WO2020173646A1

WO2020173646A1 - Device and method for ascertaining acoustic events in a track using acoustic sensors

Info

Publication number: WO2020173646A1
Application number: PCT/EP2020/052102
Authority: WO
Inventors: Dietmar SCHÜTZ; Boris CELAN
Original assignee: Siemens Mobility GmbH
Priority date: 2019-02-28
Filing date: 2020-01-29
Publication date: 2020-09-03
Also published as: DE102019202738A1

Abstract

The invention relates to a method for locating an acoustic event in a track 11. In the method, a measuring point 14 on the track is used in order to capture sound conducted through the track section 12 via sensors SEN. The sound characteristic can be used to ascertain defects in the track 11 for example. In order to detect same, a computer C is provided which can also be connected to a central computer GZ. According to the invention, longitudinal waves and transverse waves of the sound being conducted through the track are detected using the sensor. In this manner, a distance measurement of the acoustic event is made possible advantageously using only one sensor because during the propagation of longitudinal waves and transverse waves, a transit time difference results which becomes greater as the distance to the acoustic event increases. The invention also relates to a measuring point by means of which the method according to the invention can be carried out.

Description

description

Device and method for the determination of acoustic events by means of sound sensors in the track

The invention relates to a method for localizing an acoustic event in a track, in which at a measuring point located on the track with at least one sound-sensitive sensor the acoustic sound conducted through the track

Event is detected and a sensor signal generated by the sensor is output. The invention also relates to a measuring point for mounting on a track, for localizing an acoustic event in the track,

with at least one sound-sensitive sensor through which the sound of the acoustic event conducted through the track can be detected, and with an interface through which a sensor signal generated by the sensor can be output.

In rail-bound rail traffic, in addition to the rolling stock, the condition of the tracks in particular is of crucial importance for smooth, trouble-free and ultimately safe operation. Here the problem arises of how to assess the condition of the track structure or how to recognize changes to the track structure and the associated dangers. Complex influencing factors on the condition of the tracks must be taken into account, such as the loads occurring during operation or their consequences.

According to US 5743495 it is described that for detection

For example, vibration detectors can be provided for broken rails on the track, which detect the vibrations generated in the track by moving trains. Rail breaks can be detected with this method, since the transmission of vibrations beyond a broken rail is only reduced or not possible at all. A broken rail can therefore be determined by suitable evaluation of the sensor signals, with a large number of Sensors must be attached to the tracks of the track. The sensor signals are processed by a central processor

evaluated, which can determine the presence of a broken rail, with sensor signals from sensors being evaluated which are located on both sides of the broken rail (i.e. in front of or behind the broken rail).

The challenge lies in the timely detection and localization of damage in order to avoid accidents and operational restrictions by means of preventive maintenance

Minimize maintenance costs. At the same time, the effort required to localize the damage should be kept as low as possible.

The object of the invention is therefore to provide a method for localizing an acoustic event in a track by means of sound-sensitive sensors, with which the localization can take place reliably and inexpensively. It is also an object of the invention to specify a measuring point with which such a method can be carried out.

According to the invention, this object is achieved with the initially specified subject matter (method) in that

• The at least one sensor detects both longitudinal waves and transverse waves of the sound conducted through the track,

• from the transit time difference between the detected ones

Longitudinal waves and transverse waves a distance of the acoustic event from the measuring point (preferably computer-aided) can be calculated.

The invention makes use of the fact that

Longitudinal waves of an acoustic event spread faster in the track than transverse waves. While longitudinal waves in steel have a speed of sound of approx. 5900 m / s, the speed of sound in transverse waves is approx. 3200 m / s. In a solid medium such as the rail track, acoustic Events always simultaneous longitudinal waves and

Transverse waves. Since these are emitted at the same time from the location of the acoustic event, the difference in time between the two wave fronts increases with increasing distance from the acoustic event due to the different speeds of sound. The distance of the acoustic event can therefore be deduced from the difference in transit time of the measurement signal at the measurement point.

