EP3458331B1 - Method and device for monitoring at least one travel path component laid in rail construction - Google Patents

Description

The invention relates to a method for, in particular, continuous condition monitoring of at least one track component installed in railway construction, in particular a rail switch, with at least one sensor arranged on the track component, data being recorded by the sensor during and additionally before and / or after a rollover of the track component by a rail vehicle .

The invention further relates to a device for, in particular, continuous condition monitoring of at least one guideway component installed in railway construction, such as a rail switch, comprising at least one sensor arranged on the guideway component.

It is known from the prior art to examine track components in railway construction, such as rails, for example, or to monitor a state thereof, in order to be able to detect wear of such components. This is done, for example, by regular optical inspection. Here, a person checks a guideway component at predetermined intervals and, based on this inspection, decides whether to repair or replace such a guideway component. However, this method has the disadvantage that a human eye only recognizes heavy wear of a guideway component. In addition, this inspection depends on the daily condition of the inspecting person. In addition, it is necessary to block at least a section of a railway line from traffic during a visual inspection. Despite such a block, there is still a certain risk potential for the inspecting person during the inspection due to traffic on sidings.

In order to overcome these disadvantages, it is also known to automatically record data of a route component or its changes. For this purpose, sensors are arranged, for example, on a rail vehicle specially used for this purpose, which measure forces acting on rails when being driven on. A method for diagnosing a rail switch with a sensor arranged on a rail vehicle is, for example, in FIG WO 2006/032307 A1 disclosed. With one Although it is possible to record active forces or their changes, it is only possible to monitor them at certain times. In addition, even while a rail vehicle of this type is in motion, it is necessary to block a rail route at least in sections from scheduled traffic.

Furthermore, for example, the WO 02/090166 A1 a device for monitoring the condition of tracks with several sensors, measured values being compared with reference values. With such a device, a state of any route component, in particular a rail switch, cannot be monitored effectively enough, since a considerable number of defects are not recognized.

In the EP 2 022 698 A2 discloses a method and a monitoring system for the operational management of rail tracks. In terms of the method, it is provided that acceleration data is sensed in a monitoring area and evaluated with regard to a passability and / or maximum permissible speed in the monitoring area. The data evaluated in this way are output and / or used for operational management in that the data are used to control the route and / or a rail vehicle.

In the EP 0 344 145 A1 discloses a device for detecting a state of rail switches or crossing points. Although deviations of a wheel arch are measured in one direction, this is not sufficient to reliably detect a state of any travel path component.

With known methods for monitoring a route component, it is not possible to ascertain a cumulative damage to a route component or resulting from multiple causes. In particular, several causes which cause damage or change in the state of a route component cannot be detected in a decoupled manner.

This is where the invention comes in. The object of the invention is to provide a method of the type mentioned at the outset with which a state of a guideway component, in particular a rail switch, can be reliably and effectively and automatically recognized.

Another aim is to provide a device of the type mentioned at the outset with which a state of a guideway component, in particular a rail switch, can be reliably and effectively and automatically identified.

The invention is defined by the features of the independent claims.

The procedural object is achieved according to the invention in that, in a method of the type mentioned at the outset, the acquired data is segmented in time, a state of the route component being determined from the acquired and segmented data.

An advantage achieved with the invention can be seen in particular in that the state of a guideway component can be monitored or determined continuously, automatically and in-situ by segmenting the data. For example, movable switches, rigid switch hearts, rails and / or sleepers of a railway line can be monitored. Data is preferably recorded and analyzed each time a rail vehicle rolls over the guideway component, in particular a rigid switch heart. Efficient data evaluation and data interpretation such as, for example, a fault characterization and / or a data comparison while reducing computing power is thus possible. In particular, a reaction of the guideway component to an ongoing operation is used to make statements about a state of the same, for example a temporally resolved development of an expansion at a specific position. In a first step, a load of the corresponding guideway component is measured or recorded for all rail vehicles at a measuring point before, during and / or after a rail vehicle is overrun or passed over. The recorded or recorded data are segmented or a load on the guideway component is evaluated as a function of a time. The data is divided into three parts: a load on the guideway component before a crossing, during a crossing and after a crossing of the rail vehicle via the guideway component. In addition, the values of the first part and the third part are optionally compared with one another, that is to say a load on the guideway component immediately before and after a rail vehicle is crossed. In this way, a type of load on the guideway component can be characterized. A state of a guideway component is particularly preferred monitored by a single sensor, in particular by a strain sensor, which, for. B. can be designed as a strain gauge or optical strain gauge.

