Dynamic rail vehicle characteristic measurement system and method

Abstract

Dynamic rail vehicle characteristic measurement system (Fig.1,1) comprises a data collection zone 6 associated with a section of railway track (Fig.2,2). It collects data as the train travels through

Description

The present invention relates to a dynamic rail vehicle characteristic measurement system and method of measuring rail vehicle characteristics dynamically. 5 The method of operation of any rail vehicle, such as a train, is dependent upon many characteristics, including the type of rail vehicle, the rail vehicle weight, the axle weight and braking capabilities. These are typically stated based upon the original loading, braking and wear parameters determined at manufacture or during routine maintenance, and used to determine safe operating speeds by class of rail vehicle. Such operat-10 ing characteristics are therefore generic, and do not take into account the actual day-to-day condition of an individual rail vehicle. However, many characteristics that would be beneficial in deciding how to operate a rail vehicle on an individual basis are not known by the driver, signaller or signalling system, and are therefore assumed. This includes, for example, how effectively the brakes are working and the condition of the wheels. For 15 freight rail vehicles, the exact loading relative to the rail infrastructure loading gauge is also based on assumption (loading gauge, volume of material per car, for example) and / or sign off by person in a loading yard. Given the assumptions made, the operating method cleared for use by the rail vehicle may be limiting in certain circumstances. For example, a train that is lighter than assumed could run at a higher line speed. A train with 2 0 poorly performing brakes could have a temporary speed limitation. A train that is over its allowed vehicle or axle load could be speed restricted, as could a train with wheels having irregularities such as flat spots. Another issue is that within the rail network, train operators pay to use routes based on the train being used and load being carried, and use the same assumptions as for operations. This means that rail infrastructure managers rely on 2 5 the theoretical characteristics of trains to determine the relevant fees, which may lead to inaccuracies in pricing models and charges. There are three main techniques used to measure rail vehicle characteristics: classification by type; maintenance to remain within the allocated type; and diagnostic sensors used to monitor for rail vehicle faults trackside. Classification by type defines limits 3 0 for weight, dimensions, speed and braking performance, and as described above, is the common basis for operating systems. Regular maintenance is undertaken on rail vehicles 29 08 25 in order to maintain the performance characteristics within the defined parameters of their allocated type. Diagnostic sensors are normally used to monitor for specific vehicle faults, such as axle box or bearing temperature and wheel profile. Should there be any overheating or damage to wheel profiles operating systems can be updated to take into 5 account these issues until maintenance of the rail vehicle can be arranged. However, none of these systems allows for either a specific set of operating conditions to be generated for an individual rail vehicle and route, or the dynamic measurements of all of the characteristics required to determine such a specific set of operating conditions. Being able to determine rail vehicle characteristics dynamically in order to be able to generate 10 unique operating guidelines for individual rail vehicles would have the advantage, therefore, of being able to tailor better the rail vehicle and rail infrastructure usage at any given time. This would help to ensure the optimum use of routes and track sections and the overall volume of traffic running on the railway. The embodiments of the present invention aim to address these issues, by provid-15 ing, in a first instance, a dynamic rail vehicle characteristic measurement system comprising: a data collection zone associated with a section of railway track along which a rail vehicle will travel and adapted to collect data relating to rail vehicle characteristics dynamically as the rail vehicle travels through the data collection zone; a processor arranged to collate and analyse the data collected in the data collection zone; to determine rail vehi- 2 0 cle characteristics based upon the data; and to calculate corresponding rail vehicle operating criteria for the rail vehicle based on these characteristics, wherein the rail vehicle has a rail vehicle type classification; and a communications link adapted to communicate to at least one of a trackside or a rail vehicle-borne operating system; wherein the processor is further arranged to access route information for a route that has been provisionally 2 5 allocated to the rail vehicle, calculate a variance between the rail vehicle characteristics and ideal data sets for the rail vehicle type classification, and to determine