scholarly journals Analyzing Major Track Quality Indices and Introducing a Universally Applicable TQI

2020 ◽  
Vol 10 (23) ◽  
pp. 8490
Author(s):  
Stefan Offenbacher ◽  
Johannes Neuhold ◽  
Peter Veit ◽  
Matthias Landgraf
Keyword(s):  
Measurement Data ◽  
Railway Track ◽  
Quality Indices ◽  
Combine Measurement ◽  
Track Geometry ◽  
University Of Technology ◽  
Track Condition ◽  
Railway Operation ◽  
Selection Of ◽  
Track Quality

Adequate railway track condition is a prerequisite for safe and reliable railway operation. Many track quality indices (TQIs) have been developed with the aim of assessing the track condition holistically. These indices combine measurement signals of some or all relevant geometry parameters with different mathematical models. In this paper, a selection of important TQIs is evaluated. Using measurement data of a five kilometer track section, the indices are calculated and their properties are discussed. This study reveals that all indices exhibit drawbacks to varying degrees. As a consequence, a new index has been developed—the track quality index of Graz University of Technology (TUG_TQI). Its favorable characteristics are presented by means of the above-mentioned test section. The TUG_TQI combines all relevant track geometry parameters, which are normalized beforehand to eliminate over or underrepresentation of different parameters. Thus, the index reliably describes the overall geometrical track quality.

Application of data mining techniques for the investigation of track geometry and stiffness variation

2019 ◽  
Vol 234 (5) ◽  
pp. 439-453 ◽  
Author(s):  
Mohammad Mehrali ◽  
Morteza Esmaeili ◽  
Saeed Mohammadzadeh
Keyword(s):  
Data Mining ◽  
Railway Track ◽  
Quality Indices ◽  
Dominant Wavelength ◽  
Data Mining Techniques ◽  
Track Geometry ◽  
Railway Tracks ◽  
Track Condition ◽  
Track Stiffness ◽  
Track Quality

Railway tracks are one of the most important national assets of many countries. The major part of the annual budget of railway companies concerns repairing, improving, and maintaining railway tracks, which is a challenge for railway managers. The logical method of repair and maintenance should take into account all the economic and technical aspects of the problem and proper management of track maintenance—without knowing the factors and parameters responsible for the track failure—quality control methods, and finally, the choice of the appropriate repair methods. Railway track geometry is the main factor that identifies the track behavior and condition. It is based on measuring the geometric parameters of the track determined by the track quality indices. The existing track quality indices mostly represent the geometrical condition of the railway track superstructure. In the past years, the effects of track bed stiffness on the track condition have been investigated. This paper investigates the railway track condition based on the railway track geometry parameters as well as the vertical track stiffness. A method for continuous measurement of track stiffness along a railway line is described and demonstrated. By measuring the track geometry parameters and stiffness, the superstructure and the substructure condition of the railway track are assessed. In addition, the relation between these data is investigated by using data mining techniques such as classification, decision tree, clustering, and dominant wavelength filtering. It is shown that filtering the data based on the dominant wavelength provides the best correlation between the track geometry in the vertical direction and stiffness.

scholarly journals Condition monitoring of railway track systems by using acceleration signals on wheelset axle-boxes

Transport ◽  
2017 ◽  
Vol 33 (2) ◽  
pp. 555-566 ◽  
Author(s):  
Andrzej Chudzikiewicz ◽  
Roman Bogacz ◽  
Mariusz Kostrzewski ◽  
Robert Konowrocki
Keyword(s):  
Service Use ◽  
Preliminary Investigation ◽  
Measurement Data ◽  
Cost Effective ◽  
Railway Track ◽  
Track Condition ◽  
Preliminary Preparation ◽  
Multiple Unit ◽  
Acceleration Signals ◽  
Track Quality

The aim of this paper is to demonstrate the possibilities of estimating the track condition using axle-boxes and car-bodies motions described by acceleration signals. In the paper, the results presented indicate the condition of tracks obtained from the preliminary investigation on the test track. Furthermore, the results from the supervised runs (on Polish Railway Lines) of Electric Multiple Unit (EMU-ED74) with the prototype of track quality monitoring system installed on-board are described. As Track Quality Indicator (TQI) algorithm, used in the mentioned prototype, a modified Karhunen–Loève transformation is used in preliminary preparation of acceleration signals. The transformation is used to extract the principal dynamics from measurement data. Obtained results are compared to other methods of evaluating the geometrical track quality, namely methods, which apply the synthetic coefficient Jsynth and five parameters of defectiveness W5. The results from the investigation showed that track condition estimation is possible with acceptable accuracy for in-service use and for defining cost-effective maintenance strategies.

scholarly journals GELEŽINKELIO KELIO GEOMETRINIŲ PARAMETRŲ DINAMIKOS TYRIMAS TAIKANT KELIO KOKYBĖS INDEKSĄ / RAILWAYS GEOMETRICAL PARAMETERS DYNAMICS INVESTIGATION BY TRACK QUALITY INDEX

