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A Platform for Fault Diagnosis of High-Speed Train based on Big data

IFAC-PapersOnLine 2018年第18期51卷 309-314页

作者： Xu, Quan Zhang, Peng Liu, Wenqin Liu, Qiang Liu, Changxin Wang, Liangyong Toprac, Anthony Joe Qin, S. State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Mork Family Department of Chemical Engineering and Materials Science University of Southern California Los AngelesCA90089 United States

High-speed trains are very fast (e.g. 350km/h) and operate at high traffic density, so once a fault has occurred, the consequences are disastrous. In order to better control the train operational status by timely and rapid detection of faults, we need new methods to handle and analyze the huge volumes of high-speed railway data. In this paper, we propose a novel framework and platform for high-speed train fault diagnosis based on big data technologies. The framework aims to allow researchers to focus on fault detection algorithm development and on-line application, with all the complexities of big data import, storage, management, and realtime use handled transparently by the framework. The framework uses a combination of cloud computing and edge computing and a two-level architecture that handles the massive data of train operations. The platform uses Hadoop as its basic framework and combines HDFS, HBase, Redis and MySQL database as the data storage framework. A lossless data compression method is presented to reduce the data storage space and improve data storage efficiency. In order to support various types of data analysis tasks for fault diagnosis and prognosis, the framework integrates online computation, off-line computation, stream computation, real-time computation and so on. Moreover, the platform provides fault diagnosis and prognosis as services to users and a simple case study is given to further illustrate how the basic functions of the platform are implemented. © 2018

关键词： Fault detection Big data Cloud computing Digital storage Edge computing Electric fault currents Failure analysis Information management Railroad cars Railroad plant and structures Railroad transportation Railroads Speed Big data technologies Diagnosis and prognosis Fault detection algorithm Framework and platform High speed railways High speed train (HST) lossless data compression method Real time computations

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