Railway wagon brake shoe key going-out fault recognition method based on artificial neural network

An artificial neural network and railway freight car technology, applied in the field of fault detection of railway freight car operation, to achieve the effect of simple automatic recognition algorithm and strong adaptability

Active Publication Date: 2012-01-25
BEIJING CTROWELL INFRARED TECHN
View PDF2 Cites 29 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0011] Judging from the current search results of existing literature and patents, there is no relevant research and patents on such faults as closing the truncation plug handle

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 brake shoe key going-out fault recognition method based on artificial neural network
  • Railway wagon brake shoe key going-out fault recognition method based on artificial neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0040] The present invention will be further described in detail with reference to the accompanying drawings and embodiments.

[0041] The present invention is an artificial neural network-based fault identification method for brake shoes of railway wagons, and the process flow is as follows: figure 1 shown, including the following steps:

[0042] (1) When the train passes, receive the image, model and vehicle information of the running railway freight car body from the high-speed image collector;

[0043] The vehicle information is the number of trucks, including the number of vehicles. A truck consists of 40-70 vehicles and 1 locomotive. The images and models are stored in the truck body image database. The image naming rules are: x_y_z, x is the number of vehicles in the train Numbering, starting from 1; y is the part of the vehicle, x_1_z is the bogie part of the vehicle, x_2_z is the brake beam part of the vehicle, x_3_z is the middle part of the vehicle, x_4_z is the co...

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 brake shoe key going-out fault recognition method based on an artificial neural network. The method comprises the following steps: (1) obtaining an image, model and wagon information of a running railway wagon body when a train passes through; (2) reading a to-be-recognized image; (3) performing preliminary positioning according to an image name to obtain apreliminarily positioned image; (4) scaling-down the preliminarily positioned image in an equal proportion; (5) preliminarily preprocessing the image scaled down; (6) positioning a candidate region for the preliminarily preprocessed image; (7) extracting an image feature vector of the candidate region; (8) carrying out recognition computing on the feature data; (9) outputting a recognition result. The method cannot influence the normal work of a train inspector on the existing TFDS (travelling fault diagnosis system) system; an automatic recognition result can be stored in a friendly form to provide a convenient re-inspection manner for the train inspector; the method has the advantage of full automatic start or stop and is free from manual intervention in service.

Description

technical field [0001] The invention belongs to the field of detection of railway freight car operation faults, relates to the field of dynamic image detection of TFDS freight car operation faults, and in particular relates to an image automatic recognition method for faults of brake shoe brazing of railway freight cars. Background technique [0002] The trackside image detection system for railway wagon faults is a system that integrates high-speed digital image acquisition, large-capacity image real-time processing technology, precise positioning technology, network technology and automatic control technology, referred to as TFDS. [0003] At present, the TFDS system mainly performs fault identification on the collected images by manually looking at the images, which has high labor costs and high labor intensity. The effect of fault identification is restricted by subjective factors such as the inspector's physiological state and inspection experience. The application of ...

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): G06K9/00G06K9/62G06K9/46G06N3/02
Inventor 张益韩涛赵新国
Owner BEIJING CTROWELL INFRARED TECHN
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap