GB2546344A - Vehicle underframe examination system - Google Patents
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- GB2546344A GB2546344A GB1605509.7A GB201605509A GB2546344A GB 2546344 A GB2546344 A GB 2546344A GB 201605509 A GB201605509 A GB 201605509A GB 2546344 A GB2546344 A GB 2546344A
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- 238000003384 imaging method Methods 0.000 claims abstract description 68
- 238000013459 approach Methods 0.000 claims abstract description 28
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- 238000000701 chemical imaging Methods 0.000 claims description 32
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- 238000003331 infrared imaging Methods 0.000 claims description 3
- 230000006798 recombination Effects 0.000 claims description 3
- 238000005215 recombination Methods 0.000 claims description 3
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Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M11/00—Testing of optical apparatus; Testing structures by optical methods not otherwise provided for
- G01M11/08—Testing mechanical properties
- G01M11/081—Testing mechanical properties by using a contact-less detection method, i.e. with a camera
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M15/00—Testing of engines
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M17/00—Testing of vehicles
- G01M17/08—Railway vehicles
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Abstract
A vehicle underframe examination system for anomalous condition detection of an underframe of a vehicle (eg a train 22, figure 2), the system comprising an imaging apparatus 12 (such as a series of hyperspectral cameras) for acquiring images of a vehicle passing over a designated vehicle transit route; at least one vehicle approach sensor 18 and a controller 16 associated with the imaging apparatus and the approach sensor for activating the imaging apparatus; and a vehicle identification means for determining an identity of the vehicle on approach to the imaging apparatus. The controller includes a processor 24 and may be associated with a vehicle identification means 26 via a radio frequency communicator.
Description
Vehicle Underframe Examination System
The present invention relates to a vehicle underframe examination system, in particular for the inspection of the underframe of railway trains. The invention further relates to a vehicle transit network using such a system, and to a method of inspecting the underframe of a vehicle for anomalous conditions during normal operation of the vehicle.
Routine inspection and maintenance of vehicles, and in particular trains, is a continuous activity which must be undertaken so as to ensure that equipment is maintained to an acceptable safety standard. Equipment has a finite service life; the difficulty lies in determining service schedules which permit wear of the various components to be identified prior to critical failure. This can lead to increased cost and resource consumption as the vehicles are inspected and therefore not operational.
Preventing failure of the expensive major components, such as engines, gearboxes, wheel sets and axle bearings, and safely maximising their service life is therefore very important. Such components are most accurately monitored in operational conditions, for instance, whilst the train is moving, rather than whilst non-operational in a depot. The failure conditions of a running engine may, for instance, be very different to those of a cold engine.
For critical safety systems, such as the braking systems, regular servicing is important in order to mitigate the effects of normal wear-and-tear. However, a regular servicing cycle cannot anticipate critical and/or catastrophic failures, for instance, damage to components which might result in a fluid leak. It is not feasible to fully inspect all components of a vehicle on a daily basis, and some warning signs of failure may not be apparent to the unaided eye.
It is possible to provide onboard sensors on vehicle which are coupled to the most critical systems, and are capable of monitoring particular warning signs related to failure of the systems. This is, however, an expensive solution, and a separate monitor must be provided for each individual system. It is therefore only viable to do so for the most important systems onboard the vehicle.
The present invention seeks to provide a means of continuously and automatically monitoring vehicles, in particular trains, so as to overcome or limit the above-described problems.
According to a first aspect of the invention, there is provided vehicle underframe examination system for anomalous condition detection of an underframe of a vehicle, the system comprising: a hyperspectral imaging apparatus positioned to acquire images of at least an underframe of a vehicle passing over a designated vehicular transit route; at least one vehicle approach sensor which is spaced apart from the imaging apparatus; a controller associated with the hyperspectral imaging apparatus and the at least one vehicle approach sensor, the controller being arranged to automatically activate and/or deactivate the hyperspectral imaging apparatus in response to a trigger from the at least one vehicle approach sensor; a vehicle identification means for determining an identity of the said vehicle as it approaches or passes over the hyperspectral imaging apparatus; a processor in communication with the hyperspectral imaging apparatus and which is arranged to process real-time imaging data received from the hyperspectral imaging apparatus; and a memory device associated with the processor, the memory device being arranged to store historical imaging data and/or generic vehicular underframe information data associated with the vehicle or the type of vehicle, the processor being arranged to compare the real-time imaging data to the historical imaging data and/or generic vehicular underframe information data so as to detect an anomalous condition of the underframe of the vehicle.
Preferable and/or optional features of the first aspect of the invention are detailed in claims 2 to 13 below.
According to a second aspect of the invention, there is provided a vehicle transit network comprising a vehicle transit route and a vehicle underframe examination system, preferably in accordance with the first aspect of the invention, the hyperspectral imaging apparatus of the vehicle underframe examination system being positioned so as to image an underside of a vehicle passing over the designated vehicular transit route. In one embodiment, the hyperspectral imaging apparatus may include at least one imaging device which is vertically or substantially vertically aligned so as to image the underside of the vehicle and/or at least one imaging device which is positioned so as to image a side of the underframe of the vehicle. Preferably, the vehicle transit route is a railway.
According to a third aspect of the invention, there is provided a method of inspecting the underframe of a vehicle for anomalous conditions during normal operation of the vehicle, preferably using a vehicle underframe examination system in accordance with the first aspect of the invention, the method comprising the steps of: a] determining whether a vehicle is approaching a specific location; b] determining an identity of the vehicle; c] imaging an underframe of the vehicle using hyperspectral imaging as the vehicle passes over the said specific location; and d] determining, based on an output of step c] and on historical and/or generic vehicular underframe information which is relevant to the vehicle, whether the underframe of the vehicle is experiencing an anomalous condition.
Preferably, the historical and/or generic vehicular underframe information may be determined by machine learning. Furthermore, during step c], a plurality of sequential images of the underframe of the vehicle are taken to obtain an image of the entire length of the underframe of the vehicle. Preferably, during step c], the hyperspectral imaging may utilise infra-red imaging to detect underframe component temperature and at least visible wavelength imaging to detect fluid leakage at the underframe and/or underframe component displacement.
According to a fourth aspect of the invention, there is provided a vehicle underframe examination system for anomalous condition detection of an underframe of a vehicle, the system comprising: an imaging apparatus positioned to acquire images from vertically or substantially vertically above the imaging apparatus so as to image an underside of a vehicle passing over a designated vehicular transit route; at least one vehicle approach sensor which is spaced apart from the imaging apparatus; a controller associated with the imaging apparatus and the at least one vehicle approach sensor, the controller being arranged to automatically activate and/or deactivate the imaging apparatus in response to a trigger from the at least one vehicle approach sensor; and a vehicle identification means for determining an identity of the said vehicle as it approaches or passes over the imaging apparatus.
Railway vehicles pass over a set of hyperspectral sensors and specific light sources such that the digital signals from the sensors are recorded. This system is known as the vehicle underframe examination system (VUES). The system gathers data of the visible components on the underside of the vehicle using a combination of several cameras, which are sensitive to a set of wavelengths of the electromagnetic spectrum (visible, thermal, ultraviolet). Each vehicle may be identified by reading their existing RFID tags such that the history of that vehicle can be recalled. Then, unsupervised and supervised machine learning techniques are applied on the data for use with anomaly detection. The VUES system holds statistics of the measured signals as well as standard and safe operating ranges of components and equipment on-board the vehicle. The system can identify changes to any component or visible area of interest and it is not limited to particular components. These areas can be labelled on one vehicle, tagged with a specific name, for example; “gearbox bearing driveshaft flange bearing” and the temperature profile or appearance variance over time recorded. Once this labelling is complete for a type of vehicle, the data can be used for an entire fleet of the same types of vehicles using the expected component heat/visible profiles. This is achieved by reference to image and temperature history records held in the system by vehicle type.
The data patterns learned by the system are used to report out-of-bounds measurements when new recordings of the underside equipment do not fit the patterns, which is known as an anomaly. The anomaly is reported to maintenance engineers, and a service is scheduled to verify what problem the anomaly represents. The fault diagnosis information from the engineers is then entered into the system so that it can also learn whether these are significant anomalies or not. If the same anomaly is detected in the future, it will be reported with a suggested list of possible problems. As the system gathers more data, the need for routine service inspections by maintenance staff reduces since the diagnosis becomes more specific.
Advantageously, the invention can continually and automatically scan the underside equipment of every railway vehicle in near-service conditions when it passes over the inspection area during its normal timetable, and collects hyperspectral signals that can be analysed and compared automatically and also manually by human operators
By providing an accurate history and patterns of the physical state of the underframe of the railway vehicle, an operator may check back in time to identify the specific time window for when a fault/change occurred.