It is thus advantageously possible to determine the transit time difference with a single sensor. Since the frequency of the longitudinal waves and the transverse waves corresponds to the acoustic event and is therefore the same, the sensor needs one

Sensitivity in only one frequency range in which the acoustic event can be easily measured. This is advantageous

inexpensive implementation of the process possible. This is not only due to the reduction in the number of sensors required, but also to the fact that the measuring point can be installed as a unit on the track, so that installation work and, subsequently, maintenance work can be saved. The security against failure of the method is also increased, since fewer components also result in a lower susceptibility to failure.

The acoustic events are primarily triggered by trains traveling on the track. There is therefore no need for a sound generator to generate a signal. This means that the acoustic event must be examined to see whether it has anomalies that indicate damage. The damage is thus as

To understand the source of the error for the acoustic event.

The acoustic events can be through different

Sources of error are influenced. These consist, for example, of wear and tear or damage to the running surface of the track

(Rail head and flank) or from developing structural weaknesses or damage (beginning or emergent

Broken track, loose screw connections on sleepers or on Joints). In addition, external events can occur that affect the integrity of the rail track, e.g.

Rock falls / rockfalls, landslides, consequences of accidents, but also targeted terrorist attacks on the infrastructure. The detection of damage in the track makes it possible to initiate maintenance measures or repairs of the rail network before a final failure or an accident occurs.

Furthermore, the acoustic event can also be influenced by the moving train itself. In this way, sources of error can also be detected that are generated, for example, by defective train wheels. If these are recognized, it is thus also possible to determine the wear and tear on the rolling stock and, if necessary, from this

Derive maintenance measures. The sensor can also be used to implement an axle counting function.

Different types of damage on the track cause defined ones

Changes to the sound signal, and are thus recognizable. Examples are:

• Beginning or existing rail breaks make it more difficult for the sound to be transmitted along the rails. They can be recognized by sudden increases when crossing or by comparing them with the neighboring strand.

• Slip waves or ripples generate a rhythmic stimulation with every crossing, possibly better recognizable with external knowledge of the train composition (from a dispatch system) and its speed (from the safety system or

Operations Management System)

• Singular impressions of the surface or squats reveal themselves through recurring patterns, triggered by each axis when the train passes over.

The analysis of the sound signals also allows the detection of typical operating scenarios which, in contrast to normal travel, represent a particular burden on the rail, e.g. B. sanding when braking on slippery surfaces, or particularly strong Braking with possibly locking wheels. Conclusions about the axle loads can also be drawn by evaluating the frequency components. With this information, a cumulative determination of the load on the rail track is possible. Such events are revealed by means of thorough signal analysis.

Sound events that are not related to a train crossing, i.e. have an external cause, can also be evaluated. Examples are:

• Direct manipulations on the track cause a lot of noise due to the material.

• Natural events such as rockfalls, landslides,

Track bed lowering, but also accidents with effects on the track bed, generate a lot of energy, which results in sound, and possibly also a strong change in the

Transmission behavior causes.

• Deliberate feeding of a warning signal about

corresponding mobile devices (rotten warning device) or by makeshift attacks.

The evaluation of the sensor signals is advantageously carried out with the aid of a computer. This is connected to an interface of the sensor so that it can receive the sensor signals. It is also advantageous if the computer can access a database or can feed this database with data (more on this below). The database is implemented by a storage unit.

The term "computer" is to be interpreted broadly to include all electronic devices with computing capabilities. Computers can thus, for example, be personal computers, servers,

Handheld computer systems, pocket PC devices, mobile radio devices and other communication devices that can process data with the aid of computers, processors and other electronic devices for

Be data processing, which can preferably also be connected to a network. In connection with the invention, “computer-aided” can be understood to mean, for example, an implementation of the method in which one or more computers executes or executes at least one method step of the method.

