Sensor Data Mining for Gas Station Online Monitoring - Details

Author：

Wei, Zhihao (Wei, Zhihao.) | Jia, Kebin (Jia, Kebin.) (Scholars：贾克斌) | Sun, Zhonghua (Sun, Zhonghua.)

Indexed by：

EI Scopus

Abstract：

Aiming　at　the　geography　and　manpower　inconvenience　during　the　monitoring　and　inspection　of　the　gas　station,　a　remote　online　monitoring　system　for　the　gas　station　based　on　the　sensor　network　is　proposed　in　this　paper,　and　the　early　warning　analysis　of　the　abnormal　state　of　the　gas　station　is　proposed　based　on　the　data　mining　technology.　Firstly,　a　gas　station　senor　dataset　is　built　based　on　the　sensor　network　of　the　gas　station.　Then,　based　on　the　B/S　architecture,　a　gas　station　online　monitoring　system　is　built.　Finally,　based　on　the　sensor　dataset　data　mining,　an　abnormal　state　of　the　gas　station　analysis　method　is　proposed.　Experiments　show　that　the　classifier　method　proposed　in　this　paper　has　the　generalization　ability,　it　can　analysis　and　alarm　the　abnormal　state　of　the　gas　station　which　improve　the　intelligence　and　convenience　of　the　gas　station　monitoring.　©　2018,　Springer　International　Publishing　AG.

Keyword：

Large dataset Network architecture Gases Partial discharges Sensor networks Data mining Data handling Gas plants Monitoring

Author Community：

[ 1 ] [Wei, Zhihao]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China
[ 2 ] [Wei, Zhihao]Beijing Laboratory of Advanced Information Networks, Beijing, China
[ 3 ] [Wei, Zhihao]Beijing Advanced Innovation Center for Future Internet Technology, Beijing, China
[ 4 ] [Jia, Kebin]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China
[ 5 ] [Jia, Kebin]Beijing Laboratory of Advanced Information Networks, Beijing, China
[ 6 ] [Jia, Kebin]Beijing Advanced Innovation Center for Future Internet Technology, Beijing, China
[ 7 ] [Sun, Zhonghua]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, China
[ 8 ] [Sun, Zhonghua]Beijing Laboratory of Advanced Information Networks, Beijing, China
[ 9 ] [Sun, Zhonghua]Beijing Advanced Innovation Center for Future Internet Technology, Beijing, China

Reprint Author's Address：

贾克斌
[jia, kebin]beijing advanced innovation center for future internet technology, beijing, china;;[jia, kebin]beijing laboratory of advanced information networks, beijing, china;;[jia, kebin]college of electronic information and control engineering, beijing university of technology, beijing, china

Email：

kebinj@bjut.edu.cn

Show more details

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Source ：

ISSN： 2194-5357

Year： 2018

Volume： 682

Page： 257-263

Language： English

Cited Count：

WoS CC Cited Count：

SCOPUS Cited Count：

ESI Highly Cited Papers on the List： 0 Unfold All

WanFang Cited Count：

Chinese Cited Count：

30 Days PV： 28

Affiliated Colleges：

信息科学技术学院本学院/部未明确归属的数据

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