Method and system for identifying falling fault of rail wagon hook lifting rod

A technology for fault identification and railway wagons, applied in neural learning methods, character and pattern recognition, instruments, etc., can solve the problems of low accuracy rate, achieve the effect of improving accuracy rate, enhancing generalization ability, and reducing mis-segmented regions

Inactive Publication Date: 2020-04-28
HARBIN KEJIA GENERAL MECHANICAL & ELECTRICAL CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to solve the problem of low accuracy rate of detecting the fall-off fault of the freight car hook

Method used

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  • Method and system for identifying falling fault of rail wagon hook lifting rod
  • Method and system for identifying falling fault of rail wagon hook lifting rod
  • Method and system for identifying falling fault of rail wagon hook lifting rod

Examples

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Example Embodiment

[0046] Specific embodiment one: reference figure 1 Specifically explain this embodiment,

[0047] The method and system for identifying the failure of the rail freight car hook lifting rod falling off in this embodiment includes the following steps:

[0048] 1. The training set required to build a deep learning model

[0049] The high-definition gray-scale image collection of the hook lift bar is completed by the image collection equipment on both sides of the rail of the truck. Because the truck is running in the open air, the hook lift bar will be subject to natural conditions (such as rain stains, mud stains, rust) and Man-made conditions (such as oil stains) affect different gray levels in the image. Therefore, when collecting data samples of the hook-lift bar in the early stage, it is necessary to ensure the diversity of the data as much as possible to ensure that the samples cover the hook-lift bar images under various conditions as much as possible. This can improve the gene...

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PUM

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Abstract

The invention discloses a method and system for identifying a falling fault of a rail wagon hook lifting rod, and belongs to the technical field of freight train detection. The objective of the invention is to solve the problem of low accuracy of truck hook lifting rod falling fault detection by use of an existing method. The specific implementation process of the method comprises the following steps: step 1, collecting a truck image, determining a hook lifting rod region from the collected truck image, extracting a hook lifting rod region image, and constructing a training set by utilizing the extracted hook lifting rod region image; 2, constructing a deep learning model, and training the constructed deep learning model by using the training set to obtain a trained deep learning model; and step 3, inputting a to-be-detected image into the trained deep learning model to obtain an output result of the deep learning model, and processing the output result by using an image processing method to obtain a judgment result of the falling fault of the hook lifting rod. The method and system are mainly used for detecting falling of the hook lifting rod.

Description

technical field [0001] The invention relates to a method and system for identifying a fall-off fault of a rail freight car hook lifter, and belongs to the technical field of freight train detection. Background technique [0002] The hook lifter is a part for uncoupling the couplers of two connected cars. When freight cars are marshalling at the station, it is often necessary to turn the hook lifter to unmarshal the vehicles. If the hook lifter fails, it will affect the marshalling of the train. operate. In previous inspections, manual inspections were usually used. This detection method is affected by human subjective factors, and when artificial fatigue occurs, it will cause false detection and missed detection of faults, resulting in low accuracy of fault detection. [0003] Therefore, it is of great significance to carry out automatic fault detection on trucks. But there is no automatic fault detection method at present. Although the detection can be realized through ...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V20/41G06N3/045G06F18/2433
Inventor 庞博
Owner HARBIN KEJIA GENERAL MECHANICAL & ELECTRICAL CO LTD
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