TECHNICAL PAPERS
Jun 21, 2010

Research on a Short-Range Prediction Model for Track Irregularity over Small Track Lengths

Publication: Journal of Transportation Engineering
Volume 136, Issue 12

Abstract

Based on analysis of some existing prediction methods and models for track irregularities, according to the characteristics of track irregularity development for China railroad, this paper has proposed a short-range prediction model (SRPM) which applies the calculus thinking and method to estimate track irregularities over small track lengths on a single-day basis using track waveform data generated by track geometry car. We applied the SRPM to make predictions for track irregularities of many unit track sections of the up-going tacks of Beijing-Shanghai Railway Line (Jing-Hu Line) using the past two-year waveform data of this railway line. To confirm the efficiency of the SRPM, we compared the actual and estimated irregularities in both time and railway distance dimensions. The comparison shows that the SRPM can accurately predict track irregularities of unit track sections along Jing-Hu Railway Line on each day within a future short period.

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References

Chen, X. M., Wang, L., Yang, F. C., Cai, X. S., and Wu, W. Q. (2006). “Integrating factor method for predicting the developing trend of railway track irregularity.” China Railway Science, 27(6), 27–30 (in Chinese).
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Information

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Go to Journal of Transportation Engineering
Journal of Transportation Engineering
Volume 136Issue 12December 2010
Pages: 1085 - 1091

History

Received: Oct 2, 2009
Accepted: Jun 18, 2010
Published online: Jun 21, 2010
Published in print: Dec 2010

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Authors

Affiliations

Rengkui Liu, Ph.D. [email protected]
Assistant Professor and Director, Dept. of Transportation Information Management, School of Traffic and Transportation, Beijing Jiaotong Univ., No. 3 of Shangyuan Residence Haidian District, Beijing 100044, People’s Republic of China (corresponding author). E-mail: [email protected]
Ph.D. Candidate, State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong Univ., Beijing 100044, People’s Republic of China. E-mail: [email protected]
Futian Wang, Ph.D.
Associate Professor, Dept. of Transportation Information Management, School of Traffic and Transportation, Beijing Jiaotong Univ., Beijing 100044, People’s Republic of China.

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