EP4304915A1

EP4304915A1 - Method for monitoring rail vehicles

Info

Publication number: EP4304915A1
Application number: EP21740555.4A
Authority: EP
Inventors: Daniel Pfeffer; Sigrid GAMSJAEGER
Original assignee: Schunk Carbon Technology GmbH; Schunk Transit Systems GmbH
Current assignee: Schunk Carbon Technology GmbH; Schunk Transit Systems GmbH
Priority date: 2021-03-10
Filing date: 2021-07-12
Publication date: 2024-01-17
Also published as: WO2022189009A1

Abstract

The invention relates to a method for monitoring rail vehicles (11), in particular operating units (16, 17) of the rail vehicles, such as current collectors (13), grounding contacts, lubricating devices, contact shoes, contact devices, contact brushes, grounding brushes or the like, wherein, by means of detection units (18, 19) of a monitoring system (10), data are detected for different attributes of the respective operating units and are assigned to the attributes, wherein data sets formed from attributes and data by the monitoring units are transmitted to a monitoring unit (20) of the monitoring system, wherein the data sets are stored in a database (21) of the monitoring unit and are processed by an evaluation device (22) of the monitoring unit, wherein the evaluation device relates the stored data sets of the respective operating units to each another and carries out a pattern analysis of the data sets, wherein a result of the pattern analysis is output by an output device (23) of the monitoring unit.

Description

Methods for monitoring rail vehicles respective operating units are recorded and assigned to the attributes, with data records formed from attributes and data using the recording units being transmitted to a monitoring unit of the monitoring system, with the data records being stored in a database of the monitoring unit and being processed with an evaluation device of the monitoring unit, with the Evaluation device relates the stored data sets of the respective operating units to one another and performs a pattern analysis of the data sets, with a result bnis the pattern analysis is output with an output device of the monitoring unit. Methods for monitoring rail vehicles or their operating units are known in principle. In the known methods For example, a sensor that is attached directly to the rail vehicle or an operating unit monitors a state of the operating unit or determines a measured value. For example, a line to which compressed air can be applied can be arranged inside a contact strip or contact strip of a roof current collector, whereby if the contact strip breaks or is completely worn out, the compressed air escapes from the line and the contact strip is lowered by a contact wire. Alternatively, a correspondingly installed sensor can also be used to measure the contact pressure of the contact strip on the contact wire, wind speed or other environmental and operating parameters and use it to control activation of the pantograph or another operating unit of the rail vehicle. Here, the operating unit of the rail vehicle is always monitored, limited to the respective rail vehicle.

DE 10 2013 207 271 A1 also discloses wear monitoring of contact strips or contact strips of various rail vehicles. During wear monitoring, rail vehicles or contact strips are recorded with a stationary camera and their state of wear is evaluated. Thus, wear and tear of the different contact strips can be determined at an access road to a depot, independently of the type of rail vehicle.

Irrespective of the recording of actual wear or a measured value, maintenance and inspection of the operating units of the rail vehicles must be carried out at regular intervals in order to prevent undesired failures of the operating units and thus the rail vehicles and to ensure safe operation. An automated measurement of wear can be used, for example, to delay or bring forward the maintenance intervals of individual rail vehicles and thus reduce costs for an unnecessary replacement of wearing parts or a failure of the respective rail vehicle. vehicle. Different operating companies of rail vehicles naturally implement different maintenance concepts. For example, maintenance intervals are scheduled and carried out differently, or are linked to specific operating conditions and rail vehicles. The disadvantage here is that any existing potential for saving operating costs of the rail vehicles is not immediately recognizable.

The invention is therefore based on the object of proposing a method for monitoring rail vehicles that enables cost-optimized operation.

This object is achieved by a method with the features of claim 1.

In the method according to the invention for monitoring rail vehicles, in particular operating units of the rail vehicles, such as pantographs, grounding contacts, lubricating devices, contact strips, grinding devices, contact brushes, grounding brushes or the like, data is recorded with recording units of a monitoring system for various attributes of the respective operating units and assigned to the attributes, with data records formed from attributes and data using the detection units being transmitted to a monitoring unit of the monitoring system, with the data records being stored in a database of the monitoring unit and being processed with an evaluation device of the monitoring unit, with the evaluation device reading the stored data records of the respective Operating units related to each other and performs a pattern analysis of the data sets, with a result of the pattern analysis with an output device de r monitoring unit is output.

