Assessment of railway performance by monitoring land subsidence

Ziyi Yang; Felix Schmid; Clive Roberts

doi:10.1049/cp.2014.1000

Assessment of railway performance by monitoring land subsidence

Ziyi Yang, Felix Schmid, Clive Roberts

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

10 Citations (Scopus)

Abstract

Improvement of railway capability results in heavier axle loads and higher speed lines, which further induces railway subsidence. In order to ensure a good railway performance and reduce railway life cycle costs, railway subsidence should be measured regularly. The paper aims to assess railway performance by monitoring land subsidence along the railway, predicting railway subsidence in the future based on historical subsidence records. Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) is adopted in this research for monitoring land subsidence along the railway while Autoregression Moving Average (ARMA), artificial neural network and grey model are applied for subsidence prediction.

Original language	English
Title of host publication	IET Conference Publications
Publisher	Institution of Engineering and Technology
Volume	2014
Edition	CP631
DOIs	https://doi.org/10.1049/cp.2014.1000
Publication status	Published - 2014
Event	6th IET Conference on Railway Condition Monitoring, RCM 2014 - Birmingham, United Kingdom Duration: 17 Sept 2014 → 18 Sept 2014

Conference

Conference	6th IET Conference on Railway Condition Monitoring, RCM 2014
Country/Territory	United Kingdom
City	Birmingham
Period	17/09/14 → 18/09/14

Keywords

Assessment of railway performance
PS-InSAR
Railway subsidence monitoring
Subsidence prediction

ASJC Scopus subject areas

Electrical and Electronic Engineering

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10.1049/cp.2014.1000

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title = "Assessment of railway performance by monitoring land subsidence",

abstract = "Improvement of railway capability results in heavier axle loads and higher speed lines, which further induces railway subsidence. In order to ensure a good railway performance and reduce railway life cycle costs, railway subsidence should be measured regularly. The paper aims to assess railway performance by monitoring land subsidence along the railway, predicting railway subsidence in the future based on historical subsidence records. Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) is adopted in this research for monitoring land subsidence along the railway while Autoregression Moving Average (ARMA), artificial neural network and grey model are applied for subsidence prediction.",

keywords = "Assessment of railway performance, PS-InSAR, Railway subsidence monitoring, Subsidence prediction",

author = "Ziyi Yang and Felix Schmid and Clive Roberts",

year = "2014",

doi = "10.1049/cp.2014.1000",

language = "English",

volume = "2014",

booktitle = "IET Conference Publications",

publisher = "Institution of Engineering and Technology",

address = "United Kingdom",

edition = "CP631",

note = "6th IET Conference on Railway Condition Monitoring, RCM 2014 ; Conference date: 17-09-2014 Through 18-09-2014",

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TY - GEN

T1 - Assessment of railway performance by monitoring land subsidence

AU - Yang, Ziyi

AU - Schmid, Felix

AU - Roberts, Clive

PY - 2014

Y1 - 2014

N2 - Improvement of railway capability results in heavier axle loads and higher speed lines, which further induces railway subsidence. In order to ensure a good railway performance and reduce railway life cycle costs, railway subsidence should be measured regularly. The paper aims to assess railway performance by monitoring land subsidence along the railway, predicting railway subsidence in the future based on historical subsidence records. Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) is adopted in this research for monitoring land subsidence along the railway while Autoregression Moving Average (ARMA), artificial neural network and grey model are applied for subsidence prediction.

AB - Improvement of railway capability results in heavier axle loads and higher speed lines, which further induces railway subsidence. In order to ensure a good railway performance and reduce railway life cycle costs, railway subsidence should be measured regularly. The paper aims to assess railway performance by monitoring land subsidence along the railway, predicting railway subsidence in the future based on historical subsidence records. Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) is adopted in this research for monitoring land subsidence along the railway while Autoregression Moving Average (ARMA), artificial neural network and grey model are applied for subsidence prediction.

KW - Assessment of railway performance

KW - PS-InSAR

KW - Railway subsidence monitoring

KW - Subsidence prediction

UR - http://www.scopus.com/inward/record.url?scp=84928821782&partnerID=8YFLogxK

U2 - 10.1049/cp.2014.1000

DO - 10.1049/cp.2014.1000

M3 - Conference contribution

AN - SCOPUS:84928821782

VL - 2014

BT - IET Conference Publications

PB - Institution of Engineering and Technology

T2 - 6th IET Conference on Railway Condition Monitoring, RCM 2014

Y2 - 17 September 2014 through 18 September 2014

ER -

Assessment of railway performance by monitoring land subsidence

Abstract

Conference

Keywords

ASJC Scopus subject areas

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