In addition, with a method according to the invention, not only a state of a guideway component such as a rail switch is determined, but optionally, or occasionally also a state of a wheel of a rail vehicle. For example, hollow or out-of-round wheels are recognized. This is particularly useful when monitoring the condition of a rail switch, since both hollow and non-circular wheels can significantly worsen a condition of the same. Interaction of a geometry of the wheel and switch is deteriorated by individual hollow wheels, whereby larger signals are measured in the area of a wheel transition and z. B. can be recognized via threshold values. Due to out-of-round wheels, signal statistics are shifted before and after a wheel transition over a travel path component. This can be recognized by appropriate comparison algorithms. Furthermore, a transition between a rail and a rail switch is discontinuous, so that when the rail is rolled over, both the rail switch and the wheels of the rail vehicle are loaded. The conditions of the rail switch and the wheels influence each other or there is a cumulative effect. The individual effects can subsequently also be evaluated in a decoupled manner by segmenting the recorded data. In addition, acquired data can be interpreted with the aid of computer models, the computer models describing a reaction of the guideway component to wheels that roll over them. This means that various influencing factors can be separated. For example, a distinction can be made as to whether a strong shock is caused by a hollow wheel or a worn switch heart during a rollover of the guideway component.

When evaluating the recorded data to determine the state of the guideway component, the segmentation uses characteristic patterns therein to identify a type of rail vehicle. A basic distinction is made between two types of rail vehicle: rail vehicles with a load that changes with each journey, such as freight trains, and rail vehicles with essentially the same load as passenger trains with each journey. At Rail vehicles of the first-mentioned type, the load or a weight thereof is determined for each axle and from this a total weight of the rail vehicle is calculated. It is thus also possible to recognize a weight of a wagon of a freight train and thus its state of charge or to compare it with a theoretical state of charge.

It is expedient if the recorded and time-segmented data are evaluated using statistical methods and / or envelopes in order to be able to characterize and classify a state of a route component in a fully automated manner. The envelope curves automatically determine, for example, a type of rail vehicle and a speed and / or acceleration of the rail vehicle from the measured signals. This is done in particular without additional speed sensors, acceleration sensors and / or train information. Furthermore, a state of a switch heart of a rail switch is predicted using predetermined algorithms. Envelopes are also used to isolate individual measurements for further analysis. Long-term deviations from the envelope are also recognized via the envelope curve, which indicate continuous changes. A prerequisite for evaluating the data with envelopes is segmenting them and automatically determining a train speed from sensor data.

It is advantageous if the data is separated in time. The sensor signals recorded or triggered by train crossings are broken down in time according to individual axes. Individual axle loads can then be determined using a signal level. As a result, a state of the guideway component is not only recognizable and predictable, but can also be traced back to individual causes. In addition, it is also possible to decouple influences from a rail vehicle rolling over a guideway component and influences from a guideway. This is preferably done automatically. A signal analysis is particularly preferably carried out in situ , so that necessary maintenance work on the guideway component can be predicted via meaningful evaluation results.

