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Failure prediction and health management system of vehicle-mounted train set

A health management system and fault prediction technology, applied in the field of data processing, to achieve the effects of strong portability, improved rapid response capability, and increased revenue share

Active Publication Date: 2018-01-19
CRRC +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] At present, there are no mature failure prediction and health management (PHM) system-level products in the field of rail transit

Method used

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  • Failure prediction and health management system of vehicle-mounted train set
  • Failure prediction and health management system of vehicle-mounted train set
  • Failure prediction and health management system of vehicle-mounted train set

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Embodiment Construction

[0043] The core of the present invention is to provide a vehicle-mounted trainset failure prediction and health management system. The system adopts a distributed structure to sense relevant information from the component level to the subsystem level and then to the vehicle. The system has strong portability and is based on vehicle-mounted Intelligent mirroring model realizes transparent management and analysis of train status.

[0044] 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 w...

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PUM

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Abstract

The invention discloses a failure prediction and health management system of a vehicle-mounted train set. The failure prediction and health management system comprises a reserved number of vehicle level PHM sub systems and a train set level PHM sub system. Each vehicle level PHM sub system is provided with a vehicle intelligent mirror image model, and the train set level PHM sub system is providedwith a train set intelligent mirror image model. The system adopts a distribution type structure, and can perceive relevant information from a part level to a sub system level to the vehicle, the portability of the system is high, transparent management and analysis on the train state are achieved based on the vehicle-mounted intelligent mirror image model, the cost spent on vehicle-mounted trainset failure prediction and health management system analysis and application is lowered, the rapid response capability of enterprises is improved, the state maintenance capability is achieved, and the proportion of service income of the enterprises is increased.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to a failure prediction and health management system for vehicle-mounted train sets. Background technique [0002] In recent years, the total mileage of rail transit operation and the number of trains on the line have increased steadily year by year. In order to ensure the safety of operation and improve the economy of operation and maintenance, it is urgent to develop rail transit equipment failure prediction and health management system-level products. Prognostics and Health Management (PHM): A system that detects, predicts and manages the health status of complex industrial systems by using various data generated in industrial systems, through signal processing and data analysis and other computing means project. PHM technology transforms equipment health management from traditional fault management to recession management, and realizes zero downtime and continuous relia...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): B61L15/00
Inventor 张志强彭畅徐冠基韩龙王岩
Owner CRRC
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