the rail vehicle operating criteria by adjusting the provisionally allocated route to create a final route and speeds for the final route based upon the calculated variance. Determining rail vehicle characteristics dynamically by collecting data from a num-3 0 ber of sources within a known data collection zone in order to be able to generate unique 29 08 25 operating guidelines for individual rail vehicles has the advantage, of being able to tailor better the rail vehicle and rail infrastructure usage at any given time. The data collection zone preferably comprises: an axle weight sensor and a wheel impact load detector mounted on each rail; an optical sensor coupled to a light source; 5 and an image capture device. Preferably, the data collection zone further comprises an axle counter head adjacent one of the rails at the boundary of the data collection zone or a fibre optic cable passing through the data collection zone. The image capture device is preferably adapted to be triggered by a rail vehicle as it enters the data collection zone and to capture at least one image of the rail vehicle as it 10 passes through the data collection zone. Preferably, the optical sensor coupled to a light source forms part of a LiDAR scanning system adapted to be triggered by a rail vehicle as it enters the data collection zone and to scan the rail vehicle to establish gauge. Preferably, the axle weight sensors are mounted on a common axis perpendicular 15 to the rails. Preferably, the axle weight sensors are adapted to measure the relative weight of each wheel of the rail vehicle passing through the data collection zone. Preferably, the wheel impact detectors are mounted on a common axis perpendicular to the rails. Preferably, the image detector is arranged to capture at least one image of each 2 0 rail vehicle passing through the data collection zone. Preferably, the data collection zone boundary has an entrance to the data collection zone and an exit from the data collection zone, and wherein an axle counter head is positioned adjacent a rail at the entrance to the data collection zone and a second axle counter head is positioned adjacent the rail at the exit of the data collection zone. 2 5 Preferably, the data collection zone is located at an existing test point where a rail vehicle enters service. The processor may be provided either in the vicinity of the railway track, or at a remote location. In a second instance, the present invention provides a method of determining the operat-3 0 ing criteria for a rail vehicle,, wherein the rail vehicle has a rail vehicle type classification, comprising: collecting data from a data collection zone associated with a section of 29 08 25 railway track over which a rail vehicle is travelling, the section of railway track being linked to a route; communicating the collected data to a processor; collating and analysing the data collected from the data collection zone; determining rail vehicle characteristics based upon the collated and analysed data; and calculating corresponding rail vehicle 5 operating criteria for the rail vehicle based on these determined characteristics; wherein calculating the rail vehicle operating criteria comprises: accessing route information for a route provisionally allocated to the rail vehicle; calculating a variance between the rail vehicle characteristics and ideal data sets for the rail vehicle type classification; and determining the rail vehicle operating criteria by adjusting the provisionally allocated route to 10 create a final route and speeds for the final route based upon the calculated variance. The method may further comprise outputting the rail vehicle operating criteria to at least one of a trackside or a rail vehicle-borne operating system. The method may further comprise calculating a financial charge based upon the 15 determined rail vehicle operating criteria; and outputting the financial charge to an operations management system. The present invention will now be described by way of example only, and with reference to the accompanying drawings, in which: Figure 1 is a schematic illustration of a dynamic rail vehicle characteristic measurement 2 0 system in accordance with an embodiment of the present invention; Figure 2 is a schematic illustration of the components of a dynamic rail vehicle characteristic measurement system in accordance with an embodiment of the present invention; and Figure 3 is a flow chart illustrating the steps of a method of determining the operating cri-25 teria for a rail vehicle in accordance with an embodiment of the present invention. The present invention takes the approach of collating together a number of data sources in order to measure rail vehicle characteristics dynamically and to determine operating criteria for a rail vehicle. A dynamic rail vehicle characteristic measurement system is provided with a data collection zone associated with a section of railway track 3 0 along which a rail vehicle will travel. This data collection zone is adapted to collect data relating to rail vehicle characteristics dynamically