EP3458331A1 - Procédé et dispositif de surveillance d'au moins un composant de voie posé dans la construction de chemin de fer - Google Patents

Procédé et dispositif de surveillance d'au moins un composant de voie posé dans la construction de chemin de fer

Info

Publication number
EP3458331A1
EP3458331A1 EP17724725.1A EP17724725A EP3458331A1 EP 3458331 A1 EP3458331 A1 EP 3458331A1 EP 17724725 A EP17724725 A EP 17724725A EP 3458331 A1 EP3458331 A1 EP 3458331A1
Authority
EP
European Patent Office
Prior art keywords
data
sensor
rail
component
signal processing
Prior art date
Legal status (The legal status 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 status listed.)
Granted
Application number
EP17724725.1A
Other languages
German (de)
English (en)
Other versions
EP3458331B1 (fr
Inventor
Sven ECK
Reinhold Ebner
Paul O'leary
Werner KOLLMENT
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Materials Center Leoben Forschung GmbH
Original Assignee
Materials Center Leoben Forschung GmbH
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 Materials Center Leoben Forschung GmbH filed Critical Materials Center Leoben Forschung GmbH
Publication of EP3458331A1 publication Critical patent/EP3458331A1/fr
Application granted granted Critical
Publication of EP3458331B1 publication Critical patent/EP3458331B1/fr
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • 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
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B61—RAILWAYS
    • B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
    • B61L1/00—Devices along the route controlled by interaction with the vehicle or train
    • B61L1/02—Electric devices associated with track, e.g. rail contacts
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B61—RAILWAYS
    • B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
    • B61L1/00—Devices along the route controlled by interaction with the vehicle or train
    • B61L1/20—Safety arrangements for preventing or indicating malfunction of the device, e.g. by leakage current, by lightning
    • 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
    • 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
    • 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

