CN112215825A - Quality analysis method and system based on machine vision in new energy battery manufacturing - Google Patents
Quality analysis method and system based on machine vision in new energy battery manufacturing Download PDFInfo
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- CN112215825A CN112215825A CN202011117396.XA CN202011117396A CN112215825A CN 112215825 A CN112215825 A CN 112215825A CN 202011117396 A CN202011117396 A CN 202011117396A CN 112215825 A CN112215825 A CN 112215825A
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- 238000004519 manufacturing process Methods 0.000 title claims abstract description 25
- 238000004458 analytical method Methods 0.000 title claims abstract description 18
- 238000000576 coating method Methods 0.000 claims abstract description 37
- 239000011248 coating agent Substances 0.000 claims abstract description 35
- 230000004044 response Effects 0.000 claims abstract description 8
- 238000001914 filtration Methods 0.000 claims abstract description 4
- 238000009499 grossing Methods 0.000 claims abstract description 4
- 238000004590 computer program Methods 0.000 claims description 6
- 238000000034 method Methods 0.000 claims description 3
- 230000009466 transformation Effects 0.000 claims description 3
- 238000001514 detection method Methods 0.000 abstract description 2
- 238000005259 measurement Methods 0.000 description 2
- RYGMFSIKBFXOCR-UHFFFAOYSA-N Copper Chemical compound [Cu] RYGMFSIKBFXOCR-UHFFFAOYSA-N 0.000 description 1
- 230000002159 abnormal effect Effects 0.000 description 1
- 230000005856 abnormality Effects 0.000 description 1
- XAGFODPZIPBFFR-UHFFFAOYSA-N aluminium Chemical compound [Al] XAGFODPZIPBFFR-UHFFFAOYSA-N 0.000 description 1
- 229910052782 aluminium Inorganic materials 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000011889 copper foil Substances 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 239000011888 foil Substances 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 238000003908 quality control method Methods 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
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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
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/70—Denoising; Smoothing
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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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- General Physics & Mathematics (AREA)
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- Computer Vision & Pattern Recognition (AREA)
- Quality & Reliability (AREA)
- Length Measuring Devices By Optical Means (AREA)
- Image Analysis (AREA)
Abstract
The invention relates to a quality analysis method and system based on machine vision in new energy battery manufacturing. The invention aims to provide a quality analysis method and a quality analysis system based on machine vision in new energy battery manufacturing, which are used for detecting the coating condition of a pole piece in real time on line so as to ensure the product quality. The technical scheme of the invention is as follows: s1, acquiring front and back images of the product; s2, finding out approximate position areas of the beginning of the coating areas on the front and back images of the product through an image pyramid algorithm; s3, in the approximate position area, carrying out primary Gaussian smoothing filtering to remove noise signals; s4, calculating edge images of the coating area in the X direction and the Y direction by using a Prewitt operator; s5, calculating the gradient direction and derivative of each pixel point by using the X and Y direction edge values; and S6, removing pixels with small edge response according to the gradient direction and the derivative, and leaving continuous skeleton lines with maximum edge response. The invention is suitable for the field of product quality detection.
Description
Technical Field
The invention relates to a quality analysis method and system based on machine vision in new energy battery manufacturing. The method is suitable for the field of product quality detection.
Background
The key process for manufacturing the new energy battery comprises the manufacture of an insulating diaphragm, a copper foil pole piece and an aluminum foil pole piece, wherein the manufacture of the pole piece by using an interval coating process is the most complicated, the quality requirement is the highest, and the quality control relates to the measurement and control of the sizes of different areas (a coating area and a pole piece area), the synchronous consistency control of the coating of the upper surface and the lower surface and the like.
Because the products are conveyed on the production equipment at a high speed, the traditional measurement mode is that a production line is stopped, and a tool is used for measuring a specific area; the efficiency is low, the productivity of a production line is influenced, only a small amount of sampling inspection can be performed, and the production line cannot be found in time when abnormality occurs.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: aiming at the existing problems, the quality analysis method and the quality analysis system based on machine vision in the new energy battery manufacturing are provided, so that the pole piece coating condition is detected in real time on line, and the product quality is ensured.