as the rail vehicle travels through the 29 08 25 zone. A processor is also provided, and arranged to collate and analyse the data collected in the data collection zone, as well as to determine rail vehicle characteristics based upon the data. In addition, the processor calculates corresponding rail vehicle operating criteria for the rail vehicle based on these characteristics. A communications link to at least 5 one of a trackside or a rail vehicle-borne operating system is provided such that the operating criteria can be sent to a rail vehicle and / or a signalling system. Determining the operating criteria for the rail vehicle comprises, initially, collecting data from a data collection zone associated with a section of railway track over which a rail vehicle is travelling, the section of railway track being linked to a route. The collected data is then communi- 10 cated to the processor, which collates and analyses the data collected from the data collection zone. In addition, the processor determines the rail vehicle characteristics based upon the collated and analysed data and calculates the corresponding rail vehicle operating criteria for the rail vehicle based on the determined characteristics. The features of the embodiments of the present invention will now be described in more detail below. 15 Figure 1 is a schematic illustration of a dynamic rail vehicle characteristic measure ment system in accordance with an embodiment of the present invention. A dynamic rail vehicle characteristic measurement system 1 is provided on a section of railway track 2 along which a rail vehicle, such as a train, will travel. The section of railway track 2 comprises two spaced apart rails 3a, 3b mounted on sleepers 4a...4n bedded into ballast 5. A 2 0 data collection zone 6 is associated with the section of railway track 2, and is adapted to collect data relating to rail vehicle characteristics dynamically as the rail vehicle travels through the data collection zone 6. A processor 7 is provided either in the vicinity of the railway track 2, such as in an enclosed local network environment 8, or at a remote location 9, such as an RBC (Radio Block Centre) or a cloud environment and linked to the data 2 5 collection zone 6 via a communications link 10. A processor 7 provided within an enclosed local network environment 8 will also connect to the remote location 9 via the communications link 10 in order to communicate rail vehicle operating criteria to a trackside operating system, such as a signalling system. The communications link 10 also enables communication from the processor 7 to a rail vehicle-borne operating system, should 3 0 this be required. The processor 7 is arranged to collate and analyse the data collected in the data collection zone 6 and to determine rail vehicle characteristics based upon this 29 08 25 data. The processor 7 is also arranged to calculate the corresponding rail vehicle operating criteria for the rail vehicle based on these characteristics, as described in more detail below. Figure 2 is a schematic illustration of the components of a dynamic rail vehicle 5 characteristic measurement system in accordance with an embodiment of the present invention. The data collection zone 6 comprises a number of sensors each designed to measure a specific parameter relating to a rail vehicle and its capabilities. An axle weight sensor 11a, lib is mounted on each rail 3a, 3b, on a common axis A perpendicular to the rails 3a, 3b. The axle weight sensors 11a, lib are adapted to measure the relative weight 10 of each wheel of the rail vehicle as it passes through the data collection zone 6. This highlights any weight distribution issues on each axle. Preferably, each axle weight sensor 11a, lib is part of a Weigh-in-Motion (WIM) system, where each axle weight sensor 11a, lib measures the weight of an axle as a wheel passes over a measurement point on the rail 3a, 3b, by determining the deformation of the rail 3a, 3b. This may be done in a num- 15 berofways, for example, using strain gauges, fibre optic sensors and piezoelectric sensors. A wheel impact load detector 12a, 12b (commonly referred to as "WILD"), is mounted on each rail 3a, 3b, on a common axis B perpendicular to the rails 3a, 3b. Preferably the wheel impact load detectors 12a, 12b are a strain gauge system welded to 2 0 each rail 3a, 3b to measure the impact each wheel has on the rail 3a, 3b in passing. This produces a load profile for each wheel, which is then used to determine the wheel condition. An alternative system may measure the vertical displacement of a wheel impact load detector 12a, 12b and determine a load profile using Fourier transform techniques. An axle counter head 13a, 13b is positioned adjacent one of the rails at the bound- 25 ary 14 of the data collection zone 6. The data collection zone boundary 14 has an entrance 15 to the data collection zone 6 and an exit 16 from the data collection zone 6. An axle counter head 13a is positioned adjacent a rail 3a at the entrance 15 to the data collection zone 6 and a second axle counter head 13b is positioned