The invention advantageously allows for detailed visual inspection from high resolution images so as to be able to identify general anomalies and detect early signs of conditions leading to serious and expensive component failure such as overheating components, dislodged or damaged equipment and some leaking fluids. Detected faults can then be reported to maintenance engineers for investigation and service scheduling. Faulty components causing inefficiencies can be detected and replaced.
Engineer diagnosis, feedback and machine learning ensures the system is continuously self-improving. As computer learning progresses, can detect multiple different anomalies and categorise them in a message to an engineer at the control centre.
This can result in less equipment failure and higher reliability, providing opportunities for increasing the duration between routine maintenance inspections and servicing. The VUES system can help reduce the frequency of costly recovery of failed trains, reduce the costs of replacing major components by enabling component life extension and help prevent expensive knock on delays, thus improving customer service and safety within the railways industry. The system may also be applied to other vehicle systems, not just to trains.
The invention will now be more particularly described, by way of example only, with reference to the accompanying drawings, in which:
Figure 1 shows a diagrammatic representation of one embodiment of a vehicle underframe examination system in accordance with the first aspect of the invention;
Figure 2 shows a plan view of a railway, having hyperspectral imaging devices of the vehicle underframe examination system of Figure 1 positioned at the railway tracks prior to the approach of a train;
Figure 3 shows a pictorial representation of a sequence of imaging data which might be collected by the vehicle underframe examination system of Figure 2; and
Figure 4 shows a pictorial representation of the sequence of imaging data of Figure 3 following image recombination.
Continuous inspection and maintenance of railway vehicles is expensive. Even with regular scheduled checks it is difficult to detect equipment that is faulty, beginning to fail or damaged to some extent. Moreover, this is costly, increases down times and impacts customer service and safety.
An automated examination system which monitors the underside of railway vehicles looking for general anomalies and faults is indicated in Figure 1, globally at 10. Although there exist automated inspection systems for brake pad and discs wear, bearing wear, wheels profile monitoring and hot axle boxes detection, the present system 10 covers a more general approach. The present vehicle underframe examination system 10 includes a preferably hyperspectral, imaging apparatus 11, which may include at least one imaging device 12, preferably provided as an array of hyperspectral cameras, each of which may be associated with an illumination device 14.
Using machine vision algorithms, anomalies which could indicate failing components can be detected and reported. This vehicle underframe examination system 10 can be deployed as part of the infrastructure at the premises of railways operators to support and enhance the train maintenance tasks. The vehicle underframe examination system 10 could also be used in inspecting heavy goods road vehicles as they return to their depot following a delivery trip, for instance. It will therefore be apparent that the present invention is not necessarily restricted to use with vehicles which are restricted to railway travel, and any appropriate vehicle transit route can be combined with the present vehicle underframe examination system 10 so as to form a vehicle transit network capable of, potentially automatically, examining a status of the underframe of vehicles passing across the vehicle underframe examination system.
The vehicle underframe examination system 10 comprises at least one said imaging device 12, and preferably a plurality of imaging devices 12, which is in communication with a controller 16, for example, a computer server. At least one vehicle approach sensor 18 may also be provided, which can be employed to detect an oncoming vehicle. The or each vehicle approach sensor 18 may therefore be coupled to a trigger 20 which allows the controller 16 to activate and/or deactivate the at least one imaging device 12 in response to the approach of a vehicle 22. This can be visualised from Figure 2. The vehicle approach sensors 18 may, for example, be based on proximity and motion detection technologies and transmit a signal only when the vehicle 22 is detected or no longer detected.
The at least one imaging device 12 may preferably be provided as an array of hyperspectral cameras with different lenses, and a set of supporting illumination devices 14 may be installed at fixed locations on the ground at or adjacent to the hyperspectral cameras, such that the hyperspectral cameras can capture signals of different wavelengths in the form of images. Each illumination device 14 may be specifically associated with a corresponding imaging device 12 such that the correct form of illumination, such as visible light, is provided to optimise image capture.
The imaging devices 12 may be interconnected, for example through a Local Area Network (LAN) as shown in Figure 1, to the controller 16. There may then be provided a processor 24 associated with the controller 16, which is arranged to acquire and, if a memory device is provided, store the images from the imaging apparatus 11. This allows the real-time imaging data to be processed and analysed, although this may not occur until a later time.