2018 ◽  
Vol 10 (0) ◽  
pp. 1-7
Author(s):  
Vytautas Motiejus Bubnelis ◽  
Benas Slepakovas ◽  
Laura Černiauskaitė ◽  
Henrikas Sivilevičius
Keyword(s):  
Quality Index ◽  
Rail Transport ◽  
Geometric Parameters ◽  
Railway Track ◽  
Geometrical Parameters ◽  
Track Geometry ◽  
Track Condition ◽  
Over Time ◽  
Track Quality

Rail transport, in competition with other modes of transport, has to improve the quality of passenger and freight transport. In order to carry passengers and goods quickly, efficiently and safely, it is necessary take maintenance railways so that their geometric parameters do not exceed the tolerances. About real railway track condition, the data is obtained by track geometry recording car, measuring seven geometric parameters dispersion. This paper presents the methodology for determining and estimating the geometric parameters of the track geometry, which shows that the track quality index (TQI) is the sum of the variance of seven geometric parameters. Experimental research on the two-track A (8km) and B (11km) a three-year period (2015-2017) for all 12-month KKI, establish their quality dynamics (change over time). These data indicate that the quality of the analyzed sections A and B was good, but due to the increasing mass (in megatons) of transported loads, there is a tendency to deteriorate. Santrauka Geležinkelių transportas, konkuruodamas su kitomis transporto rūšimis, privalo gerinti keleivių ir krovinių vežimų kokybę. Norint greitai, efektyviai ir saugiai vežti keleivius ir krovinius, būtina taip prižiūrėti geležinkelių kelius, kad jų geometrinių parametrų nuokrypiai neviršytų leidžiamųjų nuokrypių. Apie tikrąją geležinkelių kelio būklę duomenys gaunami kelmačiu išmatavus septynių geometrinių parametrų sklaidą. Šiame darbe pateikta geležinkelio kelio geometrinių parametrų sklaidos nustatymo ir vertinimo metodika, kurioje įrodyta, kad kelio kokybės indeksas (KKI) yra septynių geometrinių parametrų dispersijų suma. Eksperimentiškai ištyrus dviejų geležinkelio kelių A (8 km) ir B (11 km) trijų metų laikotarpiu (nuo 2015 iki 2017 metų) visų 12 mėnesių KKI, nustatyta jų kokybės dinamika (kaita bėgant laikui). Šie duomenys rodo, kad ištyrinėtų A ir B ruožų kelio kokybė buvo gera, bet dėl didėjančios pervežtų krovinių suminės masės (megatonų skaičiaus) turi tendenciją blogėti.

scholarly journals Data-Driven Bias Correction and Defect Diagnosis Model for In-Service Vehicle Acceleration Measurements

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 872 ◽  
Author(s):  
Lei Bai ◽  
Rengkui Liu ◽  
Qing Li
Keyword(s):  
Bias Correction ◽  
False Positive ◽  
Measurement Data ◽  
Data Driven ◽  
Railway Track ◽  
Proposed Model ◽  
Vehicle Acceleration ◽  
Defect Diagnosis ◽  
Quality Instruments ◽  
Track Quality

Track quality instruments use low-cost accelerometers placed on or attached to the floors of operating trains, and these instruments collect substantial amounts of data over short inspection periods. The measurements collected by the instruments are the main data source for track irregularity evaluation. However, considerable measurement bias exists in the vertical and lateral vibration data obtained from such instruments. False positive track vibration defects detected by track quality instruments occur frequently. This results in considerable time and effort being expended needlessly because maintenance workers have to visit the railway track sites to check and review the track vibration defects. Therefore, we propose a model for data-driven bias correction and defect diagnosis for in-service vehicle acceleration measurements based on track degradation characteristics. Substantial amounts of historical track measurement data from different inspection methods were mined extensively to eliminate the false positive detection of track vibration defects and diagnose the causes of track vibration defects. Actual measurement data from the Lanxin Railway were used to validate our proposed model. The success rate achieved in identifying false positive track vibration defects was 84.1%, and that in track vibration defect diagnosis was 75.8%. These high success rates suggest that the proposed model can be of practical use in improving railway track maintenance management.

scholarly journals Establishment of Track Quality Index Standard Recommendations for Beijing Metro

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Reng-Kui Liu ◽  
Peng Xu ◽  
Zhuang-Zhi Sun ◽  
Ce Zou ◽  
Quan-Xin Sun
Keyword(s):  
Quality Assessment ◽  
Measurement Data ◽  
Quality Measurement ◽  
Assessment Method ◽  
Track Geometry ◽  
Quality Assessment Method ◽  
Wheel Loading ◽  
Management Experience ◽  
Track Quality

Since 2007, Beijing Metro started to use track geometry car to measure quality of its tracks under wheel loading conditions. The track quality measurement data from the track geometry car were only used to assess local track quality by means of scoring 1000 m long track segments based on track exceptions. Track quality management experience of national railroads of China shows that, in addition to local track quality assessment, an overall track quality assessment method should be employed. The paper presented research results funded by Road Administration of Beijing Municipal Commission of Transport. The paper proposed an overall track quality assessment method for Beijing Metro and determined the overall track quality standards by means of a statistical method which was proposed in the paper. The standards are necessary for the proposed method to be applied and have been approved by Road Administration of Beijing Municipal Commission of Transport and put into practice.

