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Third rail welding spot detection method and device based on deep learning

A solder joint detection and deep learning technology, applied in image data processing, instrumentation, computing, etc., can solve the problem of inability to efficiently and automatically detect the third track solder joints, achieve efficient solder joint automatic detection, and improve generalization effect of ability

Pending Publication Date: 2021-10-19
WATRIX TECH CORP LTD
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Problems solved by technology

However, using artificially designed features for classification in this method cannot achieve efficient and automatic detection of the position of the third rail solder joint

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  • Third rail welding spot detection method and device based on deep learning
  • Third rail welding spot detection method and device based on deep learning
  • Third rail welding spot detection method and device based on deep learning

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[0047] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only It is a part of the embodiments of this application, not all of them. The components of the embodiments of the application generally described and illustrated in the figures herein may be arranged and designed in a variety of different configurations. Accordingly, the following detailed description of the embodiments of the application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of the application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without...

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Abstract

The invention provides a third rail welding spot detection method and device based on deep learning. The method comprises the steps: collecting an image of a to-be-detected third rail welding spot; performing image segmentation processing on the image of the to-be-detected third rail welding spot to extract a region of interest including the third rail welding spot; constructing a residual neural network model by using the residual network structure; training the residual neural network model by using a welding spot sample; and performing third rail welding spot detection on the region of interest containing the third rail welding spot by using the trained residual neural network model. According to the embodiment of the invention, efficient welding spot automatic detection can be realized by using fewer resources.

Description

technical field [0001] The present application relates to the technical field of solder joint detection, in particular to a third-rail solder joint detection method and device based on deep learning. Background technique [0002] Solder joints are caused by uneven contact between the collector shoe and the third rail, making the third rail more susceptible to wear or other damage. Therefore, solder joint inspection is currently used as an effective basic means for rail damage analysis and prevention. [0003] In the prior art, a manual detection method is used to detect solder joints. However, detecting solder joints by manual detection methods will result in low efficiency and high cost of solder joint detection. [0004] In order to solve the above problems, traditional image processing methods are currently used to detect solder joints. However, using artificially designed features for classification in this method cannot achieve efficient and automatic detection of th...

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Application Information

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IPC IPC(8): G06T7/70G06T7/00G06T7/12G06T7/13G06T7/187
CPCG06T7/70G06T7/0004G06T7/12G06T7/13G06T7/187G06T2207/20081G06T2207/20084G06T2207/30152
Inventor 黄永祯杨少鹏
Owner WATRIX TECH CORP LTD
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