The method according to the invention is used to monitor a number of rail vehicles and in particular a number of operating units of these rail vehicles. An operating unit can be a pantograph, a pantograph, a pantograph, an inverted pantograph, an underbody pantograph, a third rail pantograph, a grounding contact, a shaft grounding system, a lubricator or a wheel alignment lubrication. According to the invention, it is provided that the rail vehicles each have at least one of the aforementioned operating units, preferably several operating units of the same type. The rail vehicles can consequently also each have several operating units of the same and/or different type. The procedure is always carried out with several rail vehicles and operating units of the same type. For its part, the monitoring system used to carry out the method comprises a plurality of acquisition units for acquiring data from the operating units. With the registration units, data is recorded for different attributes of an operating unit and assigned to these attributes. An attribute is understood here as an object-specific property of an operating unit, such as a serial number or a type of rail vehicle on which the operating unit is mounted. One of the data is understood here as attribute values, such as actual information about a serial number or actual information about a type of rail vehicle. The data can be represented by values, characters or files. The attributes, together with the respectively assigned data, form data sets which are transmitted from the respective detection units to a monitoring unit of the monitoring system. The monitoring system therefore only requires at least one individual monitoring unit in which all data sets are brought together, it also being possible for several monitoring units, for example for different applications, to be present. The data records are stored in a database of the monitoring unit and processed continuously or as required using an evaluation device of the monitoring unit. The monitoring unit or the evaluation device is in the form of a computer with a software application running on it. The data sets stored in the database for all or selected operating units, preferably for operating units of the same type, are related to one another by means of the evaluation device and a sample analysis of the data sets is carried out. Consequently, all or selected data sets can be related to each other. A possible correlation of the data sets or data is determined during the pattern analysis. It is essential that at least two attributes per operating unit and a plurality of operating units with these attributes are used for the pattern analysis in order to obtain a sufficient number of comparable data sets with which a correlation can be determined. A result of the pattern analysis or the existence of a correlation of data sets is output with an output device of the monitoring unit. The output device can be, for example, a screen or another suitable device for displaying or for transmitting data to a display device or the like.

Within the scope of the method according to the invention, it is thus possible to use the pattern analysis to determine an interrelationship between data sets, provided this is present. Causal relationships can regularly be derived from interrelationships. In the simplest embodiment of the method, correlations found by the pattern analysis can be used to determine causal relationships, the knowledge of which can in turn be used to optimize the operation of rail vehicles. This makes it possible, please include the operation of rail vehicles to make the monitoring process more cost-effective. For example, an occurrence of a fault in a specific type of operating unit can correlate with a specific type of rail vehicle. This makes it possible to determine the cause of the error or the functional relationship between the rail vehicle and the error and to eliminate it in a targeted manner. Without If the monitoring procedure had been used, the error in question might not have been taken into account any further, since the error cannot be assigned to an obvious cause when viewed individually.

In the method, at least two mutually different attributes can be used by an operating unit in each case, with the attributes from the attribute types type, identification, year of construction, vehicle, use, running time, material, wear and tear, errors, damage, location, image,

sound, detection time or the like of the operation unit can be selected. The data can then be, for example, a designation, a serial number, a year, a date, a vehicle type designation, a measured value, a description of the error, a description of the damage, a position, an image file, a sound file, a time, a period of time or the like.

If the operating unit is a pantograph or pantograph, the following attributes may be used: contact type, material of the contact, initial height and wear height, runtime of the vehicle in kilometers, runtime of the pantograph in kilometers, wear indication in millimeters for contact strip 1, Wear information in millimeters for contact strip 2.

If the operating unit is a third rail pantograph, the following attributes may be used: type of fuse, type of contact strip, material of contact strip, initial height and wear level, running time of the vehicle in kilometers, running time of the pantograph in kilometers, wear indication in millimetres for the grinding piece.

If the operating unit is an earth contact, the following attributes can be used: slip ring material, brush material, brush cross-section, initial height and wear height, running time of the vehicle in kilometers, running time of the grounding contact in kilometers, indication of wear in millimeters for several carbon brushes.