In connection with the invention, a “processor” can be understood to mean, for example, a machine or an electronic circuit. A processor can in particular be a central processing unit (CPU), a microprocessor or a microcontroller, for example an application-specific integrated circuit or a digital signal processor, possibly in combination with a

Act as a storage unit for storing program instructions, etc. A processor can also be, for example, an IC (integrated circuit), in particular an FPGA (field programmable gate array) or an ASIC (application-specific integrated circuit).

Application-Specific Integrated Circuit), or a DSP (Digital Signal Processor). A processor can also be understood to be a virtualized processor or a soft CPU. For example, it can also be a programmable processor that is equipped with a configuration for carrying out the aforementioned method according to the invention.

In connection with the invention, a “memory unit” can for example be a computer-readable memory in the form of a

Random-Access Memory (RAM) or a hard disk.

According to one embodiment of the invention it is provided that in addition to the transit time difference, a signal characteristic of the

Longitudinal waves and / or the transverse waves are taken into account. In this way, additional knowledge can advantageously be obtained for the measurement result, as will be explained in more detail below. According to one embodiment of the invention, it is provided that the signal characteristic (preferably computer-aided) are compared with entries in a database, the entries being a

Allow conclusions to be drawn about the distance of the acoustic event from the sensor.

It has been shown to be advantageous that the

The signal characteristic also changes depending on the duration of the acoustic signal. These changes can be evaluated with a view to the distance covered by the acoustic signal and thus result in additional distance information. The longitudinal waves and / or the transverse waves can be used here. The distance information that can be derived according to this embodiment of the method according to the invention can be compared with the information that is based on

The difference in runtime of the different wave types has been determined. In the event of deviations, further examinations can then be initiated, which advantageously makes the method less error-prone.

The signal characteristic can be given, for example, by the frequency response of the acoustic signals generated by the acoustic event. These can, for example, be a

Fourier transform, this being the case for the

Longitudinal waves and the transverse waves can be done separately. For example, the fact that higher-frequency signal components send ahead faster with increasing distance than low-frequency signal components can be used. This fact can easily be determined by means of a Fourier transformation of the signal.

According to one embodiment of the invention it is provided that the signal characteristic of the longitudinal waves and / or the

Transverse waves are compared with entries in a database, the entries allowing a conclusion about the type of acoustic event. The acoustic event is initially the cause of certain signal characteristics that can also be typified based on different groups of acoustic events. For the detection of certain events it is therefore helpful that the

Runtime comparison also evaluates the characteristics of the signal. In this way, events can also be recognized qualitatively, which should not occur on the monitored track per se (a rockfall is different from a broken track, for example). Even if previously unknown events are detected, security measures can be taken if a malfunction is suspected.

According to one embodiment of the invention it is provided that a computer program is used, wherein

• The computer program has access to a database with typed signal characteristics, which consist of typical acoustic

Events result, has,

• this computer program is used to compute route-specific signal characteristics and / or time-specific changes in the sensor signals from the sensor signals

route-specific signal characteristics from the

to derive typed signal characteristics.

The signals are preferably determined and analyzed

continuously. From the results, a database for all route sections (route-specific) with their peculiarities can be built up or "learned" during operation. Continuous monitoring also makes it possible to detect a change in the route-specific signal characteristics over time (time-specific change); this can be caused, for example, by wear and tear on the track. To determine the route-specific signal characteristics and their

Time-specific changes, the computer program is programmed so that it implements an artificial intelligence. In addition, findings from measurement drives should also be included. Measurement drives are carried out in a manner known per se

Rail vehicles carried out that drive on the tracks and can take measurements. These measurements can be used in particular to generate database entries and typed

Signal characteristics are used. The sensors according to the invention can of course also be used to generate this data. This better guarantees comparability with later measurements.

