Product surface defect detection method, electronic equipment and readable storage medium

A defect detection and product technology, applied in neural learning methods, image data processing, image enhancement, etc., can solve problems such as low robustness and technical scalability, long training time, low proportion of defective products, etc., to reduce errors The probability of being judged as a good product and the effect of improving the detection efficiency

Active Publication Date: 2020-04-10
SHANGHAI MICROPORT PROPHECY MEDICAL TECH CO LTD
View PDF4 Cites 18 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] (1) Manual surface defect detection requires experienced employees to operate. For the factory, it faces problems such as difficulty in recruiting employees, long training time, and high mobility.
[0005] (2) The technical effect based on traditional feature extraction depends on whether the features of defects can be effectively extracted, which is difficult to guarantee and takes a lot of time
Moreover, this technology can only target specific products, and its robustness and technical scalability are relatively low.
[0006] (3) The defect detection method based on deep learning requires a large amount of data for pre-training, but in actual scenarios, the proportion of defective products is very low, and it is difficult to find a large number of data sets for training in a short time
Moreover, the single use of deep learning algorithms is easy to ignore inconspicuous defects on the product, resulting in false negative detection results

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
  • Product surface defect detection method, electronic equipment and readable storage medium
  • Product surface defect detection method, electronic equipment and readable storage medium
  • Product surface defect detection method, electronic equipment and readable storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0052] See figure 1 , the steps of the surface defect detection method of the balloon product provided in this embodiment are as follows:

[0053] Step S1: Use an industrial camera to take pictures of the balloon to obtain an image of the balloon to be tested;

[0054] Step S2: Input the image of the balloon to be tested into the trained binary classification neural network model and the defect point location algorithm based on image processing for parallel operation, and the defect point location algorithm uses the first preset area threshold to determine Whether the balloon to be tested is a good product; if both the trained binary classification neural network model and the defect point location algorithm based on image processing are identified as a good product, then it is determined that the balloon to be tested is a good product, otherwise it is determined that the balloon to be tested is a good product. The balloon to be tested is a suspected defective product for re-...

Embodiment 2

[0103] Step S1 and step S2 of this embodiment are all the same as in embodiment 1, the difference is the review step in step S3, please refer to Figure 5 , the review link of this embodiment does not include step S31 and step S41 of embodiment 1, but includes the following step S42:

[0104] Step S42: If the defect point positioning algorithm based on image processing in step S2 determines that the product balloon to be tested is a defective product, then output the position coordinates of the suspected defect point, crop the image of the suspected defect point according to the position coordinates of the suspected defect point, and calculate The area of ​​the cropped suspected defect point image, if the area is smaller than the third preset area threshold, the target is considered to be extremely small, and the product balloon to be tested is determined to be a good product; otherwise, the product balloon to be tested is determined to be a suspected defective product. Step S...

Embodiment 3

[0107] This embodiment provides an electronic device, including a processor and a memory, where a computer program is stored on the memory, and when the computer program is executed by the processor, the detection method of Embodiment 1 or / and Embodiment 2 is implemented.

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 product surface defect detection method, electronic equipment and a readable storage medium. The detection method comprises the following steps: S1, acquiring an image of a to-be-detected product; S2, inputting the image of the to-be-tested product into a first processing module and a second processing module for parallel operation, and if the first processing module andthe second processing module both determine that the to-be-detected product is a good product, determining that the to-be-detected product is a good product, or if at least one of the first processingmodule and the second processing module determines that the to-be-detected product is a suspected defective product, entering the step S3; and S3, rechecking the suspected defective product. According to the detection method provided by the invention, the detection efficiency is improved, the probability of misjudging defective products as good products is reduced, and meanwhile, the problems ofdichotomy of defective products and good products under a small data set and accurate positioning of defect points are further solved.

Description

technical field [0001] The invention relates to a product detection method, in particular to a product surface defect detection method, electronic equipment and a readable storage medium. Background technique [0002] Defects on the surface of an object have a direct impact on the quality of the object, and also affect the user experience. Especially for some objects with high precision requirements and special usage scenarios, the presence or absence of surface defects directly determines whether the object can enter the market. For example, dilation balloons, which are mainly used in cardiovascular and cerebrovascular interventional surgery, are common interventional surgical instruments, and their function is to expand narrowed blood vessels or other lumens and stent systems. The quality of the balloon is related to the life safety of the patient. If it breaks during use, it may cause inestimable damage to the patient. With the improvement of intelligent manufacturing ca...

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): G06T7/00G06T7/187G06T7/62G06N3/04G06N3/08
CPCG06T7/0004G06T7/187G06T7/62G06N3/08G06T2207/20081G06T2207/20084G06T2207/20024G06T2207/20036G06T2207/30108G06N3/045Y02P90/30
Inventor 张武龙吕文尔赵钢黄弯弯
Owner SHANGHAI MICROPORT PROPHECY MEDICAL TECH CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products