If the operating unit is a shaft grounding system, the following attributes can be used: mating material, fiber material, fiber cross-section, output cross-section and wear level, vehicle runtime in kilometers, runtime of the grounding system in kilometers, wear specification in millimeters for fibers 1 and 2.

If the operating unit is wheel flange lubrication, the following attributes can be used: lubricating pin material, initial length and wear length, running time of the vehicle in kilometers, running time of the lubricating pin in kilometers, wear indication in millimeters.

If the operating unit is a contact strip, the following attributes can be used: material of the contact strip, initial height and wear level, running time of the vehicle in kilometers, running time of the pantograph in kilometers, wear data in millimeters for contact strip 1, wear data in millimeters for contact strip 2.

If the operating unit is a third rail contact strip, the following attributes may be used: contact strip material, initial height and wear level, running time of the vehicle in kilometers, running time of the pantograph in kilometers, wear specification in millimeters for the contact strip.

The detection units can transmit the data to the monitoring unit via a data connection. In principle, the data connection can be formed by a line connection. The data connection can also be a radio connection or another suitable type of data connection. The data connection can be established continuously, at regular intervals or based on events. Overall, it is possible with the monitoring unit records of the operating units, regardless of the Type of data connection to collect and evaluate. The detection units can be connected to or coupled to the monitoring unit via individually different data connections. The data connection can be established via an external data network. The data connection can be via a mobile network,

WLAN, a satellite connection, the Internet or any other radio standard, alone or in combination. The monitoring unit can then also be arranged at a distance from the operating units or the rail vehicles, far away from a rail vehicle in a stationary manner, for example in a building. In particular, this makes it possible to obtain data sets from a rail vehicle without a spatial assignment to the monitoring unit. A mobile end device, such as a computer,

Mobile phone, tablet computer or the like can be used. The mobile terminal device can easily be carried along by a person to the rail vehicle, in particular to an operating unit, in which case data can then be recorded in situ. The data can be recorded, for example, by image recording, sound recording, image processing, such as text recognition or a code scanner, manual data input, etc.

A computer program can be run with the acquisition unit, with which the data is acquired. For example, it can be provided that a software application is run on the mobile terminal device, with which the data is recorded. The data collection can be automated and/or carried out manually. For example, the mobile end device can also be temporarily connected to the operating unit for data acquisition. As part of data collection, a user can use the software application attributes and Selection lists for data to be recorded are presented. For example, the Year of Construction attribute with a selection of year numbers.

As an alternative or in addition, a sensor device arranged in a stationary manner on the respective operating unit or the rail vehicle and a transmission device can be used as a detection unit. The sensor device can then, for example, comprise a sensor with which a function of the relevant operating unit and an operating time can be determined. The transmission device can then transmit data sets to the monitoring unit, for example a type designation of the operating unit, a value determined with the sensor and the operating time. For this purpose, the transmission device then assigns the data recorded for the sensor to the corresponding attributes. Provision can also be made for data records that are transmitted, such as a serial number or a year of construction, to already be stored in the transmission device.

A detection time can be determined by the detection unit and a spatial position of the respective operating unit can be determined by means of a position sensor of the detection unit. The time of acquisition and the location can also be stored as a data record in the database. The spatial position can determine a position of the rail vehicle or the relevant operating unit, for example via satellite navigation. Among other things, it can be determined at which point on a route a specific data set was recorded. In this way, the location in question can be assigned to an event or to the data records recorded at this point in time. From the pattern analysis, correlations between the location, the time of detection and, if applicable, errors of the operating units can then also result, for example. For example, a comparatively increased wear or a certain error in the operating unit can then be assigned to a season or a route. A data connection can be formed between a user unit of the monitoring system and the monitoring unit, in which case the result of the pattern analysis can be transmitted to the user unit and output. The surveillance system may include one or a plurality of user units that are spatially spaced apart from each other. The data connection or data connections to the respective user units can be established via an external data network. The user unit can be a computer that is independent of the monitoring unit. This computer can be a stationary computer, a mobile radio device or the like, with which the data connection for data exchange with the monitoring unit can be established. The data can be exchanged, for example, via an external data network such as the Internet. In this way, data processed with the evaluation device can be made available to an extended group of users via the output device. the

