WO2017055838A1 - Procédé et système de prédiction de qualité de voie de chemin de fer - Google Patents

Procédé et système de prédiction de qualité de voie de chemin de fer Download PDF

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Publication number
WO2017055838A1
WO2017055838A1 PCT/GB2016/053013 GB2016053013W WO2017055838A1 WO 2017055838 A1 WO2017055838 A1 WO 2017055838A1 GB 2016053013 W GB2016053013 W GB 2016053013W WO 2017055838 A1 WO2017055838 A1 WO 2017055838A1
Authority
WO
WIPO (PCT)
Prior art keywords
track
section
degradation rates
degradation
tamped
Prior art date
Application number
PCT/GB2016/053013
Other languages
English (en)
Inventor
Valentina VIDUTO
Original Assignee
University Of Huddersfield
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by University Of Huddersfield filed Critical University Of Huddersfield
Publication of WO2017055838A1 publication Critical patent/WO2017055838A1/fr

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Classifications

    • E—FIXED CONSTRUCTIONS
    • E01—CONSTRUCTION OF ROADS, RAILWAYS, OR BRIDGES
    • E01B—PERMANENT WAY; PERMANENT-WAY TOOLS; MACHINES FOR MAKING RAILWAYS OF ALL KINDS
    • E01B35/00—Applications of measuring apparatus or devices for track-building purposes
    • E01B35/06—Applications of measuring apparatus or devices for track-building purposes for measuring irregularities in longitudinal direction
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B61—RAILWAYS
    • B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
    • B61L15/00—Indicators provided on the vehicle or train for signalling purposes
    • B61L15/0018—Communication with or on the vehicle or train
    • B61L15/0027—Radio-based, e.g. using GSM-R
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B61—RAILWAYS
    • B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
    • B61L23/00—Control, warning or like safety means along the route or between vehicles or trains
    • B61L23/04—Control, warning or like safety means along the route or between vehicles or trains for monitoring the mechanical state of the route
    • B61L23/042—Track changes detection
    • B61L23/044—Broken rails
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B61—RAILWAYS
    • B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
    • B61L23/00—Control, warning or like safety means along the route or between vehicles or trains
    • B61L23/04—Control, warning or like safety means along the route or between vehicles or trains for monitoring the mechanical state of the route
    • B61L23/042—Track changes detection
    • B61L23/045—Rail wear
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B61—RAILWAYS
    • B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
    • B61L23/00—Control, warning or like safety means along the route or between vehicles or trains
    • B61L23/04—Control, warning or like safety means along the route or between vehicles or trains for monitoring the mechanical state of the route
    • B61L23/042—Track changes detection
    • B61L23/047—Track or rail movements
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B61—RAILWAYS
    • B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
    • B61L23/00—Control, warning or like safety means along the route or between vehicles or trains
    • B61L23/04—Control, warning or like safety means along the route or between vehicles or trains for monitoring the mechanical state of the route
    • B61L23/042—Track changes detection
    • B61L23/048—Road bed changes, e.g. road bed erosion
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B61—RAILWAYS
    • B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
    • B61L27/00—Central railway traffic control systems; Trackside control; Communication systems specially adapted therefor
    • B61L27/50—Trackside diagnosis or maintenance, e.g. software upgrades
    • B61L27/53—Trackside diagnosis or maintenance, e.g. software upgrades for trackside elements or systems, e.g. trackside supervision of trackside control system conditions
    • E—FIXED CONSTRUCTIONS
    • E01—CONSTRUCTION OF ROADS, RAILWAYS, OR BRIDGES
    • E01B—PERMANENT WAY; PERMANENT-WAY TOOLS; MACHINES FOR MAKING RAILWAYS OF ALL KINDS
    • E01B35/00—Applications of measuring apparatus or devices for track-building purposes
    • E01B35/12—Applications of measuring apparatus or devices for track-building purposes for measuring movement of the track or of the components thereof under rolling loads, e.g. depression of sleepers, increase of gauge
    • E—FIXED CONSTRUCTIONS
    • E01—CONSTRUCTION OF ROADS, RAILWAYS, OR BRIDGES
    • E01B—PERMANENT WAY; PERMANENT-WAY TOOLS; MACHINES FOR MAKING RAILWAYS OF ALL KINDS
    • E01B2204/00—Characteristics of the track and its foundations
    • E01B2204/15—Layout or geometry of the track

Definitions

  • the present invention relates to a computer system and computer implemented method of predicting track quality of a section of railway track.
  • a computer implemented method of predicting track quality of a section of railway track comprising: accessing sets of track geometry quality data values for the section of railway track, wherein the sets of track geometry quality data values are obtained from one or more track geometry measuring devices traveling along the section at spaced time intervals and each of the sets of track geometry quality data values comprise at least one data channel; calculating, for the section of railway track, variance based values for at least one channel for each of the sets; calculating, for the section of railway track, degradation rates for each of the sets of the least one channel, wherein each of the degradation rates are based on a difference value between two of the variance based values over a time period therebetween; identifying if at least one of said degradation rates is a tamped degradation rate indicative an occurrence of tamping of the section of railway track; and determining a quality estimate for the section of railway track based on at least two selected said calculated degradation rates and a spaced time interval between dates associated with the selected calculated degradation
  • a computer system arranged to predicting track quality of a section of railway track, the computer system comprising: a memory storing sets of track geometry quality data values for the section of railway track, wherein the sets of track geometry quality data values are obtained from one or more track geometry measuring devices traveling along the section at spaced time intervals and each of the sets of track geometry quality data values comprise at least one data channel; a processor that in combination with the memory is arranged to: access the sets of track geometry quality data values; calculate, for the section of railway track, degradation rates for each of the sets of the least one channel, wherein each of the degradation rates are based on a difference value between two of the variance based values over a time period therebetween; identify if at least one of said degradation rates is a tamped degradation rate indicative an occurrence of tamping of the section of railway track; and determine a quality estimate for the section of railway track based on at least two selected said calculated degradation rates and a spaced time interval between dates associated with the selected calculated
  • Figure 1 is a schematic block diagram of a computer system, for predicting degradation of a section of railway track, in accordance with a preferred embodiment of the present invention
  • Figure 2 is a flow chart illustrating a computer implemented method of predicting track quality of a section of railway track, in accordance with a preferred embodiment of the present invention.
  • Figure 3 is a flow chart illustrating a storing process of figure 2, in accordance with a preferred embodiment of the present invention.
  • the computer system 100 includes a processor 102 and a memory unit 104 that typically comprises both a Read Only Memory (ROM) 106 and a Random Access Memory (RAM) 108.
  • ROM Read Only Memory
  • RAM Random Access Memory
  • the memory unit 104 is coupled by an address and data bus 120 to the processor 102.
  • the transceiver 110 and a user interface 112 are also coupled to the processor 102 by respective interconnects 130, 140.
  • the processor 102 that in combination with the memory unit 104 is arranged to perform the processes or method described below with reference to figures 2 and 3.
  • FIG. 2 there is a flow chart illustrating a computer implemented method 200 of predicting track quality of a section of railway track, in accordance with a preferred embodiment of the present invention.
  • the method 200 commences at a start block 205 and includes at a storing block 210 that provides for storing sets of track geometry quality data values for the section of railway track.
  • the sets of track geometry quality data values are obtained from one or more track geometry measuring devices and are stored in the memory unit 104.
  • the track geometry measuring devices obtain the data by traveling along the section at recorded dates, spaced by time intervals and collect raw data that is processed to provide the track geometry quality data values.
  • the track geometry measuring devices collected the data values in either an Unmanned Geometry Measuring System (UGMS) or Track Recording Vehicle (TRV) format.
  • UGMS Unmanned Geometry Measuring System
  • TRV Track Recording Vehicle
  • Each of the sets of track geometry quality data values are obtained over a period of time on the recorded dates when a train with a geometry measuring kit travelled along the section.
  • each set of the sets of geometry quality data values comprise four data channels that are known to a person skilled in the art as: AL35m; AL70m; Top35m; and Top70m.
  • a calculating block 220 performed by the processor 102 in combination with the memory unit 104, provides for calculating, variance based values that in this embodiment are standard deviation values SD for at least one data channel (AL35m, AL70m, Top35m or Top70m) for each of the sets.
  • the variance based values are the square of the standard deviation values SD and the standard deviation values SD are calculated as follows:
  • n is the number of data points along the section of railway track in the specific set
  • Xk is the value of a geometry parameter at point k in the section of railway track
  • x is the average value of all the data points in the specific set.
  • standard deviation values SD will be described although the invention is not necessarily limited to use of standard deviation values used and it will be appreciated that variance values or other variance based values can be used.
  • the standard deviation SD imk represents the location in miles, index and time of when the set for a channel was obtained.
  • each of the degradation rates D are based on a difference value between two of the standard deviation values SD over the time period between the obtaining of the sets.