The controller 16 is also be associated with a vehicle identification means 26, such as a radio-frequency communicator, which is able to determine or assign a unique identifier for each distinct vehicle 22 passing through the vehicle underframe examination system 10. This information is used to label and associate specific imaging data to be correlated with a specific vehicle 22.
Figure 2 illustrates the location of hyperspectral cameras 12 and associated lights 14 with respect to a moving railway vehicle 22. As the railway vehicle 22 approaches the or each vehicle approach sensor 18, the trigger 20 is activated such that the controller 16 can activate the hyperspectral cameras 12 and associated lights 14 so as to image the railway vehicle 22 as it passes overhead. In the illustrated example, power and data communication may be provided between the hyperspectral cameras 12 and the controller 16 by Ethernet connection, preferably using Power over Ethernet (PoE) technology. Due to the high bandwidth required to transmit the images, the data communication medium connecting hyperspectral cameras 12 and the controller 16 preferably are arranged so as to allow throughput of at least of 1Gb per imaging device 12.
The depicted array of hyperspectral cameras 12 may be provided so as to be sensitive to, for instance, the three main wavelength bands: the Visible Spectrum (from 380 to 750nm); Long-Wave Infra-Red (from 8 to 14pm); and Ultraviolet (from 10 to 400nm).
The vehicle underside examination system 10 is designed to work outdoors under varied illumination and weather conditions. Therefore, the illumination devices 14 may be provided so as to include a set of external floodlights which are used to support the visibility of underside equipment. A specific weatherproof case may also be provided to enclose at least the imaging devices 12, the case having specialist window materials, included carefully selected transmissivity to the required light and infra-red wavelengths. The remaining electronic equipment of the vehicle underside examination system 10, which may preferably be the processor 24 and/or controller 16 which may be in charge of the data collection, storage and analysis of imaging data, can be housed on a safe and protected place at a certain distance from the hyperspectral cameras 12 depending on the specific requirement and resources of the installation site. It will be appreciated, however, that for ease of manufacture, that some or all of the components of the vehicle underside examination system 10 be housed at or adjacent to the imaging devices 12.
In use, the vehicle underside examination system 10 is able to keep track of the recordings for different vehicles 22 over time, collecting useful statistics of their underside components for the automated detection of anomalies. Differentiation between different vehicles 22 can be achieved using the vehicle identification means 26, which may be communicated to the controller 16 as the vehicle 22 approaches, or may be elided by other means from the vehicle 22 itself, for instance, by utilising the imaging devices 12 to determine an identity of each vehicle 22. In any event, a memory device associated with the processor 24 may be arranged to store information regarding each individual vehicle 22 in a database. This may include the real-time imaging data, historical imaging data, or specific and/or generic information data which relates to a class or type of the particular vehicle 22 in question. For example, there could be specific information data which is applicable to all trains having a specific chassis construction.
Each time a vehicle 22 is determined to be approaching the imaging devices 12, as shown in Figure 2, the vehicle underside examination system 10 can begin to record and/or relay the digital signals comprising real-time imaging data from the hyperspectral cameras 12, preferably at a high frequency. Each vehicle 22 is identified using the vehicle identification means 26, for instance by reading their existing RFID tags. This may then in turn permit historical imaging data or other information data to be recalled by the vehicle underside examination system 10 and/or retrieved from an external source, such as a cloud-based information storage means.
Automated and/or manual machine learning techniques may be applied by the processor 24 on the imaging data received from the imaging devices 12 for anomaly detection.
The vehicle underside examination system 10 may store, in a memory circuit associated with the controller 16 and/or processor 24, statistics of the measured signals as to standard and safe operating ranges of equipment. Subsequently, the vehicle underside examination system 10 is able to identify changes to any component or visible area of interest and it is not limited to particular components. This is a specific advantage over systems which may be specifically associated with a specific component of the vehicle 22, such as an engine temperature monitoring device. The processor 24 may therefore be provided with a vehicle underframe component identification circuit, which assists with the automatic detection and determination of the individual components of the underframe of the vehicle 22, for instance, based on shape or relative position of the components on the underframe. In particular, this may assist with the detection of damage to particular components, such as an axle, for instance, if it is detected that the component is misshapen.