Definitions

  • the invention relates to a method for continuous particular
  • Condition monitoring of at least one laid in railway construction infrastructure component in particular a rail switch, with at least one arranged on the infrastructure component sensor.
  • the invention relates to a device for continuous particular
  • Condition monitoring of at least one infrastructure component laid in railway construction comprising at least one sensor arranged on the infrastructure component.
  • the invention relates to a use of such a device.
  • sensors are arranged, for example, on a specially used rail vehicle, which measure forces acting on rails on the rails.
  • a method of diagnosing a rail switch with a rail vehicle Sensor is disclosed, for example, in WO 2006/032307 A1. With such a method, it is possible to detect acting forces or their change, but there is always only a punctual monitoring instead. In addition, it is also necessary during a journey of such a rail vehicle, a
  • Rail line at least partially blocked for scheduled traffic.
  • WO 02/090166 A1 discloses a device for
  • Condition monitoring of tracks with multiple sensors comparing measured values with reference values.
  • a condition of any infrastructure component, in particular a rail switch can not be monitored effectively enough, since a considerable part of defects is not recognized.
  • EP 0 344 145 A1 discloses a device for detecting a state of
  • the object of the invention is to provide a method of the type mentioned, with which a state of a track component, in particular a rail switch, can be reliably and effectively detected and automated.
  • Another object is to provide a device of the aforementioned type, with which a state of a track component, in particular a rail switch, reliably and effectively and automatically recognizable.
  • the procedural object is achieved in that in a method of the type mentioned by the sensor at and additionally before and / or after a rollover of the infrastructure component by a rail vehicle data is collected and segmented, wherein from the detected and segmented data, a state of the infrastructure component is determined.
  • An advantage achieved with the invention is to be seen in particular in that, by segmenting the data, a state of a route component can be continuously, automatically and in-situ monitored or determined. It can be monitored, for example, moving points, rigid Weichenherzen, rails and / or sleepers of a railway line. Data is preferred in each case
  • a response of the infrastructure component to a current operation is used to make statements about a state of the same, for example, a time-resolved development of an elongation at a certain position.
  • a load of the corresponding infrastructure component before, during and / or after a rolling over or crossing of a rail vehicle is measured or recorded at a measuring point for all rail vehicles.
  • the recorded or recorded data are segmented or evaluated a load of the infrastructure component as a function of time.
  • the data is divided into three parts: a load on the infrastructure component before a crossing, during a crossing and after crossing the rail vehicle via the infrastructure component.
  • the values of the first part and the third part are optionally compared with one another, that is, a load on the
  • a type of load on the infrastructure component can be characterized.
  • a state of a track component is monitored by a single sensor, in particular by a strain sensor, which z. B. may be formed as strain gauges or optical strain gauge.
  • a state of a infrastructure component such as a railroad switch is determined by a method according to the invention, but optionally also a state of a wheel of a rail vehicle. For example, hollow or out-of-round wheels are detected. This is especially true for one
  • Movement component shifted This can be detected by appropriate comparison algorithms. Further, a transition between a rail and a
  • Track switch formed discontinuous, so that in a roll over the same both the rail switches and wheels of the rail vehicle are loaded.
  • the states of the rail switch and the wheels influence each other or there is a cumulative effect.
  • the individual effects can also be analyzed separately from each other by the segmentation of the recorded data.
  • captured data may be interpreted using computer models, where the computer models describe a response of the travel component to these rolling wheels. This allows different influencing factors to be separated. It can be distinguished, for example, whether a strong shock during a
  • Track component are used by the segmentation characteristic patterns in the same for the identification of a rail vehicle.
  • rail vehicles with a cargo that changes with each journey such as freight trains and rail vehicles, with essentially the same load as passenger trains on each journey.
  • Rail vehicles of the former type the load or a weight thereof is determined for each axle and calculated from a total weight of the rail vehicle. It is thus also possible to have a weight of a wagon of a freight train and thus to detect a state of charge of the same or with a theoretical
  • Rail vehicle determined from the measured signals. This is done in particular without additional speed sensors, acceleration sensors and / or train information. Furthermore, for example, a state of a switch heart of a rail switch is predicted with predetermined algorithms. In addition, envelopes are used to isolate individual measurements for further analysis. It will also be detected by the envelope long-term deviations of the same, which indicate continuing changes. A prerequisite for the evaluation of the data with envelopes is the segmentation of the same as well as the automated determination of a train speed from sensor data.
  • Rail vehicle influences of a track to decouple. This is preferably done automatically.
  • Signal analysis is particularly preferably carried out in situ so that necessary maintenance work on the instrument can be obtained via meaningful evaluation results
