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Welding spot quality identification method fusing knowledge graph and graph convolutional neural network

A convolutional neural network and knowledge graph technology, which is applied in neural learning methods, biological neural network models, character and pattern recognition, etc. The effect of precision

Active Publication Date: 2022-03-25
CHONGQING UNIV
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  • Abstract
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Problems solved by technology

Although deep learning technology has been initially applied in the field of welding quality prediction, it has not yet appeared in the appearance recognition of spot welding joints.

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  • Welding spot quality identification method fusing knowledge graph and graph convolutional neural network
  • Welding spot quality identification method fusing knowledge graph and graph convolutional neural network
  • Welding spot quality identification method fusing knowledge graph and graph convolutional neural network

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Embodiment Construction

[0070] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments, so that those skilled in the art can better understand the present invention and implement it, but the examples given are not intended to limit the present invention.

[0071] Taking the quality detection of automobile body solder joints as an example, the specific implementation of the method for identifying the quality of solder joints of the present invention that integrates knowledge graphs and graph convolutional neural networks will be described in detail.

[0072] According to statistics, the appearance quality of spot welding joints is not only closely related to equipment status and process parameters, but also obviously related to the position of the welding joints on the body, such as figure 1 As shown, near the edge of the body, poor control of the position of the welding torch can easily lead to incomplete solder joints; near the boss...

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Abstract

The invention discloses a welding spot quality identification method fusing a knowledge graph and a graph convolutional neural network, and the method comprises the steps: photographing a welding spot, and obtaining a welding spot appearance image; the welding spot appearance image comprises a welding spot and a position visual feature of the welding spot; cutting the welding spot appearance image to obtain a welding spot cutting image; the sizes of all the welding spot cutting images are the same, and each welding spot cutting image only comprises one welding spot and the position feature of the welding spot; importing the cutting image of the welding spots into a fine-grained network for feature mining to obtain a visual feature matrix of the welding spots; establishing a knowledge graph according to the quality of the welding spots and the position relationship between the welding spots, and performing feature mining on the knowledge graph by using a graph convolutional neural network to obtain a high-dimensional spot type spatial feature matrix of the welding spots; and carrying out vector inner product on the visual feature matrix and the high-dimensional spot type spatial feature matrix to obtain a classification detection result of the welding spot quality.

Description

technical field [0001] The invention belongs to the technical field of welding analysis, in particular to a method for identifying the quality of solder joints that integrates knowledge graphs and graph convolutional neural networks. Background technique [0002] Resistance spot welding exerts a certain pressure on the workpiece to be welded through the electrode, so that the workpiece is in stable contact, and then uses resistance heat to melt the contact point to form a weld nugget and connect metal sheets of different thicknesses. It has the characteristics and advantages of low cost, high efficiency, small deformation, and time saving, and is widely used in the production process of automobiles, aircraft, and high-speed rail. According to statistics, the body-in-white of each car contains thousands of resistance spot welding spots, and the quality of these spots has an important impact on the service performance and life of the vehicle. In the spot welding process, key ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/73G06K9/62G06N3/04G06N3/08G06F16/55G06F16/583G06V10/46G06V10/764G06V10/82
CPCG06T7/0008G06T7/73G06N3/08G06F16/55G06F16/583G06T2207/20081G06T2207/20084G06N3/047G06N3/045G06F18/2431Y02P90/30
Inventor 杨波李秋康玲王时龙王昱肖猛
Owner CHONGQING UNIV
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