Method and system for detecting abnormal state of railway overhead line system bolt

A technology of abnormal state and detection method, which is applied in image data processing, instrumentation, computing, etc., can solve the problems of poor detection effect and large dependence, and achieve the effect of solving poor generalization, reducing the amount of data labeling, and reducing work intensity

Pending Publication Date: 2020-07-14
CHINA ACADEMY OF RAILWAY SCI CORP LTD +1
View PDF9 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0009] The embodiment of the present invention provides a method and system for detecting the abnormal state of bolts in the railway catenary, which is used to solve the problem that the supervised learning algorithm used in the prior art for bolt abnormal detection needs to rely on a large number of labeled samples. When the abnormal difference is small Problems that can easily lead to poor detection results

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
  • Method and system for detecting abnormal state of railway overhead line system bolt
  • Method and system for detecting abnormal state of railway overhead line system bolt
  • Method and system for detecting abnormal state of railway overhead line system bolt

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0042] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0043] Aiming at the task of detecting the abnormal state of bolts in the catenary image of the high-speed railway, in order to solve the problem that the direct application of the supervised learning method requires a large amount of data labeling and it is difficult to solve the problem of various types of abnormalities in practical applicat...

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 embodiment of the invention provides a method and system for detecting the abnormal state of a railway overhead line system bolt. The method comprises: acquiring an image of a to-be-detected railway contact network bolt; and based on the trained image generation model and the multiple spatial mapping model, carrying out anomaly detection analysis on the to-be-detected railway contact network bolt image to obtain a railway contact network bolt abnormal state detection result. According to the embodiment of the invention, based on an unsupervised learning algorithm, the problems of poor generalization, difficulty in defining abnormal categories and great reduction of accuracy of unseen abnormal samples of an existing detection algorithm are solved, and the unsupervised learning algorithmdoes not need to define the abnormal categories in detail, so that the data annotation amount is greatly reduced, and the working intensity of detection personnel is reduced.

Description

technical field [0001] The invention relates to the technical field of railway detection, in particular to a method and system for detecting abnormal states of railway catenary bolts. Background technique [0002] In the daily maintenance of railway catenary, there are a large number of abnormal detection tasks of railway catenary images. Since the bolts are typical small-sized parts with a large number and type, the probability of abnormal state is high and the number of abnormal samples that can be collected is relatively small. This makes the bolt state anomaly detection task the most difficult. High-speed rail is a typical complex system. Due to its functional characteristics, bolts are widely used in railway catenary equipment. The detection of its abnormal state is of great significance to maintain the normal operation of high-speed rail. At present, the catenary bolt state abnormality detection task mainly relies on professionals to carry out image screening. The sho...

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): G06T7/00
CPCG06T7/001G06T2207/20081
Inventor 赵冰王同军李平朱建生代明睿马志强马小宁徐贵红杨连报程智博吴艳华曹鸿飞薛蕊
Owner CHINA ACADEMY OF RAILWAY SCI CORP LTD
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