  • each degradation rate D is defined as a variance in track quality value over time and is calculated as follows:
  • T k is an inspection date in days identifying the specific one of the sets j of track geometry quality data values.
  • T (k+1) - T k is the difference in days (time period) between the obtaining of the raw data for the values of SD im(k+1) and SD imk .
  • the method 200 provides for identifying if at least one of the degradation ratesD imk is a tamped degradation rate indicative an occurrence of tamping of the section of railway track.
  • the degradation rates D imk affected by known tamping are designated as tamped degradation rates N imk which are set to 1 or 2 depending on the following:
  • tamping data may not be available for th section of railway track then threshold estimates are used to identify and set the tamped degradation rates N imk .
  • the degradation rates N imk are identified and set as follows:
  • Each of the ten degradation rates Dl to D10 are listed in rows. As shown, if any of the ten degradation rates Dl to D10 for a section are identified as a tamped degradation rate then its calculated degradation rate D imk is replaced with the tamped degradation rate N imk of 1 or 2
  • a quality estimate S imk (or settlement rate) is determined for each section of railway track.
  • the quality estimate S imk is based on at least two selected calculated degradation rates and a spaced time interval between dates associated with the selected calculated degradation rates. For instance, consider the following four situations:
  • the method 200 performs predicting a track quality at a future date Fdate.
  • the track quality predicted includes a degradation rate D imk of the section of track based on the quality estimate S imk , a number of days T x from a reference date Ref until the future date Fdate and a degradation rate D im(Kmax) of the track at the reference date Ref. This can be expressed in the following equation.
  • a block 245 outputs the results at the user interface 112 and/or sends the results to a remote location via the transceiver 110.
  • the method 200 then ends at an end block 245.
  • FIG. 3 there is a flow chart illustrating the storing process of block 210, in accordance with a preferred embodiment of the present invention.
  • the process receives raw data from obtained from one or more track geometry measuring devices that have travelled along the section of railway track on different dates.
  • the raw data is in either the Unmanned Geometry Measuring System (UGMS) or Track Recording Vehicle (TRV) format as will be apparent to a person skilled in the art.
  • UGMS Unmanned Geometry Measuring System
  • TRV Track Recording Vehicle
  • the raw data is sorted by use of an Engineering Line Reference (ELR) code and the necessary geometry channels are extracted which in this embodiment includes 12 such channels namely: Location Miles, Location Yards, AL35m, AL70m, Top35m, Top70m, Gauge, Cant, Curvature, Velocity, Twist .
  • ELR Engineering Line Reference
  • the method cleans the data by checking for various anomalies including: spikes which are massively over standard thresholds, gradient anomalies and drop outs that are flagged and stored as a separate data future analysis if required.
  • spikes which are massively over standard thresholds, gradient anomalies and drop outs that are flagged and stored as a separate data future analysis if required.
  • the data associated with the spikes is removed which results in a cleansed data set.
  • a decision block 320 determines if alignment is required. If the cleansed data set was obtained from a UGMS data format then data alignment is required, otherwise if the data set was obtained from a TRV data format then no aligning is required. When aligning is required a process of aligning the data in the data set is performed at an aligning block 325. However when aligning is not required the process 300 goes to a storing block 330.
  • an aligning process aligns nonaligned sets of track geometry quality data values are data points that are aligned by use of a reference set of data points.
  • the aligning process filters the data in the sets to reduce noise.
  • the data is filtered using a median filter that runs through the data point by point, replacing each point with the median of neighbouring points.
  • splitting points on both reference data set and nonaligned inspection data set are identified.
  • the splitting points are used to partition the data sets into sections and the reference set is also partitioned in the same manner.
  • the alignment process then employs one of three methods to carry out the alignment for a nonaligned section to its corresponding reference section. These three methods are an average, a scale and an interpolation method and are described below.
  • the average method calculates the average value of all signal points on X coordinates of both sections, separately. Then the difference between two average values will be regarded as the shift between two signal sections. This method can be described as follows:
  • S average is the shift; is the average value of all signal points of X coordinates of reference inspection; is the average value of all signal points of X
  • the interpolation method generates the same number of points in the corresponding the nonaligned section and its corresponding reference section. Firstly, the number of points of the two sections are compared and the smaller number of sections is selected as follows:
  • n r is the number of points of the reference section and n n is the number of points of nonaligned section .
  • setp x and setp 2 are obtained they are used to interpolate and generate new coordinates of points of reference and nonaligned sections, separately.
  • the cleansed data set or cleansed data and aligned data set is stored, at the storing block 330, as one of the sets of track geometry quality data values in the RAM 108.
  • the present invention alleviates the problem associated with reliable predictions of the future track quality or track durability identification resulting from tamping.