  • Track component can be predicted. It can be provided that the data detected and / or evaluated by the sensor are compared with known data. As a result, for example, setpoint data is matched with measured data, whereby a deviation from a desired state of a travel path component is detected. It is thus possible to perform a quality control of a infrastructure component. For example, from the measured and processed data by comparison with a setpoint geometry of a switch rated a quality of Radlauflaufes directly after installation, which allows quality control of a switch geometry and local installation. In addition, it distinguishes in particular random noise or disturbances caused by natural sources from an approaching rail vehicle. Noise caused by conventional sources usually has a Gaussian distribution. Another statistical distribution of data suggests other causes, such as a defective rail vehicle itself, a misshaped wheel, a lowered rail switch or other deviations. In a first step, therefore, a statistical distribution of data is determined and checked whether the data is a
  • Gaussian distribution or statistically distributed differently.
  • a cause of the noise is determined from this. If there is no Gaussian distribution, the noise is caused by an irregularity. It has proved to be favorable to automatically check those data which are obtained from a load of the infrastructure component immediately before rolling over the same by a rail vehicle by a so-called Kolmogorov-Smirnov test.
  • the acquired data are processed in a signal processing system connected to the sensor and arranged directly on the track component for information about a condition of the track component.
  • the data processed in this way are used to evaluate influences from a rolling over vehicle such as a railroad car and a track or a track component, for example a railroad track switch.
  • a rolling over vehicle such as a railroad car and a track or a track component, for example a railroad track switch.
  • a large number of data is recorded and evaluated on the spot. For example, an elongation at at least one point of the infrastructure component is detected, in particular by means of a measuring strip or optical method, such that sensor signals triggered in particular by train crossings are resolved temporally into individual axes and a signal level is determined by individual axle loads.
  • Track component of the at least one sensor data are detected.
  • a track component such as a rail switch
  • a sensor signal is triggered.
  • punctual monitoring it is thus possible to have more precise or temporally resolved ones
  • the evaluation results are automatically and continuously transmitted to central points, such as a local traffic service or a headquarters of the infrastructure company.
  • analyzed and reduced data are transmitted to the central computer via, for example, radio networks.
  • data from different measuring points are transmitted and combined.
  • Intelligent data analysis which is made possible by computer models of the infrastructure component, allows changes to be recorded and analyzed over a longer period of time. From this further action requirements can be derived, such as a prediction of a next inspection or an exchange plan
  • Track component is measured. This is especially of a
  • Detected strain gauge which is placed directly on the track component.
  • the elongation per unit of time can also by an optical Dehnmess vide be determined.
  • a speed and / or an acceleration of a rail vehicle rolling over the travel component is subsequently determined.
  • the further goal is achieved if a signal processing system is provided in a device of the type mentioned in order to evaluate data detected by the sensor directly to the infrastructure component.
  • Arrangement of the signal processing system on the infrastructure component detected by the sensor data can be evaluated in place.
  • acquired data in the signal processing system can be processed directly on site for meaningful information about a state of a infrastructure component such as a railroad switch.
  • a point in time for a repair or an exchange of the monitored infrastructure component can be predicted.
  • a sensor for measuring or detecting an elongation per unit time may be provided, for. B. a strain sensor, which is arranged directly on the track component.
  • the strain sensor can, for example, as strain gauges or optical
  • the signal processing system determines from the data detected by the sensor, for example, a speed and / or
  • Acceleration of a rail vehicle which travels over the infrastructure component with the sensor.
  • the sensor is connected to the signal processing system.
  • a distance of the axes of the rail vehicle is generally known, since this is usually standardized. It may further be provided that the
  • Signal processing system from the processed data without additional sensors a rail vehicle type as well as a weight and a speed of
  • a single sensor is provided, preferably a strain sensor. It is favorable, however, if a plurality of sensors are arranged on a track component, wherein preferably the sensors are designed to measure different data and connected to the signal processing system.
  • Signal processing system then evaluates the data transmitted to each of these sensors.
  • sensors in addition to a strain gauge, a temperature sensor, a sound sensor, an optical strain gauge and / or the like may be provided. It is useful if the sensors are of different types, but it may also be beneficial if two or more similar sensors on a
  • Track component are arranged.
  • one or more sensors and in each case a signal processing system are arranged on a plurality of track components.
  • one or more sensors are each arranged on rails, rail switches or the like, which receive different data. It is thus provided a so-called sensor swarm, wherein the sensors at a distance of 100 m to 1000 m, preferably from 250 m to 750 m, in particular of about 500 m, are arranged from each other.
  • a distance between individual sensors depends on a routing.
  • sensors which are arranged at a distance of 1000 m or more from each other may be sufficient.
  • Rail network are always the same number and type of sensors are arranged so that the respective collected data with each other and / or optionally with
