Method for detecting position and type of workpiece on subway vehicle side inspection image

A subway and workpiece technology, applied in the field of machine vision industrial inspection, can solve a large number of manual operations and other problems, achieve the effect of reducing labor intensity, reducing difficulty, and facilitating the analysis of workpiece status

Pending Publication Date: 2021-02-26
成都川哈工机器人及智能装备产业技术研究院有限公司 +1
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The invention is a method for detecting the position and type of the workpiece on the inspection image on the side of the subway car. The technical problem to be solved is to solve the problem that a large number of manual operations are required in the inspection process of the subway train. The method of detecti

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  • Method for detecting position and type of workpiece on subway vehicle side inspection image
  • Method for detecting position and type of workpiece on subway vehicle side inspection image
  • Method for detecting position and type of workpiece on subway vehicle side inspection image

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Example Embodiment

[0029]Example one:

[0030]The present invention is a method for detecting the position and type of workpieces on the side inspection image of a subway car. The model training embodiment mainly describes that in order to obtain a workpiece detection model, the image data acquisition of the subway car body, the target labeling of the workpiece in the image, and the construction of the YOLOv4 deep learning network are mainly described. And training, and model output, the specific implementation process is as follows:

[0031]1) Install two industrial cameras on both sides of the subway track to scan the body of the subway train and output the original scanned picture with a resolution of 65535×1808, and divide the original picture into sub-pictures of 1808×1808 size to save.

[0032]2) Use the Colabeler labeling tool to label each workpiece appearing on the picture. In this embodiment, it mainly includes different screws, upper brake pads, lower brake pads, and iron wires. There are a total of...

Example Embodiment

[0035]Embodiment two:

[0036]Such asfigure 1 As shown, the invention constructs a subway train workpiece detection model based on the YOLOv4 target detection network architecture. YOLO is a target detection model based on deep learning. The present invention builds a new subway workpiece detection model based on YOLOv4. The detection algorithm flow is as followsfigure 1 As shown, the steps of model training are as follows:

[0037]a) First use the pre-trained weights of the CSPDarknet53 network to initialize the YOLOv4 backbone network. The weights are trained using MS COCO target detection data, which can detect 80 objects in the MS COCO dataset. In order to adapt to the application of subway body workpiece detection, Modify the output category of the YOLOv4 network to the number of types of artifacts (10 in the present invention), so as to meet the conditions of migration learning;

[0038]b) For a sub-picture to be trained, its resolution is 1808×1808, and the resolution of the picture n...

Example Embodiment

[0051]Embodiment three:

[0052]After the above-mentioned training method is trained on the subway car body workpiece detection data set, the present invention can obtain a trained workpiece detection model, which can run under the Darknet deep learning framework and output a length of S×S×(B×5+ The prediction tensor of C), in order to detect the position of each workpiece and identify the type of the workpiece, the present invention introduces a non-maximum suppression algorithm (NMS) to find the target frame and confidence level from the prediction tensor. The steps are as follows:

[0053]1) Set a threshold to filter out all bounding boxes of target candidate frames smaller than this threshold;

[0054]2) Select the one with the highest target confidence of the bounding box of a certain workpiece candidate frame, which is box_best;

[0055]3) Calculate the IOU (Intersection over Union) between box_best and other candidate frame bounding boxes of other workpieces, that is, the intersection of...

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Abstract

The invention discloses a method for detecting the position and type of a workpiece on a subway train side inspection image. The method employs a software algorithm to replace manual operation, employs a subway train side workpiece detection and recognition model, can be used for the development of an intelligent subway inspection system, and replaces a manual observation detection mode. Accordingto the method, the YOLOv4 is used as a basis to construct the subway train side workpiece positioning and recognition model, the YOLOv4 has a very good effect in target detection application, and thecapability is migrated to subway inspection application, so that the accuracy of train side workpiece positioning can be effectively improved; and powerful support is provided for subsequent defect analysis, by using the detection model provided by the invention, a workpiece can be quickly and accurately positioned from a subway vehicle body scanning picture, a sub-picture area can be segmented,and the output picture only comprises a workpiece with a known model, so that the subsequent analysis on the state of the workpiece is greatly facilitated, and the difficulty of subsequent analysis isreduced.

Description

technical field [0001] The invention relates to the field of machine vision industrial detection, in particular to a method for detecting the position and type of a workpiece on a subway car side inspection image. Background technique [0002] In my country, with the expansion of city scale and the continuous increase of urban population, the traffic pressure in the city is increasing. Therefore, many cities are vigorously building subway systems. my country is currently in a period of rapid development of rail transit, and the opening and operation of a large number of subway lines has put forward higher and higher requirements for the management and maintenance of rail transit equipment. Among them, the daily inspection of the train to ensure that the workpieces on the train are in a normal state is an important guarantee to ensure the safety of subway traffic. In order to ensure that the workpieces on the subway train are in a normal state, it is necessary to frequently i...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/46G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V20/20G06V10/40G06N3/045G06F18/214
Inventor 张朝龙周治宇周帆王健王贵东朱均梁海清朱冬
Owner 成都川哈工机器人及智能装备产业技术研究院有限公司
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