Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Candy package surface defect quick detection method based on machine vision

A technology of machine vision and detection methods, applied in neural learning methods, instruments, computer parts and other directions, can solve the problems of low efficiency, high cost and low accuracy of manual detection, achieve rich distribution, reduce the generation of defective products, The effect of avoiding missed detection and false detection

Pending Publication Date: 2021-12-24
力度工业智能科技(苏州)有限公司
View PDF0 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The traditional inspection method is manual visual inspection for packaging defects, but manual inspection has the problems of low efficiency, low accuracy and high cost

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Candy package surface defect quick detection method based on machine vision
  • Candy package surface defect quick detection method based on machine vision
  • Candy package surface defect quick detection method based on machine vision

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0057] see figure 1 and figure 2 , a machine vision-based rapid detection method for candy packaging defects, the specific implementation steps are as follows:

[0058] Step 1: Image acquisition.

[0059] Specifically, after the candy is packaged from the production line, it enters the image acquisition unit through the conveyor belt, and arrives directly under the flat shadowless light source, triggering the infrared sensor, which sends a signal to the industrial camera to trigger the photo, and saves it in the camera memory.

[0060] Step 2: Image processing.

[0061] The image processing software automatically makes a judgment after receiving the picture in the memory of the processor. If it is judged to be unqualified, it will quickly transmit the defective product signal to the rejecting mechanism.

[0062] Step 3: Removal of defective products.

[0063] After receiving the defective product signal, the transmission signal is sent to the PLC, and the PLC controls the...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a quick detection method for candy package defects based on machine vision. The method comprises the following steps: (1) image collection; (2) image processing: a defect quick detection algorithm based on deep learning in an image processing system is obtained by preprocessing, training, evaluating and optimizing a real candy data set on a production line through an improved VGG16 deep learning model, and a defective product signal is sent out when a defect is detected; and (3) rejecting defective products, wherein a rejecting system receives the defective product signals and executes rejecting operation. According to the invention, online detection and elimination of candy package defects are realized, the image collection rate, the unqualified product recognition rate and the elimination rate can meet the production rate of 10 candies per second, the problems of low manual detection precision and high cost are solved, and the efficiency and reliability of defect detection are greatly improved; and the method can be easily expanded to online defect detection in other fields, such as online detection of packaging defects of products of the same type and online detection of defects of mobile phone shells.

Description

technical field [0001] The invention belongs to the field of artificial intelligence technology and rapid detection of product outer packaging defects based on machine vision, and in particular relates to a rapid detection method for surface defects of candy packaging. Background technique [0002] In modern automated production lines, there may be defects on the surface of candy packaging. Such products are substandard products. Reducing the flow of substandard products into the market can bring consumers a good sensory experience and increase the competitiveness of products. The output speed of the candy packaging production line is generally very fast, reaching a speed of 0.1s / piece. During the packaging process, mechanical vibration or other environmental factors will cause packaging damage, empty bags, wrinkles and other quality problems. The traditional inspection method is manual visual inspection for packaging defects, but manual inspection has the problems of low ef...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06K9/46G06K9/62G06N3/08
CPCG06T7/0002G06N3/08G06T2207/10141G06T2207/20081G06F18/2414G06F18/2415Y02P90/30
Inventor 杜世昌
Owner 力度工业智能科技(苏州)有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products