Method and arrangement for identifying a rail vehicle wheel

Abstract

A method for recognizing a rail vehicle wheel as well as an arrangement for recognizing a rail vehicle wheel. A specific detection pattern of the rail vehicle wheel to be identified is ascertained using rollover signal of a rail vehicle wheel to be identified, which is ascertained with the aid of a load measuring device arranged on a rail, the rollover signal describing a time characteristic of a rail load induced by the rail vehicle wheel to be identified on the rail equipped with the load measuring device during the rollover, and the specific detection pattern comprising one or multiple identification parameter(s)/characteristic value(s) ascertained using the rollover signal. The ascertained specific detection pattern of the rail vehicle wheel to be identified is compared with one or multiple predefined reference-specific detection pattern(s) of rail vehicle wheels, and the rail vehicle wheel to be identified is identified by the comparison.

Claims

1. A method for recognizing a rail vehicle wheel, the method comprising: detecting a rollover of rail vehicle wheels on a load measuring device arranged on a rail; ascertaining a specific detection pattern using a rollover signal of one of the rail vehicle wheels, the specific detection pattern being ascertained via the load measuring device arranged on the rail, the rollover signal describing a time characteristic of a rail load induced by the one of the rail vehicle wheels on the rail equipped with the load-measuring device during the rollover, the ascertained specific detection pattern comprising one or multiple time-independent identification parameter(s)/characteristic value(s) ascertained using the rollover signal; comparing the ascertained specific detection pattern of the one of the rail vehicle wheels with previously stored reference-specific detection patterns associated with the rail vehicle wheels; and recognizing, via the comparison, that the ascertained specific detection pattern of the one of the rail vehicle wheels rolling over the load measuring device corresponds to one of the previously stored reference-specific detection patterns, the one of the previously stored reference-specific detection patterns being associated with a specific rail vehicle wheel of the rail vehicle wheels, such that the one of the rail vehicle wheels rolling over the load measuring device is identified as the specific rail vehicle wheel.

2. The method according to claim 1, wherein the rollover signal is ascertained with the aid of the load-measuring device when the one of the rail vehicle wheels rolls over the rail equipped with the load-measuring device, wherein the load-measuring device is a measuring section that comprises a measuring rail or a measuring tie.

3. The method according to claim 1, wherein the rollover signal is a force, moment and/or acceleration signal.

4. The method according to claim 1, wherein the one or multiple time-independent identification parameter/characteristic value is: a wheel circumference, an imperfection, a roughness or an out-of-roundness; and/or a load pattern as a function of a wheel angle or the wheel circumference; and/or a frequency spectrum, a wavelength spectrum or an amplitude ratio of the load pattern.

5. The method according to claim 1, wherein the ascertained specific detection pattern additionally comprises at least one further time-independent identification parameter/characteristic value ascertained using a further measuring signal.

6. The method according to claim 5, wherein the at least one further time-independent identification parameter/characteristic value is a rate of wear from a transverse profile of the one of the rail vehicle wheels.

7. The method according to claim 1, wherein the previously stored reference-specific detection are stored in a database and/or the previously stored reference-specific detection patterns are updated with the ascertained specific detection pattern of the one of the rail vehicle wheels to be identified in the database.

8. The method according to claim 1, wherein a deviation/tolerance is permitted or taken into account during the comparison.

9. The method according to claim 1, wherein, the method is for a trend tracking of a physical variable of the one of the rail vehicle wheels, wherein the ascertained specific detection pattern of the one of the rail vehicle wheels is ascertained and compared multiple times.

10. The method according to claim 9, wherein the method is for preventive maintenance, and wherein a wheel damage on the one of the rail vehicle wheels identified or to be identified is detected using the trend tracking and/or the multiple comparisons.

11. The method according to claim 1, wherein the method detects an axle of a rail vehicle, a bogie of the rail vehicle and/or the rail vehicle, the ascertained specific detection patterns of multiple rail vehicle wheels to be identified being combined.

12. The method according to claim 11, wherein a position of the one of the rail vehicle wheels to be identified in the rail vehicle is taken into account during the combination.

13. An arrangement for recognizing a rail vehicle wheel, the arrangement comprising: an ascertainment unit configured to carry out the method according to claim 1.

14. The arrangement according to claim 13, further comprising the load measuring device which is configured to ascertain the rollover signal.

15. The arrangement according to claim 13, further comprising a database in which the previously stored reference-specific detection patterns are stored.

16. The method according to claim 4, wherein the imperfection includes a flat spot, the out-of-roundness includes a periodic out-of-roundness, and the load pattern is a phase-adjusted and/or standardized load pattern.

17. The method according to claim 6, wherein the at least one further time-independent identification parameter/characteristic value is a wheel flange thickness, a wheel flange height and/or a flank angle.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

(1) The present invention will become more fully understood from the detailed description given hereinbelow and the accompanying drawings which are given by way of illustration only, and thus, are not limitive of the present invention, and wherein:

(2) FIG. 1 schematically shows the monitoring of a rail traffic or a rail vehicle with the aid of a digital fingerprint formed for the rail vehicle; and

(3) FIG. 2 shows a rollover signal generated by a rail vehicle wheel at different points in time when rolling over a load measuring device arranged on a rail over the circumference of the rail vehicle wheel.