The resulting database then serves as a basis for comparison to identify anomalies or long-term ones

Recognize changes. The route-specific signal characteristics obtained can also advantageously be stored as standardized signal characteristics if these are recognized as typical cases or typical developments. For this purpose, however, as will be explained in more detail below, additional data must be used.

According to one embodiment of the invention, it is provided that the sensor signals (preferably computer-aided) are compared with data from the current ferry operation and / or data from the route plan.

The current ferry service results from the timetable and any deviations from this timetable. Knowing the current ferry operation allows, for example, to assign the acoustic events to specific trains. This facilitates the comparison with typified signal characteristics of certain acoustic signals

Events. In addition, knowing the timetable makes it possible to determine in a simple manner the direction from which the acoustic event is coming if one has knowledge of where the moving train is and, consequently, where the acoustic signal is generated.

A comparison with the route map is also an advantage.

For example, the propagation of acoustic signals is controlled by the Course of the route influenced. This also facilitates the comparison with standardized signal characteristics, for example

Routes such as curves or certain track beds can be assigned.

According to one embodiment of the invention it is provided that the computer program is used

to generate computer-aided entries in the database from route-specific signal characteristics.

As already explained, through the knowledge of route plans or the current train operation, additional information can be evaluated, which advantageously also enables new, standardized information

To recognize signal characteristics. Are different

For example, the signal characteristics of passenger trains already recorded by those who generate freight trains, those of freight trains can also be stored as standardized signal characteristics. In this way, the database is expanded, and algorithms of the computer program that ensure its artificial intelligence can expand the database in a self-learning manner.

According to one embodiment of the invention it is provided that the measuring point has two sensors, which with respect to the

Track course are arranged one behind the other, due to the time difference between the sensors generated by these

Sensor signals the direction (preferably computer-aided) is determined from which the longitudinal waves and / or the transverse waves have come.

By arranging two sensors in one measuring point, it is advantageously possible to expand the method in the measuring point in such a way that, in addition to a run time comparison for the purpose of distance measurement, a run time comparison can also be made for the purpose of determining the direction of the acoustic event. Since the track extends in both directions from the measuring point, A distance measurement is not sufficient for the unambiguous localization of the acoustic event.

The direction in which the acoustic event is located is also determined using a transit time comparison. However, this requires the two sensors, which are arranged one behind the other when viewed in the direction of the track (track course). These detect the relevant acoustic signal (which was triggered by the acoustic event) in quick succession, so that the acoustic signal comes from the direction in which the sensor is located that was the first to detect the acoustic signal. With a distance of the two sensors of, for example, 30 cm, there are already differences in transit time in the microsecond range, which can be recorded with modern measurement technology.

According to one embodiment of the invention it is provided that a network of measuring points is used, whereby due to the

Time difference between the two measuring points generated sensor signals the (preferably computer-aided) direction is determined from which the longitudinal waves and / or the transverse waves came.

According to this embodiment, the fact is advantageously used that, given the presence of sensor networks, two preferably neighboring measuring points can be used to determine the direction from which the sound triggered by the acoustic event comes. If, for example, the measuring points are 5 km apart, location-related differences in transit time of the signal belonging to the acoustic event result in the range of seconds.

At the same time, a change in the signal characteristic must be taken into account here so that neighboring measuring points can identify the signal in question as the same signal. This can be achieved through the self-learning execution of the

Computer program to analyze the signals are guaranteed.

According to one embodiment of the invention, it is provided that the measuring point has sensors on both sections of the track, whereby the generated sensor signals of both tracks are output in parallel.

This embodiment improves the possibility of detecting external influences on the track, which are not caused by trains

be evoked. In this context have already been

examples of manipulations on the track or natural events. In particular, such events generally have an effect not uniformly on both rails, so that differences between the two sides can be used to initiate further analysis. This advantageously gives rise to indicators of a probable danger.

The stated object is alternatively also achieved according to the invention with the subject matter of claim (measuring point) specified at the outset in that

• the at least one sensor can detect both longitudinal waves and transverse waves of the sound conducted through the track,

• from the transit time difference between the detected ones

Longitudinal waves and transverse waves a distance of the acoustic event from the measuring point can be calculated.

