NL2027749B1 - A railway monitoring sensor unit - Google Patents
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- NL2027749B1 NL2027749B1 NL2027749A NL2027749A NL2027749B1 NL 2027749 B1 NL2027749 B1 NL 2027749B1 NL 2027749 A NL2027749 A NL 2027749A NL 2027749 A NL2027749 A NL 2027749A NL 2027749 B1 NL2027749 B1 NL 2027749B1
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- 238000012545 processing Methods 0.000 claims abstract description 64
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- 238000012423 maintenance Methods 0.000 description 10
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Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L1/00—Devices along the route controlled by interaction with the vehicle or train
- B61L1/02—Electric devices associated with track, e.g. rail contacts
- B61L1/06—Electric devices associated with track, e.g. rail contacts actuated by deformation of rail; actuated by vibration in rail
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L23/00—Control, warning or like safety means along the route or between vehicles or trains
- B61L23/04—Control, warning or like safety means along the route or between vehicles or trains for monitoring the mechanical state of the route
- B61L23/042—Track changes detection
- B61L23/048—Road bed changes, e.g. road bed erosion
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- Engineering & Computer Science (AREA)
- Mechanical Engineering (AREA)
- Automation & Control Theory (AREA)
- Train Traffic Observation, Control, And Security (AREA)
Abstract
The application describes a railway monitoring sensor unit (300) 5 comprising an IVIEIVIS acceleration sensor (302) generating acceleration signals and, a wireless communication module (310) configured to transmit data to a server for further processing. The railway monitoring sensor unit further comprises a signal processing unit (306) configured for processing the acceleration signals and generating track vibration data for a train passage. The wireless 10 communication module is configured to transmit the track vibration data to the server. Fig. 3
Description
TECHNICAL FIELD The subject disclosure relates to a railway monitoring sensor unit, more particular to a railway monitoring sensor unit configured to measure vertical displacement of a railway line, especially void (in Dutch “blinde vering").
BACKGROUND ART Railway lines are usually supported by sleepers, which rest on a ballast bed consisting of a packed bed of angular stones. Vibration caused by the passage of trains can lead to the development of voids under the sleepers. This is especially the case at locations susceptible to track subsidence, such as transition zones from ballasted track to unballasted track, or at insulated rail joints. When a train passes along the railway track, any such voids will allow vertical movement of the track and so of the train. Where such voids occur under just one end of a sleeper, this may cause the vehicles in the train to tilt or sway, and in extreme cases this can lead to derailment. Furthermore, if the vertical movement is more than about 20 mm, this can impose excessive stresses on the rails, particularly in the vicinity of welts. Accordingly, monitoring the presence and size of such voids is desirable. Similar problems can also arise where the rails are supported by a continuous support structure such as a concrete slab base rather than by conventional ballast, and it should be appreciated that in this specification the term ballast is to be interpreted as meaning the underlying medium that supports the rails, and above which the rails extend.
GB 2420627 discloses an instrument for monitoring vertical movement of a railway line relative to the supporting ballast, referred to as a void meter. The void meter consists of a shaft connected at one end to a clamp such as a magnetic base so it can be clamped onto a rail. An indicator pivots on the shaft, being displaced when a sensing member attached to the shaft is turned, and being held by friction.
JP4338273B2 discloses a track bed subsidence detector is composed of a detector body attached and fixed to the rail bottom portion of the rail and a base portion installed on the track bed. A linear shaft of the detector body is pressed downward by a compression coil spring 35 following the sinking of the base portion. Switches detect the amount of downward movement of the detector body and consequently the amount of subsidence of track bed. CN110126877A discloses a railway track vibration monitoring system comprising a plurality of railway track vibration monitoring nodes. A railway track vibration monitoring node comprises a silicon MEMS based capacitive acceleration sensor and communicates with a backstage monitoring center which analyses received track vibration data in real time. WO2017105451A1 discloses a monitoring and warning system is provided that measures a track displacement as an indication of an operational condition of railway tracks and a rail track structure. The system comprises a sensor and a device coupled to the sensor. In response to a physical measurement of a vertical displacement of a railway track in a down direction by the sensor, the device is configured to provide a warning signal indicative of a possible future failure of the railway track or the rail track structure for proactive track maintenance purposes.