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).

Evaluating the Equivalency Between Track Quality Indices and the Minimum Track Geometry Threshold Exceedances Along a Canadian Freight Railway

2016 ◽  
Author(s):  
Kirk M. Scanlan ◽  
Michael T. Hendry ◽  
C. Derek Martin
Keyword(s):  
Survey Data ◽  
Large Scale ◽  
Evaluation Methods ◽  
Quality Indices ◽  
Track Geometry ◽  
Threshold Exceedances ◽  
The Individual ◽  
Q Index ◽  
Proper Interpretation ◽  
Track Quality

Railway regulators require that track geometry measurements meet a specific set of minimum safety thresholds. A proper interpretation of track geometry survey data is fundamental for the detection of track exceeding these thresholds and in need of corrective maintenance. Irregular track geometry independent of the minimum safety thresholds can also be used as evidence of degradation in the railway foundation. Therefore, multiple evaluation methods must be applied to the track geometry survey data when assessing foundation degradation. In this study, we compare multiple track geometry evaluation methods in order to assess if they equally identify sections of irregular track geometry along a 335 kilometer section of a Canadian freight railway. The track geometry evaluation methods investigated are the Transport Canada Class 5 minimum safety threshold exceedances and three literature-suggested track quality indices; the Overall Track Geometry Index, the Polish J Index and the Swedish Q Index. Furthermore, this study also investigates the ability of the track quality indices to provide additional insight into track geometry variability in sections without a minimum safety threshold exceedance. The track under investigation is not a Class 5, however, Class 5 minimum safety thresholds were used to produce enough threshold exceedances to allow for the comparison to the track quality indices. The results of the analysis reveal that while the large-scale variability in the three track quality indices is similar, the individual equivalency with the occurrence of Class 5 threshold exceedances is highly variable. Furthermore, only the Overall Track Geometry Index demonstrates the potential to provide consistent additional track geometry variability information.

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.

Combining Track Quality and Performance Measures to Assess Track Maintenance Requirements

2015 ◽  
Author(s):  
Alireza Roghani ◽  
Renato Macciotta ◽  
Michael Hendry
Keyword(s):  
Railway Track ◽  
Threshold Values ◽  
Track Geometry ◽  
Track Maintenance ◽  
Different Types ◽  
Track Stiffness ◽  
And Performance ◽  
Maintenance Requirements ◽  
The Relationship ◽  
Track Quality

The serviceability of a section of railway highly depends on track stiffness and roughness. Railway operators regularly measure parameters associated with track stiffness and roughness to evaluate the track conditions. These measures are used in combination with performance observations to assess maintenance requirements. Although these assessments are mostly qualitative, railway operations have benefited from them. Railway operators keep comprehensive records of different types of track defects along their lines. These records are a measure of track performance and present an opportunity to quantify the relationship between track quality and performance. This brings the possibility of developing a performance-based approach for assessing the maintenance requirement along a railway track. In this paper, a database of track geometry defects along Canadian National Railway’s Lac la Biche subdivision (Alberta) has been compared against measured parameters associated with track roughness and stiffness. The analyses confirm the relationship between track stiffness and roughness, and the occurrence of track defects. This relationship is further used to define threshold values of track roughness and stiffness, and a hazard chart for maintenance requirements along the Lac la Biche subdivision is proposed.

scholarly journals Identification of Temperature-Induced Deformation for HSR Slab Track Using Track Geometry Measurement Data

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5446 ◽  
Author(s):  
Zai-Wei Li ◽  
Xiao-Zhou Liu ◽  
Yue-Lei He
Keyword(s):  
High Speed ◽  
Detection Method ◽  
Measurement Data ◽  
Railway Track ◽  
Discrete Wavelet ◽  
High Speed Rail ◽  
Track Geometry ◽  
Slab Track ◽  
Geometry Measurement ◽  
Inspection Data

Slab track is widely used in many newly built high-speed rail (HSR) lines as it offers many advantages over ballasted tracks. However, in actual operation, slab tracks are subjected to operational and environmental factors, and structural damages are frequently reported. One of the most critical problems is temperature-induced slab-warping deformation (SWD) which can jeopardize the safety of train operation. This paper proposes an automatic slab deformation detection method in light of the track geometry measurement data, which are collected by high-speed track geometry car (HSTGC). The characteristic of track vertical irregularity is first analyzed in both time and frequency domain, and the feature of slab-warping phenomenon is observed. To quantify the severity of SWD, a slab-warping index (SWI) is established based on warping-sensitive feature extraction using discrete wavelet transform (DWT). The performance of the proposed algorithm is verified against visual inspection recorded on four sections of China HSR line, which are constructed with the China Railway Track System II (CRTSII) slab track. The results show that among the 24,806 slabs being assessed, over 94% of the slabs with warping deformation can be successfully identified by the proposed detection method. This study is expected to provide guidance for efficiently detecting and locating slab track defects, taking advantage of the massive track inspection data.

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