The measuring point is therefore advantageously suitable for carrying out the method explained in more detail above. The advantages associated with performing the method are therefore also achieved by the measuring point according to the invention.

According to one embodiment of the invention, it is provided that sensors are attached to each of the two sections of the track.

As already mentioned, external events can advantageously be detected better by using sensors on both strands of the track. In addition, both tracks can be monitored at one and the same measuring point if, for example, wear in curves does not occur symmetrically on both tracks. According to one embodiment of the invention it is provided that the measuring point is provided on a switch, each of the

Switch ends of the switch is equipped with at least one sensor to monitor the tracks leading away from the switch. At the same time, it is also possible to monitor the track bordering the start of the turnout, as this is connected to one end of the turnout or the other end of the turnout in an acoustically conductive manner depending on the position of the turnout.

According to one embodiment of the invention, it is provided that the measuring point is connected to a computer for processing the sensor signals via the interface.

It is particularly advantageous if the computer is provided in the measuring point. This allows the sensor signals to be processed in real-time. In addition, the sensor signals can be reliably transmitted via the interface to the computer, which can preferably be wired. In order to collect the measurement data centrally, a connection, for example a radio link, can also be provided between the computer and another central computer.

The stated object is alternatively also achieved according to the invention with the initially specified subject matter (measuring point network) in that a plurality of measuring points of the type described above are connected to a network, at least one computer for processing the measured data being integrated into the network.

In this case the computer can be a central computer to which all measuring points are connected. This advantageously enables the use of cost-effective measuring points, since these do not have to be equipped with a computer. Alternatively, it is also possible for the measuring points to already pre-process the data with a computer and to carry out the measuring point network

These computers are networked. Finally, it is as above It is also possible that the network of individual computers can also be controlled by a central computer.

Further details of the invention are described below with reference to the drawing. Same or corresponding

Drawing elements are each provided with the same reference numerals and are only explained several times insofar as there are differences between the individual figures.

The exemplary embodiments explained below are preferred embodiments of the invention. Both

Exemplary embodiments, the described components of the embodiments each represent individual features of the invention that are to be considered independently of one another, which also develop the invention independently of one another and are thus also to be regarded as part of the invention individually or in a combination other than the one shown. Furthermore, the described embodiments can also be supplemented by further features of the invention already described.

Show it:

Figure 1 shows an embodiment of the measuring point according to the invention, with which an embodiment of the method according to the invention can be carried out, schematically in section,

Figure 2 shows a switch with further embodiments of the

measuring point according to the invention,

Figure 3 shows another embodiment of the invention

Method illustrated using a further exemplary embodiment of the measuring point according to the invention. According to FIG. 1, a track 11 with two track strings 12 is shown in section, the rail strings being mounted on a rail sleeper 13. A sensor SEN, which is shown schematically in each case, is attached to each of the tracks 12. Both sensors SEN result in a measuring point 14 for acoustic vibrations in the two track sections 12. Not shown, but just as possible, it is that the measuring point extends over only one track section and the other track section is designed without a sensor SEN.

Part of the measuring point 14 is also a computer C, which is connected to the sensors SEN via signal lines 16. The computer C also forms part of the measuring point 14, which is indicated by the dash-dotted line. This enables a decentralized evaluation of the sensor signals in each measuring point by the computer C provided there.

In addition, the computer C is connected to a central computer CZ via a connecting line 17. This central computer is provided for collecting data from different computers C, CI, C2, these computers C, CI, C2 also forming further measuring points with sensors not shown in detail. In this way, the recorded data from different measuring points can be compared.

On the other hand, the central computer CZ is connected to a database DAT. In this database DAT are typed

Signal characteristics are stored, which can be compared with the measured signal characteristics on the track for comparison. The comparison can take place both in the central computer CZ and in the local computers CI, C2, in which case these are supplied with the data from the database DAT via the central computer CZ.