It can be provided that the data recorded and / or evaluated by the sensor are compared with known data. As a result, target data are included measured data compared, whereby a deviation from a target state of a route component is detected. It is therefore possible to carry out a quality control of a guideway component. For example, the quality of a wheel overflow is assessed directly after installation from the measured and processed data by comparison with a target geometry of a switch, which enables quality control of a switch geometry and local installation. In addition, this distinguishes in particular random noise or interference caused by natural sources from an approaching rail vehicle. Noise, which is caused by common sources, usually has a Gaussian distribution. Another statistical distribution of data indicates other causes, for example a defective rail vehicle itself, a misshapen wheel of the same, a lowered rail switch or other deviations. In a first step, a statistical distribution of data is consequently determined and it is checked whether the data have a Gaussian distribution or are statistically differently distributed. In a second step, a cause of the noise is determined. If there is no Gaussian distribution, the noise is caused by an irregularity. It has proven to be advantageous to automatically check those data which are obtained from a load on the guideway component immediately before a rail vehicle overruns it by means of a so-called Kolmogorov-Smirnov test.

It is also advantageous if the acquired data are processed in a signal processing system connected to the sensor and arranged directly on the route component to form information about a state of the route component. From the data processed in this way, influences from a rolling vehicle such as a railway wagon and a track or a track component, for example a rail switch, are evaluated. Due to the direct measurement and evaluation of the data on the guideway component, a large amount of data is recorded and evaluated on the spot. For example, an extension at at least one point of the guideway component is recorded, in particular by means of a measuring strip or optical method, in such a way that sensor signals triggered by train crossings in particular are resolved in time according to individual axes and a signal level is determined by individual axle loads. By evaluating the data directly on the guideway component, a transfer of large amounts of data is saved. Furthermore, it is no longer necessary to record a railway line for Block data, which means that data can be recorded and evaluated continuously or continuously. Due to the large number of recorded and evaluated data, a guideway component or its status is monitored particularly precisely, as a result of which even small irregularities are recognized or recorded.

It is expedient if data is recorded by the at least one sensor each time a rail vehicle passes over the guideway component. As a result, a guideway component, such as a rail switch, is continuously monitored each time a rail vehicle is rolled over. A sensor signal is triggered each time a rail vehicle passes. In contrast to selective monitoring, it is thus possible to make more precise or temporally resolved predictions about a state of a route component. In addition, it can be provided that the evaluation results are automatically and continuously transmitted to central points, such as a local driving service or a headquarters of the infrastructure company. By transmitting evaluation results instead of the measured data, a quantity of data to be transmitted is significantly reduced.

To track the change in data over longer periods of time, it can be provided that analyzed and reduced data are transmitted to central computers via, for example, radio networks. In particular, data from different measuring points are transmitted and merged. Through an intelligent data analysis, which is made possible by computer models of the route component, changes can be recorded and analyzed over a longer period of time. Action requirements can subsequently be derived from this, such as, for example, predicting a next inspection or planning an exchange of the guideway component due to reaching critical wear states. This systematic merging of reduced data from different measuring points enables statements to be made about the condition of entire chassis networks. This information can be used to improve and optimize maintenance and / or replacement logistics.

It is advantageous if the sensor measures at least one elongation per unit time of the guideway component. This is recorded in particular by a strain gauge, which is arranged directly on the guideway component. Alternatively, the strain per unit of time can also be determined by an optical strain measurement method. From a measured temporal expansion signal, a speed and / or an acceleration of a rail vehicle rolling over the guideway component is subsequently determined, for example.

The further goal is achieved if a device of the type mentioned at the outset is designed to carry out a method according to the invention, a signal processing system being provided in order to evaluate data detected by the sensor directly on the route component.

An advantage achieved in this way can be seen, in particular, in the fact that, due to the direct arrangement of the signal processing system on the guideway component, data recorded by the sensor can be evaluated on the spot. Thus, recorded data can be processed in the signal processing system directly on site to provide meaningful information about a state of a guideway component such as a rail switch. Subsequently, a point in time for a repair or an exchange of the monitored guideway component can be predicted. In particular, a sensor for measuring or detecting an elongation per unit of time can be provided, e.g. B. a strain sensor, which is arranged directly on the guideway component. The strain sensor can be designed, for example, as a strain gauge or optical strain gauge. From the data recorded by the sensor, the signal processing system determines, for example, a speed and / or acceleration of a rail vehicle that travels with the sensor via the guideway component. For this purpose, the sensor is connected to the signal processing system. A distance between the axles of the rail vehicle is generally known since this is usually standardized. It can also be provided that the Signal processing system determines a type of rail vehicle as well as a weight and a speed of the rail vehicle from the processed data without additional sensors.