adjacent the rail 3a at the exit 16 of the data collection zone 6. The axle counter heads 13a, 13b detect the number 3 0 of axles of the rail vehicle at the entrance 15 to the data collection zone 6 and the exit 16 from the data collection zone 6 in order to measure the total number of wheels of each 29 08 25 individual rail vehicle. Preferably the axle counter heads 13a, 13b are an electrical, mechanical or fibre optic sensor, linked to the processor 7 to enable this to function as an evaluator, as described below. As an alternative to an axle counter head 13a, 13b, a fibre optic cable may be used to determine the counting of the number of wheels on the rail 5 vehicle. For example, fibre optic cables are often used for railway signalling applications, where they are laid alongside the railway track in order to carry data relating to the operation of the railway. Such fibre optic cables also offer the ability to observe rail vehicle behaviour due to their vibration sensing capabilities. As a rail vehicle passes a fibre optic cable it creates a characteristic vibration, or signature, that is detected by the fibre optic 10 cable. This signature is picked up by the signal processing technology inherent in the railway signalling system as a series of peaks in either a frequency-time or amplitude-time spectrum. The wheels are indicated by small peaks overlaid on the broad peak representing the entire rail vehicle, and counting these peaks indicates the number of wheels on the rail vehicle. Therefore, rather than providing the axle counter heads 13a, b, the vibra- 15 tions in a fibre optic cable passing through the data collection zone 6 at the point the rail vehicle enters or leaves the data collection zone 6 may be used to determine the number of wheels on the rail vehicle. In addition, modulations in the spectra may also indicate wheel flats or other damage that may be relevant to calculating rail vehicle operating criteria. 2 0 An optical sensor 17 is provided, coupled to a light source 18 and forming part of a LiDAR scanning system 19. The LiDAR scanning system 19 is adapted to be triggered by a rail vehicle as it enters the data collection zone 6 and to scan the rail vehicle to establish gauge. The LiDAR scanning system 19 may be based on a visible, near-infrared or ultraviolet laser light source 18, directed using a phased array. Whilst MEMS (microelectrome- 2 5 chanical mirrors) may be used, these are more susceptible to disruption due to vibration, and therefore may not be suitable for all data collection zones 6, such as those in heavy goods yards. The optical sensor 17 comprises its own light source, and detects light reflected from the rail vehicle as it passes through the data collection zone 6, which is used subsequently to determine the gauge of the train. 3 0 Finally, an image capture device 20 is also provided. The image capture device 20 is adapted to be triggered by a rail vehicle as it enters the data collection zone 6 and to 29 08 25 capture at least one image of the rail vehicle as it passes through the data collection zone 6. Preferably, the image capture device 20 is a camera able to record multiple image frames to create a video data feed. The images may be analysed to determine rail vehicle types from data panels included on individual carriages or traction units, and to confirm 5 overall train integrity. The data collection zone 6 is sized to ensure that each of the sensors 11a,lib, 12a, 12b, 13a, 13b, LiDAR scanning system 19 and the image capture device 20 are placed to be able to capture data as a rail vehicle travels past. For example, the data collection zone 6 may be an entire track section, with an entry and exit signal marking the boundary 10 of the data collection zone 6. The axle counter heads 13a, 13b may be placed adjacent to any entry and exit signals at the entrance 15 and exit 16 of the data collection zone 6. Alternatively, the data collection zone may be placed at an existing test point where a rail vehicle enters service. Alternatively, the data collection zone may be located at the exits from yards and depots, or used at the start of a section of route with restrictions (such as 15 low bridges). Both the LiDAR scanning system 19 and the image capture device 20 may be positioned at the entry 14 or the exit 16 of the data collection zone 6, or within the data collection zone 6. The LiDAR scanning system 19 is preferably positioned to be able to scan an oncoming rail vehicle laterally and parallel to the direction of rail vehicle travel, whereas the image capture device 20 is preferably positioned perpendicular to the direc- 2 0 tion of rail vehicle travel. The axle weight sensors 11a, lib and wheel impact load detectors 12a, 12b may be positioned anywhere within the data collection zone 6, but it may be convenient to position these adjacent one another at the entry 14 of the data collection zone 6. Figure 3 is a flow chart illustrating the steps of a method of determining the oper-2 5 ating criteria fora rail vehicle in accordance with an embodiment of the present invention. The method 