Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Railway wagon adapter flange breaking fault detection method and system

A technology for fault detection and railway wagons, applied in railway vehicle testing, neural learning methods, image data processing, etc., can solve problems such as low efficiency and low accuracy, achieve high operating efficiency, improve accuracy, and improve detection efficiency Effect

Active Publication Date: 2020-05-01
HARBIN KEJIA GENERAL MECHANICAL & ELECTRICAL CO LTD
View PDF7 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present invention aims to solve the problem of low efficiency and low accuracy in detecting the broken fault of the saddle rib by manually checking the image, and the problem of low accuracy in detecting the broken fault of the saddle rib by the existing image automatic detection method

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Railway wagon adapter flange breaking fault detection method and system
  • Railway wagon adapter flange breaking fault detection method and system
  • Railway wagon adapter flange breaking fault detection method and system

Examples

Experimental program
Comparison scheme
Effect test

specific Embodiment approach 1

[0068] Specific implementation mode one: refer to figure 1 To describe this embodiment in detail,

[0069] This embodiment is a method for detecting a broken side of a saddle of a railway freight car, which includes the following steps:

[0070] 1. Collect data and label it

[0071] Take high-definition truck images through the railway pillow equipment. According to the wheelbase information of the train and the prior knowledge of the position of the saddle rib, the sub-image including the saddle rib and the front cover of the rolling bearing is intercepted from the whole truck image. Put the sub-images into the dataset, the size of each sub-image needs to be consistent, and the size of the image must be an integer multiple of 32.

[0072] Because the image of the truck is easily affected by natural conditions such as rain, snow, wind and sand, mud and oil, and the shape of the saddle ribs of different bogie types will also be different. Therefore, in the process of collec...

specific Embodiment approach 2

[0102] This implementation mode is a fault detection system for the breakage of the bearing saddle rib of a railway freight car, and the system includes:

[0103] The image collection unit is used to collect the image of the whole truck, and intercept the sub-image including the bearing saddle rib and the front cover of the rolling bearing;

[0104] A segmentation processing unit, the segmentation processing unit uses a deep learning network model for predicting the image of the bearing saddle rib to be detected, and obtains the segmentation result of the bearing saddle rib and the front cover of the rolling bearing;

[0105] The described deep learning network model is as follows:

[0106] Input the image into the model, the size of the image is an integer multiple of 32, and use it as the input layer;

[0107] Use a 32-channel, 3×3-sized convolution kernel to convolve the input layer to obtain the conv1 layer, and use a 32-channel, 3×3-sized convolution kernel to convolve t...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a railway wagon adapter flange breaking fault detection method and system, and belongs to the technical field of freight train detection. The objective of the invention is to solve the problems of low efficiency and low accuracy of saddle flange breakage fault detection in a manual image inspection mode and the problem of low accuracy of saddle flange breakage fault detection in an existing image automatic detection mode. The method comprises the following steps: acquiring an image and intercepting a sub-image which comprises a bearing saddle flange and a rolling bearing front cover part; putting the sub-images into a data set, and marking two parts of bearing saddle flange areas and a rolling bearing front cover part near the bearing saddle; training a deep learning network model of bearing saddle flange and rolling bearing front cover segmentation; in the detection process, the deep learning network model of the bearing saddle flange and rolling bearing frontcover segmentation is used to predict a to-be-detected bearing saddle flange image, a segmentation result is obtained, and judgment of a bearing saddle flange breaking fault is realized. The method ismainly used for adapter flange breakage fault detection.

Description

technical field [0001] The invention relates to a method for detecting a broken fault of a load-carrying saddle rib of a truck. The invention belongs to the technical field of freight train detection. Background technique [0002] The load-bearing saddle is an important part of the truck components. When the load-bearing saddle ribs are broken, it may endanger the driving safety. In the fault detection of the broken side of the bearing saddle, the existing method uses manual inspection of the image to detect the fault. Due to the fact that the inspectors are prone to fatigue and omissions during the work process, resulting in missed inspections and wrong inspections, which affect driving safety. [0003] Due to the irregular and relatively complex structure of the bearing saddle, and due to the influence of light problems at the location of the bearing saddle and the presence of stains and other factors, it is not easy to distinguish the bearing saddle rib from other parts...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/11G06N3/04G06N3/08G01M17/08
CPCG06T7/0008G06T7/001G06T7/11G06N3/08G01M17/08G06T2207/10004G06T2207/30164G06N3/045
Inventor 孟德剑
Owner HARBIN KEJIA GENERAL MECHANICAL & ELECTRICAL CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com