These areas may be visibly labelled on a vehicle 22, so as to improve ease of recognition, and be tagged with a specific name, for example; “gearbox bearing driveshaft flange bearing” and the temperature profile or appearance variance over time may be recorded by the vehicle underside examination system 10. Afterwards, the data can be used for the entire fleet and the patterns learned by the vehicle underside examination system 10 are used to report out-of-bounds measurements when new recordings of the underside equipment do not fit the patterns, which is known as an anomaly. The anomaly is reported to maintenance engineers, whom can either manually inspect the imagery or schedule a service to verify what problem the anomaly represents. The diagnosis information is then entered into the system so that it can also learn whether these are significant anomalies or not. If the same anomaly is detected in the future, it will be reported with a suggested list of possible diagnosis. As the system gathers more data, the need for routine service inspections by maintenance staff reduces since the diagnosis becomes more specific and most routine inspections can be carried out using the recorded data.
One particular scenario in which the present invention excels is in the monitoring of the underside of vehicles 22 for the presence of fluid leakages, such as fuel, brake fluid or engine coolant. This is particularly challenging for the situation in which the vehicle 22 is already wet, since a mere visual inspection of the underframe would not be sufficient to determine whether or not the vehicle 22 were wet, or whether there had been a more serious leak.
By providing hyperspectral cameras 12, it is possible to monitor the presence of more than merely the presence of fluid. For example, water will have a different image profile under infra-red and/or ultra-violet inspection than would diesel, for instance, as the absorption and emission properties within these spectral regions are significantly different than in the visible spectrum. If an anomalous presence is imaged by a hyperspectral imaging device 12 and registered by the controller 16 and/or processor 24, then this can be raised as an issue, and the vehicle 22 sent for immediate repair.
Part of the challenge of the imaging of the underframe of a vehicle 22 lies in the fact that the underframe is positioned very close to the ground, and as such, the visual field of an imaging device positioned thereunder is limited. The present vehicle underside examination system 10 overcomes this issue by using the imaging devices 12 to image a plurality of different time-lapsed images of the underside of the vehicle 14 as it passes across the imaging devices 12, as illustrated in Figure 3, globally at 28.
Using a recombination circuit of the processor 24, the vehicle underframe examination system 10 may then be able to re-stitch or recompile a complete image of the underframe of the vehicle 22 in an in-use condition, which would otherwise not be possible to retrieve without taking the vehicle 22 out of service for some time. Such a reconstituted image of a vehicle is illustrated in Figure 4, globally at 30. This may be of particular use if some manual fault identification is performed, for instance, by a maintenance engineer, allowing them to view the underframe of the vehicle 22 remotely, and thereby determine whether more involved repairs are required.
Although it may be anticipated that, based on a reconstituted image of the underframe of the vehicle 22, manual fault identification may be more appropriate in order to utilise human experience, machine learning may make this task more readily computed than by using human intervention. As such, the processor 24 could feasibly be provided with an anomalous condition classification circuit so as to automatically determine the anomalous condition of the vehicle 22, if found, based on type of fault, component at fault, and so on, without human intervention. Such a vehicle underframe examination system 10 would be able to then alert a maintenance team to the presence of the anomalous condition as soon as it was detected. A user interface could also feasibly be provided, even were automatic classification permitted, so as to allow for a user to assist with the fault detection manually.
The words ‘comprises/comprising’ and the words ‘having/including’ when used herein with reference to the present invention are used to specify the presence of stated features, integers, steps or components, but do not preclude the presence or addition of one or more other features, integers, steps, components or groups thereof.
It is appreciated that certain features of the invention, which are, for clarity, described in the context of separate embodiments, may also be provided in combination in a single embodiment. Conversely, various features of the invention which are, for brevity, described in the context of a single embodiment, may also be provided separately or in any suitable sub-combination.
The embodiments described above are provided by way of examples only, and various other modifications will be apparent to persons skilled in the field without departing from the scope of the invention as defined herein.