DETAILED DESCRIPTION

(4) FIG. 1 shows a part of a rail vehicle combination 17, made up of multiple rail vehicles 14 (such as cargo and/or passenger cars) (referred to in short only as train 17), which is in traveling mode 18 (as illustrated in FIG. 1), in which it travels in a rail network (made up of tracks having rails 2 arranged side by side) and passes over a rail 2 (from the rail network) multiple times (as also illustrated in FIG. 1).

(5) Each rail vehicle 14 has a front and rear two-axle bogie 15, each of whose axles 16 carries a left and a right rail vehicle wheel 1.

(6) Rail 2, over which train 17 or rail vehicles 14 pass, is equipped with a stationary monitoring system 3, as shown in FIG. 1, the MULTIRAIL WheelScan in this case, which ascertains rail loads 6 acting upon rail 2 by train 17/rail vehicle 14 or by its rail vehicle wheels 1 (when traveling over them, i.e. in traveling mode 18 or during rollover 7).

(7) Monitoring system 3 MULTIRAIL WheelScan represents a measuring section 10 integrated into a rail, i.e. in rail 2 in this case, which includes or is formed by a concrete measuring tie 3 (weighing tie) equipped with measuring sensors or load cells, whose measuring sensors, in particular force sensors (and/or moment sensors), measure rail loads 6, i.e. (vertical) forces F (and moments M) as a result of track guidance forces and weight forces on rail 2.

(8) In other words, stationary monitoring system 3, or MULTIRAIL WheelScan, measures 140 a time- or speed-dependent rollover signal 4 of this type (for example vertical contact force F in this case) for a rail vehicle wheel 1 of a rail vehicle 14 of train 17 rolling thereover 7 (cf. FIG. 2).

(9) As is also shown in FIG. 1, stationary monitoring system 3, or MULTIRAIL WheelScan, is connected to a computing system/computer 51 (ascertainment system 51), which, in turn, has a database 52 (both together hereinafter referred to as MULTIRAIL WheelScan or monitoring system 3).

(10) As is also clarified in FIG. 1, loads 6 measured in this case by MULTIRAIL WheelScan for train 17, i.e. rollover signals 4 of rail vehicle wheels 1, are transmitted to computing system/computer 51 (ascertainment system 51), where an evaluation, for example a wheel diagnosis (detection of wheel imperfections, such as flat spots, roughnesses or out-of-roundnesses), a rail car detection, a distributed load control and a load regulation thereof take place.

(11) To this is now added a trend tracking or a condition monitoring 170 on/of rail vehicles 14 (within the scope of the monitoring of the rail traffic or a rail vehicle 14) to be able to monitor/establish or track a damage development on rail vehicle 14, specifically in this case on a rail vehicle wheel 1 of a rail vehicle 14. By tracking the trend of the specific detection pattern or the digital fingerprint or the associated characteristic values and parameters, a wheel damage may be detected during the course of preventive maintenance, and a wheel failure may be avoided.

(12) For this trend tracking or this condition monitoring 170 on/of rail vehicles 14 or for monitoring/establishing/tracking a damage development on a rail vehicle wheel 1 of a rail vehicle 14 by MULTIRAIL WheelScan, it is necessary to be able to assign rollover signals 4 (measured multiple times at different points in time on measuring section 10 or using MULTIRAIL WheelScan) (and thereby also then the associated evaluations carried out by MULTIRAIL WheelScan, such as the wheel diagnosis (detection of wheel imperfections, such as flat spots, roughnesses and out of-roundnesses)) to a certain rail vehicle wheel 1 of a certain rail vehicle 14.

(13) In other words, an identification of a rail vehicle wheel 1 is necessary or a prerequisite for damage trend tracking/damage condition monitoring 170.

(14) This identification 100 takes place, as illustrated in FIG. 1, in a system-immanent manner, i.e. from existing means, i.e. based on rollover signals 4 of rail vehicle wheel 1, without requiring additional systems (for example numeric identifiers/RFID, using corresponding leading/identification systems).

(15) For this purpose, time-independent identification parameters/characteristic values 8 are formed/ascertained from a rollover signal 4 measured for a rail vehicle wheel 1 in ascertainment unit 51 of MULTIRAIL WheelScan, which are combined 110 into a detection pattern 5 specific to this rail vehicle wheel 1, i.e. a digital fingerprint 5 for this rail vehicle wheel 1. This detection pattern 5 or this digital fingerprint permits a unique identification 100 of rail vehicle wheel 1 later on.

(16) In this case, (a) the wheel circumference of the rail vehicle wheel, (b) a periodic out-of-roundness of the rail vehicle wheel, (c) the load pattern, i.e. vertical force/vertical contact force F, as a function of the wheel angle, and (d) the wavelength spectrum of the load pattern, i.e. vertical force/vertical contact force F, are used as time-independent identification parameters/characteristic values 8 formed from rollover signal 4 and combined into fingerprint 5.