The output device can be formed, for example, by a server with a software application that transmits the results calculated by the evaluation device and the information contained in the database to the respective user unit. This transmission can be done by providing a website with selected information, for example an up-to-date overview of an inventory of operating units and rail vehicles. The information can be made available to companies operating rail vehicles in an individually adapted manner. External input into the monitoring unit allows the data records stored in the database to be supplemented with further data specific to the respective operating unit. If necessary, it is possible to assign additional data specific to the relevant operating unit to a type of operating unit, for example on the basis of a type designation or a serial number. This data can come, among other things, from a manufacturer of the operating unit who has the corresponding data records. For example, it is then only required to record a serial number of an operating unit mounted on a rail vehicle with a registration unit. The serial number can then be transmitted as a data record to the monitoring unit, with the serial number being able to be linked to other data records, for example to a year of construction, an image or performance data of the respective operating unit, by the external input of further data specific to the respective operating unit. The database can thus be supplemented with further data sets without great effort, which enable a more extensive pattern analysis of the data sets contained in the database.

With the acquisition units, data can be repeatedly acquired for the same attributes of an operating unit after a time interval. In order to determine the state of wear of an operating unit in particular, it is advantageous to determine this within a specific time interval or time segment. It is thus possible, for example, to determine wear over a period of use or a distance traveled by the rail vehicle. As a result of the repeated data acquisition, the database can also be updated to such an extent that it is continuously adapted to a vehicle stock or stock of operating units.

Consequently, the pattern analysis can be performed based on the data sets repeatedly stored over a period of time. It is then also possible to use the pattern analysis or a repetition of the pattern analysis to check whether changes to rail vehicles or operating units have been successful.

The evaluation device can carry out a comparison of data from different attributes for operating units and/or carry out a comparison of data from several attributes of these operating units for one attribute of the respective operating units. When comparing data from different attributes, it becomes possible to determine a correlation that can be expected, for example a runtime of the vehicle in kilometers and an indication of wear. Based on the comparison, it is now possible to identify the operating units with an exceptionally high level of wear. Alternatively, for an attribute that is comparable or identical in a number of operating units, for example the material of the contact strip, a comparison of all the other attributes of these operating units can then also be carried out. Here, for example, a correlation could be expected with regard to wear. If this is not the case for all operating units, other causes of increased wear can be identified through the comparison. In principle, there are a large number of evaluation options for the data records stored in the database. This evaluation of the data sets can be done randomly by the evaluation device, according to a specification and/or by manual selection by an operator.

Furthermore, the evaluation device can take functional dependencies of the attributes into account in the pattern analysis. A functional dependency can exist, for example, between the running time of the vehicle in kilometers and an indication of wear. During the pattern analysis, the evaluation device can then summarize the relevant data sets in such a way that they are comparable, for example by specifying wear based on a defined number of kilometers or vice versa.

Furthermore, the evaluation device can weight and evaluate the stored data sets with regard to their relevance for wear and tear, it being possible for a result to be output by means of the output device depending on the evaluation by the evaluation device. For example, a measured wear of a contact strip can be stored in the database and the evaluation device can now use the stored running time of the vehicle in kilometers to take this running time into account and assign a calculate expected wear. As a result, the output device can then output, for example, wear and tear on the contact strip with a percentage and/or an expected time for replacing the contact strip.

The evaluation device can in each case derive a key figure from the pattern analysis for structural attributes of the operating unit. The code can be used to illustrate the structural properties of the operating units. The key figure can, for example, be an indication of a wear percentage. The key figure can be a relative, dimensionless number that reflects the relevance of an attribute, for example wear and tear.

The evaluation device can carry out a statistical evaluation of the data for attributes. Data can be cleaned up during the static evaluation of the data. For example, it can be provided that only data within a data area is evaluated. Mean values, clusters, percentiles,

Trends, predictions, or the like are calculated by means of the evaluation device. In addition, it is possible to assign attributes related to costs to the operating units. As a result, the costs incurred during operation can be taken into account in the sample analysis. For example, it will then also be possible to identify an operating unit with comparatively high costs and also to make predictions about costs.

The evaluation device can derive a strategy for maintenance and/or inspection of the respective operating unit from the pattern analysis. The strategy can then be based, for example, on a pattern of wear and tear on a collector shoe or other structural components of the operating units. A change in use, for example due to a change in an operating condition of the relevant operating unit, can then lead to the evaluation device adapting the strategy to the changed use. This will make it it is not necessary to adapt or program the evaluation device manually, since it can always use a strategy for maintenance and/or inspection of the respective operating unit that is optimized for a change in use. The evaluation device can then bring forward or delay a point in time for maintenance of an operating unit.