Claims (23)
1. A vehicle underframe examination system for anomalous condition detection of at least an underframe of a vehicle, the system comprising: a hyperspectral imaging apparatus positioned to acquire images of at least an underframe of a vehicle passing over a designated vehicular transit route; at least one vehicle approach sensor which is spaced apart from the imaging apparatus; a controller associated with the hyperspectral imaging apparatus and the at least one vehicle approach sensor, the controller being arranged to automatically activate and/or deactivate the hyperspectral imaging apparatus in response to a trigger from the at least one vehicle approach sensor; a vehicle identification means for determining an identity of the said vehicle as it approaches or passes over the hyperspectral imaging apparatus; a processor in communication with the hyperspectral imaging apparatus and which is arranged to process real-time imaging data received from the hyperspectral imaging apparatus; and a memory device associated with the processor, the memory device being arranged to store historical imaging data and/or generic vehicular underframe information data associated with the vehicle or the type of vehicle, the processor being arranged to compare the real-time imaging data to the historical imaging data and/or generic vehicular underframe information data so as to detect an anomalous condition of the underframe of the vehicle.
2. A vehicle underframe examination system as claimed in claim 1, wherein the hyperspectral imaging apparatus comprises a plurality of different imaging devices covering different regions of the electromagnetic spectrum.
3. A vehicle underframe examination system as claimed in claim 1, wherein the hyperspectral imaging apparatus comprises single hyperspectral imaging device.
4. A vehicle underframe examination system as claimed in any one of the preceding claims, wherein the hyperspectral imaging apparatus includes at least two of: visible spectrum imaging; ultra-violet imaging; and infra-red imaging.
5. A vehicle underframe examination system as claimed in any one of claims 2 to 4, wherein the hyperspectral imaging apparatus includes at least one illumination device positioned at or adjacent to the at least one imaging device and arranged to illuminate the underside of the vehicle.
6. A vehicle underframe examination system as claimed in claim 5, wherein the hyperspectral imaging apparatus comprises a plurality of different illumination devices covering different regions of the electromagnetic spectrum.
7. A vehicle underframe examination system as claimed in any one of the preceding claims, wherein the hyperspectral imaging apparatus is arranged to image a sequence of consecutive images of the underside of the vehicle as it passes across the hyperspectral imaging apparatus, the processor including a recombination circuit which is arranged to recombine the sequence of consecutive images.
8. A vehicle underframe examination system as claimed in any one of the preceding claims, wherein the processor includes an anomalous condition classification circuit arranged to classify anomalous conditions of the underframe of the vehicle based on the real-time imaging data, historical imaging data, and/or generic vehicular underframe information data.
9. A vehicle underframe examination system as claimed in claim 8, wherein the processor is arranged to automatically classify anomalous conditions of the underframe of the vehicle using the anomalous condition classification circuit.
10. A vehicular underframe examination system as claimed in claim 8 or claim 9, further comprising a user interface to the anomalous condition classification circuit to permit manual classification of anomalous conditions of the underframe of the vehicle.
11. A vehicle underframe examination system as claimed in any one of the preceding claims, wherein the processor includes a vehicle underframe component identification circuit which is arranged to identify the components of the vehicle underframe based on the output of the hyperspectral imaging apparatus.
12. A vehicle underframe examination system as claimed in any one of the preceding claims, wherein the vehicle identification means comprises a radio-frequency communicator arranged to identify a radio-frequency identifier of the vehicle.
13. A vehicle underframe examination system as claimed in any one of the preceding claims, wherein the vehicle is a railway train.
14. A vehicle underframe examination system substantially as hereinbefore described, with reference to Figures 1 and 2 of the accompanying drawings.
15. A vehicle transit network comprising a vehicle transit route and a vehicle underframe examination system as claimed in any one of the preceding claims, the hyperspectral imaging apparatus of the vehicle underframe examination system being positioned so as to image at least an underside of a vehicle passing over the designated vehicular transit route.
16. A vehicle transit network as claimed in claim 15, wherein the hyperspectral imaging apparatus includes at least one imaging device which is vertically or substantially vertically aligned so as to image the underside of the vehicle.
17. A vehicle transit network as claimed in claim 15 or claim 16, wherein the hyperspectral imaging apparatus includes at least one imaging device which is positioned so as to image a side of the underframe of the vehicle.
18. A vehicle transit network as claimed in any one of claims 15 to 17, wherein the vehicle transit route is a railway.
19. A method of inspecting the underframe of a vehicle for anomalous conditions during normal operation of the vehicle using a vehicle underframe examination system as claimed in any one of claims 1 to 14, the method comprising the steps of: a] determining whether a vehicle is approaching a specific location; b] determining an identity of the vehicle; c] imaging at least an underframe of the vehicle using hyperspectral imaging as the vehicle passes over the said specific location; and dj determining, based on an output of step cj and on historical and/or generic vehicular underframe information which is relevant to the vehicle, whether the underframe of the vehicle is experiencing an anomalous condition.