(17) In other words, (a) the wheel circumference of the rail vehicle wheel, (b) a periodic out-of-roundness of the rail vehicle wheel, (c) the load pattern, i.e. vertical force/vertical contact force F, as a function of the wheel angle, and (d) the wavelength spectrum of the load pattern, i.e. vertical force/vertical contact force F, are calculated from rollover signal 4 or vertical contact force F of a rail vehicle wheel 1 (to be identified).

(18) Characteristic values 8 (a) through (d) are then compiled or combined into fingerprint 5 specific to rail vehicle wheel 1 to be identified.

(19) If digital fingerprint 5 (which includes related rollover signal 4 measured by MULTIRAIL WheelScan as well as the evaluations associated with MULTIRAIL WheelScan, including the wheel diagnosis (wheel imperfections, flat spots, roughnesses and out-of-roundnesses)) is thus ascertained 110 for a rail vehicle wheel 1, the latter is compared 120 with, for example (likewise formed) reference fingerprints 9 of already known/recognized or detected rail vehicle wheels stored in database 52, with the aid of ascertainment unit 51.

(20) In other words, a multiplicity of reference fingerprints 9 are stored in database 52, together with the particular MULTIRAIL WheelScan evaluations (among other things, related, associated wheel diagnoses (wheel imperfections, flat spots, roughnesses and out-of-roundnesses).

(21) If comparison 120 of currently ascertained fingerprint 5 and reference fingerprints 9 supply a hit, i.e. if currently ascertained fingerprint 5 matches one of stored reference fingerprints 9, possibly taking into account tolerances, rail vehicle wheel 1 to be identified is thus identified 130.

(22) The comparison between the MULTIRAIL WheelScan evaluations of currently ascertained fingerprint 5 with those of hit fingerprint 9 then provides information on a condition/damage development, for example the development of/change in the wheel imperfections, flat spots, roughnesses and out-of-roundnesses on this, now identified, rail vehicle wheel 1 (trend tracking/condition monitoring 170).

(23) In parallel thereto, the database is updated 160, i.e. stored hit fingerprint 9 and its stored MULTIRAIL WheelScan evaluations are replaced by current fingerprint 5 of recognized or identified rail vehicle wheel 1 and its MULTIRAIL WheelScan evaluations of recognized or identified rail vehicle wheel 1.

(24) FIG. 2 shows an example of time-independent identification parameter/characteristic value 8 (c), i.e. the load pattern, i.e. vertical force/vertical contact force F, as a function of the wheel angle, for one and the same rail vehicle wheel 1 at four different points in time.

(25) In other words, one and the same rail vehicle wheel rolled over 7 MULTIRAIL WheelScan at four different points in time (FIGS. 2a through 2d) (and also once in the opposite rollover direction (FIG. 2d)), digital fingerprint 5 being determined each time, and thus also time-independent identification parameter/characteristic value 8 (c), i.e. the load pattern, i.e. vertical force/vertical contact force F, as a function of the wheel angle. (FIGS. 2a through 2d) The four load patterns were thus able to be recognized by means of identification 100 of rail vehicle wheel 1 and assigned to each other as belonging to this rail vehicle wheel 1.

(26) As shown in FIGS. 2a through 2d, the four load patterns are essentially identical if one takes into account the reversed direction of rotation in FIG. 2d, which results in an opposite rollover direction by rollover 7.

(27) Measuring sections 10 of this type, equipped with MULTIRAIL WheelScan (including computing system/computer 51 (ascertainment unit 51)), may also be arranged multiple times in the rail networkand thus measure (and analyze and identify) rollover signals 4 of rail vehicle wheels 1 multiple times at different points in the rail network during their rollover 7.

(28) If the latter are networked with each other, a continuous matching with databases 52 taking place, trend tracking or condition monitoring 170 may also be expanded locally thereby.

(29) Correspondingly to the recognition or identification 100 of a rail vehicle wheel 1, an identification of an axle 16 of rail vehicle 14, a bogie 15 of rail vehicle 14 and/or rail vehicle 14 may take place, in this case digital fingerprints 5 of multiple rail vehicle wheels 1 to be identified being then combined, i.e. those of an axle 16 of rail vehicle 14, a bogie 15 of rail vehicle 14 and/or rail vehicle 14.

(30) For the recognition or the identification comparison with the one or multiple reference-specific fingerprints 9, corresponding combinations of the one or multiple reference-specific fingerprints 9 may also be formed in database 52.

(31) The comparison 120 itself then takes place as usual between current fingerprint 5 and reference fingerprints 9.

(32) Although the invention was illustrated and described in greater detail by the preferred exemplary embodiments, the invention is not limited by the disclosed examples, and other variations may be derived therefrom without departing from the scope of protection of the invention.

(33) The invention being thus described, it will be obvious that the same may be varied in many ways. Such variations are not to be regarded as a departure from the spirit and scope of the invention, and all such modifications as would be obvious to one skilled in the art are to be included within the scope of the following claims.