SUMMARY OF INVENTION It is an object of the present subject technology to provide an improved railway monitoring sensor unit which comprises at least one of the following properties: more accurate void measurement and which requires less service maintenance. According to an aspect of the subject technology, this object is achieved by a railway monitoring sensor unit having the features of claim 1. Advantageous embodiments and further ways of carrying out the present technology may be attained by the measures mentioned in the dependent claims. A railway monitoring sensor unit according to the subject technology comprises an MEMS acceleration sensor generating acceleration signals and, a wireless communication module configured to transmit data to a server for further processing. The railway monitoring sensor unit further comprises a signal processing unit configured for processing the acceleration signals and generating track vibration data. The wireless communication module is configured to transmit the track vibration data to the server.
The concept of the present technology is based on the need of a railway monitoring sensor unit that accurately measures the vertical movement of a rail and the void below said rail due to passing trains, and that requires less service maintenance.
This object is reached by processing the acceleration data from a MEMS acceleration sensor internally in the railway monitoring sensor unit and transmitting only the measured vertical movement data wirelessly, rather than the raw acceleration data from an acceleration sensor.
In this way, the amount of data to be transmitted wirelessly is significantly reduced and consequently less energy is needed to transmit the relevant data wirelessly to a server.
If the sensor unit is a stand-alone unit with internal power source, e.g. a battery, the decrease of power consumption increases the lifetime of the battery.
As a result the interval between two service moments is increased, which reduces the number of potential dangerous moments a service technician has to work on the railway track.
Furthermore, by using a MEMS acceleration sensor, no mechanical moving parts are needed to measure the vertical displacement of the rail.
This makes the sensor unit almost impervious to wear and tear and contamination.
This also reduces the moments of service maintenance of the sensor unit.
In an embodiment of the invention, the signal processing unit is configured to generate a set of track vibration data from acceleration signals corresponding to a train passage.
This feature makes it possible to further reduce energy consumption because the sensor unit only sends data from periods with significant vertical displacement of the rail and not from time periods without significant vertical movement.
In a further embodiment, the set of track vibration data includes for each train passage: a time stamp, and at least one of: maximal displacement downward, maximal displacement upward, average displacement downward of wheelsets, average displacement upward of the wheelsets, maximal swing caused by a wheelset, average swing caused by the wheelsets.
By only transmitting information that is used by the server and maintenance software, the amount of data to be transmitted wirelessly can be further reduced.
In an embodiment, the railway monitoring sensor unit is configured to repeatedly collect a number of N sets of track vibration data and to transmit the N sets of track vibration data in one transmission session to the server.
By transmitting sets of track vibration data in a batch, the energy needed to transmit the data can be further reduced. In an embodiment, the railway monitoring unit further comprises a moving train detector configured for detecting a moving train on the railway in vicinity of the sensor unit and generating a presence detection signal indicative for the presence of a moving train in vicinity of the sensor unit; and a controller to wake-up the signal processing unit in response to the detection signal. By having the signal processing unit in sleep mode when there is no train in the vicinity of the void measuring point which comprises a railway monitoring sensor unit, the power consumption can be further reduced.
In a further embodiment, the moving train detector comprises a low- power MEMS acceleration sensor generating acceleration signals, and a processor configured to derive the presence detection signal from the acceleration signals generated by the low-power MEMS acceleration sensor. By using a low- power MEMS acceleration sensor for detecting a moving train in vicinity of the measuring point on the railway and a low-noise MEMS accelerometer which consumes more power and generates acceleration signals to be processed by the signal processing unit, the power consumption can be further reduced.
In an alternative embodiment, the presence detection signal indicates the presence of a moving train in vicinity of the railway monitoring sensor unit when the acceleration signals have an amplitude exceeding a first threshold value. By using only the acceleration and not the displacement, no processing power is needed to determine whether a moving train is in vicinity of the measuring point.
In an alternative embodiment, the signal processing unit is further configured for determining a time instant corresponding to the moment that a train has passed, and configured to derive track vibration data from acceleration signals retrieved after wake-up of the signal processing unit until the time instant. This feature allows reducing the processing time of the signal processing unit and consequently the power consumption of the railway monitoring sensor unit.
In a further embodiment, the signal processing unit is configured to detect that a train has passed when the amplitude of the acceleration signals drops below a second threshold value on times defined by a time profile. By using a simple algorithm to detect the end of a train passage, less power is needed to determine corresponding moment in time.