The technical scheme adopted by the invention is as follows: a quality analysis method based on machine vision in new energy battery manufacturing is characterized in that:
s1, acquiring front and back images of the product;
s2, finding out approximate position areas of the beginning of the coating areas on the front and back images of the product through an image pyramid algorithm;
s3, in the approximate position area, carrying out primary Gaussian smoothing filtering to remove noise signals;
s4, calculating edge images of the coating area in the X direction and the Y direction by using a Prewitt operator;
s5, calculating the gradient direction and derivative of each pixel point by using the X and Y direction edge values;
s6, eliminating pixels with small edge response according to the gradient direction and the derivative, and leaving continuous skeleton lines with maximum edge response;
s7, calculating a maximum fitting linear equation of the edge points by adopting Hough transformation;
s8, repeating the steps S2 to S8 to calculate an edge straight line equation of each coating area on the product;
s9, calculating the length and width of each coating area by using an edge linear equation of each coating area, comparing the length and width with standard values, and giving results such as length and width judgment;
and S10, calculating the dislocation value of the edge of the coating area on the front and back surfaces of the product according to the edge linear equation of the coating area on the front and back surfaces of the product, comparing the dislocation value with a standard value, and giving results such as alignment judgment.
The calculating of the dislocation value of the edge of the coating area on the front side and the back side of the product comprises the following steps:
and marking high-precision grid lines on the upper surface and the lower surface of the product by using calibration equipment, and calculating a coordinate offset value of a camera for acquiring a back image relative to a camera for acquiring a front image according to the grid lines when acquiring front and back images of the product.
A quality analysis system based on machine vision in new energy battery manufacturing is characterized in that:
the camera I is used for acquiring a front image of a product;
the camera II is used for acquiring a reverse image of the product;
the encoder is in contact with the product and used for acquiring the conveying distance of the product and providing image acquisition trigger signals for the cameras I and II after the product is conveyed for a certain distance;
an upper computer having a processor and a memory, the memory having stored thereon a computer program, the computer program, when executed by the processor, implementing the steps of the machine vision-based quality analysis method in new energy battery manufacturing of claim 1.
The invention has the beneficial effects that: according to the invention, the edge linear equation of each coating area on the product is calculated by intelligently analyzing the product image, so that the width and the length of each coating area are accurately calculated, the data of the coating starting position and the coating ending position of the front side and the back side of the product are calculated, the upper and lower dislocation values are accurately analyzed, and whether the coating quality of the current production line reaches the standard or not is judged.
Drawings
Fig. 1 is a system block diagram of the present embodiment.
Detailed Description
The embodiment is a quality analysis system based on machine vision in new energy battery manufacturing, which is provided with an upper computer, a camera I, a camera II, an encoder and an alarm device, wherein the camera I is connected to the upper computer and is used for acquiring a front image of a product after receiving an image acquisition trigger signal; the camera II is used for acquiring a reverse image of the product after receiving the image acquisition trigger signal; the encoder is in contact with the product and used for acquiring the conveying distance of the product and providing image acquisition trigger signals for the cameras I and II after the product is conveyed for a certain distance; the upper computer is provided with a processor and a memory, a computer program is stored in the memory, and the computer program is executed by the processor to realize the steps of the quality analysis method based on machine vision in the manufacturing of the new energy battery.
