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3 / 2021-06-24 15:37:37
Performance Degradation Analysis of Railway Vehicle Door System Based on Density Peak Clustering
RVDS; Performance degradation; DPC; EN
Plenary track
Draft Pending
MaXiaoxiao / Nanjing University of AeroNautics and Astronaytics
LuNingyun / Nanjing University of AeroNautics and Astronaytics
XuZhixing / Nanjing Kangni Mechanical & Electrical Co., Ltd
JiangBin / Nanjing University of AeroNautics and Astronaytics






This paper proposed an intelligent analysis with Density Peak Clustering (DPC) to deal with low accuracy in the performance degradation analysis of Railway Vehicle Door System (RVDS). First, the features were evaluated and selected with the Elastic Network (EN). Subsequently, an analysis model that can select degraded data from the door operation data was established by DPC flexibly. The proposed performance degradation analysis of RVDS proposed in this paper has been verified by experiments with data collected from the bench testing door system of Hangzhou Metro Line 4, and the results can be used to validate high accuracy and practical value of the model.
Important Date

  • Conference Date

    Aug 06

    2021

    to

    Aug 08

    2021

  • Aug 08 2021

    Registration deadline

Sponsored By
Professional Committee on Fault Diagnosis and Safety for Technical Processes, Chinese Association of Automation (CAA)
Organized By
University of Electronic Science and Technology of China
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