scholarly journals A Novel Short-Range Prediction Model for Railway Track Irregularity

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Peng Xu ◽  
Rengkui Liu ◽  
Quanxin Sun ◽  
Futian Wang
Keyword(s):  
Prediction Model ◽  
Short Range ◽  
Travel Speed ◽  
Railway Track ◽  
Just In Time ◽  
Railway Network ◽  
Track Geometry ◽  
Short Period ◽  
Track Irregularity ◽  
Transport Volume

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.

A Novel Algorithm for Predicting Track Irregularities of Unit Track Sections

2010 ◽  
Author(s):  
R. K. Liu ◽  
P. Xu ◽  
Q. X. Sun
Keyword(s):  
Short Range ◽  
Computer Software ◽  
Railway Track ◽  
Railway Transportation ◽  
Waveform Data ◽  
Track Geometry ◽  
Short Period ◽  
Track Condition ◽  
Inspection And Maintenance ◽  
Track Irregularities

During train runs, the interaction between train wheels and the rail track underneath makes track geometry change, which in turn results in all kinds of track irregularities. After the 6th train speed raise of China in 2007, railway transportation has shown three main new features: speed-raised, heavy-loading and high-density. Under these features, changes in railway track irregularities of China have also presented some new characteristics: higher deterioration rates of track irregularities and more frequent occurrences of track exceptions. To ensure the train operational safety and increase the transportation service quality, the preventive inspection and maintenance of railway track facilities have been put forward once again by railway maintenance departments of China. A precondition for the preventive inspection and maintenance is about how to accurately evaluate and predict the future track condition according to the historical track inspection data. In this paper, based on the characteristics of track irregularity changes and in accordance with the calculus thinking, we have developed a short-range prediction model called SRPM. The model uses track waveform data generated by the track geometry car (TGC) to predict track irregularities of a unit track section with the length of 100m for each day in a future short period of time. An algorithm for using SRPM to predict track irregularities has also been designed. According to the designed algorithm, using ORACLE database and computer program languages, we have programmed a computer software named P-SRPM. We then used P-SRPM to deal with 25 sets of TGC-generated track waveform data from the up going track of the Beijing-Shanghai railway (Jing-Hu railway) administrated by Jinan Railway Bureau (JRB) and predicted track irregularities of unit sections in the railway track segment. Finally, errors in these predictions were analyzed in both temporal and spatial dimensions. From the error analysis results, we come to the conclusion that SRPM can fairly accurately make short-range predictions for track irregularities of each unit section in the JRB-administrated Jing-Hu railway track (up going).

scholarly journals Developing an Enhanced Short-Range Railroad Track Condition Prediction Model for Optimal Maintenance Scheduling

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Peng Xu ◽  
Chuanjun Jia ◽  
Ye Li ◽  
Quanxin Sun ◽  
Rengkui Liu
Keyword(s):  
Prediction Model ◽  
Short Range ◽  
Prediction Method ◽  
Maintenance Scheduling ◽  
Railroad Track ◽  
Track Geometry ◽  
Track Maintenance ◽  
Track Condition ◽  
Optimal Maintenance ◽  
Process Work

As railroad infrastructure becomes older and older and rail transportation is developing towards higher speed and heavier axle, the risk to safe rail transport and the expenses for railroad maintenance are increasing. The railroad infrastructure deterioration (prediction) model is vital to reducing the risk and the expenses. A short-range track condition prediction method was developed in our previous research on railroad track deterioration analysis. It is intended to provide track maintenance managers with two or three months of track condition in advance to schedule track maintenance activities more smartly. Recent comparison analyses on track geometrical exceptions calculated from track condition measured with track geometry cars and those predicted by the method showed that the method fails to provide reliable condition for some analysis sections. This paper presented the enhancement to the method. One year of track geometry data for the Jiulong-Beijing railroad from track geometry cars was used to conduct error analyses and comparison analyses. Analysis results imply that the enhanced model is robust to make reliable predictions. Our in-process work on applying those predicted conditions for optimal track maintenance scheduling is discussed in brief as well.

scholarly journals Study of Railway Track Irregularity Standard Deviation Time Series Based on Data Mining and Linear Model