Basically, it is sufficient if a single sensor is provided, preferably a strain sensor. However, it is expedient if a plurality of sensors are arranged on a guideway component, the sensors preferably being designed to measure different data and being connected to the signal processing system. The signal processing system then evaluates the data transmitted to it by each sensor. 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 expedient if the sensors are of different types, but it can also be advantageous if two or more sensors of the same type are arranged on a guideway component.

It is also expedient if one or more sensors and a signal processing system are arranged on each of several track components. For example, one or more sensors are arranged on rails, on rail switches or the like, which record different data. A so-called swarm of sensors is thus provided, the sensors being arranged at a distance of 100 m to 1000 m, preferably from 250 m to 750 m, in particular from about 500 m. The general rule is that a distance between individual sensors depends on a route. For example, sensors that are arranged at a distance of 1000 m or more from each other may be sufficient in an essentially straight section. In contrast to this, it is expedient to arrange several sensors with a smaller distance from each other in a heavily loaded route area with curves and switches. In particular, it is advantageous if the same number and type of sensors are always arranged at equidistant intervals of a route area of a rail network, so that the respective recorded data can be compared with one another and / or, where appropriate, with standard data. It is particularly expedient if only one sensor is arranged per measuring point, which is designed in particular as a strain sensor.

In order to be able to recognize or predict the most accurate possible state of several guideway components and subsequently of entire guideway networks, it is advantageous if the signal processing systems are connected to one another in order to exchange recorded and / or evaluated data. This enables even more precise condition monitoring and, subsequently, the lifespan estimation of route components. The data recorded on a route component by the sensor or sensors are preferably first evaluated by each signal processing system and the evaluated data are only subsequently exchanged with the other signal processing systems in order to keep the amount of data to be transmitted as low as possible. The exchanged data can then be compared or compared.

It is advantageous if 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 advantageous if the or each signal processing system is designed with local energy stores and a device for wireless data transmission.

A device according to the invention is advantageously used to predict necessary maintenance work on a guideway component in railway construction.

• Fig. 1 erfasste Daten von unterschiedlichen Schienenfahrzeugen bei einer Fahrt über eine Schienenweiche;
• Fig. 2 eine zeitliche Segmentierung von erfassten Daten;
• Fig. 3 erfasste und ausgewertete Daten eines Schienenfahrzeuges bei einer Fahrt über eine Schienenweiche;
• Fig. 4 erfasste und ausgewertete Daten eines weiteren Schienenfahrzeuges bei einer Fahrt über eine Schienenweiche;
• Fig. 5 zeigt erfasste Daten für sechs Schienenfahrzeuge bei einer Fahrt über eine Schienenweiche;
• Fig. 6 in Deckung gebrachte Daten gemäß Fig. 5;
• Fig. 7 Hüllkurven und Abweichungen.

Further features, advantages and effects result from the exemplary embodiment shown below. In the drawings, to which reference is made, show:

• Fig. 1 recorded data from different rail vehicles when traveling over a rail switch;
• Fig. 2 a temporal segmentation of recorded data;
• Fig. 3 recorded and evaluated data of a rail vehicle when traveling over a rail switch;
• Fig. 4 recorded and evaluated data of another rail vehicle when traveling over a rail switch;
• Fig. 5 shows recorded data for six rail vehicles when traveling over a rail switch;
• Fig. 6 Covered data according to Fig. 5 ;
• Fig. 7 Envelopes and deviations.