In an embodiment, the railway monitoring sensor is configured to switch to low-power mode after transmission of track vibration data of a train passage to the server and optionally after generation of track vibration data of a train passage. This feature keeps energy consumption to a minimum.
5 In an embodiment, the processing unit is configured to skip after the generation of track vibration data of a train passage the processing of acceleration signals to derive track vibration data for a predefined number of train passages, a predefined time period or a combination thereof. As void below a sleeper increases relative slowly, not every train passage has to be measured. This feature reduces the power consumption of the sensor unit.
In an embodiment, the MEMS acceleration sensor is configured to generate a bandpass filtered digital acceleration signals; the signal processing unit is configured to: - noise filter the bandpass filtered digital acceleration signals to obtain a filtered acceleration signal, - integrating the filtered acceleration signal to obtain a raw velocity signal; - noise filtering the raw velocity signal to obtain a filtered velocity signal; - integrating the filtered velocity signal to obtain a displacement signal; - analysing the displacement signal to obtain the track vibration data. With these process steps running on a signal processor, the vertical displacement of the track can be accurately determined.
In a further embodiment, analysing comprises: - determining for each wheelset of the train at least one of the following characteristics: maximal displacement downward, maximal displacement upward and sum of maximal displacement downward, maximal displacement upward to obtain wheelset data. In a further embodiment, analysing further comprises: - determining from the wheelset data maximal displacement downward, maximal displacement upward, average displacement downward of wheelsets, average displacement upward of the wheelsets, maximal swing caused by a wheelset, average swing caused by the wheelsets. By determining internally a characteristic for each wheelset and not characteristics for only whole train passage, a multitude of maintenance strategies can be applied to determine when a ballast bed requires maintenance. From, the measured characteristics of each wheelset a desired set of track vibration data is assembled to reduce the amount of data to be transmitted wirelessly to the server.
In an embodiment, the wireless communication module is a LPWAN transceiver. Such a transceiver is very energy efficient.
In an embodiment, the railway monitoring sensor unit comprises a battery to power the MEMS acceleration sensor, the signal processing unit and wireless communication module. In this way damage to powerlines is eliminated.
In an embodiment, the railway monitoring sensor unit comprises a coupling structure to affix the railway monitoring sensor unit to a rail. In a further embodiment, the coupling structure includes a magnet. The coupling structure enables the sensor unit to be firmly attached to a rail or sleeper. A magnet allows the sensor unit to be easily and detachably fixed to an iron rail.
BRIEF DESCRIPTION OF THE DRAWINGS These and other aspects, properties and advantages will be explained hereinafter based on the following description with reference to the drawings, wherein like reference numerals denote like or comparable parts, and in which: Fig. 1 illustrates a railway monitoring system provided with displacement sensor units; Fig. 2 illustrates the overall process of a railway monitoring system; Fig. 3 shows a block diagram of an embodiment of railway monitoring sensor unit in accordance with the present subject technology; Fig. 4 illustrates the principle of void; Fig. 5a is a graph showing a raw acceleration signal of a train passage as generated in sensor unit in accordance with the subject technology over time; Fig. 5b is a graph showing a filtered acceleration signal of a train passage as calculated in a sensor unit in accordance with the subject technology over time; Fig. 5c is a graph showing a raw velocity signal of a train passage as calculated in a sensor unit in accordance with the subject technology over time;
Fig. 5d is a graph showing a filtered velocity signal as calculated in a sensor unit in accordance with the subject technology over time; and, Fig. 5e is a graph showing a raw deflection signal as calculated in a sensor unit in accordance with the subject technology over time.
DESCRIPTION OF EMBODIMENTS Fig. 1 illustrates a railway monitoring system provided with railway monitoring sensor unit 110. The railway monitoring sensor unit is coupled to a railway 100 and is configured to measure vertical displacement of the rails and/or when a train passes a location where the sensor unit is firmly attached to the railway. The sensor unit 110 comprises a coupling structure to affix the sensor unit to the rail 104 or to a sleeper 102. A strong magnet, glue or mounting adhesive may be used to affix the sensor unit to the rail, e.g. to the web of a rail. A rail comprises a head, a foot and a web between the head and the foot. In an alternative embodiment the coupling structure comprises through holes in a housing of the sensor unit. By means of a screw coupling and/or bold and nut coupling the displacement sensor unit may be affixed to the rail or sleeper. Fig. 4 illustrates the principle of void. As trains pass over a given location, the wheelsets cause a movement of the rail 104. This is primarily down to flexure of the rail 104, compression of the ballast 402, and voiding 404 between the sleepers 102 and the ballast 402. Of primary concern to a railway engineer is what the overall deflection of the rail is. The displacement sensor unit 110 according to the subject technology is able to take also into account of any movement in the ballast itself as atrain passes.