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Jia Chaolong ◽  
Xu Weixiang ◽  
Wei Lili ◽  
Wang Hanning
Keyword(s):  
Time Series ◽  
Standard Deviation ◽  
Time Series Data ◽  
Arma Model ◽  
Railway Track ◽  
Series Data ◽  
Railway Transportation ◽  
Track Geometry ◽  
Track Irregularity ◽  
Railway Passenger

Good track geometry state ensures the safe operation of the railway passenger service and freight service. Railway transportation plays an important role in the Chinese economic and social development. This paper studies track irregularity standard deviation time series data and focuses on the characteristics and trend changes of track state by applying clustering analysis. Linear recursive model and linear-ARMA model based on wavelet decomposition reconstruction are proposed, and all they offer supports for the safe management of railway transportation.

Novel Algorithm for Mutual Alignment of Railway Track Geometry Measurements

2021 ◽  
pp. 036119812110319
Author(s):  
Kristin Eklöf ◽  
Andrew Nwichi-Holdsworth ◽  
Johan Eklöf
Keyword(s):  
Measurement Errors ◽  
Measurement Data ◽  
Weighted Average ◽  
Railway Track ◽  
Railway Network ◽  
Track Geometry ◽  
Spatially Correlated ◽  
Geometry Measurement ◽  
Variable Sample Rate ◽  
Novel Algorithm

Track geometry measurements are regularly collected to monitor the condition of a railway network. To detect deterioration patterns and enable predictive maintenance, sequential measurement runs must be mutually aligned which has been proven a serious challenge. This paper presents a novel algorithm for mutual alignment of track geometry signal data. It resolves several previously intractable alignment problems: highly segmented data with variable sample rate, spatially correlated and uncorrelated measurement errors, convergence to true locations, and consistency over time. The algorithm adjusts spatial measurement errors by splitting signals in continuous segments. Re-sampled, error-corrected signals are mutually aligned using cross correlation, and this process is repeated until the mutual alignment meets a pre-defined precision threshold. Missing measurement values are handled by imputing an interpolated offset from nearby segments, ensuring that the signals remain continuous. By using weighted average offsets over all aligned signals, the law of large numbers guarantees convergence and consistency. The practical feasibility of the algorithm is demonstrated on empirical track geometry measurement data from the British railway network, owned and operated by Network Rail.

scholarly journals Requirement Assessment of the Relative Spatial Accuracy of a Motion-Constrained GNSS/INS in Shortwave Track Irregularity Measurement

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5296 ◽  
Author(s):  
Quan Zhang ◽  
Qijin Chen ◽  
Xiaoji Niu ◽  
Chuang Shi
Keyword(s):  
Health Monitoring ◽  
Field Tests ◽  
Satellite System ◽  
Relative Accuracy ◽  
Railway Track ◽  
Spatial Accuracy ◽  
Track Geometry ◽  
Accuracy Requirement ◽  
Position Errors ◽  
Track Irregularity

Modern railway track health monitoring requires high accuracy measurements to ensure comfort and safety. Although Global Navigation Satellite System/Inertial Navigation System (GNSS/INS) integration has been extended to track geometry measurements to improve the work efficiency, it has been questioned due to its positioning accuracy at the centimeter or millimeter level. We propose the relative spatial accuracy based on the accuracy requirement of track health monitoring. A requirement assessment of the spatial relative accuracy is conducted for shortwave track irregularity measurements based on evaluation indicators and relative accuracy calculations. The threshold values of the relative spatial accuracy that satisfy the constraints of shortwave track irregularity measurements are derived. Motion-constrained GNSS/INS integration is performed to improve the navigation accuracy considering the dynamic characteristics of the track geometry measurement trolley. The results of field tests show that the mean square error and the Allan deviation of the relative position errors of motion-constrained GNSS/INS integration are smaller than 0.67 mm and 0.16 mm, respectively, which indicates that this approach meets the accuracy requirements of shortwave track irregularities, especially vertical irregularities. This work can provide support for the application of GNSS/INS systems in track irregularity measurement.