Fig. 1 shows recorded data from different rail vehicles when traveling over a rail switch. A load or expansion of a rigid switch heart of a rail switch as a function of time is shown. The strains or loads on the switch heart for different rail vehicles are shown one below the other; these are different types of passenger trains and freight trains as well as a maintenance train.

In a method according to the invention for monitoring a guideway component installed in railway construction, at least one sensor is arranged on the guideway component. For those in Fig. 1 data shown is a strain gauge on a switch heart arranged to measure an elongation per unit time of the guideway component. The recorded data are then evaluated directly on the guideway component, for which purpose a signal processing system is arranged directly there.

When evaluating the recorded data, characteristic patterns in them are used to identify a type of rail vehicle. In all rail vehicles, a load on the corresponding guideway component is measured at a measuring point before, during and after a rail vehicle is crossed, the data being segmented. This is over Fig. 1 can be seen in which the maximum deflections of the strain measurements correspond to individual axes of the rolling stock rolling over rail switches. The first strong swings correspond to the axles of a locomotive and the following swings correspond to the axles of the following wagons. The data recorded before or after corresponds to a signal from the sensor before or after the switch heart is crossed. It follows that a rail vehicle excites the sensor attached to a rail switch to measurable vibrations before and even after a crossing. These recorded data are also used to monitor the condition of the rail switch.

It is expedient to segment recorded data since, due to the different types of rail vehicles and speeds, it is not possible to compare recorded data directly. Although the speeds of similar rail vehicles vary only slightly due to a specified line speed, it is expedient to determine the speed of each individual rail vehicle directly from the expansion signals using the standardized center distance. Such a time segmentation of a continuous measurement signal of a strain gauge is shown in Fig. 2 shown, three areas A, B, C can be seen. The segmentation is carried out in order to separate a load on the rail switch into an area A before, an area B during and an area C after an overflow of the rail vehicle via the sensor arranged on the rail switch. In addition, the time segmentation can additionally or alternatively be used for separating overflow signals from a locomotive and wagons and for separate analysis of individual axles.

Monitoring the statistics of the expansion signals before and / or after an actual rail switch overflow makes it possible to distinguish running rail vehicles from rail vehicles with faulty running behavior without restrictions. Such information can therefore be provided to a railway operator. In addition, running rail vehicles can be used for condition monitoring of the route without restrictions. It is also possible to compare statistics of the expansion signals before and after a rail switch overflow. This provides further information about a condition of the rail switch, such as a permanent deformation caused by the overflow.

Fig. 3 and 4th each show recorded and evaluated data of a rail vehicle crossing of a switch heart. The uppermost part shows the data recorded by the sensor before a sensor overflow, whereby an expansion is recorded per unit of time. In the middle part, a histogram of the acquired signal is shown as a strain-dependent frequency. In the lowest part there is an evaluation of the signal by the Kolmogorow-Smirnow test. Such an evaluation distinguishes random noise, which is caused by conventional sources, from noise or disturbances, which are caused by an approaching rail vehicle. Noise caused by natural sources usually has a Gaussian distribution. Another statistical distribution points to other causes, for example to a faulty rail vehicle itself, a misshapen wheel of the same, a worn switch heart or other influences.

Fig. 3 shows a Gaussian distribution, whereas Fig. 4 shows a different distribution and the data have oscillating components. This allows the conclusion that the in the Fig. 4 recorded and evaluated data represent a deviation from a normal state. In this case, individual flat spots in wheels, which are caused, for example, by braking not conforming to the standards and which lead to non-circular running behavior, can be identified. In the case of rail vehicles which have a Gaussian distribution in the lead, overflow signals can also be used for condition monitoring of the switch.

Fig. 5 shows recorded data for six rail vehicles running without restrictions when traveling over a rail switch. Data from such rail vehicles have a Gaussian distribution in the lead. This example is a passenger train traveling at regular intervals via a rail switch instrumented with a sensor. In the same way, locomotives of freight trains can also be compared, since similar rail vehicles also pass a rail switch at regular intervals. It is possible to couple the strain measurement with information about a type of rail vehicle. However, a clear identification of different rail vehicles is also possible without such additional information.