The sensor unit determines track vibration data, which may be logged in the sensor unit 110. The track vibration data may include any vertical displacement data of the track that characterizes deterioration in the safety of the railway and may give rise to maintenance. The sensor unit sends wirelessly the track vibration data to an antenna 112 which transfers to track vibration data to a secure server 114 to allow remote web based monitoring 116 of these logged measurements. The monitoring of these operational characteristics, particularly the rail displacement during the passage of rail traffic, will give a measure of voiding and the maintenance requirements for the relevant section of rail. The sensor unit 110 also optionally measures and records rail and ambient temperature. The trending of the track vibration data with time may permit the prediction of maintenance requirements or the imposing of speed limits on the relevant sections of the rail network.
Fig. 2 illustrates the overall process of a railway monitoring system. First a rail way monitoring is affixed to the railway at locations to be monitored (reference 201). The track transition from a softer to a harder surface, and vice versa, at a railway crossover or viaduct for example, can cause vibrations. Another cause may lie just before/behind the track transition. The ballast (railway gravel) cannot support the sleepers (concrete sleepers) as well as it should. This vertical displacement is called in Dutch 'blinde vering’. The insulation rail joints before and after a track transition may also affect vibrations. The sensor unit is now waiting for a train passage (reference 202). Reference 203 indicates that when a train approaches the sensor unit, the sensor unit starts a measurement.
During a train passage, indicated with 204, acceleration data is recorded. Track vibration data is calculated 205 from the acceleration data by a signal processor. The calculated track vibration data is wirelessly transmitted 206 to the cloud 207 and distributed 208 to servers 209 for storage and further processing. The stored track vibration data may be inspected visually on a screen by a graph showing 210 the track vibration data as a function of time. This inspection may also be performed automatically by algorithms that present data for inspection to a user once the track vibration data meets predefined criteria. When the track vibration data indicates that there is too much vertical displacement or too much vibration to be expected in the near future, the railway manager 211 is informed about said locations. If the vertical displacement exceeds predefined threshold values, a notification 212 is given to start maintenance and/or visual inspection or any other suitable action to avoid serious railway accidents.
Fig. 3 shows a block diagram of an embodiment of railway monitoring sensor unit 300 in accordance with the present subject technology. The railway monitoring sensor unit 300 comprising a first MEMS acceleration sensor 302 generating acceleration signals, optionally a second MEMS acceleration sensor 304, a signal processing unit 306, data storage 308, a wireless communication module 310, an antenna 312, a power supply 314 and a power regulator 316.
The first MEMS acceleration sensor 302 comprises a 3-axis MEMS (Micro-Electro-Mechanical Systems) acceleration sensing element. It should be noted that to measure only vertical displacement a 1-axis MEMS acceleration sensing element may be used. The first MEMS acceleration sensor 302 is configured to generate acceleration signals. The first MEMS acceleration sensor converts the analogue acceleration signals to the digital domain. Preferably, the first MEMS acceleration sensor comprises an analog, low-pass, antialiasing filter to reduce out of band noise and to limit bandwidth in the analog domain, an à-A ADC to digitize the filtered analog signal, a decimation filter with a low-pass filter cutoff (3dB) at about 1 kHz and an interpolation filter after the decimation filter to produce oversampled/upconverted raw acceleration signals to be processed by the signal processing unit 306.
The signal processing unit 306 receives the acceleration signals from the first MEMS acceleration sensor 302 and processes the acceleration signals to generate a set of track vibration data. The set of track vibration data generated by the signal processing unit 306 is transmitted by wireless communication module 310 to a server for further processing using antenna 312. Data storage 308 is used by the signal processing unit to store intermediate signals and one or more sets of track vibration data. The power supply 314 is a battery and may be a rechargeable battery to power the components of the railway monitoring sensor unit 300. In this way, the railway monitoring sensor unit 300 is a stand-alone unit which does not require a connection with a main voltage. A power regulator 316 is provided to generate a fixed output voltage of a pre-set magnitude that remains constant regardless of changes to its input voltage or load conditions.
