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Non-contact monitoring defect identification method for a contact network

A defect identification, non-contact technology, applied in character and pattern recognition, special data processing applications, instruments, etc., can solve the problem of few patent achievements

Active Publication Date: 2019-07-26
CHINA RAILWAY FIRST SURVEY & DESIGN INST GRP
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, there are few studies on the monitoring of abnormal phenomena in catenary video image data using deep learning methods, especially the application of GPU graphics processing technology under the big data platform to analyze video images of catenary monitoring is in the preliminary research stage, forming fewer patents

Method used

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  • Non-contact monitoring defect identification method for a contact network
  • Non-contact monitoring defect identification method for a contact network

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Experimental program
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Effect test

Embodiment

[0090] Based on the comprehensive monitoring and detection video image information data of the railway power supply 6C system, a big data analysis platform based on the GPU hardware architecture is built, and through video image processing technology and deep learning methods, the abnormal phenomena in the catenary video image data are identified and formed. A set of distributed catenary video image intelligent monitoring system.

[0091] The system includes:

[0092] (1) Sensing terminal: Cameras or cameras on operating trains or catenary operation vehicles capture catenary panoramas and partial video screens or images of components, and upload them to the local big data analysis platform or cloud based on GPU hardware architecture through advanced wireless communication technology The data processing center is stored in databases such as HBase.

[0093] (2) Communication network: The collected video or image information data along the catenary line, using the current advanc...

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Abstract

The invention relates to a non-contact monitoring defect identification method for a contact network, which comprises the following steps of acquiring information data of videos, images and audios through a sensing terminal, caching and transmitting the information data in real time through a communication network. By adopting a distributed big data service cluster built based on GPU hardware equipment or a cloud data processing center, the information data is received and stored in a distributed file system, a training set of the information data is established, and distributed calling and parallel computing are carried out on the information data based on a deep learning technology to realize real-time monitoring and fault analysis on the contact network operation information data. Themethod is used as a technical means for monitoring and detecting a non-contact overhead line system; real-time analysis and diagnosis of non-contact video and image monitoring detection of the overhead line system can be realized, a manual intervention mode is avoided, the accuracy of analysis and diagnosis is improved, and the labor cost is reduced, so that digital, intelligent and intelligent revolution of monitoring detection of the high-speed railway overhead line system is realized.

Description

technical field [0001] The invention relates to the technical field of electrified railway catenary monitoring, in particular to a non-contact monitoring defect identification method of catenary. Background technique [0002] The catenary system is an important part of the electrified railway system, which undertakes the key work of transmitting the electric energy in the traction network to the electric locomotive. Due to the complex mechanical and electrical interactions between the pantograph and the catenary device, the vibration and shock generated by the long-term operation of the train will inevitably cause the catenary support device to fail, such as the fasteners of the wrist-arm connectors loosening or The more serious shedding state seriously affects the safe operation of the train. The catenary is exposed to the wind and the sun in the outdoor environment, and it is easy to be damaged, and the phenomenon of foreign matter hanging occurs from time to time. These...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06F16/182
CPCG06F16/182G06V20/41G06V20/52G06V2201/08G06F18/214G06F18/241
Inventor 张珹张学武聂晶鑫田升平李飞王玉环郑刚金光张晓栋赵玮吴亚飞李晋刘刚宫衍圣隋延民
Owner CHINA RAILWAY FIRST SURVEY & DESIGN INST GRP
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