20. A method as claimed in claim 19, wherein the historical and/or generic vehicular underframe information is determined by machine learning.
21. A method as claimed in claim 19 or claim 20, wherein during step c], a plurality of sequential images of the underframe of the vehicle are taken to obtain an image of the entire length of the underframe of the vehicle.
22. A method as claimed in any one of claims 19 to 21, wherein during step c], the hyperspectral imaging utilises infra-red imaging to detect underframe component temperature and at least visible wavelength imaging to detect fluid leakage at the underframe and/or underframe component displacement.
23. A vehicle underframe examination system for anomalous condition detection of an underframe of a vehicle, the system comprising: an imaging apparatus positioned to acquire images from at least an underframe of a vehicle passing over a designated vehicular transit route; at least one vehicle approach sensor which is spaced apart from the imaging apparatus; a controller associated with the imaging apparatus and the at least one vehicle approach sensor, the controller being arranged to automatically activate and/or deactivate the imaging apparatus in response to a trigger from the at least one vehicle approach sensor; and a vehicle identification means for determining an identity of the said vehicle as it approaches or passes over the imaging apparatus.
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| EP16020008 | 2016-01-12 |
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| GB2546344A true GB2546344A (en) | 2017-07-19 |
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| GB1605509.7A Withdrawn GB2546344A (en) | 2016-01-12 | 2016-03-31 | Vehicle underframe examination system |
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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| GB2577594A (en) * | 2018-08-07 | 2020-04-01 | Hitachi High Tech Fine Systems Corp | Vehicle size measurement apparatus and vehicle size measuring method |
| EP3764075A1 (en) * | 2019-07-12 | 2021-01-13 | ALSTOM Transport Technologies | Device for measuring a force in the displacement direction of a footboard of a railway vehicle slidable in the displacement direction |
| CN113822840A (en) * | 2020-06-19 | 2021-12-21 | 现代自动车株式会社 | Vehicle bottom inspection system and method |
| FR3112729A1 (en) * | 2020-07-27 | 2022-01-28 | Alstom Transport Technologies | Device for detecting contact surface degradation of a vehicle power supply system |
| DE102022204607A1 (en) | 2022-05-11 | 2023-07-13 | Deutsches Zentrum für Luft- und Raumfahrt e.V. | Apparatus, monitoring system and method for monitoring a rail vehicle for thermal damage |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| FR3078160A1 (en) * | 2018-02-22 | 2019-08-23 | Alstom Transport Technologies | RAIL VEHICLE SUB-CHASSIS INSPECTION DEVICE AND CORRESPONDING INSPECTION METHOD |
| EP3531102A1 (en) * | 2018-02-22 | 2019-08-28 | ALSTOM Transport Technologies | Device for inspecting subframes of a railway vehicle and corresponding inspection method |
| GB2577594A (en) * | 2018-08-07 | 2020-04-01 | Hitachi High Tech Fine Systems Corp | Vehicle size measurement apparatus and vehicle size measuring method |
| GB2577594B (en) * | 2018-08-07 | 2022-06-22 | Hitachi High Tech Fine Systems Corp | Vehicle size measurement apparatus and vehicle size measuring method |
| EP3764075A1 (en) * | 2019-07-12 | 2021-01-13 | ALSTOM Transport Technologies | Device for measuring a force in the displacement direction of a footboard of a railway vehicle slidable in the displacement direction |
| CN113822840A (en) * | 2020-06-19 | 2021-12-21 | 现代自动车株式会社 | Vehicle bottom inspection system and method |
| FR3112729A1 (en) * | 2020-07-27 | 2022-01-28 | Alstom Transport Technologies | Device for detecting contact surface degradation of a vehicle power supply system |
| EP3944981A1 (en) * | 2020-07-27 | 2022-02-02 | ALSTOM Transport Technologies | Device for detecting the degradation of a contact surface of a system for supplying power to a vehicle |
| DE102022204607A1 (en) | 2022-05-11 | 2023-07-13 | Deutsches Zentrum für Luft- und Raumfahrt e.V. | Apparatus, monitoring system and method for monitoring a rail vehicle for thermal damage |
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