In Fig. 5 The raw data of a time-stretching signal measurement shown can be corrected with respect to an actual speed of the rail vehicle via a standard axis spacing and then made to coincide. This is in Fig. 6 shown. This enables a direct comparison of time-expansion curves of the rail vehicles traveling over the rail switch at different times. Regardless of a rail network (heavy load network, passenger train network or mixed traffic network), it can be assumed that a track component will be run over at regular intervals by the same type of rail vehicle during the service life. It is therefore expedient to further evaluate the typical curves obtained in this way for individual types of rail vehicle using statistical methods and to use the signals of one or more typical types of rail vehicle for monitoring the condition of the guideway component.

From the time-expansion curves scaled to the same time axis Fig. 6 Desired envelopes for each type of rail vehicle are obtained by using static methods, from which a state of a guideway component is subsequently determined and predicted. Fig. 7 shows one from the in 5 and 6 Overflows of the same rail vehicle shown on different days of a week, as well as a deviation of individual measurements from the same. In this way, each new crossing of the same type of rail vehicle can be compared with the previous ones. Long-term monitoring of a form of the envelope curve thus allows direct conclusions to be drawn about a state of a Guideway component. Furthermore, continuous changes are recognized via the envelope curve.

A continuous change in the envelope curve of a specific rail switch indicates normal wear, for example, while a sudden change in the envelope curve indicates breakouts in the area of a wheel transition. It is expedient to combine the different changes in envelopes with computer simulations of a wheel overflow for a specific switch type and a selected type of rail vehicle in order to improve a correlation between a measured change in the envelopes and a physical change in the route component. Since such computer simulations are very complex, it is expedient to create the results of a computer simulation in advance, for example on an influence of a wear-related change in the geometry of a route on a shape of the envelope curve. During operation, measured envelopes can then be compared on site with calculated curves. In this way, an assessment of a change in state is possible in real time. Subsequently, this also enables a prediction of the development of the condition of a rail switch.

Claims (11)

1. A method for the, in particular, continuous condition monitoring of at least one track component laid in railway construction, in particular a swivel plate, with at least one sensor arranged on the track component, wherein data are detected by the sensor when and also before and/or after a railway vehicle rolls over the track component, characterised in that the detected data are temporally segmented, wherein a condition of the track component is determined from the detected and segmented data.
2. The method according to claim 1, characterised in that the detected and temporally segmented data are evaluated with statistical methods and/or envelope curves.
3. The method according to claim 1 or 2, characterised in that the data are separated temporally.
4. The method according to any one of claims 1 to 3, characterised in that the detected data are processed in a signal processing system connected to the sensor and arranged directly on the track component into information relating to a condition of the track component.
5. The method according to any one of claims 1 to 4, characterised in that data are detected by the at least one sensor each time a railway vehicle travels over the track component.
6. The method according to any one of claims 1 to 5, characterised in that at least one revolution per unit of time of the track component is measured by the sensor.
7. A device for the, in particular, continuous condition monitoring of at least one track component laid in railway construction, such as a swivel plate, comprising at least one sensor arranged on the track component, characterised in that the device is designed for performing a method according to any one of claims 1 to 6, wherein a signal processing system is provided in order to evaluate data detected by the sensor directly on the track component.
8. The device according to claim 7, characterised in that a plurality of sensors are arranged on a track component, wherein the sensors are preferably designed for the measurement of different data and are connected to the signal processing system.
9. The device according to claim 7 or 8, characterised in that in each case one or more sensors and in each case a signal processing system are arranged on a plurality of track components.
10. The device according to claim 9, characterised in that the signal processing systems are connected to one another in order to exchange detected and/or evaluated data.
11. The device according to any one of claims 7 to 10, characterised in that the signal processing system comprises a device for a self-sufficient energy supply.

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