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

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

CN111415326APending Publication Date: 2020-07-14CHINA ACADEMY OF RAILWAY SCI CORP LTD +1
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  • 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

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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...

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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...

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Application Information

Patent Timeline
14 Jul 2020
Publication
CN111415326A
IPC
G06T7/00
CPC
G06T7/001; G06T2207/20081
Inventors
赵冰; 王同军