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Railway wagon lower pull rod falling fault image identification method

A technology for image recognition and railway wagons, applied in image enhancement, image analysis, image data processing, etc., can solve the problems of low detection efficiency, achieve high segmentation accuracy, improve segmentation effect, and improve the effect of recognition accuracy

Inactive Publication Date: 2020-04-28
HARBIN KEJIA GENERAL MECHANICAL & ELECTRICAL CO LTD
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AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to propose an image recognition method for the fall-off failure of the lower rod of a railway freight car in view of the problem of low detection efficiency in the detection method mainly based on manual work in the prior art

Method used

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  • Railway wagon lower pull rod falling fault image identification method
  • Railway wagon lower pull rod falling fault image identification method
  • Railway wagon lower pull rod falling fault image identification method

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specific Embodiment approach 1

[0034] Specific implementation mode one: refer to figure 1 and figure 2 Specifically explaining this embodiment, a method for image recognition of a fall-off fault image of a railway freight car pull-down rod described in this embodiment includes the following steps:

[0035] Step 1: Obtain the image of the truck to be identified;

[0036] Step 2: Obtain the rough positioning sub-image of the pull-down rod by cropping;

[0037] Step 3: use the coarse positioning sub-image of the lower bar obtained in step 2 to establish a training data set;

[0038] Step 4: Build a MultiResUNet model, and use the model for training to obtain a trained deep learning model;

[0039] Step 5: Input the image to be recognized into the trained deep learning model to obtain the segmented image of the pull-down bar;

[0040] Step 6: Use the segmented image of the pull-down rod to determine whether the pull-down rod is in a detached state.

[0041] 1. Obtain the image of the truck to be recognize...

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Abstract

The invention relates to the technical field of freight train detection, in particular to a railway wagon lower pull rod falling fault image recognition method, and aims to solve the problem of low detection accuracy in a manual-based detection mode in the prior art, and the method comprises the steps of 1, obtaining a to-be-recognized wagon image, and constructing a sample data set; step 2, carrying out data amplification processing on the sample data and marking a sample data set; 3, constructing a training data set according to the data obtained in the step 2; 4, constructing a MultiResUNetmodel, and training the MultiResUNet model to obtain a trained deep learning model; 5, inputting a to-be-recognized image into the trained deep learning model to obtain a segmented image of the pull-down rod; and 6, judging whether the pull-down rod is in a falling state or not by utilizing the segmented image of the pull-down rod. Manual labor is replaced by artificial intelligence, and the accuracy and efficiency of a detection result are improved while manpower is saved.

Description

technical field [0001] The invention relates to the technical field of freight train detection, in particular to an image recognition method for a fall-off fault image of a railway freight car drop bar. Background technique [0002] The lower rod is located at the brake beam station of the railway freight car, which belongs to the basic braking system. It is connected with the brake device through the connecting round pin to ensure the reliability of the braking system. It is an important part to ensure the safe and stable operation of the freight car. Shedding faults and losing the original ability to ensure the safety of the truck will easily cause major accidents such as derailment and overturning of the vehicle. During the railway operation, if the lower rod is found to be falling off, the vehicle needs to be stopped directly, which shows the importance of the lower rod to the safe operation of the truck. The purely manual inspection method is likely to cause missed ins...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06K9/62
CPCG06T7/0004G06T2207/10004G06T2207/20081G06T2207/20084G06T2207/30108G06F18/241
Inventor 于洋
Owner HARBIN KEJIA GENERAL MECHANICAL & ELECTRICAL CO LTD
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