Unlock instant, AI-driven research and patent intelligence for your innovation.

Multistage network fusion round steel surface defect detection method and image acquisition device

A defect detection and surface image technology, applied in image analysis, image enhancement, image data processing, etc., can solve problems such as being easily affected by complex and changeable environments, insufficient algorithm generalization ability, and complex algorithm design process, etc., to achieve improved The effect of detection accuracy, improvement of training accuracy and detection accuracy, and reasonable sample division

Pending Publication Date: 2022-05-10
北京科技大学设计研究院有限公司
View PDF0 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present invention provides a multi-level network fusion round steel surface defect detection method and an image acquisition device. The existing round steel surface defect detection has the following problems, the algorithm design process is complicated, and it is easily affected by complex and changeable environments. Insufficient generalization ability of the algorithm, poor robustness, and low detection accuracy

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
  • Multistage network fusion round steel surface defect detection method and image acquisition device
  • Multistage network fusion round steel surface defect detection method and image acquisition device
  • Multistage network fusion round steel surface defect detection method and image acquisition device

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0061] Such as figure 1 and Figure 8 As shown, this embodiment provides a multi-level network fusion round steel surface defect detection method, the algorithm frame diagram of the multi-level network fusion round steel surface defect detection method is as follows Figure 8 As shown, the detection method includes:

[0062] S100. Obtain a real-time round steel surface image, establish a round steel surface defect data set with the round steel surface image with defects on the round steel surface, and establish a round steel surface defect-free image sample with the round steel surface image without defects on the round steel surface;

[0063] S200, using the round steel surface defect data set to create the round steel surface defect detection network model of the Efficient Net classification priority network and YOLOv5 network fusion, the model can classify and identify the round steel surface defect type and locate the round steel surface defect position;

[0064] S300. U...

Embodiment 2

[0086] Such as Figure 9 As shown, this embodiment provides a multi-level network fusion round steel surface defect detection method, the algorithm frame diagram of the multi-level network fusion round steel surface defect detection method is as follows Figure 8 As shown, the detection method includes:

[0087] S100. According to the requirements of the actual application scene, design an image acquisition device for the specifications and diameters of the round steel, use the acquisition device to acquire real-time round steel surface images, and establish the round steel surface images with defects on the round steel surface into a round steel surface defect data set , the round steel surface image without defects on the round steel surface is established as a non-defective image sample on the round steel surface;

[0088] S200. Using the round steel surface defect data set to create a round steel surface defect detection network model that combines the Efficient Net class...

Embodiment 3

[0092] As shown in Figure 10, this embodiment provides an image acquisition device suitable for round steel with specifications and diameters of 50-130mm, and the device is used to obtain the multi-level network fusion round steel surface defect detection method In the image of the round steel surface, the setup consists of:

[0093] The device includes a bracket on which four line-scan cameras are evenly distributed on the circumference, and the angle between each line-scan camera and the horizontal line is 45°, and the angle between the line-scan camera and the vertical line is 45°. °, the line scan camera has a GIGE digital interface, and the collected round steel surface image is transmitted to the server remotely through the network, and the server can store the round steel surface image. Specifically, four line scan cameras are distributed at intervals of 90° in the radial direction of the round steel. The setup of four line-scan cameras ensures that the circle of the r...

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 multi-level network fusion round steel surface defect detection method and an image acquisition device, and the detection method comprises the steps: obtaining real-time round steel surface images, and building a round steel surface defect data set through the round steel surface images with defects on the round steel surface; establishing a round steel surface non-defect image sample by using the round steel surface image without the defect on the round steel surface; creating a round steel surface defect detection network model fused by an Officient Net classification priority network and a YOLOv5 network by using the round steel surface defect data set, and classifying and identifying the types of the round steel surface defects and positioning the positions of the round steel surface defects by the model; training the round steel surface defect detection network model by utilizing transfer learning; and adding the round steel surface non-defect image sample into the round steel surface defect detection network model and training the model. The image acquisition device comprises a support, a line scanning camera and an annular green LED light source. The detection method is sufficient in generalization ability and good in robustness, and the training precision and the detection precision of the detection network model are effectively improved.

Description

technical field [0001] The invention relates to the technical fields of computer vision, deep learning, target detection, and metal surface defect detection equipment and methods, in particular to a multi-level network fusion round steel surface defect detection method and device. Background technique [0002] As a special steel grade and industrial raw material, round steel is widely used in the manufacture of various industrial parts such as automobiles and aerospace. The quality of round steel directly determines the quality of industrial products using it as raw material. With the continuous transformation of the manufacturing industry to intelligent production of automation, informatization, and dataization, the production of round steel continues to develop at a high speed, which puts forward higher requirements for the detection technology to ensure the quality of round steel. Therefore, ensuring the quality of round steel production is an important part of improving ...

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): G06T7/00G06V10/80G06V10/82G06K9/62G06N3/04G06N3/08
CPCG06T7/0004G06N3/08G06T2207/30136G06T2207/20081G06T2207/20084G06N3/045G06F18/241G06F18/253
Inventor 侯睿邓能辉叶俊明
Owner 北京科技大学设计研究院有限公司