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  • Engineering & Computer Science (AREA)
  • Mechanical Engineering (AREA)
  • Architecture (AREA)
  • Civil Engineering (AREA)
  • Structural Engineering (AREA)
  • Health & Medical Sciences (AREA)
  • Biomedical Technology (AREA)
  • General Health & Medical Sciences (AREA)
  • Machines For Laying And Maintaining Railways (AREA)

Abstract

L'invention concerne un système informatique et un procédé mis en œuvre par ordinateur de prédiction de qualité de voie d'une section de voie de chemin de fer. Le procédé accède à des ensembles de valeurs de données de qualité géométrique de la voie qui comprennent des canaux de données. Des valeurs d'écart standard sont calculées pour les canaux, puis des taux de dégradation basés sur une valeur de différence entre deux des valeurs d'écart standard sur une période de temps sont calculés. Le procédé identifie si l'un quelconque des taux de dégradation est un taux de dégradation de compactage indiquant une occurrence d'un compactage de la section de voie de chemin de fer. Ensuite, une estimation de qualité de la section de voie de chemin de fer est déterminée. Cette estimation de qualité est basée sur au moins deux dits taux de dégradation calculés sélectionnés et un intervalle de temps espacé entre des dates associées aux taux de dégradation calculés sélectionnés.
PCT/GB2016/053013 2015-09-28 2016-09-28 Procédé et système de prédiction de qualité de voie de chemin de fer WO2017055838A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
GB1517125.9 2015-09-28
GBGB1517125.9A GB201517125D0 (en) 2015-09-28 2015-09-28 Method and system for predicting railway track quality

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WO2017055838A1 true WO2017055838A1 (fr) 2017-04-06

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Cited By (5)

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Publication number Priority date Publication date Assignee Title
RU2671796C1 (ru) * 2017-11-14 2018-11-06 Акционерное общество "Научно-исследовательский и проектно-конструкторский институт информатизации, автоматизации и связи на железнодорожном транспорте" Система распределенного контроля железнодорожного пути для высокоскоростного движения
RU2757941C1 (ru) * 2020-12-24 2021-10-25 Федеральное государственное бюджетное образовательное учреждение высшего образования Иркутский государственный университет путей сообщения (ФГБОУ ВО ИрГУПС) Устройство оценки и контроля динамического состояния верхнего строения пути в условиях интенсификации перевозочных процессов
CN114417921A (zh) * 2022-01-05 2022-04-29 中国国家铁路集团有限公司 轨道几何异常数据的识别方法、装置、设备和存储介质
US11893322B2 (en) 2020-06-26 2024-02-06 Loram Technologies, Inc. Method and system for predicting wear in a rail system
WO2024052306A1 (fr) * 2022-09-06 2024-03-14 Plasser & Theurer Export Von Bahnbaumaschinen Gesellschaft M. B. H. Procédé et dispositif de détermination de la qualité, en particulier du degré de compactage, d'un lit de voie

Non-Patent Citations (2)

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ANDREWS JOHN ET AL: "A stochastic model for railway track asset management", RELIABILITY ENGINEERING AND SYSTEM SAFETY, vol. 130, 2013 - 2013, pages 76 - 84, XP028862919, ISSN: 0951-8320, DOI: 10.1016/J.RESS.2014.04.021 *
DARREN PRESCOTT ET AL: "Modelling maintenance in railway infrastructure management", RELIABILITY AND MAINTAINABILITY SYMPOSIUM (RAMS), 2013 PROCEEDINGS - ANNUAL, IEEE, 28 January 2013 (2013-01-28), pages 1 - 6, XP032410016, ISBN: 978-1-4673-4709-9, DOI: 10.1109/RAMS.2013.6517678 *

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
RU2671796C1 (ru) * 2017-11-14 2018-11-06 Акционерное общество "Научно-исследовательский и проектно-конструкторский институт информатизации, автоматизации и связи на железнодорожном транспорте" Система распределенного контроля железнодорожного пути для высокоскоростного движения
US11893322B2 (en) 2020-06-26 2024-02-06 Loram Technologies, Inc. Method and system for predicting wear in a rail system
US11947881B2 (en) 2020-06-26 2024-04-02 Loram Technologies, Inc. Method and system for performing and comparing financial analysis of different rail life scenarios in a rail system
RU2757941C1 (ru) * 2020-12-24 2021-10-25 Федеральное государственное бюджетное образовательное учреждение высшего образования Иркутский государственный университет путей сообщения (ФГБОУ ВО ИрГУПС) Устройство оценки и контроля динамического состояния верхнего строения пути в условиях интенсификации перевозочных процессов
CN114417921A (zh) * 2022-01-05 2022-04-29 中国国家铁路集团有限公司 轨道几何异常数据的识别方法、装置、设备和存储介质
CN114417921B (zh) * 2022-01-05 2024-04-30 中国国家铁路集团有限公司 轨道几何异常数据的识别方法、装置、设备和存储介质
WO2024052306A1 (fr) * 2022-09-06 2024-03-14 Plasser & Theurer Export Von Bahnbaumaschinen Gesellschaft M. B. H. Procédé et dispositif de détermination de la qualité, en particulier du degré de compactage, d'un lit de voie
AT18149U1 (de) * 2022-09-06 2024-03-15 Plasser & Theurer Export Von Bahnbaumaschinen Gmbh Verfahren und Vorrichtung zum Bestimmen der Beschaffenheit, insbesondere des Verdichtungsgrads, eines Gleisbetts

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