The article describes the properties and application of the original adaptive multipoint (for each irregularity size) method for predicting the values of track geometric parameters and their changes over time, based on the use of convergence theory. Prediction results are presented in the form of irregularity size distribution function (ISDF). ISDF shows the cumulative length of specific-size track irregularity within an arbitrary length track segment at the end of the prediction interval. The method is based on three main principles: using the ISDF function to describe track condition and changes therein, using only the results of previous measurements for calculations as input information about the condition of the track, using the ISDF convergence process analysis to calculate future values of the track geometric parameters. The method is invariant to the length of the time interval between past measurements. The method also allows to identify a tendency to sudden spontaneous deterioration of the track, which does not follow from a regular trend. For longitudinal level defects, the average prediction error for defect sizes s>|3|mm and prediction intervals of 2 and 6 months does not exceed 0.35%.
| Published in | American Journal of Mechanical and Industrial Engineering (Volume 7, Issue 1) |
| DOI | 10.11648/j.ajmie.20220701.12 |
| Page(s) | 7-12 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2022. Published by Science Publishing Group |
Rail Track, Degradation, Track Condition Prediction, Convergence
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| [9] | Sato Y. Convergence Theory Including Spot Tamping, Conference on Railway Engineering, s 507-511 Australia, 1998. |
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APA Style
Gregory Krug. (2022). Adaptive Multipoint Method for Predicting Geometric Parameters of the Railway Track Based on Convergence Theory. American Journal of Mechanical and Industrial Engineering, 7(1), 7-12. https://doi.org/10.11648/j.ajmie.20220701.12
ACS Style
Gregory Krug. Adaptive Multipoint Method for Predicting Geometric Parameters of the Railway Track Based on Convergence Theory. Am. J. Mech. Ind. Eng. 2022, 7(1), 7-12. doi: 10.11648/j.ajmie.20220701.12
AMA Style
Gregory Krug. Adaptive Multipoint Method for Predicting Geometric Parameters of the Railway Track Based on Convergence Theory. Am J Mech Ind Eng. 2022;7(1):7-12. doi: 10.11648/j.ajmie.20220701.12
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Download@article{10.11648/j.ajmie.20220701.12,
author = {Gregory Krug},
title = {Adaptive Multipoint Method for Predicting Geometric Parameters of the Railway Track Based on Convergence Theory},
journal = {American Journal of Mechanical and Industrial Engineering},
volume = {7},
number = {1},
pages = {7-12},
doi = {10.11648/j.ajmie.20220701.12},
url = {https://doi.org/10.11648/j.ajmie.20220701.12},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajmie.20220701.12},
abstract = {The article describes the properties and application of the original adaptive multipoint (for each irregularity size) method for predicting the values of track geometric parameters and their changes over time, based on the use of convergence theory. Prediction results are presented in the form of irregularity size distribution function (ISDF). ISDF shows the cumulative length of specific-size track irregularity within an arbitrary length track segment at the end of the prediction interval. The method is based on three main principles: using the ISDF function to describe track condition and changes therein, using only the results of previous measurements for calculations as input information about the condition of the track, using the ISDF convergence process analysis to calculate future values of the track geometric parameters. The method is invariant to the length of the time interval between past measurements. The method also allows to identify a tendency to sudden spontaneous deterioration of the track, which does not follow from a regular trend. For longitudinal level defects, the average prediction error for defect sizes s>|3|mm and prediction intervals of 2 and 6 months does not exceed 0.35%.},
year = {2022}
}
TY - JOUR T1 - Adaptive Multipoint Method for Predicting Geometric Parameters of the Railway Track Based on Convergence Theory AU - Gregory Krug Y1 - 2022/05/07 PY - 2022 N1 - https://doi.org/10.11648/j.ajmie.20220701.12 DO - 10.11648/j.ajmie.20220701.12 T2 - American Journal of Mechanical and Industrial Engineering JF - American Journal of Mechanical and Industrial Engineering JO - American Journal of Mechanical and Industrial Engineering SP - 7 EP - 12 PB - Science Publishing Group SN - 2575-6060 UR - https://doi.org/10.11648/j.ajmie.20220701.12 AB - The article describes the properties and application of the original adaptive multipoint (for each irregularity size) method for predicting the values of track geometric parameters and their changes over time, based on the use of convergence theory. Prediction results are presented in the form of irregularity size distribution function (ISDF). ISDF shows the cumulative length of specific-size track irregularity within an arbitrary length track segment at the end of the prediction interval. The method is based on three main principles: using the ISDF function to describe track condition and changes therein, using only the results of previous measurements for calculations as input information about the condition of the track, using the ISDF convergence process analysis to calculate future values of the track geometric parameters. The method is invariant to the length of the time interval between past measurements. The method also allows to identify a tendency to sudden spontaneous deterioration of the track, which does not follow from a regular trend. For longitudinal level defects, the average prediction error for defect sizes s>|3|mm and prediction intervals of 2 and 6 months does not exceed 0.35%. VL - 7 IS - 1 ER -
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