The quality analysis method based on machine vision in the manufacture of the new energy battery in the embodiment comprises the following steps:
s1, acquiring front and back images of the product collected by the camera I and the camera II;
s2, finding out approximate position areas of the beginning of the coating areas on the front and back images of the product through an image pyramid algorithm;
s3, in the approximate position area, carrying out primary Gaussian smoothing filtering to remove noise signals;
s4, calculating edge images of the coating area in the X direction and the Y direction by using a Prewitt operator;
s5, calculating the gradient direction and derivative of each pixel point by using the X and Y direction edge values;
s6, eliminating pixels with small edge response according to the gradient direction and the derivative, and leaving continuous skeleton lines with maximum edge response;
s7, calculating a maximum fitting linear equation of the edge points by adopting Hough transformation;
s8, repeating the steps S2 to S8 to calculate an edge straight line equation of each coating area on the product;
s9, calculating the length and width of each coating area by using an edge linear equation of each coating area, comparing the length and width with standard values, and giving results such as length and width judgment;
s10, calculating the dislocation value of the edge of the coating area on the front and back surfaces of the product according to the edge linear equation of the coating area on the front and back surfaces of the product, comparing the dislocation value with a standard value, and giving results such as alignment judgment;
marking high-precision grid lines on the upper surface and the lower surface of a product by using calibration equipment, wherein the upper surface and the lower surface of the product are highly aligned, the cameras on the front surface and the back surface capture images simultaneously, the physical coordinate offset value of the camera on the back surface relative to the camera on the front surface is calculated according to the positions of the grid lines imaged on the cameras, and the dislocation value of the edges of the coating areas on the front surface and the back surface of the product is calculated according to the physical coordinate offset value;
and S11, judging whether an alarm signal needs to be sent according to the results of the length and width judgment and the like and the results of the alignment judgment and the like by combining a preset standard.
In this embodiment, the alarm device receives the alarm signal to warn the production line of the abnormal coating process.
Claims (3)
1. A quality analysis method based on machine vision in new energy battery manufacturing is characterized in that:
s1, acquiring front and back images of the product;
s2, finding out approximate position areas of the beginning of the coating areas on the front and back images of the product through an image pyramid algorithm;
s3, in the approximate position area, carrying out primary Gaussian smoothing filtering to remove noise signals;
s4, calculating edge images of the coating area in the X direction and the Y direction by using a Prewitt operator;
s5, calculating the gradient direction and derivative of each pixel point by using the X and Y direction edge values;
s6, eliminating pixels with small edge response according to the gradient direction and the derivative, and leaving continuous skeleton lines with maximum edge response;
s7, calculating a maximum fitting linear equation of the edge points by adopting Hough transformation;
s8, repeating the steps S2 to S8 to calculate an edge straight line equation of each coating area on the product;
s9, calculating the length and width of each coating area by using an edge linear equation of each coating area, comparing the length and width with standard values, and giving results such as length and width judgment;
and S10, calculating the dislocation value of the edge of the coating area on the front and back surfaces of the product according to the edge linear equation of the coating area on the front and back surfaces of the product, comparing the dislocation value with a standard value, and giving results such as alignment judgment.
2. The method for quality analysis based on machine vision in the manufacture of new energy batteries according to claim 1, wherein the calculating the misalignment value of the edges of the coating areas on the front and back sides of the product comprises:
and marking high-precision grid lines on the upper surface and the lower surface of the product by using calibration equipment, and calculating a coordinate offset value of a camera for acquiring a back image relative to a camera for acquiring a front image according to the grid lines when acquiring front and back images of the product.
3. A quality analysis system based on machine vision in new energy battery manufacturing is characterized in that:
the camera I is used for acquiring a front image of a product;
the camera II is used for acquiring a reverse image of the product;
the encoder is in contact with the product and used for acquiring the conveying distance of the product and providing image acquisition trigger signals for the cameras I and II after the product is conveyed for a certain distance;
an upper computer having a processor and a memory, the memory having stored thereon a computer program, the computer program, when executed by the processor, implementing the steps of the machine vision-based quality analysis method in new energy battery manufacturing of claim 1 or 2.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113838043A (en) * | 2021-09-30 | 2021-12-24 | 杭州百子尖科技股份有限公司 | Machine vision-based quality analysis method in metal foil manufacturing |
| WO2023193150A1 (en) * | 2022-04-06 | 2023-10-12 | 宁德时代新能源科技股份有限公司 | Method, device, and system for detecting size of battery composite surface |
| WO2023193213A1 (en) * | 2022-04-08 | 2023-10-12 | 宁德时代新能源科技股份有限公司 | Method and apparatus for detecting defect of insulating coating of battery electrode plate, and computer device |
| CN117969533A (en) * | 2024-03-27 | 2024-05-03 | 宁德时代新能源科技股份有限公司 | Insulation coating detection method, device, system, equipment and storage medium |
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| CN117969533A (en) * | 2024-03-27 | 2024-05-03 | 宁德时代新能源科技股份有限公司 | Insulation coating detection method, device, system, equipment and storage medium |
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