A Novel Short-Range Prediction Model for Railway Track Irregularity
In recent years, with axle loads, train loads, transport volume, and travel speed constantly increasing and railway network steadily lengthening, shortcomings of current maintenance strategies are getting to be noticed from an economical and safety perspective. To overcome the shortcomings, permanen...
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| Format: | Article |
| Language: | English |
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Wiley
2012-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2012/591490 |
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| author | Peng Xu Rengkui Liu Quanxin Sun Futian Wang |
| author_facet | Peng Xu Rengkui Liu Quanxin Sun Futian Wang |
| author_sort | Peng Xu |
| collection | DOAJ |
| description | In recent years, with axle loads, train loads, transport volume, and travel speed constantly increasing and railway network steadily lengthening, shortcomings of current maintenance strategies are getting to be noticed from an economical and safety perspective. To overcome the shortcomings, permanent-of-way departments throughout the world have given a considerable attention to an ideal maintenance strategy which is to carry out appropriate maintenances just in time on track locations really requiring maintenance. This strategy is simplified as the condition-based maintenance (CBM) which has attracted attentions of engineers of many industries in the recent 70 years. To implement CBM for track irregularity, there are many issues which need to be addressed. One of them focuses on predicting track irregularity of each day in a future short period. In this paper, based on track irregularity evolution characteristics, a Short-Range Prediction Model was developed to this aim and is abbreviated to TI-SRPM. Performance analysis results for TI-SRPM illustrate that track irregularity amplitude predictions on sampling points by TI-SRPM are very close to their measurements by Track Geometry Car. |
| format | Article |
| id | doaj-art-ceda9bb818fd469caae8f405154de866 |
| institution | OA Journals |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-ceda9bb818fd469caae8f405154de8662025-08-20T02:19:30ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2012-01-01201210.1155/2012/591490591490A Novel Short-Range Prediction Model for Railway Track IrregularityPeng Xu0Rengkui Liu1Quanxin Sun2Futian Wang3MOE Key Laboratory for Urban Transportation Complex Systems Theory, Beijing Jiaotong University, No. 3 Shang Yuan Cun, Haidian District, Beijing 100044, ChinaMOE Key Laboratory for Urban Transportation Complex Systems Theory, Beijing Jiaotong University, No. 3 Shang Yuan Cun, Haidian District, Beijing 100044, ChinaMOE Key Laboratory for Urban Transportation Complex Systems Theory, Beijing Jiaotong University, No. 3 Shang Yuan Cun, Haidian District, Beijing 100044, ChinaMOE Key Laboratory for Urban Transportation Complex Systems Theory, Beijing Jiaotong University, No. 3 Shang Yuan Cun, Haidian District, Beijing 100044, ChinaIn recent years, with axle loads, train loads, transport volume, and travel speed constantly increasing and railway network steadily lengthening, shortcomings of current maintenance strategies are getting to be noticed from an economical and safety perspective. To overcome the shortcomings, permanent-of-way departments throughout the world have given a considerable attention to an ideal maintenance strategy which is to carry out appropriate maintenances just in time on track locations really requiring maintenance. This strategy is simplified as the condition-based maintenance (CBM) which has attracted attentions of engineers of many industries in the recent 70 years. To implement CBM for track irregularity, there are many issues which need to be addressed. One of them focuses on predicting track irregularity of each day in a future short period. In this paper, based on track irregularity evolution characteristics, a Short-Range Prediction Model was developed to this aim and is abbreviated to TI-SRPM. Performance analysis results for TI-SRPM illustrate that track irregularity amplitude predictions on sampling points by TI-SRPM are very close to their measurements by Track Geometry Car.http://dx.doi.org/10.1155/2012/591490 |
| spellingShingle | Peng Xu Rengkui Liu Quanxin Sun Futian Wang A Novel Short-Range Prediction Model for Railway Track Irregularity Discrete Dynamics in Nature and Society |
| title | A Novel Short-Range Prediction Model for Railway Track Irregularity |
| title_full | A Novel Short-Range Prediction Model for Railway Track Irregularity |
| title_fullStr | A Novel Short-Range Prediction Model for Railway Track Irregularity |
| title_full_unstemmed | A Novel Short-Range Prediction Model for Railway Track Irregularity |
| title_short | A Novel Short-Range Prediction Model for Railway Track Irregularity |
| title_sort | novel short range prediction model for railway track irregularity |
| url | http://dx.doi.org/10.1155/2012/591490 |
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