In addition, further data can be stored in the database DAT if new signal characteristics arise that have not been recorded before and are recognized as a specific event were. These new events can then also be made available as typed signal characteristics by the database DAT.

It is possible from the measured signal characteristics

to save route-specific signal characteristics for a certain measuring point. With the new typed

Signal characteristics can, on the one hand, be events that have not yet been recorded, e.g. B. a falling rock or the like rolling over the track body. It is also possible, however, to record new, standardized signal characteristics for progressive track wear, so that the track wear can be determined by a corresponding comparison with standardized signal characteristics. A certain operating time of a certain track is necessary for this, since the signs of wear only appear after a certain operating time. These changes in the signal characteristics are also called time-specific changes in the route-specific ones

Signal characteristics called.

In Figure 2, a switch is shown schematically. This has two switch ends 19 and a switch beginning 20. The turnout ends 19 are the branched part of the turnout, while the turnout start 20 represents the single-track part of the turnout, regardless of the direction in which the turnout will travel. The switch tongues 21, which enable the switch to be set in a manner known per se, can also be seen. The position of the switch shown in FIG. 2 is "straight ahead".

It can also be seen that a measuring point 14 is provided at each of the two switch ends 19. At these measuring points, only the SEN sensors attached to both tracks are shown schematically by circles.

The computer C, which processes the sensor signals according to FIG. 1, is not shown in more detail in FIG. In addition, on Switch start 20 provided a further measuring point 14, which is also equipped with two sensors SEN.

Regardless of how the switch is set, two sensors SEN of the switch start 20 can always form a pair with the sensors SEN of the switch end 19, so that the distance between these sensors SEN is used to measure the transit time difference of the signal from one sensor SEN to the other Sensor SEN can be measured. This difference in transit time can be used to determine the direction from which the measured acoustic signal came. At the same time, the equipment of both turnout ends 19 makes it possible to monitor both the one continuing track section and the other away track section.

Another exemplary embodiment of the measuring point 14 is shown in FIG. In addition to the computer C, this measuring point has two sensors SEN1 and SEN2 on one and the same rail track 12, which can, for example, be 30 cm apart. The distance is measured in the longitudinal extent of the track 12. In a manner not shown, sensors can also be attached in the manner just described to the track behind the track shown. These cannot be seen, however, since FIG. 3 is a side view of the track 11.

The computer C is also equipped with an antenna A which communicates with a corresponding antenna A of the central computer CZ with a connected database DAT via a radio interface 22. In this way, measuring points with computers C which are located at a greater distance from the central computer CZ can advantageously be connected to the central computer CZ without the sometimes considerable expense of laying cables. The arrangement of the sensors SEN1 and SEN2 advantageously enable the direction of the received signal to be determined in one and the same measuring point. The distance between the two sensors SEN1 and SEN2 already leads to a measurable difference in transit time of the measured signal. Because of the low Distance of the two sensors SEN1 and SEN2 also ensures that the measured signal does not change significantly on the way between the two sensors SEN1 and SEN2. Because of this, it is particularly easy to recognize the identity of the measured signal in this case.

As an example, various imperfections that could generate acoustic events are shown on track 11. This can be, for example, a welded connection 23, a defect 24 (for example corrugation) on the running surface of the rail track or a boulder 25. While the boulder 25 independently generates an acoustic event when it rolls onto the track 11, the connection 23 and the flaw 24 can only be recognized in a standardized signal characteristic when a rail vehicle 26 rolls over the track. The rolling noise of the wheels 27 of the rail vehicle 26 can be recorded by the sensors SEN1 and SEN2 and is changed by the connection 23 or the defect 24 as soon as this becomes apparent

Rail vehicle 26 is located beyond these anomalies. The acoustic event that is measured is therefore the change in the noises that are generated by the rolling wheels 27.