The evaluation device can derive the strategy using artificial intelligence. Artificial intelligence is understood here to mean automating the calculation of times for maintenance and/or inspection of the respective operating unit. The evaluation device is consequently programmed in such a way that it can independently adapt to a changed use of the respective operating unit.

The monitoring system may include the operating units. Consequently, the monitoring system can comprise a large number of operating units whose data are stored as data records in the monitoring unit's database. These operating units can be connected to the monitoring unit via the detection units with respective data connections.

The invention is explained in more detail below with reference to the drawings. 1 shows a schematic representation of a monitoring system with a rail vehicle;

2 shows a flowchart for carrying out the method.

1 shows a schematic representation of a monitoring system 10 together with a rail vehicle 11. The rail vehicle runs on a track 12 and has pantographs 13 on a roof 14 of the rail vehicle 11, which can be contacted with a contact wire 15. The pantographs 13 represent operating units 16 and 17 of the rail vehicle 11. The monitoring system 10 includes a plurality of detection units 18 and 19 and a monitoring unit 20. The monitoring unit 20 in turn includes a database 21, an evaluation device 22 and an output device 23. The monitoring unit 20 receives data records from the detection units 18 and 19 and stores these in the database 21. The data records are formed from attributes and data associated with them. The data is recorded via the recording units 18 and 19 and assigned to the attributes. The data records stored in the database 21 are processed by the evaluation device 22, with the evaluation device 22 relating the stored data records of the respective operating units 16 and 17 to one another and carrying out a pattern analysis of the data records, with a result of the pattern analysis being output by the output device 23 . The detection unit 18 is a mobile terminal 24 which can be handled by one person. For example, images of the operating unit 16 can be recorded with the mobile terminal device 24 . The mobile terminal 24 can be used regardless of the location of the rail vehicle 11 and can also be used for data acquisition on other rail vehicles or operating units.

The detection unit 19 consists of a sensor device 25 and a transmission device 26 . The sensor device 25 is arranged on the operating unit 17 and is directly connected to the transmission device 26 via a data connection 27 . The detection unit 19 is thus positioned or attached directly to the rail vehicle 11 . With the sensor device 25, data are recorded at the operating unit 17 and these data are processed by the transmission device 26 in such a way that they are assigned at least one attribute. The detection unit 18 and the detection unit 19 now transmit data sets or data on a plurality of attributes to the Monitoring unit 20. This transmission takes place via an external data network 28 and data connections 29, 30 and 31 by means of which the data sets are transmitted via radio signals. The output device 23 is connected to the external data network 28 via a further data connection 32 in such a way that results output by the monitoring unit 20 can also be transmitted via the external data network 28 . In principle, a connection between the monitoring unit 20 and the external data network 28 via a single data connection is possible and sufficient here. Output results can be received and displayed by the user unit 34 via a data connection 33 of a user unit 34 to the external data network 28 . Optionally, it is also possible to exchange data or datasets directly between the detection units 18 and 19, the monitoring unit 20 and the user unit 34 via the external data network 28 . Furthermore, results can also be transmitted from the monitoring unit 20 to the detection units 18 and 19 via the external data network 28 . The detection unit 19 can be connected to a driver's cab 26 of the rail vehicle 11 via a data connection 35 such that the results and/or measured values of the sensor device 25 can be displayed to a vehicle driver in the driver's cab 36 .

FIG. 2 shows an example of a method sequence of the method for monitoring rail vehicles. In a first method step 41, field data or data from the operating units of rail vehicles (not shown here) are recorded by means of a plurality of recording units (also not shown). In a second method step 42, data sets formed from attributes and data are transmitted from the detection units to a database of a monitoring unit, also not shown here, via an external network or radio network. In a third method step 43, the data sets are stored in the database. In a fourth step 44, the data records an evaluation device transmits to the monitoring unit and/or the method steps 41 to 43 are repeated immediately or at different times after or before the data sets are forwarded to the evaluation device. In a fifth method step 45, the evaluation device processes the data records contained in the database, with the evaluation device relating the stored data records of the respective operating units to one another and carrying out a pattern analysis of the data records, with a result of the pattern analysis being transmitted to an output device of the monitoring unit in a sixth method step 46 is issued.