  • Standard data are comparable. It is particularly useful if only one sensor is arranged per measuring point, which is designed in particular as a strain sensor.
  • Track components possible.
  • the data acquired by the sensor or the sensors on a track component is preferably evaluated first by each signal processing system, and the evaluated data is subsequently exchanged with the other signal processing systems in order to minimize the amount of data to be transmitted. Subsequently, the exchanged data
  • the signal processing system comprises a device for self-sufficient energy supply. This submission is designed for example as a photovoltaic system. Furthermore, it is favorable if the or each signal processing system is designed with local energy stores and a device for wireless data transmission.
  • Fig. 1 recorded data from different rail vehicles when driving over a rail switch
  • FIG. 2 shows a temporal segmentation of acquired data
  • Fig. 3 detected and evaluated data of a rail vehicle when driving over a rail switch
  • Fig. 5 shows collected data for six rail vehicles when driving over a
  • FIG. 6 shows data in accordance with FIG. 5;
  • Fig. 7 envelopes and deviations.
  • Fig. 1 shows recorded data from different rail vehicles when driving over a rail switch. It is a strain or stretching of a rigid
  • Rail vehicles are shown among themselves, these are different types of passenger trains and freight trains and a maintenance train.
  • At least one sensor is arranged on the track component.
  • a strain gauge is on a switch heart arranged to measure an elongation per unit time of the infrastructure component.
  • the acquired data is then evaluated directly on the infrastructure component, for which purpose a signal processing system is arranged directly on it.
  • characteristic patterns are used in the same for the identification of a rail vehicle.
  • a load of the corresponding infrastructure component before, during and after a crossing of a rail vehicle is measured at a measuring point, the data being segmented. This can be seen in Fig. 1, wherein maximum deflections of the strain measurements of individual axes rolling over railroad tracks
  • the temporally first strong deflections thus correspond to the axes of a traction vehicle and the temporal subsequent deflections the axes of the following cars.
  • the data recorded before or afterwards correspond to a signal from the sensor before or after the passage of the sensor
  • Fig. 2 wherein three areas A, B, C are visible. The segmentation is done to a
  • Rail switch arranged sensor to separate.
  • the temporal segmentation may be used additionally or alternatively to separate overflow signals of a locomotive and wagons as well as for the separate analysis of individual axes.
  • a monitoring of the statistics of the strain signals before and / or after an actual railroad overflow makes it possible to distinguish between rail vehicles without faulty running behavior without restrictions. Consequently, such information can be provided to a railway operator.
  • running rail vehicles can be used for condition monitoring of the guideway.
  • FIGS. 3 and 4 respectively show recorded and evaluated data of a
  • the uppermost part shows the data collected by the sensor before a sensor overflow, whereby an elongation per unit of time is recorded.
  • the middle part shows a histogram of the acquired signal as a strain-dependent frequency.
  • an evaluation of the signal by the Kolmogorow-Smirnow test By such an evaluation, random noise caused by conventional sources of noise caused by an approaching rail vehicle is generated.
  • Fig. 3 shows a Gaussian distribution
  • Fig. 4 shows a different distribution and the data have oscillating components. This allows the conclusion that the data recorded and evaluated in FIG. 4 represents a deviation from a standard state. In this case, individual flats in wheels, which are caused for example by non-standard braking and lead to a non-round running behavior can be identified.
  • FIG. 5 shows recorded data for six rail vehicles running without restrictions when traveling over a rail switch. Data from such rail vehicles have in the run on a Gaussian distribution. In this example, it is a passenger train traveling at regular intervals via a railroad track instrumented with a sensor. In the same way, locomotives of freight trains can be compared, as doing likewise at regular intervals similar
  • Raw data of a time-strain signal measurement shown in FIG. 5 can be corrected via a generally standardized axial distance with respect to an actual speed of the rail vehicle and then brought to coincidence. This is shown in FIG. As a result, a direct comparison of time-expansion curves of the rail vehicles traveling at different times over the railroad track is possible. Irrespective of a railway network (heavy-load network, passenger train network or mixed transport network), it can be assumed that during the service life of a infrastructure component it will be of similar kind at regular intervals
  • Rail vehicles is run over. It is therefore appropriate to further evaluate the typical curves obtained in this way for individual types of rail vehicles using statistical methods, and to evaluate the signals of one or more typical types
  • FIG. 7 shows an envelope determined from the overflows of the same rail vehicle shown on FIGS. 5 and 6 on different days of a week and a deviation from individual measurements of the same. In this way, each new crossing of the same type of rail vehicle can be compared with the previous ones.
  • a long-term monitoring of a shape of the envelope thus allows direct conclusions about a state of an envelope Guideway component. Furthermore, continuous changes are detected via the envelope.
  • a continuous change in the envelope of a specific rail switch indicates normal wear, while a sudden change in the envelope indicates breakouts in the area of a wheel transition. It is useful to consider the different variations of envelopes with computer simulations of a wheel overflow for a specific switch type and a selected one
  • Rail vehicle type to combine a correlation between a measured change in the envelopes and a physical change in the