Wu Guang High-Speed Rail Track Irregularity Power Spectrum Analysis

2014 ◽  
Vol 638-640 ◽  
pp. 1224-1228 ◽  
Author(s):  
Ji Yang Li ◽  
Lin Ya Liu ◽  
Dong Hua Kou
Keyword(s):  
Power Spectrum ◽  
High Speed ◽  
Railway Track ◽  
High Speed Rail ◽  
Track Geometry ◽  
Railway Line ◽  
Spectrum Density ◽  
Track Irregularity ◽  
Parameter Values ◽  
Geometry Inspection

Irregularity is the locomotive and the main excitation source of vibration, is directly related to the smooth running of the train, safety and comfort, is to control the maximum operating speed of the train one of the main factors. The statistic specimen was collected by track geometry inspection car from Wuhan-Guangzhou high-speed rail. Based on the stationarity test of the specimen, Fast Fourier Transform (FFT) method was used to evaluate the spectrum of the whole specimen space. The power spectrum density (PSD) and related functions of track irregularity were obtained by MATLAB program. We analyzed it by comparing the fitting curve of the national speed lines and fitting curve of Qinhuangdao-Shenyang dedicated passenger railway line, by comparison, the Wuhan-Guangzhou high-speed railway track irregularity is much better than the national speed lines and Qinhuangdao-Shenyang dedicated passenger railway line. The parameter values of PSD fitting curve for track irregularity are obtained by the nonlinear curve-fitting algorithm in the least-squares sense, which has referencing value to maintenance high-speed rail.

scholarly journals Deformation Law and Control Limit of CRTSIII Slab Track under Subgrade Frost Heave

2021 ◽  
Vol 11 (8) ◽  
pp. 3520
Author(s):  
Xiaopei Cai ◽  
Qian Zhang ◽  
Yanrong Zhang ◽  
Qihao Wang ◽  
Bicheng Luo ◽  
...  
Keyword(s):  
High Speed ◽  
Base Plate ◽  
Element Model ◽  
Middle Part ◽  
Railway Track ◽  
Frost Heave ◽  
Track Structure ◽  
Slab Track ◽  
Plastic Damage ◽  
Track Irregularity

In order to find out the influence of subgrade frost heave on the deformation of track structure and track irregularity of high-speed railways, a nonlinear damage finite element model for China Railway Track System III (CRTSIII) slab track subgrade was established based on the constitutive theory of concrete plastic damage. The analysis of track structure deformation under different subgrade frost heave conditions was focused on, and amplitude the limit of subgrade frost heave was put forward according to the characteristics of interlayer seams. This work is expected to provide guidance for design and construction. Subgrade frost heave was found to cause cosine-type irregularities of rails and the interlayer seams in the track structure, and the displacement in lower foundation mapping to rail surfaces increased. When frost heave occured in the middle part of the track slab, it caused the greatest amount of track irregularity, resulting in a longer and higher seam. Along with the increase in frost heave amplitude, the length of the seam increased linearly whilst its height increased nonlinearly. When the frost heave amplitude reached 35 mm, cracks appeared along the transverse direction of the upper concrete surface on the base plate due to plastic damage; consequently, the base plate started to bend, which reduced interlayer seams. Based on the critical value of track structures’ interlayer seams under different frost heave conditions, four control limits of subgrade frost heave at different levels of frost heave amplitude/wavelength were obtained.

scholarly journals The Design and Implementation of an Inertial GNSS Odometer Integrated Navigation System Based on a Federated Kalman Filter for High-Speed Railway Track Inspection

2021 ◽  
Vol 11 (11) ◽  
pp. 5244
Author(s):  
Xinchun Zhang ◽  
Ximin Cui ◽  
Bo Huang
Keyword(s):  
Kalman Filter ◽  
Navigation System ◽  
High Speed ◽  
Measurement Accuracy ◽  
Railway Track ◽  
Filter Method ◽  
Integrated Navigation ◽  
High Speed Railway ◽  
Track Geometry ◽  
Integrated Navigation System

The detection of track geometry parameters is essential for the safety of high-speed railway operation. To improve the accuracy and efficiency of the state detector of track geometry parameters, in this study we propose an inertial GNSS odometer integrated navigation system based on the federated Kalman, and a corresponding inertial track measurement system was also developed. This paper systematically introduces the construction process for the Kalman filter and data smoothing algorithm based on forward filtering and reverse smoothing. The engineering results show that the measurement accuracy of the track geometry parameters was better than 0.2 mm, and the detection speed was about 3 km/h. Thus, compared with the traditional Kalman filter method, the proposed design improved the measurement accuracy and met the requirements for the detection of geometric parameters of high-speed railway tracks.

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