Claims

patent claims

1. Method for monitoring rail vehicles (11), in particular operating units (16, 17) of the rail vehicles, such as pantographs (13), grounding contacts, lubricating devices, collector strips, grinding devices, contact brushes, grounding brushes or the like, with detection units (18, 19 ) of a monitoring system (10) for various attributes of the respective operating units in each case data is recorded and assigned to the attributes, with data records formed from attributes and data being transmitted to a monitoring unit (20) of the monitoring system with the recording units, the data records in stored in a database (21) of the monitoring unit and processed with an evaluation device (21) of the monitoring unit, the evaluation device relating the stored data sets of the respective operating units to one another and carrying out a pattern analysis of the data sets, with a result of the pattern analysis is issued with an output device (23) of the monitoring unit.

2. The method according to claim 1, characterized in that that at least two mutually different attributes of an operating unit (16, 17) are used, with the attributes from the attribute types type, identification, year of construction, vehicle, use, running time, material, wear and tear, errors, damage, location, image, sound, detection time or the like, the operation unit can be selected.

3. The method according to claim 1 or 2, characterized in that the detection units (18, 19) transmit the data to the monitoring unit (20) via a respective data connection (29, 30, 31).

4. The method according to claim 3, characterized in that the data connection (29, 30, 31, 32, 33) is formed via an external data network (28).

5. The method according to any one of the preceding claims, characterized in that a mobile terminal (24), such as a computer, mobile phone, tablet computer or the like, is used as a detection unit (18, 19).

6. The method according to any one of the preceding claims, characterized in that the acquisition unit (18, 19) executes a computer program with which the data is acquired.

7. The method according to any one of the preceding claims, characterized in that as a detection unit (18, 19) at the respective loading drive unit (16, 17) or the rail vehicle (11) stationarily arranged sensor device (25) and a transmission device (26) can be used.

8. The method according to any one of the preceding claims, characterized in that a detection time is determined by the detection unit (18, 19) and a location of the respective operating unit (16, 17) is determined by means of a position sensor of the detection unit.

9. The method according to any one of the preceding claims, characterized g e k e n n z e i c h n et that between a user unit (34) of the monitoring system (10) and the monitoring unit (20) a data connection (32,

33) is formed, with the result of the pattern analysis being transmitted to the user unit and output.

10. The method according to any one of the preceding claims, characterized in that the data records stored in the database (21) are supplemented with further data specific to the respective operating unit (16, 17) by an external input into the monitoring unit (20).

11. The method as claimed in one of the preceding claims, characterized in that data are repeatedly recorded with the recording units (18, 19) for the same attributes of an operating unit (16, 17) after a time interval.

12. The method according to any one of the preceding claims, characterized in that that the pattern analysis is carried out on the basis of the data sets stored repeatedly over a period of time.

13. The method as claimed in one of the preceding claims, characterized in that the evaluation device (22) carries out a comparison of data from different attributes for operating units (16, 17) and/or a comparison of data from other ones for an attribute of the respective operating units attributes of these operating units.

14. The method according to any one of the preceding claims, characterized in that the evaluation device (22) takes functional dependencies of the attributes into account in the pattern analysis.

15. The method according to any one of the preceding claims, characterized in that the evaluation device (22) weights and evaluates the stored data sets in terms of their relevance to wear, with a result being output by means of the output device (23) depending on the evaluation by the Evaluation device takes place.

16. The method according to any one of the preceding claims, characterized in that the evaluation device (22) derives a code number from the pattern analysis for structural attributes of the operating unit (16, 17).

17. The method according to any one of the preceding claims, characterized in that the evaluation device (22) carries out a statistical evaluation of the data for attributes.

18. Method according to one of the preceding claims, characterized in that the evaluation device (22) derives a strategy for maintenance and/or inspection of the respective operating unit (16, 17) from the pattern analysis.

19. The method according to claim 18, characterized in that the evaluation device (22) derives the strategy by means of artificial intelligence.

20. The method according to any one of the preceding claims, characterized in that the monitoring system (10) comprises the operating units (16, 17).