300 starts at step 302 with the collecting of data from a data collection zone 6 associated with a section of railway track 2 over which a rail vehicle is travelling, the section of railway track 2 being linked to a route. The route is preferably set to include the data collection zone 6 at its start. Next, at step 304, the collected data is com-30 municated to the processor 7. As outlined above, there are two options for the location of the processor 7: either in an enclosed local network environment 8, or at a remote 29 08 25 location 9, such as an RBC (Radio Block Centre) and linked to the data collection zone 6 via a communications link 10. Each of the sensors 11a,b, 12a, b, 13a,b, LiDAR scanning system 19 and image capture device 20 may communicate with the processor 7. For a processor 7 housed in an enclosed local network environment 8, this may be done using 5 an appropriate communications protocol, for example, cellular (such as 5G), LAN (local area network), WAN (wide area network), Bluetooth™, ZigBee, or a data bus. For a processor 7 located at a remote location 9, this may be done via the communications link 10 (which is either a cellular or wired network) either individually or via a second processor 21, positioned within the data collection zone 6 to gather data from each data source be-10 fore transmitting onwards to the remote processor 7. A local processor 7, 21, has the advantage that data may be manipulated without issues relating to data transfer rates, but a remote processor 7, such as that in a cloud environment, reduces the amount of local infrastructure required for the data collection zone 6. A local processor 7, 21 also acts as the evaluator for the axle counting heads 13a,b, such that the number of wheels passing 15 the first axle counting head 13a increments a counter by a value of one, and then on passing the second axle counting head 13b, the count decrements by a value of one. This enables the counting of the number of axles and a double-check on accuracy. Once the data has been communicated to the processor 7, at step 306 the data is collated and analysed. At this point any external information required, such as route de-2 0 tails, maps, and ideal operating data sets for the expected type classification of the rail vehicle may be fetched from data storage such as a database, lookup table or central memory storage device. At step 308, the rail vehicle characteristics are determined based upon the collated and analysed data. This is the point at which the number of wheels, axle weight distribution, wheel loading profiles, gauge, classification type identification 2 5 and coupling and brake pipe integrity are determined. For image data, image analysis software is used to determine the required characteristics, such as 2D and 3D object recognition based on appearance-based methods (such as edge matching, greyscale matching, gradient matching) or feature-based methods (such as geometric hashing, invariance, scale-invariant feature transforms [SIFT] and speeded up robust features 3 0 [SURF]). LiDAR results may be interpreted from heat maps indicating relative distances. At step 310, the corresponding rail vehicle operating criteria for the rail vehicle are 29 08 25 calculated based on these determined characteristics. Once the rail vehicle operating criteria are available these may be output to at least one of a trackside or a rail vehicle-borne operating system. This calculation at step 310 involves a number of sub-steps. At step 3101, the 5 route information for a route that has been provisionally allocated to the rail vehicle is accessed, from either a map, signalling system or RBC. A unique identity of the train may be used to confirm the route information, including operating speeds. The previously accessed ideal data sets are then used at step 3102 in calculating a variance between the rail vehicle characteristics and ideal data sets for the rail vehicle type classification. This 10 variance indicates the extent to which the operating conditions of the rail vehicle either can be altered or must be altered, depending on the overall condition of the rail vehicle. At step 3103 the rail vehicle operating criteria are determined by adjusting the provisionally allocated route to create a final route and speeds for the final route based upon the calculated variance. For example, if a rail vehicle has been found to be lighter than ex- 15 pected its line speed could be increased. Fora rail vehicle with wheels having irregularities, the line speed could be restricted. A further advantage of the embodiments of the present invention is that a financial charge based upon the determined rail vehicle operating criteria may be calculated. This is then output to an operations management system, enabling an infrastructure man-2 0 agement to charge the rail vehicle operator a revised fee for the rail vehicle operating the final route. These and other advantages of the embodiments of the present invention falling within the scope of the appended claims will be apparent to the person skilled in the art. 29 08 25