Landscapes

  • Engineering & Computer Science (AREA)
  • Mechanical Engineering (AREA)
  • Architecture (AREA)
  • Civil Engineering (AREA)
  • Structural Engineering (AREA)
  • Automation & Control Theory (AREA)
  • Machines For Laying And Maintaining Railways (AREA)
  • Train Traffic Observation, Control, And Security (AREA)
  • Length Measuring Devices With Unspecified Measuring Means (AREA)
  • Electric Propulsion And Braking For Vehicles (AREA)

Abstract

L'invention concerne un procédé de surveillance d'états, en particulier en continu, d'au moins un composant de voie posé dans la construction de chemin de fer, en particulier d'un aiguillage, au moyen d'au moins un capteur disposé au niveau du composant de voie. Des données sont détectées et segmentées par le capteur pendant et, en plus, avant et/ou après le passage d'un véhicule ferroviaire sur le composant de voie. Un état du composant de voie est déterminé à partir des données détectées et segmentées. En outre, l'invention concerne un dispositif de surveillance d'états, en particulier en continu, d'au moins un composant de voie posé dans la construction de chemin de fer, en particulier d'un aiguillage, comportant au moins un capteur disposé au niveau du composant de voie. Une unité de traitement de signal est prévue pour évaluer des données, détectées par le capteur, directement au niveau du composant de voie. L'invention concerne en outre l'utilisation d'un tel dispositif.
EP17724725.1A 2016-05-17 2017-05-16 Procédé et dispositif de surveillance d'au moins un composant de voie posé dans la construction de chemin de fer Active EP3458331B1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
ATA50458/2016A AT518759A1 (de) 2016-05-17 2016-05-17 Verfahren und Vorrichtung zur Überwachung zumindest einer im Bahnbau verlegten Fahrwegkomponente
PCT/AT2017/060129 WO2017197423A1 (fr) 2016-05-17 2017-05-16 Procédé et dispositif de surveillance d'au moins un composant de voie posé dans la construction de chemin de fer

Publications (2)

Publication Number Publication Date
EP3458331A1 true EP3458331A1 (fr) 2019-03-27
EP3458331B1 EP3458331B1 (fr) 2020-07-15

Family

ID=58744918

Family Applications (1)

Application Number Title Priority Date Filing Date
EP17724725.1A Active EP3458331B1 (fr) 2016-05-17 2017-05-16 Procédé et dispositif de surveillance d'au moins un composant de voie posé dans la construction de chemin de fer

Country Status (4)

Country Link
EP (1) EP3458331B1 (fr)
AT (1) AT518759A1 (fr)
ES (1) ES2823163T3 (fr)
WO (1) WO2017197423A1 (fr)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP4628387A1 (fr) 2024-04-04 2025-10-08 voestalpine Signaling Austria GmbH Procédé et dispositif de localisation d'au moins une irrégularité d'un contact de voie de roulement de roue

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11260888B2 (en) * 2018-11-16 2022-03-01 Alstom Transport Technologies Method and system for health assessment of a track circuit and/or of a track section
DE102019211406A1 (de) * 2019-07-31 2021-02-04 Siemens Mobility GmbH Verfahren zum Erkennen fehlerhafter Messereignisse und Computerprogrammprodukt
EP4342764A1 (fr) * 2022-09-20 2024-03-27 voestalpine Signaling Austria GmbH Procédé de surveillance d'un aiguillage de rails et entraînement d'aiguillage

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE4207516A1 (de) * 1992-03-10 1993-09-16 Gerd R Dipl Ing Wetzler Verfahren zur erzeugung belastungsabhaengiger schaltsignale an eisenbahnschienen
DE102007034504A1 (de) * 2007-07-24 2009-02-05 Rögener, Baldur Verfahren und Überwachungssystem zum Überwachen von Schienen-Fahrwegen
DE202010009904U1 (de) * 2010-06-24 2011-10-25 Baldur Rögener Messtechnische Anordnung zur Bestimmung der Gleislage und/oder Änderung der Gleisgeometrie (Deformation)
DE102011084160A1 (de) * 2011-10-07 2013-04-11 Siemens Aktiengesellschaft Verfahren und Vorrichtung zur Schienenbrucherkennung
DE102014216726A1 (de) * 2014-08-22 2016-02-25 Siemens Aktiengesellschaft Verfahren zur Erhöhung der Verfügbarkeit einer Raderkennungseinrichtung und Raderkennungseinrichtung

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP4628387A1 (fr) 2024-04-04 2025-10-08 voestalpine Signaling Austria GmbH Procédé et dispositif de localisation d'au moins une irrégularité d'un contact de voie de roulement de roue
WO2025210201A1 (fr) 2024-04-04 2025-10-09 Voestalpine Signaling Austria Gmbh Procédé de localisation d'au moins une discontinuité d'un contact roue-voie

Also Published As

Publication number Publication date
ES2823163T3 (es) 2021-05-06
WO2017197423A1 (fr) 2017-11-23
EP3458331B1 (fr) 2020-07-15
AT518759A1 (de) 2017-12-15

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