) | Medical colorful electronic endoscopy image bad point detection device | |
| CN113688817A (en) | Instrument identification method and system for automatic inspection | |
| CN202952978U (en) | Train part information collector | |
| CN105611184A (en) | White balance debugging method and debugging system of digital video device | |
| CN106524955A (en) | Plane equal thickness interference digital display measurement device and method of measuring optical flat flatness | |
| CN114894791A (en) | Rice growth analysis system and method based on matching factors | |
| CN115876086B (en) | Detection method and detection system for high-density connector | |
| CN106327498A (en) | Terminal shedding vision detection system and method | |
| CN105578179A (en) | System and method for detecting display frame rate of DMD (Digital Micro-mirror Device) | |
| CN105635685B (en) | A kind of automatic data collection transmission method | |
| CN208706212U (en) | A kind of LED display correction system | |
| CN109632814A (en) | Part defect detection method | |
| US20220358641A1 (en) | Information processing device and index value calculation method | |
| CN113808081A (en) | Transmission line small-size gold utensil defect detecting system | |
| CN216052441U (en) | Power equipment inspection glasses based on Augmented Reality (AR) technology |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20200601 Address after: 277800 room 115, building 1, workshop of Zaozhuang Keshun Digital Co., Ltd., east side of Fuyuan Fourth Road, high tech Zone, Zaozhuang City, Shandong Province Applicant after: Shandong high quality new energy testing Co.,Ltd. Address before: 277800 National Lithium Battery Quality Supervision and Inspection Center of Fuyuan Third Road, Zaozhuang High-tech Zone, Shandong Province Applicant before: Zaozhuang Institute of Supervision AND Inspection Product Quality |
|
| TA01 | Transfer of patent application right | ||
| WW01 | Invention patent application withdrawn after publication |
Application publication date: 20190910 |
|
| WW01 | Invention patent application withdrawn after publication |