The wireless communication module 310 may uses any suitable wireless communication protocol. When the railway monitoring sensor unit is a battery powered stand-alone unit, the wireless communication module 310 may be a LPWAN (low-power wide-area network) transceiver, LoRaWAN (Long Range Wide Area Network) transceiver, or any other suitable wireless network transceiver. The wireless communication module 310 is switched on by the signal processing unit 306 when there is a set of track vibration data available for transmission. A set of track vibration data is calculated for a train passage and includes for each train passage: a time stamp, and at least one of: maximal displacement downward, maximal displacement upward, average displacement downward of wheelsets, average displacement upward of the wheelsets, maximal swing caused by a wheelset, average swing caused by the wheelsets. After transmission of the set of track vibration data, the wireless communication module is switched in a low-power mode to reduce power consumption. To reduce power consumption further, the railway monitoring sensor unit may be configured to repeatedly collect a number of N sets of track vibration data and to transmit the N sets of track vibration data in one transmission session to the server. As said above, a set of track vibration data is calculated for a train passage. This means that the signal processing unit 306 only has to process acceleration signals corresponding to train passages. By switching the signal processing unit 306 in a low-power mode when there is no moving train in the vicinity of the location of the railway monitoring sensor unit, the power consumption is reduced. The signal processing unit 306 knows when it has finalized processing of acceleration data to obtain a set of track vibration data. Furthermore, the signal processing unit 306 controls the wireless communication unit 310 to transmit one or more sets of track vibration data and thus knows when the wireless communication unit 310 has transmitted the track vibration data. This allows the signal processing unit 306 to switch itself into an energy-saving mode. To wake-up the signal processing unit 306 from energy-saving mode to active mode, the railway monitoring unit further comprises a moving train detector configured for detecting a moving train on the railway in vicinity of the sensor unit and generating a presence detection signal indicative for the presence of a moving train in vicinity of the sensor unit; and a controller to wake-up the signal processing unit in response to the detection signal. The first MEMS acceleration sensor 302 may perform the function of moving train detector. As soon as the amplitude of the acceleration measured by the acceleration sensing element exceeds a predefined threshold value, the sensor 302 generates the presence detection signal at an output pin which is coupled to an input pin of the digital signal processing unit 306. After the presence detection signal changes from no-moving train detected value to moving train detected value, the digital signal processing unit 306 is waked-up and start capturing acceleration signals from the first acceleration sensor unit 302.
Optionally the railway monitoring sensor unit 300 comprises a second MEMS acceleration sensor 304 to perform the moving train detector function. The second MEMS acceleration sensor 304 has a power consumption which is less than the power consumption than the first MEMS acceleration unit
302. Normally, a MEMS acceleration sensor with high accuracy has a higher power consumption than a MEMS acceleration sensor with a low accuracy. By using a low-power MEMS acceleration sensor with relative low accuracy for performing the moving train detector and controller functions for generating the presence detection signal as second MEMS acceleration sensor 304, the power consumption can be further reduced. In that case, second MEMS acceleration sensor 304 continuously measures vibration and as soon as the acceleration corresponding to the vibration caused by a moving train exceeds a predefined threshold value, the sensor changes an output signal from no-moving train value to moving train value. This output signal is used by both the signal processing unit 306 and first MEMS acceleration sensor 302 to wake-up from low-power mode.