Claims

1. Dynamic rail vehicle characteristic measurement system comprising:a data collection zone associated with a section of railway track along which a rail vehicle will travel and adapted to collect data relating to rail vehicle characteristics dy-5 namically as the rail vehicle travels through the data collection zone;a processor arranged to collate and analyse the data collected in the data collection zone; to determine rail vehicle characteristics based upon the data; and to calculate corresponding rail vehicle operating criteria for the rail vehicle based on these characteristics, wherein the rail vehicle has a rail vehicle type classification; and10 a communications link adapted to communicate to at least one of a trackside or arail vehicle-borne operating system;wherein the processor is further arranged to access route information for a route that has been provisionally allocated to the rail vehicle, calculate a variance between the rail vehicle characteristics and ideal data sets for the rail vehicle type classification, and to15 determine the rail vehicle operating criteria by adjusting the provisionally allocated route to create a final route and speeds for the final route based upon the calculated variance.

2. A measurement system as claimed in claim 1, wherein the data collection zone comprises: an axle weight sensor and a wheel impact load detector mounted on each rail;2 0 an optical sensor coupled to a light source; and an image capture device.

3. A measurement system as claimed in claim 2, wherein the data collection zone further comprises an axle counter head adjacent one of the rails at the boundary of the data collection zone or a fibre optic cable passing through the data collection zone.

254. A measurement system as claimed in claim 3, wherein the image capture device is adapted to be triggered by a rail vehicle as it enters the data collection zone and to capture at least one image of the rail vehicle as it passes through the data collection zone.3 0 5. A measurement system as claimed in claim 3 or 4, wherein the optical sensor coupled to a light source forms part of a LiDAR scanning system adapted to be triggered by a29 08 25rail vehicle as it enters the data collection zone and to scan the rail vehicle to establish gauge.

6. A measurement system as claimed in any of claims 3, 4 or 5, wherein the axle 5 weight sensors are mounted on a common axis perpendicular to the rails.

7. A measurement system as claimed in claim 6, wherein the axle weight sensors areadapted to measure the relative weight of each wheel of the rail vehicle passing through the data collection zone.

108. A measurement system as claimed in any of claims 3 to 7, wherein the wheel impact detectors are mounted on a common axis perpendicular to the rails9. A measurement system as claimed in any of claims 3 to 8, wherein the image de-15 tector is arranged to capture at least one image of a rail vehicle passing through the data collection zone.

10. A measurement system as claimed in claim 2, wherein the data collection zone boundary has an entrance to the data collection zone and an exit from the data collection 2 0 zone, and wherein an axle counter head is positioned adjacent a rail at the entrance tothe data collection zone and a second axle counter head is positioned adjacent the rail at the exit of the data collection zone.

11. A measurement system as claimed in any preceding claim, wherein the data col-25 lection zone is located at an existing test point where a rail vehicle enters service.

12. A measurement system as claimed in any preceding claim, wherein the processor is provided either in the vicinity of the railway track, or at a remote location.3 0 13. A method of determining the operating criteria for a rail vehicle, wherein the railvehicle has a rail vehicle type classification, comprising:29 08 25collecting data from a data collection zone associated with a section of railway track over which a rail vehicle is travelling, the section of railway track being linked to a route;communicating the collected data to a processor;5 collating and analysing the data collected from the data collection zone;determining rail vehicle characteristics based upon the collated and analysed data; andcalculating corresponding rail vehicle operating criteria for the rail vehicle based on these determined characteristics;10 wherein calculating the rail vehicle operating criteria comprises:accessing route information for a route provisionally allocated to a rail vehicle;calculating a variance between the rail vehicle characteristics and ideal data sets for a rail vehicle type classification; anddetermining the rail vehicle operating criteria by adjusting the provisionally allo-15 cated route to create a final route and speeds for the final route based upon the calculated variance.

14. A method as claimed in claim 13, further comprising:outputting the rail vehicle operating criteria to at least one of a trackside or a rail2 0 vehicle-borne operating system.

15. A method as claimed in claim 14, further comprising:calculating a financial charge based upon the determined rail vehicle operating criteria; and2 5 outputting the financial charge to an operations management system.

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