Anomaly detection method for rail fasteners with automatic sample labeling

An automatic labeling and anomaly detection technology, applied in image analysis, image enhancement, instruments, etc., can solve problems such as poor promotion ability

Inactive Publication Date: 2021-05-11
BEIJING JIAOTONG UNIV
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

[0011] When the existing supervised railway fastener defect detection method detects new railway lines, it needs to re-collect and mark a large number of samples for training, which has the problem of poor promotion ability

Method used

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  • Anomaly detection method for rail fasteners with automatic sample labeling
  • Anomaly detection method for rail fasteners with automatic sample labeling
  • Anomaly detection method for rail fasteners with automatic sample labeling

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Embodiment Construction

[0062] The present invention will be described in further detail below in conjunction with the accompanying drawings.

[0063] Such as figure 1 As shown, a method for detecting abnormalities of rail fasteners automatically marked by a sample of the present invention comprises the following steps:

[0064] Step 1, collecting orbital images;

[0065] Step 2, set up a template library, said template library includes a fixed part and a dynamic part; at first existing fastener area templates and background area templates are added to the fixed part in the template library; for a railway line to be detected, the user needs to manually Locate the fastener region in the first frame of the track image and store it into a fixed section in the template library;

[0066] Classify the templates of the fastener area according to categories, and divide them into normal fastener templates-N and defective fastener templates, and classify the defective fastener templates according to categori...

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Abstract

The invention relates to a method for detecting abnormalities of rail fasteners with automatic labeling of samples. The present invention can automatically collect fastener samples to construct a training data set in the stage of locating the fastener area, without manually collecting and marking training samples. A multi-classification recognition model based on the knowledge base obtained by offline learning and online learning classifier is proposed, which solves the adaptability to new line data when classifying fasteners. The invention uses the idea of ​​online learning to dynamically update the template library, so that the fastener area positioning module can adapt to the track images of different railway lines or different sections. The present invention also designs a deep convolutional neural network model, which uses multi-level convolutional layers to extract image features, which has a stronger ability to express image features and can effectively improve the accuracy of image classification. Aiming at the problem of unbalanced number of samples of different types of fasteners, the present invention proposes a strategy of random sorting to reduce the impact of unbalanced number of samples on network performance.

Description

technical field [0001] The invention relates to the technical field of rail transit safety, in particular to a method for detecting abnormalities of rail fasteners with automatic labeling of samples. Background technique [0002] The fastener is a part on the track used to connect the rail and the sleeper. Its function is to fix the rail on the sleeper, maintain the gauge and prevent the vertical and lateral movement of the rail relative to the sleeper. According to the different types of track slabs, the installation spacing of fasteners is 550mm-650mm. From this, the number of fasteners per kilometer of rail is about 3400 pairs. Corresponding to the total mileage of my country's high-speed rail lines, the number of fasteners on the line is huge. of. The rails are impacted by the lateral force of the train every day, which will cause changes in the fixed assembly structure of the fasteners, resulting in the failure of the buckle to cause the rails to shift, and further caus...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00
CPCG06T7/0004G06T2207/20081G06T2207/20084G06T2207/30164
Inventor 刘俊博黄雅平王胜春戴鹏杜馨瑜
Owner BEIJING JIAOTONG UNIV
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