The first MEMS acceleration sensor 302 starts sensing the vibration of the railway and generates acceleration signals and the signal processing unit 306 starts processing the acceleration signals to obtain a set of track vibration data from acceleration signals corresponding to a train passage. The signal processing unit 306 monitors the amplitude of the acceleration signals to determine a time instant corresponding to the moment a train has passed. The signal processing unit detects that a train has passed when the amplitude of the acceleration signals drops below a second threshold value on times defined by a time profile. An exemplar embodiment of a time profile is: detecting that the amplitude of the acceleration signal is for a period of 3 seconds below a threshold value. Another exemplar embodiment of a time profile is: detecting the time instant the amplitude of the acceleration signal drops for a period of X ms below the second threshold value, check Y ms after said time instant whether the amplitude of the acceleration signal is again for a period of X' ms below the second threshold value. If this is the case, the decision is made that the train has passed the location of the railway monitoring sensor unit. The signal processing unit 306 processes the acceleration signal up to the moment a train has passed. In the exemplar embodiment of a time profile, this is the moment in time corresponding to the time instant the amplitude of the acceleration signal drops for the first period of X ms below the second threshold value. Possible values for X, Y and X' are 100, 3000 and 100 respectively. After processing the acceleration signals corresponding to a train passage and transmitting the set of track vibration data, the signal processing unit 306 switches the first MEMS acceleration sensor and itself into low-power mode. The second MEMS acceleration sensor 304 monitors the vibration of the railway and as soon as the amplitude exceeds the predefined threshold value, the sensor generates again a control signal to wake-up the signal processing unit 306 and first MEMS acceleration sensor 302.
The processing unit may further be configured to skip after the generation of track vibration data of a train passage the processing of acceleration signals to derive track vibration data for a predefined number of train passages, a predefined time period or a combination thereof. The void displacement increases slowly in time and also due to each train passage. By skipping the processing of train passages and generating and transmitting sets of track vibration data, the power consumption is reduces. In a first exemplar embodiment, the railway monitoring sensor unit 300 determines one set of track vibration data for a train passage each two hours. In a second exemplar embodiment, the railway monitoring sensor unit 300 determines a set of track vibration data for a train passage each tenth train passage. In a second exemplar embodiment, the railway monitoring sensor unit 300 determines a set of track vibration data for a train passage each tenth train passage and if a tenth train passage is not within a two hours period, a set of track vibration data for a train passage is generated for the first train passage after the 2 hour period.
The railway monitoring sensor unit according to the subject technology processes acceleration signals from a 3-axis MEMS acceleration sensor to obtain a set of track vibration data as follows. A characteristic of the vertical displacement of the rail is that the relevant information is in the frequency range from 1 Hz to 24 Hz. The first MEMS acceleration sensor 302 generates a bandpass filtered digital acceleration signal which is the raw acceleration signal that is supplied to the signal processing unit 306. Fig. 5a is a graph showing a raw acceleration signal of a train passage as generated by the MEMS acceleration sensor 302 over time. The train comprises four train units. Each unit comprises a front side wheelset and a rear side wheelset. Each wheelset comprises two axles. This raw acceleration signal is processed by the signal processing unit 306 to obtain a set of track vibration data. The raw acceleration signal is first applied to a first noise filter to attenuate frequencies below 1,3 Hz and above 24 Hz to obtain a filtered acceleration signal.
The first noise filter may be a 2" order Butterworth filter.
Fig. 5b is a graph showing the filtered acceleration signal of a train passage.
Subsequently, the filtered acceleration signal is integrated to obtain a raw velocity signal.
Fig. 5c is a graph showing the raw velocity signal of a train passage.
A second noise filter is applied on the raw velocity signal to obtain a filtered velocity signal.
Frequency components above 24 Hz are attenuated.
The second noise filter may be a 29 order Butterworth filter.
Fig. 5d is a graph showing a filtered velocity signal as calculated in a sensor unit in accordance with the subject technology over time.
The filtered velocity signal is integrated to obtain a displacement signal.
Fig. 5e is a graph showing a raw deflection signal after integrating the filtered velocity signal.
From this graph can be seen that the train comprises four train wagons and each wagon comprises two wheel sets, each with two axles.
The distance between the wheelsets of a wagon is larger than the distance between the back side wheelset of a previous wagon and the front side wheelset of a subsequent wagon coupled to the back side of the previous wagon.
The raw deflection signal represents a displacement signal.
The raw deflection signal is finally analysed to obtain the set of track vibration data.
The raw deflection signal shows the displacement of each wheelset.
Also the deflection caused by each axle can be seen in the graph.
From this raw deflection signal the displacement downward and upwards cause by a wheelset can be easily determined.
It can be seen that the displacement for each wheelset is unique.
Before a wheelset passes the sensor unit, the rail is lifted slightly before the rail is displaced downward.
Similarly, the rail is lifted slightly after the passage of the wheelset.
This allows determining for each wheelset the maximal displacement swing downward, maximal displacement swing upward.