List of reference symbols

SEN sensor

DAT database

C computer

A antenna

11 track

12 track

13 rail sleeper

14 measuring point

16 signal line

17 connecting cable

18 connecting cable

19 end of point

20 point start

21 switch tongues

22 radio interface

23 Connection

24 defect

25 boulders

26 rail vehicle 27 wheel

Claims

1. A method for localizing an acoustic event in a track (11), in which at a measuring point (14) located on the track (11) with at least one sound-sensitive sensor (SEN) the sound of the acoustic event conducted through the track (11) is detected and a sensor signal generated by the sensor (SEN) is output,

characterized,

that

• by the at least one sensor (SEN) both

Longitudinal waves as well as transverse waves of the sound conducted through the track (11) are detected,

• from the transit time difference between the detected ones

Longitudinal waves and transverse waves a distance of the acoustic event from the measuring point (14) can be calculated.

2. The method according to claim 1,

characterized,

that in addition to the transit time difference, there is also a signal characteristic of the longitudinal waves and / or the transverse waves

be taken into account.

3. The method according to claim 2,

characterized,

that the signal characteristics are compared with entries in a database (DAT), with the entries allowing conclusions to be drawn about the distance of the acoustic event from the sensor (SEN).

4. The method according to any one of the preceding claims,

characterized,

that the signal characteristics of the longitudinal waves and / or the transverse waves are compared with entries in a database (DAT), with the entries allowing conclusions to be drawn about the type of acoustic event.

5. The method according to any one of the preceding claims,

characterized,

that a computer program is used, whereby

• the computer program with access to a database (DAT)

has standardized signal characteristics that result from typical acoustic events,

• this computer program is used to derive route-specific signal characteristics and / or from the sensor signals

time-specific changes to the route-specific

Signal characteristics from the standardized

To derive signal characteristics.

6. The method according to claim 5,

characterized,

that the sensor signals are compared with data from the current ferry operation and / or data from the route map.

7. The method according to claim 5,

characterized,

that the computer program is used,

to generate entries in the database (DAT) from route-specific signal characteristics.

8. The method according to any one of the preceding claims,

characterized,

that the measuring point (14) has two sensors (SEN1, SEN2), which are arranged one behind the other with respect to the track layout, whereby the direction from which the longitudinal waves and / or or the transverse waves have come.

9. The method according to any one of the preceding claims

characterized,

that a network of measuring points (14) is used, generated due to the time difference between the 2 measuring points (14) Sensor signals the direction is determined from which the

Longitudinal waves and / or the transverse waves have come.

10. The method according to any one of the preceding claims,

characterized,

that the measuring point (14) has sensors (SEN) on both track sections (12) of the track (11), the sensor signals generated from both track sections (12) being output in parallel.

11. Measuring point (14)

• for mounting on a track (11),

• to localize an acoustic event in the track (11),

with at least one sound-sensitive sensor through which the sound of the acoustic event conducted through the track (11) can be detected, and with an interface through which a sensor signal generated by the sensor (SEN) can be output,

characterized,

that

• by the at least one sensor (SEN) both

Longitudinal waves as well as transverse waves of the sound conducted through the track (11) can be detected,

• from the transit time difference between the detected ones

12. measuring point (14) according to claim 11,

characterized,

that sensors (SEN) are attached to both tracks (12) of the track (11).

13. measuring point (14) according to one of claims 11 or 12,

characterized,

that the measuring point (14) is provided on a switch, each of the switch ends (19) of the switch, preferably also the Switch start (20) is equipped with at least one sensor (SEN).

14. Measuring point (14) according to one of claims 11 to 13,

characterized,

that the measuring point (14) is connected via the interface to a computer (C) for processing the sensor signals.

15. Measuring point network,

characterized,

that a plurality of measuring points (14) according to one of claims 11 to 14 are connected to form a network, at least one computer (C) for processing the measurement data being integrated into the network.