The maximal displacement swing is the displacement between a top 502 of raising of the rail and bottom 504 of downward displacement of the rail by an axle next to the top of lift-up of the rail.
Furthermore, the data derived for each wheelset can be used to determine for the train passage the average of maximal displacement downward of the wheelsets, average of maximal displacement upward of the wheelsets, maximal displacement downward, the maximal displacement upward relative to a reference value, the maximal displacement downward relative to the reference value.
It should be noted that in Fig. 5E the raising of the track is more than in reality and the lowering in less than in reality.
However, the distance between the top of the raising and the bottom of the lowering, defining the displacement swing, corresponds to the physical displacement. Furthermore, is the change over time is monitored, the known error in measured tops of raisings and tops of lowering can be eliminated.
Next to track vibration data, data such as a time stamp, ambient temperature, rail temperature may be added to the set of track vibration data corresponding to a train passage.
While the invention has been described in terms of several embodiments, it is contemplated that alternatives, modifications, permutations and equivalents thereof will become apparent to those skilled in the art upon reading the specification and upon study of the drawings. It must be understood that this description is given solely by way of example and not as limitation to the scope of protection, which is defined by the appended claims. -O0-0-0-0-0-
Claims (18)
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| NL2027749A NL2027749B1 (en) | 2021-03-12 | 2021-03-12 | A railway monitoring sensor unit |
| EP22161549.5A EP4056449A1 (en) | 2021-03-12 | 2022-03-11 | A railway monitoring sensor unit |
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| Application Number | Priority Date | Filing Date | Title |
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| NL2027749A NL2027749B1 (en) | 2021-03-12 | 2021-03-12 | A railway monitoring sensor unit |
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| EP4339067A1 (en) * | 2022-09-16 | 2024-03-20 | voestalpine Turnout Technology Germany GmbH | A soft or crossover component with releasable connection and a method and arrangement for monitoring the releasable connection |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB2420627A (en) | 2004-11-24 | 2006-05-31 | Aea Technology Plc | Void meter |
| JP4338273B2 (en) | 1999-12-15 | 2009-10-07 | 東日本旅客鉄道株式会社 | Method for detecting subsidence, subsidence detector and subsidence monitoring device |
| WO2017105451A1 (en) | 2015-12-17 | 2017-06-22 | Siemens Rail Automation Pty. Ltd. | Railway track displacement measurement system and method for proactive maintenance |
| US20180154914A1 (en) * | 2016-12-02 | 2018-06-07 | Commissariat A I'energie Atomique Et Aux Energies Alternatives | Railway rail guide system |
| CN110126877A (en) | 2019-05-21 | 2019-08-16 | 山东交通学院 | One kind being based on technology of Internet of things railroad track vibration monitor system and method |
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2021
- 2021-03-12 NL NL2027749A patent/NL2027749B1/en active
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2022
- 2022-03-11 EP EP22161549.5A patent/EP4056449A1/en active Pending
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| JP4338273B2 (en) | 1999-12-15 | 2009-10-07 | 東日本旅客鉄道株式会社 | Method for detecting subsidence, subsidence detector and subsidence monitoring device |
| GB2420627A (en) | 2004-11-24 | 2006-05-31 | Aea Technology Plc | Void meter |
| WO2017105451A1 (en) | 2015-12-17 | 2017-06-22 | Siemens Rail Automation Pty. Ltd. | Railway track displacement measurement system and method for proactive maintenance |
| US20180154914A1 (en) * | 2016-12-02 | 2018-06-07 | Commissariat A I'energie Atomique Et Aux Energies Alternatives | Railway rail guide system |
| CN110126877A (en) | 2019-05-21 | 2019-08-16 | 山东交通学院 | One kind being based on technology of Internet of things railroad track vibration monitor system and method |
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| FAULKNER KAREN ET AL: "Tracking bridge tilt behaviour using sensor fusion techniques", JOURNAL OF CIVIL STRUCTURAL HEALTH MONITORING, SPRINGER BERLIN HEIDELBERG, BERLIN/HEIDELBERG, vol. 10, no. 4, 29 April 2020 (2020-04-29), pages 543 - 555, XP037183673, ISSN: 2190-5452, [retrieved on 20200429], DOI: 10.1007/S13349-020-00400-9 * |
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| Publication number | Publication date |
|---|---|
| EP4056449A1 (en) | 2022-09-14 |
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